CN113691014A - Intelligent video identification monitoring alarm system for power equipment - Google Patents
Intelligent video identification monitoring alarm system for power equipment Download PDFInfo
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- CN113691014A CN113691014A CN202110776139.5A CN202110776139A CN113691014A CN 113691014 A CN113691014 A CN 113691014A CN 202110776139 A CN202110776139 A CN 202110776139A CN 113691014 A CN113691014 A CN 113691014A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B19/00—Alarms responsive to two or more different undesired or abnormal conditions, e.g. burglary and fire, abnormal temperature and abnormal rate of flow
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
- H02J13/00034—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving an electric power substation
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
- H02J13/00036—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving switches, relays or circuit breakers
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02B90/20—Smart grids as enabling technology in buildings sector
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
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Abstract
The invention discloses an intelligent video identification monitoring alarm system for power equipment. The system comprises a power plant video monitoring system, a transformer substation video monitoring system and a monitoring center server, the power plant video monitoring system and the transformer substation video monitoring system are connected with the monitoring center server, the transformer of power plant and transformer substation is respectively collected to accessible power plant video monitoring system and transformer substation video monitoring system, the circuit breaker, current transformer, voltage transformer, the lightning rod, an insulator, an isolating switch, the video image information of indoor environment and flammable equipment, and send the video image information to the monitoring center server, whether each power equipment of power plant and transformer substation exists unusually through monitoring center server identification, send out the police dispatch newspaper when unusual, high reliability, high efficiency, high accuracy, when the occurence of failure, avoid causing danger to the on-site patrol personnel.
Description
Technical Field
The invention relates to the technical field of electric power safety, in particular to an intelligent video identification monitoring alarm system for electric power equipment.
Background
A power plant is a plant that converts various primary energy sources stored in nature into electric energy (secondary energy). At the end of the 19 th century, with the growing demand for electricity, the idea of building electricity production centers began to be proposed. The development of motor manufacturing technology, the expansion of electric energy application range, the rapid increase of the demand of electricity for production and the consequent generation of power plants. There are several ways of generating electricity in power plants: thermal power plants refer to thermal power plants, hydroelectric power plants refer to hydroelectric power plants, and power plants refer to solar (photovoltaic) and wind and tidal power plants. Nuclear power plants using nuclear fuel as an energy source have played an increasing role in many countries throughout the world. The transformer substation is a place for converting voltage and current, receiving electric energy and distributing electric energy in an electric power system. The substations in the power plant are step-up substations, which are used to boost up the electrical energy generated by the generator and feed it into the high-voltage network. At present, the power equipment generally adopts different types of sensors to detect the running state of the power equipment, and in the inspection mode of auxiliary operating personnel, the abnormity is discovered by observing the external phenomenon of the power equipment, so that the safety in the power plant and the transformer substation is guaranteed. However, these sensors are often subjected to loads in terms of electricity, heat, machinery, etc. during operation of the power equipment, and the influence of external environments, such as air temperature, air pressure, humidity, etc., causes the sensors to age, fatigue, wear, and cause performance degradation and reliability to be affected after long-term operation. And the manual inspection efficiency is lower, the accuracy is limited, and when an accident happens, the danger is easily caused to the field inspection personnel. Therefore, it is necessary to provide an intelligent video identification monitoring alarm system for power equipment to solve the above problems.
Disclosure of Invention
The invention provides an intelligent video identification monitoring alarm system for power equipment, which aims to solve the problems that sensors of the power equipment of a power plant and a transformer substation are aged, fatigued and abraded after long-term working, so that the performance is reduced, the reliability is influenced, the manual inspection efficiency is low, the accuracy is limited, and the danger is easily caused to field inspection personnel.
