Method for detecting icing thickness of overhead line system based on laser radar and depth camera

Abstract

The invention discloses an overhead line system icing thickness detection method based on a laser radar and a depth camera. The method comprises the steps that laser point cloud data and depth camera point cloud data of an overhead line system cable are acquired; calculating the detection thickness of the overhead line system cable according to the laser point cloud data and the depth camera point cloud data; and determining the icing thickness of the catenary cable according to the detection thickness of the catenary cable and the size of the catenary cable. According to the method, the icing thickness of the overhead line system cable can be rapidly and efficiently detected, whether the icing of the overhead line system cable is completely removed or not is effectively determined, and the probability that safety accidents that high-speed rails and bullet trains cannot take electricity and pantographs are damaged possibly is greatly reduced.

Description

Technical Field

[0001] The present application relates to the field of contact network technology, and in particular to a method for detecting the thickness of ice coating on a contact network based on a laser radar and a depth camera. Background Art

[0002] With the development of social economy and science and technology, high-speed railways and EMUs have become an increasingly important means of travel for people due to their high speed, short travel time, safety, convenience and reliability. The safety of the contact network, which is the power source of high-speed railways and EMUs, is also of paramount importance, especially in winter. After the contact network is covered with ice, the ice will cover the cables of the contact network, resulting in the high-speed railways and EMUs being unable to obtain electricity when passing by, and even causing damage to the pantograph due to the high speed.

[0003] At present, in order to reduce the occurrence of such problems in high-speed trains and EMUs due to icing on the contact network cables, manual de-icing is usually adopted. The operation and maintenance personnel stand on a slower train and manually de-ice the contact network by knocking, hammering, etc., and then manually check whether the ice on the contact network cables has been cleared. However, this manual inspection method is not only slow and inefficient, but also cannot ensure whether the ice on the contact network cables has been cleared. If there is still ice residue on the contact network cables, it may still cause safety accidents such as the high-speed train and EMU being unable to draw power and the pantograph being damaged. Summary of the invention

[0004] The purpose of this application is to provide a method, device, electronic device and storage medium for detecting the ice thickness of the contact network based on laser radar and depth camera, so as to quickly and efficiently detect the ice thickness of the contact network cable, effectively determine whether the ice on the contact network cable has been cleared, and greatly reduce the probability of safety accidents that may cause high-speed rail, EMU inability to draw power and pantograph damage.

[0005] In order to achieve the above objectives, in a first aspect, the present application provides a method for detecting the ice thickness of a contact network based on a laser radar and a depth camera, comprising:

[0006] Obtain laser point cloud data and depth camera point cloud data of overhead line cables;

[0007] Calculating the detection thickness of the contact network cable according to the laser point cloud data and the depth camera point cloud data;

[0008] The ice coating thickness of the contact network cable is determined according to the detected thickness of the contact network cable and the size of the contact network cable.

[0009] In a preferred embodiment of the present application, the laser point cloud data includes first laser point cloud data and second laser point cloud data, the first laser point cloud data is obtained by scanning a laser radar located on one side of the contact network cable, and the second laser point cloud data is obtained by scanning a laser radar located on the other side of the contact network cable;

[0010] The step of calculating the detection thickness of the contact network cable according to the laser point cloud data and the depth camera point cloud data includes:

[0011] The detection thickness of the contact network cable is calculated based on the first laser point cloud data, the second laser point cloud data and the depth camera point cloud data.

[0012] In a preferred embodiment of the present application, the depth camera point cloud data includes first depth camera point cloud data and second depth camera point cloud data, the first depth camera point cloud data is obtained by scanning with a depth camera located on one side of the contact network cable, and the second depth camera point cloud data is obtained by scanning with a depth camera located on the other side of the contact network cable;

[0013] The method of calculating the detection thickness of the contact network cable according to the first laser point cloud data, the second laser point cloud data and the depth camera point cloud data includes:

[0014] The detected thickness of the contact network cable is calculated based on the first laser point cloud data, the second laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data.

