CN118603207B - Visual power distribution room environment monitoring method, system and device - Google Patents
Visual power distribution room environment monitoring method, system and device Download PDFInfo
- Publication number
- CN118603207B CN118603207B CN202411078468.2A CN202411078468A CN118603207B CN 118603207 B CN118603207 B CN 118603207B CN 202411078468 A CN202411078468 A CN 202411078468A CN 118603207 B CN118603207 B CN 118603207B
- Authority
- CN
- China
- Prior art keywords
- abnormal
- data
- power distribution
- attribute
- distribution room
- 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
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/243—Classification techniques relating to the number of classes
- G06F18/2433—Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computational Mathematics (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Physics (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Probability & Statistics with Applications (AREA)
- Operations Research (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The invention discloses a visualized power distribution room environment monitoring method, system and device, which comprise a data acquisition unit, a database, a data arrangement unit, an early warning analysis unit and a visualization unit. According to the visualized power distribution room environment monitoring method, system and device, the historical data in the normal state and the abnormal state are compared and analyzed, so that the abnormal attribute sets corresponding to the fault characteristics of different equipment can be determined. The method can effectively identify key parameters causing equipment faults, provide scientific basis for fault diagnosis and prevention, and enable the early warning analysis unit to conduct abnormal analysis on the environmental data collected in real time currently according to the result of arrangement analysis, and predict and warn possible equipment faults in time. The method is beneficial to operation and maintenance personnel to take preventive measures, avoids or reduces the risk of faults, and the visual information display mode is convenient for the operation and maintenance personnel to quickly understand the current power distribution room state, so that the response efficiency is improved.
Description
Technical Field
The invention relates to the technical field of environment monitoring, in particular to a visual power distribution room environment monitoring method, system and device.
Background
In the field of power distribution room environment monitoring, the traditional monitoring method often depends on manual inspection and periodic maintenance, and the mode is low in efficiency and difficult to realize real-time monitoring and early warning. Along with the development of the power system towards the intelligent and automatic directions, the power distribution room environment monitoring technology is provided with higher requirements, and the existing power distribution room environment monitoring system has the following problems:
In the prior art, the environment monitoring of the power distribution room mainly relies on staff to periodically perform field inspection, and environmental parameters such as temperature and humidity, harmful gas concentration and the like are read through a handheld instrument. The method is time-consuming and labor-consuming, cannot realize real-time monitoring, has low response speed for sudden environmental changes or equipment faults, and is difficult to discover and process problems in time.
Insufficient data collection and analysis-traditional monitoring means often lack systematic data collection and analysis capabilities. Because the data record depends on paper tables or personal records, the data is not easy to store, retrieve and analyze for a long time, so that the utilization rate of the historical data is low, and potential problems and failure modes are difficult to mine from the data.
The early warning system is lack of an effective early warning mechanism in the traditional environment monitoring system. Even though some advanced systems can send out alarms, most of the alarms are based on simple logic judgment of a single parameter threshold value, and the relevance among different environment parameters is not comprehensively considered, so that complicated fault conditions cannot be accurately predicted.
The fault diagnosis is difficult, when faults occur, the traditional monitoring means are difficult to diagnose the fault cause rapidly and accurately, shutdown maintenance is usually required, possible fault points are manually checked one by one, and the fault test method consumes a long time and affects the stable operation of the power system.
The environment parameters are various, including temperature, humidity, smoke, harmful gas concentration and the like, and different parameters have different influences on the operation of equipment, so that comprehensive monitoring and analysis are needed. The traditional monitoring means often cannot fully cover all key parameters, so that a monitoring blind area is caused.
Along with the development of the power industry to the intelligent and automatic direction, the intelligent and automatic requirements are raised to the intelligent and automatic level of the power distribution room environment monitoring technology. Modern power systems require a comprehensive solution that enables real-time monitoring, data analysis, fault early warning and intelligent decision making.
In view of the shortcomings and challenges in the background art, the invention provides a visualized power distribution room environment monitoring method, a visualized power distribution room environment monitoring system and a visualized device, and aims to realize real-time monitoring, historical data analysis, abnormal early warning and fault diagnosis of power distribution room environment parameters and improve operation safety and operation and maintenance efficiency of a power distribution room through advanced sensor technology, data analysis methods and visualization means.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a visual power distribution room environment monitoring method, a visual power distribution room environment monitoring system and a visual power distribution room environment monitoring device, and solves the problems in the background art.
In order to achieve the purpose, the invention is realized through the following technical scheme that the visualized power distribution room environment monitoring system comprises:
The data acquisition unit is used for acquiring environmental data in the power distribution room in real time through various sensors in the power distribution room;
the database is used for storing historical environment data of all power distribution facilities in the power distribution room in a normal state and in an abnormal state;
The data arrangement unit is used for arranging and analyzing normal environment data and abnormal environment data according to the historical environment data in the normal state and in the abnormal state;
the early warning analysis unit is used for carrying out abnormal analysis on the environmental data in the current real-time acquisition power distribution room according to the arrangement analysis result of the data arrangement unit, obtaining a corresponding fault signal and transmitting the fault signal to the visualization unit:
The visualization unit is used for displaying data parameters of different attributes in the environmental data in the power distribution room in real time, and displaying corresponding fault signals obtained by the early warning analysis unit on the visualization interface for notifying operation and maintenance personnel.
