CN113381331A - Intelligent inspection system for transformer substation - Google Patents

Intelligent inspection system for transformer substation Download PDF

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Publication number
CN113381331A
CN113381331A CN202110699999.3A CN202110699999A CN113381331A CN 113381331 A CN113381331 A CN 113381331A CN 202110699999 A CN202110699999 A CN 202110699999A CN 113381331 A CN113381331 A CN 113381331A
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inspection
robot
task
area
point
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CN113381331B (en
Inventor
李楠
翟东阔
刘广建
王磊
吴帅
邵乐乐
顾群
郭超
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State Grid Corp of China SGCC
Jining Power Supply Co of State Grid Shandong Electric Power Co Ltd
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State Grid Corp of China SGCC
Jining Power Supply Co of State Grid Shandong Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02B—BOARDS, SUBSTATIONS OR SWITCHING ARRANGEMENTS FOR THE SUPPLY OR DISTRIBUTION OF ELECTRIC POWER
    • H02B3/00—Apparatus specially adapted for the manufacture, assembly, or maintenance of boards or switchgear
    • 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
    • H02J13/00022—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 wireless data transmission
    • 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
    • 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
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • 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
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/16—Electric power substations
    • 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
    • Y04S40/126—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 using wireless data transmission

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Manufacturing & Machinery (AREA)
  • Manipulator (AREA)

Abstract

The utility model provides an intelligent inspection system for a transformer substation, which comprises a central control system, a plurality of inspection robots and an online monitoring device; the on-line monitoring equipment is connected with the comprehensive automatic system at the transformer substation end, acquires remote signaling and telemetry data of the comprehensive automatic system at the transformer substation end in real time and feeds the remote signaling and telemetry data back to the central control system in real time; the central control system comprises a task planning module and a path planning module; the task planning module comprises a special inspection module and a periodic inspection module, wherein the special inspection module is connected with online monitoring equipment and is used for acquiring remote signaling and remote measuring data of the comprehensive self-service system of the substation end in real time, judging whether to start a special inspection task and transmitting a judgment result to the path planning module; the periodic inspection module is used for setting a periodic inspection task and transmitting the periodic inspection task to the path planning module; whether the robot is started for special inspection is judged by acquiring remote signaling and remote measuring data of the comprehensive automatic system at the transformer substation end, so that the robot can be inspected in a targeted manner, and the inspection efficiency of the inspection robot is improved.

Description

Intelligent inspection system for transformer substation
Technical Field
The invention belongs to the technical field of transformer substation inspection, and particularly relates to an intelligent inspection system for a transformer substation.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Electric power is the most important production data in national economic development and the indispensable life data in people's life. Safe and stable power supply has very important significance for ensuring good and fast development of economic society. However, in the power transmission and transformation part, the power grid and the transformer substation are exposed in the field for a long time, and have great potential safety hazards. In order to prevent the occurrence of large-scale power grid accidents, the power transmission line and the transformer substation need to be regularly detected and maintained. However, at present, inspection work of a transformer substation starts to generally use robots for inspection work, but inspection tasks are mainly performed by using a single robot, and with the increase of the task amount, some transformer substations also perform cooperative work of a plurality of robots to improve inspection efficiency.
However, the inventor finds that, due to the limited range of motion of the robot, although a plurality of robots are used for inspection, the inspection of the whole substation equipment cannot be completely covered, so that the inspection efficiency of the substation is low, and the inspection result is greatly different from the actual inspection result.
Disclosure of Invention
In order to solve the defects of the prior art, the intelligent inspection system for the transformer substation is provided, whether the robot is started to perform special inspection or not is judged by acquiring remote signaling and telemetering data of a comprehensive self-monitoring system at the transformer substation end, so that the targeted inspection is facilitated, the inspection efficiency of the inspection robot is improved, meanwhile, the system can periodically perform full-coverage inspection on the transformer substation, and the comprehensive inspection on the transformer substation can be realized; the combination of the two inspection modes can efficiently realize inspection of the transformer substation.