[0015] In a preferred embodiment of the present application, the detection thickness of the contact network cable is calculated based on the first laser point cloud data, the second laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data, including:

[0016] Merging the first laser point cloud data and the second laser point cloud data to obtain merged laser point cloud data;

[0017] The detected thickness of the contact network cable is calculated based on the merged laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data.

[0018] In a preferred embodiment of the present application, the detection thickness of the contact network cable is calculated based on the combined laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data, including:

[0019] Calculating and obtaining a first detection thickness, a second detection thickness and a third detection thickness of the overhead line cable according to the combined laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data respectively;

[0020] The position information of the contact network cable is obtained, and according to the position information of the contact network cable, the first detection thickness, the second detection thickness or the third detection thickness is used as the detection thickness of the contact network cable.

[0021] In a preferred embodiment of the present application, the first laser point cloud data and the second laser point cloud data are merged to obtain merged laser point cloud data, including:

[0022] Get the position calibration parameters of the laser radar;

[0023] According to the position calibration parameters of the laser radar, the first laser point cloud data and the second laser point cloud data in different coordinate systems are converted to the same coordinate system to obtain merged laser point cloud data.

[0024] In a preferred embodiment of the present application, the step of obtaining the position calibration parameters of the laser radar includes:

[0025] Acquire three groups of common points from the first laser point cloud data and the second laser point cloud data;

[0026] Substituting the coordinates of the three groups of common points into a preset calibration calculation formula to calculate the position calibration parameters of the laser radar;

[0027] The preset calibration calculation formula is as follows:

[0028]

[0029] Among them, (x A ,y A ) is the coordinate of point A in the first coordinate system of the first laser point cloud data, (x B ,y B ) is the coordinate of point B in the second coordinate system where the second laser point cloud data is located, A and B are a set of common points in the first laser point cloud data and the second laser point cloud data, and a, b, c, d, e, and f are position calibration parameters of the laser radar.

[0030] In a second aspect, the present application provides a device for detecting the thickness of ice covering a contact network based on a laser radar and a depth camera, comprising:

[0031] An acquisition module is used to acquire laser point cloud data and depth camera point cloud data of the contact network cable;

[0032] A calculation module, used for calculating the detection thickness of the contact network cable according to the laser point cloud data and the depth camera point cloud data;

[0033] The thickness determination module is used to determine the ice coating thickness of the contact network cable according to the detected thickness of the contact network cable and the size of the contact network cable.

[0034] In a third aspect, the present application provides an electronic device, comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to perform the above-mentioned method for detecting the ice thickness of the contact network based on laser radar and depth camera.

[0035] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned method for detecting the ice thickness of the contact network based on laser radar and depth camera.

[0036] The present application discloses a method, device, electronic device and storage medium for detecting the ice thickness of a contact network based on a laser radar and a depth camera. Compared with the prior art, the present application discloses at least the following features:

[0037] Beneficial effects:

[0038] The present application adopts laser radar and depth camera to quickly obtain laser point cloud data and depth camera point cloud data of the contact network cable. The laser point cloud data and depth camera point cloud data can quickly, efficiently and accurately calculate the detection thickness of the contact network cable. Combined with the size of the contact network cable, the ice thickness of the contact network cable can be determined. Compared with the manual inspection method in the prior art, this method can automatically detect the ice coverage of the contact network cable, and extremely quickly and efficiently detect the ice coverage thickness of the contact network cable, and effectively determine whether the ice coverage of the contact network cable has been cleared, thereby greatly reducing the probability of safety accidents that may cause high-speed rail, EMU inability to obtain power and pantograph damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 It is a flow chart of a method for detecting the thickness of ice covering the contact network based on a laser radar and a depth camera provided in an embodiment of the present application;

[0041] Figure 2 It is a schematic diagram of an application scenario of a method for detecting the thickness of ice covering a contact network based on a laser radar and a depth camera provided in an embodiment of the present application;

[0042] Figure 3 It is a structural block diagram of a device for detecting the thickness of catenary ice based on a laser radar and a depth camera provided in an embodiment of the present application;

[0043] Figure 4 It is a schematic diagram of the internal structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0044] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but are not intended to limit the scope of the present application.