The invention provides an intelligent video identification monitoring alarm system for power equipment, which comprises: the system comprises a power plant video monitoring system, a transformer substation video monitoring system and a monitoring center server; the power plant video monitoring system and the transformer substation video monitoring system are respectively in communication connection with the monitoring center server; the power plant video monitoring system comprises a power plant transformer video monitoring device, a power plant circuit breaker video monitoring device, a power plant current transformer video monitoring device, a power plant voltage transformer video monitoring device, a power plant lightning rod video monitoring device, a power plant insulator video monitoring device, a power plant isolating switch video monitoring device, a power plant indoor environment video monitoring device and a power plant combustible equipment video monitoring device; the transformer substation video monitoring system comprises a transformer substation transformer video monitoring device, a transformer substation breaker video monitoring device, a transformer substation current transformer video monitoring device, a transformer substation voltage transformer video monitoring device, a transformer substation lightning rod video monitoring device, a transformer substation insulator video monitoring device, a transformer substation disconnecting switch video monitoring device, a transformer substation indoor environment video monitoring device and a transformer substation flammable equipment video monitoring device.
Further, the power plant transformer video monitoring device and the transformer substation transformer video monitoring device are used for acquiring transformer video image information and sending the transformer video image information to a monitoring center server; the monitoring center server is used for receiving the transformer video image information and extracting a transformer radiator oil pump fan image, a transformer oil way connecting part image, a transformer bushing image, a transformer lead image, a transformer bus connecting part image and a transformer body thermal imaging image from the transformer video image information; identifying whether the transformer has defects or not according to a pre-constructed transformer defect feature identification network model, wherein the transformer defect feature identification network model is established by adopting a deep learning algorithm and based on a transformer radiator oil pump fan defect feature image, a transformer oil circuit connection part defect feature image, a transformer bushing defect feature image, a transformer lead defect feature image, a transformer bus connection part defect feature image and a transformer body thermal imaging defect feature image; and sending out transformer defect early warning prompt information under the condition that the transformer has defects.
Furthermore, the power plant circuit breaker video monitoring device and the transformer substation circuit breaker video monitoring device are used for acquiring circuit breaker video image information and sending the circuit breaker video image information to a monitoring center server; the monitoring center server is used for receiving the circuit breaker video image information, extracting a circuit breaker switch on-off state characteristic image from the circuit breaker video image information, and identifying whether the circuit breaker has defects according to a pre-constructed circuit breaker defect characteristic identification network model, wherein the circuit breaker defect characteristic identification network model is established by adopting a deep learning algorithm and based on the circuit breaker defect characteristic image; and sending out early warning prompt information of the defects of the circuit breaker under the condition that the circuit breaker has the defects.
Further, the power plant current transformer video monitoring device and the transformer substation current transformer video monitoring device are used for acquiring current transformer video image information and sending the current transformer video image information to a monitoring center server; the monitoring center server is used for receiving the video image information of the current transformer, extracting an infrared image of the current transformer, extracting and checking a fault area of the infrared image of the current transformer by utilizing a superpixel segmentation method and an HSV color space, classifying and identifying fault positions of the current transformer through a current transformer fault deep learning model, and determining fault information of the current transformer according to different positions of faults of the current transformer; and sending out current transformer defect early warning prompt information under the condition that the current transformer has defects.
Further, the power plant voltage transformer video monitoring device and the transformer substation voltage transformer video monitoring device are used for acquiring video image information of a voltage transformer and sending the video image information of the voltage transformer to a monitoring center server; the monitoring center server is used for receiving the video image information of the voltage transformer, extracting an infrared image of the voltage transformer, extracting and checking a fault area of the infrared image of the voltage transformer by utilizing a superpixel segmentation method and an HSV color space, classifying and identifying fault positions of the voltage transformer through a fault deep learning model of the voltage transformer, and determining fault information of the voltage transformer according to different positions of faults of the voltage transformer; and sending out early warning prompt information of the defects of the voltage transformer under the condition that the voltage transformer has the defects.
