Highway pavement damage identification method and system based on laser scanner

Abstract

The invention discloses a highway pavement damage identification method and system based on a laser scanner, and relates to the technical field of pavement damage identification. Comprising a laser beam emission module, a laser beam reflection module, a time measurement module, a distance calculation module, an angle measurement module, a three-dimensional coordinate calculation module, a data acquisition module, a data analysis module, a beam emission information acquisition unit, a calculation result acquisition unit, a server, a comparison analysis unit and a comprehensive analysis unit. The accuracy is monitored when the laser scanner in the highway pavement damage identification system identifies the highway pavement damage condition, and when the hidden danger of abnormal identification accuracy possibly exists when the laser scanner identifies the highway pavement damage condition, an early warning prompt is given out in time; related highway pavement detection personnel are informed to know the condition in time, related maintenance and management work is arranged for the laser scanner in advance, and stable and efficient operation of the laser scanner is ensured.

Description

Technical Field

[0001] This invention relates to the field of road surface damage identification technology, specifically to a method and system for identifying highway road surface damage based on a laser scanner. Background Technology

[0002] A road surface damage identification system is a technological system used to monitor and detect damage and defects on road surfaces. These systems typically use image processing, computer vision technology, as well as sensors and data analysis to automatically identify problems on the road, such as cracks, potholes, asphalt damage, and other damage.

[0003] Laser scanners play a crucial role in highway pavement damage identification systems, primarily used to acquire three-dimensional shape information of the road surface. This helps the system more accurately detect and locate pavement damage. The specific functions of laser scanners in this system are as follows: 1. Laser scanners precisely measure the distances between points on the road surface by emitting a laser beam and measuring its reflection time. This allows them to obtain three-dimensional shape information of the road surface, including potholes, depressions, bulges, and slopes. 2. Laser scanners offer very high measurement accuracy, typically at the millimeter level. This enables the system to detect small road surface damage, such as cracks, potholes, and depressions, rather than just large-area damage. 3. Laser scanning is a non-contact measurement method that does not require physical contact with the road surface, thus reducing further damage to the road surface and wear on the measuring equipment. 4. Laser scanners can operate at very high scanning speeds, quickly acquiring three-dimensional road surface data. This is particularly important for large-scale road inspections and high-speed patrol vehicles. 5. Laser scanners can generate very dense point cloud data containing a large amount of road surface height information. This data density helps to describe the road surface characteristics in more detail, thereby improving the accuracy of damage detection and identification.

[0004] The existing technology has the following shortcomings: In a road surface damage identification system, accurate road surface damage identification is crucial for road safety. When the laser scanner's identification accuracy for road surface damage decreases but the system cannot intelligently perceive it, with continued use of the laser scanner, it may fail to accurately identify early, minor potholes, dents, cracks, and other dangerous road surface damage. This could worsen the damage to the road surface, thereby increasing road repair costs, or even lead to traffic accidents, vehicle damage, and pedestrian injuries, posing a potential threat to road safety.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for identifying road surface damage based on a laser scanner. By monitoring the accuracy of the laser scanner in the road surface damage identification system when identifying road surface damage, and issuing a timely warning when there is a potential risk of abnormal accuracy in the laser scanner's identification of road surface damage, the invention informs relevant road surface inspection personnel of the situation and arranges relevant maintenance and management work for the laser scanner in advance to ensure the stable and efficient operation of the laser scanner, thereby solving the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a highway pavement damage identification system based on a laser scanner, comprising a laser beam emission module, a laser beam reflection module, a time measurement module, a distance calculation module, an angle measurement module, a three-dimensional coordinate calculation module, a data acquisition module, a data analysis module, a beam emission information acquisition unit, a calculation result acquisition unit, a server, a comparison and analysis unit, and a comprehensive analysis unit; The laser beam emitting module generates a laser beam through a laser scanner, directing the laser beam toward the target area on the road surface. The beam emission information acquisition unit is used to acquire laser characteristic information of the laser scanner in the highway pavement damage identification system when identifying damage to the highway pavement. After acquisition, the laser characteristic information is processed and uploaded to the server. The laser beam reflection module reflects the laser beam after it intersects with the road surface, returning it to the laser scanner. The time measurement module is used to measure the time it takes for a laser beam to travel from emission to reflection, i.e., the optical path time. The distance calculation module calculates the round-trip distance of the laser beam based on the optical path time and the known speed of light. The calculation result acquisition unit is used to acquire linearity information of the laser scanner in the highway pavement damage identification system when identifying highway pavement damage. After acquisition, the linearity information is processed and uploaded to the server. The server comprehensively analyzes the laser characteristics and linearity information processed by the laser scanner when identifying road surface damage, generates an identification index, and transmits the identification index to the comparison and analysis unit. The comparison and analysis unit compares and analyzes the identification index generated by the laser scanner when identifying road surface damage with a pre-set identification index reference threshold, generates a high-hazard identification signal or a low-hazard identification signal, and transmits the signal to the comprehensive analysis unit. After receiving the high-risk identification signal generated by the laser scanner when identifying road surface damage, the comprehensive analysis unit establishes an analysis set based on several identification indices generated by the server during the subsequent operation of the laser scanner to perform comprehensive analysis and determine the abnormal state of the laser scanner. An angle measurement module determines the horizontal and vertical directions of the laser beam; The three-dimensional coordinate calculation module calculates the three-dimensional coordinates of the target point, namely the horizontal position, vertical position, and height of the target, based on the distance measurement results and angle measurement results. The data acquisition module organizes the acquired 3D coordinate data into a point cloud; The data analysis module analyzes point cloud data to detect and identify road surface damage, and to determine the location, type, and severity of the damage.

