Anti-vibration grid laser projection and acquisition device for pavement detection

Abstract

The invention relates to the technical field of road surface detection, in particular to an anti-vibration grid laser projection and acquisition device for road surface detection, comprising: a frame body assembly including a first bracket, a second bracket, a rotating lock catch and a mounting bracket; by integrating an anti-vibration suspension frame body and a laser projection and high-frame-rate image acquisition system which can be automatically adjusted, continuous and rapid scanning detection on a road surface in a normal driving state of a vehicle is realized; compared with a traditional fixed-point measurement method or a method depending on an expensive imported detection vehicle, the device is relatively simple in structure, cost is remarkably reduced, installation is convenient and fast, the device can be rapidly deployed on a common vehicle, and localization and popularization of detection equipment are achieved; by means of the automatic working process, the workload of manual operation and subsequent data analysis is greatly reduced, the detection efficiency and the data consistency are remarkably improved, and due to the fact that the detection speed is high, road closing or low-speed driving is not needed, interference to normal traffic flow is reduced to the maximum extent.

Description

Technical Field

[0001] This invention relates to the field of road surface inspection technology, and in particular to a vibration-resistant grid laser projection and acquisition device for road surface inspection. Background Technology

[0002] In recent years, my country's road network construction has progressed rapidly, with the mileage of trunk highways such as expressways, national highways, and provincial highways continuing to grow rapidly, forming a widely covered and interconnected road network system. While this has greatly promoted economic and social development and facilitated people's travel, it has also increasingly highlighted the pressure on the later-stage maintenance of road infrastructure. The massive scale of the road network necessitates regular, systematic, and efficient pavement inspection and maintenance to maintain the service level and service life of roads. Therefore, strengthening the scientific planning and systematic construction of road maintenance has become a key link in ensuring the long-term safe, stable, and efficient operation of the highway network. This is of great significance for effectively improving the overall quality of highways, preventing early damage, and reducing the total life-cycle cost. Among many road technical indicators, pavement smoothness is one of the core performance indicators for evaluating the quality of road construction and guiding later-stage maintenance management. Substandard pavement smoothness directly leads to bumpy driving, increased noise, and reduced comfort. More importantly, it significantly increases the dynamic impact load on the pavement structure, thereby accelerating the development of fatigue damage, crack propagation, and rutting, ultimately leading to premature deterioration of the road structure's load-bearing capacity. This will not only significantly shorten the normal maintenance cycle of roads and increase the economic cost of frequent repairs, but may also bring traffic safety hazards and cause greater indirect economic losses. Therefore, continuous and accurate monitoring and evaluation of road surface smoothness, and the implementation of scientific and timely maintenance interventions based on this, is a crucial and urgent task in my country's current and future road maintenance management.

[0003] In existing technologies, the methods for measuring road surface smoothness have many shortcomings, such as low detection efficiency, high labor intensity, traffic disruption, reliance on imported testing instruments, and high prices. How to quickly and efficiently detect road surfaces and complete road surface classification has become an important research topic in the transportation industry. Summary of the Invention

[0004] The purpose of this invention is to provide a vibration-resistant grid laser projection and acquisition device for road surface inspection in order to solve the above-mentioned problems, thereby improving the problem of low detection efficiency in the flatness measurement method.

[0005] This invention achieves the above-mentioned objective through the following technical solution: a vibration-resistant grid laser projection and acquisition device for road surface detection, comprising: The frame assembly includes a first bracket, a second bracket, a rotating latch, and a mounting bracket. There are two rotating latches, which are respectively fixedly connected to the two circumferential surfaces of the first bracket. The second bracket is installed in the two rotating latches, and the mounting bracket is rotatably connected to the surface of the second bracket. The first bracket, the second bracket, and the mounting bracket are all U-shaped structures. A connecting assembly includes two first straps, a second strap, and a second hook. The two first straps are respectively fixedly connected to the two circumferential surfaces of the first bracket, and the two first hooks are respectively fixedly connected to the ends of the two first straps. Both first hooks are connected to the vehicle body. The two second straps are respectively fixedly connected to the two circumferential surfaces of the second bracket, and the two second hooks are respectively fixedly connected to the ends of the two second straps. Both second hooks are connected to the vehicle body. Two locking blocks are provided, and the two locking blocks are respectively fixedly connected to the two circumferential surfaces of the mounting bracket; A laser assembly, comprising a laser pan-tilt unit, a rotating frame, and a laser generator, wherein the laser pan-tilt unit is fixedly connected to the lower end of one of the locking blocks, the rotating frame is rotatably connected to the lower end of the laser pan-tilt unit, and the laser generator is rotatably connected inside the rotating frame; and The shooting assembly includes a camera gimbal, a circular platform, a first rotating frame, a second rotating frame, a camera, a first servo motor, and a second servo motor. The camera gimbal is fixedly connected to the lower end of another locking block. The circular platform is fixedly connected to the lower end of the camera gimbal. The first rotating frame is rotatably connected to the surface of the circular platform. The second rotating frame is rotatably connected to the surface of the first rotating frame. The camera is fixedly connected to the surface of the second rotating frame. The first servo motor is installed inside the circular platform, and its output end is connected to the first rotating frame. The second servo motor is installed inside the first rotating frame, and its output end is connected to the second rotating frame.

