Double-arm collaborative operation method suitable for transformer substation tubular bus carrying electrified robot

Abstract

The invention discloses a double-arm collaborative operation method suitable for a transformer substation tubular bus carrying electrified robot, and relates to the technical field of power system automation. Comprising the following steps: comparing an electromagnetic change threshold value with a dynamic threshold value to obtain an electromagnetic environment change parameter and an early warning signal; adjusting the control parameters of the robot and the sensitivity of a sensor through the early warning signal; determining a strong electromagnetic field area through the electromagnetic environment change parameters, and planning an inspection path of the robot; and according to the inspection path, carrying out tubular bus-bar drainage wire lapping / dismounting operation at the target position. According to the method, the electromagnetic environment change in the transformer substation is monitored in real time, the electromagnetic change threshold value is determined and compared with the dynamic threshold value, and the early warning signals of different levels are generated, so that an operator can be reminded in time or robot parameters can be automatically adjusted, and equipment faults or safety accidents caused by a strong electromagnetic field are avoided.

Description

Technical Field

[0001] The invention relates to the technical field of power system automation, and in particular to a dual-arm collaborative operation method of an electric robot applicable to a busbar clamping transformer substation. Background Art

[0002] With the construction and development of smart grids, the automation and intelligence level of substations is constantly improving. Especially in high-voltage substations, the demand for live-line work is increasing. However, the traditional live-line work method mainly relies on manual labor, which has great safety risks and labor costs. Therefore, the dual-arm collaborative robot is widely used in live-line work in substations because it can simulate the collaborative work of human hands.

[0003] The Chinese invention patent with announcement number CN109648303A discloses a busbar hardware screw locking and unloading device for a live working robot and a locking and unloading method thereof, comprising an insulating boom truck, a boom truck working arm mounted on the insulating boom truck, a working platform provided on the boom truck working arm, a three-dimensional scanner, a slave mechanical arm, a locking / unloading electric screw mechanism, an active mechanical arm and an equipotential rod provided on the working platform, an active mechanical arm binocular camera provided at the front of the active mechanical arm, a slave mechanical arm binocular camera provided at the front of the slave mechanical arm, and the locking / unloading electric screw mechanism installed at the end of the active mechanical arm; the labor intensity of the locking and unloading operation of the busbar hardware screws of the substation equipment is reduced, the efficiency and automation level are improved, the personal safety of the operators is guaranteed, the number of robots required is small, and the impact of electromagnetic interference on information transmission is reduced.

[0004] In the process of performing live-line operations using robots in the above and similar methods, since the robots are usually equipped with multi-degree-of-freedom robotic arms, sensor systems and control systems, and there is usually a strong electromagnetic field inside the substation, the electronic equipment and sensors of the robots may be interfered with during the live-line operations, affecting their normal operation. Summary of the invention

[0005] The purpose of the present invention is to provide a dual-arm collaborative operation method of a live robot applicable to a busbar clamping in a transformer substation, so as to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a method for coordinating the operation of a busbar clamping robot with two arms in a transformer substation, comprising:

[0007] Establish an environmental monitoring module: monitor the electromagnetic environment changes in the substation, determine the electromagnetic change threshold, and compare the electromagnetic change threshold with the dynamic threshold to obtain electromagnetic environment change parameters and early warning signals;

[0008] Determine operating parameters: adjust the control parameters of the robot and the sensitivity of the sensor through the early warning signal;

[0009] Setting inspection avoidance strategy: Determine the strong electromagnetic field area in the working environment of the substation through the electromagnetic environment change parameters, and plan the inspection path of the robot according to the strong electromagnetic field area and operating parameters, including:

[0010] Comparing the electromagnetic environment change parameter with the electromagnetic field strength threshold, and dividing the working area corresponding to the electromagnetic environment change parameter into a normal area, a light interference area, a moderate interference area and a strong interference area according to the comparison result;

[0011] According to the division result of the working area, the interference level corresponding to each working area is determined, and the cost input corresponding to each working area is obtained. At the same time, according to the cost input, the inspection path is determined. The calculation formula of the cost input is specifically:

[0012]

[0013] Where: V(i, j) is the cost input from the starting point to the i-th row and j-th column in the grid, C(i, j) is the cost of reaching the i-th row and j-th column in the grid from the previous step, V(i-1, j) is the cost input from the starting point to the i-1-th row and j-th column in the grid, V(i, j-1) is the cost input from the starting point to the i-th row and j-1-th column in the grid, min(V(i-1, j), V(i, j-1)) is the minimum cost from the upper position and the left position to the current position, d is a fixed distance cost, η is the weight of the electromagnetic field strength, and R(i, j) is the electromagnetic field strength level at the i-th row and j-th column in the grid;

[0014] Double-arm collaborative operation: According to the inspection path, the robot reaches the target position and performs the operation of installing / removing the drainage line of the busbar at the target position.

[0015] Furthermore, the electromagnetic environment change parameters and early warning signals are obtained, including:

[0016] Building an environmental monitoring system: Setting up sensor nodes inside the substation and acquiring sensor data;

[0017] Determine the electromagnetic dynamic threshold: obtain the electromagnetic field strength prediction value through the sensor data, and determine the electromagnetic dynamic threshold corresponding to each moment according to the electromagnetic field strength prediction value and the smoothing results of different time windows;

[0018] Generate a warning signal: compare the electromagnetic field strength data obtained in real time with the electromagnetic dynamic threshold, and when the electromagnetic field strength data is different from the electromagnetic dynamic threshold, determine the range of the electromagnetic field strength data exceeding the electromagnetic dynamic threshold, specifically:

[0019] When the electromagnetic field strength data exceeds the electromagnetic dynamic threshold by 10%, a slight interference warning signal is generated;

[0020] When the electromagnetic field strength data exceeds 30% of the electromagnetic dynamic threshold, a warning signal of medium interference is generated;

[0021] When the electromagnetic field strength data exceeds 50% of the electromagnetic dynamic threshold, a serious interference warning signal is generated;

[0022] Obtaining electromagnetic environment change parameters: Obtaining the change in electromagnetic field strength data between two adjacent moments through the sensor data, and determining the change rate of the electromagnetic field strength data within the monitoring time according to the monitoring time.

