Non-contact railway track measurement system and method based on multi-source data

Abstract

The invention discloses a non-contact railway track measurement system and method based on multi-source data, a data acquisition end comprises a laser measurement device and an image acquisition device, the laser measurement device continuously emits laser beams to a to-be-measured part so as to acquire surface profile data of the to-be-measured part, and the image acquisition device acquires the surface profile data of the to-be-measured part; the image acquisition equipment shoots an image of the to-be-detected part at a set frequency; the data processing end is in communication connection with the data acquisition end and is used for regulating and controlling the laser measurement equipment and the image acquisition equipment to work synchronously and cooperatively and processing and analyzing data acquired by the data acquisition end so as to obtain geometric parameter measurement values, overrun conditions, wear deformation positions and degrees of the to-be-measured part; according to the invention, synchronous acquisition and storage of laser measurement data and image data are ensured, a reliable data source is provided for subsequent analysis, and information such as track geometric parameter measurement values, over-limit conditions, wear deformation positions and degrees and the like is clearly presented in various forms such as charts, reports and the like.

Description

Technical Field

[0001] This invention relates to the field of track measurement technology, and specifically to a non-contact railway track measurement system and method based on multi-source data. Background Technology

[0002] Existing non-contact railway track measurement systems mainly consist of three parts: a data acquisition system, an STM32 main control system, and a LabVIEW human-computer interaction system. The data acquisition system comprises a measuring device, a drive motor, and a corresponding laser displacement sensor.

[0003] The working principle of this measurement system is as follows: First, the test process is pre-set and the corresponding program is written. The main controller drives the motor to rotate according to the predetermined program and drives the sensor mounting bracket to achieve the predetermined process. During this period, the high-precision laser displacement sensor on the mounting bracket continuously collects the surface dimension data of the workpiece being tested. Second, the collected data is transmitted to the computer through the corresponding interface. The test software analyzes and processes the data through a certain algorithm to obtain the cylindricity error of the tested part and displays it on the display interface, automatically determining whether the cylindricity error of the tested workpiece meets the standard. Finally, the test data management, storage, and query functions are developed using LabVIEW software to facilitate the management and retrieval of the test data.

[0004] The existing non-contact railway track measurement systems still have the following shortcomings: (1) Problems of efficient data acquisition and synchronization: In traditional track detection, there are problems of asynchronous and inefficient acquisition of laser measurement data and image data, which leads to analysis errors and information loss.

[0005] (2) Bottleneck in complex data processing and analysis: Existing track detection data has large noise interference, difficult coordinate system, and complex feature extraction, which makes further prediction and analysis more difficult.

[0006] (3) Insufficient intuitive presentation of test results and lack of decision support: The existing test results are not intuitive and are difficult to guide operation and maintenance decisions.

[0007] (4) System integration and cross-device collaboration issues: The integration between existing laser measurement equipment, image acquisition equipment and data processing systems is low. Summary of the Invention

[0008] The purpose of this invention is to provide a non-contact railway track measurement system and method based on multi-source data, in order to solve the technical problems in the existing track inspection technology, such as the asynchronous and inefficient acquisition of laser measurement data and image data, as well as the lack of intuitive display of existing inspection results and difficulty in guiding operation and maintenance decisions.

[0009] To solve the above-mentioned technical problems, the present invention specifically provides the following technical solution: A non-contact railway track measurement system based on multi-source data includes: The data acquisition end includes a laser measuring device and an image acquisition device. The laser measuring device continuously emits a laser beam toward the part under test to acquire the surface contour data of the part under test. The image acquisition device captures images of the part under test at a set frequency. The data processing end is communicatively connected to the data acquisition end and is used to control the synchronous and coordinated operation of the laser measurement device and the image acquisition device. At the same time, it processes and analyzes the data acquired by the data acquisition end to obtain the geometric parameter measurement values, out-of-limit conditions, wear and deformation location and degree of the part under test.

[0010] In a preferred embodiment of the present invention, the data processing terminal includes a main control system and a human-computer interaction system communicatively connected to the main control system, wherein the main control system is communicatively connected to the data acquisition terminal; The human-computer interaction system is used to send a start command to the main control system. After receiving the start command, the main control system triggers the data acquisition terminal to start data acquisition. The data acquisition terminal sends the collected information to the main control system, which processes and analyzes the information collected by the data acquisition terminal and finally displays the measurement results on the display interface of the human-computer interaction system.

