CN118466433B - Printing and dyeing production line online monitoring method and system based on Internet of things - Google Patents
Printing and dyeing production line online monitoring method and system based on Internet of things Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 194
- 238000007639 printing Methods 0.000 title claims abstract description 187
- 238000004043 dyeing Methods 0.000 title claims abstract description 185
- 238000000034 method Methods 0.000 title claims abstract description 62
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 53
- 239000007788 liquid Substances 0.000 claims abstract description 80
- 230000003595 spectral effect Effects 0.000 claims abstract description 53
- 238000001228 spectrum Methods 0.000 claims abstract description 27
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- 238000012806 monitoring device Methods 0.000 claims description 58
- 230000002159 abnormal effect Effects 0.000 claims description 57
- 238000012423 maintenance Methods 0.000 claims description 25
- 238000007689 inspection Methods 0.000 claims description 14
- 230000001483 mobilizing effect Effects 0.000 claims description 12
- 238000010183 spectrum analysis Methods 0.000 claims description 6
- 230000001105 regulatory effect Effects 0.000 claims description 5
- 238000005259 measurement Methods 0.000 claims description 3
- 230000000875 corresponding effect Effects 0.000 description 22
- 230000005856 abnormality Effects 0.000 description 13
- 238000004364 calculation method Methods 0.000 description 12
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- 238000012545 processing Methods 0.000 description 7
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- 238000010606 normalization Methods 0.000 description 4
- 230000004044 response Effects 0.000 description 3
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- 238000004891 communication Methods 0.000 description 2
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- 238000006731 degradation reaction Methods 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000013210 evaluation model Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000009979 jig dyeing Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 239000004753 textile Substances 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000009529 body temperature measurement Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000009972 garment dyeing Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000009981 jet dyeing Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000009980 pad dyeing Methods 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 238000013024 troubleshooting Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
- 238000004804 winding Methods 0.000 description 1
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41875—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by quality surveillance of production
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
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Abstract
The application relates to the technical field of printing and dyeing equipment monitoring, and discloses an online monitoring method and system of a printing and dyeing production line based on the Internet of things, wherein the method comprises the following steps: acquiring the whole temperature data of printing and dyeing equipment, and calculating a temperature gain value; acquiring the whole humidity data of printing and dyeing equipment, and calculating a humidity gain value; obtaining liquid level data of dye of printing and dyeing equipment, and calculating a liquid level power spectrum density average value; obtaining the height data of the printing and dyeing cloth transmitted on the printing and dyeing equipment; according to the height data, calculating a height power spectrum density average value; calculating a state evaluation value of the printing and dyeing equipment by using a weighted average algorithm according to the temperature gain value, the humidity gain value, the liquid level power spectral density average value and the height power spectral density average value; and triggering an alarm mechanism if the state evaluation value exceeds the evaluation threshold value. Through multidimensional data monitoring, the quality and the efficiency of production are guaranteed.
Description
Technical Field
The application relates to the technical field of printing and dyeing equipment monitoring, in particular to an online monitoring method and system for a printing and dyeing production line based on the Internet of things.
Background
In the textile printing and dyeing industry, with the expansion of production scale and the aggravation of market competition, the requirements for monitoring and managing the production process are increasingly increased. The traditional monitoring method is often dependent on manual inspection and manual recording, and the method is low in efficiency, easy to make mistakes and difficult to meet the requirements of modern printing and dyeing enterprises. Therefore, the online monitoring method and system of the printing and dyeing production line based on the Internet of things have been developed, and a comprehensive and efficient intelligent management solution is provided for printing and dyeing enterprises.
The internet of things technology realizes intelligent recognition, positioning, tracking, monitoring and management by connecting various information sensing devices with the internet. In the textile printing and dyeing industry, the internet of things technology is widely applied to monitoring and management of production lines. The internet of things equipment such as a sensor, an intelligent terminal, a controller and the like can collect various data in the production process in real time, such as temperature, humidity, pressure, flow and the like, and basic data support is provided for monitoring and management of the production line.
At present, an online monitoring system of a printing and dyeing production line based on the Internet of things needs to process a large amount of real-time data, including data acquired by various sensors, equipment running state data and the like. In the existing monitoring schemes, a plurality of sensors are arranged on printing and dyeing equipment, and the sensors can only measure monitoring data at a certain module of the equipment, so that the whole state of the whole equipment is difficult to monitor.
Disclosure of Invention
In order to improve the overall monitoring of the equipment of the printing and dyeing production line and improve the monitoring effect of the equipment, the application provides an online monitoring method and an online monitoring system of the printing and dyeing production line based on the Internet of things, which are beneficial to ensuring the quality and the efficiency of production.
In a first aspect, the application provides an online monitoring method for a printing and dyeing production line based on the Internet of things, which adopts the following technical scheme:
an online monitoring method of a printing and dyeing production line based on the Internet of things comprises the following steps:
Acquiring overall temperature data of the printing and dyeing equipment based on a temperature sensor on the mobile monitoring equipment;
calculating a temperature gain value according to the whole temperature data;
acquiring the whole humidity data of the printing and dyeing equipment based on a humidity sensor on the mobile monitoring equipment;
according to the whole humidity data, calculating a humidity gain value;
obtaining liquid level data of dye of the printing and dyeing equipment based on a liquid level measurement sensor on the mobile monitoring equipment;
According to the liquid level data, carrying out spectrum analysis on the liquid level data to obtain a plurality of liquid level frequencies, calculating liquid level power spectral density corresponding to the liquid level frequencies, and calculating a liquid level power spectral density average value;
acquiring the height data of the printing and dyeing cloth transmitted on the printing and dyeing equipment based on a distance sensor on the mobile monitoring equipment;
According to the height data, carrying out frequency spectrum analysis on the height data to obtain a plurality of height frequencies, calculating the height power spectral density corresponding to the height frequencies, and calculating the average value of the height power spectral density;
Calculating a state evaluation value of the printing and dyeing equipment by using a weighted average algorithm according to the temperature gain value, the humidity gain value, the liquid level power spectral density average value and the height power spectral density average value;
state evaluation value = w1×temperature gain value + w2×humidity gain value + w3×liquid level power spectral density average + w4×height power spectral density average; wherein the weight of the temperature gain value is w1; the weight of the humidity gain value is w2; the weight of the average value of the liquid level power spectrum density is w3; the weight of the high power spectrum density average value is w4; and w1+w2+ w3+w4=1; the temperature gain value, the humidity gain value, the liquid level power spectral density average value and the height power spectral density average value are all dimensionless calculated;
And triggering an alarm mechanism if the state evaluation value exceeds an evaluation threshold value.
