An isolation switch monitoring method associated with the surface area of an object

Abstract

The present invention relates to a monitoring method for a disconnecting switch associated with the surface area of an object, comprising: obtaining point cloud data of a target object by using a lidar; analyzing the state of the target object based on the point cloud data to obtain a monitoring result; obtaining the distance between the lidar and the target object; obtaining the surface area of the target object; calculating a distance influence coefficient according to the distance between the lidar and the target object; and calculating the accuracy of the monitoring result according to the distance influence coefficient and the surface area. The present invention calculates the accuracy of the monitoring result by constructing a function to judge the accuracy of the monitoring result, effectively improving the overall stability of the monitoring system and having wide applicability. At the same time, the present invention captures a point cloud image of the disconnecting switch by using a lidar and analyzes and processes the attribute information of the key area of the conductive arm of the disconnecting switch by using an algorithm, discriminates the closing state of the disconnecting switch according to the angle of the conductive arm, has high monitoring result accuracy, helps power personnel to monitor the operation state of the disconnecting switch in real time and determine whether the disconnecting switch is reliably closed, and reduces accidents caused by incomplete closing of the disconnecting switch.

Description

Technical Field

[0001] The present invention relates to a monitoring method for disconnecting switches associated with the surface area of an object, and belongs to the field of disconnecting switch monitoring. Background Art

[0002] The high-voltage disconnecting switch drives the moving contact to achieve contact and separation from the static contact by means of an operating mechanism. When it operates outdoors, it is extremely vulnerable to environmental influences. Transmission jamming, component size changes, misalignment of transmission components, etc. can all cause the disconnecting switch to fail to close in place, resulting in gaps, leading to overheating and even discharging, affecting the equipment life and threatening the safe operation of the power grid. Therefore, it is necessary to monitor the closing state of the disconnecting switch.

[0003] In the prior art, a lidar is used to obtain the point cloud data of the disconnecting switch, and the point cloud data is analyzed and processed to obtain the closing state of the disconnecting switch. For details, reference can be made to the paper "Automatic Monitoring Method for Closing State of Disconnecting Switch Based on Terrestrial LiDAR". Liu Yan, Zou Yang, Tan Shuning, Long Guohua.

[0004] Although the monitoring system based on lidar can realize the visual monitoring of the disconnecting switch and the discrimination of the closing state, the measurement accuracy of the lidar is affected by environmental conditions, and the accuracy of the monitoring system is limited. Therefore, it is necessary to further determine whether the monitoring results of the monitoring system are accurate.

[0005] The patent "A Distributed Monitoring Method, System and Medium for Disconnecting Switch State" with the publication number CN111199219A discloses the following steps: obtaining the disconnecting switch image of the target disconnecting switch; obtaining the included angle α between the two arms of the disconnecting switch through image analysis; comparing the included angle α with the calibrated values of the closing and opening state included angles respectively to determine the state of the target disconnecting switch. This invention can accurately monitor the closing and opening states of the target disconnecting switch, but the accuracy of the obtained results is unknown. Summary of the Invention

[0006] In order to overcome the problems existing in the prior art, the present invention designs a monitoring method for disconnecting switches associated with the surface area of an object, obtains the distance between the lidar and the disconnecting switch, the surface area of the disconnecting switch, and constructs a function to calculate the monitoring result accuracy, so as to determine the accuracy of the monitoring results, effectively improving the overall stability of the monitoring system and having wide applicability.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] Technical Solution 1

[0009] A monitoring method for disconnecting switches associated with the surface area of an object includes the following steps:

[0010] Using a lidar to obtain the point cloud data of the target object;

[0011] Analyze the state of the target object based on the point cloud data to obtain a monitoring result;

[0012] Obtain the distance between the lidar and the target object;

[0013] Obtain the surface area of the target object;

[0014] Calculate the distance influence coefficient according to the distance between the lidar and the target object;

[0015] Calculate the accuracy of the monitoring result according to the distance influence coefficient and the surface area.

[0016] Furthermore, the target object is an isolating switch.

[0017] Furthermore, the analysis of the state of the target object based on the point cloud data to obtain the monitoring result is specifically as follows:

[0018] Cut the point cloud data in multiple coordinate axis directions to obtain the point cloud of the isolating switch conductive arm;

[0019] Enhance the edge of the point cloud of the isolating switch conductive arm;

[0020] Perform plane fitting on the point cloud of the unilateral conductive arm of the isolating switch to obtain a first fitting plane and a second fitting plane;

[0021] Calculate the included angle between the first fitting plane and the second fitting plane as the monitoring result.

[0022] Furthermore, the calculation of the accuracy of the monitoring result specifically includes:

[0023] Calculate the distance influence coefficient according to the distance between the lidar and the background environment and the distance between the lidar and the target object;

[0024] Calculate the accuracy of the monitoring result according to the distance influence coefficient and the surface area of the target object;

[0025] If the accuracy of the monitoring result is greater than the threshold, it is considered that the monitoring result is accurate.

