CN119161008B - Operation control method, equipment and medium for aerobic granular sludge - Google Patents
Operation control method, equipment and medium for aerobic granular sludge Download PDFInfo
- Publication number
- CN119161008B CN119161008B CN202411648894.5A CN202411648894A CN119161008B CN 119161008 B CN119161008 B CN 119161008B CN 202411648894 A CN202411648894 A CN 202411648894A CN 119161008 B CN119161008 B CN 119161008B
- Authority
- CN
- China
- Prior art keywords
- data
- sludge
- aerobic
- granular sludge
- aerobic granular
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000010802 sludge Substances 0.000 title claims abstract description 251
- 238000000034 method Methods 0.000 title claims abstract description 44
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims abstract description 104
- 239000001301 oxygen Substances 0.000 claims abstract description 104
- 229910052760 oxygen Inorganic materials 0.000 claims abstract description 104
- 239000010865 sewage Substances 0.000 claims abstract description 68
- 238000012544 monitoring process Methods 0.000 claims abstract description 44
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 86
- 239000002245 particle Substances 0.000 claims description 30
- 238000004422 calculation algorithm Methods 0.000 claims description 22
- 238000004364 calculation method Methods 0.000 claims description 20
- 230000004069 differentiation Effects 0.000 claims description 19
- 239000007789 gas Substances 0.000 claims description 19
- 230000010354 integration Effects 0.000 claims description 18
- 238000003860 storage Methods 0.000 claims description 17
- 238000001595 flow curve Methods 0.000 claims description 10
- 238000012545 processing Methods 0.000 claims description 7
- 238000011282 treatment Methods 0.000 claims description 7
- XKMRRTOUMJRJIA-UHFFFAOYSA-N ammonia nh3 Chemical compound N.N XKMRRTOUMJRJIA-UHFFFAOYSA-N 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 6
- 230000008030 elimination Effects 0.000 claims description 3
- 238000003379 elimination reaction Methods 0.000 claims description 3
- 230000004927 fusion Effects 0.000 claims description 3
- 239000011259 mixed solution Substances 0.000 claims description 2
- 239000007787 solid Substances 0.000 claims description 2
- 238000007405 data analysis Methods 0.000 abstract description 2
- 238000005273 aeration Methods 0.000 description 12
- 230000001276 controlling effect Effects 0.000 description 9
- 230000000694 effects Effects 0.000 description 9
- 238000001514 detection method Methods 0.000 description 7
- 238000004590 computer program Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 4
- 230000008901 benefit Effects 0.000 description 4
- 238000005265 energy consumption Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 239000000243 solution Substances 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- -1 PH value Substances 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000011276 addition treatment Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000003556 assay Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000009533 lab test Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000000813 microbial effect Effects 0.000 description 1
- 238000013486 operation strategy Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Classifications
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F3/00—Biological treatment of water, waste water, or sewage
- C02F3/006—Regulation methods for biological treatment
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F3/00—Biological treatment of water, waste water, or sewage
- C02F3/02—Aerobic processes
- C02F3/12—Activated sludge processes
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F2209/00—Controlling or monitoring parameters in water treatment
- C02F2209/005—Processes using a programmable logic controller [PLC]
- C02F2209/006—Processes using a programmable logic controller [PLC] comprising a software program or a logic diagram
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F2209/00—Controlling or monitoring parameters in water treatment
- C02F2209/22—O2
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F2209/00—Controlling or monitoring parameters in water treatment
- C02F2209/40—Liquid flow rate
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
- Y02W10/00—Technologies for wastewater treatment
- Y02W10/10—Biological treatment of water, waste water, or sewage
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Biodiversity & Conservation Biology (AREA)
- Microbiology (AREA)
- Hydrology & Water Resources (AREA)
- Engineering & Computer Science (AREA)
- Environmental & Geological Engineering (AREA)
- Water Supply & Treatment (AREA)
- Chemical & Material Sciences (AREA)
- Organic Chemistry (AREA)
- Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Feedback Control In General (AREA)
Abstract
本发明公开了一种好氧颗粒污泥的运行控制方法、设备及介质，属于好氧颗粒污泥自控系统技术领域，用于解决现有的好氧颗粒污泥自控系统的排泥数据控制不全面，难以形成针对性的排泥数据分析与控制性能，且人工成本较高，系统的自动化程度较低的技术问题。方法包括：对好氧颗粒污泥自控系统中的污水流量进行实时监测，得到关键监测数据；根据关键监测数据中的好氧污泥含量数据，对所述好氧颗粒污泥自控系统中当前污水流量进行需氧量计算，得到需氧目标值；将关键监测数据中的当前溶解氧浓度与所述需氧目标值有关PID的调整控制，得到最佳溶解氧浓度；对好氧颗粒污泥的运行负荷进行PLC调整控制，得到最佳水‑风控制量数据。
The present invention discloses an operation control method, equipment and medium of aerobic granular sludge, which belongs to the technical field of aerobic granular sludge automatic control system, and is used to solve the technical problems that the existing aerobic granular sludge automatic control system has incomplete control of sludge discharge data, is difficult to form targeted sludge discharge data analysis and control performance, has high labor costs, and has a low degree of automation of the system. The method includes: real-time monitoring of the sewage flow in the aerobic granular sludge automatic control system to obtain key monitoring data; based on the aerobic sludge content data in the key monitoring data, calculating the oxygen demand of the current sewage flow in the aerobic granular sludge automatic control system to obtain an oxygen demand target value; adjusting and controlling the current dissolved oxygen concentration in the key monitoring data and the oxygen demand target value by PID to obtain the optimal dissolved oxygen concentration; and performing PLC adjustment and control on the operation load of the aerobic granular sludge to obtain the optimal water-wind control quantity data.
Description
Technical Field
The application relates to the field of aerobic granular sludge automatic control systems, in particular to an operation control method, equipment and medium of aerobic granular sludge.