[0006] Preferably, the laser generator is equipped with a red laser emitting module, and the vehicle body is equipped with a control processor unit and sensors. The control processor unit is equipped with a control processing module, and the sensors are signal-connected to the control processor module. The sensors monitor the vehicle speed, and the control processor module controls the operation of the first and second servo motors. The red laser emitting module projects linear structured light onto the road surface, and the red laser reflects and deforms into a light strip after passing through the road surface. The control processor module controls the camera's shooting frequency and deflection angle, causing the camera to tilt and align with the light strip, and the camera captures the light strip. The control processor module is equipped with an image processing module, which processes the images captured by the camera.

[0007] Preferably, the laser generator emits multiple parallel laser lines perpendicular to the road surface, with the light rays perpendicular to the direction of travel, and the camera takes pictures of the laser lines on the road surface at a certain deflection angle.

[0008] Preferably, the control processor unit includes a control system. The control card controls the rotation angle of the gimbal, determines the shooting angle of the camera, calibrates the camera, detects the vehicle starting to move at a constant speed, the sensor transmits wheel data, the control card calculates the camera shooting frequency based on the vehicle speed, if the camera detects a laser line, the camera starts to acquire images; if no laser line is detected, the camera angle is adjusted. Software integrated in the SDK deblurs the image, the camera transmits data back to the control card, the control card processes the image, and finally calculates the IRI value.

[0009] Preferably, the image processing module uses an improved ZS algorithm to process images. The improved ZS algorithm includes a skeleton extraction stage, a skeleton refinement stage, and a spur removal stage. In the skeleton extraction stage: after camera calibration, images are captured, cropped, and the laser stripe target area is retained. Appropriate filtering is applied to process the image, eliminating noise. Laser extraction is performed using HSV specific color separation to remove reflection interference. In the skeleton refinement stage: the image is refined iteratively, processing the annular closed regions. If closed regions exist, they are filled, and image refinement continues. If no closed regions exist, logical operations are added for different redundant pixels, organically integrating them with the ZS refinement algorithm. The improved ZS refinement algorithm forms a skeleton with a single pixel width. Breakpoints may appear in the main skeleton section; these breaks are repaired. The process involves several steps: First, restoring the continuous skeleton structure. Second, removing burrs: Small branches are removed from the thinned image. Endpoints and nodes are found in the skeleton image through convolution and thresholding. Burr removal rules are defined for each node. All burr points are found by traversing the endpoints and directional chain codes. These burrs are grouped according to the nodes. Difference operations are then performed on all burrs under the same node to remove burrs while retaining the main structure. Burrs are processed in stages: when there is only one node, if the number of endpoints is 3, the burr with the fewest pixels is deleted; if the number of endpoints is greater than 3, the two burrs with the most pixels are retained; when there are two or more nodes, only the longest burr is retained for each node. The process is repeated until the skeleton has only two endpoints, at which point burr processing is complete. Difference comparison is then performed to remove burrs, and finally, the image is output.

[0010] Preferably, when calculating the IRI value, the IRI calculation method is improved. Frequency domain filtering effectively removes low-frequency trends and high-frequency noise by using Fourier transform to analyze the frequency components in the road profile data of the original signal, while retaining the mid-frequency fluctuations related to driving comfort. Then, the cumulative amplitude analysis helps to remove irrelevant low-frequency and high-frequency components by using the cumulative value of amplitude changes, further improving the accuracy of the smoothness calculation. This improved algorithm can better simulate the driver's perception experience and accurately calculate the IRI value that reflects the road surface quality.

[0011] Preferably, the laser generator is a 650nm laser, and the laser gimbal, camera gimbal, and truncated cone are all made of carbon fiber.

