An intelligent robot control system for substation inspection

Abstract

The present invention discloses an intelligent robot control system for substation inspection, which relates to the technical field of financial budget supervision. The present invention comprises a sensor selection module, a sensor analysis module, a patrol monitoring and collection module, a patrol status monitoring module, an early warning terminal and a database. By collecting the data types of various equipment corresponding to various areas of the substation, the open sensors for the intelligent robot to collect the data types of various equipment in various areas are screened out, and the intelligent robot is controlled to perform collection of various angles on the data types of various equipment in various areas, and the collection angles of the intelligent robot corresponding to the data types of various equipment in various areas are screened out, so as to control the intelligent robot to complete the patrol tasks corresponding to various areas of the substation, realize effective monitoring of the corresponding operating status of various areas of the substation, ensure the accuracy and real-time nature of the patrol collection data, and maintain the corresponding safe operation of the substation from a more diverse and comprehensive perspective.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent robot control, and in particular to an intelligent robot control system for substation inspection. Background Art

[0002] With the widespread application of intelligent robots, the corresponding inspection of substations has become easy and efficient. Based on the different monitoring data collected in various areas of the substation, the collection sensors that should be turned on by the intelligent robots during inspection are analyzed. At the same time, when the intelligent robots use sensors to collect information from various angles in various areas, the best collection angles for the data types of each device in each area are selected to achieve efficient inspections.

[0003] Prior art, such as the invention patent application with announcement number CN111399521A, discloses an intelligent robot control system for substation inspection, including an intelligent robot and a management terminal connected to the intelligent robot for communication, the intelligent robot including a motion module, a target confirmation module, a shooting module and a main control module respectively controlling the motion module, the target confirmation module and the shooting module; the management terminal can obtain the operation information of the intelligent robot through the main control module or send a control command to control the operation of the intelligent robot; the motion module includes a walking chassis, the walking chassis includes a first probe for detecting the trajectory line, and a first wheel and a second wheel symmetrically arranged about the first probe; the target confirmation module is used to confirm the position of the inspection point, and the shooting module is used to shoot the position after the target confirmation module confirms the position of the inspection point.

[0004] In view of the above scheme, the applicant of the present invention has found that the above technical problems have at least the following technical problems: the above invention mainly confirms the location of the patrol point and then takes a picture of the location. It does not analyze the different device data type information corresponding to each area of ​​the substation to determine the sensors of each device for collecting the data types of each device in each area. It cannot ensure that the sensors are correctly turned on when the intelligent robot collects the data types of each device in each area. At the same time, it does not analyze the collection of each angle of each device data type in each area by controlling the intelligent robot, and cannot screen out the collection angle of the intelligent robot corresponding to the data type of each device in each area. It cannot ensure that the intelligent robot fully completes the collection tasks of each area, and cannot guarantee the effectiveness and accuracy of data collection, thereby reducing the patrol efficiency and operation safety of each area corresponding to the substation. Summary of the invention

[0005] In view of the above-mentioned technical deficiencies, an object of the present invention is to provide an intelligent robot control system for substation inspection.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides an intelligent robot control system for substation inspection, including: a sensor selection module, used to control the intelligent robot to inspect the substation, collect the data types of each device corresponding to each area of ​​the substation, and then analyze the sensors of each device for collecting the data types of each device in each area by the intelligent robot.

[0007] The sensor analysis module is used to obtain the historical collection performance information of each device sensor corresponding to each area and each device data type from the database, where the historical collection performance information includes collection accuracy, energy consumption and efficiency, and then filter out each open sensor for the intelligent robot to collect each area and each device data type.

[0008] The patrol monitoring and collection module is used to control the intelligent robot to collect the data types of each device in each area at various angles when the open sensors of the intelligent robot are screened out to collect the data types of each device in each area. The basic information of the collection at various angles is collected according to the data types of each device in each area, and then the collection angles of the intelligent robot corresponding to the data types of each device in each area are screened out.