As a further scheme of the invention, the environmental data are data parameters of different attributes, such as temperature parameters, humidity parameters, smoke parameters, harmful gas concentration parameters, water level parameters, current parameters and voltage parameters, which are detected by sensors deployed at key positions of the power distribution room.
As a further scheme of the invention, the arrangement analysis mode is as follows:
firstly, obtaining normal environment data according to historical environment data in a normal state;
And secondly, selecting a time node corresponding to the equipment fault characteristic from multiple equipment fault characteristics of the power distribution room as an abnormal time node, acquiring a plurality of standard nodes before the abnormal time node according to a preset interval time, acquiring data parameters of different attributes on each standard node, performing abnormal analysis on the data parameters of each different attribute on all the standard nodes, obtaining an abnormal parameter set corresponding to each attribute, performing relevance analysis on the abnormal parameter set corresponding to each equipment fault characteristic, and obtaining an abnormal attribute set of the corresponding equipment fault characteristic.
As a further scheme of the invention, the specific mode of the first step is as follows:
StepA1, setting a plurality of analysis nodes with the same time interval in a target period;
StepA2, acquiring historical environmental data in all normal states on each analysis node, and then marking the data parameters with the same attribute in the analysis nodes as Ci, wherein i=1, 2 and n, namely the number of the data parameters with the same attribute, namely the number of the analysis nodes;
StepA3, by the formula Calculating discrete values CL of the data parameters of the attribute corresponding to each analysis node, wherein Cp represents the average value of all Ci participating in the calculation of the discrete values;
Meanwhile, through the formula Calculating a difference value average XC of the attribute corresponding to the data parameters on the adjacent analysis nodes, wherein i is not equal to n;
StepA4, then comparing CL with Ly, where Ly is a preset discrete threshold:
if CL < Ly is satisfied, cp is taken as a normal parameter standard value ZC of the corresponding attribute in the target period, and Normal parameter standard interval as the corresponding attribute;
Otherwise, when CL is more than or equal to Ly, sequentially deleting the corresponding Ci values according to the sequence of |Ci-Cp| from large to small until CL < Ly is met;
Extracting all undeleted Ci values, extracting data parameters adjacent to analysis nodes from all undeleted Ci values, calculating the difference value through C i-Ci-1, and then solving the data parameters on all adjacent analysis nodes to obtain an average value XC1 of the difference value;
At the same time, the average value is taken as the normal parameter standard value ZC of the corresponding attribute in the period, and then Normal parameter standard interval as the corresponding attribute;
StepA5, and the like, calculating normal parameter standard values and normal parameter standard intervals of other various attributes;
The normal parameter standard value and the normal parameter standard interval of each attribute are normal environment data.
As a further scheme of the invention, the abnormality analysis mode in the second step is as follows:
Data parameters on all standard nodes of the same attribute are selected:
extracting time difference values of each standard node and the abnormal time node, sequentially acquiring a plurality of data parameters on the corresponding standard nodes from small to large, and sequentially comparing the data parameters with the corresponding normal parameter standard intervals:
When g0 data parameters continuously in the normal parameter standard interval exist, the data parameters with larger time difference values between the standard node and the abnormal time node are not compared with the normal parameter standard interval any more, and all the data parameters before the data parameters continuously in the normal parameter standard interval correspond to the standard node exist as an abnormal parameter set of the attribute, wherein the abnormal parameter set comprises a plurality of abnormal parameter values;
and similarly, acquiring an abnormal parameter set corresponding to other attributes.
The correlation analysis method in the second step is as follows:
Firstly, respectively obtaining the number of abnormal parameter values in the abnormal parameter set corresponding to each attribute, and marking the number as YCj, wherein j=1, 2 and the number is equal to the number of the abnormal parameter values in the abnormal parameter set;
Then, through Calculating the quantity proportion YBj of the abnormal parameter values corresponding to each attribute;
The number duty ratio YBj of the abnormal parameter values corresponding to each attribute is then compared with a preset duty ratio threshold YBy:
when YBj of one attribute is more than or equal to YBy, the abnormal parameter value corresponding to the attribute is the key parameter in the fault characteristic of the equipment;
When YBj of the plurality of attributes is more than or equal to YBy, representing that the plurality of attributes are in association relation;
Then, a plurality of attributes in association relation are used as an abnormal attribute set of the equipment fault characteristics;
and similarly, calculating an abnormal attribute set of all different equipment fault characteristics.