[0011] As a preferred embodiment of the present invention, the human-computer interaction system is used to configure the equipment parameters of the laser measurement device and the image acquisition device, and to achieve precise control of the acquisition frequency and trigger mode, so as to realize the synchronous acquisition and storage of laser measurement data and image data.

[0012] As a preferred embodiment of the present invention, the human-computer interaction system includes a data preprocessing module and a feature extraction and analysis module; The data preprocessing module processes the laser measurement data by calling the signal processing function library and using median filtering and mean filtering to remove random noise; The data preprocessing module uses a coordinate transformation algorithm to transform the coordinate system of the laser measurement data and the coordinate system of the image data to the standard coordinate system.

[0013] As a preferred embodiment of the present invention, the feature extraction and analysis module includes a mathematical analysis function library and a visual development unit; In this process, functions from the mathematical analysis function library are called to perform in-depth mining on the preprocessed data, and the track gauge, level, elevation, and track orientation geometric parameters of the track are accurately calculated from the laser measurement data. The calculated geometric parameters are then compared with the standard parameter thresholds to determine whether the track geometric parameters exceed the limits. The vision development unit processes the image data to identify the wear areas and crack defects of the track. Specifically, it uses edge detection and threshold segmentation algorithms to extract the contours of defects on the track surface, calculates the area and length of the defects, and combines machine learning algorithms to classify the defect types, thereby comprehensively assessing the wear and deformation of the track.

[0014] As a preferred embodiment of the present invention, the human-computer interaction system clearly presents the measured values ​​of track geometric parameters, over-limit conditions, and information on the location and degree of wear and deformation through charts and reports. Operators can view the test results in real time through the interface and generate detailed test reports as needed.

[0015] In addition, the present invention also provides a measurement method for a non-contact railway track measurement system based on multi-source data, comprising the following steps: A multi-source data synchronous acquisition system is constructed, and precise collaborative control of laser measurement equipment and image acquisition equipment is achieved through hardware triggering and software timestamp synchronization mechanisms; Using a signal processing and mathematical analysis function library, an adaptive filtering algorithm was developed to remove point cloud noise from multi-source data, and a coordinate transformation model was constructed to unify the coordinate system of multi-source data. Using image recognition and analysis functions, wear areas and crack defects in image data are identified, and track surface defects are identified based on defect features. Furthermore, the track gauge, level, elevation, and track alignment geometric parameters are accurately calculated from laser measurement data to determine whether the track geometric parameters exceed the limits. The system displays track geometry parameter measurements, out-of-limit conditions, wear and deformation location and extent information in the form of charts and reports, and generates detailed inspection reports.

[0016] As a preferred embodiment of the present invention, the human-computer interaction system adopts the LabVIEW human-computer interaction system. The LabVIEW human-computer interaction system configures the parameters of the laser measurement device and the image acquisition device through the data acquisition module so that the data acquisition threads of the laser measurement device and the image acquisition device are the same, thereby ensuring the synchronous acquisition and storage of laser measurement data and image data.

[0017] The laser measuring device continuously emits laser beams toward the track, and accurately collects track surface contour data based on the principle of triangulation. The image acquisition device is a high-resolution camera that captures orbital images at a set frequency.

[0018] As a preferred embodiment of the present invention, the detection data that can be obtained based on the detection data of the laser measuring device and the image acquisition device includes: The track's gauge, level, elevation, and alignment geometric parameters; the track's wear area and crack defect characteristics; and the quantitative indicators of the track's defects, such as area and length. The detection data is transformed into a 3D track model, parameter trend chart, and defect heat map; by embedding a railway operation and maintenance rule base, an intelligent decision-making module is built to automatically generate detection reports that include defect levels and maintenance priorities.

[0019] As a preferred embodiment of the present invention, the human-computer interaction system uploads the detection report formed by the detection results and maintenance plan to the railway operation and maintenance management platform to realize data sharing and collaborative operation, and provide comprehensive support for ensuring the safe operation of railway tracks.

[0020] Compared with the prior art, the present invention has the following advantages: This invention achieves precise control over key parameters such as acquisition frequency and trigger mode by flexibly configuring the parameters of laser sensors, cameras, and other equipment. Specifically, it establishes an efficient data acquisition thread to ensure the synchronous acquisition and storage of laser measurement data and image data, providing a reliable data source for subsequent analysis. Furthermore, it clearly presents information such as track geometric parameter measurements, over-limit situations, and the location and degree of wear and deformation through various forms such as charts and reports. Combined with railway operation and maintenance rules and historical data, it automatically generates scientific and reasonable track maintenance suggestions and plans, solving the problem of low integration between laser measurement equipment, image acquisition equipment, and data processing systems. Attached Figure Description

[0021] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0022] Figure 1 This is a structural block diagram of a non-contact railway track measurement system according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating the non-contact railway track measurement method according to an embodiment of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] like Figure 1 As shown, the present invention provides a non-contact measurement system for railway track based on multi-source data, including a data acquisition end and a data processing end.

