A frame type robot positioning method for power docking

Abstract

The application discloses a frame type mechanical hand positioning method for power docking, and comprises the following steps: S1, starting an electrical test robot, a PLC controller drives a mechanical hand platform to move along a y axis of a frame structure, so that the mechanical hand is at the same height as a circuit breaker baffle; S2, an industrial camera is started and whether the mechanical hand is aligned with the circuit breaker baffle is detected, if not, the PLC controller controls the mechanical hand platform to move along an x axis and the y axis of the frame structure until the mechanical hand is aligned with the circuit breaker baffle; S3, the PLC controller controls the mechanical hand platform to move along a z axis of the frame structure to a specified position; S4, the PLC controller controls a switch mechanical hand to push away an earth knife baffle and push away the earth knife; and S5, the PLC controller controls a circuit breaker crank mechanical hand to push away the circuit breaker baffle and shake out the circuit breaker. The application not only realizes intelligent operation of power docking, but also has high control precision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electrical machinery technology, and particularly relates to a frame type manipulator positioning method for power docking. BACKGROUND

[0002] At present, in the electrical test of power distribution switch cabinet, manual operation is directly performed, however, manual operation is inaccurate, not timely and has many safety hazards. Meanwhile, the data of switch cabinet is complex, and manual operation is difficult to directly position and operate.

[0003] In the prior art, in the process of electrical test, the establishment of manipulator operation coordinate system adopts the method of existing industrial manipulator. However, these manipulators still need manual operation, which is difficult and cannot meet the requirements of intelligent operation. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a frame type manipulator positioning method for power docking, which can realize intelligent operation of power docking.

[0005] To solve the above technical problems, the technical scheme adopted by the present application is as follows.

[0006] A frame type manipulator positioning method for power docking comprises an electrical test robot; the electrical test robot comprises a three-axis positioning frame type manipulator for simulating manual action to directly operate the power distribution switch cabinet in the electrical test of power distribution switch cabinet, the frame type manipulator comprises a frame structure, a manipulator platform capable of moving along the x-axis, y-axis and z-axis of the frame structure is arranged on the frame structure, an operation table is arranged on the manipulator platform, and a manipulator is arranged on the operation table; the manipulator comprises a ground knife switch manipulator and a circuit breaker handle manipulator, wherein the electrical test robot further comprises an industrial camera arranged on the operation table and a PLC controller connected with the output end of the industrial camera and the controlled end of the frame type manipulator; the method comprises the following steps:

[0007] S1. Start the electrical test robot, and the PLC controller drives the manipulator platform to move along the y-axis of the frame structure, so that the manipulator is at the same height as the circuit breaker baffle;

[0008] S2. The industrial camera is turned on and detects whether the manipulator is aligned with the circuit breaker baffle, if not, the PLC controller controls the manipulator platform to move along the x-axis and y-axis of the frame structure until the manipulator is aligned with the circuit breaker baffle;

[0009] S3. The PLC controller controls the manipulator platform to move along the z-axis of the frame structure to a specified position;

[0010] S4. The PLC controller controls the switch manipulator to open the ground knife baffle and open the ground knife.

[0011] The S5 PLC controller controls the circuit breaker cranking robot to open the circuit breaker baffle and crank out the circuit breaker.

[0012] Preferably, in step S1, the PLC controller drives the robot platform to move by a first limit switch set on the y-axis of the frame structure to achieve control of the robot and the circuit breaker baffle at the same height.

[0013] Preferably, step S2 includes the following steps:

[0014] S21. Mathematical modeling of the power distribution switchgear is performed, and images are acquired using an industrial camera for measurement.

[0015] S22. PLC controller performs preliminary positioning analysis based on OpenCV;

[0016] The S23.PLC controller uses an unscented Kalman filter algorithm to achieve positioning and control the robot platform to move along the x and y axes of the frame structure.

[0017] Preferably, step S21 includes the following steps:

[0018] S211. The method for measuring the position of the robotic arm is as follows:

[0019] The position of the robot arm is determined by manual assisted experimental measurement and the affixing of markers. The position of the robot arm is determined by acquiring images using an industrial camera. When the center point of the image pixel coincides with the center of the marker after the position is determined, the robot arm and the center of the circuit breaker baffle coincide in the x-axis and y-axis directions.