By adopting the technical scheme, whether the equipment is in a normal running state is judged by arranging the sensor on the mobile monitoring equipment, monitoring the whole temperature and humidity of the printing and dyeing equipment in the moving process and monitoring the dye liquid level of the printing and dyeing equipment and the height of the cloth in the conveying process; and finally, calculating the monitored data to obtain a state evaluation value, and alarming if the state evaluation value exceeds a threshold value. Further, normalization or normalization processing of the data is considered to ensure that data of different dimensions and ranges can participate fairly in the state evaluation, and thus dimensionless calculation is considered.
Optionally, the method further comprises:
identifying device information of the printing and dyeing device;
acquiring the current service life Y and the reference service life Yref of the current printing and dyeing equipment according to the equipment information;
according to the service life Y of the printing and dyeing equipment, the weight w3 of the average value of the liquid level power spectral density is adjusted in a positive correlation mode, and the shorter the service life Y is, the smaller the weight w3 of the average value of the liquid level power spectral density is; the longer the service life, the greater the weight w3 of the average value of the liquid level power spectral density;
w3' =10× (w3×y/Yref) × (w1+w2+w3) +w4)/[ w1+w2+ (w3×Y/Yref) +w4]; wherein w3' is the adjusted weight.
By adopting the technical scheme, if the printing and dyeing equipment is used for a long time, the probability of abnormality of the printing and dyeing equipment is increased, the weight corresponding to the average value of the liquid level power spectrum density is increased, the importance of the liquid level data is improved, and the weight of one or more of w2, w3 and w4 is reduced.
Optionally, the method further comprises:
identifying device information of the printing and dyeing device;
acquiring the maintenance or replacement quantity of the parts of the printing and dyeing equipment currently according to the equipment information;
Obtaining the total number of maintenance or replacement parts on the total printing and dyeing equipment;
according to the proportion of the number of parts maintained or replaced on the current printing and dyeing equipment to the total number of parts maintained or replaced on the total printing and dyeing equipment, the weight w3 of the average value of the liquid level power spectrum density is adjusted in an opposite relation mode; the larger the ratio, the smaller the weight w3; the smaller the ratio, the greater the weight w 3.
By adopting the technical scheme, in practical application, the data of the maintenance or replacement parts needs to be updated regularly so as to ensure the accuracy of weight adjustment. The weight of the average value of the liquid level power spectral density is thus adjusted in an inversely correlated manner by the repair or replacement of the printing and dyeing installation parts.
Optionally, the method further comprises:
identifying equipment information of each printing and dyeing equipment;
Acquiring the current service life of the printing and dyeing equipment and the interval time of the last maintenance;
according to the service life of a plurality of printing and dyeing equipment and the interval time of last maintenance, the moving path of the mobile monitoring equipment is adjusted: the shorter the interval time of the last maintenance is, the fewer the monitoring times are; the longer the life, the greater the number of monitoring.
By adopting the technical scheme, the equipment with shorter maintenance interval time at last time is considered to be stable in current state, and monitoring times can be properly reduced, so that resources are saved and unnecessary interference is reduced. Whereas for longer life devices the risk of failure or performance degradation may be higher, thus requiring increased monitoring times in order to find potential problems in time.
Optionally, the method further comprises:
According to the temperature data, adjusting the moving path of the mobile monitoring equipment: when the temperature gain value exceeds a temperature threshold value, a first mobilizing instruction is sent out, so that the mobile monitoring equipment moves to the current printing and dyeing equipment, and the monitoring frequency of the current printing and dyeing equipment is increased;
According to the humidity data, adjusting the moving path of the mobile monitoring equipment: and when the humidity gain value exceeds the humidity threshold value, a second mobilizing instruction is sent out, so that the mobile monitoring equipment moves to the current printing and dyeing equipment, and the monitoring frequency of the current printing and dyeing equipment is increased.
By adopting the technical scheme, as the monitoring state of the mobile monitoring equipment is that the data of a plurality of dimensions are acquired, namely equipment for starting to patrol the next sequence and calculating while walking, when the temperature abnormality occurs, new sensor data are acquired again, so that the accuracy of the data is further ensured. When the temperature gain value of a certain piece of printing and dyeing equipment exceeds a temperature threshold value, the equipment is considered to have overheat risk or temperature control problem. The mobile monitoring device is immediately moved to the printing and dyeing device for more detailed monitoring and inspection. Meanwhile, the monitoring frequency of the printing and dyeing equipment is increased so as to track the temperature change condition of the printing and dyeing equipment in real time; when the humidity gain value of a certain piece of printing and dyeing equipment exceeds the humidity threshold value, the equipment is considered to have the problem of excessive humidity or humidity control. The mobile monitoring device is also immediately moved to the printing and dyeing device for detailed monitoring and inspection. Also, the frequency of monitoring the printing and dyeing equipment is increased to ensure that the humidity problem is found and solved in time. If a certain device has the condition that the temperature and humidity gain values exceed the threshold value at the same time, the device should be preferentially processed and take urgent measures into consideration.