[0025] The data acquisition end includes a laser measuring device and an image acquisition device. The laser measuring device continuously emits a laser beam toward the part under test to acquire the surface contour data of the part under test, and the image acquisition device captures images of the part under test at a set frequency. The data processing end is connected to the data acquisition end for controlling the synchronous and coordinated operation of the laser measurement equipment and the image acquisition equipment. At the same time, it processes and analyzes the data acquired by the data acquisition end to obtain the geometric parameter measurement values, out-of-limit conditions, and the location and degree of wear and deformation of the part under test.

[0026] The data processing end includes a main control system and a human-machine interface system that communicates with the main control system. The main control system also communicates with the data acquisition end.

[0027] The human-computer interaction system is used to send a start command to the main control system. After receiving the start command, the main control system triggers the data acquisition terminal to start data acquisition.

[0028] The data acquisition terminal sends the collected information to the main control system, which processes and analyzes the information collected by the data acquisition terminal and finally displays the measurement results on the human-computer interaction system's display interface.

[0029] The human-computer interaction system is used to configure the equipment parameters of the laser measurement equipment and the image acquisition equipment, and to achieve precise control of the acquisition frequency and trigger mode, so as to realize the synchronous acquisition and storage of laser measurement data and image data.

[0030] In traditional track inspection, the acquisition of laser measurement data and image data is asynchronous and inefficient, leading to analysis errors and information loss. However, the laser measurement device and image acquisition device in this embodiment can work together. The laser measurement device continuously emits a laser beam to the track through a laser emitter and accurately acquires the track surface contour data based on the principle of triangulation. The image acquisition device captures track images at a set frequency using a high-resolution camera.

[0031] By flexibly configuring the parameters of laser sensors, cameras, and other equipment, precise control over key parameters such as acquisition frequency and trigger mode can be achieved. In other words, by establishing an efficient data acquisition thread, the synchronous acquisition and storage of laser measurement data and image data can be ensured, providing a reliable data source for subsequent analysis.

[0032] The human-computer interaction system includes a data preprocessing module and a feature extraction and analysis module. The data preprocessing module processes the laser measurement data by calling the signal processing function library and using median filtering and mean filtering to remove random noise; the data preprocessing module also uses a coordinate transformation algorithm to transform the coordinate system of the laser measurement data and the coordinate system of the image data to the standard coordinate system.

[0033] The feature extraction and analysis module includes a mathematical analysis function library and a vision development unit. Specifically, by calling functions from the mathematical analysis function library, it performs in-depth mining of the preprocessed data, accurately calculating the track gauge, level, elevation, and alignment geometric parameters from the laser measurement data. The calculated geometric parameters are then compared with standard parameter thresholds to determine if the track geometric parameters exceed the limits.

[0034] The visual development unit processes the image data to identify the wear areas and crack defects of the track. Specifically, edge detection and threshold segmentation algorithms are used to extract the contours of defects on the track surface, calculate the area and length of the defects, and classify the defect types using machine learning algorithms, thereby comprehensively assessing the wear and deformation of the track.

[0035] The human-computer interaction system clearly presents the measured values ​​of track geometric parameters, over-limit situations, and information on the location and degree of wear and deformation through charts and reports. Operators can view the test results in real time through the interface and generate detailed test reports as needed.

[0036] In order to integrate laser measurement data and image acquisition data, this embodiment first performs filtering and noise reduction operations on the laser measurement data and image acquisition data. For example, median filtering, mean filtering and other algorithms are used to process the laser measurement data to effectively remove random noise. Then, the data in different coordinate systems are uniformly converted to the standard orbital coordinate system.

[0037] Then, the preprocessed data undergoes in-depth analysis. On one hand, the track's geometric parameters, such as gauge, level, elevation, and orientation, are precisely calculated from the laser measurement data. By comparing these parameters with standard parameters and setting thresholds, it is determined whether the track's geometric parameters exceed the limits. On the other hand, LabVIEW's image recognition and analysis capabilities are used to process the track images and identify defects such as wear areas and cracks. For example, edge detection and threshold segmentation algorithms are used to extract the contours of defects on the track surface, calculate quantitative indicators such as the area and length of defects, and combine machine learning algorithms to classify defect types, thereby comprehensively assessing the track's wear and deformation.