[0020] S212. Establish a spatial state model, the method is as follows:

[0021] definition α 1. β 1 represents the center of the marker and the center of the circuit breaker baffle, respectively. y The actual distance along the axis versus the pixel distance;

[0022] definition α 2. β 2 represents the center of the marker and the center of the circuit breaker baffle, respectively. x The actual distance along the axis versus the pixel distance;

[0023] definition α 3. β 3 represents the center point of the marker and the center point of the image pixels, respectively. y The actual distance along the axis versus the pixel distance;

[0024] definition α 4. β4 respectively represent the actual distance and the pixel distance of the marker and the image pixel center point in the x axial direction;

[0025] Definition α 5, β 5 respectively represent the actual distance and the equivalent pixel distance of the industrial camera in the z axial direction and the vertical direction of the power distribution switchgear;

[0026] Definition θ is the horizontal field of view angle of the industrial camera;

[0027] wherein, α 1 and α 2 are known by measurement;

[0028] The actual distance corresponding to one pixel is:

[0029] Formula (2-1)

[0030] In formula (2-1), is the image width pixel value;

[0031] The pixel distance β 1, β 2, β 3, β 4 is taken as the measurement:

[0032] Formula (2-2)

[0033] The actual distance α 3, α 4, α 5 is taken as the state:

[0034] Formula (2-3)

[0035] The model observation equation is:

[0036] Formula (2-4)

[0037] wherein, is the measurement noise; M is a constant vector, and

[0038] Formula (2-5)

[0039] The state transition equation of the model is:

[0040] Formula (2-6)

[0041] In formula (2-6),U k is a control item; is k +1 time and k The mechanical arm platform controls the motion vector of the industrial camera between the sampling times; is k The process noise of the +1 time state transition is k

[0042] S213. Analytically solve the robot position, the method is:

[0043] According to formula (2-4), the distance between the robot and the circuit breaker cabin door plane z The axis distance is:

[0044] Formula (2-7)

[0045] According to the analytical method, the distance between the robot and the circuit breaker baffle (7) x The axis distance is: y

[0046] Formula (2-8).

[0047] Preferably, the step S22 comprises the following steps:

[0048] S221. Read the image;

[0049] S222. By using the mean shift algorithm characteristics in the pyrMeanShiftFiltering function in Opencv, realize the smoothing filtering in the image color layer, neutralize the color distribution similar color, smooth the color details, erode the small color area, to eliminate the noise of the image;

[0050] S223. By using the cvtColor function in Opencv, realize the color space conversion from the color image to the gray image after eliminating the noise, and still retain the feature information in the image;

[0051] S224. By using the threshold function in Opencv, carry out the threshold processing on the gray image;

[0052] S225. By using the Canny function in Opencv, carry out the edge detection on the image after threshold processing;

[0053] ​​S226. Detect the circle in the image after edge detection by HoughCircles function in Opencv, the method is: first, execute Sobel operator on the original image, calculate the gradient value of all pixels in the neighborhood, initialize the spatial coordinates of the center of the circle; then traverse all non-zero pixel points in the Canny edge binary image, draw a line along the gradient direction, and accumulate the count of the line segment passing through the initialized center of the circle, the more the number is, the greater the possibility of the point being the center of the circle is; according to the setting of the threshold, calculate the center position and the possible radius; judge whether the number of circles is 2, if not equal to 2, continue to detect the circle; if equal to 2, it means that the image is collected and recognized correctly, and the circle and the center of the circle are drawn on the original image;

[0054] S227. Output the image size;

[0055] S228. Output the distance that the manipulator needs to move in the x 、 y axis;

[0056] S229. Read the focal length attribute of the image;

[0057] S2210. Calculate the field of view angle θ ;

[0058] S2211. Output the distance that the manipulator needs to move in the z axis.

[0059] Preferably, the step S23 comprises the following steps:

[0060] S231. The PLC controller calculates the position of the manipulator by using the unscented Kalman filter algorithm;

[0061] S232. The PLC controller judges whether the error in the x-axis direction meets the error requirement according to the calculated position of the manipulator, if not, the PLC controller sends the x-axis movement instruction according to the calculated relative position, if yes, enter S233;

[0062] S233. The PLC controller judges whether the error in the y-axis direction meets the error requirement according to the calculated position of the manipulator, if not, the PLC controller sends the y-axis movement instruction according to the calculated relative position, if yes, enter S234;

[0063] S234. The PLC controller re-judges whether the errors in the x-axis and y-axis directions meet the error requirement, if both meet, stop moving, otherwise, repeat S232 and S233 until the requirement is met.

