Intelligent supervision system and method for in-station safe operation and operation and maintenance of transformer substation

Abstract

The invention discloses an intelligent supervision system and method for safe operation and operation and maintenance in a transformer substation, and relates to the technical field of supervision in the transformer substation, and the system comprises a transformer substation image acquisition module, a safety supervision unit, an early warning terminal and a database. Secondly, monitoring the intelligent robot to inspect the transformer substation, monitoring whether the inspection in the transformer substation corresponding to the intelligent robot is in safe operation or not, and analyzing to obtain a safe operation mode of the inspection in the transformer substation corresponding to the intelligent robot so as to guarantee the basic safety of the inspection in the transformer substation corresponding to the intelligent robot; the corresponding real-time operation and maintenance condition in the transformer substation can be monitored more comprehensively only on the basis of ensuring the inspection safety operation, so that the corresponding safety operation of the transformer substation is maintained, the service life of the intelligent robot is prolonged, and the application damage of the intelligent robot is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of in-station supervision of substations, and in particular to a system and method for intelligent supervision of safe operation and operation and maintenance in substations. Background Art

[0002] Substations are indispensable in our daily life, so it is necessary to carry out corresponding intelligent supervision on the inspection safety in substations in order to ensure the corresponding operation and maintenance stability and inspection safety of substations. First, we need to understand the basic phenomena in the substation, and then perform corresponding self-inspections on the inspection robots to confirm that the robots are in full marks so as to perform the corresponding inspection tasks in the substation. At the same time, we need to monitor whether the inspection robots are in a safe inspection state during the inspection, so as to ensure the inspection safety of the robots and maintain the safe operation of the substations at all times.

[0003] Prior art, such as the invention patent application with announcement number CN115000859A, discloses a method for safety supervision of substation operations, including: constructing a three-dimensional simulation scene in the substation; constructing a two-dimensional electronic map in the substation; constructing safety entry criteria for all equipment in the substation based on all equipment models in the three-dimensional simulation scene in the substation; patrol personnel carry positioning equipment and patrol APP to enter the substation to perform patrol tasks; obtain the position information and task execution information of the patrol personnel in the three-dimensional simulation scene through the station operation safety supervision platform, and automatically realize safety supervision of the patrol personnel. The present invention realizes the precise real-time positioning of substation patrol personnel, converts the safety production supervision of substations from passive discovery to active exposure mode; gradually realizes real-time unmanned supervision of the safety position of patrol personnel, and transforms safety supervision from post-warning to pre-warning, effectively preventing the occurrence of personal safety accidents and ensuring the safe operation of equipment in the station.

[0004] In response to the above scheme, the applicant of the present invention found that the above technical problems exist in at least the following technical problems: the above invention is mainly to achieve accurate real-time positioning of substation inspection personnel, convert the substation production safety supervision from passive discovery to active exposure mode, and realize real-time unmanned supervision of the safety position of the inspection personnel, while the present invention is mainly to supervise the safety of the corresponding inspection operations of the robots in the substation, ensure the corresponding inspection safety of the robots, and further maintain the smooth operation of the substation, and the above invention does not perform corresponding self-inspections on the inspection robots, and cannot ensure that the robots currently waiting to be inspected are in a qualified state, cannot ensure the effectiveness of the substation inspection and the safety of the robots performing inspection tasks, reduce the inspection efficiency and accuracy, and cannot ensure the safety of the inspection operations of the inspection robots themselves, reduce the service life of the robots, and increase the inspection costs and inspection safety risks. Summary of the invention

[0005] In view of the above-mentioned technical deficiencies, the object of the present invention is to provide a system and method for intelligent supervision of safe operation and operation and maintenance within a substation.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solution: The present invention provides an intelligent supervision system for safe operation and operation and maintenance within a substation, including: a substation image acquisition module, a safety supervision unit and an early warning terminal.

[0007] The substation image acquisition module is used to acquire the corresponding basic image in the substation, and then analyze to obtain the inspection route of the intelligent robot to be dispatched in the substation, and perform self-inspection on the intelligent robot to be dispatched to inspect the substation, and obtain the corresponding self-state of the intelligent robot to be dispatched.