[0012] The beneficial effects of this invention are: 1. This solution integrates an anti-vibration suspension frame, an automatically adjustable laser projection system, and a high frame rate image acquisition system to achieve continuous and rapid scanning and detection of the road surface under normal vehicle driving conditions. Compared with traditional fixed-point measurement or methods relying on expensive imported inspection vehicles, this device has a relatively simple structure, significantly reduced costs, and is easy to install, enabling rapid deployment on ordinary vehicles and realizing the localization and popularization of inspection equipment. Its automated workflow, including automatic tracking, shooting, image processing, and IRI calculation, greatly reduces the workload of manual operation and subsequent data analysis, significantly improving detection efficiency and data consistency. At the same time, due to its fast detection speed and the fact that it does not require road closures or low-speed driving, it minimizes interference with normal traffic flow.

[0013] 2. This solution employs laser stripe image processing technology based on an improved ZS algorithm. This technology effectively overcomes environmental interference such as road surface reflections and stains, accurately extracting sub-pixel-level light strip centerlines to obtain high-precision road profile data. Furthermore, by improving the IRI calculation algorithm and introducing frequency domain filtering and cumulative amplitude analysis, the final smoothness index more accurately reflects road surface fluctuations affecting driving comfort, and the calculation results are closer to the actual driving experience. Simultaneously, the device features comprehensive vibration-resistant design from its mechanical structure (such as the U-shaped floating frame and lightweight carbon fiber gimbal) to its control logic and vehicle speed-synchronized shooting frequency. This effectively isolates measurement errors caused by vehicle driving bumps, ensuring the stability and reliability of data collected under real road driving conditions. This provides high-quality, reliable data support for road maintenance management, assisting in scientific maintenance decision-making. Attached Figure Description

[0014] Figure 1 This is a perspective view of the present invention; Figure 2 This is a perspective view of the camera gimbal described in this invention; Figure 3This is a flowchart of the control system in this invention; Figure 4 This is a block diagram of the composition structure of the acquisition system in this invention; Figure 5 This is a schematic diagram of the installation of the road data acquisition device in this invention; Figure 6 This is a flowchart of the improved ZS algorithm in this invention.

[0015] In the diagram: 1. First bracket; 101. Protective cotton ring; 102. First strap; 103. First hook; 2. Second bracket; 201. Second strap; 202. Second hook; 3. Rotary lock; 4. Mounting bracket; 401. Locking block; 402. Laser pan-tilt head; 403. Rotating frame; 404. Laser generator; 5. Camera pan-tilt head; 501. Frustum; 502. First rotating frame; 503. Second rotating frame; 504. Camera. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] In practical implementation: such as Figures 1-6 As shown, a vibration-resistant grid laser projection and acquisition device for road surface detection includes: The frame assembly includes a first bracket 1, a second bracket 2, a rotating latch 3, and a mounting bracket 4. There are two rotating latches 3, which are respectively fixedly connected to the two circumferential surfaces of the first bracket 1. The second bracket 2 is installed in the two rotating latches 3. The mounting bracket 4 is rotatably connected to the surface of the second bracket 2. The first bracket 1, the second bracket 2, and the mounting bracket 4 are all U-shaped structures. The connecting assembly includes two first straps 102 and 203, a second strap 201, and a second hook 202. The two first straps 102 are fixedly connected to the two circumferential surfaces of the first bracket 1, and two protective cotton rings 101 are fixedly connected to the circumferential surface of the first bracket 1. The two first hooks 103 are fixedly connected to the ends of the two first straps 102, and both first hooks 103 are connected to the vehicle body. The two second straps 201 are fixedly connected to the two circumferential surfaces of the second bracket 2, and the two second hooks 202 are fixedly connected to the ends of the two second straps 201, and both second hooks 202 are connected to the vehicle body. Two locking blocks 401 are provided, and the two locking blocks 401 are respectively fixedly connected to the two circumferential surfaces of the mounting bracket 4; The laser assembly includes a laser pan-tilt unit 402, a rotating frame 403, and a laser generator 404. The laser pan-tilt unit 402 is fixedly connected to the lower end of one of the locking blocks 401, the rotating frame 403 is rotatably connected to the lower end of the laser pan-tilt unit 402, and the laser generator 404 is rotatably connected inside the rotating frame 403. The shooting assembly includes a camera gimbal 5, a truncated cone 501, a first rotating frame 502, a second rotating frame 503, a camera 504, a first servo motor, and a second servo motor. The camera gimbal 5 is fixedly connected to the lower end of another locking block 401. The truncated cone 501 is fixedly connected to the lower end of the camera gimbal 5. The first rotating frame 502 is rotatably connected to the surface of the truncated cone 501. The second rotating frame 503 is rotatably connected to the surface of the first rotating frame 502. The camera 504 is fixedly connected to the surface of the second rotating frame 503. The first servo motor is installed inside the truncated cone 501, and its output end is connected to the first rotating frame 502. The second servo motor is installed inside the first rotating frame 502, and its output end is connected to the second rotating frame 503.