As a further scheme of the invention, the specific mode of the early warning analysis unit is as follows:
firstly, at the current time node, environmental data in a power distribution room are collected in real time, and data parameters of different attributes in the environmental data are compared with normal parameter standard intervals corresponding to the attributes of the data parameters:
then, all the attributes of which the data parameters are not in the normal parameter standard interval are obtained from the data parameters, and the attributes are marked as abnormal attributes;
Then, all the abnormal attributes are respectively matched with a plurality of attributes in a plurality of abnormal attribute sets:
if the same rate of all the abnormal attributes and a plurality of attributes in one abnormal attribute set reaches a k value, the node at the current time is indicated to have equipment fault characteristics corresponding to the abnormal attribute set, and a known fault signal is generated;
if the same rate of all the abnormal attributes and a plurality of attributes in one abnormal attribute set does not reach a k value, the node at the current time is indicated to have unknown equipment fault characteristics, and an unknown fault signal is generated;
wherein k is a preset percentage coefficient, and the value of k is 96.54%;
When an unknown fault signal is generated, acquiring environmental data in the power distribution room in real time at a next time node with a designated interval duration from the current time node, and continuing to analyze through the steps;
As a further proposal of the invention, when the data parameters corresponding to different attributes in the collected environment data are compared with the normal parameter standard intervals corresponding to the attributes,
If all the attributes do not contain the data parameters which are not in the normal parameter standard interval, the corresponding fault signals are not generated, and the normal running state of the power distribution room corresponding to the acquisition time node is indicated.
A visual power distribution room environment monitoring method is realized through the visual power distribution room environment monitoring system.
The visualized power distribution room environment monitoring device comprises a sensor group, a central processing unit and a touch display, wherein the sensor group, the central processing unit and the touch display are in communication connection, and the device is used for realizing the visualized power distribution room environment monitoring system;
The sensor group is used for detecting and acquiring data parameters with different attributes and comprises a temperature sensor, a humidity sensor, a smoke sensor, a harmful gas concentration sensor, a water level sensor and a current and voltage sensor;
The central processing unit comprises a data acquisition unit, a database, a data arrangement unit and an early warning analysis unit;
the touch display includes a visualization unit.
The invention provides a visual power distribution room environment monitoring method, a visual power distribution room environment monitoring system and a visual power distribution room environment monitoring device. Compared with the prior art, the method has the following beneficial effects:
the beneficial effects, benefits and advantages of the present invention are mainly embodied in the following aspects:
And the real-time monitoring and data acquisition can acquire environmental data including parameters such as temperature, humidity, smoke, harmful gas concentration, water level, current, voltage and the like in real time by arranging various sensors in the power distribution room. The real-time monitoring mechanism is beneficial to timely finding out potential problems in the power distribution room and ensuring safe and stable operation of the power distribution system.
And (3) establishing a historical data analysis and standard, namely storing and analyzing historical environmental data of the power distribution room in normal and abnormal states by the system, so as to establish the standard of the normal environmental data and the abnormal environmental data. This helps to provide an accurate reference for subsequent early warning analysis and fault diagnosis.
And determining an abnormal attribute set, namely determining the abnormal attribute set corresponding to different equipment fault characteristics by comparing and analyzing the historical data in the normal state and the abnormal state. The method can effectively identify key parameters causing equipment faults and provide scientific basis for fault diagnosis and prevention.
The early warning analysis and fault prediction, namely the early warning analysis unit can perform abnormal analysis on the environmental data acquired in real time currently according to the result of the arrangement analysis, and predict and warn the equipment faults possibly occurring in time. This helps the service personnel take precautions to avoid or reduce the risk of failure.
The visual display system is characterized in that the visual unit provided by the system can display the environmental data in the power distribution room in real time and intuitively display the early warning analysis result on the interface. The visual information display mode is convenient for operation and maintenance personnel to quickly understand the current power distribution room state, and response efficiency is improved.
And the system can adaptively adjust the normal parameter standard interval in the analysis process so as to adapt to the change of the power distribution room environment. The self-adaptive capacity enables the system to be more flexible and accurate, and can be better adapted to different running conditions.
And generating and processing fault signals, namely generating known or unknown fault signals according to a preset matching rule when the system detects the abnormal attribute. For unknown faults, the system can continue to analyze at the subsequent time nodes so as to find new fault modes and continuously perfect a fault database.
The invention can improve the safety and reliability of the power distribution room, reduce equipment faults caused by environmental factors, reduce operation and maintenance cost and ensure the stability of power supply.
In summary, the invention provides a comprehensive and automatic solution for monitoring the environment of the power distribution room by integrating the functions of data monitoring, historical data analysis, abnormal attribute set determination, early warning analysis, visual display and the like, and remarkably improves the management level and fault coping capacity of the power distribution room.