[0008] The safety supervision unit includes a substation inspection monitoring module and a substation inspection analysis module.

[0009] The substation inspection monitoring module is used to monitor the intelligent robot's inspection inside the substation.

[0010] The substation inspection analysis module is used to monitor whether the intelligent robot is performing safe inspections in the substation and to analyze the safe operation mode of the intelligent robot during inspections in the substation.

[0011] The early warning terminal is used to issue early warning prompts when the intelligent robot is not in safe operation during inspection in the power station.

[0012] In a second aspect, the present invention provides a method for intelligent supervision of safe operations and operation and maintenance in a substation, comprising: step one, substation image acquisition: acquiring the corresponding basic image in the substation, and then analyzing to obtain the inspection route in the substation corresponding to the intelligent robot to be dispatched, and performing self-inspection on the intelligent robot to be dispatched for inspection of the substation, and the self-inspection obtains the corresponding self-state of the intelligent robot to be dispatched.

[0013] Step 2: Safety supervision: including substation inspection monitoring and substation inspection analysis;

[0014] Step 3: Substation inspection and monitoring: The monitoring intelligent robot conducts inspections inside the substation.

[0015] Step 4: Substation inspection analysis: monitor whether the intelligent robot is performing safe inspections in the substation, and analyze the safe operation methods of the intelligent robot during inspections in the substation.

[0016] Step 5: Early warning: When the intelligent robot responds to the inspection in the power station, it will issue an early warning when it is not in safe operation.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides a system and method for intelligent supervision of safe operation and operation and maintenance in a substation, by analyzing the inspection route of the intelligent robot to be dispatched in the substation, and performing self-inspection on the intelligent robot to be dispatched to understand its own status, and then monitoring the intelligent robot's inspection in the substation, supervising whether the intelligent robot's inspection in the substation is in safe operation, and analyzing the safe operation mode of the intelligent robot when inspecting in the substation, thereby ensuring the basic safety of the intelligent robot's inspection in the substation. Only on the basis of ensuring the safe operation of the inspection can a more comprehensive monitoring of the substation be achieved. The corresponding real-time operation and maintenance status can realize the efficient and safe protection of intelligent operation and maintenance inspection in the substation, so that the intelligent robot can prevent the safety risks in the substation in time while ensuring its own inspection safety, which solves the shortcomings of the current technology. At the same time, the inspection method based on the intelligent robot in the substation has greatly liberated the inconvenience and cost of the current manual inspection, further improved the efficiency of the inspection in the substation, and comprehensively guaranteed the efficient, safe and intelligent operation and maintenance of the substation, realizing the efficient and safe protection of the intelligent robot inspection operation, effectively extending the use time of the intelligent robot, ensuring the performance of the intelligent robot, and reducing the application damage of the intelligent robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 The present invention is a schematic flow chart of the steps for implementing the method.

[0020] Figure 2 It is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] See also Figure 1 As shown, a substation in-station safety operation and operation and maintenance intelligent supervision system includes a substation image acquisition module, a safety supervision unit, an early warning terminal and a database.

[0023] The substation image acquisition module is connected to the safety supervision unit and the database respectively, and the safety supervision unit is connected to the early warning terminal and the database respectively.

[0024] The substation image acquisition module is used to acquire the corresponding basic image in the substation, and then analyze to obtain the inspection route of the intelligent robot to be dispatched in the substation, and perform self-inspection on the intelligent robot to be dispatched to inspect the substation, and obtain the corresponding self-state of the intelligent robot to be dispatched.

[0025] It should be noted that the shortest path algorithm in graph theory refers to an algorithm for finding a path with the minimum total weight from a specified starting point to an end point in a weighted directed graph, including Dijkstra algorithm, Bellman-Ford algorithm, Floyd algorithm and SPFA algorithm, etc., which are currently known public technologies.