In order to achieve the purpose, the following technical scheme is adopted in the disclosure:
in one or more embodiments, a substation intelligent inspection system includes: the system comprises a central control system, a plurality of inspection robots and online monitoring equipment;
the on-line monitoring equipment is connected with the comprehensive automatic system at the transformer substation end, acquires remote signaling and telemetry data of the comprehensive automatic system at the transformer substation end in real time and feeds the remote signaling and telemetry data back to the central control system in real time;
the inspection robot comprises a data acquisition device, a robot data processing device, a robot driving device and a robot communication device;
the central control system comprises a task planning module and a path planning module; the task planning module comprises a special inspection module and a periodic inspection module, wherein the special inspection module is connected with online monitoring equipment and is used for acquiring remote signaling and remote measuring data of the comprehensive self-service system of the substation end in real time, judging whether to start a special inspection task and transmitting a judgment result to the path planning module; the periodic inspection module is used for setting a periodic inspection task and transmitting the periodic inspection task to the path planning module;
the path planning module is respectively connected with the task planning module and the robot communication device, and determines an output planned path according to the inspection task of the task planning module based on a biological excitation neural network and a priority heuristic combination algorithm.
Compared with the prior art, the beneficial effect of this disclosure is:
the method judges whether to start the special inspection of the robot or not by acquiring the remote signaling and remote measuring data of the comprehensive self-monitoring system at the transformer substation end, so that the specific inspection is facilitated, the inspection efficiency of the inspection robot is improved, meanwhile, the system can periodically perform full-coverage inspection on the transformer substation, and the comprehensive inspection on the transformer substation can be realized; the combination of the two inspection modes can efficiently realize inspection of the transformer substation.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
Fig. 1 is a structural diagram of a substation intelligent inspection system in a first embodiment of the invention;
fig. 2 is an overall structure diagram of the inspection robot connected with the central control system in the first embodiment of the invention;
fig. 3 is a flowchart of a working method of the intelligent inspection system for the substation in the second embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
Example one
As shown in fig. 1-2, a transformer substation intelligent inspection system includes:
the system comprises a central control system, a plurality of inspection robots and online monitoring equipment;
the on-line monitoring equipment is connected with the comprehensive automatic system at the transformer substation end, acquires remote signaling and telemetry data of the comprehensive automatic system at the transformer substation end in real time, such as transformer substation monitoring video, environment monitoring data, fire alarm signals, security alarm signals, light power control signals and the like, and feeds the data back to the central control system in real time;
the inspection robot comprises a data acquisition device, a robot data processing device, a robot driving device and a robot communication device; wherein the content of the first and second substances,
the data acquisition device is used for acquiring visible light photos, infrared spectrums, health state information of equipment and environment information of the substation equipment; the robot data processing device is electrically connected with the data acquisition device, acquires and preprocesses substation equipment data acquired by the data acquisition device, and is also electrically connected with the robot driving device and used for sending a patrol task instruction of the central control system to the robot driving device; the robot driving device is used for driving the robot to move; in addition, the robot communication device is electrically connected with the robot data processing device and is also in communication connection with the central control system, so that the inspection robot and the central control system can transmit data and control instructions in a real-time and bidirectional mode.
The central control system comprises a path planning module, a task planning module, a patrol data analysis module and a patrol result display module; wherein the content of the first and second substances,
the task planning module is connected with the online monitoring equipment and is also divided into a special inspection module which is used for judging whether to start special inspection according to a real-time data signal of the online monitoring equipment and transmitting a judgment result to the path planning module; the periodic inspection module is used for setting a periodic inspection task and transmitting the periodic inspection task to the path planning module;
the path planning module is respectively connected with the task planning module and the robot communication device, determines an output planned path according to the inspection task of the task planning module based on a biological excitation neural network and a priority heuristic combination algorithm, specifically plans a multi-point inspection path according to special inspection, and plans a whole-area coverage inspection path according to periodic inspection.