[0045] At present, when the contact network cables are covered with ice, the usual practice is manual de-icing. The operation and maintenance personnel stand on a slow train and use knocking, hammering and other methods to manually de-ice the contact network, and then manually check whether the ice on the contact network cables has been cleared. However, this manual inspection method is not only slow and inefficient, but also cannot ensure whether the ice on the contact network cables has been cleared. If there is still ice residue on the contact network cables, it may still cause safety accidents such as the high-speed rail and EMU being unable to draw power and the pantograph being damaged.

[0046] In response to the above-mentioned problems in the prior art, the embodiments of the present application provide a method, device, electronic device and storage medium for detecting the ice thickness of the contact network based on laser radar and depth camera, so as to quickly and efficiently detect the ice thickness of the contact network cable and effectively determine whether the ice on the contact network cable has been cleared, thereby greatly reducing the probability of safety accidents that may cause high-speed railways and EMUs to be unable to draw power and pantographs to be damaged.

[0047] See also Figure 1 , Figure 1 It is a flow chart of a method for detecting ice thickness of a contact network based on a laser radar and a depth camera provided in an embodiment of the present application.

[0048] The following method for detecting the thickness of ice covering the contact network based on laser radar and depth camera in the embodiment of the present application can be applied to computer equipment such as servers.

[0049] The present application provides a method for detecting the thickness of catenary ice based on a laser radar and a depth camera, comprising the following steps:

[0050] Step S110, obtaining laser point cloud data and depth camera point cloud data of the overhead line cable.

[0051] The overhead line cable may be an overhead line cable that has been artificially de-iced or an overhead line cable that has not been de-iced. It is understandable that the overhead line cable may be covered with ice or not.

[0052] The laser point cloud data of the contact network cable is obtained by laser radar scanning, optionally, the laser radar can use a 3D profiler; the depth camera point cloud data of the contact network cable is obtained by depth camera scanning; it can be understood that the laser point cloud data and depth camera point cloud data of the contact network cable are point cloud data of the cross section of the contact network cable.

[0053] The laser radar and depth camera can be set on the top of the high-speed railway or the motor vehicle and installed in a predetermined manner to scan the contour of the contact network cable above the high-speed railway or the motor vehicle to obtain the laser point cloud data and depth camera point cloud data of the contact network cable. The following embodiments use this application scenario as an example to illustrate, describe and explain the corresponding contents of the embodiment scheme.

[0054] Step S120, calculating the detection thickness of the contact network cable according to the laser point cloud data and the depth camera point cloud data.

[0055] In one embodiment, the detection thickness of the contact network cable corresponding to the two different point cloud data can be calculated respectively using laser point cloud data and depth camera point cloud data, and then the detection thickness of the contact network cable corresponding to the two different point cloud data can be combined to finally calculate the detection thickness of the contact network cable.

[0056] In other embodiments, the laser point cloud data and the depth camera point cloud data may also be fitted, and then the detected thickness of the contact network cable may be calculated using the fitted point cloud data.

[0057] By combining the laser point cloud data of the contact network cable and the depth camera point cloud data, the thickness of the contact network cable can be detected more accurately, thereby ensuring the accuracy of the ice thickness of the contact network cable.

[0058] Step S130, determining the ice coating thickness of the overhead line cable according to the detected thickness of the overhead line cable and the size of the overhead line cable.

[0059] The ice thickness of the contact network cable is understood as the thickness of the ice on the contact network cable, which is the thickness of the ice on the contact network cable in the vertical direction. When there is no ice on the contact network cable, the ice thickness of the contact network cable is 0.

[0060] In one embodiment, the size of the contact network cable is the diameter of the contact network cable. When determining the ice thickness of the contact network cable, the ice thickness of the contact network cable is determined by the difference between the detected thickness of the contact network cable and the diameter of the contact network cable.