Further, the power plant lightning rod video monitoring device and the transformer substation lightning rod video monitoring device are used for acquiring lightning rod video image information and sending the lightning rod video image information to a monitoring center server; the monitoring center server is used for receiving lightning rod video image information, extracting a lightning rod state characteristic image from the lightning rod video image information, identifying whether a lightning rod has defects or not according to a pre-constructed lightning rod defect characteristic identification network model, wherein the lightning rod defect characteristic identification network model adopts a deep learning algorithm and is established on the basis of the lightning rod defect characteristic image; and sending lightning rod defect early warning prompt information under the condition that the lightning rod has defects.
Further, the power plant insulator video monitoring device and the transformer substation insulator video monitoring device are used for acquiring insulator video image information and sending the insulator video image information to a monitoring center server; the monitoring center server is used for receiving insulator video image information, extracting an insulator state characteristic image from the insulator receiving video image information, and identifying whether the insulator has defects or not according to a pre-constructed insulator defect characteristic identification network model, wherein the insulator defect characteristic identification network model is established by adopting a deep learning algorithm and based on the insulator defect characteristic image; and sending out early warning prompt information of the defects of the insulator under the condition that the insulator has the defects.
Furthermore, the power plant disconnecting switch video monitoring device and the transformer substation disconnecting switch video monitoring device are used for acquiring disconnecting switch video image information and sending the disconnecting switch video image information to a monitoring center server; the monitoring center server is used for receiving the video image information of the disconnecting switch, extracting a state characteristic image of the disconnecting switch from the received video image information of the disconnecting switch, and identifying whether the disconnecting switch has defects or not according to a pre-constructed defect characteristic identification network model of the disconnecting switch, wherein the defect characteristic identification network model of the disconnecting switch adopts a deep learning algorithm and is established on the basis of the defect characteristic image of the disconnecting switch; and sending out early warning prompt information of the defects of the isolating switch under the condition that the isolating switch has the defects.
Furthermore, the power plant indoor environment video monitoring device and the transformer substation indoor environment video monitoring device are used for acquiring indoor environment video image information and sending the indoor environment video image information to a monitoring center server; the monitoring center server is used for receiving indoor environment video image information, extracting indoor environment state characteristic images from the received indoor environment video image information, identifying whether defects exist in the indoor environment according to a pre-constructed indoor environment defect characteristic identification network model, wherein the indoor environment defect characteristic identification network model adopts a deep learning algorithm and is established based on the indoor environment defect characteristic images; and sending out early warning prompt information of the defects of the indoor environment under the condition that the defects exist in the indoor environment.
Further, the power plant combustible equipment video monitoring device and the transformer substation combustible equipment video monitoring device are used for acquiring combustible equipment video image information and sending the combustible equipment video image information to a monitoring center server; the monitoring center server is used for receiving video image information of the combustible equipment, extracting a state characteristic image of the combustible equipment from the received video image information of the combustible equipment, identifying a network model according to a pre-constructed defect characteristic of the combustible equipment, and identifying whether the combustible equipment has defects, wherein the defect characteristic identification network model of the combustible equipment adopts a deep learning algorithm and is established based on the defect characteristic image of the combustible equipment; and sending out early warning prompt information of the defects of the flammable equipment under the condition that the flammable equipment has the defects.
