A method and system for quickly detecting the detachment of a highway sound barrier

Abstract

The present invention relates to the field of sound barrier detection technology, specifically a method and system for rapid detection of the detachment of a highway sound barrier screen, comprising the following steps: S1. The detection vehicle travels at a constant speed, starts and calibrates the laser displacement meter module, and obtains a correction value; S2. Continuously measures the distance between the sound barrier and the vehicle, and constructs a distance information model; S3. Preprocesses and identifies abnormalities in the data, and determines abnormal conditions of the sound barrier; S4. If the detachment or displacement of the sound barrier screen is detected to exceed a preset threshold, the abnormal information and its position are recorded; S5. Automatically analyzes the detection data and generates a sound barrier detection report. The advantages of the present invention are: efficient and automated detection of the service status of the sound barrier screen is achieved, and formatted data is effectively accumulated, providing a corresponding data basis for the detection, maintenance, and management of road and bridge sound barriers, and providing a strong guarantee for the safe maintenance of transportation infrastructure.

Description

Technical Field

[0001] The present invention relates to the technical field of sound barrier detection, in particular to a method and system for rapid detection of the detachment of a highway sound barrier screen, and in particular to a method and system for rapid detection of the detachment of a sound barrier screen based on a vehicle-mounted laser displacement meter. Background Art

[0002] Elevated roads and bridges in cities often have to pass through residential areas, where vehicle traffic noise has caused significant interference to residents' daily lives. In order to mitigate this impact, sound barriers have become an effective tool to reduce traffic noise. Taking Shanghai as an example, the total length of elevated bridges in the city that have installed sound barriers is close to 80 kilometers, and some of these sound barriers have been in use for more than 15 years. Over time, these barriers may become unstable due to corrosion or external forces, which will not only affect their sound insulation effect, but may also threaten public safety. At present, the inspection of elevated bridge sound barriers mainly relies on manual inspections and regular inspections, and the inspection contents include the appearance damage of the barriers, the spacing and verticality of the columns, and the quality of the welds.

[0003] Since viaducts usually cross rivers and roads and are located at high altitudes, traditional manual inspection methods require closing roads or using special equipment such as aerial platforms and bridge inspection vehicles for inspection, which not only affects the normal operation of traffic, but also requires a lot of manpower and material resources due to the large amount of engineering, making it difficult to achieve comprehensive coverage. In addition, the results of manual inspections may be affected by subjective judgments and are prone to omissions and errors. Currently, data management and analysis usually rely on paper reports or hard disk storage, which limits the effective integration and utilization of data.

[0004] Although there are some applications of digital bridge detection technologies, these technologies have not been developed specifically for the problem of sound barrier detection, so it is difficult to meet the needs of large-scale detection. Therefore, it is particularly important to design a fast detection device and method for highway sound barriers based on a vehicle-mounted laser displacement meter, which will help improve the automation level of detection, reduce the impact on traffic, and improve the efficiency and accuracy of detection. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a method and system for quickly detecting the detachment of a highway sound barrier screen, so as to solve the problems of low efficiency, high labor cost and limited detection accuracy in the existing sound barrier detection technology, realize real-time and accurate detection of the detachment of the sound barrier screen, and greatly improve the automation and efficiency of road and elevated bridge sound barrier detection.