[0061] The method for detecting ice thickness of the contact network based on laser radar and depth camera in the embodiment of the present application adopts laser radar and depth camera to quickly obtain laser point cloud data and depth camera point cloud data of the contact network cable. The detection thickness of the contact network cable can be quickly, efficiently and accurately calculated through the laser point cloud data and the depth camera point cloud data. Combined with the size of the contact network cable, the ice thickness of the contact network cable can be determined. Compared with the manual inspection method in the prior art, this method can automatically detect the ice condition of the contact network cable, and extremely quickly and efficiently detect the ice thickness of the contact network cable, and effectively determine whether the ice on the contact network cable has been cleared, thereby greatly reducing the probability of safety accidents such as the inability of high-speed rail and EMU to obtain power and the damage of pantograph.

[0062] In addition, due to the transmittance and scattering properties of the ice layer, it is actually difficult to detect ice coating on the contact network. Moreover, due to the particularity of the application scenario, most detection equipment cannot directly contact the contact network. In view of this, the method for detecting the ice coating thickness of the contact network in the embodiment of the present application uses a laser radar and a depth camera to scan the contact network cable. This is a method for detecting the ice coating thickness of the contact network without contacting the contact network cable. It has high stability, safety and reliability, and high applicability.

[0063] After determining the ice thickness of the contact network cables, it can be displayed in real time on the server background, so that the operation and maintenance personnel can determine whether it is necessary to de-ice the contact network cables at the corresponding positions based on the determined ice thickness of the contact network cables, or when the determined ice thickness of the contact network cables exceeds a predetermined thickness threshold, an alarm will be issued on the server background.

[0064] See also Figure 2 , Figure 2 It is a schematic diagram of an application scenario of a method for detecting the thickness of ice covering on a contact network based on a laser radar and a depth camera provided in an embodiment of the present application. The wires in the figure represent contact network cables.

[0065] In one embodiment, the laser point cloud data includes first laser point cloud data and second laser point cloud data, the first laser point cloud data is obtained by scanning a laser radar located on one side of the contact network cable, and the second laser point cloud data is obtained by scanning a laser radar located on the other side of the contact network cable, that is, laser radars are installed on the left and right sides of the top of the high-speed rail or the motor vehicle. Usually, the contact network cable is located in the middle position above the high-speed rail or the motor vehicle, and there are also cases where it is biased to the left or right. Basically, the laser radars installed on the left and right sides of the top of the high-speed rail or the motor vehicle are also located on both sides of the contact network cable; preferably, the laser radars installed on the left and right sides of the top of the high-speed rail or the motor vehicle are symmetrically arranged, and the scanning angles are corresponding;

[0066] Since the laser radar has a limited field of view and emits a single line of laser, a single laser radar can only scan one side of the overhead contact cable. By setting laser radars on both sides of the overhead contact cable, the outline of the overhead contact cable scanned by the laser radar is more complete.

[0067] Furthermore, when the detection thickness of the contact network cable is calculated based on the laser point cloud data and the depth camera point cloud data, the detection thickness of the contact network cable is calculated based on the first laser point cloud data, the second laser point cloud data and the depth camera point cloud data, thereby improving the accuracy of the detection thickness of the contact network cable, thereby improving the accuracy of the ice coating thickness of the contact network cable.

[0068] In this embodiment, as an optional implementation, the depth camera point cloud data includes first depth camera point cloud data and second depth camera point cloud data, the first depth camera point cloud data is obtained by scanning with a depth camera located on one side of the contact network cable, and the second depth camera point cloud data is obtained by scanning with a depth camera located on the other side of the contact network cable, that is, depth cameras are installed on the left and right sides of the top of the high-speed rail or the motor vehicle. Usually, the contact network cable is located in the middle position above the high-speed rail or the motor vehicle, and there are also cases where it is biased to the left or right. Basically, the depth cameras installed on the left and right sides of the top of the high-speed rail or the motor vehicle are also located on both sides of the contact network cable; preferably, the depth cameras installed on the left and right sides of the top of the high-speed rail or the motor vehicle are symmetrically arranged;

[0069] Furthermore, when the detection thickness of the contact network cable is calculated according to the first laser point cloud data, the second laser point cloud data and the depth camera point cloud data, the detection thickness of the contact network cable is calculated according to the first laser point cloud data, the second laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data. By arranging depth cameras on both sides of the contact network cable, it is possible to avoid the situation where the contact network cable is positioned to the left or right above the high-speed railway or the EMU, resulting in the depth camera being unable to scan the contact network cable, thereby ensuring the validity of the depth camera point cloud data, and further ensuring the accuracy of the detection thickness of the contact network cable, thereby improving the accuracy of the ice thickness of the contact network cable.

