Method, device, medium and equipment for measuring vehicle bottom vibration based on structured light system

Abstract

The present application provides a method, device, medium and equipment for measuring vehicle bottom vibration based on a structured light system. The present invention calibrates the relative position relationship between the camera and the laser plane, establishes a mapping relationship between the two-dimensional laser point and the three-dimensional space, and accurately measures the relative displacement of the train and the track in real time. It also uses a tracking and matching algorithm for real-time calibration to achieve compensation for geometric parameters, thus solving the problem of large cumulative errors and inability to calibrate in current train vibration measurement methods.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle bottom vibration measurement, and in particular to a vehicle bottom vibration measurement method, device, medium and equipment based on a structured light system. Background Art

[0002] Catenary geometry is one of the most critical parameters to monitor during rail transit train operation. Detecting geometric parameter anomalies directly impacts train safety. Currently, all methods for measuring catenary geometry use the vehicle roof as the base point. This means that regardless of the accuracy of the measurement method, only the relative position between the vehicle roof and the catenary can be determined. However, the truly valuable geometric parameter is the relative position between the catenary and the track. Due to the vibrations generated by high-speed trains, centimeter-level displacements can occur between the train and the track surface. The relative position of the catenary and the track is not identical to the relative position of the catenary and the train, but rather comprises the relative positions of the catenary and the train, and the train and the track. Therefore, measuring the vibration offset between the train and the track and compensating for the geometric parameters is crucial for ensuring train safety.

[0003] The current mainstream method for measuring train vibration is based on inertial sensors, which use 6-degree-of-freedom accelerometers, gyroscopes, and magnetometers to calculate the offset between the train and the track in real time. However, inertial sensors often have poor measurement accuracy for high-frequency and irregular train vibrations. Furthermore, the long-term operation of trains leads to increasing cumulative errors, making real-time calibration impossible. Summary of the Invention

[0004] In view of the shortcomings of the existing technology mentioned above, the purpose of this application is to provide a vehicle bottom vibration measurement method, device, medium and equipment based on a structured light system, which is used to solve the technical problem that the existing vehicle bottom vibration measurement method has increasingly large cumulative errors and cannot achieve real-time calibration.

[0005] To achieve the above-mentioned objectives and other related objectives, the first aspect of the present application provides a method for measuring vehicle bottom vibration based on a structured light system, comprising: calibrating the structured light system; the structured light system includes an image acquisition device and a laser; obtaining a rail image captured by the calibrated image acquisition device, locating the laser lines in the rail image through a visual algorithm and summarizing the number of laser lines to be identified, and sorting the contours of all laser lines in descending order according to the degree of shape feature matching; repeating the above steps until a contour is detected in the current frame; if the current frame is the initial frame or there is no matching contour in the previous frame, selecting the contour with the largest shape feature matching degree as the initial position of the target laser line, jumping to the next frame and re-executing the steps after the calibration of the structured light system; if there is a matched contour in the previous frame, traversing the candidate contours from large to small according to the degree of shape feature matching; if the pixel deviation of the candidate contour in the image with the matched contour in the previous frame is less than a preset threshold, calculating the displacement between the train and the track in the vertical direction and the lateral direction of the train based on the pixel deviation as the compensation value of the contact network geometric parameters; otherwise, jumping to the next frame and re-executing the steps after the calibration of the structured light system.

[0006] In some embodiments of the first aspect of the present application, the results of calibrating the structured light system include: obtaining the industrial camera internal parameter K; obtaining the expression of the laser plane in the camera coordinate system: ax+by+cz+d=0; wherein x, y, z are the three-dimensional point coordinates in the camera coordinate system, and a, b, c, d are the laser plane coefficients.

[0007] In some embodiments of the first aspect of the present application, the method of locating the laser lines in the rail image by a visual algorithm and summarizing the number of laser lines to be identified, and sorting the contours of all laser lines in descending order according to the degree of shape feature matching, includes: preprocessing the rail image, which includes: filtering the laser lines in the rail system that are not bright enough and / or occupy too small a pixel area using binarization and corrosion operations; extracting the contours of the laser lines in the rail image; extracting the shape features of the extracted laser line contours, and comparing the similarity with the preset shape features, and arranging the similarity comparison results in descending order.