According to the technical scheme, the intelligent video identification monitoring alarm system for the power equipment is characterized in that a power plant video monitoring system is arranged in a power plant, a substation video monitoring system is arranged in a substation, the power plant video monitoring system and the substation video monitoring system are connected with a monitoring center server, video image information of a transformer, a circuit breaker, a current transformer, a voltage transformer, a lightning rod, an insulator, an isolating switch, an indoor environment and flammable equipment of the power plant and the substation can be respectively collected through the power plant video monitoring system and the substation video monitoring system and sent to the monitoring center server, whether the transformer, the circuit breaker, the current transformer, the voltage transformer, the lightning rod, the insulator, the isolating switch, the indoor environment and the flammable equipment of the power plant and the substation are abnormal or not is identified through the monitoring center server, send out the police dispatch newspaper when unusual, compare with traditional sensor monitoring mode, avoid the sensor to receive the load effect in aspects such as electricity, heat, machinery often in service at power equipment to and external environment, like the influence of temperature, atmospheric pressure, humidity etc, lead to the sensor long-term work to arouse ageing, fatigue, wearing and tearing, thereby lead to the performance to descend, the reliability also receives the problem of influence, it is efficient to patrol and examine than the manual work, the accuracy is high, and when the occurence of failure, avoid patrolling and examining the personnel to the scene and cause danger.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without any inventive exercise.
Fig. 1 is a schematic diagram of an intelligent video identification monitoring alarm system of power equipment according to the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the specific embodiments of the present invention and the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below with reference to the accompanying drawings.
Referring to fig. 1, the present invention provides an intelligent video identification monitoring alarm system for power equipment, including: the system comprises a power plant video monitoring system 100, a transformer substation video monitoring system 200 and a monitoring center server 300, wherein the power plant video monitoring system 100 and the transformer substation video monitoring system 200 are respectively in communication connection with the monitoring center server 300. The power plant video monitoring system 100 is disposed within a power plant and the substation video monitoring system 200 is disposed within a substation. The power plant video monitoring system 100, the substation video monitoring system 200 and the monitoring center server 300 are connected through a network. Both power plants and substations have transformers, circuit breakers, current transformers, voltage transformers, lightning rods, insulators, disconnectors, indoor environments and flammable equipment to be monitored.
The power plant video monitoring system 100 may specifically include a power plant transformer video monitoring apparatus 101, a power plant breaker video monitoring apparatus 102, a power plant current transformer video monitoring apparatus 103, a power plant voltage transformer video monitoring apparatus 104, a power plant lightning rod video monitoring apparatus 105, a power plant insulator video monitoring apparatus 106, a power plant disconnector video monitoring apparatus 107, a power plant indoor environment video monitoring apparatus 108, and a power plant flammable equipment video monitoring apparatus 109.
The substation video monitoring system 200 may specifically include a substation transformer video monitoring device 201, a substation breaker video monitoring device 202, a substation current transformer video monitoring device 203, a substation voltage transformer video monitoring device 204, a substation lightning rod video monitoring device 205, a substation insulator video monitoring device 206, a substation disconnecting switch video monitoring device 207, a substation indoor environment video monitoring device 208, and a substation flammable equipment video monitoring device 209.
In this embodiment, the power plant transformer video monitoring apparatus 101 and the substation transformer video monitoring apparatus 201 are configured to collect transformer video image information and send the transformer video image information to the monitoring center server 300. And the monitoring center server 300 is configured to receive the transformer video image information, and extract an image of an oil pump fan of the transformer radiator, an image of an oil path connection part of the transformer, an image of a bushing of the transformer, an image of a lead of the transformer, an image of a bus connection part of the transformer, and an image of a body thermal image of the transformer from the transformer video image information. And identifying whether the transformer has defects according to a pre-constructed transformer defect feature identification network model, wherein the transformer defect feature identification network model adopts a deep learning algorithm and is established on the basis of a transformer radiator oil pump fan defect feature image, a transformer oil circuit connection part defect feature image, a transformer bushing defect feature image, a transformer lead defect feature image, a transformer bus connection part defect feature image and a transformer body thermal imaging defect feature image. And sending out transformer defect early warning prompt information under the condition that the transformer has defects. The related responsible personnel can also be equipped with a handheld mobile terminal, and the early warning prompt information is sent to the handheld mobile terminal through the monitoring center server 300.