The inspection data analysis module is respectively connected with the robot communication device and the inspection result display module and used for acquiring inspection data of the robot communication device, analyzing the inspection data and transmitting the result of the inspection data analysis to the inspection result display module.
In one embodiment, the inspection data analysis module is connected with the robot data processing device through the robot communication device, acquires the acquired data preprocessed by the robot data processing device in real time, analyzes the acquired data, generates a visual comprehensive display report, sends the visual comprehensive display report to the inspection result display module, and receives the visual comprehensive display report sent by the inspection data analysis module for display. It can be understood that the inspection result display module is connected with the display screen to display the visual comprehensive display report.
Specifically, the data acquisition device comprises an infrared camera, a visible light camera, a partial discharge sensor, an oil chromatograph, a breaker spring pressure sensor, a mechanical characteristic sensor, a temperature and humidity sensor and the like, the health state and the environmental information of the transformer substation equipment are jointly inspected and comprehensively sensed, the data information of the equipment is mastered and uploaded to the robot data processing device; the data acquisition device acquires the position information of the substation equipment while acquiring the information of the substation equipment and uploads the position information to the robot data processing device.
Specifically, the robot data processing device continuously processes data acquired by the data acquisition device, and continuously sends a processing result to a path planning module and a patrol data analysis module of the central control system through the robot communication device, and the path planning module continuously updates an optimized path according to the position information of the substation equipment sent by the data acquisition device; the inspection data analysis module analyzes the health state and the environmental information of the transformer substation equipment acquired by the data acquisition device, judges whether abnormality occurs or not and generates a visual comprehensive display report.
Specifically, the periodic inspection module sets a periodic trigger condition, namely, issues a task of comprehensive inspection of the transformer substation in a certain period, and the general period can be selected from days, weeks or months, and specifically can be selected according to the actual condition of the transformer substation; the special inspection module triggers the multi-point inspection task according to data information of substation equipment remote measurement remote signaling transmitted by online monitoring equipment, wherein the triggering condition of the multi-point inspection task can be the abnormity of substation monitoring video, environment monitoring data, fire alarm signals, security alarm signals and light power control signals, once the data is abnormal, the multi-point inspection task is triggered immediately, the special inspection module sends the multi-point inspection task to the path planning module, the path planning module determines an output planned path according to the inspection task of the task planning module based on a biostimulation neural network algorithm, the multi-point inspection path is planned according to the special inspection task, and the whole area coverage inspection path is planned according to the periodic inspection task.
Wherein, according to special task planning multiple spot task of patrolling and examining, specifically do:
s01: acquiring special routing inspection task information of a path planning module, and regarding routing inspection of each equipment point as a subtask j in a task area;
s02: the total cost T is required to be minimum on the premise of completing all subtasks of multi-point routing inspection in the task area, namely:
Figure RE-GDA0003213178170000061
in the formula, xijIndicates whether robot i is assigned to subtask j, and cij＝ω1Lij+ω2θijRepresents the cost, L, of the robot i to complete the subtask jijAnd thetaijRespectively representing the path length and the rotation angle, omega, of the completed task1，ω2Respectively representing the two coefficients, the situation that the number of subtasks is equal to the number of robots is considered in the text, and one subtask can only be allocated to one robot, namelyThe individual robot can only assign one task.
S03: in the known environment information, each robot gives the cost for completing each subtask based on a biological excitation neural network algorithm to form a cost table;
s04: the method comprises the following steps of (1) adopting a Hungarian algorithm to distribute multiple tasks, namely solving formula (1) to obtain an optimal task distribution scheme for robot routing inspection;
s05: the optimal task allocation plan according to step S04 is sent to the path planning module.