Background
The conventional detection data related to the aerobic granular sludge in the prior art are conventional data such as water inflow rate, aeration flowmeter, temperature, dissolved oxygen, PH value, sludge concentration and the like, and are not introduced, such as COD (chemical oxygen demand), granular sludge content and the like, and only an inspector can provide the data for a debugging engineer through an assay, and then the engineer can know the operation load, the treatment effect and the like of an aerobic granular sludge operation system through manual calculation, so that the data provided by the PLC or the DCS only has a guiding effect.
Because the detected data are limited, the degree of automation is limited, the start and stop control of equipment can be basically realized, the on-line instrument data are mostly only detected, the linkage control is basically only realized by linkage of dissolved oxygen and an aeration fan, and an analysis control function and a formula algorithm are not provided. The linkage of the dissolved oxygen and the aeration fan is that the frequency of the frequency converter of the aeration fan is controlled through feedback of the online dissolved oxygen meter and setting a target value through PID regulation, and the frequency converter of the aeration fan can realize linkage control but has a plurality of defects, firstly, the position detected by the online dissolved oxygen meter is fixed, the data is not representative, the position slightly fluctuates, the data fluctuates, and the reasonable target value is found out in debugging to play a certain role by relying on the experience of a debugging engineer, secondly, the frequency of the frequency converter fluctuates when the online dissolved oxygen meter detects, so that the frequency of the frequency converter fluctuates frequently under the interference condition and is difficult to stably control.
And, the data to be assayed is relatively slow, has strong hysteresis, and also has hysteresis on the operation control of the system, so that the debugging time is long and the time is wasted. The personnel demand is large, and the unstable energy consumption of fan control is large. Meanwhile, a debugging engineer with high experience and an operator with high experience are needed, and the dependency on the experienced engineer is high.
Disclosure of Invention
The embodiment of the application provides an operation control method, equipment and medium for aerobic granular sludge, which are used for solving the technical problems that the sludge discharge data of the existing aerobic granular sludge automatic control system is incomplete in control, the specific sludge discharge data analysis and control performance is difficult to form, the labor cost is high, and the automation degree of the system is low.
The embodiment of the application adopts the following technical scheme:
On one hand, the embodiment of the application provides an operation control method of aerobic granular sludge, which comprises the steps of monitoring sewage flow in an aerobic granular sludge automatic control system in real time through a plurality of types of pre-deployed sensors to obtain key monitoring data, calculating the current sewage flow in the aerobic granular sludge automatic control system according to the aerobic sludge content data in the key monitoring data to obtain an aerobic target value, regulating and controlling the current dissolved oxygen concentration in the key monitoring data and PID (proportion integration differentiation) related to the aerobic target value to obtain an optimal dissolved oxygen concentration, and carrying out PLC (programmable logic controller) regulation and control on the operation load of the aerobic granular sludge based on the optimal dissolved oxygen concentration to obtain optimal water-wind control quantity data so as to complete the generation control of the optimal growth environment of the aerobic granular sludge.
The embodiment of the application can accurately control the aerobic granular sludge automatic control system by utilizing the accurate control of the PID and the PLC, thereby realizing the automatic control of the operation load of the aerobic granular sludge, the automatic control of the optimal growth environment of the aerobic granular sludge, the automatic control of the aeration quantity, namely the oxygen demand, the automatic control of the water inflow, the automatic control of the sludge discharge quantity of the aerobic granular sludge and the like. And the method also provides an optimal dissolved oxygen environment for the growth of the aerobic granular sludge, and is easy to realize and integrate the aerobic granular sludge. The intelligent of the aerobic granular sludge automatic control system is high, human factors can be thoroughly eliminated, and the economic benefit of the aerobic granular sludge is greatly improved.
In a feasible implementation mode, the method monitors the sewage flow in the aerobic granular sludge automatic control system in real time through a plurality of types of pre-deployed sensors to obtain key monitoring data, specifically comprises the steps of arranging a water inlet flowmeter at a water inlet of the sewage flow in the aerobic granular sludge automatic control system, acquiring the water inlet flow data of the sewage flow through the water inlet flowmeter and generating a corresponding water inlet flow curve, arranging an online COD detector at the water inlet and a water outlet in the aerobic granular sludge automatic control system, acquiring first COD content data of the water inlet and second COD content data of the water outlet through the online COD detector and generating a corresponding water inlet and outlet COD content curve, arranging a gas flowmeter at an aerobic zone in the aerobic granular sludge automatic control system, acquiring the gas flow data of the aerobic zone through the gas flowmeter and generating a gas flow curve correspondingly, arranging an online particle size detector at the sewage flow of the aerobic granular sludge automatic control system, acquiring the sludge data of the aerobic granular sludge in the sewage flow through the online particle size detector and generating a sludge flow curve correspondingly, arranging a PH value of the sewage flow meter at the aerobic granular sludge automatic control system, and acquiring the PH value of the sewage flow corresponding to the PH value of the sewage flow, and generating the PH value corresponding to the PH value of the sewage flow.
In a feasible implementation mode, the method comprises the steps of carrying out oxygen demand calculation on current sewage flow in the aerobic granular sludge automatic control system according to aerobic sludge content data in the key monitoring data to obtain an oxygen demand value, carrying out classification treatment on the aerobic sludge content data according to a sludge particle size curve corresponding to the current sewage flow to obtain flocculent sludge concentration data and granular sludge concentration data, carrying out absolute sludge calculation on the flocculent sludge concentration data and the granular sludge concentration data according to a tank capacity corresponding to the current sewage flow in the aerobic granular sludge automatic control system to obtain flocculent sludge absolute sludge data and granular sludge absolute sludge data, carrying out addition treatment on the flocculent sludge absolute sludge data and the granular sludge absolute sludge data to obtain absolute sludge total amount data, carrying out oxygen demand calculation on the oxygen demand value according to a plurality of types of curve key points in the key monitoring data corresponding to the current sewage flow and on the basis of the absolute sludge total amount data, and calculating the flocculent sludge content data and ammonia nitrogen content data, and carrying out oxygen demand calculation on the current target value according to the flocculent sludge absolute sludge and the oxygen demand value.