[0009] The patrol status monitoring module is used to control the intelligent robot to perform collection and patrol on the data types of each device in each area according to the collection angle, obtain the collection information corresponding to the data type of each device in each area, and then analyze and obtain the corresponding status evaluation coefficient of each area, and determine the corresponding patrol status of each area.

[0010] The early warning terminal is used to issue an early warning prompt when the patrol status corresponding to a certain area is abnormal.

[0011] Preferably, the analysis obtains the various device sensors of each equipment data type in each area collected by the intelligent robot. The specific analysis process is as follows: compare the various equipment data types collected corresponding to the needs of each area of ​​the substation with the various sensor function types stored in the database. If a certain equipment data type collected corresponding to the needs of a certain area of ​​the substation is within a certain sensor function type stored in the database, then the sensor is used as the device sensor corresponding to the intelligent robot in that area, so as to analyze and obtain the various device sensors of each equipment data type in each area collected by the intelligent robot.

[0012] Preferably, the screening obtains each turn-on sensor of each device data type in each area collected by the intelligent robot, and the specific screening process is as follows: according to the historical collection performance information of each device sensor corresponding to each device data type in each area, wherein the historical collection performance information includes collection accuracy, energy consumption and efficiency, and then selects the corresponding machine learning model, and inputs the historical collection performance information of each device sensor corresponding to each device data type in each area into the machine learning model, and analyzes to obtain the performance evaluation coefficient of each device sensor corresponding to each device data type in each area. When the performance evaluation coefficient of a device sensor corresponding to a device data type in a certain area is 0, it is determined that the device sensor is not used as a turn-on sensor for the intelligent robot to collect the device data type in the area. When the performance evaluation coefficient of a device sensor corresponding to a device data type in a certain area is 1, it is determined that the device sensor is used as a turn-on sensor for the intelligent robot to collect the device data type in the area. In this way, the turn-on sensors of each device data type in each area collected by the intelligent robot are obtained by screening.

[0013] Preferably, the analysis obtains the performance evaluation coefficient of each device sensor corresponding to each device data type in each area. The specific analysis process is as follows: by calculating the formula:

[0014] The performance evaluation coefficient of the hth device sensor corresponding to the xth device data type in the ith area is obtained by analysis. h is the number of each device sensor, h=1,2,.....,f, f is any integer greater than 2, i is the number of each area, i=1,2,......,k, k is any integer greater than 2, x is the number of each device data type, x=1,2,.....,s, s is any integer greater than 2, m hix is the acquisition accuracy of the xth device data type in the ith area corresponding to the hth device sensor, n hix is the energy consumption of the h-th device sensor corresponding to the x-th device data type in the ith area, σ hix is the efficiency of the hth device sensor corresponding to the xth device data type in the ith area, p1, p2 and p3 are the weight factors of acquisition accuracy, energy consumption and efficiency respectively, e is a natural constant, q is a preset reference performance value, 0<p1<1,

[0015] 0<p2<1,0<p3<1.

[0016] Preferably, the screening obtains the collection angle of the intelligent robot corresponding to each device data type in each area, and the specific screening process is as follows: basic information of each device data type in each area performing collection at each angle, wherein the basic information includes real-time data and coverage, and the real-time data includes frequency and transmission speed, and the corresponding machine learning model is selected, and the basic information of each device data type in each area performing collection at each angle is input into the machine learning model, and the performance coefficient of each device data type in each area performing collection at each angle is obtained by analysis. When the performance coefficient of a device data type in a certain area performing collection at a certain angle is 0, it is determined that the angle is not used as the collection angle of the intelligent robot corresponding to the device data type in the area. When the performance coefficient of a device data type in a certain area performing collection at a certain angle is 1, it is determined that the angle is used as the collection angle of the intelligent robot corresponding to the device data type in the area, thereby screening to obtain the collection angle of the intelligent robot corresponding to each device data type in each area.

