CN112363029A - Equipment corona discharge online monitoring system and monitoring method thereof - Google Patents
Equipment corona discharge online monitoring system and monitoring method thereof Download PDFInfo
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Abstract
An equipment corona discharge online monitoring system comprises a solar blind ultraviolet light sensing module, a conditioning module, a digital-to-analog conversion module, a data receiving module, a data preprocessing module, a characteristic value operation module, a monitoring and early warning module, a data transmission module and a big data visualization platform; the solar blind ultraviolet sensing module is in signal connection with the conditioning module, and the conditioning module is in signal connection with the digital-to-analog conversion module; the data receiving module is in communication connection with the digital-to-analog conversion module and the data preprocessing module; the characteristic value operation module is in communication connection with the data preprocessing module and the monitoring and early warning module; the data transmission module is in communication connection with the monitoring and early warning module and the big data visualization platform; the invention also provides an equipment corona discharge on-line monitoring method. The invention improves the safety, the economy and the usability of the power grid insulator, realizes the visual maintenance based on state evaluation and fault prediction, reduces the maintenance investment, reduces the use and maintenance cost, and is beneficial to popularization and use.
Description
Technical Field
The invention relates to the technical field of corona discharge monitoring, in particular to an equipment corona discharge on-line monitoring system and a monitoring method thereof.
Background
Because the environment deteriorates, the weather is damaged, and the insulation equipment of the power transmission and transformation equipment is exposed to various complex environments for a long time, the damage of the insulation layer is more and more serious, when the local voltage of the insulator exceeds the critical voltage, the air can be dissociated to generate corona discharge, and the huge loss is caused by large and small accidents, so that the method is one of the sources of the major potential safety hazards of a power system; the generation of insulation accidents usually originates from corona formed by partial discharge, and then gradually becomes stronger, and finally accidents occur;
in view of the current situation of insulator operation and maintenance, the current detection methods include methods such as visual inspection, telescope, discharge sound, insulation resistance, salt adhesion measurement and the like, but all have certain limitations; the visual inspection and telescope method is comprehensive, but has large business volume and no side points, the planned inspection cycle is difficult to determine, the personnel level occupational literacy is uneven, the criterion is difficult to quantify, and the detection quality is difficult to control; the discharge sound method has too large randomness and poor operability; the insulation resistance and salt adhesion measurement method is comprehensive, but has large service volume and needs power failure operation; other mechanical damages are difficult to observe, the test method needs power failure operation, and the limitation of the current method is that the test time is long; the defects of maintenance and repair are that no regular cleaning and power failure operation is needed; the antifouling paint has large workload of failure detection, and the failure standard is difficult to establish; the failure of the insulator is difficult to detect, the service volume is large, and the replacement basis is difficult to determine;
on-line monitoring becomes an important component of preventive tests, and the on-line monitoring makes up for the shortage of pretesting only by periodical power failure in many aspects; in recent years, the importance of online monitoring is fully proved by large-scale power failure accidents of a power system caused by insulation reasons at home and abroad; therefore, the research and development of the insulator corona discharge online monitoring system and the establishment of the corona discharge online monitoring system of the ubiquitous power internet of things power equipment are necessary; and because the energy structure of China causes the main power generation area to have a certain degree of mismatching with the main power utilization area, therefore guarantee the safe operation of the electric wire netting especially extra-high voltage long distance transmission net is the important one to guarantee the energy safety of China, and in numerous means of guaranteeing the electric wire netting safety, the solution based on the insulator corona discharge on-line monitoring system has important value to improve the utilization rate of the electric wire netting equipment, save the maintenance cost and prolong the service life of the equipment.
Disclosure of Invention
Objects of the invention
In order to solve the technical problems in the background art, the invention provides the equipment corona discharge online monitoring system and the monitoring method thereof, which improve the safety, the economy and the usability of the power grid insulator, realize the visual maintenance based on state evaluation and fault prediction, reduce the maintenance investment, reduce the use and maintenance cost and are beneficial to popularization and use.