[0008] Preferably, the laser characteristic information used by the laser scanner to identify road surface damage includes the laser pulse frequency anomaly concealment coefficient and the scanning speed variation coefficient. After acquisition, the laser pulse frequency anomaly concealment coefficient and the scanning speed variation coefficient used by the laser scanner to identify road surface damage are respectively calibrated by the beam emission information acquisition unit. and .

[0009] Preferably, the logic for obtaining the laser pulse frequency anomaly concealment coefficient is as follows: A101. Obtain the optimal laser pulse frequency range for using a laser scanner to identify road surface damage, and calibrate the optimal laser pulse frequency range as follows: ; A102. Obtain the actual laser pulse frequencies at different time intervals within time T when using a laser scanner to identify road surface damage, and calibrate the actual laser pulse frequencies as follows: , v This indicates the number of the actual laser pulse frequencies at different times within time T when the laser scanner identifies road surface damage. v =1, 2, 3, 4, ... s , s It is a positive integer; A103. When using a laser scanner to identify road surface damage, the actual laser pulse frequencies acquired within time T that are not within the optimal laser pulse frequency range are recalibrated as follows: , This indicates the number of the actual laser pulse frequency that is not within the optimal laser pulse frequency range, acquired within time T when the laser scanner is identifying road surface damage. , It is a positive integer; A104. Calculate the laser pulse frequency anomaly concealment coefficient. The expression for the calculation is: In the formula, .

[0010] Preferably, the logic for obtaining the scanning speed variation coefficient is as follows: B101. Obtain the actual scanning speed of the laser scanner at different time intervals within time T when identifying road surface damage, and calibrate the actual scanning speed as... , x This indicates the number representing the actual scanning speed of the laser scanner at different time points within time T when identifying road surface damage. x =1, 2, 3, 4, ... m , m It is a positive integer; B102. Calculate the scanning speed variation coefficient. The expression for the calculation is: , m This represents the total number of actual scanning speeds acquired within time T when a laser scanner identifies road surface damage.

[0011] Preferably, the linearity information of the laser scanner in identifying road surface damage includes the optical path time offset coefficient. After acquisition, the optical path time offset coefficient for identifying road surface damage is calibrated by the calculation result acquisition unit. .

[0012] Preferably, the logic for obtaining the optical path time offset coefficient is as follows: C101. Obtain the initial ratio constant between the time travel and the actual distance during laser scanner identification of road surface damage, and calibrate the initial ratio constant as follows: ; C102. When using a laser scanner to identify road surface damage, acquire several actual ratio constants generated within time T for each beam's optical path time compared to the actual distance, and calibrate these actual ratio constants as follows: , y This represents the numbering of several actual ratio constants generated within time T for each beam travels through the optical path time compared to the actual distance when a laser scanner identifies road surface damage. y =1, 2, 3, 4, ... n , n It is a positive integer; C103. Calculate the optical path time offset coefficient. The expression for the calculation is: .

[0013] Preferably, the server uses a processed laser pulse frequency anomaly concealment coefficient to identify road surface damage by the laser scanner. Scanning speed variation coefficient and optical path time offset coefficient Afterwards, , as well as Formulating the data to generate a recognition index The formula used is: In the formula, , , These are the laser pulse frequency anomaly concealment coefficients. Scanning speed variation coefficient and optical path time offset coefficient The preset proportional coefficient, and , , All are greater than 0.

[0014] Preferably, the comparison and analysis unit compares the recognition index generated by the laser scanner when identifying road surface damage with a pre-set recognition index reference threshold. The results of the comparison and analysis are as follows: If the identification index is greater than or equal to the identification index reference threshold, a high-risk identification signal is generated by the comparison analysis unit and transmitted to the comprehensive analysis unit. If the identification index is less than the identification index reference threshold, a low-risk identification signal is generated by the comparison analysis unit and transmitted to the comprehensive analysis unit.

[0015] Preferably, after receiving the high-risk identification signal generated by the laser scanner when identifying road surface damage, the comprehensive analysis unit establishes an analysis set based on several identification indices generated by the server during subsequent operation of the laser scanner, and calibrates the analysis set as follows: Z ,but , j This indicates the identification index number within the analysis set. j =1, 2, 3, 4, ... u , u It is a positive integer; The standard deviation and mean of the recognition index are calculated by analyzing the recognition index within the set, and the standard deviation and mean of the recognition index are respectively calibrated as follows: and ,but: ,but: ; To identify the exponential standard deviation and the average of the identification index Each was compared with a pre-set standard deviation reference threshold. and the preset limited recognition index reference threshold The comparative analysis was performed, and the results are as follows: like If an accidental signal is generated by the comprehensive analysis unit and transmitted to the mobile terminal, the mobile terminal will notify the relevant road surface inspection personnel that an accidental anomaly has occurred when the laser scanner is identifying road surface damage. No maintenance or management of the laser scanner is required. like or If the signal is not accidental, the comprehensive analysis unit will generate a non-accidental signal and transmit it to the mobile terminal. The mobile terminal will then prompt the relevant road surface inspection personnel that the laser scanner is not encountering an accidental anomaly when it is identifying road surface damage, and that the laser scanner needs to be maintained and managed in a timely manner.