In this embodiment, the power plant circuit breaker video monitoring device 102 and the substation circuit breaker video monitoring device 202 are configured to acquire circuit breaker video image information and send the circuit breaker video image information to the monitoring center server 300; the monitoring center server 300 is used for receiving the video image information of the circuit breaker, extracting a characteristic image of the on-off state of the switch of the circuit breaker from the video image information of the circuit breaker, and identifying whether the circuit breaker has defects according to a pre-constructed circuit breaker defect characteristic identification network model, wherein the circuit breaker defect characteristic identification network model adopts a deep learning algorithm and is established based on the circuit breaker defect characteristic image; and sending out early warning prompt information of the defects of the circuit breaker under the condition that the circuit breaker has the defects. The circuit breaker defect feature identification network model can be constructed according to the specific switch on-off state and the specific switch on-off state of the abnormal state of different circuit breakers in the normal state, so that defect early warning prompt is carried out according to the actual condition of each circuit breaker when the corresponding circuit breaker is identified.
In this embodiment, the power plant current transformer video monitoring device 103 and the substation current transformer video monitoring device 203 are configured to collect current transformer video image information and send the current transformer video image information to the monitoring center server 300; the monitoring center server 300 is used for receiving video image information of the current transformer, extracting an infrared image of the current transformer, extracting and verifying a fault area of the infrared image of the current transformer by using a superpixel segmentation method and an HSV color space, classifying and identifying fault positions of the current transformer through a current transformer fault deep learning model, and determining fault information of the current transformer according to different positions of faults of the current transformer; and sending out current transformer defect early warning prompt information under the condition that the current transformer has defects.
In this embodiment, the power plant voltage transformer video monitoring device 104 and the substation voltage transformer video monitoring device 204 are configured to collect video image information of a voltage transformer, and send the video image information of the voltage transformer to the monitoring center server 300; the monitoring center server 300 is used for receiving video image information of the voltage transformer, extracting an infrared image of the voltage transformer, extracting and verifying a fault area of the infrared image of the voltage transformer by using a superpixel segmentation method and an HSV color space, classifying and identifying fault positions of the voltage transformer through a fault deep learning model of the voltage transformer, and determining fault information of the voltage transformer according to different positions of faults of the voltage transformer; and sending out early warning prompt information of the defects of the voltage transformer under the condition that the voltage transformer has the defects.
In this embodiment, the power plant lightning rod video monitoring device 105 and the substation lightning rod video monitoring device 205 are configured to collect lightning rod video image information and send the lightning rod video image information to the monitoring center server 300; the monitoring center server 300 is used for receiving the lightning rod video image information, extracting a lightning rod state characteristic image from the lightning rod video image information, identifying whether the lightning rod has defects or not according to a pre-constructed lightning rod defect characteristic identification network model, wherein the lightning rod defect characteristic identification network model is established by adopting a deep learning algorithm and based on the lightning rod defect characteristic image; and sending lightning rod defect early warning prompt information under the condition that the lightning rod has defects. Defects of the lightning rod may include tilting of the lightning rod, bending of the lightning rod, breaking of the lightning rod, etc.
In this embodiment, the power plant insulator video monitoring apparatus 106 and the substation insulator video monitoring apparatus 206 are configured to collect insulator video image information and send the insulator video image information to the monitoring center server 300; the monitoring center server 300 is used for receiving insulator video image information, extracting an insulator state characteristic image from the insulator video image information, and identifying whether the insulator has a defect according to a pre-constructed insulator defect characteristic identification network model, wherein the insulator defect characteristic identification network model is established by adopting a deep learning algorithm and based on the insulator defect characteristic image; and sending out early warning prompt information of the defects of the insulator under the condition that the insulator has the defects.
In this embodiment, the power plant disconnecting switch video monitoring device 107 and the substation disconnecting switch video monitoring device 207 are configured to acquire disconnecting switch video image information and send the disconnecting switch video image information to the monitoring center server 300; the monitoring center server 300 is used for receiving the video image information of the disconnecting switch, extracting a state characteristic image of the disconnecting switch from the received video image information of the disconnecting switch, identifying whether the disconnecting switch has defects according to a pre-constructed defect characteristic identification network model of the disconnecting switch, wherein the defect characteristic identification network model of the disconnecting switch adopts a deep learning algorithm and is established on the basis of the defect characteristic image of the disconnecting switch; and sending out early warning prompt information of the defects of the isolating switch under the condition that the isolating switch has the defects.