[0006] In order to achieve the above purpose, a method for quickly detecting the detachment of a highway sound barrier is designed, and the method comprises the following steps: Step S1. The detection vehicle travels at a constant speed along the set sound barrier route and maintains a fixed parallel distance with the sound barrier to ensure the normal operation and accurate calibration of the laser displacement meter module. All laser displacement meters have pre-deducted the correction value caused by the curvature of the vehicle side. ; Step S2. While the inspection vehicle is driving slowly, the laser displacement meter module is used to continuously measure the distance between the sound barrier and the vehicle, and the position data of the sound barrier is collected in real time. The laser displacement meter module continuously measures the distance between the sound barrier screen and the inspection vehicle by emitting a laser beam and receiving the signal reflected from the surface of the sound barrier. , through continuous data collection, the laser displacement meter module constructs a distance information model of the screen surface of the sound barrier from the vehicle; step S3. The data acquisition and processing module receives the measurement data of the laser displacement meter, performs data preprocessing and abnormality identification, so as to automatically determine whether the sound barrier is detached, offset or other abnormal conditions occur. The step S3 includes: step S301: preprocessing the distance measurement data returned by the laser displacement meter, including removing abnormal values, filtering noise signals and data smoothing; wherein, the data error caused by the inability of the vehicle to maintain a fixed vehicle-screen distance and the curvature of the vehicle side is eliminated to generate a data set , data set D is a 5-column n A numeric matrix of rows, n Indicates the total number of points collected by a laser displacement meter. n is an integer, , T Indicates the total collection time. f Indicates the acquisition frequency, = , i =1~5 and i is an integer, where i =1, ; Gaussian filtering method is used to filter the original data sequence D Perform noise reduction to obtain a smoothed data sequence D ′={ d 1 ′ , d 2 ′ , d 3 ′ , d 4 ′ , d 5 ′}; Step S302: The pre-processed data are preliminarily analyzed using a clustering algorithm. The clustering algorithm is used to automatically divide the measurement data into different groups, identify the data sets that differ greatly from the standard values, and detect the detachment or significant displacement of the screen; Step S303: After the cluster analysis identifies the area where the screen is missing or detached, the system will remove these abnormal data from the subsequent analysis, apply the control chart method to the remaining data to evaluate the verticality of the screen, set the upper control limit UCL and the lower control limit LCL to identify the verticality deviation, and mark the abnormal area according to the data deviation; Step S304: After the abnormal situation is identified, the data acquisition and processing module records the relevant data of the abnormal state, including the specific location, deviation degree and related location information of each abnormal point; Step S4. If the detachment or displacement of the sound barrier screen is detected to exceed the preset threshold, the specific detection time is recorded, and a timestamp is generated to associate the corresponding sound barrier abnormal information and its location; Step S5. After the detection is completed, the detection data is automatically analyzed and a sound barrier detection report is generated, which includes the location and degree of the screen detachment, the area that needs further inspection and the recommended maintenance measures.

[0007] Preferably, the method for rapid detection of falling off of a highway sound barrier according to the present invention has other technical features, wherein the Gaussian filtering method in step S301 is: by smoothing each data point of the data set with the weighted average of the surrounding data, the Gaussian filtering uses a filter, and the smoothed data , the data According to the following formula:

[0008] ;

[0009] in: G ( x ) is the weight of the Gaussian filter, which depends on the relative position j and σ , The original data is located at t Time data The surrounding data, m is the radius of the filter; the weight of the filter G ( x ) is determined by a Gaussian distribution function, which is as follows:

[0010] ;

[0011] in, σ is the standard deviation, xIndicates the distance between the surrounding data points and the central data point. The surrounding data is determined by the window size of the filter. The window size is used to determine the range of neighboring data points of each data point when performing weighted averaging. The size of the window is determined by the standard deviation σ Determine that the Gaussian filter is one-dimensional and the window size is as follows: Window size = , ┌┐ indicates rounding up, which is used to make the window size an odd number.

[0012] Preferably, the method for rapid detection of highway sound barrier screen falling off of the present invention has other technical features, wherein the step S302 is as follows: first, the data set D ′={ d 1 ′ , d 2 ′ , d 3 ′ , d 4 ′ , d 5 ′} cluster analysis, where d i ′ Represents the distance data between the sound barrier and the detection vehicle after preprocessing; the grouping method of the clustering algorithm adopts the k-means clustering algorithm to group the data set D ' is divided into p clusters, each cluster represents the distance measurement value of the sound barrier in different states, and clustering optimization is achieved by minimizing the sum of squares of the distances within the cluster. The formula is as follows:

[0013] ;

[0014] in, J represents the objective function, which is used to measure the compactness of clustering or clustering error. Represents filtered data Middle q The denoised data points, Indicates q A collection of clusters, It is a cluster The average value of all points in the cluster is obtained; the data points that significantly deviate from the normal distance range are identified as possible screen missing locations through a clustering algorithm.

[0015] Preferably, the method for rapid detection of falling off of a highway sound barrier according to the present invention has other technical features, wherein the step S303 is specifically as follows: the control chart method is used to control the remaining data sets. use As a reference line to evaluate the verticality of the sound barrier screen, Represents the average vertical distance of the sound barrier in normal state. The upper control limit UCL and the lower control limit LCL are set to identify the verticality deviation. The calculation formulas of UCL and LCL are as follows:

[0016] ;

[0017] in, σ d is the vertical distance dataset The standard deviation of k is the control limit coefficient, by choosing k =3 The control probability is 99.73%; when a certain measurement value Beyond the control limit, that is > UCL or < LCL , it is judged as verticality abnormality and the area is marked.

[0018] Preferably, the method for rapid detection of detachment of highway sound barrier screens described in the present invention has other technical features, wherein step S4 specifically includes the following steps: step S401, when it is identified that the detachment or displacement of the sound barrier screen exceeds a preset threshold, automatically record the degree of displacement or detachment of the abnormal point, the relevant timestamp, and the information of the laser displacement meter measurement data; step S402, through the timestamp association method, in combination with the records of the positioning system, associate the location information with the detected abnormal situation, the location information includes the geographical coordinates of the abnormal point of the sound barrier and the specific route location of the detection vehicle; step S403, store the abnormal information of the marked position in association with the geographical location, and generate a comprehensive abnormal distribution map; step S404, generate maintenance instructions, the instructions include detailed information and accurate geographical coordinates of each abnormal point.

