CN113991837A - Protection device intelligence inspection system based on many first perception techniques - Google Patents
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- 238000007689 inspection Methods 0.000 title claims abstract description 26
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- 238000004458 analytical method Methods 0.000 claims abstract description 15
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- 239000013307 optical fiber Substances 0.000 claims description 6
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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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- 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
- H02J13/00006—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
- H02J13/00016—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 using a wired telecommunication network or a data transmission bus
- H02J13/00017—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 using a wired telecommunication network or a data transmission bus using optical fiber
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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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- Engineering & Computer Science (AREA)
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- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
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Abstract
The invention discloses a protection device intelligent patrol system based on a multivariate perception technology, which comprises: the device comprises a device perception layer, a network interconnection layer, an analysis application layer and a platform sharing layer, wherein the device perception layer comprises: the infrared camera and the multi-element sensing device; the network interconnection layer comprises: the system comprises a station control layer central switch, a hard disk video recorder and an intelligent local module; the analysis application layer includes: the image recognition host and the secondary intelligent inspection device; the platform sharing layer comprises a cloud platform and a regulation and control system. The intelligent patrol system of the protection device based on the multi-element sensing technology can integrate and utilize information of different dimensions for discovering equipment and loop abnormity and carrying out early warning, realizes quick response of defects of the protection device and accurate positioning of hidden dangers, improves the patrol working efficiency of secondary equipment, and really realizes unmanned or less-humanized patrol.
Description
Technical Field
The invention relates to an intelligent patrol system of a protection device based on a multivariate perception technology, belonging to the technical field of intelligent patrol systems.
Background
Along with the enhancement of electric wire netting, transformer substation and relay protection device's quantity increases by a wide margin, and relay protection fortune dimension personnel's daily work load of patrolling has already tended to the saturation, but in order to ensure relay protection device safe and reliable operation, regularly patrols protection device and is indispensable again, because the guarantee rate of the safe operation of electric wire netting constantly improves, the mode of patrolling also by normal inspection, develops to turn off the light inspection, patrol comprehensively, special inspection etc..
Therefore, the existing patrol method cannot meet the high-quality patrol mode without dead angles, and a new intelligent patrol system must be designed to ensure that the existing protection device can be better ensured.
Disclosure of Invention
The purpose is as follows: in order to solve the problems of the prior patrol method in the prior art, the invention provides the intelligent patrol system of the protection device based on the multivariate perception technology, and lays a foundation for unmanned or few patrol of relay protection.
The technical scheme is as follows: in order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a protection device intelligent patrol system based on a multivariate perception technology comprises: the device comprises an equipment sensing layer, a network interconnection layer and an analysis application layer;
the device sensing layer includes: infrared camera, many first sensing devices, infrared camera and many first sensing devices are installed on from running gear, patrol on secondary equipment screen cabinet inside and outside track from running gear, realize the monitoring to in-cabinet device, return circuit and the outer environment of cabinet, collect the required data of intelligent tour system.
The network interconnection layer comprises: station control layer central switch, digital video recorder, intelligent local module. And the central switch of the station control layer acquires the online monitoring data and the alarm information of the protection device and then uploads the online monitoring data and the alarm information to the secondary intelligent inspection device of the analysis application layer. The hard disk video recorder is used for being connected with the infrared camera, storing and uploading images to the image recognition host. The intelligent on-site module sends the information collected by the multiple sensing devices to the secondary intelligent inspection device.
The analysis application layer includes: image identification host computer, secondary intelligence inspection device. And the image recognition host detects the images collected and sent by the hard disk video recorder by adopting a convolutional neural network model. Aiming at different image contents of patrol, the states of a protection device, a switch handle, a pressing plate, a terminal row wiring, a grounding copper plate, a cable state, an optical fiber state, a spare optical fiber dustproof cap, a screen cabinet plugging and a screen cabinet foreign matter are identified. The secondary intelligent inspection device utilizes the online monitoring data of the protection device and the image recognition result output by the image recognition host, judges the running state and the change trend of the protection device by adopting homologous comparison and trend analysis, and automatically recognizes the dominant and recessive faults of the protection device. The possible fault position judged by the alarm signal is moved to the abnormal equipment and the possible fault position by the self-walking device to acquire images, so that operation and maintenance personnel are assisted to troubleshoot faults.
As a preferred scheme, the system further comprises a platform sharing layer, wherein the platform sharing layer comprises a cloud platform and a regulation and control system, and a scheduling data network uploads the related information to a scheduling end to provide data support for the regulation and control system and the advanced application of the cloud platform.
Preferably, the multivariate sensing device comprises: temperature and humidity sensor, smoke detector.
Preferably, the convolutional neural network model comprises three convolutional layers and three pooling layers.
Preferably, the convolutional layer adopts a depth separable convolution formula, and the depth separable convolution formula is as follows:
KS×KS×C×Q
wherein, KSC is the number of channels, Q is the number of convolution kernels, the convolution kernels of the three depth separable convolutions are 2, 3 and 4 respectively, and the number of convolution kernels is 8, 16 and 16 respectively.