[0016] A method for identifying road surface damage based on laser scanners includes the following steps: S1. A laser beam is generated by a laser scanner and directed towards the target area on the road surface. S2. Collect laser characteristic information of the laser scanner in the highway pavement damage identification system when identifying highway pavement damage; S3. After the laser beam intersects with the road surface, it is reflected and returns to the laser scanner. The time from emission to reflection of the laser beam is measured, which is the optical path time. The round-trip distance of the laser beam is calculated based on the optical path time and the known speed of light. S4. Collect linearity information of the laser scanner in the highway pavement damage identification system when identifying highway pavement damage. S5. The laser characteristic information and linearity information processed by the laser scanner when identifying road surface damage are comprehensively analyzed to generate an identification index. S6. When the laser scanner identifies the damage to the road surface, it compares and analyzes the identification index generated with the pre-set identification index reference threshold to generate a high-hazard identification signal or a low-hazard identification signal. After receiving the high-hazard identification signal generated by the laser scanner when identifying the damage to the road surface, it establishes an analysis set for several identification indices generated by the laser scanner during subsequent operation to conduct a comprehensive analysis and determine the abnormal state of the laser scanner. S7. Determine the horizontal and vertical directions of the laser beam. Based on the distance and angle measurement results, calculate the three-dimensional coordinates of the target point, namely the horizontal position, vertical position, and height of the target. Organize the acquired three-dimensional coordinate data into a point cloud. Analyze the point cloud data to detect and identify road surface damage, and determine the location, type, and severity of the road surface damage.

[0017] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention monitors the accuracy of laser scanners in a road surface damage identification system when identifying road surface damage. When there is a potential risk of abnormal accuracy in the laser scanner's identification of road surface damage, a timely warning is issued to inform the relevant road surface inspection personnel. The system also allows for advance maintenance and management of the laser scanner to ensure its stable and efficient operation. This invention, when sensing a potential malfunction in the accuracy of laser scanners used for identifying road surface damage, comprehensively analyzes the situation. If an occasional anomaly occurs during laser scanner identification, no maintenance is required. However, if the anomaly is not accidental, it indicates a potential malfunction in accuracy, necessitating timely maintenance. This effectively prevents frequent warnings from the road surface damage identification system due to occasional laser scanner malfunctions, improves the accuracy of laser scanner monitoring, and further ensures the stable and efficient operation of the laser scanner. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0019] Figure 1 This is a schematic diagram of the modules of the highway pavement damage identification method and system based on laser scanner of the present invention.

[0020] Figure 2 This is a flowchart of the method and system for identifying road surface damage based on a laser scanner, as described in this invention. Detailed Implementation