In a feasible implementation mode, the current dissolved oxygen concentration in the key monitoring data and the PID regulation control related to the oxygen demand target value are controlled to obtain the optimal dissolved oxygen concentration, and the method specifically comprises the steps of determining the current dissolved oxygen concentration of the current sewage according to a COD content curve of water inlet and outlet in the key monitoring data, calculating the difference value between the current dissolved oxygen concentration and the oxygen demand target value to obtain deviation data, regulating and controlling the deviation data through a preset PID control algorithm to obtain regulation control parameters, and controlling the frequency of an oxygen supply fan frequency converter based on the regulation control parameters to obtain the optimal dissolved oxygen concentration.
In a feasible implementation mode, the deviation data are adjusted and controlled through a preset PID control algorithm to obtain adjustment control parameters, specifically, the method comprises the steps of determining the deviation data as current error data through a proportion link of the PID control algorithm, performing product output control of the current error data with respect to the proportion coefficient to perform proportional adjustment to determine first control parameters, performing steady-state error elimination processing on error integration accumulated by the deviation data through an integration link of the PID control algorithm, outputting second control parameters with respect to product of the integral coefficient and the error integral, performing error trend prediction of error differentiation of the deviation data with respect to time sequence change rate through a differentiation link of the PID control algorithm, outputting third control parameters with respect to product of the error differentiation and the differential coefficient, and performing superposition output control on the first control parameters, the second control parameters and the third control parameters to obtain the adjustment control parameters.
In a feasible implementation mode, the method comprises the steps of carrying out PLC adjustment control on the operation load of aerobic granular sludge based on the optimal dissolved oxygen concentration to obtain optimal water-air control quantity data, specifically, carrying out food micro ratio calculation on key monitoring data of the current sewage flow through a preset PLC control system to generate a food micro ratio curve, carrying out operation load calculation on the key monitoring data of the current sewage flow to generate an operation load curve, carrying out multi-point trend control on the gas flow curve, the food micro ratio curve and the operation load curve in the key monitoring data through the PLC control system to obtain the optimal operation load of the current sewage flow, carrying out feedback control on the water pump frequency and the fan frequency of the current sewage flow based on the optimal operation load and the optimal dissolved oxygen concentration to respectively obtain optimal water inflow control data and optimal air supply control data, and carrying out data fusion on the optimal water inflow control data and the optimal air supply control data to obtain the optimal water-air control quantity data.
In a possible embodiment, according toObtaining the operation load of the aerobic granular sludge in the aerobic zoneWherein, the method comprises the steps of,The treated water amount of the aerobic zone; the first COD content data of the water inlet in the aerobic zone is obtained; the second COD content data of the water outlet in the aerobic zone is obtained; Is the total volume of the aerobic zone; And generating an operation load curve based on the operation load and through an upper computer in the aerobic granular sludge automatic control system.
In a possible embodiment, according toObtaining the food micro ratioWherein, the method comprises the steps of,The treated water amount of the aerobic zone; The difference value content data between the first COD content data of the water inlet in the aerobic zone and the second COD content data of the water outlet in the aerobic zone; The total volume of the aerobic zone; Is the concentration of the aerobic granular sludge; is the value of the aerobic sludge content in the aerobic sludge content data; And generating the food micro ratio curve based on the food micro ratio and through an upper computer in the aerobic granular sludge automatic control system.
In a second aspect, the embodiment of the application also provides operation control equipment of the aerobic granular sludge, which comprises at least one processor and a memory in communication connection with the at least one processor, wherein the memory stores instructions capable of being executed by the at least one processor so that the at least one processor can execute the operation control method of the aerobic granular sludge in any one of the embodiments.
In a third aspect, an embodiment of the present application further provides a nonvolatile computer storage medium, where the storage medium is a nonvolatile computer readable storage medium, where at least one program is stored in the nonvolatile computer readable storage medium, where each program includes instructions, where the instructions when executed by a terminal, cause the terminal to execute an operation control method for aerobic granular sludge according to any one of the foregoing embodiments.
Compared with the prior art, the embodiment of the application has the following beneficial technical effects:
The embodiment of the application can accurately control the aerobic granular sludge automatic control system by utilizing the accurate control of the PID and the PLC, thereby realizing the automatic control of the operation load of the aerobic granular sludge, the automatic control of the optimal growth environment of the aerobic granular sludge, the automatic control of the aeration quantity, namely the oxygen demand, the automatic control of the water inflow, the automatic control of the sludge discharge quantity of the aerobic granular sludge and the like. And the method also provides an optimal dissolved oxygen environment for the growth of the aerobic granular sludge, and is easy to realize and integrate the aerobic granular sludge. The intelligent of the aerobic granular sludge automatic control system is high, human factors can be thoroughly eliminated, and the economic benefit of the aerobic granular sludge is greatly improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to the drawings without inventive effort to those skilled in the art. In the drawings:
FIG. 1 is a flow chart of a method for controlling the operation of aerobic granular sludge according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an operation control device for aerobic granular sludge according to an embodiment of the present application.
Detailed Description
In order to make the technical solution of the present application better understood by those skilled in the art, the technical solution of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
The aerobic granular sludge automatic control system of the application has the following functions:
1. And automatically detecting key parameters of the aerobic granular sludge system in real time, such as dissolved oxygen concentration, the content of the aerobic granular sludge detected by a particle size detector, inflow water flow, COD (chemical oxygen demand) content, aeration flow, pH value and the like.
2. And oxygen supply control, namely automatically adjusting the required amount according to the set value, the reference value and the feedback value.
3. And load control, namely automatically adjusting the system load according to the detection data and optimizing the processing effect.
4. And controlling the flow, namely automatically adjusting the water treatment amount according to the optimal operation load.