Optionally, the method further comprises:
deploying a single mobile monitoring device on a printing and dyeing production line;
Based on inspection monitoring of a single mobile monitoring device, if a frequency spectrum which is located outside a set frequency spectrum range exists in the liquid level power spectrum density of the printing and dyeing device at present, a third mobilizing instruction is sent out and used for changing the moving path of the mobile monitoring device in real time: and the mobile monitoring equipment is used for moving to the next printing and dyeing equipment in the moving path after acquiring the monitoring data of the current printing and dyeing equipment in the monitoring process.
By adopting the technical scheme, the moving path and the monitoring frequency of the mobile monitoring equipment are dynamically optimized. The method ensures that the high-risk areas and the key equipment are monitored more frequently, and avoids wasting resources in the low-risk areas; because the calculation needs to be time-consuming, especially for a plurality of arrays, or more printing and dyeing equipment, or when the data volume to be monitored is larger, the mobile monitoring equipment starts to monitor the next printing and dyeing equipment, and the calculation time is completed in the path to the next printing and dyeing equipment, so that the calculation time is saved, and the monitoring efficiency is improved.
Optionally, the method further comprises:
disposing a plurality of mobile monitoring devices on a printing and dyeing production line;
Based on the inspection monitoring of a plurality of mobile monitoring devices, if one or more of the whole temperature data, the whole humidity data, the liquid level data and the height data of the printing and dyeing device monitored by the current mobile monitoring device are larger than a set threshold value in a set time period, the current mobile monitoring device is judged to be an abnormal mobile device, and the monitored data is judged to be abnormal data; a fourth mobilizing instruction is sent out to call the mobile monitoring equipment of the companion;
Fusing the moving path of the current abnormal mobile equipment into the moving path of the companion mobile monitoring equipment; the temperature gain value, the humidity gain value, the liquid level power spectral density average value and the height power spectral density average value are average values after being monitored by a plurality of mobile monitoring devices.
By adopting the technical scheme, for the monitoring of a plurality of printing and dyeing equipment, a single mobile monitoring device may not be enough, so that a plurality of mobile monitoring devices can monitor according to different planning paths at the same time, so as to meet actual monitoring requirements. In the monitoring process, if an abnormal condition occurs in a certain mobile monitoring device, cooperative monitoring of other mobile monitoring devices of peers is needed, so that the abnormal overall data monitoring caused by the abnormal condition of the mobile monitoring device is reduced, and the accuracy of data monitoring is guaranteed.
Optionally, the method for calling the mobile monitoring device of the peer comprises the following steps:
In a set time period, when a plurality of monitored data are judged to be abnormal data, calling the mobile monitoring equipment of the companion in sequence according to the type of the monitored data;
wherein, the data priority of the monitoring is set as follows: the priority corresponding to the whole temperature data is greater than the priority corresponding to the whole humidity data is greater than the priority corresponding to the liquid level data is greater than the priority corresponding to the height data.
By adopting the technical scheme, if the overall temperature data with the highest priority has abnormality, the companion device is immediately called, and the type and the position of the abnormality are described. If the overall temperature data is normal, but the overall humidity data is abnormal, the companion device is next called to handle the humidity abnormality. And so on until all types of anomaly data are scheduled for further monitoring or processing by the companion mobile monitoring device. When a plurality of monitoring data are abnormal, the system can rapidly and orderly call resources, and the most important abnormal conditions are preferentially processed, so that the stability and the efficiency of a production line are improved.
Optionally, the method further comprises:
According to the quantity of the abnormal devices or the abnormal data, the quantity of the mobile monitoring devices is adjusted in a positive correlation mode, and the quantity of the abnormal devices or the abnormal data is larger as the quantity of the abnormal devices or the abnormal data is larger; the smaller the amount of the abnormal devices or abnormal data, the smaller the number of the mobile monitoring devices;
the mobile monitoring device is an unmanned aerial vehicle or a tracking trolley and is used for acquiring and processing monitored data.
Through adopting above-mentioned technical scheme, the quantity of dynamic adjustment mobile monitoring equipment ensures to increase the monitoring dynamics when needs, reduces resource consumption when the condition improves to improve monitoring efficiency and the overall stability of production line.
In a second aspect, the application provides an online monitoring system of a printing and dyeing production line based on the Internet of things, which adopts the following technical scheme:
the online monitoring system of the printing and dyeing production line based on the Internet of things comprises a processor, wherein a program of the online monitoring method of the printing and dyeing production line based on the Internet of things is operated in the processor.
In summary, the present application includes at least one of the following beneficial technical effects:
According to the quantity of abnormal equipment or abnormal data, the quantity of the mobile monitoring equipment is regulated in a positive correlation manner, so that the monitoring force can be rapidly increased in an abnormal high-incidence period, and the overall response speed and the inspection efficiency are improved. By calling the peer mobile monitoring devices in sequence according to the priority of the data, it is ensured that the abnormal data with high priority is responded and processed more quickly. By dynamically adjusting the number of the mobile monitoring devices, the waste and idling of resources are avoided. The number of equipment is reduced when the abnormality is less, so that the energy and labor cost can be saved; and when the abnormality is increased, the number of the devices is increased, so that the timely completion of the monitoring task can be ensured. Timely anomaly monitoring and handling is helpful for preventing potential production accidents and reducing the influence of equipment faults on a production line. By increasing the number of monitoring devices and improving the response speed, the problems can be found and solved earlier, thereby ensuring the stable operation of the production line.
Drawings
Fig. 1 is a step diagram of an online monitoring method of a printing and dyeing production line based on the internet of things.
Fig. 2 is a step diagram of adjusting the weight w3 according to the service life Y of the printing apparatus.
Fig. 3 is a step diagram of adjusting the weight w3 according to the number of repairs or replacements of parts of the printing apparatus.
Fig. 4 is a step diagram of adjusting the weight w3 according to the current service life of the printing apparatus and the interval time of the last maintenance.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings.