[0026] It should be noted that the self-inspection options taken by the intelligent robot during each historical inspection are obtained from the database. The total values ​​of the same self-inspection options corresponding to the intelligent robot during each historical inspection are counted, and the total values ​​are arranged in descending order. The top three self-inspection options in the total value are used as reference historical self-inspection options.

[0027] It should be noted that the self-test coefficients corresponding to each intelligent robot referring to the historical self-test options are obtained from the database, and the average self-test coefficient is obtained based on the average value calculation formula, and the average self-test coefficient is used as the historical reference self-test coefficient threshold.

[0028] It should be noted that the visibility of each intelligent robot's corresponding inspection in the substation is obtained from the database, and the average visibility is obtained based on the average value calculation formula, and the average visibility is used as the reference visibility.

[0029] As an optional implementation manner, the basic image corresponding to the substation is obtained, and then the inspection route of the intelligent robot to be dispatched in the substation is obtained by analysis. The specific acquisition process is as follows: basic layout information of the substation is collected by a high-definition camera to obtain the basic image corresponding to the substation, and then the visibility corresponding to the substation in the basic image is extracted, and the corresponding visibility in the current substation is compared with the reference visibility stored in the database. If the corresponding visibility in the current substation is less than the reference visibility stored in the database, the corresponding self-inspection is performed on the intelligent robot, and the corresponding layout information of the substation is extracted from the basic image, wherein the layout information includes equipment location, equipment density and number of line connections. The extracted layout information of the substation is regarded as the corresponding graph structure, and the corresponding inspection route in the substation is generated based on the shortest path algorithm in graph theory, so as to analyze and obtain the inspection route of the intelligent robot to be dispatched in the substation.

[0030] As an optional implementation, the intelligent robot to be dispatched to inspect the substation performs self-inspection, and the specific self-inspection process is as follows: W1. Obtain the reference historical self-inspection options corresponding to the intelligent robot stored in the database, and use the reference historical self-inspection options as the self-inspection options corresponding to the current robot to be dispatched, and then obtain the self-inspection information corresponding to the current robot to be dispatched, wherein the self-inspection information includes lens clarity, sensor sensing accuracy and mobile device sensitivity, and perform corresponding data normalization processing on the self-inspection information.

[0031] W2, by substituting into the calculation formula Then the self-check coefficient of the intelligent robot to be launched is obtained by analysis. is the lens clarity corresponding to the intelligent robot to be launched, φ is the sensor sensing accuracy corresponding to the intelligent robot to be launched, η is the sensitivity of the mobile device corresponding to the intelligent robot to be launched, β1, β2, and β3 are the weight factors of the set lens clarity, sensor sensing accuracy, and mobile device sensitivity, respectively, 0<β1<1, 0<β2<1, 0<β3<1.

[0032] It should also be noted that the weight factor of lens clarity, the weight factor of sensor sensing accuracy, and the weight factor of mobile device sensitivity are calculated using the CRITIC weight method, and the contrast intensity is multiplied by the conflict index and normalized to obtain the final weight.

[0033] It should be noted again that the CRITIC weighting method is an objective weighting method. It determines the objective weight of indicators based on two basic concepts. The comparative intensity is the difference between the values ​​of various evaluation schemes for the same indicator, which is expressed by the standard deviation, and the conflict is expressed by the correlation coefficient.

[0034] As an optional implementation manner, the self-inspection obtains the corresponding self-state of the intelligent robot to be dispatched, and the specific self-inspection process is as follows: the self-inspection coefficient corresponding to the intelligent robot to be dispatched is compared with the historical reference self-inspection coefficient threshold corresponding to the intelligent robot stored in the database. If the self-inspection coefficient corresponding to the intelligent robot to be dispatched is less than the historical reference self-inspection coefficient threshold corresponding to the intelligent robot stored in the database, it is determined that the corresponding self-state of the intelligent robot to be dispatched is unqualified, and the corresponding functional maintenance is performed. If the self-inspection coefficient corresponding to the intelligent robot to be dispatched is greater than or equal to the historical reference self-inspection coefficient threshold corresponding to the intelligent robot stored in the database, it is determined that the corresponding self-state of the intelligent robot to be dispatched is qualified, and the corresponding inspection task in the substation is allowed to be performed, so as to obtain the corresponding self-state of the intelligent robot to be dispatched through self-inspection.