[0064] Preferably, the step S231 comprises the following steps:

[0065] S2311. State prediction is performed on the manipulator using a nonlinear Gaussian system, and a state variable is calculated;

[0066] S2312. Measurement update is performed using the predicted state variable and a measurement variable, and a new state variable is calculated.

[0067] Preferably, the nonlinear Gaussian system is:

[0068] Equation (2-9)

[0069] In Equation (2-9): and are an n-dimensional state variable and an m-dimensional measurement variable at time k, respectively;

[0070] and are system process noise and measurement noise, respectively;

[0071] is a nonlinear state transition function;

[0072] is a nonlinear measurement function;

[0073] The method of step S2311 is:

[0074] Suppose that the state variable at time k-1 is subject to a distribution: According to a symmetric sampling strategy, 2n+1 sigma points are selected:

[0075] Equation (2-10)

[0076] The weight corresponding to is:

[0077] Equation (2-11)

[0078] In Equation (2-11): ; K is a scale parameter, when is a univariate, λ is equal to 0; when is a multivariate, λ is equal to 3-n; wherein, is a scaling factor, used to control the position of the sigma point set, is greater than 0 and less than 1;

[0079] is a Cholesky decomposition of the matrix; represents the i-th column of the matrix in the parentheses;

[0080] After the sigma point set is passed through the nonlinear state transition function, the predicted propagated state quantity mean value and error covariance are calculated:

[0081] Equation (2-12).

[0082] Preferably, the method of step S2312 is:

[0083] Using the predicted state quantity mean value and covariance, the sigma points are calculated according to the symmetric sampling strategy After being propagated through the nonlinear measurement function, the measurement quantity mean value, self-covariance matrix and mutual covariance matrix are calculated:

[0084] Equation (2-13)

[0085] The new measurement value is obtained After that, the filtering update is performed:

[0086] Equation (2-14)

[0087] In equation (2-14), K k is the filtering gain, is the predicted coordinate, P k is the estimated covariance.

[0088] Preferably, in step S3, the PLC controller drives the manipulator platform to move along the z-axis of the frame structure to a specified position by the second limit switch arranged on the z-axis of the frame structure.

[0089] Thanks to the above technical solutions, the present application has the following technical progress.

[0090] The present application can simulate artificial action to directly operate the power distribution switch cabinet, simultaneously uses the industrial camera to collect images for measurement, uses the unscented Kalman filtering algorithm to complete positioning, uses the PLC controller to control the servo motor to move in the xyz multi-plane, realizes the specific positioning of the frame type manipulator, completes the opening of the ground knife and the shaking out of the circuit breaker handle, not only realizes the intelligent operation of the power connection, but also has high control precision. BRIEF DESCRIPTION OF DRAWINGS

[0091] Figure 1 is the flow chart of the present application;

[0092] Figure 2 is the schematic diagram of the frame type manipulator structure of the present application;

[0093] Figure 3 is the schematic diagram of the relative position of the circuit breaker cabin door of the present application;

[0094] Figure 4 Geometric model of the industrial camera and the circuit breaker cabin door of the application;

[0095] Figure 5 Flow chart of the preliminary positioning analysis method based on OpenCV for the PLC controller of the application;

[0096] Figure 6 Flow chart of the manipulator control method based on UKF for the PLC controller of the application.

[0097] Wherein: 1. frame structure, 2. manipulator platform, 3. operation table, 4. ground knife switch manipulator, 5. circuit breaker handle manipulator, 6. marker, 7. image pixel center point, 8. circuit breaker baffle. DETAILED DESCRIPTION

[0098] The application will be further described in detail below in combination with the drawings and specific embodiments.

[0099] A frame manipulator positioning method for power docking, based on an electrical test robot, the electrical test robot comprising a three-axis positioning frame manipulator, an industrial camera and a PLC controller, wherein the input end of the PLC controller is connected with the output end of the industrial camera, and the output end of the PLC controller is connected with the controlled end of the frame manipulator. The positioning method of the application completes positioning by mathematical modeling of the power distribution switchgear, image acquisition and determination by the industrial camera, and positioning by the unscented Kalman filtering algorithm, controls the controlled end of the frame manipulator by the PLC controller, moves in the xyz planes, realizes specific positioning, and thus completes the frame manipulator in the electrical test of the power distribution switchgear to simulate manual operation to directly operate the power distribution switchgear.

[0100] As shown in Figure 2 The frame manipulator comprises a frame structure 1, a manipulator platform 2 is arranged on the frame structure 1, the manipulator platform 2 is connected with the frame structure 1 through a transmission mechanism and a servo motor, the manipulator platform 2 is controlled by the servo motor to walk along the x-axis, y-axis and z-axis of the frame structure 1 (the specific means is the prior art, which is not described here), the controlled end of the servo motor is connected with the output end of the PLC controller; an operation table 3 is arranged on the manipulator platform 2, a manipulator is arranged on the operation table 3, the manipulator moves with the movement of the manipulator platform 2, the manipulator comprises a ground knife switch manipulator 4 and a circuit breaker handle manipulator 5, the controlled end of the ground knife switch manipulator 4 and the circuit breaker handle manipulator 5 is connected with the output end of the PLC controller, wherein the ground knife switch manipulator 4 is used to open the ground knife; the circuit breaker handle manipulator 5 is used to shake out the circuit breaker handle of the circuit breaker.

[0101] The industrial camera is fixedly arranged on the operation table 3.

[0102] As shown in Figure 3 , a circuit breaker baffle 8 is arranged on the power distribution switch cabinet and is parallel to the plane of the circuit breaker cabin door.

[0103] As shown in Figure 1 , the positioning method of the application comprises the following steps:

[0104] S1. Start the electrical test robot, and the PLC controller drives the manipulator platform 2 to move along the y-axis of the frame structure 1, so that the manipulator is at the same height as the circuit breaker baffle 8.

[0105] The specific implementation method is that a first limit switch is arranged on the y-axis of the frame structure 1, and the PLC controller controls the movement of the manipulator platform 2 along the y-axis of the frame structure 1 through the first limit switch, so as to control the manipulator to be at the same height as the circuit breaker baffle 8.

[0106] S2. The industrial camera is turned on and detects whether the manipulator is aligned with the circuit breaker baffle 8. If not, the PLC controller controls the manipulator platform 2 to move along the x-axis and y-axis of the frame structure 1 until the manipulator is aligned with the circuit breaker baffle 8. Specifically, the following steps are included:

[0107] S21. The power distribution switch cabinet is mathematically modeled, and the image collected by the industrial camera is used for measurement. Specifically, the following steps are included:

[0108] S211. The position of the manipulator is measured by the following method:

[0109] As shown in Figure 3 , the position of the manipulator is measured by manually assisted test and the position is calibrated by pasting a marker 6, and the image collected by the industrial camera is used for measurement of the position of the manipulator; the relative position between the industrial camera and the manipulator is fixed, and when the image pixel center point 7 and the center of the marker 6 coincide after position calibration, the center of the manipulator and the circuit breaker baffle 8 coincide in the x-axis and y-axis directions.

[0110] S212. The space state model is established by the following method:

[0111] As shown in Figure 4 , the space state model is established according to the actual position of the power distribution switch cabinet and the industrial camera and the real position measurement of the manipulator.

[0112] Definition α 1, β 1 represents the actual distance and pixel distance in the x-axis direction between the marker 6 and the center of the circuit breaker baffle 8. y

[0113] Definition α 2, β ​2 represents the actual distance between the marker 6 and the center of the circuit breaker shutter 8 in the x actual distance and pixel distance in the

[0114] Definition α 3, β 3 represents the actual distance between the marker 6 and the center of the image pixel 7 in the y actual distance and pixel distance in the

[0115] Definition α 4, β 4 represents the actual distance between the marker 6 and the center of the image pixel 7 in the x actual distance and pixel distance in the

[0116] Definition α 5, β 5 represents the actual distance between the industrial camera and the vertical of the power distribution switchgear in the z actual distance and pixel distance in the

[0117] Definition θ is the horizontal field of view angle of the industrial camera.

[0118] wherein, α 1 and α 2 are obtained by measurement.

[0119] The actual distance corresponding to one pixel is:

[0120] Formula (2-1)

[0121] In formula (2-1), is the image width pixel value.

[0122] The pixel distance β 1, β 2, β 3, β 4 as a measure, that is, the image distance:

[0123] Formula (2-2)

[0124] It should be noted that, y k is not y the axis distance, but a symbol, the image distance from the x-axis, y-axis and z-axis in the model, which is obtained by formula (2-2).

[0125] The actual distance α 3, α 4, α 5 as a state variable:

[0126] Equation (2-3)

[0127] It should be noted that, is the image distance y k The corresponding actual distance, not the x-axis distance, the actual distance from the x-axis, y-axis and z-axis in the model, are obtained by equation (2-3).

[0128] The model observation equation is:

[0129] Equation (2-4)

[0130] Where, is the measurement noise; M is a constant vector, and Equation (2-5)

[0131] The state transition equation of the model is:

[0132] Equation (2-6)

[0133] In equation (2-6), U k is the control term; is k +1 order and k the sampling interval mechanical hand platform 2 control industrial camera motion vector; is k the process noise of k +1 order state transition.

[0134] S213. Analytical method for solving the position of the manipulator, the method is:

[0135] According to equation (2-4), the distance between the manipulator and the circuit breaker cabin door plane z axis distance is:

[0136] Equation (2-7)

[0137] Further, according to the analytical method, the distance between the manipulator and the circuit breaker baffle 8 x axis and y axis distance is:

[0138] Equation (2-8)

[0139] S22. The PLC controller based on OpenCV performs preliminary positioning analysis, so as to realize preliminary positioning analysis before the manipulator starts moving, as shown in Figure 5 , including the following steps:

[0140] S221. Read the image.

[0141] S222. Smooth filtering in the color layer of the image is realized by using the mean shift algorithm feature in the pyrMeanShiftFiltering function in Opencv, neutralizing colors with similar color distribution, smoothing color details, and eroding small color areas to eliminate image noise.

[0142] S223. Color space conversion from the color image to the grayscale image is realized by using the cvtColor function in Opencv, which eliminates noise and still retains the feature information in the image, reducing the difficulty of image processing.

[0143] S224. Threshold processing is performed on the grayscale image by using the threshold function in Opencv to prepare for the subsequent edge detection.

[0144] S225. Edge detection is performed on the image after threshold processing by using the Canny function in Opencv.

[0145] S226. Circle detection is performed on the image after edge detection by using the HoughCircles function in Opencv, and the specific method is as follows:

[0146] First, a Sobel operator is performed on the original image to calculate the gradient value of all pixels in the neighborhood, and the spatial coordinates of the center of the circle are initialized. Then, all non-zero pixel points in the Canny edge binary image are traversed, and lines are drawn along the gradient direction. The number of line segments passing through the initialized center of the circle is counted, and the greater the number, the greater the possibility of the point being the center of the circle. According to the threshold setting, the center position and possible radius of the circle are calculated. It is judged whether the number of circles is equal to 2. If not, the circle detection continues. If it is equal to 2, it means that the image is correctly collected and recognized, and the circle and center are drawn on the original image.

[0147] S227. Output the image size.

[0148] S228. Output the distance that the manipulator needs to move in the x-axis and y-axis;

[0149] S229. Read the image focal length attribute.

[0150] S2210. Calculate the field of view angle θ ;

[0151] S2211. Output the distance that the manipulator needs to move in the z-axis.

[0152] S23. The PLC controller completes positioning by using the unscented Kalman filter algorithm, and controls the manipulator platform 2 to move along the x-axis and y-axis of the frame structure 1.

[0153] This is the process of the robot platform 2 driven robot starts moving, only to identify the robot, used to improve the accuracy. The principle is simply that, constantly measuring, through the last frame of the state prediction of the next frame of the state. Using the noise ω and observation noise υ in the state process, give reasonable weight, to the state x k Estimation.

[0154] As Figure 6 shown, specifically includes the following steps:

[0155] S231.PLC controller uses the UKF algorithm to calculate the position of the robot. Specifically includes the following steps:

[0156] S2311. According to the motion characteristics of the robot, the state of the robot is predicted by applying a nonlinear Gaussian system, and the state quantity is calculated.

[0157] The nonlinear Gaussian system is:

[0158] Formula (2-9)

[0159] In formula (2-9): and are the n-dimensional state quantity and the m-dimensional measurement at time k, respectively;

[0160] and are the system process noise and measurement noise, respectively;

[0161] is the nonlinear state transition function;

[0162] is the nonlinear measurement function.

[0163] The method of step S2111 is:

[0164] Assume that the state quantity at time k-1 obeys the distribution: , according to the symmetric sampling strategy, select 2n+1 sigma points:

[0165] Formula (2-10)

[0166] The weight corresponding to is:

[0167] Formula (2-11)

[0168] In formula (2-11): ; K is a proportional parameter, when For single variable, λ equals 0; when For multi-variable, λ equals 3-n; wherein, is a scaling factor for controlling the position of the sigma point set, greater than 0 and less than 1, usually taking a very small positive number;

[0169] is the Cholesky decomposition of the matrix; represents the i-th column of the matrix in the parentheses;

[0170] After the sigma point set is transmitted through the nonlinear state transition function, the predicted propagated state quantity mean value and error covariance are calculated:

[0171] Formula (2-12)

[0172] The first formula in formula (2-12) is a process quantity, which is a predicted state parameter; the second formula is a predicted state quantity mean value; and the third formula is an error covariance, which is used to judge the error.

[0173] S2312. The predicted state quantity and the measurement are used for measurement update, and a new state quantity is calculated.

[0174] According to the above principle, the predicted state quantity mean value and the covariance are used to calculate the sigma point according to the symmetric sampling strategy After being propagated through the nonlinear measurement function, the measurement mean value, self-covariance matrix and cross-covariance matrix are calculated:

[0175] Formula (2-13)

[0176] The new measurement value is obtained After that, the filtering update is performed:

[0177] Formula (2-14)

[0178] In formula (2-14), K k is the filtering gain, is the predicted coordinate, P k is the estimated covariance. In this method, it is necessary to express by coordinates, but all are directly processed by matrix, so in the Kalman filtering method, the specific movement mode of x-axis, y-axis and z-axis does not need to be separately explained.

[0179] S232. The PLC controller determines whether the error in the x-axis direction meets the error requirement according to the calculated position of the manipulator, and if not, the PLC controller sends the x-axis movement instruction according to the calculated relative position, and if so, it goes to S233;

[0180] S233. The PLC controller determines whether the error in the y-axis direction meets the error requirement according to the calculated position of the manipulator, and if not, the PLC controller sends the y-axis movement instruction according to the calculated relative position, and if so, it goes to S234;

[0181] S234. The PLC controller re-determines whether the errors in the x-axis and y-axis directions meet the error requirements, and if both meet, it stops moving, otherwise it repeats S232 and S233 until the requirements are met.

[0182] S3. The PLC controller controls the manipulator platform 2 to move along the z-axis of the frame structure 1 to a specified position.

[0183] The PLC controller outputs the distance that the manipulator needs to move in the z-axis and outputs frame by frame according to S2211, and finally controls the movement of the manipulator platform 2 along the z-axis of the frame structure 1 through the second limit switch set on the z-axis of the frame structure 1, so as to realize the movement of the manipulator platform 2 along the z-axis of the frame structure 1 to a specified position, i.e. the movement of the manipulator along the z-axis of the frame structure 1 to a specified position.

[0184] S4. The PLC controller controls the ground knife switch manipulator 4 to move away the ground knife baffle and move away the ground knife.

[0185] S5. The PLC controller controls the circuit breaker handle manipulator 5 to move away the circuit breaker baffle 8 and shake out the circuit breaker.

[0186] In use, the present application can simulate manual operation to directly operate the power distribution switch cabinet, and at the same time, images are collected by an industrial camera for measurement, positioning is completed by using a Kalman filter algorithm, a servo motor is controlled by a PLC controller, xyz multi-plane movement is performed, specific positioning of the frame-type manipulator is realized, the ground knife is moved away and the circuit breaker handle is shaken out, not only realizing intelligent operation of power connection, but also having high control precision.

Claims

1. A frame-type manipulator positioning method for power connection, based on an electrical testing robot; the electrical testing robot includes a three-axis positioning frame-type manipulator for simulating manual actions to directly operate the power distribution switchgear in electrical testing of the switchgear, the frame-type manipulator includes a frame structure (1), a manipulator platform (2) is provided on the frame structure (1) and can move along the x-axis, y-axis and z-axis of the frame structure (1), an operating table (3) is provided on the manipulator platform (2), and a manipulator is provided on the operating table (3); the manipulator includes a grounding switch manipulator (4) and a circuit breaker crank manipulator (5), characterized in that: The electrical testing robot also includes an industrial camera mounted on the operating table (3) and a PLC controller connected to the output end of the industrial camera and the controlled end of the frame-type manipulator, respectively; the method includes the following steps: S1. Start the electrical test robot. The PLC controller drives the robot platform (2) to move along the y-axis of the frame structure (1) so that the robot is at the same height as the circuit breaker baffle (8). S2. The industrial camera is turned on and detects whether the robot arm is aligned with the circuit breaker baffle (8). If it is not aligned, the PLC controller controls the robot arm platform (2) to move along the x and y axes of the frame structure (1) until the robot arm is aligned with the circuit breaker baffle (8). Step S2 includes the following steps: S21. Mathematical modeling of the power distribution switchgear is performed, and images are acquired using an industrial camera for measurement. S22. PLC controller performs preliminary positioning analysis based on OpenCV; The S23.PLC controller uses the unscented Kalman filter algorithm to complete the positioning and control the robot platform (2) to move along the x and y axes of the frame structure (1); Step S23 includes the following steps: The S231.PLC controller uses an unscented Kalman filter algorithm to calculate the position of the robot arm. Step S231 includes the following steps: S2311. Apply a nonlinear Gaussian system to predict the state of the robot and calculate the state variables; The nonlinear Gaussian system is: Formula (2-9) In formula (2-9): and These are measurements of the n-dimensional state variables and m-dimensional variables at time k, respectively. and These are system process noise and measurement noise, respectively. It is a nonlinear state transition function; It is a nonlinear measurement function; The method for step S2311 is as follows: Assume the state variables at time k-1 follow a distribution: 2n+1 sigma points are selected according to the symmetric sampling strategy: Formula (2-10) Corresponding to The weights are: Formula (2-11) In formula (2-11): ; K For proportional parameters, ,when For a single variable, λ equals 0; when For multiple variables, λ equals 3-n; where, This is a scaling factor used to control the position of the sigma point set. Greater than 0 and less than 1; For the Cholesky decomposition of the matrix; This represents the i-th column of the matrix within the brackets; After passing the sigma point set through a nonlinear state transition function, predict the mean and error covariance of the propagated state variables: Formula (2-12); S2312. Use the predicted state variables and the measured quantities to perform measurement updates and calculate the new state variables; S232. The PLC controller determines whether the x-axis direction error meets the error requirements based on the calculated position of the robot. If it does not meet the requirements, the PLC controller sends an x-axis motion command based on the calculated relative position. If it meets the requirements, it enters S233. S233. The PLC controller determines whether the y-axis direction error meets the error requirements based on the calculated position of the robot. If it does not meet the requirements, the PLC controller sends a y-axis motion command based on the calculated relative position. If it meets the requirements, it proceeds to S234. S234. The PLC controller re-evaluates whether the x-axis and y-axis direction errors meet the error requirements. If both are met, the movement stops; otherwise, S232 and S233 are repeated until the requirements are met. S3. The PLC controller controls the robotic arm platform (2) to move along the z-axis of the frame structure (1) to the specified position; S4. The PLC controller controls the ground knife switch robot (4) to open the ground knife baffle and open the ground knife; The S5.PLC controller controls the circuit breaker cranking robot (5) to open the circuit breaker baffle and crank out the circuit breaker.

2. The frame-type robotic arm positioning method for power docking according to claim 1, characterized in that: In step S1, the PLC controller drives the robot platform (2) to move by setting the first limit switch on the y-axis of the frame structure (1) so as to achieve the control of the robot and the circuit breaker baffle (8) at the same height.