[0023] Furthermore, determining the electromagnetic dynamic threshold corresponding to each moment includes:

[0024] M1: according to the electromagnetic field strength data in the sensor data, obtaining an average value of the electromagnetic field strength data, wherein the average value of the electromagnetic field strength data is the initial dynamic threshold value;

[0025] M2: Setting a machine learning model, and using the electromagnetic field strength data as input of the machine learning model, and outputting a predicted value of the electromagnetic field strength data;

[0026] M3: According to the initial dynamic threshold and the predicted value of the electromagnetic field intensity data, the short-time smoothing result and the long-time smoothing result corresponding to each moment are obtained, and the short-time smoothing result and the long-time smoothing result are merged to obtain the dynamic threshold corresponding to each moment, specifically:

[0027]

[0028] Where: Y t is the dynamic threshold corresponding to the tth moment, ω1 is the weight corresponding to the short-time smoothing result, is the short-time smoothing result corresponding to the tth moment, ω2 is the weight corresponding to the long-time smoothing result, is the long-term smoothing result corresponding to the tth moment.

[0029] Furthermore, the smoothing result corresponding to each moment is as follows:

[0030]

[0031] Where: y t is the smoothing result corresponding to the tth moment, α is the smoothing factor, is the predicted value of the electromagnetic field intensity corresponding to the tth moment, y t-1 is the smoothing result corresponding to the t-1th moment.

[0032] Furthermore, the smoothing factors corresponding to the smoothing results at different times satisfy the following relationship, specifically:

[0033] The size of the smoothing factor corresponding to the short-time smoothing result is greater than the size of the smoothing factor corresponding to the long-time smoothing result.

[0034] Furthermore, adjusting the control parameters of the robot and the sensitivity of the sensor includes:

[0035] Adjust the robot's inspection speed and frequency: according to the level of the warning signal, increase the robot's inspection speed and frequency, specifically:

[0036] When the level of the warning signal is slight interference, the inspection speed and frequency of the robot remain unchanged;

[0037] When the level of the warning signal is medium interference, the inspection speed of the robot is reduced by 30% and the inspection frequency is increased by 10%;

[0038] When the level of the warning signal is severe interference, the inspection speed of the robot is reduced by 50% and the inspection frequency is increased by 20%;

[0039] Adjust the sensitivity of the sensor: according to the level of the warning signal, increase the sensitivity of the sensor, specifically:

[0040] When the level of the warning signal is slight interference, the sensitivity of the sensor remains unchanged;

[0041] When the level of the warning signal is medium interference, the sensitivity of the sensor increases by 10%;

[0042] When the level of the early warning signal is severe interference, the sensitivity of the sensor increases by 20%.

[0043] Furthermore, according to the cost investment, the inspection path is determined, including:

[0044] N1: Divide the inspection area in the substation into grids, and determine the coordinate position corresponding to each inspection area, and determine the interference level corresponding to each inspection area according to the division result of the working area;

[0045] N2: Obtaining the cost investment corresponding to each coordinate position according to the coordinate position and the interference level;

[0046] N3: According to the target position of the robot, the cost inputs of all previous positions corresponding to the target position are obtained, and the minimum cost input is determined from the cost inputs of all previous positions. The position corresponding to the minimum cost input is the inspection position on the inspection path. Repeat step N3 until the position corresponding to the minimum cost input is determined to be the starting position of the robot.

[0047] Furthermore, the electromagnetic field intensity thresholds are set to 100 μT, 200 μT and 300 μT.

[0048] Furthermore, the operation of installing / removing the drainage line of the busbar at the target position includes:

[0049] Environmental modeling: The position of the busbar in the substation is modeled in three dimensions by using a laser radar, and the parking position and the lifting height position of the lifting vehicle are determined based on the three-dimensional modeling;

[0050] Laying / leading line operation: The robot is transported to the position of the pipe busbar through the parking position and the rising height position of the lifting work vehicle, and the main arm of the robot is hung with a pulley and equipotential operation is performed. The slave arm of the robot is visually assisted, and the operating status of the main arm and the slave arm of the robot is determined according to the classification of the laying / leading operation, specifically:

[0051] When performing rigging operations:

[0052] The slave arm fixes the drainage plate, the master arm grinds the drainage plate, and at the same time the master arm grabs the bolt tool, the slave arm grabs the nut tool, and pierces and tightens the bolt tool and the nut tool;

[0053] When dismantling operations are being performed:

[0054] The main arm takes the bolt tool, and the slave arm takes the nut tool, and removes the bolt tool and the nut tool.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] Firstly, the present invention can monitor the electromagnetic environment changes in the substation in real time by establishing an environmental monitoring module, determine the electromagnetic change threshold and compare it with the dynamic threshold, obtain the electromagnetic environment change parameters and early warning signals, and generate early warning signals of different levels according to the changes in the electromagnetic field strength, so as to timely remind the operator or automatically adjust the robot parameters, thereby avoiding equipment failure or safety accidents caused by strong electromagnetic fields;