5. When the system is abnormal or the load exceeds the set range, early warning information is automatically sent.
6. And the historical data is stored to form a historical curve, so that the system operation strategy can be analyzed and optimized conveniently.
Meanwhile, the aerobic granular sludge automatic control system of the application is also provided with a plurality of modules:
1) And the detection module is used for monitoring key parameters of the aerobic system in real time by adopting high-precision multiple sensors.
2) And the control module is used for automatically adjusting the oxygen demand, the system running load, the treated water quantity and the like according to the monitoring data and the program calculation, so as to ensure the minimum energy consumption, the most stable treatment effect and the maximum treatment quantity.
3) And the early warning module can set an early warning threshold value, automatically trigger an early warning mechanism when the monitored data exceeds the range, and automatically adjust according to the item exceeding the threshold value.
4) And the data storage module is used for safely and efficiently storing the historical data by adopting a cloud storage technology.
The embodiment of the application provides an operation control method of aerobic granular sludge, as shown in fig. 1, specifically comprising the following steps of S101-S104:
S101, monitoring the sewage flow in the aerobic granular sludge automatic control system in real time through a plurality of types of pre-deployed sensors to obtain key monitoring data. Wherein, the various sensors can comprise a water inlet flowmeter, an online COD detector, a gas flowmeter, an online particle size detector, a PH value detector, a sludge concentration meter and the like.
Specifically, a water inlet flowmeter is arranged at a sewage flow inlet of the aerobic granular sludge automatic control system, water inlet flow data of the sewage flow are collected through the water inlet flowmeter, and a corresponding water inlet flow curve is generated.
Further, a water inlet and a water outlet in the aerobic granular sludge automatic control system are arranged on an online COD detector, first COD content data of the water inlet and second COD content data of the water outlet are collected through the online COD detector, and a corresponding water inlet and outlet COD content curve is generated.
Further, a gas flowmeter is arranged in an aerobic zone in the aerobic granular sludge automatic control system, and gas flow data of the aerobic zone are collected through the gas flowmeter and a gas flow curve is correspondingly generated.
Further, an online particle size detector is arranged in the sewage flow of the aerobic particle sludge automatic control system, and sludge particle size data of the aerobic particle sludge in the sewage flow are collected through the online particle size detector, and a sludge particle size curve is correspondingly generated.
The particle size detector is used for detecting the aerobic granular sludge in real time, so that the problem that the content of the aerobic granular sludge needs to be detected by a photoelectric microscope in a laboratory stage is solved, (two defects of detection by the photoelectric microscope are provided, 1, the laboratory in a common factory is not provided with the photoelectric microscope and needs to be detected externally, 2, the particle size detector is not real-time, the time interval is longer, and if the external detection time needs to be longer). The data after the particle size detector is used in the aerobic granular sludge automatic control system is real-time detection data, so that the sludge particle size data of the aerobic granular sludge in the sewage flow can be accurately and rapidly acquired.
Further, a PH value detector is arranged at the water inlet of the aerobic granular sludge automatic control system, and PH value data of sewage flow of the water inlet is collected through the PH value detector and correspondingly generated.
Further, a sludge concentration meter is arranged in the sewage flow of the aerobic granular sludge automatic control system, and the aerobic sludge content data of the aerobic granular sludge is collected through the sludge concentration meter and correspondingly generated into an aerobic sludge content curve.
In one embodiment, the collected water inflow data, the first COD content data of the water inlet, the second COD content data of the water outlet, the gas flow data, the sludge grain diameter data, the PH value data, the aerobic sludge content data and the like can be fed back to a PLC (programmable logic controller) or a DCS (distributed control system) in the aerobic granular sludge automatic control system, and then corresponding curves are formed in an upper computer respectively, so that subsequent PID (proportion integration differentiation) control and PLC automatic judgment are facilitated, and parameter control data such as optimal water inflow, optimal air supply amount and the like are fed back.
S102, according to the aerobic sludge content data in the key monitoring data, the current sewage flow in the aerobic granular sludge automatic control system is subjected to oxygen demand calculation, and an oxygen demand value is obtained.
Specifically, firstly, classifying the aerobic sludge content data by utilizing a sludge particle size curve corresponding to the current sewage flow to obtain flocculent sludge concentration data and granular sludge concentration data.
Further, based on the tank capacity corresponding to the current sewage flow in the aerobic granular sludge automatic control system, the flocculent sludge concentration data and the granular sludge concentration data are subjected to absolute dry sludge calculation to obtain flocculent sludge absolute dry sludge data and granular sludge absolute dry sludge data.
Further, adding the flocculent sludge absolute dry sludge amount data and the granular sludge absolute dry sludge amount data to obtain absolute dry sludge total amount data.
Further, according to the multi-type curve key points in the key monitoring data corresponding to the current sewage flow, BOD food amount data and ammonia nitrogen content data are calculated based on the absolute dry sludge total amount data.
Further, based on BOD food amount data and ammonia nitrogen content data, oxygen demand calculation is performed on the current sewage flow to obtain an oxygen demand value. Wherein the aerobic target value corresponds to aerobic sludge content data in the current sewage flow.
In one embodiment, the accurate content data of the flocculent sludge concentration data and the granular sludge concentration data is measured according to a particle size detector. The method comprises the steps of installing a sludge content detection system beside a pool of aerobic granular sludge, wherein main equipment of the sludge content detection system is an online particle size detector, and rapidly analyzing the content of granular sludge and flocculent sludge in the aerobic system according to the online particle size detector;
And finally, calculating accurate oxygen demand data corresponding to the aerobic sludge content data in the current sewage flow, namely an oxygen demand target value, according to the detected BOD and ammonia nitrogen content data in the inflow water quality.
And S103, adjusting and controlling the PID related to the current dissolved oxygen concentration and the oxygen demand value in the key monitoring data to obtain the optimal dissolved oxygen concentration.