[0026] Furthermore, the calculation of the accuracy of the monitoring result is expressed by the formula:

[0027]

[0028] In the formula, γ represents the accuracy of the monitoring result; η r represents the transmission efficiency of the lidar receiving optical system; K l represents the distance influence coefficient; S n represents the surface area of the target object; S L represents the area of the lidar vision range; T represents the atmospheric environment transmittance; Represents an adjustment factor.

[0029] Furthermore, the calculation of the distance influence coefficient is expressed by the formula:

[0030]

[0031] In the formula, K l represents the distance influence coefficient; l b represents the distance between the lidar generator and the background environment; l n represents the distance between the laser generator and the target object; c1 represents a constant.

[0032] Furthermore, the monitoring result includes the monitoring value of the included angle of the isolating switch conductive arm;

[0033] Based on the monitoring value of the included angle of the isolating switch conductive arm and the actual value of the included angle of the isolating switch conductive arm, calculate the error factor; according to the error factor, update the accuracy of the monitoring result.

[0034] Furthermore, the update of the monitoring result accuracy according to the error factor is expressed by the formula:

[0035] δ = 0.5(1 - 100σ) + 0.5γ

[0036] In the formula, γ represents the monitoring result accuracy; δ represents the updated monitoring result accuracy; σ represents the error factor.

[0037] Technical solution two

[0038] An isolating switch monitoring system associated with the surface area of an object, comprising:

[0039] A lidar, which is used to obtain the point cloud data of the target object;

[0040] A host computer, which is used to analyze the state of the target object based on the point cloud data to obtain a monitoring result; obtain the distance between the lidar and the target object; obtain the surface area of the target object; calculate the distance influence coefficient according to the distance between the lidar and the target object; calculate the monitoring result accuracy according to the distance influence coefficient and the surface area.

[0041] Compared with the prior art, the present invention has the following characteristics and beneficial effects:

[0042] Considering that the measurement distance and the surface area of the object will affect the accuracy of the point cloud data collected by the lidar, thus affecting the accuracy of the monitoring result. The present invention obtains the distance between the lidar and the isolating switch, the surface area of the isolating switch and constructs a function to calculate the monitoring result accuracy, so as to judge the accuracy of the monitoring result, effectively improving the overall stability of the monitoring system and having wide applicability.

[0043] The present invention captures the point cloud image of the disconnector through a lidar and uses an algorithm to extract the attribute information of the key area of the disconnector's conductive arm for analysis and processing. It discriminates the closing state of the disconnector according to the angle of the conductive arm. The monitoring result has high precision, which helps power personnel to monitor the operating state of the disconnector in real time and determine whether the disconnector is reliably closed, reducing accidents caused by improper closing of the disconnector. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is the flowchart of the present invention;

[0045] Figure 2 is the schematic diagram of the monitoring system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] The present invention will be described in more detail below in conjunction with embodiments.

[0047] Embodiment 1

[0048] As Figure 1 shown, a monitoring system for the characteristics of the disconnector's conductive arm associated with the surface area of an object includes: a lidar and a host computer.

[0049] The emission surface of the lidar is placed vertically upward, provided with an Ethernet interface, and connected to the host computer through a network cable. The lidar captures the three-dimensional image of the disconnector and saves it in the form of point cloud data; then the point cloud data is transmitted to the host computer through the network cable.

[0050] The host computer calculates the distance between the lidar and the target object; obtains the surface area of the target object; calculates the distance influence coefficient according to the distance between the lidar and the target object; and calculates the monitoring result accuracy according to the distance influence coefficient and the surface area.

[0051] Embodiment 2

[0052] A method for monitoring a disconnector associated with the surface area of an object includes the following steps:

[0053] Calculate the distance influence coefficient K of the distance on the monitoring result according to the distance between the target object and the lidar l , which is expressed by the formula:

[0054]

[0055] In the formula, l b is the distance between the laser generator and the background environment, in meters; l n is the distance between the laser generator and the target object, in meters.

[0056] The number of valid point clouds collected by the lidar is related to the surface area of the conductive arm of the isolated switch under monitoring. The more the number of valid point clouds, the higher the accuracy of the monitoring result. Therefore, based on the surface area of the target object and the distance influence coefficient K l , calculate the accuracy of the monitoring result, which is expressed by the formula:

[0057]

[0058] In the formula, η r is the transmission efficiency of the receiving optical system; S n is the surface area of the target object, with the unit of m 2 ; S L is the area of the lidar's field of view, with the unit of m 2 ; T is the atmospheric transmittance; is the adjustment factor, taking 1.385.