In the description of the present specification, reference to the terms "certain embodiments," "one embodiment," "some embodiments," "an exemplary embodiment," "an example," "a particular example," or "some examples" means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The embodiment of the application discloses an online monitoring method of a printing and dyeing production line based on the Internet of things, which refers to fig. 1 and comprises the following steps:
Acquiring overall temperature data of the printing and dyeing equipment based on a temperature sensor on the mobile monitoring equipment; the mobile monitoring device is an unmanned plane or a tracking trolley and is used for acquiring and processing monitored data. The unmanned aerial vehicle can carry various devices such as high-definition cameras, infrared sensors, radars and the like. The tracking trolley is good at accurately monitoring the ground, and can navigate to a specific area along a preset path or autonomously to perform fine data acquisition and processing. The small and flexible design is convenient for shuttling in complex environments, and the accuracy and the integrity of data are ensured. The whole temperature data, such as unmanned aerial vehicle is wound and flown above the printing and dyeing equipment, or is laterally above, the surrounding environment of the printing and dyeing equipment is subjected to multi-point temperature measurement through a carried sensor, and finally, an average value is calculated, or different weighting values are set according to different orientations, so that weighted average calculation is performed; for example, the power direction may be hotter, the device may be located away from the power source, and the temperature may be relatively higher. Or the monitoring of the heat distribution of the printing and dyeing equipment is realized by shooting a heat energy diagram, the heat quantity value is calculated by an image recognition technology, and finally, the corresponding temperature value is sent out by using a table lookup.
Calculating a temperature gain value according to the overall temperature data; temperature gain value = current monitored bulk temperature data-last monitored bulk temperature data.
Acquiring the whole humidity data of the printing and dyeing equipment based on a humidity sensor on the mobile monitoring equipment; the unmanned plane can be provided with a humidity sensor, a printing and dyeing equipment is wound to measure humidity, and a mode of averaging is finally adopted, or different weighting values are set according to different directions to carry out weighted average calculation; for example, the humidity is higher in the direction of the printed cloth, the temperature is lower in the position of the equipment far away from the printed cloth.
Calculating a humidity gain value according to the overall humidity data; humidity gain value = current monitored global humidity data-last monitored global humidity data.
And obtaining liquid level data of the dye of the printing and dyeing equipment based on a liquid level measurement sensor on the mobile monitoring equipment. There are a variety of dyeing apparatuses, such as continuous pad dyeing machines, jig dyeing machines, overflow dyeing machines, jet dyeing machines, garment dyeing apparatuses, or other dyeing apparatuses. The liquid level of the dye can be measured by a sensor for measuring the distance or can be obtained by means of photographing identification, and particularly is different according to different storage forms of different printing and dyeing liquids in the printing and dyeing equipment.
According to the liquid level data, performing spectrum analysis on the liquid level data by using Fast Fourier Transform (FFT) to obtain a plurality of liquid level frequencies, calculating the frequency spectrum by using the Fast Fourier Transform (FFT), further calculating the liquid level power spectral density corresponding to the liquid level frequencies, and calculating the liquid level power spectral density average value. Thereby, the stability and fluctuation of the data are evaluated according to the height change condition of the liquid level, and the running state of the production line is deduced
And obtaining the height data of the printing and dyeing cloth transmitted on the printing and dyeing equipment based on the distance sensor on the mobile monitoring equipment. Distance sensor can be carried through unmanned aerial vehicle, and printing and dyeing equipment is like to the jig dyeing machine, and the in-process of cloth at the printing and dyeing can be around establishing on the live-rollers, realizes the transmission and the winding of cloth. By monitoring the height of the cloth, whether the conveying of the cloth is abnormal or not is judged.
According to the height data, performing spectrum analysis on the height data by using Fast Fourier Transform (FFT) to obtain a plurality of height frequencies, calculating the frequency spectrum by using Fast Fourier Transform (FFT), further calculating the height power spectral density corresponding to the height frequencies, and calculating the average value of the height power spectral density. Therefore, the stability and fluctuation condition of the data are evaluated according to the height change condition of the cloth, and the running state of the production line is deduced.
Calculating a state evaluation value of the printing and dyeing equipment by using a weighted average algorithm according to the temperature gain value, the humidity gain value, the liquid level power spectral density average value and the height power spectral density average value; the information of multiple dimensions is considered, so that the actual state of the equipment can be more comprehensively reflected.
State evaluation value = w1×temperature gain value + w2×humidity gain value + w3×liquid level power spectral density average + w4×height power spectral density average; wherein the weight of the temperature gain value is w1; the weight of the humidity gain value is w2; the weight of the average value of the liquid level power spectrum density is w3; the weight of the high power spectrum density average value is w4; and w1+w2+ w3+w4=1; the temperature gain value, the humidity gain value, the liquid level power spectral density average value and the height power spectral density average value are all dimensionless calculation.
For example, the following values and weights are set:
temperature gain value (dimensionless): 0.8;
humidity gain value (dimensionless): 0.6;
liquid level power spectral density average (dimensionless): 0.5;
high power spectral density average (dimensionless): 0.7;
Weight distribution:
w1 (weight of temperature gain value): 0.3;
w2 (weight of humidity gain value): 0.2;
w3 (weight of liquid level power spectral density average): 0.25;
w4 (weight of the high power spectral density average): 0.25;
the weighted average algorithm calculates the state estimate = 0.24+0.12+0.125+0.175 = 0.66.
And triggering an alarm mechanism if the state evaluation value exceeds the evaluation threshold value. For example, the evaluation threshold is set to 0.7 and the previously calculated state evaluation value is 0.66 (as previously shown), then the alarm mechanism is not triggered at this time because the state evaluation value is below the threshold. But if the status assessment value increases to 0.75 (or any other value exceeding 0.7), an alarm mechanism is triggered.
The alarm mechanism may take the following measures: and sending the alarm information to related personnel responsible for equipment maintenance, operation or management in a mode of short messages, mails, monitoring systems and the like. And according to the alarm information, the equipment is subjected to detailed inspection to determine the specific reason causing the exceeding of the state evaluation value. And according to the checking result, adopting corresponding measures to repair the problem, preventing the fault from further developing, or adjusting the operation parameters to improve the equipment state. Alarm events, troubleshooting procedures, and countermeasures are documented for subsequent analysis and improvement. At the same time, these data can also be used to optimize the evaluation model and the threshold settings. The status assessment system and alarm mechanism of the device are reviewed regularly to ensure its effectiveness and accuracy. Depending on the change in equipment performance and new operating experience, adjustments to the evaluation model and threshold values may be required.