[0035] The safety supervision unit includes a substation inspection monitoring module and a substation inspection analysis module.

[0036] The substation inspection monitoring module is used to monitor the intelligent robot's inspection inside the substation.

[0037] It should be noted that the electromagnetic values ​​at each occurrence of high electromagnetic phenomena in the substation are obtained from the database, and the electromagnetic value ranked first and the electromagnetic value ranked last are recorded as the historical high electromagnetic value interval.

[0038] As an optional implementation, the monitoring intelligent robot performs inspections inside the substation, and the specific monitoring process is as follows: W1. When the intelligent robot performs inspections inside the substation according to the inspection route, the total inspection distance based on the intelligent robot's corresponding inspection route is divided into points according to the average length to obtain each point.

[0039] W2. When the intelligent robot arrives at each monitored point in the substation, it automatically turns on the corresponding electromagnetic field monitoring sensor to obtain the electromagnetic value corresponding to each point in the substation, and compares the electromagnetic value corresponding to each point with the historical high electromagnetic value interval stored in the database. If the electromagnetic value corresponding to a point is within the historical high electromagnetic value interval stored in the database, the point is determined to be a high magnetic field area, and the distance between the current point and the nearest high magnetic field area is obtained.

[0040] W3. Simultaneously turn on the corresponding infrared sensors to obtain the infrared images corresponding to each point in the substation, and observe whether there is dust in the infrared images. If there is dust in the infrared images, extract the dust coverage area, turn on the corresponding dust sensors, and obtain the corresponding dust concentration, so as to obtain the dust information corresponding to each point in the substation, and combine the above-mentioned monitoring of electromagnetic values ​​in the substation to complete the inspection of the substation by the monitoring intelligent robot.

[0041] The substation inspection analysis module is used to monitor whether the intelligent robot is performing safe inspections in the substation and to analyze the safe operation mode of the intelligent robot during inspections in the substation.

[0042] It should be noted that the intelligent robot is equipped with autonomous computing function, which can automatically obtain the distance between the current position of the intelligent robot and the nearest high magnetic field area.

[0043] As an optional implementation, the supervisory intelligent robot monitors whether the inspection in the substation is in safe operation, and the specific supervision process is as follows: Q1. Based on the fact that the intelligent robot's inspection in the substation is divided into two parts of monitoring: dust and magnetic field, the inspection safety operation supervision in the substation is further divided into dust judgment and high magnetic field judgment.

[0044] Q2. Compare the distance between the current intelligent robot position and the nearest high magnetic field area with the reference high magnetic field safety distance value stored in the database. If the distance between the current intelligent robot position and the nearest high magnetic field area is less than or equal to the reference high magnetic field safety distance value stored in the database, it is determined that the intelligent robot will be affected by the high magnetic field area, and the intelligent robot is determined to be in a dangerous operation for the inspection in the strain power station. If the distance between the current intelligent robot position and the nearest high magnetic field area is greater than the reference high magnetic field safety distance value stored in the database, it is determined that the intelligent robot will not be affected by the high magnetic field area, and the intelligent robot is determined to be in a safe operation for the inspection in the strain power station. In this way, whether the intelligent robot is in a safe operation for the inspection in the strain power station is supervised.

[0045] As an optional implementation manner, the determination of whether the intelligent robot is performing an inspection in a strain power station safely is specifically carried out as follows: the dust information corresponding to each point in the strain power station of the intelligent robot is imported into the learning model, and then the dust safety value of the intelligent robot's inspection in the strain power station is calculated; if the dust safety value result output of the intelligent robot's inspection in the strain power station is 0, it is determined that the dust in the strain power station of the intelligent robot will not have a dangerous effect on the intelligent robot, and the inspection of the intelligent robot in the strain power station is determined to be in a safe operation; if the dust safety value result output of the intelligent robot's inspection in the strain power station is 1, it is determined that the dust will have a dangerous effect on the intelligent robot, and the inspection of the intelligent robot is determined to be unsafe, thereby determining whether the intelligent robot is performing an inspection in the strain power station safely.