[0021] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0022] This invention provides, for example Figure 1The highway pavement damage identification system based on a laser scanner shown includes a laser beam emission module, a laser beam reflection module, a time measurement module, a distance calculation module, an angle measurement module, a three-dimensional coordinate calculation module, a data acquisition module, a data analysis module, a beam emission information acquisition unit, a calculation result acquisition unit, a server, a comparison and analysis unit, and a comprehensive analysis unit. The laser beam emitting module generates a laser beam through a laser scanner, directing the laser beam toward the target area on the road surface. This laser beam is usually emitted by a laser diode or laser and has a highly directional characteristic. The laser scanner orients the laser beam so that it is directed at the target area on the road surface. Typically, the rotating or oscillating device of the laser scanner allows the laser beam to scan the entire width and length of the road. Once the laser beam is ready, the laser scanner emits the laser beam and projects it onto the target area on the road surface. The beam emission information acquisition unit is used to acquire laser characteristic information of the laser scanner in the highway pavement damage identification system when identifying damage to the highway pavement. After acquisition, the laser characteristic information is processed and uploaded to the server. The laser characteristic information used by the laser scanner to identify road surface damage includes the laser pulse frequency anomaly concealment coefficient and the scanning speed variation coefficient. After acquisition, the laser pulse frequency anomaly concealment coefficient and the scanning speed variation coefficient used by the laser scanner to identify road surface damage are respectively calibrated by the beam emission information acquisition unit. and ; The laser pulse frequency of a laser scanner refers to the number of laser pulses emitted per second, usually expressed in Hertz (Hz). The laser scanner continuously emits laser pulses and then measures the reflection time of these pulses to calculate the distance to the target. The laser pulse frequency directly affects the performance and data acquisition speed of the laser scanner. Both excessively low and excessively high laser pulse frequencies in laser scanners can reduce the accuracy of identifying road surface damage, but the reasons for this are not entirely the same. The following is a detailed explanation of these two situations: Laser pulse frequency too low: Reduced accuracy: When the laser pulse frequency is too low, the number of laser pulses emitted per second is limited, which will result in insufficient point cloud data on the road surface. This makes it difficult for the system to capture small-sized damage, such as tiny potholes, small cracks or bulges. These damages usually require higher data density to be accurately identified, and low-frequency laser pulses may not provide enough data. Inconsistency: Low-frequency laser pulses may cause data points to be unevenly distributed over time, thereby reducing the consistency of the data. This can cause problems for the recognition algorithm, because continuity is very important for accurately modeling the shape and characteristics of road damage. Limiting data density: Low-frequency laser pulses limit the amount of point cloud data collected per second, resulting in insufficient 3D representation of the road surface. This is especially true when high-precision data is required, such as for detecting road surface irregularities, where low data density may reduce the accuracy of identification. Missing small targets: Low-frequency laser pulses may not be able to effectively capture small road surface damage, making these small damages almost invisible in the data. This will cause the system to ignore some important minor damage, reducing the comprehensiveness of maintenance. Laser pulse frequency too high: Increased data processing complexity: High-frequency laser pulses generate a large number of data points, which may increase the complexity of data processing. Processing and analyzing large amounts of data may require more computing resources and time, thus the real-time performance of the system may be threatened. Increased data noise: High-frequency laser pulses may increase the noise level in the data because the measurement interval between each data point is short, which may cause noise to interfere with the identification algorithm and reduce accuracy; Increased vibration sensitivity: High-frequency laser pulses may place higher demands on the vibration and stability of the laser scanner. Vibration and shock may cause the position of data points to shift, thereby affecting the accuracy of recognition. Therefore, monitoring the laser pulse frequency when using a laser scanner to identify road surface damage can help detect potential problems such as reduced accuracy in identifying road surface damage due to abnormal laser pulse frequency. The logic for obtaining the laser pulse frequency anomaly concealment coefficient is as follows: A101. Obtain the optimal laser pulse frequency range for using a laser scanner to identify road surface damage, and calibrate the optimal laser pulse frequency range as follows: ; It should be noted that a series of experiments and performance tests were conducted, including scanning known road surface damage using laser pulses of different frequencies. The point cloud data acquired at different frequencies can be used to evaluate the recognition accuracy. These tests should cover a certain range of frequencies, from low to high. Based on actual needs, the optimal laser pulse frequency range for the laser scanner to identify road surface damage was determined comprehensively. The optimal laser pulse frequency range for the laser scanner to identify road surface damage is not specifically limited here and can be adjusted according to the performance test results and actual needs. A102. Obtain the actual laser pulse frequencies at different time intervals within time T (the duration of each time interval can be all equal, all unequal, or a combination of both; no specific limitation is made here) when the laser scanner is used to identify road surface damage. Then, calibrate the actual laser pulse frequencies as follows: , v This indicates the number of the actual laser pulse frequencies at different times within time T when the laser scanner identifies road surface damage. v =1, 2, 3, 4, ... s , s It is a positive integer; It should be noted that external sensors and tools can be used to monitor the laser pulse frequency in real time. This can include using devices such as frequency meters or laser rangefinders to measure the emission and reception times of the laser pulses, thereby calculating the frequency. A103. When using a laser scanner to identify road surface damage, the actual laser pulse frequencies acquired within time T that are not within the optimal laser pulse frequency range are recalibrated as follows: , This indicates the number of the actual laser pulse frequency that is not within the optimal laser pulse frequency range, acquired within time T when the laser scanner is identifying road surface damage. , It is a positive integer; A104. Calculate the laser pulse frequency anomaly concealment coefficient. The expression for the calculation is: In the formula, ; The expression for the laser pulse frequency anomaly concealment coefficient shows that the larger the value of the laser pulse frequency anomaly concealment coefficient generated within time T when the laser scanner identifies road surface damage, the greater the potential for a decrease in the accuracy of the laser scanner in identifying road surface damage. Conversely, the smaller the value, the smaller the potential for a decrease in the accuracy of the laser scanner in identifying road surface damage. The scanning speed of the laser scanner in the highway pavement damage identification system refers to the speed at which the laser scanner completes the scanning of the laser beam and data acquisition per unit time. This speed is usually expressed in degrees per second (degrees / second) or radians per second (rad / s), representing the speed at which the laser scanner rotates or oscillates in the horizontal and vertical directions. Significant fluctuations in the scanning speed of laser scanners may reduce the accuracy of road surface damage identification systems for the following reasons: Uneven distribution of data points: Fluctuations in scanning speed can lead to uneven distribution of data points over time. This means that at some times, the scanner may scan at a faster speed and at other times at a slower speed. This can result in a discontinuous distribution of point cloud data on the road surface in both time and space, which can affect the work of the recognition algorithm. The algorithm may encounter discontinuous data and find it difficult to correctly model and identify damage. Increased distance measurement error: Fluctuations in scanning speed may lead to increased distance measurement error. When the scanning speed changes, the time it takes for the laser pulse to reach the target also changes, which may cause instability in distance measurement, thereby affecting the accuracy of the measured distance value. Inaccurate distance data will lead to inaccurate modeling of road damage. Difficulty in capturing small-sized damage: Fluctuations in scanning speed may cause laser scanners to have difficulty capturing small-sized damage, such as tiny pits or small cracks. Higher scanning speeds may cause the system to miss these small-sized features because the density of data points is insufficient to accurately represent these data points. Increased data processing complexity: Unstable scanning speeds may increase the complexity of data processing. The discontinuous distribution of data points and the increase in distance measurement errors may require more complex algorithms to process the data, and to perform noise filtering and data correction to compensate for the problems caused by speed fluctuations. Therefore, monitoring the scanning speed of the laser scanner when identifying road surface damage can help detect potential problems such as reduced accuracy in identifying road surface damage due to abnormal scanning speed. The logic for obtaining the scanning speed variation coefficient is as follows: B101. Obtain the actual scanning speed of the laser scanner during different time periods within time T (the duration of each time period can be all equal, all unequal, or a combination of both; no specific limitation is made here), and calibrate the actual scanning speed as... , x This indicates the number representing the actual scanning speed of the laser scanner at different time points within time T when identifying road surface damage. x =1, 2, 3, 4, ... m , m It is a positive integer; It should be noted that existing laser scanners typically have built-in speed sensors, usually rotary encoders or inertial measurement units (IMUs). These sensors can measure changes in the angle or position of the laser scanner and calculate the scanning speed over time, which is a common method for real-time speed monitoring. B102. Calculate the scanning speed variation coefficient. The expression for the calculation is: , mThis represents the total number of actual scanning speeds acquired within time T when the laser scanner is identifying road surface damage. According to the calculation expression of the laser pulse frequency anomaly concealment coefficient, the larger the value of the scanning speed variation coefficient generated within time T when the laser scanner identifies road surface damage, the greater the potential for a decrease in the accuracy of the laser scanner in identifying road surface damage. Conversely, the smaller the value, the smaller the potential for a decrease in the accuracy of the laser scanner in identifying road surface damage. The laser beam reflection module reflects the laser beam after it intersects with the road surface, returning it to the laser scanner. The time measurement module is used to measure the time it takes for a laser beam to travel from emission to reflection, i.e., the optical path time. The laser scanner contains a high-precision timing device to measure the time it takes for a laser beam to travel from emission to reflection, i.e., the optical path time. Because the speed of light is very fast, this time measurement can determine the round-trip time of the laser beam very accurately. The distance calculation module calculates the round-trip distance of the laser beam based on the optical path time and the known speed of light. This can be accomplished using the following formula: This gives the distance between the laser beam and the target; The calculation result acquisition unit is used to acquire linearity information of the laser scanner in the highway pavement damage identification system when identifying highway pavement damage. After acquisition, the linearity information is processed and uploaded to the server. The linearity information of the laser scanner in identifying road surface damage includes the optical path time offset coefficient. After acquisition, the optical path time offset coefficient for identifying road surface damage is calibrated by the calculation result acquisition unit. ; Optical path time offset refers to a constant offset between the measured optical path time and the actual distance (as can be seen from the above calculation formula, the ratio between the optical path time and the measured distance is a fixed constant). This offset may be caused by system hardware failure. If there is optical path time offset, the laser scanner will not be able to accurately measure the distance of the object, which will lead to inaccurate estimation of the location and depth of road damage. The nonlinear relationship between optical path time and actual distance may negatively impact the accuracy of laser scanners in identifying road surface damage. This is explained in detail below: Nonlinear error accumulation: Nonlinear relationship means that the error between optical path time and actual distance is not constant but varies within different distance ranges. When this nonlinear error accumulates to a certain extent, it may cause the cumulative error of the measurement results to become significant, which will make the distance value in the point cloud data inaccurate and affect the accurate identification of road damage. Positioning error: Nonlinear relationships may cause inconsistent distance measurement errors by the scanner at different locations. This may lead to deviations in the positioning of objects in the point cloud data, because the scanner cannot accurately determine the distance of the target object. Such positioning errors will affect the detection and accurate positioning of road surface damage. Difficult identification of damaged shapes: Nonlinear relationships may cause different rates of change in optical path time at different distances, which may lead to damage of certain specific shapes, especially complex shapes, which are difficult to identify accurately because the scanner has difficulty obtaining accurate distance information. These damaged shapes may be misidentified or ignored. Therefore, monitoring the ratio between the optical path time and the actual distance when using a laser scanner to identify road surface damage can promptly detect the potential problem of reduced accuracy in identifying road surface damage caused by abnormal optical path time deviation (changes in the ratio between optical path time and actual distance). The logic for obtaining the optical path time offset coefficient is as follows: C101. Obtain the initial ratio constant between the optical path time and the actual distance (i.e., the ratio of optical path time to actual distance) when the laser scanner identifies road surface damage, and calibrate the initial ratio constant as follows: ; It should be noted that laser scanners are usually precisely calibrated at the factory. The manufacturer records an initial ratio constant between the optical path time and the actual distance. This ratio constant is usually written into the device's internal storage or firmware and provided as a default parameter. C102. When using a laser scanner to identify road surface damage, acquire several actual ratio constants generated within time T for each beam's optical path time compared to the actual distance, and calibrate these actual ratio constants as follows: , y This represents the numbering of several actual ratio constants generated within time T for each beam travels through the optical path time compared to the actual distance when a laser scanner identifies road surface damage. y =1, 2, 3, 4, ... n , n It is a positive integer; C103. Calculate the optical path time offset coefficient. The expression for the calculation is: ; As can be seen from the calculation expression of the optical path time offset coefficient, the larger the value of the optical path time offset coefficient generated within time T when the laser scanner identifies road surface damage, the greater the potential for a decrease in the accuracy of the laser scanner in identifying road surface damage; conversely, the smaller the value, the smaller the potential for a decrease in the accuracy of the laser scanner in identifying road surface damage. The server comprehensively analyzes the laser characteristics and linearity information processed by the laser scanner when identifying road surface damage, generates an identification index, and transmits the identification index to the comparison and analysis unit. The server processes the laser pulse frequency anomaly concealment coefficient when the laser scanner identifies road surface damage. Scanning speed variation coefficient and optical path time offset coefficient Afterwards, , as well as Formulating the data to generate a recognition index The formula used is: In the formula, , , These are the laser pulse frequency anomaly concealment coefficients. Scanning speed variation coefficient and optical path time offset coefficient The preset proportional coefficient, and , , All are greater than 0; As can be seen from the calculation formula, the larger the frequency anomaly concealment coefficient, the larger the scanning speed variation coefficient, and the larger the optical path time offset coefficient generated by the laser scanner within time T when identifying road surface damage, the greater the recognition index generated by the laser scanner within time T. The higher the performance value, the greater the potential for a decrease in the accuracy of the laser scanner when identifying road surface damage; conversely, the lower the performance value, the smaller the potential for a decrease in the accuracy of the laser scanner when identifying road surface damage. It should be noted that the above-mentioned time T is a relatively short time period. The time within this period is not specifically limited and can be set according to the actual situation. The purpose is to monitor the situation of the laser scanner in identifying road surface damage within time T, so as to monitor the operating status of the laser scanner in different time periods (within time T) in real time. The comparison and analysis unit compares and analyzes the identification index generated by the laser scanner when identifying road surface damage with a pre-set identification index reference threshold, generates a high-hazard identification signal or a low-hazard identification signal, and transmits the signal to the comprehensive analysis unit. The comparison and analysis unit compares the recognition index generated by the laser scanner when identifying road surface damage with a pre-set reference threshold for the recognition index. The results of the comparison and analysis are as follows: If the identification index is greater than or equal to the identification index reference threshold, a high-risk identification signal is generated by the comparison analysis unit and transmitted to the comprehensive analysis unit. If the identification index is less than the identification index reference threshold, a low-risk identification signal is generated by the comparison analysis unit and transmitted to the comprehensive analysis unit. After receiving the high-risk identification signal generated by the laser scanner when identifying road surface damage, the comprehensive analysis unit establishes an analysis set based on several identification indices generated by the server during the subsequent operation of the laser scanner to perform comprehensive analysis and determine the abnormal state of the laser scanner. After receiving the high-risk identification signal generated by the laser scanner when identifying road surface damage, the comprehensive analysis unit establishes an analysis set based on several identification indices generated by the server during subsequent operation of the laser scanner, and calibrates the analysis set as follows: Z ,but , j This indicates the identification index number within the analysis set. j =1, 2, 3, 4, ... u , u It is a positive integer; The standard deviation and mean of the recognition index are calculated by analyzing the recognition index within the set, and the standard deviation and mean of the recognition index are respectively calibrated as follows: and ,but: ,but: ; To identify the exponential standard deviation and the average of the identification index Each was compared with a pre-set standard deviation reference threshold. and the preset limited recognition index reference threshold The comparative analysis was performed, and the results are as follows: like If an accidental signal is generated by the comprehensive analysis unit and transmitted to the mobile terminal, the mobile terminal will notify the relevant road surface inspection personnel that an accidental anomaly has occurred when the laser scanner is identifying road surface damage. No maintenance or management of the laser scanner is required. like or If the signal is not accidental, the comprehensive analysis unit will generate a non-accidental signal and transmit it to the mobile terminal. The mobile terminal will then prompt the relevant road surface inspection personnel that the laser scanner is not encountering an accidental anomaly when identifying road surface damage. There may be a hidden danger of abnormal identification accuracy when the laser scanner is identifying road surface damage. It is necessary to maintain and manage the laser scanner in a timely manner to ensure that the laser scanner operates stably and efficiently. An angle measurement module determines the horizontal and vertical directions of the laser beam; Laser scanners are typically equipped with horizontal and vertical angle measuring devices to determine the horizontal and vertical directions of the laser beam, which allows the system to know the orientation of the laser beam in the horizontal and vertical directions. The three-dimensional coordinate calculation module calculates the three-dimensional coordinates of the target point, namely the horizontal position, vertical position, and height of the target, based on the distance measurement results and angle measurement results. The data acquisition module organizes the acquired 3D coordinate data into a point cloud; A 3D coordinate point cloud is a dataset composed of a large number of points, which contains the positional information of each point on the road surface; The data analysis module analyzes point cloud data to detect and identify road surface damage, and to determine the location, type, and severity of the damage. This invention monitors the accuracy of laser scanners in a road surface damage identification system when identifying road surface damage. When there is a potential risk of abnormal accuracy in the laser scanner's identification of road surface damage, a timely warning is issued to inform the relevant road surface inspection personnel. The system also allows for advance maintenance and management of the laser scanner to ensure its stable and efficient operation. This invention, when sensing a potential malfunction in the accuracy of laser scanners used for identifying road surface damage, comprehensively analyzes the situation. If an occasional anomaly occurs during laser scanner identification, no maintenance is required. However, if the anomaly is not accidental, it indicates a potential malfunction in accuracy, necessitating timely maintenance. This effectively prevents frequent warnings from the road surface damage identification system due to occasional laser scanner malfunctions, improves the accuracy of laser scanner monitoring, and further ensures the stable and efficient operation of the laser scanner.

