Tactile sense-based method and system for detecting tiny cracks on tire surface and predicting crack propagation direction

Abstract

The invention relates to the technical field of tire detection, in particular to a method and system for detecting small cracks on the surface of a tire and predicting the crack propagation direction based on tactile sensation. According to the method, a three-dimensional displacement table and a three-way force sensor are combined for use, and the sensor is accurately controlled to scan the surface of a tire and collect stress data in X, Y and Z directions. Extracting a crack region through an image processing technology including Canny edge detection and morphological operation; and further calculating the stress gradient, and obtaining the stress change direction of the crack region by using a Sobel operator. And the main trend of the crack is extracted by combining a Hough transformation technology, so that the crack propagation direction is predicted. By judging whether crack propagation enters a preset dangerous area or not, the system automatically sends out an early warning signal to remind an operator to take necessary maintenance measures. The technology can detect small cracks with high precision and predict the expansion trend of the small cracks, so that the tire safety management level is effectively improved, and potential safety hazards and loss caused by the cracks are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of tire detection, and in particular to a method and system for detecting fine cracks on a tire surface based on tactile sensation and predicting the crack propagation direction. Background Art

[0002] As the requirements for material performance and reliability in the industrial field continue to increase, especially in the production and use of automobile tires, the detection and expansion prediction of tire surface cracks has become an important technical topic. Tires are key components of automobiles, and their surface cracks not only affect the safety and service life of tires, but may also cause serious traffic accidents. Therefore, early detection and accurate prediction of the expansion direction of small cracks on the tire surface are of great significance for ensuring traffic safety, improving tire performance and reducing maintenance costs.

[0003] Traditional tire crack detection methods mostly rely on manual visual inspection, ultrasonic detection or optical image processing technology. Although manual inspection can detect larger cracks, it has certain limitations for the detection of tiny cracks or inner cracks, and the operation efficiency is low, and the false detection rate and missed detection rate are high. Although the existing automated detection methods based on optical imaging can detect cracks more accurately, they also face problems such as lighting changes, unstable image clarity, and complex crack textures. These methods are difficult to form effective image features for tiny cracks or areas with similar textures, resulting in limited detection accuracy.

[0004] As an emerging non-destructive testing technology, tactile sensing technology has the advantages of high sensitivity, real-time and convenience. The Chinese invention patent application (publication number: CN116818172A, publication date: 2023-09-29) discloses a flexible interface detection method and device based on tactile perception, which includes the following steps: controlling the three-dimensional displacement stage to move downward along the Z-axis direction, obtaining the Z-direction force value of the three-axis force sensor in real time, stopping the movement when the force value reaches the preset threshold, and establishing a reference plane for the sensor to scan the flexible interface; on the reference plane, realizing the synchronous control of the three-axis force sensor data acquisition and the displacement stage based on the hard trigger method; scanning the flexible interface line by line based on the data acquisition method, collecting the force change data of the sensor and the flexible interface in the X, Y and Z directions as three-dimensional tactile information; fusing and calculating the three-dimensional force data to achieve high-precision, high-resolution, multi-dimensional tactile scanning imaging of the flexible interface, and finally realizing flexible interface detection based on tactile perception.

[0005] However, the current tactile sensing technology used in the detection of small cracks in tires is still immature. In particular, it has not effectively combined force gradient information and image processing technology to predict the direction of crack expansion. Crack expansion is usually affected by stress concentration and material structure. Accurately predicting the direction of crack expansion is the key to achieving intelligent early warning and optimizing maintenance plans. Although some traditional methods try to use mechanical models or simplified algorithms to predict crack expansion, the accuracy and practicality of these methods are still facing great challenges due to the complexity of mechanical models and application limitations.

[0006] Therefore, there is an urgent need for a new detection and prediction method that can combine tactile sensing technology, force gradient information and image processing algorithms to accurately detect small cracks on the tire surface and predict the direction of crack expansion, so as to improve the detection accuracy and prediction accuracy, thereby providing a scientific basis for tire safety monitoring and maintenance decisions. Summary of the invention

[0007] In order to achieve the above-mentioned purpose, the purpose of the present invention is to provide a method for detecting fine cracks on the tire surface and predicting the crack propagation direction based on tactile sensation. The method can effectively detect fine cracks on the tire surface that are difficult to detect with the naked eye, and predict the crack propagation direction by analyzing the force gradient of the crack area and applying Hough transform technology, thereby providing an accurate judgment basis for tire safety monitoring and maintenance.