[0046] It should be noted that the learning models include linear regression models, logistic regression models, support vector regression models, decision tree models, and random forest models.

[0047] As an optional implementation, the intelligent robot responds to the dust safety value of the power station inspection, and the specific calculation process is as follows: by calculating the formula The dust safety value AQ of the intelligent robot corresponding to the inspection in the power station is calculated, g is the number of each point, g = 1, 2, ..., j, j is any integer greater than 2, W g R is the dust distribution area of ​​the g-th point in the power station corresponding to the intelligent robot. g The intelligent robot responds to the dust concentration at the g-th point in the power station. n1 and n2 are the weight factors of the dust coverage area and dust concentration, respectively. B is the set reference dust safety value, 0<n1<1, 0<n2<1.

[0048] It should be noted that the inspection images corresponding to the dust values ​​during each inspection by the intelligent robot are obtained from the database, and the corresponding dust safety values ​​are obtained according to the clarity of the inspection images.

[0049] It should be noted that the weight factor of the dust coverage area and the weight factor of the dust concentration are calculated using the CRITIC weight method, and the contrast intensity is multiplied by the conflict index and normalized to obtain the final weight.

[0050] As an optional implementation method, the analysis obtains the safe operation mode of the intelligent robot during inspection in the power station, and the specific analysis process is as follows: R1. When the intelligent robot is affected by the high magnetic field area: compare the distance between the current intelligent robot position and the nearest high magnetic field area with the distance values ​​of each level stored in the database. If the distance between the current intelligent robot position and the nearest high magnetic field area is the same as a high-level distance value stored in the database, then turn on the anti-interference electromagnetic device of the intelligent robot; if the distance between the current intelligent robot position and the nearest high magnetic field area is the same as a low-level distance value stored in the database, then turn on the anti-interference electromagnetic device of the intelligent robot and cut off the corresponding networking option of the intelligent robot.

[0051] R2. When the dust in the substation poses a dangerous threat to the intelligent robot: compare the dust safety value of the intelligent robot for inspection in the substation with the dust safety values ​​corresponding to each level stored in the database. If the dust safety value of the intelligent robot for inspection in the substation is the same as a dust safety value of a low level stored in the database, turn on the cleaning tool corresponding to the intelligent robot. If the dust safety value of the intelligent robot for inspection in the substation is the same as a dust safety value of a high level stored in the database, turn on the dust protection device corresponding to the intelligent robot while turning on the cleaning tool. Combined with the above-mentioned high magnetic field safety operations, this analysis can be used to obtain the safe operation mode of the intelligent robot when inspecting in the substation.

[0052] The database is used to store visibility, reference visibility, layout information, self-check information, historical reference self-check coefficient threshold, the distance between the current point and the nearest high magnetic field area, and dust information.

[0053] The early warning terminal is used to issue early warning prompts when the intelligent robot is not in safe operation during inspection in the power station.

[0054] See also Figure 2As shown, a method for intelligent supervision of safe operation and operation and maintenance in a substation includes step 1, substation image acquisition: acquiring the corresponding basic image in the substation, and then analyzing to obtain the inspection route of the intelligent robot to be dispatched in the substation, and performing self-inspection on the intelligent robot to be dispatched to inspect the substation, and the self-inspection obtains the corresponding self-state of the intelligent robot to be dispatched.

[0055] Step 2: Safety supervision: including substation inspection monitoring and substation inspection analysis;

[0056] Step 3: Substation inspection and monitoring: The monitoring intelligent robot conducts inspections inside the substation.

[0057] Step 4: Substation inspection analysis: monitor whether the intelligent robot is performing safe inspections in the substation, and analyze the safe operation methods of the intelligent robot during inspections in the substation.