[0008] In some embodiments of the first aspect of the present application, the shape feature extraction of the extracted laser line profile is performed, and a similarity comparison is performed with the preset shape feature, and the similarity comparison results are arranged in descending order, including: extracting the shape feature of the laser line profile by extracting the Hu moment feature, calculating the Euclidean distance between the extracted Hu moment feature and the preset Hu moment feature to calculate its similarity with the preset rail head shape.

[0009] In some embodiments of the first aspect of the present application, the displacement between the train and the track in the vertical direction and the lateral direction of the train is calculated based on pixel deviation as a compensation value for the contact network geometric parameters, which includes: projecting the pixel offset value of the current frame contour and the matched contour of the previous frame into the camera coordinate system to calculate the corresponding three-dimensional offset value; calculating the corresponding rotation matrix according to the installation position and angle of the camera coordinate system on the train; and calculating the displacement between the train and the track in the vertical direction and the lateral direction of the train based on the rotation matrix as a compensation value for the height guide value and pull-out value in the contact network geometric parameters.

[0010] In some embodiments of the first aspect of the present application, the calculation process of the compensation value of the contact network geometric parameters includes: defining the pixel coordinates of the center point of the matched contour in the previous frame and the pixel coordinates of the center point of the matched contour in the current frame; mapping each pixel coordinate to the camera coordinate system through the camera calibration result; converting the camera coordinates corresponding to each pixel coordinate in the camera coordinate system to the train world coordinate system according to the module and position to obtain the corresponding world coordinates; according to the world coordinates of the center point pixel of the matched contour in the previous frame and the center point pixel of the matched contour in the current frame, subtracting the Z coordinates of the two world coordinates to obtain a vertical vibration measurement value as a guide height compensation value, and subtracting the X coordinates of the two world coordinates to obtain a horizontal vibration measurement value as a pull-out compensation value.

[0011] To achieve the above-mentioned purpose and other related purposes, the second aspect of the present application provides a vehicle bottom vibration measurement device, which is installed on both sides of a moving train; the device includes: a laser emitting unit, which is used to emit a laser beam to the target rail; an image acquisition unit, which is used to acquire images of the target rail; wherein the image acquisition unit is externally connected to a control device; the control device executes the vehicle bottom vibration measurement method based on the structured light system after receiving the rail image acquired by the image acquisition unit.

[0012] To achieve the above-mentioned purpose and other related purposes, the third aspect of the present application provides a vehicle bottom vibration measurement system, comprising: at least one pair of the vehicle bottom vibration measurement devices installed on a moving train; the control device establishes a communication connection with the image acquisition unit in the vehicle bottom vibration measurement device to execute the vehicle bottom vibration measurement method based on the structured light system after receiving the rail image captured by the image acquisition unit.

[0013] To achieve the above-mentioned purpose and other related purposes, the fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the vehicle bottom vibration measurement method based on the structured light system.

[0014] To achieve the above-mentioned purpose and other related purposes, the fifth aspect of the present application provides a computer device, including: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal executes the vehicle bottom vibration measurement method based on the structured light system.

[0015] As described above, the vehicle bottom vibration measurement method, device, medium and equipment based on the structured light system of the present application have the following beneficial effects: the present invention calibrates the relative position relationship between the camera and the laser plane, establishes a mapping relationship between the two-dimensional laser point and the three-dimensional space, and accurately measures the relative displacement of the train and the track in real time. It also realizes real-time calibration through the tracking and matching algorithm to achieve compensation for the geometric parameters, thereby solving the problem of large cumulative errors and inability to calibrate in the current train vibration measurement method. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Shown is a flow chart of a method for measuring vehicle bottom vibration based on a structured light system in one embodiment of the present application.

[0017] Figure 2 Shown is a schematic structural diagram of a vehicle bottom vibration measuring device in one embodiment of the present application.

[0018] Figure 3 Shown is a schematic diagram of the installation of a vehicle bottom vibration measuring device in one embodiment of the present application.

[0019] Figure 4 Shown is a flow chart of a vehicle bottom vibration measurement method in one embodiment of the present application.

[0020] Figure 5 Shown is a structural diagram of a computer device in one embodiment of the present application.