(II) technical scheme
The invention provides an equipment corona discharge online monitoring system which comprises a solar blind ultraviolet light sensing module, a conditioning module, a digital-to-analog conversion module, a data receiving module, a data preprocessing module, a characteristic value operation module, a monitoring and early warning module, a data transmission module and a big data visualization platform, wherein the solar blind ultraviolet light sensing module is used for sensing the solar blind ultraviolet light;
the solar blind ultraviolet sensing module is in signal connection with the conditioning module, and the conditioning module is in signal connection with the digital-to-analog conversion module; the input end of the data receiving module is in communication connection with the digital-to-analog conversion module, and the output end of the data receiving module is in communication connection with the input end of the data preprocessing module; the input end of the characteristic value operation module is in communication connection with the data preprocessing module, and the output end of the characteristic value operation module is in communication connection with the monitoring and early warning module; the data transmission module is in communication connection with the monitoring and early warning module and the big data visualization platform;
the solar blind ultraviolet sensing module senses the insulator corona flashover phenomenon based on the gallium oxide sensor, collects and stores information in real time, acquires the operation information, the image information and the state information of the insulator, and sends the information to the conditioning module;
the conditioning module and the digital-to-analog conversion module are used for conditioning conversion and sending the converted real-time data to the data preprocessing module;
the data preprocessing module is used for preprocessing the converted real-time data and sending the preprocessed data to the characteristic value operation module;
the eigenvalue operation module is used for analyzing and calculating eigenvalues based on the preprocessed data and sending related information to the monitoring and early warning module;
the monitoring and early warning module monitors the operation information and sends out early warning, and the data transmission module sends related information to the big data visualization platform;
the big data visualization platform is used for visually displaying real-time monitoring data, alarm data and health data.
Preferably, the solar blind ultraviolet sensing module is a solar blind ultraviolet sensor array, so that time domain analysis of the intensity of the light sensing position is realized, the flashover development process is described in real time, the fault phenomenon is dynamically analyzed, and finally, the positioning of the initial position of the flashover corona, the identification of the fault position and the evaluation of the fault type are realized.
Preferably, the conditioning module comprises a front-end impact protection circuit, a signal amplification circuit, an amplification filter circuit, a current-voltage conversion circuit, a photoelectric isolation circuit, a sensor driving circuit and an ultraviolet pulse signal conditioning circuit;
the output end of the current-voltage conversion circuit, the output end of the ultraviolet pulse signal conditioning circuit and the output end of the photoelectric isolation circuit are respectively connected with the input end of the analog-digital conversion module, the output end of the sensor driving circuit is connected with the input end of the ultraviolet pulse signal conditioning circuit, and the output end of the front-end impact protection circuit is connected with the input end of the current-voltage conversion circuit after being connected with the amplifying filter circuit in series.
Preferably, the system also comprises a fault diagnosis module, a video module, a data mining module, a configuration module, a historical data module and an operation and maintenance module;
the fault diagnosis module is used for identifying the fault type timely and accurately and determining the fault reason; the video module monitors and records the insulator, and constantly pays attention to whether the running state of the insulator is abnormal or not; mainstream machine learning and neural network algorithms are embedded in the data mining module, and deep data mining and fault prediction are carried out on the basis of a big data platform; the configuration module can configure various parameters according to requirements, and the parameters comprise insulator manufacturer information and service condition information; the historical data module is used for comprehensively recording historical faults and providing powerful support for operation and maintenance; the operation and maintenance module records various maintenance information, wherein the maintenance information comprises maintenance personnel information, maintenance object ID and the like.
Preferably, the big data visualization platform comprises a data center big screen, a PC (personal computer) end and a mobile APP (application) end, so that personnel at each level can conveniently check and know the real-time state of the equipment;
the big data visualization platform accesses the intelligent equipment to the network based on Ethernet, 5G network, Bluetooth and Zigbee communication protocols; the method comprises the steps that working condition data of industrial equipment are collected through intelligent equipment, collected data are transmitted to a cloud end from an edge side by utilizing multiple data protocols of MQTT, CoAP, AMQP, XMPP and HTTP to achieve remote access of the data, and equipment-level authentication and strategy authorization are supported;
the big data visualization platform is combined with industrial experience, based on different data storage engines including a distributed file system, a MYSQL database, a relational database and a time sequence database according to industrial data characteristics, a high-reliability, high-performance and telescopic distributed storage system and a storage cluster are built by adopting a virtualization storage technology and a cloud computing technology, mass storage of industrial equipment working condition data is achieved, and real-time monitoring data, alarm data and health data are visually displayed.