[0023] This invention provides, for example Figure 2The method for identifying road surface damage based on a laser scanner, as shown, includes the following steps: S1. A laser beam is generated by a laser scanner and directed towards the target area on the road surface. S2. Collect laser characteristic information of the laser scanner in the highway pavement damage identification system when identifying highway pavement damage; S3. After the laser beam intersects with the road surface, it is reflected and returns to the laser scanner. The time from emission to reflection of the laser beam is measured, which is the optical path time. The round-trip distance of the laser beam is calculated based on the optical path time and the known speed of light. S4. Collect linearity information of the laser scanner in the highway pavement damage identification system when identifying highway pavement damage. S5. The laser characteristic information and linearity information processed by the laser scanner when identifying road surface damage are comprehensively analyzed to generate an identification index. S6. When the laser scanner identifies the damage to the road surface, it compares and analyzes the identification index generated with the pre-set identification index reference threshold to generate a high-hazard identification signal or a low-hazard identification signal. After receiving the high-hazard identification signal generated by the laser scanner when identifying the damage to the road surface, it establishes an analysis set for several identification indices generated by the laser scanner during subsequent operation to conduct a comprehensive analysis and determine the abnormal state of the laser scanner. S7. Determine the horizontal and vertical directions of the laser beam. Based on the distance and angle measurement results, calculate the three-dimensional coordinates of the target point, namely the horizontal position, vertical position, and height of the target. Organize the acquired three-dimensional coordinate data into a point cloud. Analyze the point cloud data to detect and identify road surface damage, and determine the location, type, and severity of the road surface damage. The highway pavement damage identification method based on a laser scanner provided in this embodiment of the invention is implemented through the aforementioned highway pavement damage identification system based on a laser scanner. For details of the specific method and process of the highway pavement damage identification method based on a laser scanner, please refer to the aforementioned embodiment of the highway pavement damage identification system based on a laser scanner, which will not be repeated here.