[0021] Figure 6 Shown is a schematic structural diagram of a vehicle bottom vibration measurement system based on a structured light system in one embodiment of the present application. DETAILED DESCRIPTION

[0022] The following describes the embodiments of the present application through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present application from the content disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0023] It should be noted that in the following description, reference is made to the accompanying drawings, which describe several embodiments of the present application. It should be understood that other embodiments may also be used, and that mechanical, structural, electrical, and operational changes may be made without departing from the spirit and scope of the present application. The following detailed description should not be considered restrictive, and the scope of the embodiments of the present application is limited only by the claims of the published patents. The terms used herein are only for describing specific embodiments and are not intended to limit the present application. Spatially related terms, such as "upper", "lower", "left", "right", "below", "below", "lower", "above", "upper", etc., may be used in the text to facilitate the description of the relationship between one element or feature shown in the figure and another element or feature.

[0024] In this application, unless otherwise specified or limited, the terms "mounted," "connected," "connect," "fixed," "holding," and the like should be understood broadly. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediary; or internal communication between two components. Those skilled in the art will understand the specific meanings of these terms in this application based on specific circumstances.

[0025] Furthermore, as used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It should be further understood that the terms "comprise", "include" indicate the presence of the described features, operations, elements, components, items, kinds, and / or groups, but do not exclude the presence, occurrence, or addition of one or more other features, operations, elements, components, items, kinds, and / or groups. The terms "or" and "and / or" used herein are interpreted as inclusive, or mean any one or any combination. Thus, "A, B, or C" or "A, B, and / or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B, and C". Exceptions to this definition occur only when the combination of elements, functions, or operations is inherently mutually exclusive in some way.

[0026] In order to solve the problems in the above-mentioned background technology, the present invention proposes a method, device, medium and equipment for measuring vehicle bottom vibration based on a structured light system. The purpose is to establish a mapping relationship between two-dimensional laser points and three-dimensional space by calibrating the relative position relationship between the camera and the laser plane, so as to accurately measure the relative displacement of the train and the track in real time, and realize real-time calibration through tracking and matching algorithm to achieve compensation for geometric parameters, thereby solving the problem of large cumulative error and inability to calibrate the current train vibration measurement method.

[0027] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the following embodiments and the accompanying drawings are used to further describe the technical solutions in the embodiments of the present invention. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0028] Before further explaining the present invention in detail, the nouns and terms involved in the embodiments of the present invention are explained. The nouns and terms involved in the embodiments of the present invention are subject to the following interpretations:

[0029] (1) Structured light: A system consisting of a projector and a camera. The projector projects specific light information onto the surface of an object and the background, which is then captured by the camera. The position and depth of the object are calculated based on the changes in the light signal caused by the object, thereby restoring the entire three-dimensional space.

[0030] (2) Catenary: The catenary is a high-voltage transmission line that is erected in a zigzag pattern above the rails on an electrified railway and is used by pantographs to draw current. The catenary is the main structure of the railway electrification project and is a special form of transmission line erected above the railway line to supply power to electric locomotives. It consists of contact suspension, support devices, positioning devices, pillars, and foundations.

[0031] Embodiments of the present invention provide a method for measuring vehicle bottom vibrations using a structured light system, a system for performing such a method, and a storage medium storing an executable program for implementing such a method. Regarding the implementation of such a method, embodiments of the present invention will describe an exemplary implementation scenario for such a method.

[0032] like Figure 1 FIG. 1 is a flow chart showing a method for measuring vehicle bottom vibration based on a structured light system according to an embodiment of the present invention. The method for measuring vehicle bottom vibration based on a structured light system according to this embodiment mainly includes the following steps:

[0033] Step S11: calibrating the structured light system; the structured light system includes an image acquisition device and a laser.

[0034] Optionally, an industrial camera can be used as the image acquisition device. An industrial camera is a key component in a machine vision system. Its most essential function is to convert optical signals into ordered electrical signals. Compared to conventional cameras, industrial cameras offer higher image stability, higher transmission capabilities, and greater anti-interference capabilities. Suitable industrial cameras include those based on CCD (Charge Coupled Device) or CMOS (Complementary Metal Oxide Semiconductor) chips.