Preferably, the monitoring and early warning module is applied by a solar blind ultraviolet imaging technology, and a relation model of the flashover voltage of the power supply on the surface of the insulator and the trap density on the surface of the insulator is researched to complete estimation of dirt, cracks and other damage positions on the surface of the insulator;
the monitoring and early warning module is combined with an artificial intelligence recognition mechanism of system design, and related analysis is completed through training of tag data, and the specific process comprises quantitative relation between surface flashover phenomenon and loaded voltage of the power grid insulator, judgment basis of flashover severity and pollution flashover disaster of the power grid insulator and threshold training of each fault prediction stage of the power grid insulator online monitoring system.
The invention also provides an equipment corona discharge on-line monitoring method, which comprises the following steps:
s1, building an insulator corona discharge monitoring system framework based on an advanced sensing technology, a data processing technology, a communication technology, big data and a prediction and diagnosis algorithm;
s2, the solar blind ultraviolet sensing module senses the insulator corona flashover phenomenon to monitor the insulator corona condition, the conditioning module and the digital-to-analog conversion module perform conditioning conversion, and the converted real-time data are sent to the data preprocessing module;
s3, preprocessing the converted data, analyzing and calculating the characteristic values, sending the analyzed data to a monitoring and early warning module, and monitoring and early warning by the monitoring and early warning module;
s4, the data transmission module sends the related information to the big data visualization platform, and the big data visualization platform visually displays the real-time monitoring data, the alarm data and the health data, so that the personnel can conveniently check and know the real-time state of the power equipment.
Preferably, the method further comprises the following steps:
establishing an L-V model of light sensation intensity and applied voltage; through system operation, data increase and online training of the L-V model, a neural network model from sensing data to applying voltage is obtained; and outputting a resistivity monitoring report of the insulator by using the reasoning L-V model.
Preferably, the method further comprises the following steps:
constructing an LF-F model of which the light sensation intensity and the flashover frequency correspond to the failure of the insulator; training an LF-F model on line by system operation and data increase to obtain a neural network model for sensing data and insulator failure parameters; and outputting an insulator failure report as a maintenance decision data basis by using a reasoning LF-F model.
Preferably, in S3, the eigenvalue analysis calculation is mainly analyzed for light sensation intensity, light sensation energy, and light sensation frequency;
wherein, the analysis process of the photosensitive intensity is as follows: monitoring the transient light sensation intensity, firstly, judging a threshold value, and filtering noise and sensor dark current; estimating the flashover applied voltage by analyzing the transient intensity, thereby judging whether the insulation performance of the insulator is reduced; constructing a light sensing intensity and a light sensing frequency 2D image, and then carrying out time statistics recording, thereby weighting the maintenance attention of the group of insulators according to a phenomenon record statistics list;
the analysis of the light sensation energy is as follows: by performing timing integration on the light induction current, omission of continuous low-light-intensity corona flashover is avoided; setting a threshold value for the timing integral to realize the drying treatment of the flashover corona; combining with the true phenomenon frequency, making subsequent early warning diagnosis algorithm processing;
the light perception frequency analysis process is as follows: and recording statistical data through light sensing frequency, analyzing, and optimizing a system fault discrimination threshold value by combining an actual maintenance result.
The technical scheme of the invention has the following beneficial technical effects:
the insulator monitoring system can effectively monitor the running state of the insulator on line, realize early warning, alarming and diagnosis of pollution flashover and discharge of the insulator, ensure running safety, reduce the corona discharge fault rate of the insulator and realize predictive maintenance of the insulator, and can also carry out health management on a power system, reduce the occurrence probability of accidents and faults and improve the reliability and safety of the whole power system; the method comprises the steps that an on-line corona discharge monitoring system of the power equipment is utilized to collect and store information such as insulator faults, relevant digital information is provided from the operating angle of a power system, and a foundation is laid for constructing a ubiquitous power internet of things safety public information service platform; through the data collection of system formula, see through data analysis and excavation, finally feed back to electric power system's design and manufacture end, solve the product design blind area, avoid the processing defect, impel the power equipment producer further to improve insulator product quality.
Drawings
Fig. 1 is a system diagram of an apparatus corona discharge online monitoring system and a monitoring method thereof according to the present invention.
Fig. 2 is a method flowchart of an apparatus corona discharge online monitoring system and a monitoring method thereof according to the present invention.
Fig. 3 is a flow chart of analyzing light sensation intensity in the corona discharge on-line monitoring system and the monitoring method thereof of the present invention.