[0017] Preferably, the analysis obtains the performance coefficient of each device data type in each area corresponding to each angle of collection. The specific analysis process is as follows: by calculating the formula:

[0018] The performance coefficient Φ corresponding to the c-th angle acquisition of the x-th device data type in the i-th area is obtained by analysis. ixc , i is the number of each area, i=1,2,.....,k, k is any integer greater than 2, x is the number of each device data type, x=1,2,.....,s, s is any integer greater than 2, c is the x number of each angle, c=1,2,.....b, b is any integer greater than 2, Q ixc is the frequency collected at the cth angle corresponding to the xth device data type in the ith region, R ixc is the transmission speed of the xth device data type in the ith area corresponding to the cth angle acquisition, J ixc is the coverage rate collected at the c-th angle for the x-th device data type in the ith area, L is the set reference performance value, ν1, ν2, and ν3 are the weighting factors of frequency, transmission speed, and coverage, respectively, 0<ν1<1, 0<ν2<1, 0<ν3<1.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides an intelligent robot control system for substation inspection, which collects the data types of each device corresponding to each area of ​​the substation, and then selects the open sensors for the intelligent robot to collect the data types of each device in each area, and controls the intelligent robot to perform various angles of collection on the data types of each device in each area, and selects the collection angles of the intelligent robot corresponding to the data types of each device in each area, so as to control the intelligent robot to complete the inspection tasks corresponding to each area of ​​the substation, realize effective monitoring of the corresponding operating status of each area of ​​the substation, and ensure the safe operation of the substation, solve the deficiencies in the current technology, implement effective inspections corresponding to the data types of each device in each area, ensure the accuracy and efficiency of the inspection results of each area of ​​the substation, realize effective control of the intelligent robot to perform the inspection tasks of each area of ​​the substation, experience convenient and efficient inspection monitoring, ensure that each area of ​​the substation is fully inspected by the robot, reduce the corresponding safety hazards of each area of ​​the substation, and reduce the cost of manpower inspection. At the same time, the intelligent robot is equipped with high-precision equipment, which can monitor the equipment parameters of each area of ​​the substation in real time, ensure the accuracy and real-time of the inspection collection data, and maintain the corresponding safe operation of the substation from a more diverse and comprehensive perspective. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] 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.

[0021] Figure 1 It is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0022] 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.

[0023] See also Figure 1 As shown, an intelligent robot control system for substation inspection includes a sensor selection module, a sensor analysis module, a patrol monitoring and acquisition module, a patrol status monitoring module, an early warning terminal and a database.

[0024] The sensor selection module is connected to the sensor analysis module and the database respectively, the patrol monitoring collection module is connected to the patrol status monitoring module and the database respectively, and the patrol status monitoring module is connected to the early warning terminal.

[0025] The sensor selection module is used to control the intelligent robot to patrol the substation, collect the data types of each device corresponding to each area of ​​the substation, and then analyze the sensors of each device used by the intelligent robot to collect the data types of each device in each area.

[0026] It should be noted that the data types of each device include but are not limited to temperature, humidity, gas concentration and current, and the sensors of each device include but are not limited to temperature sensors, infrared sensors, humidity sensors, gas sensors, gas detectors and current sensors.

[0027] As an optional implementation, the analysis obtains the various device sensors that collect the data types of each device in each area by the intelligent robot. The specific analysis process is as follows: compare the data types of each device collected in response to the needs of each area of ​​the substation with the functional types of each sensor stored in the database. If a certain device data type collected in response to the needs of a certain area of ​​the substation is within a certain sensor functional type stored in the database, then the sensor is used as the device sensor corresponding to the intelligent robot in that area, and the various device sensors that collect the data types of each device in each area by the intelligent robot are obtained through this analysis.

[0028] The sensor analysis module is used to obtain the historical collection performance information of each device sensor corresponding to each area and each device data type from the database, where the historical collection performance information includes collection accuracy, energy consumption and efficiency, and then filter out each open sensor for the intelligent robot to collect each area and each device data type.