In this embodiment, the power plant indoor environment video monitoring device 108 and the substation indoor environment video monitoring device 208 are configured to collect indoor environment video image information and send the indoor environment video image information to the monitoring center server 300; the monitoring center server 300 is used for receiving indoor environment video image information, extracting indoor environment state characteristic images from the received indoor environment video image information, identifying whether the indoor environment has defects according to a pre-constructed indoor environment defect characteristic identification network model, wherein the indoor environment defect characteristic identification network model adopts a deep learning algorithm and is established based on the indoor environment defect characteristic images; and sending out early warning prompt information of the defects of the indoor environment under the condition that the defects exist in the indoor environment.
In this embodiment, the power plant combustible equipment video monitoring device 109 and the substation combustible equipment video monitoring device 209 are configured to collect combustible equipment video image information and send the combustible equipment video image information to the monitoring center server 300; the monitoring center server 300 is used for receiving video image information of the combustible equipment, extracting a state characteristic image of the combustible equipment from the received video image information of the combustible equipment, identifying a network model according to a pre-constructed defect characteristic of the combustible equipment, and identifying whether the combustible equipment has defects, wherein the defect characteristic identification network model of the combustible equipment adopts a deep learning algorithm and is established based on the defect characteristic image of the combustible equipment; and sending out early warning prompt information of the defects of the flammable equipment under the condition that the flammable equipment has the defects.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention.
Claims (10)
1. The utility model provides an electrical equipment intelligence video identification monitoring alarm system which characterized in that includes: the monitoring system comprises a power plant video monitoring system (100), a transformer substation video monitoring system (200) and a monitoring center server (300), wherein the power plant video monitoring system (100) and the transformer substation video monitoring system (200) are respectively in communication connection with the monitoring center server (300);
the power plant video monitoring system (100) comprises a power plant transformer video monitoring device (101), a power plant circuit breaker video monitoring device (102), a power plant current transformer video monitoring device (103), a power plant voltage transformer video monitoring device (104), a power plant lightning rod video monitoring device (105), a power plant insulator video monitoring device (106), a power plant disconnecting switch video monitoring device (107), a power plant indoor environment video monitoring device (108) and a power plant combustible equipment video monitoring device (109);
the transformer substation video monitoring system (200) comprises a transformer substation transformer video monitoring device (201), a transformer substation breaker video monitoring device (202), a transformer substation current transformer video monitoring device (203), a transformer substation voltage transformer video monitoring device (204), a transformer substation lightning rod video monitoring device (205), a transformer substation insulator video monitoring device (206), a transformer substation disconnecting switch video monitoring device (207), a transformer substation indoor environment video monitoring device (208) and a transformer substation flammable equipment video monitoring device (209).
2. The intelligent video identification monitoring and alarming system for the power equipment as claimed in claim 1, wherein the power plant transformer video monitoring device (101) and the substation transformer video monitoring device (201) are used for acquiring transformer video image information and transmitting the transformer video image information to the monitoring center server (300); the monitoring center server (300) is used for receiving the transformer video image information and extracting a transformer radiator oil pump fan image, a transformer oil way connecting part image, a transformer sleeve image, a transformer lead image, a transformer bus connecting part image and a transformer body thermal imaging image from the transformer video image information; identifying whether the transformer has defects or not according to a pre-constructed transformer defect feature identification network model, wherein the transformer defect feature identification network model is established by adopting a deep learning algorithm and based on a transformer radiator oil pump fan defect feature image, a transformer oil circuit connection part defect feature image, a transformer bushing defect feature image, a transformer lead defect feature image, a transformer bus connection part defect feature image and a transformer body thermal imaging defect feature image; and sending out transformer defect early warning prompt information under the condition that the transformer has defects.