[0035] In this embodiment, the structured light system is a vehicle bottom vibration measuring device, and the structure diagram of the vehicle bottom vibration measuring device is as shown in FIG. Figure 2 As shown, the field of view of the industrial camera is perpendicular to the track axis, and the angle between the laser and the industrial camera is preferably 45° to ensure that the laser line hitting the rail is clearly and completely displayed on the image. At the same time, the rigid structure of the tooling ensures that the industrial camera and the laser remain relatively stationary.

[0036] Furthermore, the installation diagram of the vehicle bottom vibration measuring device is as follows: Figure 3 As shown, the undercarriage vibration measurement devices are installed on both sides of the train's interior, at a 34° angle to the vertical axis of the train body and 280 mm from the train's centerline. A laser beam is emitted by the laser onto the rails, and an industrial camera captures a clear and complete image of the laser beam. It should be noted that the above installation diagram is only one embodiment of the present invention, and the angles and dimensions shown in the figure are for illustrative purposes only and are not intended to be limiting.

[0037] In this embodiment, the method of calibrating the structured light system includes: calculating the intrinsic parameters of the industrial camera and its rotation and translation matrix with the laser plane; and calculating the corresponding three-dimensional coordinates in the camera coordinate system through the pixel position of the laser point.

[0038] Specifically, the calibration results of industrial cameras and lasers are as follows:

[0039] (1) Industrial camera internal reference: K;

[0040] (2) The formula of the laser plane in the camera coordinate system:

[0041] ax+by+cz+d=0; (Formula 1)

[0042] Among them, x, y, z are the three-dimensional point coordinates in the camera coordinate system, and a, b, c, d are the laser plane coefficients.

[0043] It should be noted that the internal parameter K of industrial cameras includes a total of 6 parameters as follows: f, k, Sx, Sy, Cx, Cy; among them, f represents the focal length; k represents the magnitude of radial distortion, a negative value of k indicates barrel distortion, and a positive value of k indicates pincushion distortion; Sx and Sy are scaling factors; Cx and Cy are the principal points of the image, that is, the intersection of the lens axis perpendicular to the imaging plane and the image plane.

[0044] Step S12: Obtain a rail image captured by the calibrated image acquisition device, locate the laser lines in the rail image using a visual algorithm, summarize the number of laser lines to be identified, and sort the contours of all laser lines in descending order according to the degree of shape feature matching.

[0045] In this embodiment, the specific implementation process of step S12 is as follows:

[0046] Step S121: pre-processing the rail image, which includes: filtering the laser lines in the rail system that are not bright enough and / or have too small a pixel area using binarization and corrosion operations.

[0047] It should be noted that binarization refers to converting an image into values ​​between 0 and 1. An image consists of a target object, background, and noise. To directly extract the target object from a multi-valued digital image, a global threshold T must be set. This threshold divides the image data into two parts: a group of pixels with values ​​greater than T and a group of pixels with values ​​less than T. The pixel values ​​in the group with values ​​greater than T are set to white (or black), while the pixel values ​​in the group with values ​​less than T are set to black (or white). Erosion generally operates on binary images, meaning they have only two values: 0 and 1; 0 represents black and 1 represents white. Erosion targets the foreground color of the image, meaning those pixels with a value of 1. During the erosion process, a convolution kernel is used to traverse each pixel in the original image. When a pixel is reached, if all surrounding pixels within the convolution kernel are white, the pixel's color remains unchanged (i.e., remains 1, white). If a black point exists within the convolution kernel's range, the pixel is set to black.

[0048] Step S122: extracting the contour of the laser line in the rail image.

[0049] Optionally, a contour extraction method of hollowing out internal points can be used to extract the contour of the laser line in the rail image. The process includes: binarizing the rail image; if the target pixel in the image is black and the eight pixels adjacent to it are not black, then the target pixel is deleted (set to white); and each pixel that is removed is traversed to obtain a new target image.

[0050] Optionally, a boundary tracking method can be used to extract the contour of the laser line in the rail image. The process includes: binarizing the rail image; traversing each pixel point, selecting the pixel point at the lower left of the object as the starting pixel point, and the pixel value of the starting pixel point is 0; when the starting pixel point is found, the direction is recorded, and the next pixel point is found along the scanning direction; the cycle continues until the starting point is found again.

[0051] Step S123: performing shape feature extraction on the extracted laser line profile, performing similarity comparison with preset shape features, and arranging the similarity comparison results in descending order.