[0057] Second: The present invention dynamically adjusts the sensitivity of the sensor according to the level of the early warning signal, ensuring that environmental data can be accurately obtained under different interference conditions. At the same time, the inspection speed and frequency of the robot can be adjusted according to the level of the early warning signal, further ensuring the safety of operations in strong electromagnetic field areas;

[0058] Thirdly, the present invention determines the strong electromagnetic field area through the electromagnetic environment change parameters, and plans the robot's inspection path according to these areas and operating parameters, thereby avoiding the robot from operating in high-risk areas. At the same time, in the path planning, the cost investment of each position is calculated to select the optimal path, thereby ensuring the safety and effectiveness of the inspection task;

[0059] Fourthly: the robot of the present invention carries out division of labor and cooperation through the main arm and the slave arm, wherein the main arm is responsible for the main operation, and the slave arm provides visual assistance and auxiliary operation, thereby improving the coordination and flexibility of the operation. At the same time, the robot can complete the operation task continuously and efficiently without being affected by fatigue and environmental factors, thereby improving the operation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a schematic diagram of the process of the dual-arm collaborative operation method of the present invention;

[0061] Figure 2 A schematic diagram of a process for obtaining an early warning signal according to the present invention;

[0062] Figure 3 A schematic diagram of a process for determining an inspection path according to the present invention;

[0063] Figure 4 A grid distribution map corresponding to the area to be inspected in the substation of the present invention;

[0064] Figure 5 It is the electromagnetic field intensity distribution diagram corresponding to each area of ​​the present invention;

[0065] Figure 6 It is the interference level distribution diagram corresponding to each area of ​​the present invention;

[0066] Figure 7 The inspection path diagram corresponding to each area of ​​the present invention;

[0067] Figure 8 It is a position distribution diagram between the robot and the lifting work vehicle of the present invention. DETAILED DESCRIPTION

[0068] 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.

[0069] With the rapid development of modern industry and the improvement of people's living standards, power users' requirements for power supply reliability are also constantly increasing. In order to reduce power outage time or even achieve uninterrupted operation, power supply companies in various places have accelerated the application and promotion of live working robots in substations. However, since robots are usually equipped with multi-degree-of-freedom robotic arms, sensor systems and control systems, and there is usually a strong electromagnetic field inside the substation, the electronic equipment and sensors of the robot will be interfered with during live working, affecting its normal operation. The technical solution provided by this application, by establishing an environmental monitoring module, determines the strong electromagnetic field area in the substation, and avoids the strong electromagnetic field area in advance when planning the robot's inspection route. At the same time, according to the early warning signal, the control parameters of the robot and the sensitivity of the sensor are adjusted, thereby avoiding equipment failures or safety accidents caused by strong electromagnetic fields.

[0070] refer to Figure 1-Figure 3 This embodiment provides a dual-arm collaborative operation method for a busbar clamping robot in a substation, and the collaborative operation method includes the following steps:

[0071] Step S1: Establish an environmental monitoring module. That is, by monitoring the electromagnetic environment changes in the substation, determine the electromagnetic change threshold. At the same time, compare the determined electromagnetic change threshold with the dynamic threshold to obtain the electromagnetic environment change parameters and early warning signals. The details are as follows:

[0072] Step S1.1: Build an environmental monitoring system. That is, by deploying multiple sensor nodes at different locations in the substation, specifically, sensor nodes are set up in key equipment (such as transformers, circuit breakers and busbars), inlet and outlet areas, control rooms and operation rooms, and outdoor areas (such as around the substation wall) to form a grid monitoring network, so as to effectively monitor the changes in the electromagnetic environment in the substation. Further, the electromagnetic field strength in the substation is monitored by electromagnetic field strength sensors, such as fluxgate magnetometers and Hall effect sensors. The ambient temperature is detected by temperature sensors, such as thermocouples and thermistors. The ambient humidity is monitored by humidity sensors, such as capacitive humidity sensors and resistive humidity sensors. The ambient air pressure is monitored by pressure sensors, such as piezoresistive air pressure sensors and capacitive air pressure sensors.

[0073] In the specific implementation process, sensors are deployed near key equipment such as transformers, circuit breakers and busbars to monitor the electromagnetic field strength, temperature, humidity and air pressure around the key equipment. Similarly, sensors are deployed in the incoming and outgoing line areas of the substation to monitor the environmental parameters of the incoming and outgoing line areas. Similarly, sensors are deployed in the control room and operation room to ensure that the environmental conditions in the area meet the operating requirements. Similarly, sensors are deployed around the substation walls to monitor the impact of the external environment on the substation.

[0074] Step S1.2: Determine the dynamic threshold of electromagnetic. That is, continuously collect the electromagnetic field strength, temperature, humidity and air pressure data in the substation to obtain the signal data set of the substation. At the same time, the obtained signal data set is preprocessed, including but not limited to data cleaning and denoising. Further, the dynamic threshold of electromagnetic is obtained through the preprocessed signal data set. The details are as follows:

[0075] Step M1: Obtain electromagnetic field strength data through the environmental monitoring system built in step S1.1, and determine the size of the initial dynamic threshold based on the electromagnetic field strength data. That is, the average value of the acquired electromagnetic field strength data is the initial size of the dynamic threshold.

[0076] In the process of specific implementation, the electromagnetic field strength data shown in the following table is set, specifically:

[0077] time t＝1 t＝2 t＝3 t＝4 t＝5 Electromagnetic field strength 100 105 110 115 120

[0078] According to the above data, the average value of the electromagnetic field strength data is 110, that is, the initial value of the dynamic threshold is set to 100.