[0018] In this embodiment, the device includes a frame assembly for mounting and vibration damping, which consists of a first bracket 1, a second bracket 2, a rotating latch 3, and a mounting bracket 4. The two rotating latches 3 are respectively fixed to the two circumferential surfaces of the first bracket 1, and the second bracket 2 is installed in the two rotating latches 3, so that the second bracket 2 has a certain degree of floating freedom relative to the first bracket 1 to buffer vibrations from the vehicle body. The mounting bracket 4 is rotatably connected to the surface of the second bracket 2 and is used to support the core measuring component. The first bracket 1, the second bracket 2, and the mounting bracket 4 are all designed with a U-shaped structure to provide a stable mounting base and facilitate suspension on the side of the vehicle body. To securely and easily disassemble the entire device to the testing vehicle, a connecting assembly is provided. This assembly includes two first straps 102, two first hooks 103, two second straps 201, and two second hooks 202. The two first straps 102 are respectively fixed to both sides of the first bracket 1, and their first hooks 103 are used to hook onto the top or a high fixing point of the vehicle body. The two second straps 201 are respectively fixed to both sides of the second bracket 2, and their second hooks 202 are used to hook onto the side or a low fixing point of the vehicle body. This multi-point suspension method effectively suppresses the swaying of the device during vehicle movement. A locking block 401 is fixedly connected to the circumferential surface of each side of the mounting bracket 4. The core measuring component of the device consists of a laser assembly and an imaging assembly. The laser assembly includes a laser gimbal 402, a rotating frame 403, and a laser generator 404. The laser gimbal 402 is fixed to the lower end of one of the locking blocks 401. The rotating frame 403 is rotatably connected to the lower end of the laser gimbal 402 for pitch adjustment, and the laser generator 404 is rotatably connected inside the rotating frame 403 for roll adjustment, thereby achieving precise alignment of the laser projection angle. The imaging assembly includes a camera gimbal 5, a frustum 501, a first rotating frame 502, a second rotating frame 503, a camera 504, a first servo motor, and a second servo motor. The camera gimbal 5 is fixed to the other... At the lower end of the locking block 401, the frustum 501 is fixed to the lower end of the camera gimbal 5 for horizontal rotation adjustment. The first rotating frame 502 is rotatably connected to the surface of the frustum 501 and is driven by the first servo motor to perform pitch movement. The second rotating frame 503 is rotatably connected to the surface of the first rotating frame 502 and is driven by the second servo motor to perform roll movement. The camera 504 is fixed to the surface of the second rotating frame 503, thereby realizing all-round automatic control of the camera's shooting angle and ensuring continuous and stable shooting of the laser light strip on the road surface. This solves the problems of low efficiency, high labor intensity, traffic interference, and reliance on expensive imported equipment in existing road surface smoothness measurement methods.

[0019] like Figures 1-6As shown, a red laser emitting module is installed inside the laser generator 404. A control processor unit and sensors are installed inside the vehicle body. The control processor unit contains a control processing module. The sensors are connected to the control processor module. The sensors monitor the vehicle speed. The control processor module controls the operation of the first and second servo motors. The red laser emitting module projects linear structured light onto the road surface. The red laser reflects and deforms into a light strip after passing through the road surface. The control processor module controls the shooting frequency and deflection angle of the camera 504, causing the camera to tilt and align with the light strip. The camera 504 then captures the light strip. An image processing module is installed inside the control processor module to process the images captured by the camera 504.

[0020] In this embodiment: a red laser emitting module is installed inside the laser generator 404 for projecting linear structured light onto the road surface; a control processor unit and a sensor for monitoring vehicle speed are installed inside the detection vehicle; the control processor unit has a control processing module inside; the sensor is signal-connected to the control processor module to monitor and provide feedback on the vehicle speed in real time; the control processor module automatically calculates and controls the operation of the first and second servo motors based on the received vehicle speed signal, thereby dynamically adjusting the deflection angle of the camera 504 to track the light band; after the linear structured light projected by the red laser emitting module illuminates the road surface, it will produce a reflected and deformed light band due to the unevenness of the road surface; the control processor module synchronously controls the shooting frequency of the camera 504 and the deflection angle adjusted by the servo motors, so that the camera lens is always tilted to shoot at the deformed light band; the control processor module also has an image processing module installed inside, which is used to process the image containing the deformed light band captured by the camera 504 to extract the road surface contour information.

[0021] like Figures 1-6 As shown, the laser generator 404 emits multiple parallel laser lines perpendicular to the road surface, with the light rays perpendicular to the direction of travel. The camera 504 takes pictures of the laser lines on the road surface at a certain deflection angle.