[0052] Specifically, the shape features of the laser line profile are extracted by extracting Hu moment features. The Euclidean distance between the extracted Hu moment features and the preset Hu moment features is calculated to determine their similarity to the preset rail head shape. It should be understood that the Hu moment of an image is an image feature that is invariant to translation, rotation, and scale.

[0053] Step S13: Repeat the above steps until a contour is detected in the current frame.

[0054] Specifically, it is determined whether any contour is detected in the current frame; if no contour is detected in the current frame, jump to the next frame and continue to execute step S12; if a contour is detected in the current frame, jump to the next step and execute.

[0055] Step S14: If the current frame is the initial frame or there is no matching contour in the previous frame, the contour with the largest shape feature matching degree is selected as the initial position of the target laser line, and the next frame is jumped to and the steps after the structured light system calibration are re-executed.

[0056] Step S15: If there is a matched contour in the previous frame, the candidate contours are traversed from large to small according to the shape feature matching degree.

[0057] Step S16: If the pixel deviation of the candidate contour found in the picture with the matched contour of the previous frame is less than the preset threshold, the displacement between the train and the track in the vertical direction and the lateral direction of the train is calculated based on the pixel deviation as a compensation value for the contact network geometric parameters; otherwise, jump to the next frame and re-execute the steps after the structured light system calibration.

[0058] In this embodiment, the displacement between the train and the track in the vertical direction and the lateral direction of the train is calculated based on pixel deviation as a compensation value for the contact network geometric parameters, which includes: projecting the pixel offset value of the current frame contour and the matched contour of the previous frame into the camera coordinate system to calculate the corresponding three-dimensional offset value; calculating the corresponding rotation matrix according to the installation position and angle of the camera coordinate system on the train; and calculating the displacement between the train and the track in the vertical direction and the lateral direction of the train based on the rotation matrix as a compensation value for the height guide value and pull-out value in the contact network geometric parameters.

[0059] More specifically, the calculation process of the compensation value of the contact network geometric parameters includes:

[0060] Step S161: define the pixel coordinates of the center point of the matched contour in the previous frame as (u1, v1); define the pixel coordinates of the center point of the matched contour in the current frame as (u2, v2).

[0061] Step S162: Map the coordinates of each pixel to the camera coordinate system using the camera calibration result, as follows:

[0062]

[0063] s=-d / (M[1]*a+M[2]*b+M[3]*c); (Formula 3)

[0064]

[0065] Among them, M is the projection matrix, M is a 3*1 matrix, M[1] represents the first element of the matrix, M[2] represents the second element of the matrix, and M[3] represents the third element of the matrix; K is the internal parameter of the industrial camera, K -1 is the inverse matrix of K; s is the depth coefficient calculated based on the laser plane, a, b, c, d are the laser plane coefficients; X c ,Y c ,Z c is the camera coordinate after depth information correction; respectively, (u1, v1) and (u2, v2) are substituted into the above formula to obtain the corresponding camera coordinates (X c1 ,Y c1 ,Z c1 ), (X c2 ,Y c2 ,Z c2 ).

[0066] Step S163: The camera coordinates corresponding to each pixel coordinate in the camera coordinate system are converted to the train world coordinate system according to the module and position to obtain the corresponding world coordinates. The specific process is as follows:

[0067]

[0068]

[0069] Among them, R is the rotation matrix from the camera coordinate system to the train world coordinate system, I is the unit matrix, θ is the installation angle, which is actually 34°; r x , r y , r z is the component of the unit vector r in all directions. In fact, the camera coordinate system and the train coordinate system are equivalent to rotating around the z axis, that is, the vertical axis of the train, so r x =0, r y =0, r z =1; respectively (X c1 ,Y c1 ,Z c1 ), (X c2 ,Y c2 ,Z c2 ) into the above formula to get the corresponding camera coordinates (X w1 ,Y w1,Z w1 ), (X w2 ,Y w2 ,Z w2 ).

[0070] Step S164: Based on the world coordinates of the center point pixel of the matched contour in the previous frame and the center point pixel of the matched contour in the current frame, subtract the Z coordinates of the two world coordinates to obtain a vertical vibration measurement value as a guide height compensation value, and subtract the X coordinates of the two world coordinates to obtain a horizontal vibration measurement value as a pull-out compensation value.