Preferably, the down-sampling ratios of the pooling layers are all 2.
Preferably, the image recognition host further comprises a target detection model, wherein the target detection model is used for labeling the image recognition result, and the target detection model adopts a Fasterr-cnn structure.
Has the advantages that: the intelligent patrol system of the protection device based on the multi-element sensing technology can integrate and utilize information of different dimensions for discovering equipment and loop abnormity and carrying out early warning, realizes quick response of defects of the protection device and accurate positioning of hidden dangers, improves the patrol working efficiency of secondary equipment, and really realizes unmanned or less-humanized patrol.
Drawings
FIG. 1 is a block diagram of the system of the present invention.
Fig. 2 is a flow diagram of a system specific data signal of the present invention.
FIG. 3 is an abstract flow diagram of the system of the present invention.
FIG. 4 is a flow chart for image detection using an image feature model.
Detailed Description
The present invention will be further described with reference to the following examples.
A protection device intelligent patrol system based on a multivariate perception technology comprises: the system comprises an equipment sensing layer, a network interconnection layer, an analysis application layer and a platform sharing layer, and automatic inspection of the protection device is realized by applying an image recognition technology and an intelligent inspection and fault diagnosis technology.
Wherein the device sensing layer comprises: infrared camera, many first sensing devices, infrared camera and many first sensing devices are installed on from running gear, patrol on secondary equipment screen cabinet inside and outside track from running gear, realize the monitoring to in-cabinet device, return circuit and the outer environment of cabinet, collect the required data of intelligent tour system. The multivariate sensing device comprises: temperature and humidity sensor, smoke detector.
Wherein, the network interconnection layer includes: station control layer central switch, digital video recorder, intelligent local module. And the central switch of the station control layer acquires the online monitoring data and the alarm information of the protection device and then uploads the online monitoring data and the alarm information to the secondary intelligent inspection device of the analysis application layer. The hard disk video recorder is used for being connected with the high-definition infrared camera, storing and uploading images to the image recognition host. The intelligent on-site module sends the information collected by the multiple sensing devices to the secondary intelligent inspection device.
Wherein, the analysis application layer comprises: image identification host computer, secondary intelligence inspection device. And the image recognition host detects the images collected and sent by the hard disk video recorder by adopting a convolutional neural network model. Aiming at different image contents of patrol, the states of a protection device, a switch handle, a pressing plate, a terminal row wiring, a grounding copper plate, a cable, an optical fiber, a spare optical fiber dustproof cap, a screen cabinet plug and a screen cabinet foreign body are identified, and corresponding convolutional neural network models are trained respectively.
Under the condition of ensuring the accuracy, the convolutional neural network model provided by the invention comprises three convolutional layers and three pooling layers, wherein the convolutional layers adopt deep separable convolution. As shown in equation 1, is a standard convolution equation:
KS×KS×C+C×Q (1)
KSis the size of the convolution kernel, C is the number of channels, and Q is the number of convolution kernels.
Compared with the standard convolution, the depth separable convolution has less parameter quantity, as shown in formula 2, the depth separable convolution firstly considers the region and then considers the channel, and the separation of the channel and the region is realized.
KS×Ks×C×Q (2)
In the formula, KSThe convolution layers in the model respectively adopt K for the size of convolution kernel, C for the number of channels and Q for the number of convolution kernelsSSmall convolution kernels of 2, 3, 4 and the number Q of convolution kernels is 8, 16, respectively.
In addition, the down-sampling ratios of the pooling layers are all 2, so that the image needs to pass through KS2 deep convolution, normalization layer, activation layer, KSThe layers are stacked three times, 1 point-by-point convolution, normalization, activation, and then pooling, resulting in the final feature map. The small convolution kernel is adopted because the small convolution kernel can reduce the operation amount, increase the model reasoning speed, and fully consider the situations of different inspection project identification tasks and the acquired image samples with the resolution of 800 multiplied by 600, and after a plurality of experiments, when the layer number of the image feature extraction model is 6, the features extracted by the model have good detail information and semantic information. In addition, the number of samples input in each training is unified to be 50, and the testing accuracy of different trained inspection project models can be kept to be more than 96%.
The secondary intelligent inspection device utilizes the online monitoring data of the protection device and the image recognition result output by the image recognition host, judges the running state and the change trend of the protection device by adopting homologous comparison and trend analysis, and automatically recognizes the dominant and recessive faults of the protection device. The possible fault position judged by the alarm signal is moved to the abnormal equipment and the possible fault position by the self-walking device to acquire images, so that operation and maintenance personnel are assisted to troubleshoot faults.
The platform sharing layer comprises a cloud platform and a regulation and control system, and the scheduling data network transmits related information to the scheduling end to provide data support for the D5000 regulation and control system and the advanced application of the cloud platform.
Example 1:
as shown in fig. 2 to 4, an intelligent patrol system for a protection device based on a multivariate perception technology includes an equipment perception layer, a network interconnection layer, an analysis application layer, and a platform sharing layer.