According to the periodic inspection task, planning a whole-area coverage inspection task, and specifically comprises the following steps:
s11: the method comprises the following steps of decomposing the whole target area to be patrolled and examined into a plurality of sub-areas, specifically:
decomposing the task area based on the tangent method of the position of the obstacle based on the map information in the known environment, and mainly aiming at decomposing the area to be patrolled into a plurality of subareas which do not contain the obstacle:
let the a-th obstacle be OaThe d-th equipment to be patrolled is EdAdding tangent lines intersecting with the obstacles or the boundaries in the vertical direction in the original map to form a plurality of sub-regions enclosed by the tangent lines, the obstacles, the boundaries, the equipment and the like, and making O ═ { O ═ O { (O)1O2...OkDenotes all the obstacle regions, E ═ E1E2...EmDenotes all the device areas, N ═ oeu E denotes an unreachable area, and an unreachable area connected to the map boundary is denoted as Ne(ii) a If the tangent line q ═ a, q ═ d intersects the same unreachable region at point paAnd pdThe maximum point of the two ordinate is called the upper boundary point and is recorded as
Figure RE-GDA0003213178170000071
The minimum point is called the lower boundary point and is recorded as
Figure RE-GDA0003213178170000072
The method comprises the steps of firstly dividing a known map into an area A with the outermost periphery not containing obstacles and an area B with the inner ring containing obstacles and equipment, taking the area A as an obstacle-free area to be separately distributed to operation robots for inspection, and then regarding the area B as a new map with inaccessible areas and connected boundaries to operate according to an area decomposition algorithm in a table 1.
TABLE 1 region decomposition Algorithm
Figure RE-GDA0003213178170000073
Figure RE-GDA0003213178170000081
S12: distributing a plurality of sub-areas to each robot, specifically:
after the inspection area is divided into a plurality of sub-areas according to the step S11, distributing the sub-areas to each mobile robot; the number of sub-regions I obtained by the region decomposition method of step S11 is fixed, so that in the multi-robot cooperative inspection, the number of robots n and the number of divided sub-regions I have two possibilities of n ≧ I and n < I.
When n is larger than or equal to I, namely the number of the robots is larger than that of the sub-areas, each sub-area is randomly allocated to one robot, so that each area can be divided into one robot, the robots finish the inspection task in the task area, but the allocation mode can cause some robots to be idle and cause resource waste, and therefore the method is only suitable for the condition that the area of the sub-areas is small. When the sub-area is large, the sub-area can be decomposed again according to the same area mode, the decomposed area is distributed to the idle robots, and then the multiple robots can cooperate to complete the routing inspection task of the sub-area.
When n is less than I, when each sub-area can not be divided into one robot, some robots need to allocate a plurality of sub-areas, and the area inspection task can be completed by allocating a plurality of sub-areas with smaller connection areas to a single robot.
S13: and sending the routing inspection task obtained in the step S12 to a path planning module.
The inspection task based on the biological excitation neural network and the priority heuristic combined algorithm according to the task planning module specifically comprises the following steps:
the system adopts a grid map, and map information is represented by two values. After the tasks are distributed to the robots, the robots move to the inspection subareas, and the inspection tasks of the target areas are achieved according to a certain mode. The path of the robot is planned according to a method based on the combination of a priority heuristic and a biostimulation neural network, wherein the priority heuristic algorithm is responsible for the problem of selecting the path when the robot normally runs, and the biostimulation neural network algorithm is mainly used for processing the problem of selecting the path when the robot enters a dead zone.
Priority heuristic algorithm: the method ranks the neuron priorities in the neighborhood, and two heuristic algorithms with different priority sequences are designed in the method and respectively correspond to different types of maps, and for the terrain with large length-width ratio of the map, a first priority sequence is adopted: no → e → w → s → noe → now → se → sw, whereas the second priority order is adopted: w → s → sw → nw → no → e → se → noe, where no, e, w, s represent north, east, west, south directions, respectively.