[0058] Step 5: Early warning: When the intelligent robot responds to the inspection in the power station, it will issue an early warning when it is not in safe operation.

[0059] The embodiment of the present invention analyzes the inspection route of the intelligent robot to be dispatched in the substation, performs self-inspection on the intelligent robot to be dispatched, understands its own status, and then monitors the intelligent robot to inspect the substation, supervises whether the intelligent robot is in safe operation during the inspection in the substation, and analyzes the safe operation mode of the intelligent robot during the inspection in the substation, so as to ensure the basic safety of the intelligent robot during the inspection in the substation. Only on the basis of ensuring the safe operation of the inspection can a more comprehensive monitoring of the corresponding real-time operation and maintenance situation in the substation be achieved, thereby realizing efficient and safe protection of the intelligent operation and maintenance inspection in the substation, so that the intelligent robot can prevent the safety risks in the substation in time while ensuring its own inspection safety, solves the deficiencies in the current technology, and at the same time, based on the inspection mode of the intelligent robot in the substation, it also greatly liberates the inconvenience and cost of the current manual inspection, further improves the efficiency of the inspection in the substation, comprehensively guarantees the efficient, safe and intelligent operation and maintenance of the substation, realizes the efficient and safe protection of the intelligent robot inspection operation, effectively extends the service life of the intelligent robot, guarantees the performance of the intelligent robot, and reduces the application damage of the intelligent robot.

[0060] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.

Claims

1. A substation safety operation and operation and maintenance intelligent supervision system, characterized in that: include: Substation image acquisition module, safety supervision unit and early warning terminal; The substation image acquisition module is used to acquire the corresponding basic image in the substation, and then analyze to obtain the inspection route of the intelligent robot to be dispatched in the substation, and perform self-inspection on the intelligent robot to be dispatched to inspect the substation, and obtain the corresponding state of the intelligent robot to be dispatched; The safety supervision unit includes a substation inspection monitoring module and a substation inspection analysis module; The substation inspection monitoring module is used to monitor the inspection of the substation by the intelligent robot; The substation inspection analysis module is used to monitor whether the intelligent robot is performing safe inspections in the substation and to analyze the safe operation methods of the intelligent robot during inspections in the substation. The early warning terminal is used to issue early warning prompts when the intelligent robot is not in safe operation during inspection in the power station.

2. A substation safety operation and operation and maintenance intelligent supervision system as claimed in claim 1, characterized in that: The basic image corresponding to the substation is obtained, and then the inspection route of the intelligent robot to be launched corresponding to the substation is obtained through analysis. The specific acquisition process is as follows: The basic layout information of the substation is collected through a high-definition camera to obtain the corresponding basic image of the substation, and then the corresponding visibility of the substation in the basic image is extracted, and the corresponding visibility in the current substation is compared with the reference visibility stored in the database. If the corresponding visibility in the current substation is less than the reference visibility stored in the database, the corresponding self-inspection is performed on the intelligent robot, and the corresponding layout information of the substation is extracted from the basic image, where the layout information includes equipment location, equipment density and number of line connections. The extracted layout information of the substation is regarded as the corresponding graph structure, and the corresponding inspection route in the substation is generated based on the shortest path algorithm in graph theory. The inspection route in the substation corresponding to the intelligent robot to be dispatched is obtained by analysis.

3. The intelligent monitoring system for safe operation and operation and maintenance in a substation according to claim 1, characterized in that: The intelligent robot to be dispatched to inspect the substation performs self-inspection, and the specific self-inspection process is as follows: W1. Obtain the reference historical self-test options corresponding to the intelligent robot stored in the database, and use the reference historical self-test options as the self-test options corresponding to the current robot to be launched, thereby obtaining the self-test information corresponding to the current robot to be launched, wherein the self-test information includes lens clarity, sensor sensing accuracy and mobile device sensitivity, and perform corresponding data normalization processing on the self-test information; W2, by substituting into the calculation formula Then the self-check coefficient of the intelligent robot to be launched is obtained by analysis. ζ is the lens clarity corresponding to the intelligent robot to be launched, φ is the sensor sensing accuracy corresponding to the intelligent robot to be launched, η is the sensitivity of the mobile device corresponding to the intelligent robot to be launched, β1, β2, and β3 are the weight factors of the set lens clarity, sensor sensing accuracy, and mobile device sensitivity, respectively, 0<β1<1, 0<β2<1, 0<β3<1.