[0079] Step M2: Obtain the predicted value of the electromagnetic field strength data obtained by the machine learning model through the machine learning model and the electromagnetic field strength data obtained in step M1. In this embodiment, the machine learning model is set to an LSTM model, that is, the electromagnetic field strength data obtained in step M1 is used as the input of the LSTM model, and the output obtains the corresponding electromagnetic field strength predicted value.

[0080] In the specific implementation process, according to the electromagnetic field strength data in step M1, the electromagnetic field strength prediction value output by the LSTM model as shown in the following table is obtained, specifically:

[0081] Time / t t＝1 t＝2 t＝3 t＝4 t＝5 <![CDATA[Electromagnetic field strength / x t > 102 107 112 117 122

[0082] Step M3: Obtain smoothing results of different time windows, and fuse the smoothing results of different time windows. At the same time, dynamically obtain the size of the dynamic threshold corresponding to each moment according to the electromagnetic field strength prediction value obtained in step M2. In this embodiment, the formula for obtaining the dynamic threshold corresponding to each moment is specifically:

[0083]

[0084] Where: Y t is the dynamic threshold corresponding to the tth moment, ω1 is the weight corresponding to the short-time smoothing result, is the short-time smoothing result corresponding to the tth moment, ω2 is the weight corresponding to the long-time smoothing result, is the long-term smoothing result corresponding to the tth moment.

[0085] In this embodiment, the short-time smoothing result corresponding to the tth moment is The formula for obtaining is:

[0086]

[0087] in: is the short-time smoothing result corresponding to the tth moment, α d is the short-term smoothing factor, is the predicted value of the electromagnetic field intensity corresponding to the tth moment, is the short-time smoothing result corresponding to the t-1th moment.

[0088] Furthermore, the long-term smoothing result corresponding to the tth moment is The formula for obtaining is:

[0089]

[0090] in: is the long-term smoothing result corresponding to the tth moment, α l is the long-term smoothing factor, is the predicted value of the electromagnetic field intensity corresponding to the tth moment, is the long-term smoothing result corresponding to the t-1th moment.

[0091] It is worth noting that the short-term smoothing factor α d The size of > long-term smoothing factor α l At the same time, in this embodiment, the short-term smoothing factor α d The size is generally set to 0.1 or 0.2, and the long-term smoothing factor α l The size is generally set to 0.05 or 0.1.

[0092] In the process of specific implementation, the short-term smoothing factor α d The size is set to 0.1, and the long-term smoothing factor α l The size of is set to 0.05, the size of the weight ω1 corresponding to the short-time smoothing result is set to 0.7, and the size of the weight ω2 corresponding to the long-time smoothing result is set to 0.3.

[0093] That is to say, according to the initial value of the dynamic threshold obtained in the above step M1 being 100, according to the predicted value of the electromagnetic field intensity at the future moment obtained in the above step M2, the short-time smoothing results corresponding to the moment t1 to the moment t5 are respectively:

[0094] At time t1:

[0095] At time t2:

[0096] Time t3:

[0097] Time t4:

[0098] Time t5:

[0099] Similarly, the long-term smoothing results corresponding to time t1-t5 are:

[0100] At time t1:

[0101] At time t2:

[0102] Time t3:

[0103] Time t4:

[0104] Time t5:

[0105] That is to say, the dynamic threshold values ​​corresponding to time t1 to time t5 are:

[0106] At moment t1: Y1=0.7×100.2+0.3×100.1=100.17.

[0107] At moment t2: Y2=0.7×100.88+0.3×100.245=100.6545.

[0108] At time t3: Y3 = 0.7 × 101.692 + 0.3 × 100.48275 = 101.187175.

[0109] At moment t4: Y4=0.7×102.6228+0.3×100.7636125≈101.7808576.

[0110] At moment t5: Y5 = 0.7×103.66052+0.3×101.0754319≈102.4339176.

[0111] Step S1.3: Generate an early warning signal. The real-time monitored electromagnetic field strength data is compared with the electromagnetic dynamic threshold values ​​corresponding to different times determined in step M3. When the real-time monitored electromagnetic field strength data is different from the electromagnetic dynamic threshold value, it is determined that the electromagnetic field strength data exceeds the range of the electromagnetic dynamic threshold value.

[0112] Specifically, when the electromagnetic field intensity data exceeds 10% of the electromagnetic dynamic threshold value, a slight interference warning signal is generated, and the robot can continue to operate at this time.

[0113] When the electromagnetic field intensity data exceeds 30% of the electromagnetic dynamic threshold value, a medium interference warning signal is generated, and the control parameters of the robot need to be adjusted at this time.

[0114] When the electromagnetic field intensity data exceeds 50% of the electromagnetic dynamic threshold value, a serious interference warning signal is generated, and the robot stops running.

[0115] Step S1.4: Obtain electromagnetic environment change parameters. That is, through the environmental monitoring system built in step S1.1, the sensor data can be obtained, that is, the electromagnetic field strength, temperature, humidity and air pressure data monitored in real time can be obtained. In other words, by calculating the change rate of the electromagnetic field strength corresponding to each moment, the degree of interference of the electromagnetic field on the operation of the robot at each moment can be determined during the operation of the robot. Furthermore, by obtaining the cumulative change of the electromagnetic field strength, the interference situation over a long period of time can be determined.