3. The frame-type robotic arm positioning method for power docking according to claim 1, characterized in that: Step S21 includes the following steps: S211. The method for measuring the position of the robotic arm is as follows: The position of the robot arm is determined by manual assisted test measurement and the pasting of markers (6). The position of the robot arm is determined by using an industrial camera to collect images. When the center point (7) of the image pixel coincides with the center of the marker (6) after the position is determined, the robot arm and the center of the circuit breaker baffle (8) coincide in the x-axis and y-axis directions. S212. Establish a spatial state model, the method is as follows: definition α 1. β 1 represents the center of the marker (6) and the circuit breaker baffle (8) respectively. y The actual distance along the axis versus the pixel distance; definition α 2. β 2 represents the center of the marker (6) and the circuit breaker baffle (8), respectively. x The actual distance along the axis versus the pixel distance; definition α 3. β 3 represents the position of the marker (6) and the center point (7) of the image pixel, respectively. y The actual distance along the axis versus the pixel distance; definition α 4. β 4 represents the position of the marker (6) and the center point (7) of the image pixel, respectively. x The actual distance along the axis versus the pixel distance; definition α 5. β 5 represents the industrial camera in z The actual distance perpendicular to the power distribution switch cabinet along the axial direction and the equivalent pixel distance; definition θ This refers to the horizontal field of view of an industrial camera. in, α 1 and α 2. This information was obtained through measurement; The actual distance corresponding to a unit pixel is: Formula (2-1) In formula (2-1), This represents the image width in pixels. In pixel distance β 1. β 2. β 3. β 4. As a measurement: Formula (2-2) actual distance α 3. α 4. α 5 as a state variable: Formula (2-3) The model observation equation is: Formula (2-4) in, For measuring noise; M Let the vector be a constant, then: Formula (2-5) The state transition equation of the model is: Formula (2-6) In formula (2-6), U k For control items; Yes k +1 times and k The subsampling room robotic arm platform (2) controls the motion vector of the industrial camera; for k Next k +1 state transition process noise; S213. The analytical method for determining the position of the robot arm is as follows: The distance between the manipulator and the circuit breaker compartment door plane is obtained analytically using formula (2-4). z The axial distance is: Formula (2-7) Then, based on the analytical method, the distance between the robot arm and the circuit breaker baffle (8) is obtained. x shaft and y The axial distances are as follows: Formula (2-8).

4. The frame-type robotic arm positioning method for power docking according to claim 3, characterized in that: Step S22 includes the following steps: S221. Read the image; S222. By utilizing the mean shift algorithm characteristics of the pyrMeanShiftFiltering function in OpenCV, smoothing filtering at the image color level is achieved, neutralizing colors with similar color distributions, smoothing color details, and eroding small color areas to eliminate image noise. S223. The cvtColor function in OpenCV is used to perform a color space transformation from a noise-reduced color image to a grayscale image while still preserving the image's feature information; S224. Use the threshold function in OpenCV to perform thresholding on the grayscale image; S225. Perform edge detection on the thresholded image using the Canny function in OpenCV; S226. Use the HoughCircles function in OpenCV to detect circles in the edge-detected image. The method is as follows: First, perform a Sobel operator on the original image to calculate the neighborhood gradient values ​​of all pixels and initialize the spatial coordinates of the circle center; then, traverse all non-zero pixels in the Canny edge binary image, draw lines along the gradient direction, and accumulate the count of line segments that pass through the initialized circle center. The more segments, the greater the probability that the point is the circle center; calculate the circle center position and possible radius according to the threshold setting; check if the number of circles is 2. If it is not equal to 2, continue to detect circles; if it is equal to 2, it means that the image acquisition and recognition are correct, and draw the circle and its center on the original image. S227. Output image size; S228. Output the distance the robot arm needs to move along the x and y axes; S229. Read the image focal length attribute; S2210. Calculate the field of view. θ ; S2211. Output the distance the robot arm needs to move along the z-axis.

5. A frame-type robotic arm positioning method for power docking according to claim 1, characterized in that: The method for step S2312 is as follows: The sigma point is calculated using the mean and covariance of the predicted state variables, following a symmetric sampling strategy. After propagation through a nonlinear measurement function, the mean, autocovariance matrix, and crosscovariance matrix of the measurements are calculated: Formula (2-13) Obtain new measurement values Then, the filter is updated: Formula (2-14) In formula (2-14), K k It is the filter gain. For the expected coordinates, P k It estimates the covariance.

6. A frame-type robotic arm positioning method for power docking according to claim 5, characterized in that: In step S3, the PLC controller drives the robotic arm platform (2) to move along the z-axis of the frame structure (1) to the designated position by using the second limit switch set on the z-axis of the frame structure (1).

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