[0019] Preferably, the method for rapid detection of highway sound barrier screen detachment described in the present invention has other technical features, wherein step S5 specifically includes the following steps: step S501 summarizes and analyzes all data collected during the entire detection process, compares all detection points, identifies anomalies, and comprehensively evaluates potential problems, processes the detection data through an algorithm, and screens out possible sound barrier problem areas; step S502 automatically generates a sound barrier detection report based on the data analysis results, and the report content includes: the location of the screen detachment: clearly mark the specific location where the sound barrier screen detached, including its geographical coordinates on the road or bridge and the specific distance reference; the degree of detachment or deviation: describe the severity of the detachment or deviation, including the specific values ​​of the deviation distance and the detached area; areas for further inspection: mark the areas that need further inspection; recommended maintenance measures: generate maintenance recommendations, the recommendations include repair measures, construction tools, required materials, and possible repair time ranges; report storage and distribution: automatically store the generated detection report and automatically send it to the relevant maintenance team and management department via email or other communication methods.

[0020] The present invention also designs a system that adopts the above-mentioned method for rapid detection of the detachment of the highway sound barrier screen, including a detection vehicle, and the system also includes a laser displacement meter module, a data processing module, a positioning system, and a data storage and analysis module; the laser displacement meter module is arranged on both sides or the top of the detection vehicle, and captures the surface position information of the sound barrier screen by emitting a high-frequency laser beam and receiving the laser signal reflected from the surface of the sound barrier, so as to measure the distance between the sound barrier screen and the detection vehicle in real time; the data acquisition and processing module, the core algorithm of which includes noise filtering, cluster analysis and anomaly recognition, and is used to receive and process the distance data transmitted back by the laser displacement meter module; the positioning system includes GPS and a positioning device, which is used to record the precise geographic coordinates of the detection vehicle during driving; the data storage and analysis module is used to record and store the location information of the sound barrier, the detection date, the detection results and detailed records of abnormal conditions, and perform subsequent analysis, comparison and report generation on the stored data through a data management platform.

[0021] Preferably, the system for rapid detection of detachment of highway sound barrier screens described in the present invention has other technical features, wherein the laser displacement meter module includes a plurality of laser displacement meters, wherein all of the laser displacement meters are arranged on the same vertical plane of the inspection vehicle; wherein the first laser displacement meter is arranged at the lowest point from the ground on the vertical plane of the inspection vehicle, and is used to measure the distance between the inspection vehicle and the crash barrier, eliminating the impact caused by the vehicle's inability to maintain a fixed distance and parallel to the sound barrier; and the plurality of laser displacement meters are arranged at equal intervals in the vertical direction.

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] Through the precise measurement and data processing of the vehicle-mounted laser displacement meter, efficient and automated detection of the service condition of the sound barrier screen is achieved, and formatted data is effectively accumulated, providing a corresponding data basis for the detection, maintenance and management of road and bridge sound barriers, and providing a strong guarantee for the safe maintenance of transportation infrastructure. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 , is a flow chart of the method of the present invention;

[0025] Figure 2 , is a schematic diagram of the system of the present invention;

[0026] Figure 3 , is a schematic diagram of the method of the present invention;

[0027] Figure 4 , is a schematic diagram of screen shedding abnormal value identification in Example 1;

[0028] In the figure: 1. detection vehicle, 2. first laser displacement meter, 3. other laser displacement meters, 4. sound barrier. DETAILED DESCRIPTION

[0029] In order to make the purpose, principle and structure of the present invention more clear, it is further described below in conjunction with the drawings and specific embodiments.

[0030] The basic design technical solution of the present invention is as follows: The vehicle-mounted detection device of the present invention mainly includes a laser radar module, a data processing module, a positioning system, and a data storage and analysis module.

[0031] Laser displacement meter module: This module is the core sensing device of the present invention. It is installed on both sides of the detection vehicle and is used to measure the distance between the sound barrier screen and the vehicle. The laser displacement meter captures the surface position information of the screen by emitting a laser beam and converts this information into distance data.

[0032] Data acquisition and processing module: This module is responsible for real-time acquisition of distance data sent back by the laser displacement meter and processes the data through a preset algorithm. This module can identify the normal state and abnormal conditions (such as falling off or offset) of the sound barrier screen.

[0033] Positioning system: including GPS or other precise positioning devices, used to record the location information of the inspection vehicle during its driving process, so that the inspection data of each section of the sound barrier has clear spatial coordinates corresponding to it.