Specifically, the current dissolved oxygen concentration of the current sewage is determined according to the COD content curve of the inlet and outlet water in the key monitoring data.
Further, the difference value between the current dissolved oxygen concentration and the oxygen demand value is calculated to obtain deviation data.
In one embodiment, the dissolved oxygen concentration in the current sewage flow is determined according to the COD content curve of the inlet and outlet water in the monitored key monitoring data, the oxygen particle sludge automatic control system automatically adjusts the running state of the oxygen supply fan and can automatically adjust the control parameters according to the deviation data of the real-time dissolved oxygen concentration and the target value so as to keep the dissolved oxygen within the required range of the target value.
As a possible implementation mode, the current dissolved oxygen concentration measured in real time is compared with a target value to obtain a deviation value (deviation data), a PID control algorithm is used for calculating a control output according to the deviation value, and a specific control instruction is generated according to the control output, such as adjusting the frequency of an oxygen supply fan frequency converter. The oxygen particle sludge automatic control system is connected with the frequency converter of the oxygen supply fan, so that automatic control of equipment is realized. The process comprises the following steps that in an aerobic granular sludge operation system, a PID controller receives real-time data from a dissolved oxygen sensor, calculates an error between the current dissolved oxygen concentration and a set target value, and then calculates control output by using a PID control algorithm. The output is used to adjust the frequency input of the frequency converter of the oxygen supply fan, thereby changing the behavior of the system and achieving the purpose of controlling the concentration of the dissolved oxygen in the current sewage flow. That is, through the accurate adjustment of the PID control algorithm, the stable control of the concentration of the dissolved oxygen in the sewage can be realized, thereby improving the sewage treatment efficiency and quality.
Furthermore, the deviation data is required to be adjusted and controlled through a preset PID control algorithm, so as to obtain adjustment control parameters. That is, the deviation data is determined as current error data through a proportional link of the PID control algorithm. And performing the product output control of the related proportional coefficient on the current error data to perform the proportional adjustment, and determining a first control parameter. And (3) performing steady-state error elimination processing on error integration accumulated by the deviation data through an integration link of a PID control algorithm, and outputting a second control parameter related to the product of the integration coefficient and the error integration. And carrying out error trend prediction on the time sequence change rate by the error differentiation of the deviation data through a differentiation link of a PID control algorithm, and outputting a third control parameter related to the product of the error differentiation and the differentiation coefficient.
Further, the first control parameter, the second control parameter and the third control parameter are subjected to superposition output control, and the adjustment control parameter is obtained. And based on the adjustment control parameters, the frequency control is carried out on the frequency converter of the oxygen supply fan, so as to obtain the optimal dissolved oxygen concentration.
As a possible implementation, an advanced PID control algorithm is used to achieve accurate control of the optimal dissolved oxygen concentration. A PID (Proportional-Integral-Derivative) control algorithm is an algorithm widely used in industrial process control, which adjusts the output of a system through three links of Proportional, integral and Derivative to achieve a desired control target. In an oxygen particle sludge autonomous system, a PID control algorithm is used to automatically adjust the dissolved oxygen concentration.
In the proportional link, the system output is adjusted according to the magnitude of the current error (the difference between the actual value and the target value). The larger the error, the faster the output adjusts to quickly reduce the error. The output of the scaling element is the product of the error and the scaling factor.
In the integration step, the cumulative effect of errors is taken into account. It not only focuses on the current error, but also considers the sum of errors over a period of time. The addition of the integration section can eliminate steady-state errors (i.e., errors that exist for a long time and cannot be eliminated by the proportional section). The output of the integration section is the product of the error integral and the integral coefficient.
In the differential step, the change trend of the future error is predicted. It adjusts the system output according to the rate of change of error over time to account for possible error variations in advance. The output of the differentiation element is the product of the error differentiation and the differentiation coefficient.
Finally, the final output of the PID controller is superposition of the outputs of three links of proportion, integration and differentiation, namely, the first control parameter, the second control parameter and the third control parameter are subjected to superposition output control, so that the frequency control can be performed on the frequency converter of the oxygen supply fan based on the adjustment control parameter, and the optimal dissolved oxygen concentration is obtained.
S104, based on the optimal dissolved oxygen concentration, performing PLC adjustment control on the operation load of the aerobic granular sludge to obtain optimal water-wind control quantity data so as to complete the generation control on the optimal growth environment of the aerobic granular sludge.
The PLC control system can calculate the food micro ratio and the running load of the aerobic granular sludge rapidly according to curve data feedback and formula calculation. The edible micro ratio calculated in real time is used as a reference value and forms a curve, the edible micro ratio is used as a reference, the operation load of the aerobic granular sludge can be adjusted, and whether the operation load of the aerobic granular sludge is in an optimal state can be detected, wherein the proper range of the edible micro ratio is generally between 0.1 and 0.25kg BOD5/kg MLSS. D, the excessive edible micro ratio indicates that the microbial food is excessive, the aeration tank is in a high-load operation state, and the aeration tank is in a low-load operation state when the edible micro ratio is too low. And then forming a history curve by using the calculated aerobic granular sludge load, and definitely feeding back the actual running condition of the aerobic granular sludge system.
Specifically, firstly, calculating the food micro ratio of key monitoring data of the current sewage flow through a preset PLC control system, and generating a food micro ratio curve.
Further, the operation load calculation of the aerobic granular sludge is carried out on the key monitoring data of the current sewage flow, and an operation load curve is generated.
Further, through a PLC control system, the gas flow curve, the food micro ratio curve and the running load curve in the key monitoring data are subjected to curve multi-point trend control, and the optimal running load of the current sewage flow is obtained.
Further, based on the optimal operation load and the optimal dissolved oxygen concentration, feedback control is performed on the current sewage flow rate, namely the frequency of the water pump and the frequency of the fan, so as to obtain optimal water inflow control data and optimal air supply control data respectively.