[0024] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0025] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0026] It should be noted that, in this document, the use of relational terms such as "first" and "second" is merely for distinguishing one entity or operation from another, and does not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0027] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0028] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0029] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0030] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0031] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0032] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0033] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A highway pavement damage identification system based on a laser scanner, characterized in that, include: The laser beam emitting module generates a laser beam through a laser scanner, directing the laser beam toward the target area on the road surface. The beam emission information acquisition unit is used to acquire laser characteristic information of the laser scanner in the highway pavement damage identification system when identifying damage to the highway pavement. After acquisition, the laser characteristic information is processed and uploaded to the server. The laser beam reflection module reflects the laser beam after it intersects with the road surface, returning it to the laser scanner. The time measurement module is used to measure the time it takes for a laser beam to travel from emission to reflection, i.e., the optical path time. The distance calculation module calculates the round-trip distance of the laser beam based on the optical path time and the known speed of light. The calculation result acquisition unit is used to acquire linearity information of the laser scanner in the highway pavement damage identification system when identifying highway pavement damage. After acquisition, the linearity information is processed and uploaded to the server. The server comprehensively analyzes the laser characteristics and linearity information processed by the laser scanner when identifying road surface damage, and generates an identification index. The comparison and analysis unit compares and analyzes the identification index generated by the laser scanner when identifying road surface damage with a pre-set identification index reference threshold to generate a high-hazard identification signal or a low-hazard identification signal. After receiving the high-risk identification signal generated by the laser scanner when identifying road surface damage, the comprehensive analysis unit establishes an analysis set based on several identification indices generated by the server during the subsequent operation of the laser scanner to perform comprehensive analysis and determine the abnormal state of the laser scanner. An angle measurement module determines the horizontal and vertical directions of the laser beam; The three-dimensional coordinate calculation module calculates the three-dimensional coordinates of the target point, namely the horizontal position, vertical position, and height of the target, based on the distance measurement results and angle measurement results. The data acquisition module organizes the acquired 3D coordinate data into a point cloud; The data analysis module analyzes point cloud data to detect and identify road surface damage, and to determine the location, type, and severity of the damage.