[0034] Data collection, storage and analysis module: The data generated during the test will be stored in this module for subsequent analysis and report generation. The data may include the location information of the sound barrier, the test date, the test results, etc.

[0035] Detection method: The method comprises the following steps:

[0036] Step 1: The inspection vehicle drives beside the sound barrier. The inspection vehicle moves at a constant speed along the route of the sound barrier to be inspected and maintains a fixed parallel distance with the sound barrier. Ensure that the laser displacement meter module is operating normally and calibrate the positioning system.

[0037] Step 2: When the detection vehicle slowly drives along the sound barrier, the laser displacement meter module will continuously measure the distance between the sound barrier and the vehicle, and collect the position information of the sound barrier in real time.

[0038] Step 3: After receiving the measurement data from the laser displacement meter, the data acquisition and processing module will pre-process the data and identify abnormalities, and automatically determine whether the screen has fallen off, offset or other abnormal conditions.

[0039] Step 4: If the sound barrier screen is detected to be detached or offset beyond the preset threshold, the system will record the specific detection time and associate the sound barrier abnormality information and its location through the timestamp to facilitate accurate positioning during maintenance.

[0040] Step 5: After the test is completed, the test data is automatically analyzed and a sound barrier test report is generated. The report includes the location and degree of screen detachment, as well as areas that require further inspection and recommended maintenance measures.

[0041] <Example 1>

[0042] See also Figure 2 The detection system of the present invention includes the following key components: a laser displacement meter module, a data processing module, a positioning system, and a data storage and analysis module.

[0043] The laser displacement meter module is the core sensing device of the present invention, which is responsible for measuring the distance between the sound barrier screen and the detection vehicle in real time. The module is installed on both sides or the top of the detection vehicle, and captures the surface position information of the sound barrier screen by emitting high-frequency laser beams and receiving laser signals reflected from the surface of the sound barrier. The laser displacement meter can generate accurate distance data and convert these data into three-dimensional coordinates for use by subsequent data processing modules. The module has extremely high accuracy and can detect millimeter-level displacement changes to ensure accurate identification of every subtle structural change of the sound barrier. The laser displacement meter is set on the outer surface of the detection vehicle. It is recommended to configure six laser displacement meters, and all laser displacement meters are installed in the same vertical plane. The first laser displacement meter is located at the lowest point from the ground, mainly used to measure the distance between the detection vehicle and the crash barrier, eliminating the impact of the vehicle being unable to maintain a fixed distance parallel to the sound barrier. And form a comparative reference with the data obtained by other displacement meters, and the remaining laser displacement meters are arranged at equal intervals in the vertical direction. Since the side of the vehicle has a certain curvature, the influence of the side curvature should be considered when calculating the actual distance between the detection vehicle and the sound barrier, and a fixed correction value should be subtracted in advance to ensure that the measurement results of all laser displacement meters are on the same vertical plane.

[0044] The data acquisition and processing module is responsible for receiving and processing the distance data sent back by the laser displacement meter module. This module uses a preset algorithm to process the real-time collected data and can identify the normal state and abnormal conditions of the sound barrier screen, such as the screen falling off, offset or other structural damage. The core algorithm of the data processing module includes steps such as noise filtering, cluster analysis and anomaly identification to ensure the accuracy and reliability of the data.

[0045] The positioning system is a location recording device for the inspection vehicle, usually including GPS or other precise positioning devices, which is used to record the precise geographic coordinates of the inspection vehicle during driving. The role of the positioning system is to provide clear spatial coordinate correspondence for the inspection data of each section of the sound barrier, so that the subsequent inspection report can accurately mark the location where the abnormal situation occurred. The positioning system is closely integrated with the data acquisition module to ensure that the inspection data corresponds to the specific geographic location, thereby achieving precise positioning and efficient inspection.

[0046] The data storage and analysis module is used to record and store all data generated during the inspection process, including the location information of the sound barrier, the inspection date, the inspection results, and detailed records of abnormal conditions. This module provides a comprehensive data management platform that can perform subsequent analysis, comparison, and report generation on the stored data. In addition, the automatic generation of inspection reports further simplifies the data analysis and application process, allowing the inspection results to be quickly converted into detailed maintenance guidance documents, greatly improving the efficiency of data utilization.

[0047] <Example 2>

[0048] See also Figure 1 , 3 , the method of the present invention is as follows:

[0049] Step 1: The inspection vehicle drives next to the sound barrier. The inspection vehicle moves at a constant speed along the route of the sound barrier to be inspected and maintains a fixed parallel distance with the sound barrier. Ensure that the laser displacement meter module is operating normally and calibrate the positioning system;

[0050] Step 1 specifically includes the following steps:

[0051] Step 101 Before driving, confirm that the laser displacement meter module has been operating normally and calibrated. All laser displacement meters have been pre-deducted from the correction value caused by the curvature of the vehicle side. , ensuring the consistency and reliability of measurement data.