[0116] In the process of specific implementation, the data in the following table can be obtained, specifically:

[0117] time Electromagnetic field strength temperature humidity Air pressure t＝1 100 20 50 1013 t＝2 105 22 52 1012 t＝3 110 21 51 1011 t＝4 115 23 53 1010 t＝5 120 24 54 1009

[0118] According to the data in the above table and the dynamic threshold values ​​obtained in the above process, we can know that:

[0119] At time t1: the electromagnetic field intensity monitored in real time is 100, and the dynamic threshold value is 100.17. At this time, the excess range between the two is: 0.0017.

[0120] In other words, the electromagnetic field strength at time t1 did not trigger the generation of a warning signal.

[0121] At time t2: the electromagnetic field intensity monitored in real time is 105, and the dynamic threshold value is 100.6545. At this time, the excess range between the two is: 0.0432.

[0122] In other words, the electromagnetic field strength at time t2 did not trigger the generation of a warning signal.

[0123] At time t3: the electromagnetic field intensity monitored in real time is 110, and the dynamic threshold value is 101.187175. At this time, the excess range between the two is: 0.0871.

[0124] In other words, the electromagnetic field strength at time t3 did not trigger the generation of a warning signal.

[0125] At time t4: the real-time monitored electromagnetic field strength is 115, and the dynamic threshold value is 101.7808576. At this time, the excess range between the two is: 0.1299.

[0126] That is to say, the electromagnetic field strength at time t4 exceeds the range, which triggers the generation of a warning signal for slight interference.

[0127] At time t5: the electromagnetic field intensity monitored in real time is 120, and the dynamic threshold value is 102.4339176. At this time, the excess range between the two is: 0.1715.

[0128] That is to say, the electromagnetic field strength at time t5 exceeds the range, which triggers the generation of a warning signal for slight interference.

[0129] Furthermore, according to the data in the above table, it can be known that the size of the electromagnetic environment change parameter is the cumulative result of the change rate of the electromagnetic field intensity in the above table data, and the result is: 20.

[0130] Step S2: Determine the operating parameters. That is, adjust the robot's control parameters and sensor sensitivity according to the level of the warning signal generated in step S1.3. The details are as follows:

[0131] Step S2.1: Adjust the robot's inspection speed and frequency. That is, increase the robot's inspection speed and frequency according to the level of the warning signal. Specifically:

[0132] When the level of the warning signal is slight interference, the robot's inspection speed and frequency remain unchanged.

[0133] When the level of the warning signal is medium interference, the robot's inspection speed is reduced to 70% of the current speed, and the robot's inspection frequency is increased by 10%.

[0134] When the level of the warning signal is severe interference, the robot's inspection speed is reduced to 50% of the current speed, and the robot's inspection frequency is increased by 20%.

[0135] Step S2.2: Adjust the sensitivity of the sensor. That is, adjust the sensitivity of the sensor according to the level of the warning signal. Specifically:

[0136] When the level of the warning signal is slight interference, the sensitivity of the sensor remains unchanged.

[0137] When the level of the warning signal is medium interference, the sensitivity of the sensor increases by 10%.

[0138] When the level of the warning signal is severe interference, the sensitivity of the sensor increases by 20%.

[0139] In the process of specific implementation, the data in the following table can be obtained, specifically:

[0140] time Electromagnetic field strength Dynamic Threshold speed Inspection frequency Sensor sensitivity t＝1 100 100.17 1.0m / s 1 time / hour 1.0 t＝2 105 100.6545 1.0m / s 1 time / hour 1.0 t＝3 110 101.187175 1.0m / s 1 time / hour 1.0 t＝4 115 101.7808576 1.0m / s 1 time / hour 1.0 t＝5 120 102.4339176 1.0m / s 1 time / hour 1.0

[0141] According to the data in the above table:

[0142] If the warning signal is not triggered at time t1, the robot's inspection speed and frequency remain unchanged, and the sensitivity of the sensor remains unchanged.

[0143] If the warning signal is not triggered at time t2, the robot's inspection speed and frequency remain unchanged, and the sensitivity of the sensor remains unchanged.

[0144] If the warning signal is not triggered at time t3, the robot's inspection speed and frequency remain unchanged, and the sensitivity of the sensor remains unchanged.

[0145] When a slight interference warning signal is triggered at time t4, the robot's inspection speed and frequency remain unchanged, and the sensitivity of the sensor remains unchanged.

[0146] When a slight interference warning signal is triggered at time t5, the robot's inspection speed and frequency remain unchanged, and the sensitivity of the sensor remains unchanged.

[0147] Step S3: Set the inspection avoidance strategy. That is, through the electromagnetic environment change parameters, the strong electromagnetic field area is determined in the working environment of the substation, and the robot's inspection path is planned according to the determined strong electromagnetic field area and the operating parameters determined in step S2, so as to effectively avoid the robot from operating in high-risk areas and ensure the safety and effectiveness of the inspection task. The details are as follows:

[0148] Step S3.1: Compare the electromagnetic environment change parameter obtained in step S1.4 with the preset electromagnetic field strength threshold, and divide the working area corresponding to the electromagnetic environment change parameter according to the comparison result. It is worth noting that the preset electromagnetic field strength threshold is generally set to 100μT, 200μT and 300μT. In other words, according to the different values ​​of the electromagnetic field strength threshold, the obtained electromagnetic environment change parameter is divided into different ranges, specifically:

[0149] Normal area: Electromagnetic environment change parameters <100μT.

[0150] Mild interference area: 100μT≤electromagnetic environment change parameter<200μT.

[0151] Moderate interference area: 200μT≤electromagnetic environment change parameter<300μT.

[0152] Strong interference area: electromagnetic environment change parameter ≥ 300μT.