[0029] As an optional implementation manner, the screening obtains each open sensor of each device data type in each area collected by the intelligent robot, and the specific screening process is as follows: according to the historical collection performance information of each device sensor corresponding to each device data type in each area, wherein the historical collection performance information includes collection accuracy, energy consumption and efficiency, and then selects the corresponding machine learning model, and inputs the historical collection performance information of each device sensor corresponding to each device data type in each area into the machine learning model, and analyzes to obtain the performance evaluation coefficient of each device sensor corresponding to each device data type in each area. When the performance evaluation coefficient of a device sensor corresponding to a device data type in a certain area is 0, it is determined that the device sensor is not used as a start sensor for the intelligent robot to collect the device data type in the area. When the performance evaluation coefficient of a device sensor corresponding to a device data type in a certain area is 1, it is determined that the device sensor is used as a start sensor for the intelligent robot to collect the device data type in the area. In this way, the open sensors of each device data type in each area collected by the intelligent robot are obtained by screening.

[0030] As an optional implementation, the analysis obtains the performance evaluation coefficient of each device sensor corresponding to each device data type in each area. The specific analysis process is as follows: by calculating the formula: The performance evaluation coefficient of the hth device sensor corresponding to the xth device data type in the ith area is obtained by analysis. h is the number of each device sensor, h=1,2,.....,f, f is any integer greater than 2, i is the number of each area, i=1,2,......,k, k is any integer greater than 2, x is the number of each device data type, x=1,2,.....,s, s is any integer greater than 2, m hix is the acquisition accuracy of the xth device data type in the ith area corresponding to the hth device sensor, n hix is the energy consumption of the h-th device sensor corresponding to the x-th device data type in the ith area, σ hix is the efficiency of the h-th device sensor corresponding to the x-th device data type in the ith area, p1, p2 and p3 are the weight factors of acquisition accuracy, energy consumption and efficiency respectively, e is a natural constant, q is a preset reference performance value, 0<p1<1, 0<p2<1, 0<p3<1.

[0031] It should also be noted that the weight factors of acquisition accuracy, energy consumption and efficiency are obtained through principal component analysis. The information of the corresponding acquisition accuracy, energy consumption and efficiency is condensed first, and then the corresponding variance explanation rate is obtained, and then divided by the variance explanation rate to get the corresponding weight.

[0032] It is important to note again that information condensation refers to condensing multiple analysis items into several key summary indicators, and the variance explanation rate refers to the contribution of each principal component or factor to the overall variance, usually expressed as a percentage, indicating how much information the factor contains about the original data.

[0033] The patrol monitoring and collection module is used to control the intelligent robot to collect the data types of each device in each area at various angles when the open sensors of the intelligent robot are screened out to collect the data types of each device in each area. The basic information of the collection at various angles is collected according to the data types of each device in each area, and then the collection angles of the intelligent robot corresponding to the data types of each device in each area are screened out.

[0034] It should be noted that the basic information collected from various angles is obtained from the database for each device data type in the area.

[0035] As an optional implementation manner, the basic information collected at each angle by each device data type in each area includes real-time data and coverage, and the real-time data includes frequency and transmission speed.

[0036] As an optional implementation method, the screening obtains the collection angle of the intelligent robot corresponding to each device data type in each area, and the specific screening process is as follows: according to the basic information of each device data type in each area, the collection is performed at each angle, wherein the basic information includes real-time data and coverage, and the real-time data includes frequency and transmission speed, and the corresponding machine learning model is selected, and the basic information of each device data type in each area for collecting at each angle is input into the machine learning model, and the performance coefficient of each device data type in each area for collecting at each angle is obtained by analysis. When the performance coefficient of a certain device data type in a certain area for collecting at a certain angle is 0, it is determined that the angle is not used as the collection angle of the intelligent robot corresponding to the device data type in the area. When the performance coefficient of a certain device data type in a certain area for collecting at a certain angle is 1, it is determined that the angle is used as the collection angle of the intelligent robot corresponding to the device data type in the area, so as to obtain the collection angle of the intelligent robot corresponding to each device data type in each area through screening.