Further, the optimal water inflow control data and the optimal air supply control data are subjected to data fusion to obtain the optimal water-air control data.
As a possible implementation mode, the optimal operation load and the optimal growth environment of the aerobic granular sludge are automatically judged by a PLC by utilizing an automatically generated curve of the operation load, a micro ratio curve and a gas flowmeter curve of the aerobic granular sludge, and the operation load, the water inflow (the frequency of a water pump is adjusted) and the air supply quantity (the frequency of a fan is adjusted) can be automatically adjusted according to the water inflow. And then feeding back the data and automatically analyzing the PLC to calculate the operation load of the whole aerobic granular sludge, thereby obtaining the optimal water inflow. And according to the optimal operation load and the optimal dissolved oxygen concentration of the aerobic granular sludge, the optimal air supply quantity is calculated, so that the operation frequency of the fan is controlled, and the optimal air supply quantity control data is determined to ensure that the air supply quantity is always in an optimal state, thereby achieving the energy-saving effect. Because the optimal growth environment is created for the aerobic granular sludge, the aerobic granular sludge can grow quickly, a periodic sludge discharge system can be arranged according to the conforming range of the aerobic granular sludge, and the discharged aerobic granular sludge can further improve the economic benefit.
As a possible embodiment, according toObtaining the operation load of the aerobic granular sludge in the aerobic zone. Wherein, The treated water amount of the aerobic zone; the first COD content data of the water inlet in the aerobic zone; the second COD content data is the water outlet in the aerobic zone; Is the total volume of the aerobic zone; The suspended solid is the average concentration of the mixed solution in the aerobic zone. Based on the operation load, an operation load curve is generated through an upper computer in the aerobic granular sludge automatic control system.
As a possible embodiment, according toObtaining the food micro ratio. Wherein, The treated water amount of the aerobic zone; Is the difference value content data between the first COD content data of the water inlet in the aerobic zone and the second COD content data of the water outlet in the aerobic zone; The total volume of the aerobic zone; Is the concentration of the aerobic granular sludge; is the value of the aerobic sludge content in the aerobic sludge content data; The BOD food amount is the BOD food amount entering the aerobic granular sludge automatic control system. Based on the food micro ratio, and through an upper computer in the aerobic granular sludge automatic control system, a food micro ratio curve is generated.
The application solves the problem of data support required by full-automatic control by adding the water inlet COD, the water outlet COD and the particle size detector. And the operation load of the aerobic granular sludge can be rapidly calculated by adding a preset algorithm conforming to an enterprise into a program of a PLC or DCS control system. And the optimal running load and the optimal growing environment of the aerobic granular sludge can be automatically judged by the automatic control program according to the running load curve of the aerobic granular sludge and the gas flowmeter curve and through the selection of the data judging program. And the running load, the water inflow (adjusting the frequency of the water pump) and the air supply (adjusting the frequency of the fan) can be automatically adjusted according to the water inflow. Meanwhile, the sensor instrument and the like in the application are all online instruments and feed back in real time, the calculation time of a formula calculation program set by the PLC or the DCS is 10-100 milliseconds, the calculation time is quick, laboratory test and manual calculation are not needed to be carried out in a large amount of time, and the problem of time lag is solved. Therefore, the energy consumption is accurately controlled by accurately controlling the aeration air quantity and the sludge load, the full automation can be realized, and the dependence on people is eliminated.
In addition, the embodiment of the application also provides an operation control device for aerobic granular sludge, as shown in fig. 2, the operation control device 200 for aerobic granular sludge specifically comprises:
at least one processor 201. And a memory 202 communicatively coupled to the at least one processor 201. Wherein the memory 202 stores instructions executable by the at least one processor 201 to enable the at least one processor 201 to perform:
monitoring the sewage flow in the aerobic granular sludge automatic control system in real time through a plurality of types of pre-deployed sensors to obtain key monitoring data;
according to the aerobic sludge content data in the key monitoring data, carrying out oxygen demand calculation on the current sewage flow in the aerobic granular sludge automatic control system to obtain an oxygen demand value;
adjusting and controlling PID (proportion integration differentiation) related to the current dissolved oxygen concentration and the oxygen demand value in the key monitoring data to obtain the optimal dissolved oxygen concentration;
Based on the optimal dissolved oxygen concentration, the operation load of the aerobic granular sludge is subjected to PLC adjustment control to obtain optimal water-wind control quantity data so as to complete the generation control of the optimal growth environment of the aerobic granular sludge.
The embodiment of the application can accurately control the aerobic granular sludge automatic control system by utilizing the accurate control of the PID and the PLC, thereby realizing the automatic control of the operation load of the aerobic granular sludge, the automatic control of the optimal growth environment of the aerobic granular sludge, the automatic control of the aeration quantity, namely the oxygen demand, the automatic control of the water inflow, the automatic control of the sludge discharge quantity of the aerobic granular sludge and the like. And the method also provides an optimal dissolved oxygen environment for the growth of the aerobic granular sludge, and is easy to realize and integrate the aerobic granular sludge. The intelligent of the aerobic granular sludge automatic control system is high, human factors can be thoroughly eliminated, and the economic benefit of the aerobic granular sludge is greatly improved.
The embodiments of the present application are described in a progressive manner, and the same and similar parts of the embodiments are all referred to each other, and each embodiment is mainly described in the differences from the other embodiments. In particular, for apparatus, non-volatile computer storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.
The devices and media provided in the embodiments of the present application are in one-to-one correspondence with the methods, so that the devices and media also have similar beneficial technical effects as the corresponding methods, and since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media are not repeated here.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
The foregoing describes certain embodiments of the present application. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the embodiments of the application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present application should be included in the scope of the claims of the present application.