[0022] In this embodiment, the laser generator 404 is adjusted to be perpendicular to the road surface and projects multiple parallel laser lines. The arrangement of these laser lines on the road surface is perpendicular to the direction of vehicle travel. The camera 504 then takes pictures of these laser lines on the road surface at a pre-calibrated fixed deflection angle. This tilted shooting configuration allows the camera to clearly capture the lateral torsion deformation of the laser lines caused by the undulation of the road surface. This deformation directly reflects the longitudinal profile information of the road surface along the direction of travel.

[0023] like Figures 1-6As shown, the control processor unit contains a control system. The control card controls the rotation angle of the gimbal, determines the shooting angle of the camera 504, calibrates the camera 504, and the detection vehicle begins to move at a constant speed. The sensor transmits wheel data back, and the control card calculates the shooting frequency of the camera 504 based on the vehicle speed. If the camera 504 detects a laser line, it begins to acquire images. If no laser line is detected, the angle of the camera 504 continues to be adjusted. Software integrated in the SDK deblurs the image. The camera 504 transmits the data back to the control card, which processes the image and finally calculates the IRI value.

[0024] In this embodiment: the control processor unit is equipped with a control system. This system first controls the rotation of the camera gimbal 5 and the servo system through the control card to determine the optimal initial shooting angle of the camera 504 and complete the calibration of the camera's intrinsic and extrinsic parameters. After the detection vehicle starts moving at a constant speed, the sensors transmit data such as wheel speed in real time. The control card calculates the matching shooting frequency required by the camera 504 based on the real-time vehicle speed to achieve equal spatial interval sampling. The system continuously detects whether laser lines appear in the image. If detected, the camera 504 starts to acquire image sequences at the set frequency. If not detected, the control card continues to adjust the camera angle until the detection is successful. During image acquisition, motion blur is deblurred in real time through software algorithms integrated in the SDK to improve image clarity. The camera 504 transmits the processed image data back to the control card, which further processes the image and finally calculates the International Roughness Index (IRI) value based on the processed road surface contour data.

[0025] like Figures 1-6As shown, the image processing module uses an improved ZS algorithm to process images. The improved ZS algorithm includes a skeleton extraction stage, a skeleton refinement stage, and a spur removal stage. In the skeleton extraction stage: after the camera is calibrated to 504, the image is captured, cropped, and the laser stripe target area is retained. Appropriate filtering is applied to process the image, eliminating noise. Laser extraction is performed using HSV specific color separation to remove reflection interference. In the skeleton refinement stage: the image is refined iteratively, processing the annular closed regions. If closed loops exist, they are filled, and image refinement continues. If no closed loops exist, logical operations are added for different redundant pixels, organically integrating them with the ZS refinement algorithm. The improved ZS refinement algorithm forms a skeleton with a single pixel width. Breakpoints may appear in the main skeleton section; these breaks are repaired. The process involves several steps: First, restoring the continuous skeleton structure. Second, removing burrs: Small branches are removed from the thinned image. Endpoints and nodes are found in the skeleton image through convolution and thresholding. Burr removal rules are defined for each node. All burr points are found by traversing the endpoints and directional chain codes. These burrs are grouped according to the nodes. Difference operations are then performed on all burrs under the same node to remove burrs while retaining the main structure. Burrs are processed in stages: when there is only one node, if the number of endpoints is 3, the burr with the fewest pixels is deleted; if the number of endpoints is greater than 3, the two burrs with the most pixels are retained; when there are two or more nodes, only the longest burr is retained for each node. The process is repeated until the skeleton has only two endpoints, at which point burr processing is complete. Difference comparison is then performed to remove burrs, and finally, the image is output.