[0038] Finally, information such as track geometric parameter measurements, out-of-limit conditions, and the location and extent of wear and deformation are clearly presented through various formats including charts and reports. Operators can view the inspection results in real time through the interface and generate detailed inspection reports as needed.

[0039] In addition, such as Figure 2 As shown, the present invention also provides a measurement method for a non-contact railway track measurement system based on multi-source data, comprising the following steps: A multi-source data synchronous acquisition system was constructed, which uses hardware triggering and software timestamp synchronization mechanisms to achieve precise collaborative control of laser measurement equipment and image acquisition equipment, overcome the challenge of sub-millisecond synchronous acquisition of laser ranging data and orbit images, and build a highly stable data acquisition platform.

[0040] Using signal processing and mathematical analysis function libraries, we developed an adaptive filtering algorithm to remove point cloud noise from multi-source data and constructed a coordinate transformation model to unify the coordinate system of multi-source data.

[0041] By utilizing image recognition and analysis functions, wear areas and crack defects in image data are identified, and track surface defects are identified based on these defects. Furthermore, the track gauge, level, elevation, and alignment geometric parameters are accurately calculated from laser measurement data to determine whether the track geometric parameters exceed limits. By combining track geometric parameter calculation with image recognition algorithms, the automatic extraction of parameters such as track gauge and level, as well as the accurate identification of track surface defects, are achieved.

[0042] The system displays track geometry parameter measurements, out-of-limit conditions, wear and deformation location and extent information in the form of charts and reports, and generates detailed inspection reports.

[0043] The human-computer interaction system adopts the LabVIEW human-computer interaction system. The LabVIEW human-computer interaction system configures the parameters of the laser measurement device and the image acquisition device through the data acquisition module so that the data acquisition threads of the laser measurement device and the image acquisition device are the same, ensuring the synchronous acquisition and storage of laser measurement data and image data.

[0044] The laser measuring equipment continuously emits laser beams toward the track, accurately collecting track surface contour data based on the principle of triangulation. The image acquisition device is a high-resolution camera that captures orbital images at a set frequency.

[0045] Based on the detection data from laser measurement equipment and image acquisition equipment, the detection data that can be obtained includes: The track's gauge, level, elevation, and alignment geometric parameters; the track's wear area and crack defect characteristics; and the quantitative indicators of the track's defects, such as area and length. The detection data is transformed into a 3D track model, parameter trend chart, and defect heat map; by embedding a railway operation and maintenance rule base, an intelligent decision-making module is built to automatically generate detection reports that include defect levels and maintenance priorities.

[0046] The human-computer interaction system uploads the inspection reports generated from the inspection results and maintenance plans to the railway operation and maintenance management platform, enabling data sharing and collaborative operations, and providing comprehensive support for ensuring the safe operation of railway tracks.

[0047] This implementation utilizes LabVIEW's modular programming features to encapsulate laser measurement, data processing, visualization, and other functions into independent modules. Through standardized interfaces, it achieves seamless integration between the equipment and the system, supports flexible adjustment of the detection scheme according to different railway scenarios (conventional speed, high-speed rail, and subway), and improves system adaptability and scalability.

[0048] The above embodiments are merely exemplary embodiments of this application and are not intended to limit this application. The scope of protection of this application is defined by the claims. Those skilled in the art can make various modifications or equivalent substitutions to this application within its substance and scope of protection, and such modifications or equivalent substitutions should also be considered to fall within the scope of protection of this application.

Claims

1. A non-contact railway track measurement system based on multi-source data, characterized in that, include: The data acquisition end includes a laser measuring device and an image acquisition device. The laser measuring device continuously emits a laser beam toward the part under test to acquire the surface contour data of the part under test. The image acquisition device captures images of the part under test at a set frequency. The data processing end is communicatively connected to the data acquisition end and is used to control the synchronous and coordinated operation of the laser measurement device and the image acquisition device. At the same time, it processes and analyzes the data acquired by the data acquisition end to obtain the geometric parameter measurement values, out-of-limit conditions, wear and deformation location and degree of the part under test.