[0052] Step 102 ensures that the route of the inspection vehicle corresponds accurately to the actual position of the sound barrier. The positioning system should have a high-precision geographic coordinate recording function to facilitate accurate positioning and analysis of the inspection data in subsequent steps.

[0053] Step 103: The detection vehicle should travel in the lane closest to the sound barrier and try to maintain a fixed parallel distance from the sound barrier to prevent inaccurate measurement results due to vehicle deviation.

[0054] Step 104: The detection vehicle drives at a constant speed beside the sound barrier to avoid data fluctuations and detection errors caused by speed changes. Keep the vehicle running smoothly to ensure the measurement accuracy of the laser displacement meter module.

[0055] Step 2: When the detection vehicle slowly drives along the sound barrier, the laser displacement meter module continuously measures the distance between the sound barrier and the vehicle, and collects the position information of the sound barrier in real time;

[0056] Step 2 specifically includes the following steps:

[0057] Step 201: As the inspection vehicle moves forward, the laser displacement meter module continuously measures the distance between the sound barrier and the inspection vehicle by emitting a laser beam and receiving the signal reflected from the surface of the sound barrier. Each laser displacement meter module continuously acquires distance data during driving, ensuring seamless monitoring of the entire length of the sound barrier.

[0058] In step 202, the distance data collected by the laser displacement meter module is transmitted to the data processing module in real time at a very high frequency. Since the laser displacement meter module has a millimeter-level measurement accuracy, it can capture small changes in the surface of the sound barrier, ensuring high accuracy and high resolution of the position information.

[0059] Step 203: Through continuous data collection, the laser displacement meter module can construct a distance information model of the sound barrier surface from the vehicle, which can reflect the true shape of the sound barrier surface, including any slight deformation, offset or detached areas that may exist.

[0060] Step 3: After receiving the measurement data from the laser displacement meter, the data acquisition and processing module will pre-process the data and identify abnormalities, and automatically determine whether the screen has fallen off, offset or other abnormal conditions.

[0061] Step 3 specifically includes the following steps:

[0062] Step 301: The data acquisition and processing module first receives the distance measurement data sent back by the laser displacement meter. These data are usually transmitted continuously at a high frequency, so the module will first pre-process the data, including removing abnormal values, filtering out noise signals, and smoothing the data to ensure the accuracy and reliability of the measurement data.

[0063] First, eliminate the data errors caused by the vehicle's inability to maintain a fixed distance between the vehicle and the screen and the curvature of the vehicle's side, and generate a data set for checking the screen's detachment or significant displacement. . Among them, the data set D is a 5-column n A numeric matrix of rows, n Indicates the total number of points collected by a laser displacement meter. n is an integer, , T Indicates the total collection time. f Indicates the acquisition frequency, = , i =1~5 and i is an integer, where i =1, .

[0064] Secondly, before abnormality identification, the system first performs noise reduction on the raw data measured by the laser displacement meter to eliminate noise caused by vehicle movement, environmental interference and other factors to ensure data accuracy. Gaussian filtering is used as a noise reduction method. This method reduces noise by smoothing each data point with the weighted average of its surrounding data.

[0065] The Gaussian filter uses a filter to filter the original data sequence. D Perform noise reduction to obtain a smoothed data sequence D ′={ d 1 ′ , d 2 ′ , d3 ′ , d 4 ′ , d 5 ′}. Smoothed data , the data According to the following formula:

[0066] ;

[0067] in: G ( x ) is the weight of the Gaussian filter, which depends on the relative position j and σ , The original data is located at t Time data The surrounding data, m is the radius of the filter;

[0068] The weight of the filter is determined by a Gaussian distribution function, as follows:

[0069] ;

[0070] in, σ is the standard deviation, x Indicates the distance between the surrounding data points and the central data point. The surrounding data is determined by the window size of the filter. The window size is used to determine the range of neighboring data points of each data point when performing weighted averaging. The size of the window is determined by the standard deviation σ Determine that the Gaussian filter is one-dimensional and the window size is as follows: Window size = , ┌┐ indicates rounding up, which is used to make the window size an odd number.

[0071] Step 302: The pre-processed data is preliminarily analyzed using a clustering algorithm. The clustering algorithm can automatically divide the measured data into different groups and identify the data sets that differ greatly from the standard values. These outlier data usually correspond to the situation where the screen is missing or significantly offset. Through this automated clustering analysis, the system can effectively detect the position where the screen falls off or is significantly displaced.