[0037] As an optional implementation, the analysis obtains the performance coefficient of each device data type in each area corresponding to each angle of collection. The specific analysis process is as follows: by calculating the formula:

[0038] The performance coefficient Φ corresponding to the c-th angle acquisition of the x-th device data type in the i-th area is obtained by analysis. ixc , i is the number of each area, i=1,2,.....,k, k is any integer greater than 2, x is the number of each device data type, x=1,2,.....,s, s is any integer greater than 2, c is the x number of each angle, c=1,2,.....b, b is any integer greater than 2, Q ixc is the frequency collected at the cth angle corresponding to the xth device data type in the ith region, R ixc is the transmission speed of the xth device data type in the ith area corresponding to the cth angle acquisition, J ixc is the coverage rate collected at the c-th angle for the x-th device data type in the ith area, L is the set reference performance value, ν1, ν2, and ν3 are the weighting factors of frequency, transmission speed, and coverage, respectively, 0<ν1<1, 0<ν2<1, 0<ν3<1.

[0039] It should also be noted that the weight factors of frequency, transmission speed, and coverage are obtained through principal component analysis. The information of the corresponding frequency, transmission speed, and coverage is first condensed, and then the corresponding variance explanation rate is obtained, and then divided by the variance explanation rate to get the corresponding weight.

[0040] The patrol status monitoring module is used to control the intelligent robot to perform collection and patrol on the data types of each device in each area according to the collection angle, obtain the collection information corresponding to the data type of each device in each area, and then analyze and obtain the corresponding status evaluation coefficient of each area, and determine the corresponding patrol status of each area.

[0041] It should be noted that the collected information includes gas concentration and leakage current. A gas detector is used to obtain the gas concentration corresponding to the data type of each device in each area, and a leakage current detector is used to obtain the leakage current corresponding to the data type of each device in each area.

[0042] As an optional implementation, the analysis obtains the state assessment coefficient corresponding to each area, and the specific calculation process is as follows: by the calculation formula: The patrol state θ corresponding to the i-th area is obtained by analysis i , i is the number of each area, i = 1, 2, ..., k, k is an arbitrary integer greater than 2, x is the number of each device data type, x = 1, 2, ..., s, s is an arbitrary integer greater than 2, r "is the preset reference gas concentration, h "is the preset reference leakage current, r ix is the gas concentration corresponding to the xth device data type in the ith area, h ix is the leakage current corresponding to the xth device data type in the ith region, w1 and w2 are the weight factor of the set gas concentration and the weight factor of the leakage current, respectively, 0<w1<1, 0<w2<1.

[0043] It should also be noted that the weight factors of gas concentration and leakage current are obtained by principal component analysis. The information of the corresponding gas concentration and leakage current is first condensed, and then the corresponding variance explanation rate is obtained, and then the corresponding weight is obtained by dividing the variance explanation rate.

[0044] As an optional implementation, the judgment obtains the patrol status corresponding to each area, and the specific judgment process is as follows: the state evaluation coefficient corresponding to each area is compared with the state evaluation coefficient threshold stored in the database. If the state evaluation coefficient corresponding to a certain area is greater than the state evaluation coefficient threshold stored in the database, then the patrol status corresponding to the area is judged to be abnormal, and it is fed back to the substation terminal. If the state evaluation coefficient corresponding to a certain area is less than or equal to the state evaluation coefficient threshold stored in the database, then the patrol status corresponding to the area is judged to be normal, and the patrol status corresponding to each area is obtained by judgment.

[0045] The database is used to store the data type, historical collection information, basic information, collection information and status evaluation coefficient threshold of each device.

[0046] The early warning terminal is used to issue an early warning prompt when the patrol status corresponding to a certain area is abnormal.

[0047] The embodiment of the present invention collects the data types of each device corresponding to each area of ​​the substation, and then selects the open sensors for the intelligent robot to collect the data types of each device in each area, and controls the intelligent robot to perform collection at various angles on the data types of each device in each area, and selects the collection angles of the intelligent robot corresponding to the data types of each device in each area, so as to control the intelligent robot to complete the patrol tasks corresponding to each area of ​​the substation, realize effective monitoring of the corresponding operating status of each area of ​​the substation, and ensure the safe operation of the substation, solve the deficiencies in the current technology, implement effective patrols corresponding to the data types of each device in each area, ensure the accuracy and efficiency of the patrol results of each area of ​​the substation, realize effective control of the intelligent robot to perform patrol tasks in each area of ​​the substation, experience convenient and efficient patrol monitoring, ensure that each area of ​​the substation is fully patrolled by the robot, reduce the corresponding safety hazards of each area of ​​the substation, and reduce the cost of manpower patrol. At the same time, the intelligent robot is equipped with high-precision equipment, which can monitor the equipment parameters of each area of ​​the substation in real time, ensure the accuracy and real-time of the patrol collection data, and maintain the corresponding safe operation of the substation from a more diverse and comprehensive perspective.