The data flow is mainly divided into three paths: the first path is that the alarm information of the secondary equipment on-line monitoring and analyzing system is respectively transmitted to the monitoring host and the secondary intelligent inspection device through the station control layer central switch; the second path is that images are collected through a high-definition camera and an infrared camera and then stored in a hard disk video recorder, an image recognition host acquires image data from the hard disk video recorder for target detection, and a detection result is uploaded to a secondary intelligent inspection device; the third way is that the intelligent on-site module containing the temperature and humidity sensor and the smoke detector transmits the collected environmental information to the secondary intelligent inspection device. The secondary intelligent inspection device comprehensively utilizes multidimensional data, and is more favorable for detecting the state of the device and troubleshooting.
The convolutional neural network model in the image recognition host has fewer parameters and smaller calculated amount under the condition of ensuring the accuracy, and the detection speed is greatly improved. In addition, an object detection model is also included, the object detection model is based on fast r-cnn, the detection algorithm involves an anchor mechanism, the number of anchor frames which are foreground is usually small, most of the anchor frames are background anchor frames, and therefore samples of the foreground and the background are unbalanced. The imbalance of samples leads the model to be prone to the category with a large number of samples, which leads to the reduction of the generalization capability of the model, and therefore, the local loss is introduced in the final classification stage, as shown in formula 3, the principle is to assign weights to the loss of different categories.
FL(pt)＝-αt(1-pt)γlog(pt) (3)
As shown in formula alphatUsed to adjust the class weights, and gamma is used to adjust the weights of different difficult and easy samples, so that the model can focus on the difficult samples more quickly, and t represents different classes.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.
Claims (7)
1. The utility model provides a protection device intelligence system of patrolling based on many first perception techniques which characterized in that: the method comprises the following steps: the device comprises an equipment sensing layer, a network interconnection layer and an analysis application layer;
the device sensing layer includes: the infrared camera and the multi-element sensing device are mounted on the self-walking device, and the self-walking device patrols the inner and outer rails of the secondary equipment screen cabinet, so that monitoring of the inner equipment, the loop and the environment outside the cabinet is realized, and data required by an intelligent patrol system is collected;
the network interconnection layer comprises: the system comprises a station control layer central switch, a hard disk video recorder and an intelligent local module; after acquiring online monitoring data and alarm information of the protection device, the central switch of the station control layer uploads the online monitoring data and the alarm information to a secondary intelligent inspection device of an analysis application layer; the hard disk video recorder is used for connecting the infrared camera, storing and uploading images to the image recognition host; the intelligent on-site module uploads the information collected by the multiple sensing devices to the secondary intelligent inspection device;
the analysis application layer includes: the image recognition host and the secondary intelligent inspection device; the image recognition host detects images collected and sent by the hard disk video recorder by adopting a convolutional neural network model; aiming at different image contents of patrol, identifying the states of a protection device, a switch handle, a pressing plate, a terminal row wiring, a grounding copper plate, a cable state, an optical fiber state, a spare optical fiber dustproof cap, a screen cabinet blockage and screen cabinet foreign matters; the secondary intelligent inspection device judges the running state and the change trend of the protection device by utilizing the online monitoring data of the protection device and the image recognition result output by the image recognition host and adopting homologous comparison and trend analysis, and automatically recognizes the dominant and recessive faults of the protection device; the possible fault position judged by the alarm signal is moved to the abnormal equipment and the possible fault position by the self-walking device to acquire images, so that operation and maintenance personnel are assisted to troubleshoot faults.
2. The intelligent patrol system for protection devices based on multivariate perception technology as claimed in claim 1, wherein: the system further comprises a platform sharing layer, wherein the platform sharing layer comprises a cloud platform and a regulation and control system, the relevant information is uploaded to a scheduling end through a scheduling data network, and data support is provided for the regulation and control system and advanced applications of the cloud platform.
3. The intelligent patrol system for protection devices based on multivariate perception technology as claimed in claim 1, wherein: the multivariate sensing device comprises: temperature and humidity sensor, smoke detector.
4. The intelligent patrol system for protection devices based on multivariate perception technology as claimed in claim 1, wherein: the convolutional neural network model comprises three convolutional layers and three pooling layers.
5. The intelligent patrol system for protection devices based on multivariate perception technology as claimed in claim 4, wherein: the convolutional layer adopts a depth separable convolution formula as follows:
KS×KS×C×Q
wherein, KSC is the number of channels, Q is the number of convolution kernels, the convolution kernels of the three depth separable convolutions are 2, 3 and 4 respectively, and the number of convolution kernels is 8, 16 and 16 respectively.
6. The intelligent patrol system for protection devices based on multivariate perception technology as claimed in claim 4, wherein: the pooling layer down-sampling ratios are all 2.
7. The intelligent patrol system for protection devices based on the multivariate perception technology as claimed in any one of claims 1 to 6, wherein: the image recognition host further comprises a target detection model, the target detection model is used for labeling the image recognition result, and the target detection model adopts a Faster r-cnn structure.
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