Drawings
FIG. 1 is a system block diagram of the present invention;
FIG. 2 is a flow chart of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1-2, the present invention provides a technical solution, a visual power distribution room environment monitoring system, comprising:
The data acquisition unit is used for acquiring environmental data in the power distribution room in real time through various sensors in the power distribution room;
The environmental data are data parameters with different attributes, such as temperature parameters, humidity parameters, smoke parameters, harmful gas concentration parameters, water level parameters, current parameters and voltage parameters, which are obtained by detection of sensors arranged at key positions of the power distribution room;
the database is used for storing historical environment data of all power distribution facilities in the power distribution room in a normal state and in an abnormal state;
the data arrangement unit is used for obtaining normal environment data according to the history environment data in the normal state;
StepA1, setting a plurality of analysis nodes with the same time interval in a target period;
StepA2, acquiring historical environmental data in all normal states on each analysis node, and then marking the data parameters with the same attribute in the analysis nodes as Ci, wherein i=1, 2 and n, namely the number of the data parameters with the same attribute, namely the number of the analysis nodes;
StepA3, by the formula Calculating discrete values CL of the data parameters of the attribute corresponding to each analysis node, wherein Cp represents the average value of all Ci participating in the calculation of the discrete values;
Meanwhile, through the formula Calculating a difference value average XC of the attribute corresponding to the data parameters on the adjacent analysis nodes, wherein i is not equal to n;
StepA4, then comparing CL with Ly, where Ly is a preset discrete threshold:
if CL < Ly is satisfied, cp is taken as a normal parameter standard value ZC of the corresponding attribute in the target period, and Normal parameter standard interval as the corresponding attribute;
Otherwise, when CL is more than or equal to Ly, sequentially deleting the corresponding Ci values according to the sequence of |Ci-Cp| from large to small until CL < Ly is met;
Extracting all undeleted Ci values, extracting data parameters adjacent to analysis nodes from all undeleted Ci values, calculating the difference value through C i-Ci-1, and then solving the data parameters on all adjacent analysis nodes to obtain an average value XC1 of the difference value;
At the same time, the average value is taken as the normal parameter standard value ZC of the corresponding attribute in the period, and then Normal parameter standard interval as the corresponding attribute;
StepA5, and the like, calculating normal parameter standard values and normal parameter standard intervals of other various attributes;
The normal parameter standard value and the normal parameter standard interval of each attribute are normal environment data;
the early warning analysis unit is used for carrying out abnormal analysis on the environmental data in the current real-time acquisition power distribution room according to the arrangement analysis result of the data arrangement unit:
The specific mode is as follows:
firstly, at the current time node, environmental data in a power distribution room are collected in real time, and data parameters of different attributes in the environmental data are compared with normal parameter standard intervals corresponding to the attributes of the data parameters:
then, all the attributes of which the data parameters are not in the normal parameter standard interval are obtained from the data parameters, and the attributes are marked as abnormal attributes;
the data parameters corresponding to different attributes in the acquired environment data are compared with normal parameter standard intervals corresponding to the attributes of the data parameters:
If all the attributes do not contain the data parameters which are not in the normal parameter standard interval, the corresponding fault signals are not generated, and the normal running state of the power distribution room corresponding to the acquisition time node is indicated;
The system can timely monitor potential problems and send early warning through various sensors to collect environment data in the power distribution room, such as temperature, humidity and smoke, compared with traditional manual inspection, the efficiency and accuracy of monitoring are greatly improved, standard environment parameters are established through historical data, objective references are provided for fault detection, operation and maintenance personnel are helped to make more accurate maintenance and adjustment decisions based on the data, abnormal attributes can be quickly identified through comparison of the real-time data and a preset normal parameter standard interval, fault diagnosis process is accelerated, equipment downtime is reduced, the situation that safety of personnel is possibly threatened due to exceeding of concentration of harmful gases and the like can be timely found, measures are taken in advance, and safety of the personnel and the equipment is protected.