[0026] In this embodiment, the image processing module uses the improved ZS algorithm—the core algorithm for accurately extracting the laser line skeleton from the captured image. This algorithm includes three stages: skeleton extraction, skeleton refinement, and burr removal. In the skeleton extraction stage, after the camera 504 completes calibration and captures the image, it first crops the image to retain only the target area containing the laser stripes. Then, an appropriate filtering method, such as Gaussian filtering, is used to eliminate image noise. Next, the HSV color space model is used to separate and extract the specific red color of the laser, effectively removing interference from ambient light such as road surface reflections. In the skeleton refinement stage, the binarized laser stripe image is refined. An iterative refinement method is used to handle possible closed loops. First, it checks for closed loops; if any are found, the closed loop area is filled before further refinement. For redundant pixels that may be generated by the traditional ZS refinement algorithm, specific logical operations are organically integrated to form an improved ZS refinement algorithm, generating a skeleton with a single pixel width. During this process, breakpoints may appear in the skeleton backbone; the algorithm detects and repairs these breakpoints to restore the continuity of the skeleton. In the spur removal stage, the aim is to remove interfering small branches from the refined skeleton image. Through convolution operations and threshold conditions, all endpoints and nodes are located in the skeleton image. Spur removal rules are formulated for each node; all spur points are found by traversing endpoints and using directional chain codes, and these spurs are grouped according to the connected nodes. Differential operations are performed on all spurs under the same node to remove spurs and retain the main structure. A hierarchical strategy is adopted for spur processing: when the skeleton connects only one node, if the number of endpoints is equal to 3, the spur with the fewest pixels is deleted; if the number of endpoints is greater than 3, the two spurs with the most pixels are retained; when the skeleton connects two or more nodes, each node retains only the longest spur. The process then returns to the first-level iteration until only 2 endpoints remain in the skeleton, indicating that spur removal is complete. Finally, spurs are thoroughly removed through differential comparison, outputting a clean, continuous single-pixel laser skeleton image for subsequent calculations.

[0027] like Figures 1-6 As shown, when calculating the IRI value, the IRI calculation method is improved. Frequency domain filtering effectively removes low-frequency trends and high-frequency noise by using Fourier transform to analyze the frequency components in the road profile data of the original signal, while retaining the mid-frequency fluctuations related to driving comfort. Then, the cumulative amplitude analysis helps to remove irrelevant low-frequency and high-frequency components by using the cumulative value of amplitude changes, further improving the accuracy of the smoothness calculation. This improved algorithm can better simulate the driver's perception experience and accurately calculate the IRI value that reflects the road surface quality.

[0028] In this embodiment: the control processor unit is equipped with a control system. This system first controls the rotation of the camera gimbal 5 and the servo system through the control card to determine the optimal initial shooting angle of the camera 504 and complete the calibration of the camera's intrinsic and extrinsic parameters. After the detection vehicle starts moving at a constant speed, the sensors transmit data such as wheel speed in real time. The control card calculates the matching shooting frequency required by the camera 504 based on the real-time vehicle speed to achieve equal spatial interval sampling. The system continuously detects whether laser lines appear in the image. If detected, the camera 504 starts to acquire image sequences at the set frequency. If not detected, the control card continues to adjust the camera angle until the detection is successful. During image acquisition, motion blur is deblurred in real time through software algorithms integrated in the SDK to improve image clarity. The camera 504 transmits the processed image data back to the control card, which further processes the image and finally calculates the International Roughness Index (IRI) value based on the processed road surface contour data. In calculating the International Road Surface Roughness Index (IRI), the IRI primarily focuses on unevenness within a specific wavelength range. Preprocessing and filtering of the raw data are necessary to remove high-frequency noise and low-frequency trends, retaining only mid-frequency fluctuations relevant to driving comfort. This processing allows the calculated IRI value to more accurately reflect the driver's perceived experience. Low-frequency fluctuations are typically caused by large-scale road surface irregularities, such as potholes or undulations, and do not reflect the vehicle's actual vibration perception. High-frequency fluctuations, on the other hand, may originate from noise or suspension system responses—namely, noise from the measuring equipment itself or the high-frequency response of the vehicle's suspension system. While these noises may manifest as short-wavelength vibrations in the measurement, they do not directly reflect road surface smoothness. To achieve this filtering process, traditional methods typically employ a combination of low-pass and high-pass filters. However, introducing algorithms based on frequency domain and cumulative amplitude analysis can more intelligently determine filtering parameters and achieve more accurate fluctuation separation. Frequency domain filtering effectively removes low-frequency trends and high-frequency noise by analyzing the frequency components in the road profile data using Fourier Transform (FFT) on the original signal, while retaining mid-frequency fluctuations related to driving comfort. Cumulative amplitude analysis, through the cumulative value of amplitude changes, helps remove irrelevant low-frequency and high-frequency components, further improving the accuracy of smoothness calculation. This improved algorithm can better simulate the driver's perceptual experience and accurately calculate the IRI value reflecting road surface quality.

[0029] like Figures 1-6 As shown, the laser generator 404 is a 650nm laser, and the laser gimbal 402, camera gimbal 5, and circular platform 501 are all made of carbon fiber.

[0030] In this embodiment, the laser generator 404 is a red laser with a wavelength of 650nm. This wavelength has good reflectivity on common road surface materials and is relatively safe for the human eye. In order to minimize the weight of the device, reduce inertia, and reduce the impact of vibration while ensuring structural strength, the laser gimbal 402, camera gimbal 5, and truncated cone 501 are all specified to be made of high-rigidity, lightweight carbon fiber material.