Fig. 4 is a flow chart of analyzing light-induced energy in the corona discharge on-line monitoring system and the monitoring method thereof of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
As shown in fig. 1, the corona discharge on-line monitoring system for equipment provided by the invention comprises a solar blind ultraviolet sensing module, a conditioning module, a digital-to-analog conversion module, a data receiving module, a data preprocessing module, a characteristic value operation module, a monitoring and early warning module, a data transmission module and a big data visualization platform;
the solar blind ultraviolet sensing module is in signal connection with the conditioning module, and the conditioning module is in signal connection with the digital-to-analog conversion module; the input end of the data receiving module is in communication connection with the digital-to-analog conversion module, and the output end of the data receiving module is in communication connection with the input end of the data preprocessing module; the input end of the characteristic value operation module is in communication connection with the data preprocessing module, and the output end of the characteristic value operation module is in communication connection with the monitoring and early warning module; the data transmission module is in communication connection with the monitoring and early warning module and the big data visualization platform;
the solar blind ultraviolet sensing module senses the insulator corona flashover phenomenon based on the gallium oxide sensor, collects and stores information in real time, acquires the operation information, the image information and the state information of the insulator, and sends the information to the conditioning module;
the conditioning module and the digital-to-analog conversion module are used for conditioning conversion and sending the converted real-time data to the data preprocessing module;
the data preprocessing module is used for preprocessing the converted real-time data and sending the preprocessed data to the characteristic value operation module;
the eigenvalue operation module is used for analyzing and calculating eigenvalues based on the preprocessed data and sending related information to the monitoring and early warning module;
the monitoring and early warning module monitors the operation information and sends out early warning, and the data transmission module sends related information to the big data visualization platform;
the big data visualization platform is used for visually displaying real-time monitoring data, alarm data and health data.
In an optional embodiment, the solar-blind ultraviolet sensing module is a solar-blind ultraviolet sensor array, so that time-domain analysis of the intensity of the light-sensing position is realized, a flashover development process is described in real time, a fault phenomenon is dynamically analyzed, and finally, positioning of an initial flashover corona position, fault position identification and fault type evaluation are realized.
In an optional embodiment, the conditioning module comprises a front-end impact protection circuit, a signal amplification circuit, an amplification filter circuit, a current-voltage conversion circuit, a photoelectric isolation circuit, a sensor driving circuit and an ultraviolet pulse signal conditioning circuit; the output end of the current-voltage conversion circuit, the output end of the ultraviolet pulse signal conditioning circuit and the output end of the photoelectric isolation circuit are respectively connected with the input end of the analog-digital conversion module, the output end of the sensor driving circuit is connected with the input end of the ultraviolet pulse signal conditioning circuit, and the output end of the front-end impact protection circuit is connected with the input end of the current-voltage conversion circuit after being connected with the amplifying filter circuit in series.
In an optional embodiment, the system further comprises a fault diagnosis module, a video module, a data mining module, a configuration module, a historical data module and an operation and maintenance module; the fault diagnosis module is used for identifying the fault type timely and accurately and determining the fault reason; the video module monitors and records the insulator, and constantly pays attention to whether the running state of the insulator is abnormal or not; mainstream machine learning and neural network algorithms are embedded in the data mining module, and deep data mining and fault prediction are carried out on the basis of a big data platform; the configuration module can configure various parameters according to requirements, and the parameters comprise insulator manufacturer information and service condition information; the historical data module is used for comprehensively recording historical faults and providing powerful support for operation and maintenance; the operation and maintenance module records various maintenance information, wherein the maintenance information comprises maintenance personnel information, maintenance object ID and the like.
In an optional embodiment, the big data visualization platform comprises a data center big screen, a PC end and a mobile APP end, so that personnel at each level can conveniently view and know the real-time state of the equipment; the big data visualization platform accesses the intelligent equipment to the network based on Ethernet, 5G network, Bluetooth and Zigbee communication protocols; the method comprises the steps that working condition data of industrial equipment are collected through intelligent equipment, collected data are transmitted to a cloud end from an edge side by utilizing multiple data protocols of MQTT, CoAP, AMQP, XMPP and HTTP to achieve remote access of the data, and equipment-level authentication and strategy authorization are supported; the big data visualization platform is combined with industrial experience, based on different data storage engines including a distributed file system, a MYSQL database, a relational database and a time sequence database according to industrial data characteristics, a high-reliability, high-performance and telescopic distributed storage system and a storage cluster are built by adopting a virtualization storage technology and a cloud computing technology, mass storage of industrial equipment working condition data is achieved, and real-time monitoring data, alarm data and health data are visually displayed.