[0072] The system first converts the data set measured by the laser displacement meter into D ′={ d 1 ′ , d 2 ′ , d 3 ′ , d 4 ′ , d 5 ′}Conduct cluster analysis. d i ′ Represents the distance data between the sound barrier and the detection vehicle after preprocessing. Using the k-means clustering algorithm, the data set D ' is divided into p clusters, each cluster represents the distance measurement value of the sound barrier in different states, and clustering optimization is achieved by minimizing the sum of squares of the distances within the cluster. The formula is as follows:

[0073] ;

[0074] in, J represents the objective function, which is used to measure the compactness of clustering or clustering error. Represents filtered data Middle q The denoised data points, Indicates q A collection of clusters, It is a cluster The average value of all points in the cluster is obtained; the data points that significantly deviate from the normal distance range are identified as possible screen missing locations through a clustering algorithm.

[0075] Step 303: After cluster analysis identifies areas where the screen is missing or detached, the system removes these abnormal data from subsequent analysis and performs a cluster analysis on the remaining data sets. The control chart method is used to evaluate the verticality of the screen. As a baseline, representing the average vertical distance of the sound barrier in normal conditions, control limits UCL (Upper Control Limit) and LCL (Lower Control Limit) are set to identify verticality deviations:

[0076] ;

[0077] in, σ d is the vertical distance dataset The standard deviation of k is the control limit coefficient, usually chosen k =3 to achieve a 99.73% control probability. Beyond the control limit, that is > UCL or < LCL , it is judged as verticality abnormality and the area is marked.

[0078] Once an abnormal situation is identified in step 304, the data acquisition and processing module will immediately mark the relevant data as abnormal. At the same time, the module will record the specific location, deviation degree and related location information of each abnormal point, providing a detailed basis for subsequent analysis and disposal.

[0079] The abnormal situation identification results are shown in Figure 4 .

[0080] Step 4: If the sound barrier is detected to be detached or offset beyond the preset threshold, the system will record the specific detection time and associate the abnormal information of the sound barrier and its location through the timestamp to facilitate accurate positioning during maintenance;

[0081] Step 4 specifically includes the following steps:

[0082] Step 401: When the data acquisition and processing module identifies that the sound barrier screen has fallen off or deviated beyond a preset threshold, the system will immediately and automatically record detailed information about the abnormal point, including the degree of deviation or falling off, the relevant timestamp, and the laser displacement meter measurement data.

[0083] Step 402: To ensure that subsequent maintenance personnel can accurately locate the abnormal area, the system will simultaneously associate the location information with the detected abnormal situation through the timestamp association method and the records of the positioning system. The location information includes the geographical coordinates of the abnormal point of the sound barrier, the specific route location of the detection vehicle, etc., to ensure the accuracy and reliability of positioning.

[0084] After completing the location marking in step 403, the system associates and stores the abnormal information with its corresponding geographical location. This operation not only clearly corresponds the detected abnormal situation to the specific area of ​​the sound barrier, but also generates a comprehensive abnormal distribution map in the data storage and analysis module. Through this distribution map, maintenance personnel can see at a glance the damage to the sound barrier and its location, which is convenient for the organization and implementation of subsequent maintenance work.

[0085] After all abnormal records and location data are stored in step 404, a detailed maintenance guide will be generated. This guide includes detailed information and accurate geographic coordinates of each detected abnormal point, helping the maintenance team to quickly locate the area that needs to be repaired. In this way, maintenance personnel can directly reach the damaged area based on the positioning information provided by the system in actual work, greatly reducing the time waste and duplication of work caused by incomplete or inaccurate information.

[0086] Step 5: After the detection is completed, the detection data is automatically analyzed and a sound barrier detection report is generated. The report includes the location and degree of screen detachment, as well as areas that require further inspection and recommended maintenance measures.

[0087] Step 5 specifically includes the following steps:

[0088] After the test in step 501 is completed, the data collection and processing module will summarize and analyze all the data collected during the entire test process. This analysis process is automated and includes comparison of all test points, abnormality identification, and comprehensive evaluation of potential problems. The system will process the test data through algorithms to screen out possible sound barrier problem areas.

[0089] Step 502 Based on the data analysis results, the system will automatically generate a detailed sound barrier detection report. The report content includes the following aspects:

[0090] Location of screen detachment: Clearly mark the specific location where the sound barrier screen detached, including its geographical coordinates and specific distance reference on the road or bridge, to ensure that maintenance personnel can quickly locate the problem area.

[0091] Extent of shedding or displacement: Describe the severity of shedding or displacement in detail, including specific values ​​such as the displacement distance and shedding area, to help maintenance personnel assess the urgency of the problem.

[0092] Areas for further inspection: Based on the inspection results, the report will indicate areas that require further inspection. These areas may have potential structural issues but have not yet reached the alarm threshold, and the system will recommend a second inspection or regular monitoring.