Bio-excitation neural network: after the robot completes the inspection task at a certain point, if the positions of 8 peripheral nerve cells are inspection regions or inaccessible regions, the robot enters a dead zone state. In this case, the robot scans whether an area which is not inspected yet exists in the sub-area, if so, an optimal path from the dead zone point to each non-inspection point is drawn according to the biostimulation neural network algorithm, then the minimum cost F of each non-inspection point is compared according to the formula (2), and the path point with the minimum cost is selected as the next inspection point of the robot.
Fg＝min cos tg＝min f(Mg,Dg)＝min((εMgs+ηDgs,s＝1,2,3...z)) (2)
In the formula, g represents a point which is not patrolled in a target area, and M and D respectively represent indexes for measuring the quality of a path: path length and total steering angle; and coefficients representing the two, respectively, z represents the number of possible paths from the dead point to the g-th non-patrol point.
Specifically, the robot driving device is connected with the robot data processing device to obtain an inspection path instruction of the movement of the robot; the robot data processing device is connected with the path planning module through the communication processing device to obtain the routing inspection path instruction of the robot.
In one embodiment, when the inspection robot needs to return to a parking point after completing the inspection task, the inspection robot firstly reaches the position near the GPS coordinates of the preset parking point. However, because the GPS has a certain precision error, the inspection robot may deviate from the preset parking point, and the robot data processing device may calculate the offset of the current position according to the visual characteristics of the preset parking point, and continuously feed the result back to the robot driving device, thereby realizing accurate return of the inspection robot.
The robot communication device is used for communication between the inspection robot and the central control system. It can be understood that the robot communication device can send the state information of the inspection robot to the central control system in real time at a frequency of not less than 2 Hz. Meanwhile, the robot communication device receives one or more of the visible light image, the infrared image and the state information of the inspection robot transmitted by the data acquisition device and then sends the images to the central control system in real time. It can be understood that the robot communication device can receive the state control or parameter adjustment commands of the central control system and transmit the commands to the robot driving device in real time through the robot data processing device. The robot communication device can transmit information based on a wireless transmission module and/or a 4G communication device between the inspection robot and the central control system.
It can be understood that the data transmission relationship between the inspection robot and the central control system is set according to the operation habit of the user, the motion state presentation mode, the module management complexity and the organization mode of each module.
In one embodiment, the inspection data analysis module is connected with the robot data processing device through the robot communication device, acquires data preprocessed by the robot data processing device on the data acquisition device in real time, analyzes the data to generate a visual comprehensive display report, sends the visual comprehensive display report to the inspection result display module, and the inspection result display module receives and displays the visual comprehensive display report sent by the inspection data analysis module. It can be understood that the inspection result display module is connected with the display screen to display the visual comprehensive display report.
In one embodiment, the central control system can be a PC ground station, the main control chip adopts a singlechip, and the singlechip is provided with a path planning module, a task planning module, a routing inspection data analysis module and a routing inspection result display module; it can be understood that the robot communication device further comprises a wireless transmission module which is in communication connection with the robot communication device and/or an interface or a serial port of the 4G communication device.
The embodiment judges whether to start the special routing inspection of the robot or not by acquiring remote signaling and remote measuring data of the comprehensive self-monitoring system at the transformer substation end, so that the specific routing inspection is facilitated, the routing inspection efficiency of the routing inspection robot is improved, meanwhile, the system can periodically perform full-coverage routing inspection on the transformer substation, and the comprehensive routing inspection on the transformer substation can be realized; the combination of the two inspection modes can efficiently realize inspection of the transformer substation.