[0070] It should be noted that the embodiment of the present application does not limit the number of laser radars and depth cameras to two each. In other embodiments, the number of laser radars and depth cameras may also vary. For example, one laser radar and one depth camera may be used, or one laser radar and two depth cameras may be used.

[0071] Optionally, calculating the detection thickness of the contact network cable according to the first laser point cloud data, the second laser point cloud data, the first depth camera point cloud data, and the second depth camera point cloud data may include:

[0072] Merging the first laser point cloud data and the second laser point cloud data to obtain merged laser point cloud data;

[0073] The detection thickness of the contact network cable is calculated based on the combined laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data.

[0074] The merged laser point cloud data obtained by merging the first laser point cloud data and the second laser point cloud data is laser point cloud data that represents a more complete outline of the contact network cable. This method can more conveniently and effectively obtain laser point cloud data that represents a more complete outline of the contact network cable.

[0075] Further, calculating the detection thickness of the contact network cable according to the combined laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data may include:

[0076] According to the combined laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data, a first detection thickness, a second detection thickness and a third detection thickness of the contact network cable are calculated accordingly;

[0077] The position information of the contact network cable is obtained, and according to the position information of the contact network cable, the first detection thickness, the second detection thickness or the third detection thickness is used as the detection thickness of the contact network cable.

[0078] When the first detection thickness of the contact network cable is calculated based on the merged laser point cloud data, the first detection thickness of the contact network cable can be calculated by using the minimum outer bounding rectangle method, so as to improve the accuracy of the first detection thickness of the contact network cable;

[0079] When the second detection thickness of the contact network cable is calculated according to the point cloud data of the first depth camera and the third detection thickness of the contact network cable is calculated according to the point cloud data of the second depth camera, the interference point cloud data in the corresponding depth camera point cloud data can be filtered out based on the distance from the contact network cable to the first depth camera or the second depth camera to obtain the corresponding target point cloud data, and then the corresponding second detection thickness or third detection thickness of the contact network cable is calculated by the average value calculation method. The distance from the contact network cable to the depth camera can be used to exclude interference from objects other than the contact network cable scanned by the depth camera, thereby greatly reducing the amount of calculation and ensuring the accuracy of the calculated second detection thickness or third detection thickness of the contact network cable. The average value calculation method can further improve the accuracy of the second detection thickness or third detection thickness of the contact network cable.

[0080] The position information of the overhead contact cable may be the position of the section of the overhead contact cable above the high-speed railway or the motor vehicle, and there are three situations in which the section of the overhead contact cable is located in the middle position, the left position, or the right position above the high-speed railway or the motor vehicle. It can be understood that the position information of the overhead contact cable of different sections on the same overhead contact cable may be different; optionally, the position information of the overhead contact cable may be obtained by using a position detection sensor;

[0081] In this embodiment, if the position information of the contact network cable is located in the middle position above the high-speed railway or the motor vehicle, the first detection thickness of the contact network cable calculated by merging the laser point cloud data is used as the detection thickness of the contact network cable; if the position information of the contact network cable is located on the left side of the high-speed railway or the motor vehicle, the second detection thickness of the contact network cable calculated by the first depth camera point cloud data (assuming that the first depth camera point cloud data is obtained by the depth camera located on the left side of the top of the high-speed railway or the motor vehicle) is used as the detection thickness of the contact network cable; if the position information of the contact network cable is located on the right side of the high-speed railway or the motor vehicle, the third detection thickness of the contact network cable calculated by the second depth camera point cloud data (assuming that the second depth camera point cloud data is obtained by the depth camera located on the right side of the top of the high-speed railway or the motor vehicle) is used as the detection thickness of the contact network cable. Measure thickness; during the actual detection process, the train moves forward at a certain speed, the position of the contact network cable will move left and right, and the contact network cable is not necessarily located in the middle position, so the contact network cable is not necessarily in the center. When the contact network cable is on the left, the detection results corresponding to the lidar and the right depth camera may both be 0, and the detection result corresponding to the left depth camera shall prevail; when the wire is in the middle, the detection result corresponding to the merging of the lidar point cloud data shall prevail; when the wire is on the right, the detection results corresponding to the lidar and the left depth camera may both be 0, and the detection result corresponding to the right depth camera shall prevail. In this way, various situations of the position of the contact network cable are fully considered, and the detection thickness of the contact network cable can be calculated in a relatively convenient, fast and accurate manner for different position situations.