4. The intelligent monitoring system for safe operation and operation and maintenance in a substation according to claim 1, characterized in that: The self-checking obtains the corresponding self-state of the intelligent robot to be started. The specific self-checking process is as follows: The self-test coefficient corresponding to the intelligent robot to be dispatched is compared with the historical reference self-test coefficient threshold corresponding to the intelligent robot stored in the database. If the self-test coefficient corresponding to the intelligent robot to be dispatched is less than the historical reference self-test coefficient threshold corresponding to the intelligent robot stored in the database, it is determined that the self-state of the intelligent robot to be dispatched is unqualified, and the corresponding functional maintenance is performed. If the self-test coefficient corresponding to the intelligent robot to be dispatched is greater than or equal to the historical reference self-test coefficient threshold corresponding to the intelligent robot stored in the database, it is determined that the self-state of the intelligent robot to be dispatched is qualified, and the inspection task in the corresponding power station is allowed to be performed, so as to obtain the self-state of the intelligent robot to be dispatched through self-test.

5. The intelligent monitoring system for safe operation and operation and maintenance in a substation according to claim 1, characterized in that: The monitoring intelligent robot performs inspections inside the substation, and the specific monitoring process is as follows: W1. When the intelligent robot performs inspections in the substation according to the inspection route, the total inspection distance of the inspection route corresponding to the intelligent robot is divided into points according to the average length to obtain each point; W2. When the intelligent robot reaches each monitoring point in the substation, it automatically turns on the corresponding electromagnetic field monitoring sensor to obtain the electromagnetic value corresponding to each point in the substation, and compares the electromagnetic value corresponding to each point with the historical high electromagnetic value interval stored in the database. If the electromagnetic value corresponding to a point is within the historical high electromagnetic value interval stored in the database, the point is determined to be a high magnetic field area, and the distance between the current point and the nearest high magnetic field area is obtained; W3. Turn on the corresponding infrared sensors at the same time to obtain the infrared images corresponding to each point in the substation, and observe whether there is dust in the infrared images. If there is dust in the infrared images, extract the dust coverage area, turn on the corresponding dust sensors, and obtain the corresponding dust concentration. In this way, the dust information corresponding to each point in the substation is obtained, and the above-mentioned monitoring of electromagnetic values ​​in the substation is combined to complete the inspection of the substation by the monitoring intelligent robot.

6. A substation safety operation and operation and maintenance intelligent supervision system as claimed in claim 5, characterized in that: The supervisory intelligent robot is responsible for checking whether the inspection in the power station is in safe operation. The specific supervision process is as follows: Q1. Based on the intelligent robot, the inspection in the substation is divided into two parts: dust and magnetic field monitoring. Then the inspection safety operation supervision in the substation is divided into dust judgment and high magnetic field judgment; Q2. Compare the distance between the current intelligent robot position and the nearest high magnetic field area with the reference high magnetic field safety distance value stored in the database. If the distance between the current intelligent robot position and the nearest high magnetic field area is less than or equal to the reference high magnetic field safety distance value stored in the database, it is determined that the intelligent robot will be affected by the high magnetic field area, and the intelligent robot is determined to be in a dangerous operation for the inspection in the strain power station. If the distance between the current intelligent robot position and the nearest high magnetic field area is greater than the reference high magnetic field safety distance value stored in the database, it is determined that the intelligent robot will not be affected by the high magnetic field area, and the intelligent robot is determined to be in a safe operation for the inspection in the strain power station. In this way, whether the intelligent robot is in a safe operation for the inspection in the strain power station is supervised.