Example two
As an embodiment two of the present application, when the present application is implemented, compared with the embodiment one, the technical solution of the present embodiment is different from the embodiment one only in that in the present embodiment,
The data arrangement unit is also used for obtaining normal environment data through the historical environment data in the normal state and obtaining an abnormal attribute set by combining the historical environment data in the abnormal state;
StepV1, selecting a time node corresponding to a device fault feature from multiple device fault features of a power distribution room as an abnormal time node, acquiring a plurality of standard nodes before the abnormal time node according to preset interval duration, acquiring data parameters of different attributes on each standard node, and performing abnormal analysis on the data parameters of each different attribute on all the standard nodes;
the anomaly analysis method is as follows:
Taking data parameters on all standard nodes of the same attribute as an example:
extracting time difference values of each standard node and the abnormal time node, sequentially acquiring a plurality of data parameters on the corresponding standard nodes from small to large, and sequentially comparing the data parameters with the corresponding normal parameter standard intervals:
When g0 data parameters continuously in the normal parameter standard interval exist, the data parameters with larger time difference values between the standard node and the abnormal time node are not compared with the normal parameter standard interval any more, and all the data parameters before the data parameters continuously in the normal parameter standard interval correspond to the standard node exist as an abnormal parameter set of the attribute, wherein the abnormal parameter set comprises a plurality of abnormal parameter values;
Similarly, obtaining an abnormal parameter set corresponding to other attributes;
StepV2, carrying out relevance analysis on an abnormal parameter set corresponding to all the attributes of one equipment fault feature:
the correlation analysis mode is as follows:
Firstly, respectively obtaining the number of abnormal parameter values in the abnormal parameter set corresponding to each attribute, and marking the number as YCj, wherein j=1, 2 and the number is equal to the number of the abnormal parameter values in the abnormal parameter set;
Then, through Calculating the quantity proportion YBj of the abnormal parameter values corresponding to each attribute;
The number duty ratio YBj of the abnormal parameter values corresponding to each attribute is then compared with a preset duty ratio threshold YBy:
when YBj of one attribute is more than or equal to YBy, the abnormal parameter value corresponding to the attribute is the key parameter in the fault characteristic of the equipment;
When YBj of the plurality of attributes is more than or equal to YBy, representing that the plurality of attributes are in association relation;
Then, a plurality of attributes in association relation are used as an abnormal attribute set of the equipment fault characteristics;
And similarly, calculating an abnormal attribute set of all the fault characteristics of different equipment;
the early warning analysis unit is also used for respectively matching all the abnormal attributes with a plurality of attributes in a plurality of abnormal attribute sets:
if the same rate of all the abnormal attributes and a plurality of attributes in one abnormal attribute set reaches a k value, the node at the current time is indicated to have equipment fault characteristics corresponding to the abnormal attribute set, and a known fault signal is generated;
if the same rate of all the abnormal attributes and a plurality of attributes in one abnormal attribute set does not reach a k value, the node at the current time is indicated to have unknown equipment fault characteristics, and an unknown fault signal is generated;
where k is a predetermined percentage factor, in this example, k takes a value of 96.54%;
When an unknown fault signal is generated, acquiring environmental data in the power distribution room in real time at a next time node with a designated interval duration from the current time node, and continuing to analyze through the steps;
The method and the system introduce the concept of an abnormal attribute set, can identify parameter change modes related to specific fault characteristics by analyzing historical fault data, improve the accuracy of fault prediction, can find out the connection among different attributes by correlation analysis, help understand the cause of complex faults, realize deeper fault analysis and prevention, and can generate known and unknown fault signals according to the matched abnormal attributes and preset matching rate (k value), thereby being beneficial to timely taking corresponding maintenance measures or further investigating unknown fault causes.
Example III
As an embodiment three of the present application, in the implementation of the present application, compared with the first embodiment and the second embodiment, the technical solution of the present embodiment is that the solutions of the first embodiment and the second embodiment are implemented in combination, and the difference between the technical solution of the present embodiment and the first embodiment and the second embodiment is only that the present embodiment further includes:
The visualization unit is used for displaying data parameters of different attributes in the environmental data in the power distribution room in real time, and displaying corresponding abnormal attributes and fault signals obtained by the early warning analysis unit on the visualization interface for notifying operation and maintenance personnel:
The embodiment displays the real-time data and the early warning information on the visual interface, so that operation and maintenance personnel can intuitively know the running state of the power distribution room, the monitoring efficiency and the response speed are improved, and a comprehensive monitoring system is provided by combining the technical schemes of the first embodiment and the second embodiment, so that real-time monitoring and early warning can be realized, and deep fault diagnosis can be provided through historical data analysis.
Example IV
As an embodiment four of the present application, in the implementation of the present application, compared with the first, second and third embodiments, the technical solution of the present embodiment is to combine the solutions of the first, second and third embodiments.
According to the technical scheme of the first three embodiments, the integrated system integrating real-time monitoring, historical data analysis, fault mode identification and information visualization is constructed, powerful technical support is provided for efficient, safe and intelligent management of a power distribution room, high automation and intellectualization from data acquisition to fault early warning, fault diagnosis and information presentation are achieved, operation and maintenance efficiency and reliability of the power distribution room are greatly improved, operation and maintenance resources can be distributed more pertinently by means of intelligent analysis capability of the system, maintenance work is optimized, and operation and maintenance cost is reduced.
In summary, these embodiments demonstrate a stepwise deep and comprehensive approach to improving the monitoring and management level of a power distribution room to ensure stable operation of the power system.
The invention also provides a technical scheme that the visual power distribution room environment monitoring method is realized by the visual power distribution room environment monitoring system:
The method comprises the following steps:
Step one, data acquisition
Environmental data within the power distribution room is collected in real time by deploying various sensors within the power distribution room. These data include parameters such as temperature, humidity, smoke, concentration of harmful gases, water level, current and voltage.