[0093] Recommended maintenance measures: The system automatically generates maintenance recommendations based on the inspection data and analysis results. These recommendations include specific repair measures, recommended construction tools, required materials, and possible repair timeframes. This information will provide clear operational guidance for the maintenance team.

[0094] Report storage and distribution: The generated test reports will be automatically stored in the system's data storage and analysis module to ensure secure data storage and convenient access. According to needs, the reports can also be automatically sent to the relevant maintenance team and management department via email or other communication methods to ensure timely delivery of information.

[0095] The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field.

[0096] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent substitutions or changes according to the technical solutions and novel concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for quickly detecting the falling off of a highway sound barrier, characterized in that: The method comprises the following steps: Step S1. The detection vehicle drives at a constant speed along the set sound barrier route and maintains a fixed parallel distance with the sound barrier to ensure the normal operation and accurate calibration of the laser displacement meter module. All laser displacement meters have pre-deducted the correction value caused by the curvature of the vehicle side. ; Step S2. While the inspection vehicle is driving slowly, the laser displacement meter module is used to continuously measure the distance between the sound barrier and the vehicle, and collect the position data of the sound barrier in real time. The laser displacement meter module continuously measures the distance between the sound barrier screen and the inspection vehicle by emitting a laser beam and receiving the signal reflected from the surface of the sound barrier. ,Through continuous data collection, the laser displacement meter module constructs a distance information model between the surface of the sound barrier and the vehicle; Step S3. Receive the measurement data of the laser displacement meter through the data acquisition and processing module, perform data preprocessing and abnormality identification, so as to automatically determine whether the sound barrier is detached, offset or other abnormal conditions occur. Step S3 includes: Step S301: pre-processing the distance measurement data sent back by the laser displacement meter, including removing abnormal values, filtering out noise signals and performing data smoothing; Among them, the data error caused by the vehicle's inability to maintain a fixed distance between the vehicle and the screen and the curvature of the vehicle's side is eliminated to generate a data set , data set D is a 5-column n A numeric matrix of rows, n Indicates the total number of points collected by a laser displacement meter. n is an integer, , T Indicates the total collection time. f Indicates the acquisition frequency, = , i =1~5 and i is an integer, where i =1, ; The original data sequence is filtered using Gaussian filtering. D Perform noise reduction to obtain a smoothed data sequence D ′={ d 1 ′ , d 2 ′ , d 3 ′ , d 4 ′ , d 5 ′ }; Step S302: The pre-processed data are preliminarily analyzed using a clustering algorithm. The clustering algorithm is used to automatically divide the measurement data into different groups, identify the data sets that differ greatly from the standard values, and detect the falling off or significant displacement position of the screen body; Step S303: After cluster analysis identifies areas where the screen is missing or detached, the system removes these abnormal data from subsequent analysis, applies the control chart method to the remaining data to evaluate the verticality of the screen, sets the upper control limit UCL and the lower control limit LCL to identify verticality deviations, and marks abnormal areas according to data deviations; Step S304: After identifying the abnormal situation, the data acquisition and processing module records the relevant data of the abnormal state, including the specific location of each abnormal point, the degree of deviation and the relevant location information; Step S4. If it is detected that the sound barrier screen is detached or offset beyond the preset threshold, the specific detection time is recorded, and a timestamp is generated to associate the corresponding sound barrier abnormality information and its location; Step S5. After the detection is completed, the detection data is automatically analyzed and a sound barrier detection report is generated, which includes the location and degree of screen detachment, areas that require further inspection, and recommended maintenance measures.

2. A method for rapid detection of road sound barrier screen falling off as described in claim 1, characterized in that The Gaussian filtering method in step S301 is: The Gaussian filter uses a filter to smooth each data point in the data set by combining it with the weighted average of the surrounding data. , the data According to the following formula: ； in: G ( x ) is the weight of the Gaussian filter, which depends on the relative position j and σ , The original data is located at t Time data The surrounding data, m is the radius of the filter; The weights of the filters G ( x ) is determined by a Gaussian distribution function, which is as follows: ； in, σ is the standard deviation, x Indicates the distance between the surrounding data points and the central data point. The surrounding data is determined by the window size of the filter. The window size is used to determine the range of neighboring data points of each data point when performing weighted averaging. The size of the window is determined by the standard deviation σ Determine that the Gaussian filter is one-dimensional and the window size is as follows: Window size = , ⌈⌉ represents the rounding up operation, which is used to make the window size an odd number.