The method comprises the steps that a sensor is arranged on the mobile monitoring equipment, the whole temperature and the humidity of the printing and dyeing equipment are monitored in the moving process, and the dye liquid level of the printing and dyeing equipment and the height of the cloth in the conveying process are monitored to judge whether the equipment is in a normal running state; and finally, calculating the monitored data to obtain a state evaluation value, and alarming if the state evaluation value exceeds a threshold value. Further, normalization or normalization processing of the data is considered to ensure that data of different dimensions and ranges can participate fairly in the state evaluation, and thus dimensionless calculation is considered.
Referring to fig. 2, method one of adjusting weights:
Identifying device information of the printing and dyeing device; device information including, but not limited to, device model number, serial number, etc. Specifically, the unmanned aerial vehicle can be used for matching corresponding equipment information and the like from the system in a mode of identifying an electronic tag or a bar code on the equipment through a radio frequency technology and the like.
Acquiring the current service life Y and the reference service life Yref of the current printing and dyeing equipment according to the equipment information; for example, the current printing equipment has a service life of 2 years and a reference service life of 20 years.
According to the service life Y of the printing and dyeing equipment, the weight w3 of the average value of the liquid level power spectral density is regulated in a positive correlation mode, and the shorter the service life Y is, the smaller the weight w3 of the average value of the liquid level power spectral density is; the longer the life, the greater the weight w3 of the average of the liquid level power spectral density.
W3' =10× (w3×y/Yref) × (w1+w2+w3) +w4)/[ w1+w2+ (w3×Y/Yref) +w4]; wherein w3' is the adjusted weight, ensuring that the sum of all weights is still 1.
For example, initial weights: w1=0.2, w2=0.3, w3=0.2, w4=0.3. When the service life of the current printing and dyeing equipment is 2 years, w3' is calculated to be 0.123. When the service life of the current printing and dyeing equipment is 3 years, w3' is 0.36.
If the printing and dyeing equipment is used for a longer time, the probability of abnormality of the printing and dyeing equipment is increased, the weight corresponding to the average value of the liquid level power spectrum density is increased, the importance of the liquid level data is improved, and the weight of one or more of w2, w3 and w4 is reduced.
Referring to fig. 3, method two of adjusting weights:
Identifying device information of the printing and dyeing device; likewise, device information, including but not limited to device model number, serial number, etc. Specifically, the unmanned aerial vehicle can be used for matching corresponding equipment information and the like from the system in a mode of identifying an electronic tag or a bar code on the equipment through a radio frequency technology and the like.
Acquiring the maintenance or replacement quantity of the parts of the current printing and dyeing equipment according to the equipment information; the total number of repairs or replacements of the parts on the total printing and dyeing equipment is obtained.
For example, 2 parts are replaced or maintained in the current printing and dyeing equipment, and the total amount of replacement or maintenance of the parts on the total printing and dyeing equipment is 10 in the whole production line.
According to the proportion of the number of parts maintained or replaced on the current printing and dyeing equipment to the total number of parts maintained or replaced on the total printing and dyeing equipment, the weight w3 of the average value of the liquid level power spectrum density is adjusted in an opposite relation mode; the larger the ratio, the smaller the weight w3; the smaller the ratio, the greater the weight w 3.
For example, when 2 parts are replaced or maintained in the current printing and dyeing apparatus, the ratio is 2/10=0.2, w3=0.3; when 1 part is replaced or maintained in the current printing and dyeing equipment, and the proportion is 1/10=0.1, w3=0.4.
In practical applications, the data for repairing or replacing the parts needs to be updated periodically to ensure the accuracy of weight adjustment. The weight of the average value of the liquid level power spectral density is thus adjusted in an inversely correlated manner by the repair or replacement of the printing and dyeing installation parts.
Referring to fig. 4, in order to flexibly adjust the frequency of monitoring to be more suitable for the requirement of monitoring, the method further includes:
Identifying equipment information of each printing and dyeing equipment; likewise, device information, including but not limited to device model number, serial number, etc. Specifically, the unmanned aerial vehicle can be used for matching corresponding equipment information and the like from the system in a mode of identifying an electronic tag or a bar code on the equipment through a radio frequency technology and the like.
Acquiring the current service life of the current printing and dyeing equipment and the interval time of the last maintenance; for example, the current equipment has a service life of 5 years, and the last maintenance interval is 2 months.
According to the service life of a plurality of printing and dyeing equipment and the interval time of last maintenance, the moving path of the mobile monitoring equipment is adjusted: the shorter the interval time of the last maintenance is, the fewer the monitoring times are; the longer the life, the greater the number of monitoring. For example, when the interval time of the last maintenance is 2 months, the monitoring times are once per day by taking half a year as the judging node with the interval time of the last maintenance; when the interval time of the last maintenance is 8 months, the monitoring times are once every half day; the number of times of monitoring is one time in half a day when the service life is 5 years, and the number of times of monitoring is one time per day when the service life is 2 years. The specific time can be set according to the actual use requirements, which is assumed by way of example.
For the equipment with shorter maintenance interval time, the current state of the equipment is considered to be stable, and the monitoring times can be properly reduced, so that resources are saved and unnecessary interference is reduced. Whereas for longer life devices the risk of failure or performance degradation may be higher, thus requiring increased monitoring times in order to find potential problems in time.
In order to flexibly adjust the monitoring frequency to be more suitable for the monitoring requirement, the method further comprises the following steps:
Dimension one: according to the temperature data, adjusting a moving path of the mobile monitoring device: when the temperature gain value exceeds the temperature threshold value, a first mobilizing instruction is sent out, so that the mobile monitoring equipment moves to the current printing and dyeing equipment, and the monitoring frequency of the current printing and dyeing equipment is increased. For example, currently monitored printing and dyeing equipment operates steadily after the last maintenance. Temperature threshold: set to 5 ℃ per hour, i.e. if the temperature gain value (the difference between the current temperature and the average temperature of the previous hour divided by the time) exceeds 5 ℃ per hour, a significant change in temperature is considered.
Dimension two: according to the humidity data, adjusting a moving path of the mobile monitoring device: and when the humidity gain value exceeds the humidity threshold value, a second mobilizing instruction is sent out, so that the mobile monitoring equipment moves to the current printing and dyeing equipment, and the monitoring frequency of the current printing and dyeing equipment is increased.
For example, humidity threshold: set to 5% rh/hour, i.e. if the humidity gain value (the difference between the current humidity and the average humidity of the previous hour divided by the time) exceeds 5% rh/hour, a significant change in humidity is considered.
For example, time 10:00: the monitoring center receives the data and displays that the temperature gain value around the printing and dyeing equipment A is 4 ℃ per hour and the humidity gain value is 3%RH per hour. Both values do not exceed the respective threshold values, so the mobile monitoring device maintains its current path and the monitoring frequency of the printing and dyeing device a remains normal.
Time 11:00: due to external weather changes, the monitoring center receives new data, showing that the temperature gain value around the printing and dyeing equipment a suddenly rises to 7 ℃ per hour, and the humidity gain value also increases to 6% rh per hour. At this point, the gain values for both temperature and humidity exceed their respective thresholds.
The first mobilization command is triggered immediately (due to the exceeding of the temperature gain value) indicating that the mobile monitoring device is better toward the printing device a. After receiving the instruction, the mobile monitoring equipment adjusts the path of the mobile monitoring equipment to reach the printing and dyeing equipment A as soon as possible.
Because the monitoring state of the mobile monitoring equipment is that the data of a plurality of dimensions are acquired, namely equipment for starting to inspect the next sequence, and calculation is performed while walking, when temperature abnormality occurs, new sensor data are acquired again, so that the accuracy of the data is further ensured. When the temperature gain value of a certain piece of printing and dyeing equipment exceeds a temperature threshold value, the equipment is considered to have overheat risk or temperature control problem. The mobile monitoring device is immediately moved to the printing and dyeing device for more detailed monitoring and inspection. Meanwhile, the monitoring frequency of the printing and dyeing equipment is increased so as to track the temperature change condition of the printing and dyeing equipment in real time; when the humidity gain value of a certain piece of printing and dyeing equipment exceeds the humidity threshold value, the equipment is considered to have the problem of excessive humidity or humidity control. The mobile monitoring device is also immediately moved to the printing and dyeing device for detailed monitoring and inspection. Also, the frequency of monitoring the printing and dyeing equipment is increased to ensure that the humidity problem is found and solved in time. If a certain device has the condition that the temperature and humidity gain values exceed the threshold value at the same time, the device should be preferentially processed and take urgent measures into consideration.
The method further comprises the steps of:
Deploying a single mobile monitoring device on a printing and dyeing production line; under the assumption that the number of printing and dyeing equipment in a workshop is small, only one mobile monitoring equipment, such as an unmanned aerial vehicle monitoring equipment, can be deployed, and flying is performed according to a set planned path.
Based on inspection monitoring of a single mobile monitoring device, if a frequency spectrum which is located outside a set frequency spectrum range exists in the liquid level power spectrum density of the current printing and dyeing device, a third mobilizing instruction is sent out and used for changing the moving path of the mobile monitoring device in real time: and the mobile monitoring equipment is used for acquiring the monitoring data of the current printing and dyeing equipment in the monitoring process, and then moving to the next printing and dyeing equipment in the moving path. During the monitoring process, the frequency spectrum outside the set frequency spectrum range is found in the liquid level power spectrum density of the current printing and dyeing equipment, which indicates that abnormal frequency components exist in the liquid level fluctuation, and the abnormal frequency components can be caused by various reasons, including but not limited to equipment failure, improper operation, external environment change or change of liquid property and the like.
And dynamically optimizing the moving path and the monitoring frequency of the mobile monitoring equipment. The method ensures that the high-risk areas and the key equipment are monitored more frequently, and avoids wasting resources in the low-risk areas; because the calculation needs to be time-consuming, especially for a plurality of arrays, or more printing and dyeing equipment, or when the data volume to be monitored is larger, the mobile monitoring equipment starts to monitor the next printing and dyeing equipment, and the calculation time is completed in the path to the next printing and dyeing equipment, so that the calculation time is saved, and the monitoring efficiency is improved.
In the actual monitoring process, besides the printing and dyeing equipment needs to be monitored, the state of the mobile monitoring equipment also needs to be monitored so as not to influence the accuracy of data monitoring, and the method further comprises the following steps:
Disposing a plurality of mobile monitoring devices on a printing and dyeing production line; if the number of printing and dyeing equipment in the workshop is relatively large, only a plurality of mobile monitoring equipment, such as a plurality of unmanned aerial vehicle monitoring equipment, can be deployed, so that all the printing and dyeing equipment can be covered. Each unmanned aerial vehicle is initialized and set, and the initialization setting comprises presetting of a routing inspection path, monitoring parameters (temperature, humidity, liquid level, height and the like), a data discrete value threshold value, a communication protocol and the like.
Based on the inspection monitoring of a plurality of mobile monitoring devices, if one or more of the whole temperature data, the whole humidity data, the liquid level data and the height data of the printing and dyeing device monitored by the current mobile monitoring device are in a set time period, the discrete value of the corresponding data is larger than a set threshold value; the current mobile monitoring device is judged to be an abnormal mobile device, and the monitored data is judged to be abnormal data; and sending a fourth mobilizing instruction, calling the mobile monitoring equipment of the companion in a wireless communication mode, and carrying out secondary monitoring on the printing and dyeing equipment corresponding to the current abnormal data by the mobile monitoring equipment of the companion so as to check whether the mobile monitoring equipment has a problem or not, thereby ensuring the accuracy of a monitoring result.
Fusing the moving path of the current abnormal mobile equipment into the moving path of the companion mobile monitoring equipment; the temperature gain value, the humidity gain value, the liquid level power spectral density average value and the height power spectral density average value are average values after being monitored by a plurality of mobile monitoring devices. And the companion unmanned aerial vehicle receiving the calling instruction adjusts the self-moving path according to the current position and the task priority, and fuses the patrol path or the key monitoring point of the abnormal mobile equipment into the patrol plan of the companion unmanned aerial vehicle.
For the monitoring of multiple printing and dyeing devices, a single mobile monitoring device may not be sufficient, so that multiple mobile monitoring devices can monitor according to different planned paths at the same time to meet actual monitoring requirements. In the monitoring process, if an abnormal condition occurs in a certain mobile monitoring device, cooperative monitoring of other mobile monitoring devices of peers is needed, so that the abnormal overall data monitoring caused by the abnormal condition of the mobile monitoring device is reduced, and the accuracy of data monitoring is guaranteed.
The method for calling the mobile monitoring equipment of the companion comprises the following steps:
And in the set time period, when a plurality of monitored data are judged to be abnormal data, calling the mobile monitoring equipment of the companion in sequence according to the type of the monitored data. Wherein, the data priority of the monitoring is set as follows: the priority corresponding to the whole temperature data is greater than the priority corresponding to the whole humidity data is greater than the priority corresponding to the liquid level data is greater than the priority corresponding to the height data. The priority represents the emergency degree of the event, the temperature is taken as the highest priority, and in the printing and dyeing process, the too high or the too low temperature can have serious influence on the quality of printing and dyeing equipment and products, and the temperature has great influence on the quality of printing and dyeing, so the temperature is taken as the highest priority. Secondly, humidity factors, humidity has important influence on chemical reaction and product quality in the printing and dyeing process. Level anomalies affect the proper operation of the plant and the uniformity of the product, but generally do not immediately lead to serious consequences, and are therefore a third priority. The height data is used to monitor the operating state of the equipment, but its anomalies have relatively little direct impact on the production line.
After issuing the call instruction, the system should wait for the response of the companion device. If the companion device accepts the call and goes to process the exception, the system will continue to monitor and process other exception data; if the companion device cannot respond in time or cannot handle the exception, the system should continue to call the next priority companion device or take other emergency action.
The called companion device should arrive at the abnormal site as soon as possible and work in conjunction with the original monitoring device to re-monitor and evaluate the abnormal situation.
For the overall temperature data with the highest priority, if an abnormality exists, the companion device is immediately called and the abnormality type and location are specified. If the overall temperature data is normal, but the overall humidity data is abnormal, the companion device is next called to handle the humidity abnormality. And so on until all types of anomaly data are scheduled for further monitoring or processing by the companion mobile monitoring device. When a plurality of monitoring data are abnormal, the system can rapidly and orderly call resources, and the most important abnormal conditions are preferentially processed, so that the stability and the efficiency of a production line are improved.
The method further comprises the steps of:
In the set time period, according to the quantity of the abnormal equipment or abnormal data, the quantity of the mobile monitoring equipment is regulated in a positive correlation way, and the more the quantity of the abnormal equipment or abnormal data is, the more the quantity of the mobile monitoring equipment is; the smaller the amount of abnormal devices or abnormal data, the smaller the number of mobile monitoring devices. Different abnormal total quantity thresholds are set according to the actual conditions and monitoring requirements of the production line, and corresponding regulation rules are formulated. For example, when the total quantity of the anomalies exceeds a certain low threshold value, adding a mobile monitoring device; and when the total quantity of the abnormality falls below a certain high threshold value, reducing one mobile monitoring device. The system automatically or manually triggers an adjusting mechanism according to the abnormal total amount counted in real time or periodically to dynamically adjust the number of the mobile monitoring devices. Such adjustments should be flexible and capable of responding quickly to changes in the production line.
The quantity of mobile monitoring equipment is dynamically regulated, so that the monitoring force is increased when required, and the resource consumption is reduced when the condition is improved, thereby improving the monitoring efficiency and the overall stability of the production line.
The embodiment of the application also discloses an online monitoring system of the printing and dyeing production line based on the Internet of things, which comprises a processor, wherein the processor is internally provided with a program of any online monitoring method of the printing and dyeing production line based on the Internet of things.
While embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (9)
1. The online monitoring method for the printing and dyeing production line based on the Internet of things is characterized by comprising the following steps of:
Acquiring overall temperature data of the printing and dyeing equipment based on a temperature sensor on the mobile monitoring equipment;
calculating a temperature gain value according to the whole temperature data;
acquiring the whole humidity data of the printing and dyeing equipment based on a humidity sensor on the mobile monitoring equipment;
according to the whole humidity data, calculating a humidity gain value;
obtaining liquid level data of dye of the printing and dyeing equipment based on a liquid level measurement sensor on the mobile monitoring equipment;
According to the liquid level data, carrying out spectrum analysis on the liquid level data to obtain a plurality of liquid level frequencies, calculating liquid level power spectral density corresponding to the liquid level frequencies, and calculating a liquid level power spectral density average value;
acquiring the height data of the printing and dyeing cloth transmitted on the printing and dyeing equipment based on a distance sensor on the mobile monitoring equipment;
According to the height data, carrying out frequency spectrum analysis on the height data to obtain a plurality of height frequencies, calculating the height power spectral density corresponding to the height frequencies, and calculating the average value of the height power spectral density;
Calculating a state evaluation value of the printing and dyeing equipment by using a weighted average algorithm according to the temperature gain value, the humidity gain value, the liquid level power spectral density average value and the height power spectral density average value;
state evaluation value = w1×temperature gain value + w2×humidity gain value + w3×liquid level power spectral density average + w4×height power spectral density average; wherein the weight of the temperature gain value is w1; the weight of the humidity gain value is w2; the weight of the average value of the liquid level power spectrum density is w3; the weight of the high power spectrum density average value is w4; and w1+w2+ w3+w4=1; the temperature gain value, the humidity gain value, the liquid level power spectral density average value and the height power spectral density average value are all dimensionless calculated;
triggering an alarm mechanism if the state evaluation value exceeds an evaluation threshold value;
The method further comprises the steps of:
identifying device information of the printing and dyeing device;
acquiring the current service life Y and the reference service life Yref of the current printing and dyeing equipment according to the equipment information;
according to the service life Y of the printing and dyeing equipment, the weight w3 of the average value of the liquid level power spectral density is adjusted in a positive correlation mode, and the shorter the service life Y is, the smaller the weight w3 of the average value of the liquid level power spectral density is; the longer the service life, the greater the weight w3 of the average value of the liquid level power spectral density;
w3' =10× (w3×y/Yref) × (w1+w2+w3) +w4)/[ w1+w2+ (w3×Y/Yref) +w4]; wherein w3' is the adjusted weight.
2. The online monitoring method of the printing and dyeing production line based on the internet of things according to claim 1, wherein the method further comprises:
identifying device information of the printing and dyeing device;
acquiring the maintenance or replacement quantity of the parts of the printing and dyeing equipment currently according to the equipment information;
Obtaining the total number of maintenance or replacement parts on the total printing and dyeing equipment;
according to the proportion of the number of parts maintained or replaced on the current printing and dyeing equipment to the total number of parts maintained or replaced on the total printing and dyeing equipment, the weight w3 of the average value of the liquid level power spectrum density is adjusted in an opposite relation mode; the larger the ratio, the smaller the weight w3; the smaller the ratio, the greater the weight w 3.
3. The online monitoring method of the printing and dyeing production line based on the internet of things according to claim 2, wherein the method further comprises:
identifying equipment information of each printing and dyeing equipment;
Acquiring the current service life of the printing and dyeing equipment and the interval time of the last maintenance;
according to the service life of a plurality of printing and dyeing equipment and the interval time of last maintenance, the moving path of the mobile monitoring equipment is adjusted: the shorter the interval time of the last maintenance is, the fewer the monitoring times are; the longer the life, the greater the number of monitoring.
4. The online monitoring method of the printing and dyeing production line based on the internet of things according to claim 1, wherein the method further comprises:
According to the temperature data, adjusting the moving path of the mobile monitoring equipment: when the temperature gain value exceeds a temperature threshold value, a first mobilizing instruction is sent out, so that the mobile monitoring equipment moves to the current printing and dyeing equipment, and the monitoring frequency of the current printing and dyeing equipment is increased;
According to the humidity data, adjusting the moving path of the mobile monitoring equipment: and when the humidity gain value exceeds the humidity threshold value, a second mobilizing instruction is sent out, so that the mobile monitoring equipment moves to the current printing and dyeing equipment, and the monitoring frequency of the current printing and dyeing equipment is increased.
5. The online monitoring method of the printing and dyeing production line based on the internet of things according to claim 1, wherein the method further comprises:
deploying a single mobile monitoring device on a printing and dyeing production line;
Based on inspection monitoring of a single mobile monitoring device, if a frequency spectrum which is located outside a set frequency spectrum range exists in the liquid level power spectrum density of the printing and dyeing device at present, a third mobilizing instruction is sent out and used for changing the moving path of the mobile monitoring device in real time: and the mobile monitoring equipment is used for moving to the next printing and dyeing equipment in the moving path after acquiring the monitoring data of the current printing and dyeing equipment in the monitoring process.
6. The online monitoring method of the printing and dyeing production line based on the internet of things according to claim 1, wherein the method further comprises:
disposing a plurality of mobile monitoring devices on a printing and dyeing production line;
Based on the inspection monitoring of a plurality of mobile monitoring devices, if one or more of the whole temperature data, the whole humidity data, the liquid level data and the height data of the printing and dyeing device monitored by the current mobile monitoring device are larger than a set threshold value in a set time period, the current mobile monitoring device is judged to be an abnormal mobile device, and the monitored data is judged to be abnormal data; a fourth mobilizing instruction is sent out to call the mobile monitoring equipment of the companion;
Fusing the moving path of the current abnormal mobile equipment into the moving path of the companion mobile monitoring equipment; the temperature gain value, the humidity gain value, the liquid level power spectral density average value and the height power spectral density average value are average values after being monitored by a plurality of mobile monitoring devices.
7. The online monitoring method of the printing and dyeing production line based on the internet of things according to claim 6, wherein the method for calling the mobile monitoring equipment of the companion comprises the following steps:
In a set time period, when a plurality of monitored data are judged to be abnormal data, calling the mobile monitoring equipment of the companion in sequence according to the type of the monitored data;
wherein, the data priority of the monitoring is set as follows: the priority corresponding to the whole temperature data is greater than the priority corresponding to the whole humidity data is greater than the priority corresponding to the liquid level data is greater than the priority corresponding to the height data.
8. The online monitoring method of the printing and dyeing production line based on the internet of things according to claim 7, wherein the method further comprises:
According to the quantity of abnormal equipment or abnormal data, the quantity of the mobile monitoring equipment is regulated in a positive correlation way, and the more the quantity of the abnormal equipment or the abnormal data is, the more the quantity of the mobile monitoring equipment is; the smaller the amount of the abnormal devices or abnormal data, the smaller the number of the mobile monitoring devices;
the mobile monitoring equipment is an unmanned aerial vehicle or a tracking trolley.
9. An online monitoring system of a printing and dyeing production line based on the internet of things, which is characterized by comprising a processor, wherein a program of the online monitoring method of the printing and dyeing production line based on the internet of things as claimed in any one of claims 1 to 8 is run in the processor.
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