[0048] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art 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 shall all fall within the protection scope of the present invention.

Claims

1. An intelligent robot control system for substation inspection, characterized in that: include: The sensor selection module is used to control the intelligent robot to patrol the substation, collect the data types of each device corresponding to each area of ​​the substation, and then analyze the sensors of each device that the intelligent robot collects the data types of each device in each area; The sensor analysis module is used to obtain the historical collection performance information of each device sensor corresponding to each device data type in each area from the database, wherein the historical collection performance information includes collection accuracy, energy consumption and efficiency, and then screen out each open sensor for the intelligent robot to collect each device data type in each area; The patrol monitoring and collection module is used to control the intelligent robot to collect the data types of each device in each area at various angles when the open sensors of each area for collecting the data types of each device are screened, and to perform the collection of the data types of each area and each device according to the basic information of the data types of each area and each device according to the basic information of the data types of each area and each device, and then screen the collection angles of the intelligent robot corresponding to the data types of each area and each device; The basic information collected from each angle by each device data type in each area includes real-time data and coverage, and the real-time data includes frequency and transmission speed; The patrol status monitoring module is used to control the intelligent robot to perform collection and patrol of the data types of each device in each area according to the collection angle, obtain the collection information corresponding to the data type of each device in each area, and then analyze and obtain the corresponding status evaluation coefficient of each area, and determine the corresponding patrol status of each area; The analysis obtains the state assessment coefficient corresponding to each area, and the specific calculation process is as follows: By calculation formula: The patrol state θ corresponding to the i-th area is obtained by analysis i , i is the number of each area, i = 1, 2, ..., k, k is an arbitrary integer greater than 2, x is the number of each device data type, x = 1, 2, ..., s, s is an arbitrary integer greater than 2, r "is the preset reference gas concentration, h "is the preset reference leakage current, r ix is the gas concentration corresponding to the xth device data type in the ith area, h ix is the leakage current corresponding to the xth device data type in the ith region, w1 and w2 are the weight factor of the set gas concentration and the weight factor of the leakage current, 0<w1<1, 0<w2<1; The early warning terminal is used to issue an early warning prompt when the patrol status corresponding to a certain area is abnormal.

2. An intelligent robot control system for substation inspection according to claim 1, characterized in that: The analysis obtains the sensors of each device that the intelligent robot collects the data types of each device in each area. The specific analysis process is as follows: The data types of each device collected in response to the needs of each area of ​​the substation are compared with the functional types of sensors stored in the database. If the data type of a certain device collected in response to the needs of a certain area of ​​the substation is within a certain sensor functional type stored in the database, then the sensor is used as the device sensor corresponding to the intelligent robot in that area. In this way, the device sensors of each device data type collected in each area by the intelligent robot are analyzed.

3. The intelligent robot control system for substation inspection according to claim 1, characterized in that: The screening obtains each open sensor of each device data type collected by the intelligent robot in each area, and the specific screening process is as follows: According to the historical collection performance information of each device sensor corresponding to each equipment data type in each area, wherein the historical collection performance information includes collection accuracy, energy consumption and efficiency, the corresponding machine learning model is selected, and the historical collection performance information of each device sensor corresponding to each equipment data type in each area is input into the machine learning model, and the performance evaluation coefficient of each device sensor corresponding to each equipment data type in each area is obtained by analysis. When the performance evaluation coefficient of a device sensor corresponding to a device data type in a certain area is 0, it is determined that the device sensor is not used as a start sensor for the intelligent robot to collect the data type of the device in the area. When the performance evaluation coefficient of a device sensor corresponding to a device data type in a certain area is 1, it is determined that the device sensor is used as a start sensor for the intelligent robot to collect the data type of the device in the area. In this way, the start sensors for the intelligent robot to collect the data types of the devices in each area are screened.