Step two, data storage
And storing the collected environmental data in a database, wherein the database stores historical environmental data of all power distribution facilities of the power distribution room in a normal state and an abnormal state.
Step three, data arrangement and analysis
And obtaining a standard value and a standard interval of the normal environment data from the historical data.
And carrying out anomaly analysis on the environmental data acquired in real time currently, and identifying any anomaly attribute by comparing the current data with a normal parameter standard interval.
Step four, analysis of abnormal attribute sets
In conjunction with historical fault data, the anomaly property set is analyzed and established, which facilitates more accurate prediction and diagnosis of faults.
Step five, information matching and fault signal generation
Matching all the abnormal attributes with a known abnormal attribute set, and generating a known or unknown fault signal according to a preset matching rate (k value);
If no abnormality is detected, the power distribution room is indicated to be in normal operation.
And step six, visually displaying, namely displaying environmental data in the power distribution room in real time through a visual unit, and displaying an early warning analysis result and a fault signal on a visual interface so as to enable operation and maintenance personnel to respond in time.
The method provides powerful technical support for efficient, safe and intelligent management of the power distribution room through real-time monitoring, historical data analysis, fault mode identification and information visualization. The monitoring efficiency and the response speed are improved, maintenance work is optimized through intelligent analysis, operation and maintenance cost is reduced, and stable operation of the power system is ensured.
The invention also provides a technical scheme that the visualized power distribution room environment monitoring device comprises a sensor group, a central processing unit and a touch display, wherein the sensor group, the central processing unit and the touch display are in communication connection, and the visualized power distribution room environment monitoring device is used for realizing the visualized power distribution room environment monitoring system;
The sensor group is used for detecting and acquiring data parameters with different attributes and comprises a temperature sensor, a humidity sensor, a smoke sensor, a harmful gas concentration sensor, a water level sensor and a current-voltage sensor;
The central processing unit comprises a data acquisition unit, a database, a data arrangement unit and an early warning analysis unit;
the touch display comprises a visualization unit.
The above formulas are all formulas with dimensionality removed and numerical calculation, the formulas are formulas with the latest real situation obtained by software simulation through collecting a large amount of data, and preset parameters and threshold selection in the formulas are set by those skilled in the art according to the actual situation.
And all that is not described in detail in this specification is well known to those skilled in the art.
The foregoing describes one embodiment of the present invention in detail, but the disclosure is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (6)
1. A visual power distribution room environmental monitoring system, comprising:
The data acquisition unit is used for acquiring environmental data in the power distribution room in real time through various sensors in the power distribution room;
the database is used for storing historical environment data of all power distribution facilities in the power distribution room in a normal state and in an abnormal state;
The data arrangement unit is used for arranging and analyzing normal environment data and abnormal environment data according to the historical environment data in the normal state and in the abnormal state;
the arrangement analysis mode is as follows:
firstly, obtaining normal environment data according to historical environment data in a normal state;
Secondly, selecting a time node corresponding to a device fault feature from multiple device fault features of a power distribution room as an abnormal time node, acquiring a plurality of standard nodes before the abnormal time node according to preset interval time, acquiring data parameters of different attributes on each standard node, performing abnormal analysis on the data parameters of each different attribute on all the standard nodes, acquiring an abnormal parameter set corresponding to each attribute, performing relevance analysis on the abnormal parameter set corresponding to each device fault feature, and acquiring an abnormal attribute set of the corresponding device fault feature;
the second step is the exception analysis mode as follows:
Data parameters on all standard nodes of the same attribute are selected:
extracting time difference values of each standard node and the abnormal time node, sequentially acquiring a plurality of data parameters on the corresponding standard nodes from small to large, and sequentially comparing the data parameters with the corresponding normal parameter standard intervals:
When g0 data parameters continuously in the normal parameter standard interval exist, the data parameters with larger time difference values between the standard node and the abnormal time node are not compared with the normal parameter standard interval any more, and all the data parameters before the data parameters continuously in the normal parameter standard interval correspond to the standard node exist as an abnormal parameter set of the attribute, wherein the abnormal parameter set comprises a plurality of abnormal parameter values;
Similarly, obtaining an abnormal parameter set corresponding to other attributes;
the correlation analysis mode in the second step is as follows:
Firstly, respectively obtaining the number of abnormal parameter values in the abnormal parameter set corresponding to each attribute, and marking the number as YCj, wherein j=1, 2 and the number is equal to the number of the abnormal parameter values in the abnormal parameter set;
Then, through 、、......Calculating the quantity proportion YBj of the abnormal parameter values corresponding to each attribute;