[0031] In use, the operator first installs the device onto the side of the vehicle being inspected via the frame assembly. The specific steps are as follows: The first bracket 1 and the second bracket 2 are initially connected via a rotating locking buckle 3; the first hooks 103 at the ends of the two first straps 102 are hooked onto a stable anchor point on or above the vehicle body, and the second hooks 202 at the ends of the two second straps 201 are hooked onto an anchor point below the side of the vehicle body. By adjusting the strap length and tightening, the entire device is securely suspended from the vehicle body, and the mounting bracket 4 is approximately horizontal. Subsequently, the system is powered on and initialized. The control processor unit inside the vehicle is activated. After the system self-test, the operator manually or automatically controls the laser pan-tilt unit 402 and the camera pan-tilt unit 5 via the control software. The angle of the laser generator 404 is adjusted so that it is perpendicular to the road surface and projects multiple red laser lines parallel to the vehicle axle, i.e., perpendicular to the direction of travel. Simultaneously, the angle of camera 504 is adjusted, and the first and second servo motors drive the first rotating frame 502 and the second rotating frame 503 to align the camera with the laser beam illumination area at a predetermined optimal deflection angle, thus completing camera calibration. After preparation, the vehicle begins to travel at a constant speed. During vehicle movement, sensors within the vehicle, such as the vehicle speed sensor, transmit vehicle speed signals to the control processor module in real time. The control processor module dynamically calculates and controls the shooting frequency of camera 504 based on the real-time vehicle speed, ensuring image acquisition at equal spatial intervals; simultaneously, based on preset logic or image feedback, it fine-tunes the servo motors to maintain continuous tracking and focus of the camera on the laser beam. The laser beam illuminates the road surface, forming light bands deformed due to unevenness, and camera 504 continuously captures images of these light bands at a set frequency and angle. The captured image data is transmitted to the control processor unit in real time. The image processing module immediately processes the acquired images, first cropping and color separation to extract the red laser stripes, and then employing an improved ZS algorithm, including skeleton extraction, skeleton thinning, and burr removal, to accurately obtain a single-pixel-wide, continuous laser line centerline skeleton. Based on the processed image sequence, the longitudinal profile elevation data of the road surface is reconstructed. Then, the control processor applies an improved IRI calculation algorithm, combined with frequency domain filtering and cumulative amplitude analysis, to process the profile data and finally calculate the International Roughness Index (IRI) value reflecting the road surface smoothness. During the inspection process, the device's multiple vibration-resistant designs, such as the floating connection frame and the lightweight carbon fiber gimbal, effectively isolate the interference of vehicle vibration on laser projection and image acquisition. No manual intervention is required throughout the process; the inspection vehicle can quickly and continuously complete long-distance road surface smoothness inspection and grading assessment in a single operation.

[0032] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A vibration-resistant grid laser projection and acquisition device for road surface detection, characterized in that, include: The frame assembly includes a first bracket (1), a second bracket (2), a rotating latch (3), and a mounting bracket (4). There are two rotating latches (3), which are respectively fixedly connected to the two circumferential surfaces of the first bracket (1). The second bracket (2) is installed inside the two rotating latches (3). The mounting bracket (4) is rotatably connected to the surface of the second bracket (2). The first bracket (1), the second bracket (2), and the mounting bracket (4) are all U-shaped structures. The connecting component includes two first straps (102) and (203), a second strap (201), and a second hook (202). The two first straps (102) are fixedly connected to the two circumferential surfaces of the first bracket (1), and the two first hooks (103) are fixedly connected to the ends of the two first straps (102). Both first hooks (103) are connected to the vehicle body. The two second straps (201) are fixedly connected to the two circumferential surfaces of the second bracket (2), and the two second hooks (202) are fixedly connected to the ends of the two second straps (201). Both second hooks (202) are connected to the vehicle body. Two locking blocks (401) are provided, and the two locking blocks (401) are respectively fixedly connected to the two circumferential surfaces of the mounting bracket (4); A laser assembly, comprising a laser pan-tilt unit (402), a rotating frame (403), and a laser generator (404), wherein the laser pan-tilt unit (402) is fixedly connected to the lower end of one of the locking blocks (401), the rotating frame (403) is rotatably connected to the lower end of the laser pan-tilt unit (402), and the laser generator (404) is rotatably connected inside the rotating frame (403); and The shooting assembly includes a camera gimbal (5), a truncated cone (501), a first rotating frame (502), a second rotating frame (503), a camera (504), a first servo motor, and a second servo motor. The camera gimbal (5) is fixedly connected to the lower end of another block (401). The truncated cone (501) is fixedly connected to the lower end of the camera gimbal (5). The first rotating frame (502) is rotatably connected to the surface of the truncated cone (501). The second rotating frame (503) is rotatably connected to the surface of the first rotating frame (502). The camera (504) is fixedly connected to the surface of the second rotating frame (503). The first servo motor is installed inside the truncated cone (501). The output end of the first servo motor is connected to the first rotating frame (502). The second servo motor is installed inside the first rotating frame (502). The output end of the second servo motor is connected to the second rotating frame (503). The laser generator (404) is equipped with a red laser emitting module. The vehicle body is equipped with a control processor unit and a sensor. The control processor unit is equipped with a control processing module. The sensor is connected to the control processor module. The sensor monitors the vehicle speed. The control processor module controls the operation of the first servo and the second servo. The red laser emitting module projects a straight structured light onto the road surface. The red laser is reflected and deformed by the road surface. The control processor module controls the shooting frequency and deflection angle of the camera (504) so ​​that the camera is tilted and aligned with the light strip. The camera (504) captures the light strip. The control processor module is equipped with an image processing module. The control processor module processes the image captured by the camera (504).