[0071] Specifically, the world coordinates of the center point pixel of the matched contour in the previous frame are (X w1 ,Y w1 ,Z w1 ), the world coordinates of the center point pixel of the current frame matching contour are (X w2 ,Y w2 ,Z w2 ). Calculate (Z w2 -Z w1 ) is the vertical vibration measurement value, which is the guide height compensation value; (X w2 -X w1 ) is the horizontal vibration measurement value, which is the pull-out compensation value.

[0072] In this embodiment, in order to improve the stability and accuracy of the calculation results, vibration measurement devices are preferably installed on both sides of the train, and the abnormal displacement values ​​are filtered or averaged by comparing with the compensation values ​​obtained above.

[0073] For the convenience of understanding by those skilled in the art, Figure 4 The method flow in one embodiment is further explained to illustrate the vehicle bottom vibration measurement method based on the structured light system provided in an embodiment of the present invention:

[0074] Step 1: Install the vehicle bottom vibration measurement device; place the measurement device on both sides of the moving train to perform real-time image acquisition and analysis.

[0075] Step 2: Calibration initialization. For the calibration method and process of industrial cameras, please refer to the above content.

[0076] Step 3: Collect rail images.

[0077] Step 4: Image preprocessing. The image preprocessing method and process can refer to the above content.

[0078] Step 5: Determine whether a contour is detected. If yes, jump to step 6, otherwise go back to step 3.

[0079] Step 6: Check if there is a matching contour. If yes, jump to step 7, otherwise jump to step 8.

[0080] Step 7: Traverse the candidate contours from large to small according to the shape feature matching degree, and jump to step 9.

[0081] Step 8: Match the largest contour as the initial match and return to step 3.

[0082] Step 9: Determine whether there is a contour with a pixel deviation less than the threshold value from the matched contour? If so, jump to step 10, otherwise return to step 3.

[0083] Step 10: Calculate the compensation value. The calculation method and process of the compensation value can refer to the above content.

[0084] In summary, the vehicle bottom vibration measurement method based on the structured light system provided in the embodiment of the present invention establishes a mapping relationship between two-dimensional laser points and three-dimensional space by calibrating the relative position relationship between the camera and the laser plane, and accurately measures the relative displacement of the train and the track in real time. It also uses real-time calibration through a tracking and matching algorithm to achieve compensation for geometric parameters, thus solving the problem of large cumulative errors and inability to calibrate in current train vibration measurement methods.

[0085] The vehicle bottom vibration measurement method based on the structured light system provided in the embodiment of the present invention can be implemented on the terminal side or the server side. As for the hardware structure of the vehicle bottom vibration measurement terminal based on the structured light system, please refer to Figure 5 , which is an optional hardware structure diagram of a computer device 500 based on a structured light system provided in an embodiment of the present invention. The device 500 may be a mobile phone, a computer device, a tablet device, a personal digital processing device, a factory background processing device, etc. The vehicle bottom vibration measurement terminal 500 based on a structured light system includes: at least one processor 501, a memory 502, at least one network interface 504 and a user interface 506. The various components in the device are coupled together through a bus system 505. It can be understood that the bus system 505 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 505 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, Figure 5 In the text, various buses are labeled as bus systems.

[0086] The user interface 506 may include a display, a keyboard, a mouse, a trackball, a click gun, keys, buttons, a touch pad or a touch screen.

[0087] It will be appreciated that the memory 502 may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM) or a programmable read-only memory (PROM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM) and synchronous static random access memory (SSRAM). The memory described in the embodiments of the present invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0088] The memory 502 in the embodiment of the present invention is used to store various categories of data to support the operation of the vehicle bottom vibration measurement terminal 500 based on the structured light system. Examples of these data include: any executable program for operating on the vehicle bottom vibration measurement terminal 500 based on the structured light system, such as an operating system 5021 and an application 5022; the operating system 5021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application 5022 can include various applications, such as a media player (MediaPlayer), a browser (Browser), etc., for implementing various application services. The vehicle bottom vibration measurement method based on the structured light system provided in the embodiment of the present invention can be included in the application 5022.