[0153] Step S3.2: According to the interference area determined in step S3.1, the initial inspection path is adjusted to avoid the determined interference area and ensure the safety and effectiveness of the robot inspection work. The details are as follows:

[0154] Step N1: According to the plan of the substation, the inspection area in the substation is divided into grids, and the coordinate position corresponding to each inspection area is determined.

[0155] Furthermore, according to the division range of the electromagnetic environment change parameter determined in the above step S3.1, it is matched with each inspection area, so as to determine the interference level corresponding to each inspection area. Specifically, the interference level of the normal area is 0, the interference level of the lightly interfered area is 1, the interference level of the moderately interfered area is 2, and the interference level of the strongly interfered area is 3.

[0156] Step N2: According to the coordinate position and interference level corresponding to each inspection area determined in step N1, the cost investment corresponding to each position is determined. In this embodiment, the calculation formula of the cost investment is specifically:

[0157]

[0158] Where: V(i, j) is the cost from the starting point to the i-th row and j-th column in the grid, C(i, j) is the cost from the previous step to the i-th row and j-th column in the grid, V(i-1, j) is the cost from the starting point to the i-1-th row and j-th column in the grid, V(i, j-1) is the cost from the starting point to the i-th row and j-1-th column in the grid, min(V(i-1, j), V(i, j-1)) is the minimum cost from the upper position and the left position to the current position, d is a fixed distance cost, η is the weight of the electromagnetic field strength, and R(i, j) is the electromagnetic field strength level at the i-th row and j-th column in the grid.

[0159] Step N3: According to the initial position of the robot and the target position to be inspected, trace back from the target position to the initial position. Specifically, according to the cost input corresponding to each position obtained in step N2, starting from the target position, gradually determine all the cost inputs at the previous position adjacent to it, and determine the minimum cost input from all the cost inputs at the previous position. The previous position corresponding to the minimum cost input is the inspection position during the inspection process. Repeat this process until it traces back to the initial position. In other words, in the process of backtracking from the target position, the connection lines of all the previous positions obtained are the inspection path of the robot from the initial position to the target position.

[0160] In the process of specific implementation, refer to Figure 4-Figure 7 ,in Figure 4 The grid distribution diagram after the grid division of the area to be inspected in the substation. Figure 5 is the electromagnetic field intensity distribution diagram corresponding to each area, Figure 6 is the interference level distribution map corresponding to each area, Figure 7 The inspection route map determined for each area; Figure 4-Figure 6 The data in Figure 4 Take the data location in as an example to explain it in detail):

[0161] The cost input corresponding to the first row is:

[0162] V(1,1)=0.

[0163] V(1,2)=V(1,1)+1+10*1=11.

[0164] V(1,3)=V(1,2)+1+10*3=42.

[0165] V(1,4)=V(1,3)+1+10*1=53.

[0166] The cost input corresponding to the second line is:

[0167] V(2,1)=V(1,1)+1+10*3=31.

[0168] V(2,2)=min(V(2,1), V(1,2))+1+10*0=11+1+0=12.

[0169] V(2,3)=min(V(2,2), V(1,3))+1+10*0=12+1+0=13.

[0170] V(2,4)=min(V(2,3), V(1,4))+1+10*1=13+1+10=24.

[0171] The cost input corresponding to the third line is:

[0172] V(3,1)=V(2,1)+1+10*3=61.

[0173] V(3,2)=min(V(3,1), V(2,2))+1+10*0=12+1+0=13.

[0174] V(3,3)=min(V(3,2), V(2,3))+1+10*0=13+1+0=14.

[0175] V(3,4)=min(V(3,3), V(2,4))+1+10*2=14+1+20=35.

[0176] The cost input corresponding to the fourth line is:

[0177] V(4,1)=V(3,1)+1+10*1=73.

[0178] V(4,2)=min(V(4,1), V(3,2))+1+10*1=13+1+10=24.

[0179] V(4,3)=min(V(4,2), V(3,3))+1+10*3=14+1+30=45.

[0180] V(4,4)=min(V(4,3), V(3,4))+1+10*0=35+1+0=36.

[0181] In this embodiment, the target position to be inspected is set to (4,4), and the initial position to start is set to (1,1). Therefore, according to the cost investment obtained above, it can be known that:

[0182] Starting from the cost input V(4,4) corresponding to the target position, determine the cost inputs in all the previous adjacent positions one by one. Specifically:

[0183] The size of the cost input V(4,4) is 36, and all of its previous adjacent positions are position (3,4) and position (4,3). In this embodiment, the size of the cost input V(3,4) is 35, and the size of the cost input V(4,3) is 45. That is, the previous adjacent position of position (4,4) is position (3,4).

[0184] Furthermore, the size of the cost input V(3,4) is 35, and all of its previous adjacent positions are position (3,3) and position (2,4). In this embodiment, the size of the cost input V(2,4) is 24, and the size of the cost input V(3,3) is 14. That is, the previous adjacent position of position (3,4) is position (3,3).

[0185] Furthermore, the size of the cost input V(3,3) is 14, and all of its previous adjacent positions are position (3,2) and position (2,3). In this embodiment, the size of the cost input V(2,3) is 13, and the size of the cost input V(3,2) is 13. In other words, the previous adjacent position of position (3,4) is position (2,3) or position (3,2).

[0186] It is worth noting that at this time, the inspection path can be further determined by the size of the previous adjacent position of position (2,3) and the previous adjacent position of position (3,2). Specifically, all the previous adjacent positions of position (2,3) are position (2,2) and position (1,3). In this embodiment, the size of the cost input V(2,2) is 12, and the size of the cost input V(1,3) is 42. In other words, the previous adjacent position of position (2,3) selects position (2,2).