The number duty ratio YBj of the abnormal parameter values corresponding to each attribute is then compared with a preset duty ratio threshold YBy:
when YBj of one attribute is more than or equal to YBy, the abnormal parameter value corresponding to the attribute is the key parameter in the fault characteristic of the equipment;
When YBj of the plurality of attributes is more than or equal to YBy, representing that the plurality of attributes are in association relation;
Then, a plurality of attributes in association relation are used as an abnormal attribute set of the equipment fault characteristics;
And similarly, calculating an abnormal attribute set of all the fault characteristics of different equipment;
The early warning analysis unit is used for carrying out abnormal analysis on the environmental data in the current real-time acquisition power distribution room according to the arrangement analysis result of the data arrangement unit, obtaining a corresponding fault signal and transmitting the fault signal to the visualization unit;
The specific mode of the early warning analysis unit is as follows:
firstly, at the current time node, environmental data in a power distribution room are collected in real time, and data parameters of different attributes in the environmental data are compared with normal parameter standard intervals corresponding to the attributes of the data parameters:
then, all the attributes of which the data parameters are not in the normal parameter standard interval are obtained from the data parameters, and the attributes are marked as abnormal attributes;
Then, all the abnormal attributes are respectively matched with a plurality of attributes in a plurality of abnormal attribute sets:
if the same rate of all the abnormal attributes and a plurality of attributes in one abnormal attribute set reaches a k value, the node at the current time is indicated to have equipment fault characteristics corresponding to the abnormal attribute set, and a known fault signal is generated;
if the same rate of all the abnormal attributes and a plurality of attributes in one abnormal attribute set does not reach a k value, the node at the current time is indicated to have unknown equipment fault characteristics, and an unknown fault signal is generated;
wherein k is a preset percentage coefficient, and the value of k is 96.54%;
When an unknown fault signal is generated, acquiring environmental data in the power distribution room in real time at a next time node with a designated interval duration from the current time node, and continuing to analyze through the steps;
The visualization unit is used for displaying data parameters of different attributes in the environmental data in the power distribution room in real time, and displaying corresponding fault signals obtained by the early warning analysis unit on the visualization interface for notifying operation and maintenance personnel.
2. The visual power distribution room environment monitoring system of claim 1, wherein the environment data are data parameters of different attributes detected by sensors arranged at key positions of the power distribution room, and the data parameters of different attributes comprise temperature parameters, humidity parameters, smoke parameters, harmful gas concentration parameters, water level parameters, current parameters and voltage parameters.
3. A visual power distribution room environment monitoring system according to claim 2, wherein the specific mode in the first step is as follows:
StepA1, setting a plurality of analysis nodes with the same time interval in a target period;
StepA2, acquiring historical environmental data in all normal states on each analysis node, and then marking the data parameters with the same attribute in the analysis nodes as Ci, wherein i=1, 2 and n, namely the number of the data parameters with the same attribute, namely the number of the analysis nodes;
StepA3, by the formula Calculating discrete values CL of the attribute corresponding to the data parameters on each analysis node, wherein Cp represents the average value of all Ci participating in the calculation of the discrete values;
Meanwhile, through the formula Calculating a difference value average XC of the attribute corresponding to the data parameters on the adjacent analysis nodes, wherein i is not equal to n;
StepA4, then comparing CL with Ly, where Ly is a preset discrete threshold:
if CL < Ly is satisfied, cp is taken as a normal parameter standard value ZC of the corresponding attribute in the target period, and Normal parameter standard interval as the corresponding attribute;
Otherwise, when CL is more than or equal to Ly, sequentially deleting the corresponding Ci values according to the sequence of |Ci-Cp| from large to small until CL < Ly is met;
Extracting all undeleted Ci values, extracting data parameters adjacent to analysis nodes from all undeleted Ci values, and passing Calculating the difference value, and then obtaining the data parameters on all adjacent analysis nodes to obtain an average value XC1 of the difference value;
At the same time, the average value is taken as the normal parameter standard value ZC of the corresponding attribute in the period, and then Normal parameter standard interval as the corresponding attribute;
StepA5, and the like, calculating normal parameter standard values and normal parameter standard intervals of other various attributes;
The normal parameter standard value and the normal parameter standard interval of each attribute are normal environment data.
4. The visual power distribution room environment monitoring system of claim 1, wherein when comparing the data parameters corresponding to each different attribute in the collected environment data with the normal parameter standard intervals corresponding to the attribute,
If all the attributes do not contain the data parameters which are not in the normal parameter standard interval, the corresponding fault signals are not generated, and the normal running state of the power distribution room corresponding to the acquisition time node is indicated.
5. A method for visual monitoring of the environment of a power distribution room, characterized in that the method is realized by a visual monitoring system of the environment of the power distribution room according to any one of claims 1-4.