In an optional embodiment, the monitoring and early warning module is applied by a solar blind ultraviolet imaging technology, and researches a relation model of the flashover voltage of the power supply on the surface of the insulator and the trap density on the surface of the insulator so as to estimate the positions of dirt, cracks and other damages of the surface of the insulator; the monitoring and early warning module is combined with an artificial intelligence recognition mechanism of system design, and related analysis is completed through training of tag data, and the specific process comprises quantitative relation between surface flashover phenomenon and loaded voltage of the power grid insulator, judgment basis of flashover severity and pollution flashover disaster of the power grid insulator and threshold training of each fault prediction stage of the power grid insulator online monitoring system.
As shown in fig. 2-4, the present invention also provides an on-line monitoring method for corona discharge of equipment, comprising the following steps:
s1, building an insulator corona discharge monitoring system framework based on an advanced sensing technology, a data processing technology, a communication technology, big data and a prediction and diagnosis algorithm;
s2, the solar blind ultraviolet sensing module senses the insulator corona flashover phenomenon to monitor the insulator corona condition, the conditioning module and the digital-to-analog conversion module perform conditioning conversion, and the converted real-time data are sent to the data preprocessing module;
s3, preprocessing the converted data, analyzing and calculating the characteristic values, sending the analyzed data to a monitoring and early warning module, and monitoring and early warning by the monitoring and early warning module;
s4, the data transmission module sends the related information to the big data visualization platform, and the big data visualization platform visually displays the real-time monitoring data, the alarm data and the health data, so that the personnel can conveniently check and know the real-time state of the power equipment.
In an optional embodiment, the method further comprises the following steps: establishing an L-V model of light sensation intensity and applied voltage (when pollution flashover corona occurs in the insulator); through system operation, data increase and online training of the L-V model, a neural network model (mathematical relation) from sensing data to applied voltage is obtained; and outputting a monitoring report of the resistivity (insulation voltage) of the insulator by using the reasoning L-V model.
In an optional embodiment, the method further comprises the following steps: constructing an LF-F model of light sensation intensity and flashover frequency corresponding to insulator failure (performance reduction); training an LF-F model on line by system operation and data increase to obtain a neural network model (mathematical relation) of perception data and insulator failure (performance degradation) parameters; and outputting an insulator failure report as a maintenance decision data basis by using a reasoning LF-F model.
In an alternative embodiment, in S3, the eigenvalue analysis calculation is mainly analyzed for light sensation intensity, light sensation energy, and light sensation frequency;
wherein, the analysis process of the photosensitive intensity is as follows: monitoring the transient light sensation intensity, firstly, judging a threshold value, and filtering noise and sensor dark current; estimating the flashover applied voltage by analyzing the transient intensity, thereby judging whether the insulation performance of the insulator is reduced; constructing a light sensing intensity and a light sensing frequency 2D image, and then carrying out time statistics recording, thereby weighting the maintenance attention of the group of insulators according to a phenomenon record statistics list;
the analysis of the light sensation energy is as follows: by performing timing integration on the light induction current, omission of continuous low-light-intensity corona flashover is avoided; setting a threshold value for the timing integral to realize the drying treatment of the flashover corona; combining with the true phenomenon frequency, making subsequent early warning diagnosis algorithm processing;
the light perception frequency analysis process is as follows: and recording statistical data through light sensing frequency, analyzing, and optimizing a system fault discrimination threshold value by combining an actual maintenance result.