7. A substation safety operation and operation and maintenance intelligent supervision system as claimed in claim 6, characterized in that: The specific judgment process of judging whether the intelligent robot is operating safely in the power station is as follows: The dust information corresponding to each point in the strain power station of the intelligent robot is imported into the learning model, and then the dust safety value of the intelligent robot for the inspection in the strain power station is calculated. If the dust safety value result output of the intelligent robot for the inspection in the strain power station is 0, it is determined that the dust in the strain power station of the intelligent robot will not have a dangerous effect on the intelligent robot, and the inspection of the intelligent robot in the strain power station is determined to be in safe operation. If the dust safety value result output of the intelligent robot for the inspection in the strain power station is 1, it is determined that the dust will have a dangerous effect on the intelligent robot, and the inspection of the intelligent robot is determined to be unsafe, so as to judge whether the inspection of the intelligent robot in the strain power station is in safe operation.

8. The intelligent monitoring system for safe operation and operation and maintenance in a substation according to claim 7, characterized in that: The intelligent robot responds to the dust safety value of the power station inspection, and the specific calculation process is as follows: By calculating the formula The dust safety value AQ of the intelligent robot corresponding to the inspection in the power station is calculated, g is the number of each point, g = 1, 2, ..., j, j is any integer greater than 2, W g R is the dust distribution area of ​​the g-th point in the power station corresponding to the intelligent robot. g The intelligent robot responds to the dust concentration at the g-th point in the power station. n1 and n2 are the weight factors of the dust coverage area and dust concentration, respectively. B is the set reference dust safety value, 0<n1<1, 0<n2<1.

9. The intelligent monitoring system for safe operation and operation and maintenance in a substation according to claim 1, characterized in that: The analysis obtained the safe operation mode of the intelligent robot during the inspection in the power station. The specific analysis process is as follows: R1. When the intelligent robot is affected by a high magnetic field area: compare the distance between the current intelligent robot position and the nearest high magnetic field area with the distance values ​​of each level stored in the database. If the distance between the current intelligent robot position and the nearest high magnetic field area is the same as a certain high-level distance value stored in the database, turn on the anti-interference electromagnetic device of the intelligent robot. If the distance between the current intelligent robot position and the nearest high magnetic field area is the same as a certain low-level distance value stored in the database, turn on the anti-interference electromagnetic device of the intelligent robot and cut off the networking option of the intelligent robot at the same time. R2. When the dust in the substation poses a dangerous threat to the intelligent robot: compare the dust safety value of the intelligent robot for inspection in the substation with the dust safety values ​​corresponding to each level stored in the database. If the dust safety value of the intelligent robot for inspection in the substation is the same as a dust safety value of a low level stored in the database, turn on the cleaning tool corresponding to the intelligent robot. If the dust safety value of the intelligent robot for inspection in the substation is the same as a dust safety value of a high level stored in the database, turn on the dust protection device corresponding to the intelligent robot while turning on the cleaning tool. Combined with the above-mentioned high magnetic field safety operations, this analysis can be used to obtain the safe operation mode of the intelligent robot when inspecting in the substation.

10. A method for intelligent supervision of safe operation and operation and maintenance in a substation, which implements the intelligent supervision system for safe operation and operation and maintenance in a substation according to any one of claims 1 to 9, characterized in that: include: Step 1: Substation image acquisition: Obtain the corresponding basic image in the substation, and then analyze and obtain the inspection route of the intelligent robot to be dispatched in the substation, and perform self-inspection on the intelligent robot to be dispatched to inspect the substation, and obtain the corresponding state of the intelligent robot to be dispatched; Step 2: Safety supervision: including substation inspection monitoring and substation inspection analysis; Step 3: Substation inspection and monitoring: The monitoring intelligent robot conducts inspections inside the substation; Step 4: Substation inspection analysis: monitor whether the intelligent robot is performing safe inspections in the substation, and analyze the safe operation mode of the intelligent robot during inspections in the substation; Step 5: Early warning: When the intelligent robot responds to the inspection in the power station, it will issue an early warning when it is not in safe operation.

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