2. The highway pavement damage identification system based on a laser scanner according to claim 1, characterized in that, The laser characteristic information used by the laser scanner to identify road surface damage includes the laser pulse frequency anomaly concealment coefficient and the scanning speed variation coefficient. After acquisition, the laser pulse frequency anomaly concealment coefficient and the scanning speed variation coefficient used by the laser scanner to identify road surface damage are respectively calibrated by the beam emission information acquisition unit. and .

3. The highway pavement damage identification system based on a laser scanner according to claim 2, characterized in that, The logic for obtaining the laser pulse frequency anomaly concealment coefficient is as follows: A101. Obtain the optimal laser pulse frequency range for using a laser scanner to identify road surface damage, and calibrate the optimal laser pulse frequency range as follows: ; A102. Obtain the actual laser pulse frequencies at different time intervals within time T when using a laser scanner to identify road surface damage, and calibrate the actual laser pulse frequencies as follows: , v This indicates the number of the actual laser pulse frequencies at different times within time T when the laser scanner identifies road surface damage. v =1, 2, 3, 4, ... s , s It is a positive integer; A103. When using a laser scanner to identify road surface damage, the actual laser pulse frequencies acquired within time T that are not within the optimal laser pulse frequency range are recalibrated as follows: , This indicates the number of the actual laser pulse frequency that is not within the optimal laser pulse frequency range, acquired within time T when the laser scanner is identifying road surface damage. , It is a positive integer; A104. Calculate the laser pulse frequency anomaly concealment coefficient. The expression for the calculation is: In the formula, .

4. The highway pavement damage identification system based on a laser scanner according to claim 3, characterized in that, The logic for obtaining the scanning speed variation coefficient is as follows: B101. Obtain the actual scanning speed of the laser scanner at different time intervals within time T when identifying road surface damage, and calibrate the actual scanning speed as... , x This indicates the number representing the actual scanning speed of the laser scanner at different time points within time T when identifying road surface damage. x =1, 2, 3, 4, ... m , m It is a positive integer; B102. Calculate the scanning speed variation coefficient. The expression for the calculation is: , m This represents the total number of actual scanning speeds acquired within time T when a laser scanner identifies road surface damage.