[0059] The larger γ is, the better the monitoring performance; conversely, the worse the performance. In this embodiment, if γ is greater than 0.7, it is considered that the accuracy of the monitoring result is high; if γ is less than 0.7, it is considered that the target object or the installation distance needs to be adjusted.

[0060] Example Three

[0061] Furthermore, according to the error factor, update the accuracy of the monitoring result, which is expressed by the formula:

[0062] δ = 0.5(1 - 100σ) + 0.5γ

[0063] In the formula, γ represents the accuracy of the monitoring result; δ represents the updated accuracy of the monitoring result; σ represents the error factor.

[0064] Among them, the calculation formula of the error factor σ is as follows:

[0065]

[0066] In the formula, θ1 represents the monitored value of the included angle of the conductive arm of the isolated switch; θ2 represents the actual value of the included angle of the conductive arm of the isolated switch.

[0067] Using the updated accuracy of the monitoring result δ, quantitatively characterize the accuracy level of the monitoring result, and use the logic module of the terminal management platform to achieve output display. When δ ≥ 0.8, the monitoring effect level of the conductive arm characteristics of the isolated switch is displayed as excellent; when 0.8 > δ ≥ 0.6, the monitoring effect level of the conductive arm characteristics of the isolated switch is displayed as good; when δ < 0.6, the monitoring effect level of the conductive arm characteristics of the isolated switch is displayed as poor.

[0068] Example Four

[0069] Analyze the state of the target object based on the point cloud data to obtain the monitoring result, including the following steps:

[0070] Step 3-1: Use the software CloudCompare to synthesize ten single-frame PCD data collected during the same time period for the disconnector point cloud data to increase the point cloud data volume, improve the image imaging effect, be more conducive to the extraction of the disconnector conductive arm features, and enhance the data reliability;

[0071] Step 3-2: Use the image target area cropping algorithm to perform point cloud cutting: Introduce shrinkage factors S x 、S y 、S z in the x, y, and z-axis directions respectively; change the shrinkage factor values to make the disconnector conductive arm in the point cloud data have the best tightening boundary effect; cut the point cloud data in multiple coordinate axis directions: create the x-axis cropping object area value [-4, 4] and crop and retain the area; create the y-axis cropping object area value [-4, 8] and crop and retain the area; create the z-axis cropping object area value [0, 4.5] and crop and retain the area to obtain the disconnector conductive arm point cloud to better retain the side point cloud of each single-side conductive arm of the disconnector;

[0072] Step 3-3: Use the edge enhancement operator to enhance the local edges in the disconnector conductive arm point cloud: Locate the edge points by the zero-crossing points of the second-order derivative obtained from the point cloud; eliminate some boundary points or fill the boundary discontinuity points in the edge point set to obtain the three-dimensional edge point cloud data distributed along the surface of the disconnector conductive arm;

[0073] Step 3-4: Use the Euclidean clustering algorithm to perform noise reduction processing on the disconnector conductive arm point cloud to reduce environmental background noise points; among them, set the value range of the clustering threshold coefficient k of the Euclidean clustering algorithm within the interval [0.03, 0.12];

[0074] Step 3-5: Use the LMedS algorithm to perform a primary plane fitting on the point cloud data: Randomly extract N sample subsets from the point cloud samples; use the least squares method to calculate the model parameters and model errors for each sample subset; record the intermediate values of the model parameters and model errors, and finally select the model parameters corresponding to the minimum intermediate value of the model errors in the N sample subsets as the plane parameters. After multiple iterations to determine the optimal threshold and eliminate the outlier points; use the eigenvalue method to perform a secondary plane fitting on the point cloud data to obtain the fitting plane equations S1 and S2 of the side of the disconnector single-side conductive arm;

[0075] Step 3-6: Use the data processing method to obtain the normal vectors of the two planes, and calculate the included angle θ1 between the two normal vectors as the monitoring value of the disconnector conductive arm included angle.

[0076] It should be noted that the above-mentioned disconnector conductive arm feature monitoring system and computer-readable storage medium associated with the object surface area are also used to implement the above-mentionedFigure 1 The method steps corresponding to the embodiments in the method for monitoring the characteristics of the isolating switch conducting arm associated with the surface area of an object shown are not repeated herein in this application.

[0077] It should be noted that in each embodiment of the present invention, each functional unit / module can be integrated in one processing unit / module, or each unit / module can exist physically alone, or two or more units / module can be integrated in one unit / module. The above integrated unit / module can be implemented in the form of hardware or in the form of a software functional unit / module.