[0089] The methods disclosed in the above embodiments of the present invention can be applied to or implemented by processor 501. Processor 501 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in processor 501 or by software instructions. The above processor 501 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 501 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor 501 may be a microprocessor or any conventional processor. The steps of the accessory optimization method provided in conjunction with the embodiments of the present invention can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium located in a memory. The processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0090] In an exemplary embodiment, the vehicle bottom vibration measurement terminal 500 based on the structured light system can be used by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), and complex programmable logic devices (CPLDs) to execute the aforementioned method.

[0091] The present invention also provides a vehicle bottom vibration measuring device, the structure of which can refer to Figure 2 Schematic diagram of the device structure shown. The vehicle bottom vibration measurement device in this embodiment is installed on both sides of a moving train and includes: a laser emitting unit for emitting a laser beam toward a target rail; an image acquisition unit for capturing images of the target rail; wherein the image acquisition unit is externally connected to a control device; the control device receives the rail images captured by the image acquisition unit and executes the vehicle bottom vibration measurement method based on the structured light system described above.

[0092] It should be noted that the implementation of the vehicle bottom vibration measurement device provided in the embodiment of the present invention is similar to the vehicle bottom vibration measurement method based on the structured light system mentioned above, so it will not be described in detail.

[0093] like Figure 6Figure 1 shows a schematic diagram of the structure of a vehicle bottom vibration measurement system according to one embodiment of the present invention. In this embodiment, the vehicle bottom vibration measurement system includes a pair of vehicle bottom vibration measurement devices 61 mounted on a moving train, and a control device 62 in communication with the vehicle bottom vibration devices. The control device 62 receives rail images captured by the image acquisition units of the vehicle bottom vibration measurement devices 61 and then executes the vehicle bottom vibration measurement method based on the structured light system.

[0094] It should be noted that the implementation of the vehicle bottom vibration measurement system provided in the embodiment of the present invention is similar to the vehicle bottom vibration measurement method based on the structured light system mentioned above, so it will not be described in detail.

[0095] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with a computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When executed, the program performs the steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0096] In the embodiments provided herein, the computer readable and writable storage medium may include a read-only memory, a random access memory, an EEPROM, a CD-ROM or other optical disk storage device, a magnetic disk storage device or other magnetic storage device, a flash memory, a USB flash drive, a mobile hard disk, or any other medium that can be used to store desired program code in the form of instructions or data structures and can be accessed by a computer. In addition, any connection can be appropriately referred to as a computer readable medium. For example, if the instruction is sent from a website, a server or other remote source using a coaxial cable, a fiber optic cable, a twisted pair, a digital subscriber line (DSL) or wireless technologies such as infrared, radio and microwaves, the coaxial cable, fiber optic cable, twisted pair, DSL or wireless technologies such as infrared, radio and microwaves are included in the definition of the medium. However, it should be understood that computer readable and writable storage media and data storage media do not include connections, carriers, signals or other temporary media, but are intended to be non-temporary, tangible storage media. Disk and disc, as used in this application, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers.

[0097] In summary, this application provides a method, device, medium, and equipment for measuring underbody vibration based on a structured light system. By calibrating the relative positional relationship between the camera and the laser plane, the present invention establishes a mapping relationship between two-dimensional laser points and three-dimensional space, accurately measuring the relative displacement of the train and track in real time. This method also uses a tracking and matching algorithm for real-time calibration, achieving compensation for geometric parameters. This solves the problem of large cumulative errors and inability to calibrate existing train vibration measurement methods. Therefore, this application effectively overcomes the various shortcomings of the existing technology and has high industrial application value.

[0098] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical concepts disclosed in this application shall be covered by the claims of this application.