3. The intelligent video identification monitoring alarm system for power equipment as claimed in claim 1, wherein the power plant circuit breaker video monitoring device (102) and the substation circuit breaker video monitoring device (202) are used for collecting circuit breaker video image information and sending the circuit breaker video image information to the monitoring center server (300); the monitoring center server (300) is used for receiving the circuit breaker video image information, extracting a circuit breaker switch on-off state characteristic image from the circuit breaker video image information, and identifying whether the circuit breaker has defects according to a pre-constructed circuit breaker defect characteristic identification network model, wherein the circuit breaker defect characteristic identification network model adopts a deep learning algorithm and is established on the basis of the circuit breaker defect characteristic image; and sending out early warning prompt information of the defects of the circuit breaker under the condition that the circuit breaker has the defects.
4. The intelligent video identification monitoring and alarming system for the power equipment as claimed in claim 1, wherein the power plant current transformer video monitoring device (103) and the substation current transformer video monitoring device (203) are used for acquiring current transformer video image information and transmitting the current transformer video image information to the monitoring center server (300); the monitoring center server (300) is used for receiving the video image information of the current transformer, extracting an infrared image of the current transformer, extracting and checking a fault area of the infrared image of the current transformer by using a superpixel segmentation method and an HSV color space, classifying and identifying fault positions of the current transformer through a current transformer fault deep learning model, and determining fault information of the current transformer according to different positions of faults of the current transformer; and sending out current transformer defect early warning prompt information under the condition that the current transformer has defects.
5. The intelligent video identification monitoring and alarming system for power equipment as claimed in claim 1, wherein the power plant voltage transformer video monitoring device (104) and the substation voltage transformer video monitoring device (204) are used for acquiring voltage transformer video image information and transmitting the voltage transformer video image information to a monitoring center server (300); the monitoring center server (300) is used for receiving the video image information of the voltage transformer, extracting an infrared image of the voltage transformer, extracting and checking a fault area of the infrared image of the voltage transformer by utilizing a superpixel segmentation method and an HSV color space, classifying and identifying fault positions of the voltage transformer through a fault deep learning model of the voltage transformer, and determining fault information of the voltage transformer according to different positions of faults of the voltage transformer; and sending out early warning prompt information of the defects of the voltage transformer under the condition that the voltage transformer has the defects.
6. The intelligent video identification monitoring and alarming system for the power equipment as claimed in claim 1, wherein the power plant lightning rod video monitoring device (105) and the substation lightning rod video monitoring device (205) are used for acquiring lightning rod video image information and transmitting the lightning rod video image information to the monitoring center server (300); the monitoring center server (300) is used for receiving lightning rod video image information, extracting a lightning rod state characteristic image from the lightning rod video image information, and identifying whether a lightning rod has a defect according to a pre-constructed lightning rod defect characteristic identification network model, wherein the lightning rod defect characteristic identification network model is established by adopting a deep learning algorithm and based on the lightning rod defect characteristic image; and sending lightning rod defect early warning prompt information under the condition that the lightning rod has defects.
7. The intelligent video identification monitoring and alarming system for power equipment as claimed in claim 1, wherein the power plant insulator video monitoring device (106) and the substation insulator video monitoring device (206) are used for acquiring insulator video image information and sending the insulator video image information to the monitoring center server (300); the monitoring center server (300) is used for receiving insulator video image information, extracting an insulator state characteristic image from the insulator receiving video image information, and identifying whether the insulator has defects or not according to a pre-constructed insulator defect characteristic identification network model, wherein the insulator defect characteristic identification network model is established by adopting a deep learning algorithm and based on the insulator defect characteristic image; and sending out early warning prompt information of the defects of the insulator under the condition that the insulator has the defects.