[0078] Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments described herein can be implemented by hardware, software, firmware, middleware, code, or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor, controller, microcontroller, microprocessor, or other electronic units designed to implement the functions described herein or a combination thereof. For software implementation, part or all of the process of the embodiment can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. The computer-readable medium includes computer storage media and communication media, where the communication media includes any medium facilitating the transfer of a computer program from one place to another. The storage media can be any available medium accessible by a computer. The computer-readable medium can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM, or other optical disc storage, magnetic disk storage media, or other magnetic storage devices, or any other medium capable of carrying or storing the desired program code in the form of instructions or data structures and accessible by a computer.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the protection scope of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should analyze that the technical solutions of the present invention can be modified or equivalently replaced without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. An isolating switch monitoring method associated with the surface area of an object, characterized in that, It includes the following steps: Obtain the point cloud data of the target object using a lidar; Analyze the state of the target object based on the point cloud data to obtain a monitoring result; Obtain the distance between the lidar and the target object; Obtain the surface area of the target object; Calculate the distance influence coefficient according to the distance between the lidar and the target object; Calculate the monitoring result accuracy according to the distance influence coefficient and the surface area; Wherein, the target object is a disconnector; Wherein, the analyzing the state of the target object based on the point cloud data to obtain a monitoring result is specifically as follows: Use an image target area cropping algorithm to cut the point cloud data in multiple coordinate axes directions to obtain the point cloud of the disconnector conductive arm; Use an edge enhancement operator to enhance the edge of the point cloud of the disconnector conductive arm; Use the Euclidean clustering algorithm to perform noise reduction processing on the point cloud of the disconnector conductive arm; Perform plane fitting on the point cloud of the unilateral conductive arm of the disconnector to obtain a first fitting plane and a second fitting plane; Calculate the angle between the first fitting plane and the second fitting plane as the monitoring result; Wherein, the calculating the monitoring result accuracy is expressed by the formula: In the formula, γ represents the accuracy of monitoring results; η r represents the transmission efficiency of the laser radar receiving optical system; K l Represents the distance influence coefficient; S n Represents the surface area of ​​the target object; S L represents the area of ​​the laser radar's field of view; T represents the atmospheric environment transmittance; φ represents the adjustment factor; Wherein, the calculating the distance influence coefficient is expressed by the formula: Where K l represents the distance influence coefficient; l b represents the distance between the lidar generator and the background environment; l n represents the distance between the laser generator and the target object; c1 represents a constant.

2. The isolation switch monitoring method associated with the surface area of an object according to claim 1, wherein The calculating the distance influence coefficient is specifically as follows: Calculate the distance influence coefficient according to the distance between the lidar and the background environment and the distance between the lidar and the target object.

3. The isolation switch monitoring method associated with the surface area of an object according to claim 2, characterized in that, The monitoring result includes the monitoring value of the disconnector conductive arm angle; Calculate the error factor according to the monitoring value of the disconnector conductive arm angle and the actual value of the disconnector conductive arm angle; update the monitoring result accuracy according to the error factor.

4. The isolation switch monitoring method associated with the surface area of an object according to claim 3, wherein The updating the monitoring result accuracy according to the error factor is expressed by the formula: δ = 0.5(1 - 100σ) + 0.5γ In the formula, γ represents the monitoring result accuracy; δ represents the updated monitoring result accuracy; σ represents the error factor.

5. An isolating switch monitoring system associated with the surface area of an object, characterized in that It includes: A lidar, which is used to obtain the point cloud data of the target object; An upper computer, which is used to analyze the state of the target object based on the point cloud data to obtain a monitoring result; obtain the distance between the lidar and the target object; obtain the surface area of the target object; calculate the distance influence coefficient according to the distance between the lidar and the target object; calculate the monitoring result accuracy according to the distance influence coefficient and the surface area; Wherein, the target object is a disconnector; Wherein, the analyzing the state of the target object based on the point cloud data to obtain a monitoring result is specifically as follows: Use an image target area cropping algorithm to cut the point cloud data in multiple coordinate axes directions to obtain the point cloud of the disconnector conductive arm; Use an edge enhancement operator to enhance the edge of the point cloud of the disconnector conductive arm; Use the Euclidean clustering algorithm to perform noise reduction processing on the point cloud of the disconnector conductive arm; Perform plane fitting on the point cloud of the unilateral conductive arm of the disconnector to obtain a first fitting plane and a second fitting plane; Calculate the angle between the first fitting plane and the second fitting plane as the monitoring result; Wherein, the calculating the monitoring result accuracy is expressed by the formula: where γ represents the accuracy of the monitoring result; η r represents the transmission efficiency of the lidar receiving optical system; K l represents the distance influence coefficient; S n represents the surface area of the target object; S L represents the lidar field of view area; T represents the atmospheric environment transmittance; represents the adjustment factor; Wherein, the calculating the distance influence coefficient is expressed by the formula: where K l represents the distance influence coefficient; l b represents the distance between the lidar generator and the background environment; l n represents the distance between the laser generator and the target object; c1 represents a constant.

6. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program is used to execute a method for monitoring a disconnect switch associated with an object surface area according to any one of claims 1-4 above.

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