[0082] As an optional implementation, merging the first laser point cloud data and the second laser point cloud data to obtain merged laser point cloud data may include:

[0083] Get the position calibration parameters of the laser radar;

[0084] According to the position calibration parameters of the laser radar, the first laser point cloud data and the second laser point cloud data in different coordinate systems are converted to the same coordinate system to obtain merged laser point cloud data.

[0085] Through the position calibration parameters of the laser radar, it is convenient to convert the first laser point cloud data and the second laser point cloud data in different coordinate systems into the same coordinate system to obtain the merged laser point cloud data, and ensure the accuracy of the merged laser point cloud data.

[0086] Optionally, obtaining the position calibration parameters of the laser radar may include:

[0087] Acquire three groups of common points from the first laser point cloud data and the second laser point cloud data;

[0088] Substitute the coordinates of the three sets of common points into the preset calibration calculation formula to calculate the position calibration parameters of the laser radar;

[0089] The preset calibration calculation formula is as follows:

[0090]

[0091] Among them, (x A ,y A ) is the coordinate of point A in the first coordinate system where the first laser point cloud data is located, (x B ,y B ) is the coordinate of point B in the second coordinate system where the second laser point cloud data is located, A and B are a group of common points in the first laser point cloud data and the second laser point cloud data, and a, b, c, d, e, and f are position calibration parameters of the laser radar.

[0092] Since the laser radars installed on the left and right sides of the top of the high-speed rail or the motor vehicle used in the embodiment are located in the same plane, the three-dimensional coordinate system is changed to a two-dimensional coordinate system, and considering that the laser radar and its installation may have processing errors and installation errors, the above-mentioned preset calibration calculation formula is used to calculate the position calibration parameters of the laser radar with the three groups of common points in the first laser point cloud data and the second laser point cloud data. The error influence caused by the processing error and the installation error can be eliminated, and the availability and accuracy of the position calibration parameters of the laser radar can be maximized, thereby ensuring the accuracy of the merged laser point cloud data.

[0093] In order to execute the methods corresponding to the above embodiments and achieve corresponding functions and technical effects, a device for detecting the ice thickness of a contact network based on a laser radar and a depth camera is provided below.

[0094] See also Figure 3 , Figure 3 It is a structural block diagram of a device for detecting the thickness of ice covering the contact network based on a laser radar and a depth camera provided in an embodiment of the present application.

[0095] The embodiment of the present application provides a device for detecting the thickness of ice on a contact network based on a laser radar and a depth camera, comprising:

[0096] An acquisition module 310 is used to acquire laser point cloud data and depth camera point cloud data of the overhead line cable;

[0097] A calculation module 320 is used to calculate the detection thickness of the contact network cable according to the laser point cloud data and the depth camera point cloud data;

[0098] The thickness determination module 330 is used to determine the ice coating thickness of the overhead line cable according to the detected thickness of the overhead line cable and the size of the overhead line cable.

[0099] The device for detecting ice coating thickness of the contact network based on laser radar and depth camera in the embodiment of the present application adopts laser radar and depth camera to quickly obtain laser point cloud data and depth camera point cloud data of the contact network cable. The detection thickness of the contact network cable can be quickly, efficiently and accurately calculated through the laser point cloud data and the depth camera point cloud data. Combined with the size of the contact network cable, the ice coating thickness of the contact network cable can be determined. Compared with the manual inspection method in the prior art, this method can automatically detect the ice coating of the contact network cable, and extremely quickly and efficiently detect the ice coating thickness of the contact network cable, and effectively determine whether the ice coating of the contact network cable has been cleared, thereby greatly reducing the probability of safety accidents such as the inability of high-speed railways and EMUs to obtain power and damage to pantographs.