Claims (7)
1. An operation control method of aerobic granular sludge, which is characterized by comprising the following steps:
monitoring the sewage flow in the aerobic granular sludge automatic control system in real time through a plurality of types of pre-deployed sensors to obtain key monitoring data;
according to the aerobic sludge content data in the key monitoring data, carrying out oxygen demand calculation on the current sewage flow in the aerobic granular sludge automatic control system to obtain an oxygen demand target value;
adjusting and controlling PID (proportion integration differentiation) related to the current dissolved oxygen concentration in the key monitoring data and the oxygen demand value to obtain the optimal dissolved oxygen concentration;
based on the optimal dissolved oxygen concentration, performing PLC adjustment control on the operation load of the aerobic granular sludge to obtain optimal water-wind control quantity data so as to complete generation control on the optimal growth environment of the aerobic granular sludge, wherein the method specifically comprises the following steps:
calculating the food micro ratio of the key monitoring data of the current sewage flow through a preset PLC control system, and generating a food micro ratio curve;
Performing operation load calculation on the aerobic granular sludge according to the key monitoring data of the current sewage flow to generate an operation load curve;
The PLC control system is used for performing curve multi-point trend control on the gas flow curve, the food micro ratio curve and the running load curve in the key monitoring data to obtain the optimal running load of the current sewage flow;
based on the optimal running load and the optimal dissolved oxygen concentration, respectively performing feedback control on the water pump frequency and the fan frequency of the current sewage flow to respectively obtain optimal water inflow control data and optimal air supply control data;
Performing data fusion on the optimal water inflow control data and the optimal air supply control data to obtain the optimal water-air control data;
wherein:
according to Obtaining the running load L s of the aerobic granular sludge in the aerobic zone, wherein Q is the treatment water quantity of the aerobic zone, S 0 is the first COD content data of a water inlet in the aerobic zone, S e is the second COD content data of a water outlet in the aerobic zone, V 0 is the total volume of the aerobic zone, and X is the average concentration of suspended solids of a mixed solution in the aerobic zone;
generating an operation load curve based on the operation load and through an upper computer in the aerobic granular sludge automatic control system;
Obtaining a food micro ratio F/M according to the ratio of F/M=Q to COD/(MLVSS) V 0, wherein Q is the treated water quantity of an aerobic zone, COD is the difference value content data between the first COD content data of a water inlet in the aerobic zone and the second COD content data of a water outlet in the aerobic zone, V 0 is the total volume of the aerobic zone, MLVSS is the aerobic granular sludge concentration, M is the aerobic sludge content value in the aerobic sludge content data, and F is the BOD food quantity entering the aerobic granular sludge automatic control system;
And generating the food micro ratio curve based on the food micro ratio and through an upper computer in the aerobic granular sludge automatic control system.
2. The method for controlling the operation of the aerobic granular sludge according to claim 1, wherein the sewage flow in the aerobic granular sludge automatic control system is monitored in real time by a plurality of types of pre-deployed sensors to obtain key monitoring data, and the method specifically comprises the following steps:
Arranging a water inlet flowmeter at a water inlet of sewage flow in the aerobic granular sludge automatic control system, collecting water inlet flow data of the sewage flow through the water inlet flowmeter, and generating a corresponding water inlet flow curve;
A water inlet and a water outlet in the aerobic granular sludge automatic control system are arranged in an online COD detector, first COD content data of the water inlet and second COD content data of the water outlet are collected through the online COD detector, and a corresponding water inlet and outlet COD content curve is generated;
arranging a gas flowmeter in an aerobic zone in the aerobic granular sludge automatic control system, collecting gas flow data of the aerobic zone through the gas flowmeter, and correspondingly generating a gas flow curve;
an online particle size detector is arranged in the sewage flow of the aerobic particle sludge automatic control system, and sludge particle size data of the aerobic particle sludge in the sewage flow are collected through the online particle size detector and a sludge particle size curve is correspondingly generated;
A PH value detector is arranged at the water inlet of the aerobic granular sludge automatic control system, and PH value data of sewage flow of the water inlet is collected through the PH value detector and correspondingly generated;
And arranging a sludge concentration meter in the sewage flow of the aerobic granular sludge automatic control system, collecting aerobic sludge content data of the aerobic granular sludge through the sludge concentration meter, and correspondingly generating an aerobic sludge content curve.
3. The method for controlling the operation of the aerobic granular sludge according to claim 1, wherein the method for calculating the oxygen demand of the current sewage flow in the aerobic granular sludge automatic control system according to the aerobic sludge content data in the key monitoring data, and obtaining the oxygen demand target value specifically comprises the following steps:
Classifying the aerobic sludge content data according to a sludge particle size curve corresponding to the current sewage flow to obtain flocculent sludge concentration data and granular sludge concentration data;
Based on the tank capacity corresponding to the current sewage flow in the aerobic granular sludge automatic control system, performing absolute dry sludge calculation on the flocculent sludge concentration data and the granular sludge concentration data to obtain flocculent sludge absolute dry sludge data and granular sludge absolute dry sludge data;
Adding the flocculent sludge absolute dry sludge amount data and the granular sludge absolute dry sludge amount data to obtain absolute dry sludge total amount data;
calculating BOD food amount data and ammonia nitrogen content data according to a plurality of types of curve key points in key monitoring data corresponding to the current sewage flow and based on the absolute dry sludge total amount data;
And calculating the oxygen demand of the current sewage flow based on the BOD food amount data and the ammonia nitrogen content data to obtain an oxygen demand value, wherein the oxygen demand value corresponds to the oxygen sludge content data in the current sewage flow.
4. The method according to claim 1, wherein the adjusting control of PID of the current dissolved oxygen concentration in the key monitoring data and the oxygen demand value is performed to obtain an optimal dissolved oxygen concentration, and the method specifically comprises:
determining the current dissolved oxygen concentration of the current sewage according to the COD content curve of the inlet and outlet water in the key monitoring data;
Performing difference calculation on the current dissolved oxygen concentration and the oxygen demand value to obtain deviation data;
And carrying out frequency control on the frequency converter of the oxygen supply fan based on the adjustment control parameters to obtain the optimal dissolved oxygen concentration.