2. The non-contact railway track measurement system based on multi-source data according to claim 1, characterized in that, The data processing terminal includes a main control system and a human-computer interaction system that is communicatively connected to the main control system. The main control system is communicatively connected to the data acquisition terminal. The human-computer interaction system is used to send a start command to the main control system. After receiving the start command, the main control system triggers the data acquisition terminal to start data acquisition. The data acquisition terminal sends the collected information to the main control system, which processes and analyzes the information collected by the data acquisition terminal and finally displays the measurement results on the display interface of the human-computer interaction system.

3. The non-contact railway track measurement system based on multi-source data according to claim 2, characterized in that, The human-computer interaction system is used to configure the equipment parameters of the laser measurement device and the image acquisition device, and to achieve precise control of the acquisition frequency and trigger mode, so as to realize the synchronous acquisition and storage of laser measurement data and image data.

4. The non-contact railway track measurement system based on multi-source data according to claim 3, characterized in that, The human-computer interaction system includes a data preprocessing module and a feature extraction and analysis module; The data preprocessing module processes the laser measurement data by calling the signal processing function library and using median filtering and mean filtering to remove random noise; The data preprocessing module uses a coordinate transformation algorithm to transform the coordinate system of the laser measurement data and the coordinate system of the image data to the standard coordinate system.

5. A non-contact railway track measurement system based on multi-source data according to claim 4, characterized in that, The feature extraction and analysis module includes a mathematical analysis function library and a visual development unit; In this process, functions from the mathematical analysis function library are called to perform in-depth mining on the preprocessed data, and the track gauge, level, elevation, and track orientation geometric parameters of the track are accurately calculated from the laser measurement data. The calculated geometric parameters are then compared with the standard parameter thresholds to determine whether the track geometric parameters exceed the limits. The vision development unit processes the image data to identify the wear areas and crack defects of the track. Specifically, it uses edge detection and threshold segmentation algorithms to extract the contours of defects on the track surface, calculates the area and length of the defects, and combines machine learning algorithms to classify the defect types, thereby comprehensively assessing the wear and deformation of the track.

6. A non-contact railway track measurement system based on multi-source data according to claim 5, characterized in that, The human-computer interaction system clearly presents the measured values ​​of track geometric parameters, over-limit situations, and information on the location and degree of wear and deformation through charts and reports. Operators can view the test results in real time through the interface and generate detailed test reports as needed.

7. A measurement method for the non-contact measurement system for the cylindricity error of large rotating parts according to any one of claims 1-6, characterized in that, Includes the following steps: A multi-source data synchronous acquisition system is constructed, and precise collaborative control of laser measurement equipment and image acquisition equipment is achieved through hardware triggering and software timestamp synchronization mechanisms; Using a signal processing and mathematical analysis function library, an adaptive filtering algorithm was developed to remove point cloud noise from multi-source data, and a coordinate transformation model was constructed to unify the coordinate system of multi-source data. Using image recognition and analysis functions, wear areas and crack defects in image data are identified, and track surface defects are identified based on defect features. Furthermore, the track gauge, level, elevation, and track alignment geometric parameters are accurately calculated from laser measurement data to determine whether the track geometric parameters exceed the limits. The system displays track geometry parameter measurements, out-of-limit conditions, wear and deformation location and extent information in the form of charts and reports, and generates detailed inspection reports.

8. The measurement method according to claim 7, characterized in that, The human-computer interaction system adopts the LabVIEW human-computer interaction system. The LabVIEW human-computer interaction system configures the parameters of the laser measurement device and the image acquisition device through the data acquisition module so that the data acquisition threads of the laser measurement device and the image acquisition device are the same, ensuring the synchronous acquisition and storage of laser measurement data and image data. The laser measuring device continuously emits laser beams toward the track, and accurately collects track surface contour data based on the principle of triangulation. The image acquisition device is a high-resolution camera that captures orbital images at a set frequency.

9. The measurement method according to claim 7, characterized in that, Based on the detection data from the laser measurement device and the image acquisition device, the detection data that can be obtained includes: The track's gauge, level, elevation, and alignment geometric parameters; the track's wear area and crack defect characteristics; and the quantitative indicators of the track's defects, such as area and length. The detection data is transformed into a 3D track model, parameter trend chart, and defect heat map; by embedding a railway operation and maintenance rule base, an intelligent decision-making module is built to automatically generate detection reports that include defect levels and maintenance priorities.

10. The measurement method according to claim 7, characterized in that, The human-computer interaction system uploads the test results and maintenance plan-generated test reports to the railway operation and maintenance management platform, enabling data sharing and collaborative operations, and providing comprehensive support for ensuring the safe operation of railway tracks.

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