[0100] In one embodiment, the calculation module 320 may be specifically configured to:

[0101] The detection thickness of the contact network cable is calculated based on the first laser point cloud data, the second laser point cloud data and the depth camera point cloud data.

[0102] As an optional implementation, when the calculation module 320 calculates the detection thickness of the contact network cable according to the first laser point cloud data, the second laser point cloud data and the depth camera point cloud data, it can:

[0103] The detection thickness of the contact network cable is calculated based on the first laser point cloud data, the second laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data.

[0104] Optionally, when the calculation module 320 calculates the detection thickness of the contact network cable according to the first laser point cloud data, the second laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data, it can:

[0105] Merging the first laser point cloud data and the second laser point cloud data to obtain merged laser point cloud data;

[0106] The detection thickness of the contact network cable is calculated based on the combined laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data.

[0107] Furthermore, when the calculation module 320 calculates the detection thickness of the contact network cable according to the combined laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data, it can:

[0108] According to the combined laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data, a first detection thickness, a second detection thickness and a third detection thickness of the contact network cable are calculated accordingly;

[0109] The position information of the contact network cable is obtained, and according to the position information of the contact network cable, the first detection thickness, the second detection thickness or the third detection thickness is used as the detection thickness of the contact network cable.

[0110] Furthermore, when the calculation module 320 combines the first laser point cloud data and the second laser point cloud data to obtain combined laser point cloud data, it can:

[0111] Get the position calibration parameters of the laser radar;

[0112] According to the position calibration parameters of the laser radar, the first laser point cloud data and the second laser point cloud data in different coordinate systems are converted to the same coordinate system to obtain merged laser point cloud data.

[0113] Furthermore, when obtaining the position calibration parameters of the laser radar, the calculation module 320 may:

[0114] Acquire three groups of common points from the first laser point cloud data and the second laser point cloud data;

[0115] Substitute the coordinates of the three sets of common points into the preset calibration calculation formula to calculate the position calibration parameters of the laser radar;

[0116] The preset calibration calculation formula is as follows:

[0117]

[0118] Among them, (x A ,y A ) is the coordinate of point A in the first coordinate system where the first laser point cloud data is located, (x B ,y B ) is the coordinate of point B in the second coordinate system where the second laser point cloud data is located, A and B are a group of common points in the first laser point cloud data and the second laser point cloud data, and a, b, c, d, e, and f are position calibration parameters of the laser radar.

[0119] The above-mentioned device for detecting the thickness of catenary ice coating based on laser radar and depth camera can implement the above-mentioned method for detecting the thickness of catenary ice coating based on laser radar and depth camera. The specific limitations and other contents of the above-mentioned embodiment of the device for detecting the thickness of catenary ice coating based on laser radar and depth camera can be referred to the contents of the above-mentioned method for detecting the thickness of catenary ice coating based on laser radar and depth camera, and will not be repeated in the embodiment.

[0120] An embodiment of the present application also provides an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the above-mentioned method for detecting the ice thickness of the contact network based on laser radar and depth camera.

[0121] Optionally, the electronic device mentioned above may be a computer device such as a server.

[0122] In one embodiment, the internal structure of the electronic device of the present application can be as follows: Figure 4 shown.

[0123] An embodiment of the present application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned method for detecting the ice thickness of the contact network based on a laser radar and a depth camera.

[0124] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0125] In addition, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0126] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0127] The above description is only an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0128] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0129] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations; at the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

Claims

1. A method for detecting the thickness of catenary ice based on laser radar and depth camera, characterized in that: include: Obtain laser point cloud data and depth camera point cloud data of overhead line cables; Calculating the detection thickness of the contact network cable according to the laser point cloud data and the depth camera point cloud data; The ice coating thickness of the contact network cable is determined according to the detected thickness of the contact network cable and the size of the contact network cable.