5. The method for controlling the operation of aerobic granular sludge according to claim 4, wherein the deviation data is adjusted and controlled by a preset PID control algorithm to obtain adjustment control parameters, and the method specifically comprises:
determining the deviation data as current error data through a proportion link of the PID control algorithm, and performing product output control proportional adjustment of related proportion coefficients on the current error data to determine a first control parameter;
performing steady-state error elimination processing on error integration accumulated by the deviation data through an integration link of the PID control algorithm, and outputting a second control parameter related to the product of an integration coefficient and the error integration;
Carrying out error trend prediction on the time sequence change rate by the error differentiation of the deviation data through a differentiation link of the PID control algorithm, and outputting a third control parameter related to the product of the error differentiation and a differentiation coefficient;
and performing superposition output control on the first control parameter, the second control parameter and the third control parameter to obtain the adjustment control parameter.
6. An operation control apparatus for aerobic granular sludge, characterized in that the apparatus comprises:
At least one processor, and
A memory communicatively coupled to the at least one processor, wherein,
The memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method of controlling the operation of an aerobic granular sludge according to any one of claims 1-5.
7. A non-volatile computer storage medium, characterized in that the storage medium is a non-volatile computer readable storage medium storing at least one program, each of the programs comprising instructions which, when executed by a terminal, cause the terminal to perform a method of controlling the operation of aerobic granular sludge according to any of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411648894.5A CN119161008B (en) | 2024-11-19 | 2024-11-19 | Operation control method, equipment and medium for aerobic granular sludge |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411648894.5A CN119161008B (en) | 2024-11-19 | 2024-11-19 | Operation control method, equipment and medium for aerobic granular sludge |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN119161008A CN119161008A (en) | 2024-12-20 |
| CN119161008B true CN119161008B (en) | 2025-03-04 |
Family
ID=93880925
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202411648894.5A Active CN119161008B (en) | 2024-11-19 | 2024-11-19 | Operation control method, equipment and medium for aerobic granular sludge |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN119161008B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118724260A (en) * | 2024-07-11 | 2024-10-01 | 广东工业大学 | A method for biological phosphorus removal based on F/M regulation to enhance continuous flow aerobic granular sludge-membrane bioreactor |
| CN118908436A (en) * | 2024-10-09 | 2024-11-08 | 济南智泽德源环保科技有限公司 | Dissolved oxygen control method, device and medium for aerobic granular sludge system |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8980091B2 (en) * | 2013-05-07 | 2015-03-17 | Praxair Technology, Inc. | Oxygen control system and method for wastewater treatment |
| CN117486429B (en) * | 2023-12-20 | 2024-12-06 | 北京城市排水集团有限责任公司 | A sewage treatment load balancing feedback water distribution system and method |
-
2024
- 2024-11-19 CN CN202411648894.5A patent/CN119161008B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118724260A (en) * | 2024-07-11 | 2024-10-01 | 广东工业大学 | A method for biological phosphorus removal based on F/M regulation to enhance continuous flow aerobic granular sludge-membrane bioreactor |
| CN118908436A (en) * | 2024-10-09 | 2024-11-08 | 济南智泽德源环保科技有限公司 | Dissolved oxygen control method, device and medium for aerobic granular sludge system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN119161008A (en) | 2024-12-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| O’Brien et al. | Model predictive control of an activated sludge process: A case study | |
| Azman et al. | Modeling and comparative study of PID Ziegler Nichols (ZN) and Cohen-Coon (CC) tuning method for Multi-tube aluminum sulphate water filter (MTAS) | |
| EP2414901B1 (en) | System and method for monitoring an integrated system | |
| CN115793471A (en) | Adjustable control method and system based on sewage treatment monitoring | |
| US8515581B2 (en) | Method and device arrangement for automatic dose control of chemicals | |
| CN201433129Y (en) | Aeration biological filter tank dissolved oxygen intelligent control system | |
| Wang et al. | Composite control of post-chlorine dosage during drinking water treatment | |
| Robles et al. | Advanced control system for optimal filtration in submerged anaerobic MBRs (SAnMBRs) | |
| CN115215436A (en) | Intelligent dosing dephosphorization control system and control method based on synchronous dephosphorization | |
| CN102621883A (en) | PID (proportion integration differentiation) parameter turning method and PID parameter turning system | |
| CN113289759B (en) | Method and device for regulating particle size distribution of micropowder in dry grinding system | |
| CN119430489B (en) | SND-ED intelligent wastewater treatment deep denitrification system and control method thereof | |
| CN109368760B (en) | A method for realizing pH adaptive control of wastewater in DCS | |
| JP6655975B2 (en) | Aeration control device and aeration control method | |
| CN118348933A (en) | A method for accurately controlling dissolved oxygen in a sewage aerobic treatment system | |
| CN108821435B (en) | Dissolved oxygen control method in sewage treatment | |
| CN119161008B (en) | Operation control method, equipment and medium for aerobic granular sludge | |
| Phuc et al. | Robust control synthesis for the activated sludge process | |
| CN118908436B (en) | Dissolved oxygen control method, device and medium for aerobic granular sludge system | |
| Liu et al. | Extremum-seeking with variable gain control for intensifying biogas production in anaerobic fermentation | |
| WO1998003434A1 (en) | Device for controlling dissolved oxygen concentration of aeration tank, device for controlling temperature of aeration tank, device for controlling flow rate of raw water for homogeneous-flow liquid surface, and wastewater treatment equipment used in activated sludge process | |
| Tandon et al. | Genetic algorithm based parameter tuning of PID controller for composition control system | |
| JP2002219481A (en) | Control device for dissolved oxygen concentration in aeration tank | |
| Hirsch et al. | Supervisory control system for adaptive phase and work cycle management of sequencing wastewater treatment plant | |
| Ingildsen et al. | Exploiting online in-situ ammonium, nitrate and phosphate sensors in full-scale wastewater plant operation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |