CN105116273A - Insulator on-line monitoring system - Google Patents
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- CN105116273A CN105116273A CN201510537587.4A CN201510537587A CN105116273A CN 105116273 A CN105116273 A CN 105116273A CN 201510537587 A CN201510537587 A CN 201510537587A CN 105116273 A CN105116273 A CN 105116273A
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Abstract
The invention discloses an insulator on-line monitoring system, belonging to the high voltage protection electric appliance technology field. The insulator on-line monitoring system comprises a data collection module, a control module, a communication module and a remote data center; the data collection module is connected to the control module for collecting leakage current, environment humidity, and humidity data of the insulator; the control module is connected to the communication module; the communication module is in wireless connection with the remote data center; the control module performs preliminary current leakage determination and then transmits the data to the remote data center through the communication module; the remote data center performs data processing on received insulator related data by utilizing a wavelet fuzzy neural network model to obtain an insulator contamination degree analysis result. The insulator on-line monitoring system is high in prediction accuracy and high in efficiency and feasibility, and realizes the insulator on-line monitoring and promptly alarms for the insulator faults. Besides, the insulator on-line monitoring system solves the problem that the noise in the insulator leakage current signal is big, which affects the data analysis and monitoring result.
Description
Technical field
The invention belongs to high voltage protective technical field of electric appliances, relate to composite insulator monitoring direction, be specifically related to a kind of insulator on-line monitoring system.
Background technology
Insulator is a kind of special insulation control, can play an important role in overhead transmission line.In one's early years, insulator is used for electric pole, and slowly develop and hung the insulator of a lot of plate-like in one end of high type high-tension bus-bar connection tower, it is made up of glass or pottery usually in order to increase creepage distance, is just insulator.Insulator should not to change the various dynamo-electric stress that causes and losing efficacy due to environment and electric load condition, otherwise insulator would not produce great effect, will damage use and the operation life of whole piece circuit.
The filth such as floating dust is adhered at insulator surface, form path to be punctured by insulator both end voltage, especially in wet weather situation, easily there is flashover electric discharge in dirty insulator, the harm that the hazard ratio of the insulator contamination that filth causes causes because being struck by lightning is larger, and the loss caused is even more serious.According to statistics, insulator contamination accident is only second to thunderbolt in recent years, quantitatively occupies the second of power grid accident, and loss is 9.3 times of lightning strike accident, so the filthy on-line monitoring of insulator seems particularly important.
Summary of the invention
According to above the deficiencies in the prior art, technical matters to be solved by this invention proposes a kind of insulator on-line monitoring system, by gathering the leakage current of insulator, the humidity of environment, humidity data, the data collected being delivered to remote data center utilizes wavelet fuzzy neural network model to carry out data processing, draw insulator contamination degree analyzing result, solve noise in the Leakage Current signal of insulator large, affect the problem of data analysis and on-line monitoring result, there is prediction accuracy high, validity and feasibility are very high, achieve online insulator monitoring, the advantage of timely early warning insulator breakdown.
In order to solve the problems of the technologies described above, the technical solution used in the present invention is: a kind of insulator on-line monitoring system, described insulator on-line monitoring system comprises data acquisition module, control module, communication module and length of run data center, the input end of data acquisition module link control module is used for gathering the leakage current of insulator, the humidity of environment, humidity data, and the data collected are sent in control module, the output terminal of control module connects communication module, communication module wireless connections remote data center, control module carries out, after preliminary Leakage Current judges, the data of data acquisition module are sent to remote data center by communication module, remote data center utilizes wavelet fuzzy neural network model to carry out data processing to the insulator related data received, draw insulator contamination degree analyzing result.
In said system, described data acquisition module comprises temperature sensor, humidity sensor and Leakage Current sensor, humidity sensor gathers the humidity data of tested point insulator, temperature sensor gathers ambient temperature data, Leakage Current sensor gathers the Leakage Current signal data of insulator, temperature sensor, humidity sensor and Leakage Current sensor link control module.Arrange alarm unit in described control module, in alarm unit link control module, differentiate the Leakage Current data in the data acquisition module received, Leakage Current data exceed setting threshold value, and give the alarm signal.Described remote data center comprises receiving element, processor and database, the input end of receiving element connection handling device, the output terminal connection data storehouse of processor, the data that remote data center is sent by receiving element received communication module, the data that the transmission and reception of receiving element connection handling device are arrived are to processor, and processor utilizes wavelet fuzzy neural network model to carry out to the data received the pollution level analysis result that data processing draws insulator.Arrange wavelet fuzzy neural network model in described processor, wavelet fuzzy neural network model has mode identificating ability and carries out denoising to signals and associated noises, and wavelet fuzzy neural network model is hierarchical structure.After described wavelet fuzzy neural network model is set up, carry out model training, model training data from database, the data of model training comprise the insulator related data under the Different periods of data collecting module collected, different filthy state, and after model training, Input Online detects data and exports pollution level analysis result.Described remote data center also comprises display, and display is connected to the output terminal of processor, the pollution level analysis result of video-stream processor.Described remote data center also comprises input block, and input block connection handling device is used for artificial input signal, and the insulator time of day that manual site detects is input in processor by input block and contrasts with the result of prediction.
Beneficial effect of the present invention is: the invention provides a kind of insulator on-line monitoring system, propose based on wavelet fuzzy neural network insulator contamination degree on-line monitoring, by the humidity of the leakage current to insulator, pulse current and environment, relative humidity as the input variable of wavelet fuzzy neural network, through wavelet fuzzy neural network, it is carried out to the Comprehensive Assessment of insulator contamination degree on-line monitoring result.
Accompanying drawing explanation
Below the content expressed by this Figure of description and the mark in figure are briefly described:
Fig. 1 is the principle of work block diagram of the specific embodiment of the present invention;
Fig. 2 is the principle of work block diagram of the remote data center of the specific embodiment of the present invention.
Embodiment
Contrast accompanying drawing below, by the description to embodiment, the specific embodiment of the present invention is as the effect of the mutual alignment between the shape of involved each component, structure, each several part and annexation, each several part and principle of work, manufacturing process and operation using method etc., be described in further detail, have more complete, accurate and deep understanding to help those skilled in the art to inventive concept of the present invention, technical scheme.
Wavelet analysis is the mathematical tool with time and frequency domain analysis ability of a kind of advanced person, can by orthogonal wavelet decomposition containing noisy leakage current signal, utilize the high frequency of noise signal main manifestations, threshold value quantizing process is carried out to the high frequency coefficient after decomposing, and the leakage current signal after reconstruction processing is with stress release treatment, be particularly suitable for, to the leakage current containing higher hamonic wave noise signal, there is de-noising function.Fuzzy neural network has good study and very strong mode identificating ability thereof, so fuzzy neural network is suitable for identifying insulator contamination fault.Wavelet fuzzy neural network, as a development of neural network, has not only possessed the ability of wavelet decomposition non-stationary signal, also inherits the advantage of neural network completely simultaneously, self study, self-adaptation, the features such as height is fault-tolerant, thus remarkable characteristic is had in approximation of function side.The present invention proposes based on wavelet fuzzy neural network on this basis to insulator contamination degree on-line monitoring, by the humidity of the leakage current to insulator, pulse current and environment, relative humidity as the input variable of wavelet fuzzy neural network, through wavelet fuzzy neural network, it is carried out to the Comprehensive Assessment of insulator contamination degree on-line monitoring result.
Insulation sublist and filth is formed by the deposition of the suspension in air, liquid, gas particles.Filthy deposition is relevant with dirty source character, meteorological condition, type, insulator surface, proterties and electric field intensity, insulation sublist and contaminant flashover always formed to disappear to be formed again and go round and begin again like this, so just there will be corresponding current pulse signal in the leakage current of insulator and pulse current, so the present invention proposes the humidity of a kind of leakage current based on insulator, pulse current and environment, the insulator on-line monitoring system of relative humidity.
As shown in Figure 1, insulator on-line monitoring system comprises data acquisition module, control module, communication module and length of run data center, the input end of data acquisition module link control module is used for gathering the leakage current of insulator, the humidity of environment, humidity data, and the data collected are sent in control module, control module carries out, after preliminary Leakage Current judges, data are sent to remote data center by communication module, the output terminal of control module connects communication module, communication module wireless connections remote data center, remote data center carries out the process of wavelet fuzzy neural network model to the related data of insulator, draw insulator contamination degree analyzing result, sending early warning when drawing alarm signal reminds staff to look in time and repair.
Data acquisition module comprises temperature sensor, humidity sensor and Leakage Current sensor, data collecting module collected is all be sent to control module to the related data of insulator, humidity sensor gathers the ambient humidity data of tested point insulator, temperature sensor gathers ambient temperature data, and Leakage Current sensor gathers the current pulse signal size of insulator whether Leakage Current and insulator.The data of data acquisition module comprise the data of environment temperature, humidity and leakage current thereof in Different periods, different filthy situation residing for insulator, and the data in various situations data collecting module collected arrived are as the data sample of training wavelet fuzzy neural network.
After control module receives the data of data acquisition module, the state of Leakage Current data in data acquisition module can be judged, after control module has received Leakage Current signal, control module can give the alarm signal, staff is reminded to note, be provided with the signal of alarm unit to Leakage Current in control module to differentiate, Leakage Current data exceed setting threshold value, are receiving the signal that gives the alarm of alarm signal.The output terminal of control module connects communication module, and control module receives the data of data acquisition module, after rough handling, data is sent to remote data center by communication module.
Remote data center equipment is superior, complicated data analysis can be compared, in order to reduce cost, the data analysis function of control module reduces, general data analytic function is at remote data center, predicts the filthy degradation of insulator from the data of the humidity of the leakage current of the insulator data acquisition module, pulse current and environment, relative humidity.As shown in Figure 2, remote data center comprises receiving element, processor, database and display, the input end of receiving element connection handling device, the output terminal of processor connects display and database, the teledata that remote data center is sent by receiving element received communication module, the data that the transmission and reception of receiving element connection handling device are arrived are to processor, and processor utilizes wavelet fuzzy neural network model to carry out to the data received the pollution level analysis result that data processing draws insulator.
Be provided with wavelet fuzzy neural network model in processor and fuzzy evaluation detection is carried out to insulator contamination degree, fuzzy neural network has good study and very strong mode identificating ability and small echo thereof and has good noise removal capability to signals and associated noises, wavelet fuzzy neural network is used for insulator on-line detection, thus realizes Substation Insulator real time on-line monitoring and the serious insulator of the filthy degradation of Timeliness coverage can be entered.Wavelet fuzzy neural network model is divided into hierarchical structure, and every one deck is made up of multiple node.Ground floor wavelet neural unit, data rough handling is carried out in input Leakage Current data-signal to One-dimension Time Series model, actual signal and noise signal is contained in time series models, Mallat algorithm is adopted to make Discrete Orthogonal Wavelet Transform to time series models, in leakage current, useful signal is mainly low frequency signal, noise signal is then generally high-frequency signal, with threshold value formal layout wavelet coefficient, the high frequency coefficient being about to be not more than threshold value is considered as zero and casts out and take the data of more than threshold value, and the data reconstruction after process, both most of noise had been eliminated, be unlikely to again to destroy the useful part in signal, reach noise reduction object.The each node of the second layer represents a linguistic variable value, and its effect is the membership function that each input component of calculating belongs to each linguistic variable value fuzzy set.Each node on behalf fuzzy rule of third layer, its effect is used to the former piece mating fuzzy rule, calculates the relevance grade of every rule.The nodes of the 4th layer is identical with the 3rd layer, realization be normalization calculate.Layer 5 is output layer, realization be sharpening calculate, sharpening calculate adopt method of weighted mean, wavelet fuzzy neural network model construction is complete.After wavelet fuzzy neural network model is built up, extract the data of environment temperature, humidity and the leakage current thereof in database in Different periods, different filthy situation residing for insulator, it can be used as the data sample of training wavelet fuzzy neural network, utilize data sample to model training, obtain optimization model.
After model training set up by wavelet fuzzy neural network model, can come into operation, the insulator related data parameter that Input Online detects, just can realize the evaluation to the pollution level running insulator, wavelet fuzzy neural network the insulating property that can provide insulator in the data analysis of on-line monitoring are more exactly being carried out to the insulator chain of transformer station, also can provide maintenance suggestion clearly, this has very important significance to the maintenance of the insulator of transformer station.Processor utilizes wavelet fuzzy neural network to draw, and the filthy situation interpretation of result of insulator can show over the display, the data reaching alarm value also can be glimmered and be reminded staff to check, the data that processor receives all can be deposited in a database, and what facilitate network model to train transfers use.
Also input block is provided with in remote data center, input block connection handling device is used for artificial input signal, the insulator time of day that manual site detects can be input in processor and contrast with the result of prediction, and preservation is combined with corresponding insulator state data in a database, facilitate wavelet fuzzy neural network model to revise, improve accuracy.
Above by reference to the accompanying drawings to invention has been exemplary description; obvious specific implementation of the present invention is not subject to the restrictions described above; as long as have employed the improvement of the various unsubstantialities that method of the present invention is conceived and technical scheme is carried out; or design of the present invention and technical scheme directly applied to other occasion, all within protection scope of the present invention without to improve.The protection domain that protection scope of the present invention should limit with claims is as the criterion.
Claims (8)
1. an insulator on-line monitoring system, it is characterized in that, described insulator on-line monitoring system comprises data acquisition module, control module, communication module and length of run data center, the input end of data acquisition module link control module is used for gathering the leakage current of insulator, the humidity of environment and humidity data, and the data collected are sent in control module, the output terminal of control module connects communication module, communication module wireless connections remote data center, control module carries out, after preliminary Leakage Current judges, the data of data acquisition module are sent to remote data center by communication module, remote data center utilizes wavelet fuzzy neural network model to carry out data processing to the insulator related data received, draw insulator contamination degree analyzing result.
2. insulator on-line monitoring system according to claim 1, it is characterized in that, described data acquisition module comprises temperature sensor, humidity sensor and Leakage Current sensor, humidity sensor gathers the humidity data of tested point insulator, temperature sensor gathers ambient temperature data, Leakage Current sensor gathers the Leakage Current signal data of insulator, temperature sensor, humidity sensor and Leakage Current sensor link control module.
3. insulator on-line monitoring system according to claim 1, it is characterized in that, in described control module, alarm unit is set, in alarm unit link control module, Leakage Current data in the data acquisition module received are differentiated, Leakage Current data exceed setting threshold value, and give the alarm signal.
4. insulator on-line monitoring system according to claim 1, it is characterized in that, described remote data center comprises receiving element, processor and database, the input end of receiving element connection handling device, the output terminal connection data storehouse of processor, the data that remote data center is sent by receiving element received communication module, the data that the transmission and reception of receiving element connection handling device are arrived are to processor, and processor utilizes wavelet fuzzy neural network model to carry out to the data received the pollution level analysis result that data processing draws insulator.
5. insulator on-line monitoring system according to claim 4, it is characterized in that, wavelet fuzzy neural network model is set in described processor, wavelet fuzzy neural network model has mode identificating ability and carries out denoising to signals and associated noises, and wavelet fuzzy neural network model is hierarchical structure.
6. insulator on-line monitoring system according to claim 4, it is characterized in that, after described wavelet fuzzy neural network model is set up, carry out model training, model training data from database, the data of model training comprise the insulator related data under the Different periods of data collecting module collected, different filthy state, and after model training, Input Online detects data and exports pollution level analysis result.
7. insulator on-line monitoring system according to claim 4, is characterized in that, described remote data center also comprises display, and display is connected to the output terminal of processor, the pollution level analysis result of video-stream processor.
8. insulator on-line monitoring system according to claim 4, it is characterized in that, described remote data center also comprises input block, input block connection handling device is used for artificial input signal, and the insulator time of day that manual site detects is input in processor by input block and contrasts with the result of prediction.
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| CN105571644A (en) * | 2016-01-19 | 2016-05-11 | 西安工程大学 | Metal dust pollution on-line monitoring device for insulator, and monitoring method thereof |
| CN106443309A (en) * | 2016-11-24 | 2017-02-22 | 中国矿业大学 | Online monitoring system for leakage current of contaminated insulator |
| CN106814269A (en) * | 2016-12-14 | 2017-06-09 | 国家电网公司 | Monolithic insulator Natural contamination attribute testing data handling system and processing method |
| CN106908376A (en) * | 2017-03-06 | 2017-06-30 | 云南电网有限责任公司电力科学研究院 | A kind of metal-ware electrolytic etching Monitoring Data system of DC Insulator |
| CN107515362A (en) * | 2017-08-08 | 2017-12-26 | 江苏大学 | A kind of insulator dirty degree monitoring and method for early warning based on leak current characteristic |
| CN108181562A (en) * | 2018-01-18 | 2018-06-19 | 福州大学 | Insulator breakdown diagnostic device and method based on Study On Reliability Estimation Method For Cold Standby Systems |
| CN109612702A (en) * | 2018-12-13 | 2019-04-12 | 江苏省产品质量监督检验研究院 | A kind of durability detection method of power construction connecting component |
| CN110133454A (en) * | 2019-04-17 | 2019-08-16 | 南京合继思瑞电力科技有限公司 | A kind of electric insulation part leakage current monitoring device |
| CN112488208A (en) * | 2020-12-03 | 2021-03-12 | 上海电力大学 | Method for acquiring remaining life of island pillar insulator |
| CN112698163A (en) * | 2020-12-09 | 2021-04-23 | 国网江苏省电力有限公司盐城供电分公司 | Insulator discharge fault detection and positioning method |
| CN113916281A (en) * | 2021-09-06 | 2022-01-11 | 广东电网有限责任公司广州供电局 | Distribution room monitoring method and system |
| CN117054872A (en) * | 2023-09-15 | 2023-11-14 | 合肥融讯电子科技有限公司 | Motor fault prediction detection system based on data model |
| CN117517907A (en) * | 2024-01-04 | 2024-02-06 | 山东思极科技有限公司 | Insulation state monitoring method and system for transformer substation capacitive equipment |
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Cited By (18)
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| CN105571644B (en) * | 2016-01-19 | 2018-07-06 | 西安工程大学 | A kind of insulator metallic dust filth on-Line Monitor Device and its monitoring method |
| CN105571644A (en) * | 2016-01-19 | 2016-05-11 | 西安工程大学 | Metal dust pollution on-line monitoring device for insulator, and monitoring method thereof |
| CN106443309A (en) * | 2016-11-24 | 2017-02-22 | 中国矿业大学 | Online monitoring system for leakage current of contaminated insulator |
| CN106814269B (en) * | 2016-12-14 | 2020-02-18 | 国家电网公司 | System and method for processing natural dirt accumulation characteristic test data of single-chip insulator |
| CN106814269A (en) * | 2016-12-14 | 2017-06-09 | 国家电网公司 | Monolithic insulator Natural contamination attribute testing data handling system and processing method |
| CN106908376A (en) * | 2017-03-06 | 2017-06-30 | 云南电网有限责任公司电力科学研究院 | A kind of metal-ware electrolytic etching Monitoring Data system of DC Insulator |
| CN107515362A (en) * | 2017-08-08 | 2017-12-26 | 江苏大学 | A kind of insulator dirty degree monitoring and method for early warning based on leak current characteristic |
| CN108181562A (en) * | 2018-01-18 | 2018-06-19 | 福州大学 | Insulator breakdown diagnostic device and method based on Study On Reliability Estimation Method For Cold Standby Systems |
| CN109612702B (en) * | 2018-12-13 | 2021-07-30 | 江苏省产品质量监督检验研究院 | Durability detection method for electric power construction connecting part |
| CN109612702A (en) * | 2018-12-13 | 2019-04-12 | 江苏省产品质量监督检验研究院 | A kind of durability detection method of power construction connecting component |
| CN110133454A (en) * | 2019-04-17 | 2019-08-16 | 南京合继思瑞电力科技有限公司 | A kind of electric insulation part leakage current monitoring device |
| CN112488208A (en) * | 2020-12-03 | 2021-03-12 | 上海电力大学 | Method for acquiring remaining life of island pillar insulator |
| CN112488208B (en) * | 2020-12-03 | 2023-02-14 | 上海电力大学 | Method for acquiring remaining life of island pillar insulator |
| CN112698163A (en) * | 2020-12-09 | 2021-04-23 | 国网江苏省电力有限公司盐城供电分公司 | Insulator discharge fault detection and positioning method |
| CN113916281A (en) * | 2021-09-06 | 2022-01-11 | 广东电网有限责任公司广州供电局 | Distribution room monitoring method and system |
| CN117054872A (en) * | 2023-09-15 | 2023-11-14 | 合肥融讯电子科技有限公司 | Motor fault prediction detection system based on data model |
| CN117517907A (en) * | 2024-01-04 | 2024-02-06 | 山东思极科技有限公司 | Insulation state monitoring method and system for transformer substation capacitive equipment |
| CN117517907B (en) * | 2024-01-04 | 2024-03-22 | 山东思极科技有限公司 | Insulation state monitoring method and system for transformer substation capacitive equipment |
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