4. An intelligent robot control system for substation inspection as claimed in claim 3, characterized in that: The analysis obtains the performance evaluation coefficient of each device sensor corresponding to each device data type in each area. The specific analysis process is as follows: By calculation formula: The performance evaluation coefficient of the hth device sensor corresponding to the xth device data type in the ith area is obtained by analysis. h is the number of each device sensor, h=1,2,.....,f, f is any integer greater than 2, i is the number of each area, i=1,2,......,k, k is any integer greater than 2, x is the number of each device data type, x=1,2,.....,s, s is any integer greater than 2, m hix is the acquisition accuracy of the xth device data type in the ith area corresponding to the hth device sensor, n hix is the energy consumption of the h-th device sensor corresponding to the x-th device data type in the ith area, σ hix is the efficiency of the h-th device sensor corresponding to the x-th device data type in the ith area, p1, p2 and p3 are the weight factors of acquisition accuracy, energy consumption and efficiency respectively, e is a natural constant, q is a preset reference performance value, 0<p1<1, 0<p2<1, 0<p3<1.

5. The intelligent robot control system for substation inspection according to claim 1, characterized in that: The screening obtains the collection angle of the intelligent robot corresponding to the data type of each device in each area. The specific screening process is as follows: According to the basic information of each area and each device data type executing collection at each angle, where the basic information includes real-time data and coverage, and the real-time data includes frequency and transmission speed, the corresponding machine learning model is selected, and the basic information of each area and each device data type executing collection at each angle is input into the machine learning model, and the performance coefficient of each area and each device data type executing collection at each angle is analyzed to obtain. When the performance coefficient of a certain device data type in a certain area executing collection at a certain angle is 0, it is determined that the angle is not used as the collection angle of the intelligent robot corresponding to the device data type in the area. When the performance coefficient of a certain device data type in a certain area executing collection at a certain angle is 1, it is determined that the angle is used as the collection angle of the intelligent robot corresponding to the device data type in the area, so as to screen and obtain the collection angle of the intelligent robot corresponding to each area and each device data type.

6. An intelligent robot control system for substation inspection as claimed in claim 5, characterized in that: The analysis obtains the performance coefficients of each device data type in each area for performing acquisition at each angle. The specific analysis process is as follows: By calculation formula: The performance coefficient Φ corresponding to the c-th angle acquisition of the x-th device data type in the i-th area is obtained by analysis. ixc , i is the number of each area, i=1,2,.....,k, k is any integer greater than 2, x is the number of each device data type, x=1,2,.....,s, s is any integer greater than 2, c is the x number of each angle, c=1,2,.....b, b is any integer greater than 2, Q ixc is the frequency collected at the cth angle corresponding to the xth device data type in the ith region, R ixc is the transmission speed of the xth device data type in the ith area corresponding to the cth angle acquisition, J ixc is the coverage rate collected at the c-th angle for the x-th device data type in the ith area, L is the set reference performance value, ν1, ν2, and ν3 are the weighting factors of frequency, transmission speed, and coverage, respectively, 0<ν1<1, 0<ν2<1, 0<ν3<1.

7. The intelligent robot control system for substation inspection according to claim 1, characterized in that: The judgment obtains the patrol status corresponding to each area, and the specific judgment process is as follows: The state assessment coefficient corresponding to each area is compared with the state assessment coefficient threshold stored in the database. If the state assessment coefficient corresponding to an area is greater than the state assessment coefficient threshold stored in the database, the patrol state corresponding to the area is judged to be abnormal, and it is fed back to the substation terminal. If the state assessment coefficient corresponding to an area is less than or equal to the state assessment coefficient threshold stored in the database, the patrol state corresponding to the area is judged to be normal. The patrol state corresponding to each area is determined in this way.

8. The intelligent robot control system for substation inspection according to claim 1, characterized in that: It also includes a database, which is used to store the data type, historical collection information, basic information, collection information and status evaluation coefficient threshold of each device.

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