In the invention, by developing an insulator-based corona discharge online monitoring system, the power industry is promoted to gradually realize maintenance according to needs, the safe operation level is improved, the operation state of the insulator can be effectively monitored online, the early warning, alarming and diagnosis of pollution flashover and discharge of the insulator are realized, the operation safety is ensured, the corona discharge fault rate of the insulator is reduced, the insulator predictive maintenance is realized, a maintenance suggestion is provided from the power management perspective, the health management is carried out on the power system, the occurrence probability of accidents and faults is reduced, and the reliability and the safety of the whole power system are improved;
by integrating related information such as real-time remote monitoring of the operation state of the insulator, dynamic supervision and real-time recording of the insulator maintenance behavior and the like, the supervision capability of the insulator maintenance behavior can be effectively improved, an on-line corona discharge monitoring system of the power equipment is utilized to collect and store information such as insulator faults and the like, related digital information is provided from the operation angle of the power system, and a foundation is laid for constructing a ubiquitous power internet of things safety public information service platform;
and can finally feed back to the design and manufacturing end of the power system through the system type data collection, data analysis and excavation, solve the product design blind area, avoid the processing defect, and promote the power equipment manufacturer to further improve the quality of the insulator product.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (10)
1. An equipment corona discharge online monitoring system is characterized by comprising a solar blind ultraviolet light sensing module, a conditioning module, a digital-to-analog conversion module, a data receiving module, a data preprocessing module, a characteristic value operation module, a monitoring and early warning module, a data transmission module and a big data visualization platform;
the solar blind ultraviolet sensing module is in signal connection with the conditioning module, and the conditioning module is in signal connection with the digital-to-analog conversion module; the input end of the data receiving module is in communication connection with the digital-to-analog conversion module, and the output end of the data receiving module is in communication connection with the input end of the data preprocessing module; the input end of the characteristic value operation module is in communication connection with the data preprocessing module, and the output end of the characteristic value operation module is in communication connection with the monitoring and early warning module; the data transmission module is in communication connection with the monitoring and early warning module and the big data visualization platform;
the solar blind ultraviolet sensing module senses the insulator corona flashover phenomenon based on the gallium oxide sensor, collects and stores information in real time, acquires the operation information, the image information and the state information of the insulator, and sends the information to the conditioning module;
the conditioning module and the digital-to-analog conversion module are used for conditioning conversion and sending the converted real-time data to the data preprocessing module;
the data preprocessing module is used for preprocessing the converted real-time data and sending the preprocessed data to the characteristic value operation module;
the eigenvalue operation module is used for analyzing and calculating eigenvalues based on the preprocessed data and sending related information to the monitoring and early warning module;
the monitoring and early warning module monitors the operation information and sends out early warning, and the data transmission module sends related information to the big data visualization platform;
the big data visualization platform is used for visually displaying real-time monitoring data, alarm data and health data.
2. The on-line equipment corona discharge monitoring system of claim 1, wherein the solar-blind ultraviolet light sensing module is a solar-blind ultraviolet sensor array, and is used for performing time-domain analysis on light-sensing position intensity, describing a flashover development process in real time, performing dynamic analysis on a fault phenomenon, and finally performing flashover corona initial position positioning, fault position identification and fault type evaluation.
3. The device corona discharge online monitoring system according to claim 1, wherein the conditioning module comprises a front-end impact protection circuit, a signal amplification circuit, an amplification filter circuit, a current-voltage conversion circuit, a photoelectric isolation circuit, a sensor driving circuit and an ultraviolet pulse signal conditioning circuit;
the output end of the current-voltage conversion circuit, the output end of the ultraviolet pulse signal conditioning circuit and the output end of the photoelectric isolation circuit are respectively connected with the input end of the analog-digital conversion module, the output end of the sensor driving circuit is connected with the input end of the ultraviolet pulse signal conditioning circuit, and the output end of the front-end impact protection circuit is connected with the input end of the current-voltage conversion circuit after being connected with the amplifying filter circuit in series.
4. The equipment corona discharge online monitoring system according to claim 1, further comprising a fault diagnosis module, a video module, a data mining module, a configuration module, a historical data module and an operation and maintenance module;
the fault diagnosis module is used for identifying the fault type timely and accurately and determining the fault reason; the video module monitors and records the insulator, and constantly pays attention to whether the running state of the insulator is abnormal or not; mainstream machine learning and neural network algorithms are embedded in the data mining module, and deep data mining and fault prediction are carried out on the basis of a big data platform; the configuration module can configure various parameters according to requirements, and the parameters comprise insulator manufacturer information and service condition information; the historical data module is used for comprehensively recording historical faults and providing powerful support for operation and maintenance; the operation and maintenance module records various maintenance information, wherein the maintenance information comprises maintenance personnel information, maintenance object ID and the like.