2. The anti-vibration grid laser projection and acquisition device for road surface detection according to claim 1, characterized in that: The laser generator (404) emits multiple parallel laser lines perpendicular to the road surface, with the light rays perpendicular to the direction of travel. The camera (504) takes pictures of the laser lines on the road surface at a certain deflection angle.

3. The anti-vibration grid laser projection and acquisition device for road surface detection according to claim 2, characterized in that: The control processor unit is equipped with a control system. The control card controls the rotation angle of the gimbal and determines the shooting angle of the camera (504). The camera (504) is calibrated, the detection vehicle starts to move at a constant speed, the sensor transmits wheel data, the control card calculates the shooting frequency of the camera (504) based on the vehicle speed, if the camera (504) detects laser lines, the camera (504) starts to acquire images, if no laser lines are detected, the angle of the camera (504) is adjusted, the software integrated in the SDK deblurs the image, the camera (504) transmits the data back to the control card, the control card processes the image, and finally calculates the IRI value.

4. The anti-vibration grid laser projection and acquisition device for road surface detection according to claim 3, characterized in that: The image processing module uses an improved ZS algorithm to process images. The improved ZS algorithm includes a skeleton extraction stage, a skeleton refinement stage, and a burr removal stage. Skeleton extraction stage: After the camera (504) is calibrated, the image is captured, the image is cropped, the laser stripe target area is retained, and the image is processed by appropriate filtering to eliminate noise in the image. The laser is extracted using HSV specific color separation extraction to remove reflective interference. Skeleton Refinement Stage: The image is refined iteratively, processing circular closed regions and checking for closed loops. If a closed loop exists, it is filled, and image refinement continues. If no closed loop exists, logical processing is added for different redundant pixels, organically integrating it with the ZS refinement algorithm. The improved ZS refinement algorithm forms a skeleton with a single pixel width. Discontinuities may appear in the main skeleton; these are repaired to restore a continuous skeleton structure. Spur Removal Stage: Small branches are removed from the refined image. Through convolution operations and threshold conditions, endpoints and nodes are found in the skeleton image. Spur removal rules are formulated for the nodes. All spur points are found by traversing the endpoints and direction chain codes. These spurs are grouped according to the nodes. Then, a difference operation is performed on all spurs under the same node to remove spurs and retain the main body. The spurs are processed in stages. When there is only one node, if the number of endpoints is equal to 3, the spur with the fewest pixels is deleted. If the number of endpoints is greater than 3, the two spurs with the most pixels are retained. When there are two or more nodes, only the longest spur is retained for each node. The process is then repeated until the skeleton has only 2 endpoints. The spurs are then removed by difference comparison. Finally, the image is output.

5. The anti-vibration grid laser projection and acquisition device for road surface detection according to claim 4, characterized in that: When calculating the IRI value, the IRI calculation method is improved. Frequency domain filtering effectively removes low-frequency trends and high-frequency noise by using Fourier transform to analyze the frequency components in the road profile data of the original signal, while retaining the mid-frequency fluctuations related to driving comfort. The cumulative amplitude analysis helps to remove irrelevant low-frequency and high-frequency components by using the cumulative value of amplitude changes, further improving the accuracy of the smoothness calculation. This improved algorithm can better simulate the driver's perception experience and accurately calculate the IRI value that reflects the road surface quality.

6. The anti-vibration grid laser projection and acquisition device for road surface detection according to claim 5, characterized in that: The laser generator (404) is a 650nm laser, and the laser gimbal (402), camera gimbal (5) and truncated cone (501) are all made of carbon fiber.

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