5. The highway pavement damage identification system based on a laser scanner according to claim 4, characterized in that, The linearity information of the laser scanner in identifying road surface damage includes the optical path time offset coefficient. After acquisition, the optical path time offset coefficient for identifying road surface damage is calibrated by the calculation result acquisition unit. .

6. The highway pavement damage identification system based on a laser scanner according to claim 5, characterized in that, The logic for obtaining the optical path time offset coefficient is as follows: C101. Obtain the initial ratio constant between the time travel and the actual distance during laser scanner identification of road surface damage, and calibrate the initial ratio constant as follows: ; C102. When using a laser scanner to identify road surface damage, acquire several actual ratio constants generated within time T for each beam's optical path time compared to the actual distance, and calibrate these actual ratio constants as follows: , y This represents the numbering of several actual ratio constants generated within time T for each beam travels through the optical path time compared to the actual distance when a laser scanner identifies road surface damage. y =1, 2, 3, 4, ... n , n It is a positive integer; C103. Calculate the optical path time offset coefficient. The expression for the calculation is: .

7. The highway pavement damage identification system based on a laser scanner according to claim 6, characterized in that, The server processes the laser pulse frequency anomaly concealment coefficient when the laser scanner identifies road surface damage. Scanning speed variation coefficient and optical path time offset coefficient Afterwards, , as well as Formulating the data to generate a recognition index The formula used is: In the formula, , , These are the laser pulse frequency anomaly concealment coefficients. Scanning speed variation coefficient and optical path time offset coefficient The preset proportional coefficient, and , , All are greater than 0.

8. The highway pavement damage identification system based on a laser scanner according to claim 7, characterized in that, The comparison and analysis unit compares the recognition index generated by the laser scanner when identifying road surface damage with a pre-set reference threshold for the recognition index. The results of the comparison and analysis are as follows: If the identification index is greater than or equal to the identification index reference threshold, a high-risk identification signal is generated by the comparison analysis unit and transmitted to the comprehensive analysis unit. If the identification index is less than the identification index reference threshold, a low-risk identification signal is generated by the comparison analysis unit and transmitted to the comprehensive analysis unit.

9. The highway pavement damage identification system based on a laser scanner according to claim 7, characterized in that, After receiving the high-risk identification signal generated by the laser scanner when identifying road surface damage, the comprehensive analysis unit establishes an analysis set based on several identification indices generated by the server during subsequent operation of the laser scanner, and calibrates the analysis set as follows: Z ,but , j This indicates the identification index number within the analysis set. j =1, 2, 3, 4, ... u , u It is a positive integer; The standard deviation and mean of the recognition index are calculated by analyzing the recognition index within the set, and the standard deviation and mean of the recognition index are respectively calibrated as follows: and ,but: ,but: ; To identify the exponential standard deviation and the average of the identification index Each was compared with a pre-set standard deviation reference threshold. and the preset limited recognition index reference threshold The comparative analysis was performed, and the results are as follows: like If an accidental signal is generated by the comprehensive analysis unit and transmitted to the mobile terminal, the mobile terminal will notify the relevant road surface inspection personnel that an accidental anomaly has occurred when the laser scanner is identifying road surface damage. No maintenance or management of the laser scanner is required. like or If the signal is not accidental, the comprehensive analysis unit will generate a non-accidental signal and transmit it to the mobile terminal. The mobile terminal will then prompt the relevant road surface inspection personnel that the laser scanner is not encountering an accidental anomaly when it is identifying road surface damage, and that the laser scanner needs to be maintained and managed in a timely manner.

10. A method for identifying road surface damage based on a laser scanner, implemented by the road surface damage identification system based on a laser scanner as described in any one of claims 1-9, characterized in that, Includes the following steps: S1. A laser beam is generated by a laser scanner and directed towards the target area on the road surface. S2. Collect laser characteristic information of the laser scanner in the highway pavement damage identification system when identifying highway pavement damage; S3. After the laser beam intersects with the road surface, it is reflected and returns to the laser scanner. The time from emission to reflection of the laser beam is measured, which is the optical path time. The round-trip distance of the laser beam is calculated based on the optical path time and the known speed of light. S4. Collect linearity information of the laser scanner in the highway pavement damage identification system when identifying highway pavement damage. S5. The laser characteristic information and linearity information processed by the laser scanner when identifying road surface damage are comprehensively analyzed to generate an identification index. S6. When the laser scanner identifies the damage to the road surface, it compares and analyzes the identification index generated with the pre-set identification index reference threshold to generate a high-hazard identification signal or a low-hazard identification signal. After receiving the high-hazard identification signal generated by the laser scanner when identifying the damage to the road surface, it establishes an analysis set for several identification indices generated by the laser scanner during subsequent operation to conduct a comprehensive analysis and determine the abnormal state of the laser scanner. S7. Determine the horizontal and vertical directions of the laser beam. Based on the distance and angle measurement results, calculate the three-dimensional coordinates of the target point, namely the horizontal position, vertical position, and height of the target. Organize the acquired three-dimensional coordinate data into a point cloud. Analyze the point cloud data to detect and identify road surface damage, and determine the location, type, and severity of the road surface damage.

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