[0187] Similarly, the previous adjacent positions of position (3,2) are position (3,1) and position (2,2). In this embodiment, the size of cost input V(2,2) is 12, and the size of cost input V(3,1) is 62. In other words, the previous adjacent position of position (3,2) is position (2,2).

[0188] That is to say, the cost of reaching position (3,2) and position (2,3) via position (2,2) is the same, so either position (3,2) or position (2,3) can be chosen.

[0189] Further, the size of the cost input V(2,2) is 12, and all of its previous adjacent positions are position (1,2) and position (2,1). In this embodiment, the size of the cost input V(1,2) is 11, and the size of the cost input V(2,1) is 31. In other words, the previous adjacent position of position (2,2) is position (1,2).

[0190] Furthermore, the cost input V(1,2) is 11, and all of its previous adjacent positions are positions (1,1), which are the initial positions. Thus, the required inspection path can be obtained based on the positions obtained by the above comparison. In other words, the inspection path determined in this embodiment is:

[0191] (1,1)→(1,2)→(2,2)→(3,2) / (2,3)→(3,3)→(3,4)→(4,4).

[0192] In other words, the area corresponding to its inspection path is:

[0193] A→B→F→G / J→K→L→P.

[0194] Step S4: Double-arm collaborative operation. That is, according to the inspection path determined in step N3, the robot moves from the starting position to the target position, and performs the operation of laying / removing the drainage line of the pipe busbar at the target position. The details are as follows:

[0195] Step S4.1: Environmental modeling. That is, the surrounding environment of the busbar in the substation is modeled in three dimensions by laser radar, and the parking position of the lifting vehicle is determined based on the three-dimensional modeling results. It is worth noting that the robot is set on the upper part of the lifting vehicle, such as Figure 8 Place it.

[0196] That is to say, after determining the parking position of the lifting vehicle according to the position of the busbar in the substation, the three-phase line of the busbar is scanned by the laser radar to determine the height position to which the lifting vehicle should rise. At the same time, a safety fence is built for the other two phases to ensure a safe distance when the robot performs streamlined operations.

[0197] Step S4.2: Attaching / draining line operation. That is, controlling the robot's main arm to hang the pulley and hang the equal potential, while the robot's slave arm performs visual assistance, that is, during the process of the main arm hanging the pulley and the equal potential operation, the slave arm performs visual observation to ensure the accuracy of the main arm's operation.

[0198] Furthermore, during the rigging operation, after the pulley and equipotential operations are completed, the slave arm grabs the clamping device to fix the drain plate to ensure the stability of the drain plate. At the same time, the main arm grabs the grinding device to grind the rust and stains on the drain plate to ensure the cleanness of the contact surface. After that, the main arm grabs the bolt tool and the slave arm grabs the nut tool to pierce and tighten the bolts and nuts to complete the rigging operation. It is worth noting that during the dismantling operation, after the pulley and equipotential operations are completed, the main arm takes the bolt tool and the slave arm takes the nut tool to remove the bolts and nuts in turn to complete the dismantling operation.

[0199] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is limited by the attached embodiments and their equivalents.

Claims

1. A method for coordinating the operation of a robot with two arms for clamping an electric busbar in a substation, characterized in that: Included are: Establish an environmental monitoring module: monitor the electromagnetic environment changes in the substation, determine the electromagnetic change threshold, and compare the electromagnetic change threshold with the dynamic threshold to obtain electromagnetic environment change parameters and early warning signals; Determine operating parameters: adjust the control parameters of the robot and the sensitivity of the sensor through the early warning signal; Setting inspection avoidance strategy: Determine the strong electromagnetic field area in the working environment of the substation through the electromagnetic environment change parameters, and plan the inspection path of the robot according to the strong electromagnetic field area and operating parameters, including: Comparing the electromagnetic environment change parameter with the electromagnetic field strength threshold, and dividing the working area corresponding to the electromagnetic environment change parameter into a normal area, a light interference area, a moderate interference area and a strong interference area according to the comparison result; According to the division result of the working area, the interference level corresponding to each working area is determined, and the cost input corresponding to each working area is obtained. At the same time, according to the cost input, the inspection path is determined. The calculation formula of the cost input is specifically: Where: V(i, j) is the cost input from the starting point to the i-th row and j-th column in the grid, C(i, j) is the cost of reaching the i-th row and j-th column in the grid from the previous step, V(i-1, j) is the cost input from the starting point to the i-1-th row and j-th column in the grid, V(i, j-1) is the cost input from the starting point to the i-th row and j-1-th column in the grid, min(V(i-1, j), V(i, j-1)) is the minimum cost from the upper position and the left position to the current position, d is a fixed distance cost, η is the weight of the electromagnetic field strength, and R(i, j) is the electromagnetic field strength level at the i-th row and j-th column in the grid; Double-arm collaborative operation: According to the inspection path, the robot reaches the target position and performs the operation of installing / removing the drainage line of the busbar at the target position.

2. A method for coordinating the operation of a robot with two arms for clamping an electric busbar in a transformer substation according to claim 1, characterized in that: Obtain electromagnetic environment change parameters and early warning signals, including: Building an environmental monitoring system: Setting up sensor nodes inside the substation and acquiring sensor data; Determine the electromagnetic dynamic threshold: obtain the electromagnetic field strength prediction value through the sensor data, and determine the electromagnetic dynamic threshold corresponding to each moment according to the electromagnetic field strength prediction value and the smoothing results of different time windows; Generate an early warning signal: compare the electromagnetic field strength data acquired in real time with the electromagnetic dynamic threshold, and when the electromagnetic field strength data is different from the electromagnetic dynamic threshold, determine the range of the electromagnetic field strength data exceeding the electromagnetic dynamic threshold, specifically: When the electromagnetic field strength data exceeds the electromagnetic dynamic threshold by 10%, a slight interference warning signal is generated; When the electromagnetic field strength data exceeds 30% of the electromagnetic dynamic threshold, a warning signal of medium interference is generated; When the electromagnetic field strength data exceeds 50% of the electromagnetic dynamic threshold, a serious interference warning signal is generated; Obtaining electromagnetic environment change parameters: Obtaining the change in electromagnetic field strength data between two adjacent moments through the sensor data, and determining the change rate of the electromagnetic field strength data within the monitoring time according to the monitoring time.