Example two
The embodiment shown in fig. 3 provides a working method of a substation intelligent inspection system, which includes:
step 1: a special routing inspection module in a task planning module of a central control system is connected with an online monitoring device, remote signaling telemetry data of a comprehensive self-system of a substation end is obtained in real time, whether the special routing inspection task is started or not is judged, a judgment result is transmitted to a path planning module, and once the remote signaling telemetry data of the comprehensive self-system of the substation end is abnormal, a multi-point routing inspection task is triggered immediately;
step 2: the path planning module determines an output planned path according to the inspection task of the task planning module based on a biological excitation neural network and a priority heuristic combined algorithm, and sends the determined planned path to the robot communication device;
and step 3: the robot communication device sends an inspection task instruction of the central control system to the robot driving device, and the robot driving device drives the robot to perform inspection;
and 4, step 4: the transformer substation equipment data acquired by the data acquisition device is not sent to the robot data processing device, the robot data processing device preprocesses the transformer substation equipment data acquired by the data acquisition device and sends the transformer substation equipment data to the robot communication device, and the robot communication device sends the processed transformer substation equipment data to the patrol data analysis module;
and 5: the inspection data analysis module is connected with the robot data processing device through the robot communication device, acquires the acquired data preprocessed by the data acquisition device in real time by the robot data processing device, analyzes the acquired data, generates a visual comprehensive display report, and sends the visual comprehensive display report to the inspection result display module;
and the inspection result display module receives and displays the visual comprehensive display report sent by the inspection data analysis module.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. The utility model provides a transformer substation's intelligence system of patrolling and examining which characterized in that includes: the system comprises a central control system, a plurality of inspection robots and online monitoring equipment;
the on-line monitoring equipment is connected with the comprehensive automatic system at the transformer substation end, acquires remote signaling and telemetry data of the comprehensive automatic system at the transformer substation end in real time and feeds the remote signaling and telemetry data back to the central control system in real time;
the inspection robot comprises a data acquisition device, a robot data processing device, a robot driving device and a robot communication device;
the central control system comprises a task planning module and a path planning module; the task planning module comprises a special inspection module and a periodic inspection module, wherein the special inspection module is connected with online monitoring equipment and is used for acquiring remote signaling and remote measuring data of the comprehensive self-service system of the substation end in real time, judging whether to start a special inspection task and transmitting a judgment result to the path planning module; the periodic inspection module is used for setting a periodic inspection task and transmitting the periodic inspection task to the path planning module;
the path planning module is respectively connected with the task planning module and the robot communication device, and determines an output planned path according to the inspection task of the task planning module based on a biological excitation neural network and a priority heuristic combination algorithm.
2. The intelligent substation inspection system according to claim 1, wherein the robot data processing device is electrically connected with the data acquisition device, acquires and preprocesses substation equipment data acquired by the data acquisition device, and is also electrically connected with the robot driving device and used for sending an inspection task instruction of the central control system to the robot driving device; the robot communication device is electrically connected with the robot data processing device and is also in communication connection with the central control system, so that the inspection robot and the central control system can bidirectionally transmit data and control instructions in real time;
the data acquisition device comprises an infrared camera, a visible light camera, a partial discharge sensor, an oil chromatograph, a breaker spring pressure sensor, a mechanical characteristic sensor and a temperature and humidity sensor;
the data acquisition device is used for acquiring visible light photos, infrared spectrums, health state information of equipment and environmental information of the substation equipment.
3. The substation intelligent inspection system according to claim 1, wherein the central control system further comprises an inspection data analysis module, the inspection data analysis module is connected with the robot data processing device through the robot communication device, acquires the acquired data preprocessed by the robot data processing device in real time, analyzes the acquired data, generates a visual comprehensive display report, and sends the visual comprehensive display report to the inspection result display module;
and the inspection result display module receives and displays the visual comprehensive display report sent by the inspection data analysis module.