5. The equipment corona discharge online monitoring system according to claim 1, wherein the big data visualization platform comprises a data center big screen, a PC end and a mobile APP end, so that personnel at each level can conveniently check and know the real-time state of the equipment;
the big data visualization platform accesses the intelligent equipment to the network based on Ethernet, 5G network, Bluetooth and Zigbee communication protocols; the method comprises the steps that working condition data of industrial equipment are collected through intelligent equipment, collected data are transmitted to a cloud end from an edge side by utilizing multiple data protocols of MQTT, CoAP, AMQP, XMPP and HTTP to achieve remote access of the data, and equipment-level authentication and strategy authorization are supported;
the big data visualization platform is combined with industrial experience, based on different data storage engines including a distributed file system, a MYSQL database, a relational database and a time sequence database according to industrial data characteristics, a high-reliability, high-performance and telescopic distributed storage system and a storage cluster are built by adopting a virtualization storage technology and a cloud computing technology, mass storage of industrial equipment working condition data is achieved, and real-time monitoring data, alarm data and health data are visually displayed.
6. The equipment corona discharge online monitoring system according to claim 1, wherein the monitoring and early warning module is applied by a solar blind ultraviolet imaging technology, and researches a relation model of flashover voltage of a power supply on the surface of the insulator and trap density on the surface of the insulator so as to estimate dirt, cracks and other damage positions on the surface of the insulator;
the monitoring and early warning module is combined with an artificial intelligence recognition mechanism of system design, and related analysis is completed through training of tag data, and the specific process comprises quantitative relation between surface flashover phenomenon and loaded voltage of the power grid insulator, judgment basis of flashover severity and pollution flashover disaster of the power grid insulator and threshold training of each fault prediction stage of the power grid insulator online monitoring system.
7. An on-line monitoring method for equipment corona discharge is characterized by comprising the following steps:
s1, building an insulator corona discharge monitoring system framework based on an advanced sensing technology, a data processing technology, a communication technology, big data and a prediction and diagnosis algorithm;
s2, the solar blind ultraviolet sensing module senses the insulator corona flashover phenomenon to monitor the insulator corona condition, the conditioning module and the digital-to-analog conversion module perform conditioning conversion, and the converted real-time data are sent to the data preprocessing module;
s3, preprocessing the converted data, analyzing and calculating the characteristic values, sending the analyzed data to a monitoring and early warning module, and monitoring and early warning by the monitoring and early warning module;
s4, the data transmission module sends the related information to the big data visualization platform, and the big data visualization platform visually displays the real-time monitoring data, the alarm data and the health data, so that the personnel can conveniently check and know the real-time state of the power equipment.
8. The on-line equipment corona discharge monitoring method according to claim 7, further comprising the following steps:
establishing an L-V model of light sensation intensity and applied voltage; through system operation, data increase and online training of the L-V model, a neural network model from sensing data to applying voltage is obtained; and outputting a resistivity monitoring report of the insulator by using the reasoning L-V model.
9. The on-line equipment corona discharge monitoring method according to claim 7, further comprising the following steps:
constructing an LF-F model of which the light sensation intensity and the flashover frequency correspond to the failure of the insulator; training an LF-F model on line by system operation and data increase to obtain a neural network model for sensing data and insulator failure parameters; and outputting an insulator failure report as a maintenance decision data basis by using a reasoning LF-F model.
10. The on-line monitoring method for corona discharge of equipment as claimed in claim 7, wherein in S3, the eigenvalue analysis calculation mainly analyzes the intensity of light sensation, the energy of light sensation and the frequency of light sensation;
wherein, the analysis process of the photosensitive intensity is as follows: monitoring the transient light sensation intensity, firstly, judging a threshold value, and filtering noise and sensor dark current; estimating the flashover applied voltage by analyzing the transient intensity, thereby judging whether the insulation performance of the insulator is reduced; constructing a light sensing intensity and a light sensing frequency 2D image, and then carrying out time statistics recording, thereby weighting the maintenance attention of the group of insulators according to a phenomenon record statistics list;
the analysis of the light sensation energy is as follows: by performing timing integration on the light induction current, omission of continuous low-light-intensity corona flashover is avoided; setting a threshold value for the timing integral to realize the drying treatment of the flashover corona; combining with the true phenomenon frequency, making subsequent early warning diagnosis algorithm processing;
the light perception frequency analysis process is as follows: and recording statistical data through light sensing frequency, analyzing, and optimizing a system fault discrimination threshold value by combining an actual maintenance result.
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