6. The visualized power distribution room environment monitoring device is characterized by comprising a sensor group, a central processing unit and a touch display, wherein the sensor group, the central processing unit and the touch display are in communication connection, and the device is used for realizing the visualized power distribution room environment monitoring system according to any one of claims 1-4;
The sensor group is used for detecting and acquiring data parameters with different attributes and comprises a temperature sensor, a humidity sensor, a smoke sensor, a harmful gas concentration sensor, a water level sensor and a current and voltage sensor;
The central processing unit comprises a data acquisition unit, a database, a data arrangement unit and an early warning analysis unit;
the touch display includes a visualization unit.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411078468.2A CN118603207B (en) | 2024-08-07 | 2024-08-07 | Visual power distribution room environment monitoring method, system and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411078468.2A CN118603207B (en) | 2024-08-07 | 2024-08-07 | Visual power distribution room environment monitoring method, system and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118603207A CN118603207A (en) | 2024-09-06 |
| CN118603207B true CN118603207B (en) | 2024-12-17 |
Family
ID=92559713
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202411078468.2A Active CN118603207B (en) | 2024-08-07 | 2024-08-07 | Visual power distribution room environment monitoring method, system and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118603207B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119002377B (en) * | 2024-10-23 | 2025-03-07 | 昱源宁海环保科技股份有限公司 | Centralized monitoring method and system based on ceramsite production line |
| CN119030155B (en) * | 2024-10-28 | 2025-03-14 | 广东联航智能科技有限公司 | An intelligent power distribution room operation monitoring system and method |
| CN119276012B (en) * | 2024-12-09 | 2025-03-18 | 太原银泰联创科技有限公司 | A data monitoring system based on electric power telecontrol |
| CN119314307A (en) * | 2024-12-11 | 2025-01-14 | 福建省港航勘察设计院有限公司 | A monitoring and early warning platform for unmanned operation areas in ports |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118035925A (en) * | 2024-04-11 | 2024-05-14 | 国网信息通信产业集团有限公司 | A data processing system based on large power model |
| CN118449277A (en) * | 2024-05-22 | 2024-08-06 | 济宁众达利电气设备有限公司 | High-low voltage power distribution cabinet abnormal fault information remote monitoring system |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3766208B2 (en) * | 1998-07-09 | 2006-04-12 | 株式会社東芝 | Process data monitoring device |
| CN116128472A (en) * | 2022-12-28 | 2023-05-16 | 福建亿山能源管理有限公司 | Power distribution room fault operation and maintenance management method and system |
| CN116911829A (en) * | 2023-07-25 | 2023-10-20 | 广东电网有限责任公司 | A power distribution room operation and maintenance management method and system |
-
2024
- 2024-08-07 CN CN202411078468.2A patent/CN118603207B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118035925A (en) * | 2024-04-11 | 2024-05-14 | 国网信息通信产业集团有限公司 | A data processing system based on large power model |
| CN118449277A (en) * | 2024-05-22 | 2024-08-06 | 济宁众达利电气设备有限公司 | High-low voltage power distribution cabinet abnormal fault information remote monitoring system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN118603207A (en) | 2024-09-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN118603207B (en) | Visual power distribution room environment monitoring method, system and device | |
| JP5081998B1 (en) | Abnormal sign diagnostic apparatus and abnormal sign diagnostic method | |
| JP5081999B1 (en) | How to display abnormal sign diagnosis results | |
| CN107733357A (en) | The fault detection algorithm of battery panel in a kind of large-sized photovoltaic power station | |
| CN118261584A (en) | Transformer status assessment method and system based on multi-parameter data | |
| CN115640860B (en) | Electromechanical equipment remote maintenance method and system for industrial cloud service | |
| CN118687632B (en) | A coal mine electromechanical equipment operating status monitoring system based on data analysis | |
| CN118118319A (en) | A network equipment intelligent diagnosis method and system based on big data | |
| CN112580858A (en) | Equipment parameter prediction analysis method and system | |
| CN117807155B (en) | Method, equipment and storage medium for generating multi-dimensional early warning prompt information | |
| CN119378989A (en) | An intelligent early warning management system and method for an information center computer room | |
| CN118035925A (en) | A data processing system based on large power model | |
| CN104317778A (en) | Massive monitoring data based substation equipment fault diagnosis method | |
| CN117761423A (en) | A method for predicting distribution network faults | |
| CN119312197B (en) | Instrument equipment fault detection system based on big data technology | |
| CN118899958B (en) | A monitoring method for high and low voltage distribution cabinet and distribution cabinet | |
| CN110455370B (en) | Flood-prevention drought-resisting remote measuring display system | |
| CN120046035A (en) | Intelligent fault diagnosis device and method with BIT capability | |
| CN119249208A (en) | Rail vehicle traction filter detection method, device, equipment and storage medium | |
| CN118444080A (en) | Distribution branch line power failure analysis method based on big data | |
| CN117937733A (en) | Electric power big data electric power acquisition and analysis system and method | |
| CN113836203A (en) | Network data diagnosis detection analysis system | |
| CN119064052B (en) | Real-time detection method and system for activated carbon adsorption device based on deep learning | |
| CN119249324B (en) | Wind power plant data quality assessment method based on high-dimensional space anomaly identification | |
| CN114487283B (en) | Remote intelligent diagnosis and operation and maintenance method and system for air quality monitoring system |
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 |