4. The substation intelligent inspection system according to claim 1, wherein the periodic inspection module is configured to set a periodic inspection task, plan a full-area coverage inspection task according to the periodic inspection task, transmit the coverage inspection task to the path planning module, and send the coverage inspection task to the path planning module;
the special inspection module plans a multi-point inspection task according to the special inspection task, triggers the multi-point inspection task according to remote signaling remote measuring data of the comprehensive self-system of the transformer substation end transmitted by the on-line monitoring equipment, triggers the multi-point inspection task immediately once the remote signaling remote measuring data of the comprehensive self-system of the transformer substation end is abnormal, and sends the multi-point inspection task to the path planning module.
5. The substation intelligent inspection system according to claim 4, wherein the periodic inspection module plans the full-area coverage inspection task according to the periodic inspection task, and specifically comprises:
s11: decomposing the whole target area to be inspected into a plurality of sub-areas;
s12: after the inspection area is divided into a plurality of sub-areas according to the step S11, distributing the sub-areas to each mobile robot according to the relation between the number of the robots and the number of the divided sub-areas;
s13: and sending the routing inspection task obtained in the step S12 to a path planning module.
6. The substation intelligent inspection system according to claim 4, wherein the special inspection module plans the multi-point inspection task according to the special inspection task, and specifically comprises:
s01: acquiring special routing inspection task information of a path planning module, and regarding routing inspection of each equipment point as a subtask j in a task area;
s02: the total cost T is required to be minimum on the premise of completing all subtasks of multi-point routing inspection in the task area, namely:
Figure FDA0003129433260000031
Figure FDA0003129433260000032
Figure FDA0003129433260000033
xij＝0 or 1，i，j∈{1，...，n} (1)
in the formula, xijIndicates whether robot i is assigned to subtask j, and cij＝ω1Lij+ω2θijRepresents the cost, L, of the robot i to complete the subtask jijAnd thetaijRespectively representing the path length and the rotation angle, omega, of the completed task1，ω2The two coefficients are respectively expressed, the situation that the number of the subtasks is equal to the number of the robots is considered, one subtask can be distributed to only one robot, and one robot can be distributed to only one task.
S03: in the known environment information, each robot gives the cost for completing each subtask based on a biological excitation neural network algorithm to form a cost table;
s04: the method comprises the following steps of (1) adopting a Hungarian algorithm to distribute multiple tasks, namely solving formula (1) to obtain an optimal task distribution scheme for robot routing inspection;
s05: the optimal task allocation plan according to step S04 is sent to the path planning module.
7. The substation intelligent inspection system according to claim 5, wherein the whole target area to be inspected is decomposed into a plurality of sub-areas, specifically:
decomposing the task area based on the tangent method of the position of the obstacle based on the map information in the known environment, and mainly aiming at decomposing the area to be patrolled into a plurality of subareas which do not contain the obstacle:
let the a-th obstacle be OaThe d-th equipment to be patrolled is EdAdding tangent lines intersecting with the obstacles or the boundaries in the vertical direction in the original map to form a plurality of sub-regions enclosed by the tangent lines, the obstacles, the boundaries, the equipment and the like, and making O ═ { O ═ O { (O)1O2...OkDenotes all the obstacle regions, E ═ E1E2...EmDenotes all the device areas, N ═ oeu E denotes an unreachable area, and an unreachable area connected to the map boundary is denoted as Ne(ii) a If the tangent line q ═ a, q ═ d intersects the same unreachable region at point paAnd pdThe maximum point of the two ordinate is called the upper boundary point and is recorded as
Figure FDA0003129433260000041
The minimum point is called the lower boundary point and is recorded as
Figure FDA0003129433260000042
The known map is divided into an area A with the outermost periphery not containing obstacles and an area B with the inner ring containing obstacles and equipment, the area A is taken as an area without obstacles and is separately distributed to an operation robot for inspection, and the area B is taken as a new map with an inaccessible area and connected with boundaries to operate according to an area decomposition algorithm.