8. The intelligent video identification monitoring and alarming system for the power equipment as recited in claim 1, wherein the power plant disconnecting switch video monitoring device (107) and the substation disconnecting switch video monitoring device (207) are used for acquiring disconnecting switch video image information and transmitting the disconnecting switch video image information to the monitoring center server (300); the monitoring center server (300) is used for receiving the video image information of the disconnecting switch, extracting a state characteristic image of the disconnecting switch from the video image information of the disconnecting switch, and identifying whether the disconnecting switch has defects or not according to a pre-constructed defect characteristic identification network model of the disconnecting switch, wherein the defect characteristic identification network model of the disconnecting switch adopts a deep learning algorithm and is established on the basis of the defect characteristic image of the disconnecting switch; and sending out early warning prompt information of the defects of the isolating switch under the condition that the isolating switch has the defects.
9. The intelligent video identification monitoring and alarming system for the power equipment as claimed in claim 1, wherein the power plant indoor environment video monitoring device (108) and the substation indoor environment video monitoring device (208) are used for acquiring indoor environment video image information and transmitting the indoor environment video image information to the monitoring center server (300); the monitoring center server (300) is used for receiving indoor environment video image information, extracting indoor environment state characteristic images from the received indoor environment video image information, identifying whether defects exist in the indoor environment according to a pre-constructed indoor environment defect characteristic identification network model, wherein the indoor environment defect characteristic identification network model adopts a deep learning algorithm and is established based on the indoor environment defect characteristic images; and sending out early warning prompt information of the defects of the indoor environment under the condition that the defects exist in the indoor environment.
10. The intelligent video identification monitoring and alarming system for the power equipment as claimed in claim 1, wherein the power plant combustible equipment video monitoring device (109) and the substation combustible equipment video monitoring device (209) are used for acquiring combustible equipment video image information and transmitting the combustible equipment video image information to the monitoring center server (300); the monitoring center server (300) is used for receiving video image information of the combustible equipment, extracting a state characteristic image of the combustible equipment from the video image information of the combustible equipment, identifying whether the combustible equipment has defects according to a pre-constructed defect characteristic identification network model of the combustible equipment, wherein the defect characteristic identification network model of the combustible equipment adopts a deep learning algorithm and is established based on the defect characteristic image of the combustible equipment; and sending out early warning prompt information of the defects of the flammable equipment under the condition that the flammable equipment has the defects.
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| CN202110776139.5A CN113691014A (en) | 2021-07-09 | 2021-07-09 | Intelligent video identification monitoring alarm system for power equipment |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114264868A (en) * | 2021-11-30 | 2022-04-01 | 深圳飞音时代网络通讯技术有限公司 | Detection circuit and method for power receiving end equipment |
| CN115077605A (en) * | 2022-06-06 | 2022-09-20 | 昂顿科技（上海）有限公司 | Intelligent substation management system |
| CN116088398A (en) * | 2023-04-10 | 2023-05-09 | 中国电力工程顾问集团西南电力设计院有限公司 | Be used for wisdom prison dish alarm system of thermal power plant |
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2021
- 2021-07-09 CN CN202110776139.5A patent/CN113691014A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114264868A (en) * | 2021-11-30 | 2022-04-01 | 深圳飞音时代网络通讯技术有限公司 | Detection circuit and method for power receiving end equipment |
| CN114264868B (en) * | 2021-11-30 | 2023-10-20 | 深圳飞音时代网络通讯技术有限公司 | Detection circuit and method of power receiving end equipment |
| CN115077605A (en) * | 2022-06-06 | 2022-09-20 | 昂顿科技（上海）有限公司 | Intelligent substation management system |
| CN116088398A (en) * | 2023-04-10 | 2023-05-09 | 中国电力工程顾问集团西南电力设计院有限公司 | Be used for wisdom prison dish alarm system of thermal power plant |
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