2. The method for detecting the thickness of catenary ice based on laser radar and depth camera according to claim 1 is characterized in that: The laser point cloud data includes first laser point cloud data and second laser point cloud data, the first laser point cloud data is obtained by scanning a laser radar located on one side of the contact network cable, and the second laser point cloud data is obtained by scanning a laser radar located on the other side of the contact network cable; The step of calculating the detection thickness of the contact network cable according to the laser point cloud data and the depth camera point cloud data includes: The detection thickness of the contact network cable is calculated based on the first laser point cloud data, the second laser point cloud data and the depth camera point cloud data.

3. The method for detecting the thickness of catenary ice based on laser radar and depth camera according to claim 2 is characterized in that: The depth camera point cloud data includes first depth camera point cloud data and second depth camera point cloud data, the first depth camera point cloud data is obtained by scanning with a depth camera located on one side of the contact network cable, and the second depth camera point cloud data is obtained by scanning with a depth camera located on the other side of the contact network cable; The method of calculating the detection thickness of the contact network cable according to the first laser point cloud data, the second laser point cloud data and the depth camera point cloud data includes: The detected thickness of the contact network cable is calculated based on the first laser point cloud data, the second laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data.

4. The method for detecting the thickness of catenary ice based on laser radar and depth camera according to claim 3 is characterized in that: The method of calculating the detection thickness of the contact network cable according to the first laser point cloud data, the second laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data comprises: Merging the first laser point cloud data and the second laser point cloud data to obtain merged laser point cloud data; The detected thickness of the contact network cable is calculated based on the merged laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data.

5. The method for detecting the thickness of ice coating on the contact network based on laser radar and depth camera according to claim 4 is characterized in that: The method of calculating the detection thickness of the contact network cable according to the combined laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data comprises: Calculating and obtaining a first detection thickness, a second detection thickness and a third detection thickness of the overhead line cable according to the combined laser point cloud data, the first depth camera point cloud data and the second depth camera point cloud data respectively; The position information of the contact network cable is obtained, and according to the position information of the contact network cable, the first detection thickness, the second detection thickness or the third detection thickness is used as the detection thickness of the contact network cable.

6. The method for detecting the thickness of catenary ice based on laser radar and depth camera according to claim 4 is characterized in that: The step of merging the first laser point cloud data and the second laser point cloud data to obtain merged laser point cloud data includes: Get the position calibration parameters of the laser radar; According to the position calibration parameters of the laser radar, the first laser point cloud data and the second laser point cloud data in different coordinate systems are converted to the same coordinate system to obtain merged laser point cloud data.

7. The method for detecting the thickness of catenary ice based on laser radar and depth camera according to claim 6 is characterized in that: The step of obtaining the position calibration parameters of the laser radar includes: Acquire three groups of common points from the first laser point cloud data and the second laser point cloud data; Substituting the coordinates of the three groups of common points into a preset calibration calculation formula to calculate the position calibration parameters of the laser radar; The preset calibration calculation formula is as follows: Among them, (x A ,y A ) is the coordinate of point A in the first coordinate system of the first laser point cloud data, (x B ,y B ) is the coordinate of point B in the second coordinate system where the second laser point cloud data is located, A and B are a set of common points in the first laser point cloud data and the second laser point cloud data, and a, b, c, d, e, and f are position calibration parameters of the laser radar.

8. A device for detecting the ice thickness of a contact network based on a laser radar and a depth camera, characterized in that: include: An acquisition module is used to acquire laser point cloud data and depth camera point cloud data of the contact network cable; A calculation module, used for calculating the detection thickness of the contact network cable according to the laser point cloud data and the depth camera point cloud data; The thickness determination module is used to determine the ice coating thickness of the contact network cable according to the detected thickness of the contact network cable and the size of the contact network cable.

9. An electronic device, characterized in that: It includes a memory and a processor, the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to perform the method for detecting the ice thickness of the contact network based on a laser radar and a depth camera according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: It stores a computer program, which, when executed by a processor, implements a method for detecting the ice thickness of a contact network based on a laser radar and a depth camera as described in any one of claims 1 to 7.

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