8. The substation intelligent inspection system according to claim 7, wherein the region decomposition algorithm specifically comprises:
step1 in the new map B, continue with the tangent line q ═ h in the q direction, sweep the target area through the tangent line;
step2if meet OaJudgment of OaWhether or not it belongs to NeIf yes, skipping step8, otherwise, continuing;
step3 records the tangent and the obstacle OaIf the tangent point is the upper intersection point, step6 is switched, otherwise, the process continues;
step4 remembers the intersection as
Figure FDA0003129433260000043
From point
Figure FDA0003129433260000044
Making a vertical line downwards if the vertical line is in contact with other unreachable regions NdIntersect, note the point of intersection as pdConnection point
Figure FDA0003129433260000045
And pdOtherwise, continuing;
step5 if there is no other NdIntersect, i.e. denote the intersection with the x-axis and paxPoints, connection points
Figure FDA0003129433260000046
And pax(ii) a Otherwise, skipping step 8;
step6 remembers the intersection as
Figure FDA0003129433260000051
From point
Figure FDA0003129433260000052
Making a vertical line upwards if the vertical line is not in contact with other unreachable regions NdIntersect, note the point of intersection as pdConnection point
Figure FDA0003129433260000053
And pdOtherwise, continuing;
step7 if there is no other NdIntersect, then record ymaxCross over with pymaxPoints, connection points
Figure FDA0003129433260000054
And pymax；
step8 judges that q is more than or equal to qmaxIf so, the calculation is terminated, otherwise step1 is skipped.
9. The substation intelligent inspection system according to claim 5, wherein the sub-areas are allocated to the mobile robots according to the relationship between the number of the robots and the number of the divided sub-areas, specifically:
the number n of the robots and the data I of the divided sub-areas have two relations of n being more than or equal to I and n being less than I,
when n is larger than or equal to I, namely the number of the robots is larger than that of the sub-areas, each sub-area is randomly allocated to one robot, so that each area can be divided into one robot, the robots finish the inspection task in the task area, but the allocation mode can cause some robots to be idle and cause resource waste, and therefore the method is only suitable for the condition that the area of the sub-areas is small. When the sub-area is large, the sub-area can be decomposed again according to the same area mode, the decomposed area is distributed to the idle robots, and then the multiple robots can cooperate to complete the routing inspection task of the sub-area.
When n is less than I, when each sub-area can not be divided into one robot, some robots need to allocate a plurality of sub-areas, and the area inspection task can be completed by allocating a plurality of sub-areas with smaller connection areas to a single robot.
10. The substation intelligent inspection system according to claim 1, wherein the inspection task based on the biostimulation neural network and the priority heuristic combined algorithm according to the task planning module specifically comprises:
for the terrain with large length-width ratio of the map, a first priority order is adopted: no → e → w → s → noe → now → se → sw, whereas the second priority order is adopted: w → s → sw → nw → no → e → se → noe, wherein no, e, w, s respectively represent north, east, west, south directions;
according to the priority relationship, an inspection path of the inspection robot is obtained by combining the inspection tasks sent by the task planning module; the routing inspection path is represented in the form of uniformly distributed coordinate points.
After the inspection robot finishes an inspection task at a certain point, if the positions of 8 peripheral nerve cells are inspection regions or inaccessible regions, the robot enters a dead zone state;
in this case, the robot scans whether an area which is not inspected yet exists in the sub-area, if so, an optimal path from the dead zone point to each inspection point is drawn according to the biostimulation neural network algorithm, then the minimum cost F of each inspection point is compared according to the formula (2), and the path point with the minimum cost is selected as the next inspection point of the robot;
Fg＝min costg＝minf(Mg,Dg)＝min((εMgs+ηDgs,s＝1,2,3...z)) (2)
in the formula, g represents a point which is not patrolled in a target area, and M and D respectively represent indexes for measuring the quality of a path: path length and total steering angle; and coefficients representing the two, respectively, z represents the number of possible paths from the dead point to the g-th non-patrol point.
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