Claims

1. A method for measuring vehicle bottom vibration based on a structured light system, characterized in that: include: Calibrate the structured light system; The structured light system includes an image acquisition device and a laser; Obtain rail images captured by a calibrated image acquisition device, locate laser lines in the rail images using a visual algorithm, summarize the number of laser lines to be identified, and sort the contours of all laser lines in descending order of shape feature matching; Repeat the above steps until the contour is detected in the current frame; If the current frame is the initial frame or there is no matching contour in the previous frame, the contour with the largest shape feature matching degree is selected as the initial position of the target laser line, and the next frame is jumped to and the steps after the structured light system calibration are re-executed; If there is a matched contour in the previous frame, the candidate contours are traversed from large to small according to the shape feature matching degree; If the pixel deviation of the candidate contours found in the image with the contour matched in the previous frame is less than the preset threshold, the displacement between the train and the track in the vertical direction and the lateral direction of the train is calculated based on the pixel deviation to serve as the compensation value of the contact network geometric parameters; otherwise, jump to the next frame and re-execute the steps after the structured light system calibration; The pixel deviation-based calculation of the displacement between the train and the track in the vertical direction and the lateral direction of the train as compensation values ​​for the contact network geometric parameters includes: projecting the pixel offset values ​​of the current frame contour and the matched contour of the previous frame into the camera coordinate system to calculate the corresponding three-dimensional offset values; calculating the corresponding rotation matrix according to the installation position and angle of the camera coordinate system on the train; and calculating the displacement between the train and the track in the vertical direction and the lateral direction of the train based on the rotation matrix as compensation values ​​for the height guide value and the pull-out value in the contact network geometric parameters. The calculation process of the compensation value of the contact network geometric parameter includes: defining the pixel coordinates of the center point of the matched contour in the previous frame and the pixel coordinates of the center point of the matched contour in the current frame; mapping each pixel coordinate to the camera coordinate system through the camera calibration result; converting the camera coordinates corresponding to each pixel coordinate in the camera coordinate system to the train world coordinate system according to the module and position to obtain the corresponding world coordinates; according to the world coordinates of the center point pixel of the matched contour in the previous frame and the center point pixel of the matched contour in the current frame, subtracting the Z coordinates of the two world coordinates to obtain a vertical vibration measurement value as a guide height compensation value, and subtracting the X coordinates of the two world coordinates to obtain a horizontal vibration measurement value as a pull-out compensation value.

2. The vehicle bottom vibration measurement method based on the structured light system according to claim 1, characterized in that: The results of calibrating the structured light system include: Get the intrinsic parameter K of the industrial camera; The expression of the laser plane in the camera coordinate system is obtained: ax+by+cz+d=0; where x, y, and z are the three-dimensional coordinates of the point in the camera coordinate system, and a, b, c, and d are the laser plane coefficients.

3. The vehicle bottom vibration measurement method based on the structured light system according to claim 1, characterized in that: The method of locating the laser lines in the rail image using a visual algorithm and summing up the number of laser lines to be identified, and sorting the contours of all laser lines in descending order according to the degree of shape feature matching, includes: Preprocessing the rail image includes: filtering laser lines in the rail system that are not bright enough and / or have too small a pixel area using binarization and erosion operations; Extract the contours of the laser lines in the rail images; The extracted laser line profile is subjected to shape feature extraction and similarity comparison with the preset shape features, and the similarity comparison results are arranged in descending order.

4. The vehicle bottom vibration measurement method based on the structured light system according to claim 3, characterized in that: The method of extracting shape features of the extracted laser line profile and performing similarity comparison with preset shape features, and arranging the similarity comparison results in descending order, includes: extracting the shape features of the laser line profile by extracting Hu moment features, calculating the Euclidean distance between the extracted Hu moment features and the preset Hu moment features, and calculating the similarity between the extracted Hu moment features and the preset Hu moment features to calculate the similarity with the preset rail head shape.

5. A vehicle bottom vibration measuring device, characterized in that: Installed on both sides of the running train; the device includes: a laser emitting unit, for emitting a laser beam toward a target rail; An image acquisition unit, used for acquiring images of the target rail; The image acquisition unit is externally connected to a control device; the control device executes the vehicle bottom vibration measurement method based on the structured light system according to any one of claims 1 to 4 after receiving the rail image acquired by the image acquisition unit.

6. A vehicle bottom vibration measurement system, characterized in that: include: At least one pair of vehicle bottom vibration measuring devices as claimed in claim 5 installed on a moving train; A control device establishes a communication connection with the image acquisition unit in the vehicle bottom vibration measuring device to execute the vehicle bottom vibration measuring method based on the structured light system according to any one of claims 1 to 4 after receiving the rail image acquired by the image acquisition unit.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the vehicle bottom vibration measurement method based on a structured light system according to any one of claims 1 to 4 is implemented.

8. A computer device, characterized in that: include: processor and memory; The memory is used to store computer programs; The processor is configured to execute the computer program stored in the memory, so as to enable the computer device to execute the vehicle bottom vibration measurement method based on the structured light system according to any one of claims 1 to 4.

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