3. A method for rapid detection of highway sound barrier screen falling off as described in claim 1, characterized in that The step S302 is specifically as follows: First, the dataset D ′={ d 1 ′ , d 2 ′ , d 3 ′ , d 4 ′ , d 5 ′ } cluster analysis, where d i ′ Represents the distance data between the sound barrier and the detection vehicle after preprocessing; The clustering algorithm uses the 𝑘-mean clustering algorithm to group the data set D ' is divided into p clusters, each cluster represents the distance measurement value of the sound barrier in different states, and clustering optimization is achieved by minimizing the sum of squares of the distances within the cluster. The formula is as follows: ； in, J represents the objective function, which is used to measure the compactness of clustering or clustering error. Represents filtered data Middle q The denoised data points, Indicates q A collection of clusters, It is a cluster The average of all points in ; The data points that significantly deviate from the normal distance range are identified as possible screen missing locations through a clustering algorithm.

4. A method for rapid detection of road sound barrier falling off as described in claim 1, characterized in that The step S303 is specifically as follows: The control chart method is applied to the remaining data sets use As a reference line to evaluate the verticality of the sound barrier screen, Represents the average vertical distance of the sound barrier in a normal state. The upper control limit 𝑈𝐶𝐿 and the lower control limit 𝐿𝐶𝐿 are set to identify the verticality deviation. The calculation formulas of UCL and LCL are as follows: ； in, σ d is the vertical distance dataset The standard deviation of k is the control limit coefficient, by choosing k =3 The control probability is 99.73%; When a measurement value Beyond the control limit, that is > UCL or < LCL , it is judged as verticality abnormality and the area is marked.

5. A method for rapid detection of road sound barrier falling off as described in claim 1, characterized in that The step S4 specifically comprises the following steps: Step S401: When it is identified that the sound barrier screen body is detached or deviated beyond a preset threshold, the degree of deviation or detachment of the abnormal point, the relevant timestamp and the information of the laser displacement meter measurement data are automatically recorded; Step S402 associates the location information with the detected abnormality by means of a timestamp association method in combination with the records of the positioning system, wherein the location information includes the geographical coordinates of the abnormal point of the sound barrier and the specific route location of the detection vehicle; Step S403 stores the abnormal information of the marked position in association with the geographical location and generates a comprehensive abnormal distribution map; Step S404 generates maintenance instructions, which include detailed information and accurate geographic coordinates of each abnormal point.

6. A method for rapid detection of road sound barrier falling off as described in claim 1, characterized in that The step S5 specifically comprises the following steps: Step S501 summarizes and analyzes all data collected during the entire detection process, compares all detection points, identifies anomalies, and comprehensively evaluates potential problems. The detection data is processed through an algorithm to screen out possible sound barrier problem areas; Step S502 automatically generates a sound barrier detection report based on the data analysis results, and the report content includes: Location of screen detachment: clearly mark the specific location where the sound barrier screen detached, including its geographical coordinates and specific distance reference on the road or bridge; Degree of shedding or displacement: Describe the severity of shedding or displacement, including the specific values ​​of the displacement distance and the shedding area; Areas for further inspection: Indicate areas that require further inspection; Recommended maintenance measures: Generate maintenance recommendations that include repair measures, construction tools, required materials, and possible repair timeframes; Report storage and distribution: The generated inspection reports are automatically stored and sent to the relevant maintenance team and management department via email.

7. A highway sound barrier screen falling off rapid detection system, using the method as claimed in claim 1, including a detection vehicle, characterized in that The system also includes a laser displacement meter module, a data processing module, a positioning system, and a data storage and analysis module; The laser displacement meter module is installed on both sides or the top of the inspection vehicle. It captures the surface position information of the sound barrier screen by emitting high-frequency laser beams and receiving laser signals reflected from the surface of the sound barrier, and is used to measure the distance between the sound barrier screen and the inspection vehicle in real time. A data acquisition and processing module, the core algorithms of which include noise filtering, cluster analysis and anomaly recognition, is used to receive and process the distance data transmitted back by the laser displacement meter module; Positioning system, including GPS and positioning device, used to record the precise geographic coordinates of the inspection vehicle during driving; The data storage and analysis module is used to record and store the location information, test date, test results and detailed records of abnormal conditions of the sound barrier, and conduct subsequent analysis, comparison and report generation of the stored data through the data management platform.

8. A highway sound barrier screen falling off rapid detection system as claimed in claim 7, characterized in that The laser displacement meter module includes a plurality of laser displacement meters. Among them, all laser displacement meters are set on the same vertical plane of the inspection vehicle; The first laser displacement meter is set at the lowest point from the ground on the vertical plane of the inspection vehicle to measure the distance between the inspection vehicle and the anti-collision wall, eliminating the influence caused by the vehicle being unable to maintain a fixed distance and parallel to the sound barrier; The plurality of laser displacement meters are arranged at equal intervals in the vertical direction.

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