3. A method for coordinating the operation of a robot with two arms for clamping an electric busbar in a transformer substation according to claim 2, characterized in that: Determining the electromagnetic dynamic threshold corresponding to each moment includes: M1: according to the electromagnetic field strength data in the sensor data, obtaining an average value of the electromagnetic field strength data, wherein the average value of the electromagnetic field strength data is the initial dynamic threshold value; M2: Setting a machine learning model, and using the electromagnetic field strength data as input of the machine learning model, and outputting a predicted value of the electromagnetic field strength data; M3: According to the initial dynamic threshold and the predicted value of the electromagnetic field intensity data, the short-time smoothing result and the long-time smoothing result corresponding to each moment are obtained, and the short-time smoothing result and the long-time smoothing result are merged to obtain the dynamic threshold corresponding to each moment, specifically: Where: Y t is the dynamic threshold corresponding to the tth moment, ω1 is the weight corresponding to the short-time smoothing result, is the short-time smoothing result corresponding to the tth moment, ω2 is the weight corresponding to the long-time smoothing result, is the long-term smoothing result corresponding to the tth moment.

4. A method for coordinating the operation of a robot with two arms for clamping an electric busbar in a transformer substation according to claim 3, characterized in that: The smoothing results corresponding to each moment are as follows: Where: y t is the smoothing result corresponding to the tth moment, α is the smoothing factor, is the predicted value of the electromagnetic field intensity corresponding to the tth moment, y t-1 is the smoothing result corresponding to the t-1th moment.

5. A method for coordinating the operation of a robot with two arms applicable to a busbar clamp in a transformer substation according to claim 3 or 4, characterized in that: The smoothing factors corresponding to the smoothing results at different times satisfy the following relationship, specifically: The size of the smoothing factor corresponding to the short-time smoothing result is greater than the size of the smoothing factor corresponding to the long-time smoothing result.

6. The method for coordinating the operation of a robot with two arms for clamping live busbars in a transformer substation according to claim 1 is characterized in that: Adjust the control parameters of the robot and the sensitivity of the sensors, including: Adjust the robot's inspection speed and frequency: according to the level of the warning signal, increase the robot's inspection speed and frequency, specifically: When the level of the warning signal is slight interference, the inspection speed and frequency of the robot remain unchanged; When the level of the warning signal is medium interference, the inspection speed of the robot is reduced by 30% and the inspection frequency is increased by 10%; When the level of the warning signal is severe interference, the inspection speed of the robot is reduced by 50% and the inspection frequency is increased by 20%; Adjust the sensitivity of the sensor: according to the level of the warning signal, increase the sensitivity of the sensor, specifically: When the level of the warning signal is slight interference, the sensitivity of the sensor remains unchanged; When the level of the warning signal is medium interference, the sensitivity of the sensor increases by 10%; When the level of the early warning signal is severe interference, the sensitivity of the sensor increases by 20%.

7. The method for coordinating the operation of a robot with two arms for clamping an electric busbar in a transformer substation according to claim 1 is characterized in that: According to the cost investment, the inspection path is determined, including: N1: Divide the inspection area in the substation into grids, and determine the coordinate position corresponding to each inspection area, and determine the interference level corresponding to each inspection area according to the division result of the working area; N2: Obtaining the cost investment corresponding to each coordinate position according to the coordinate position and the interference level; N3: According to the target position of the robot, the cost inputs of all previous positions corresponding to the target position are obtained, and the minimum cost input is determined from the cost inputs of all previous positions. The position corresponding to the minimum cost input is the inspection position on the inspection path. Repeat step N3 until the position corresponding to the minimum cost input is determined to be the starting position of the robot.

8. The method for coordinating the operation of a robot with two arms for clamping live busbars in a transformer substation according to claim 1 is characterized in that: The electromagnetic field intensity thresholds are set to 100 μT, 200 μT and 300 μT.

9. The method for coordinating the operation of a robot with two arms applicable to a busbar clamp in a transformer substation according to claim 1, characterized in that: The operation of installing / removing the drainage line of the pipe busbar at the target position includes: Environmental modeling: The position of the busbar in the substation is modeled in three dimensions by using a laser radar, and the parking position and the lifting height position of the lifting vehicle are determined based on the three-dimensional modeling; Laying / leading line operation: The robot is transported to the position of the pipe busbar through the parking position and the rising height position of the lifting work vehicle, and the main arm of the robot is hung with a pulley and equipotential operation is performed. The slave arm of the robot is visually assisted, and the operating status of the main arm and the slave arm of the robot is determined according to the classification of the laying / leading operation, specifically: When performing rigging operations: The slave arm fixes the drainage plate, the master arm grinds the drainage plate, and at the same time the master arm grabs the bolt tool, the slave arm grabs the nut tool, and pierces and tightens the bolt tool and the nut tool; When dismantling operations are being performed: The main arm takes the bolt tool, and the slave arm takes the nut tool, and removes the bolt tool and the nut tool.

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