[0008] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions: A method for detecting fine cracks on a tire surface and predicting crack propagation directions based on tactile sensation, the method comprising the following steps: 1) Using a three-dimensional translation stage to control the three-axis force sensor to slowly move downward along the Z-axis direction and collect the force value in the Z-direction in real time. When the force value in the Z-direction reaches a preset threshold, the displacement is stopped to establish a tire surface reference plane; 2) On the reference plane, control the three-dimensional translation stage to scan line by line along the X and Y directions, collect the friction force data of the three-axis force sensor in the X and Y directions and the normal pressure data in the Z direction in real time, and obtain the force data of the tire surface; 3) performing image processing on the force data, and extracting the crack area on the tire surface by edge detection and morphological processing; 4) Calculating the gradient information of the force data in the X and Y directions of the crack region to obtain the force gradient direction of the crack region; 5) Applying Hough transform to the crack area to extract the main direction of the crack, and comparing it with the force gradient direction to predict the crack extension direction; 6) Based on the predicted crack propagation direction, determine the future crack expansion trend and issue an early warning.

[0009] Preferably, the reference plane is determined by controlling the precise movement of the three-dimensional translation stage along the Z-axis direction and collecting the force data in the Z-direction in real time, and when the force data reaches a set threshold.

[0010] Preferably, the edge detection adopts the Canny edge detection algorithm, and the morphological processing includes dilation and erosion operations to eliminate noise and enhance the coherence of the crack area.

[0011] Preferably, the gradient calculation of the force data adopts the Sobel operator, and the force gradient map is obtained by calculating the force changes in the X direction and the Y direction.

[0012] Preferably, the Hough transform is used to extract a main strike straight line from an edge image of a crack region, and the angle of the straight line is combined with the force gradient direction to predict the crack propagation direction.

[0013] Preferably, the prediction of the crack propagation direction is calculated based on the angle between the gradient direction and the straight line direction extracted by Hough transform, and when the angle is less than a predetermined threshold, it is considered that the crack will propagate along this direction.

[0014] Furthermore, the present invention also discloses a system for detecting fine cracks on the tire surface and predicting the crack propagation direction based on tactile sensation, wherein the system implements the method, including: Three-dimensional translation stage, used to control the precise movement of the three-axis force sensor along the X, Y, and Z directions; The three-axis force sensor can simultaneously detect the friction force in the X and Y directions and the normal pressure in the Z direction, and output the force signal; the integrated acquisition control platform is used to control the movement of the three-dimensional translation stage, collect the force data of the three-axis force sensor, and process the data synchronously; A data processing unit, used to receive the force data of the three-axis force sensor, perform image processing, gradient calculation and Hough transform processing, so as to extract the crack area and predict the crack extension direction; The display device is used to display the crack area on the tire surface, the predicted crack propagation direction and the detection result in real time.

[0015] Preferably, the three-dimensional displacement stage comprises a stepper motor, a precision guide rail and a transmission screw, and can provide precise displacement control.

[0016] Preferably, the data processing unit includes a central processing unit and a field programmable logic device (FPGA), wherein the central processing unit is responsible for system control and data storage, and the field programmable logic device is responsible for efficient data acquisition and processing.

[0017] Preferably, the display device comprises a display, an image processing unit and an alarm module, which are used to display the crack detection results and issue a warning signal according to the crack extension prediction results.

[0018] Furthermore, the present invention also discloses a computer-readable storage medium on which a computer program or instruction is stored. When the computer program or instruction is executed by a processor, step 3) to step 6) of the method are implemented.

[0019] Furthermore, the present invention also discloses a computer program product, including a computer program or an instruction, which implements step 3) to step 6) of the method when executed by a processor.

[0020] The present invention adopts the above technical solution, and by combining a high-precision three-dimensional displacement stage, a three-axis force sensor and advanced image processing technology, it can efficiently and accurately detect small cracks on the tire surface and effectively predict their expansion direction. The implementation of this technical solution brings the following significant technical effects: 1. High-precision fine crack detection: The present invention combines a three-dimensional displacement stage with a three-axis force sensor, and effectively captures the force changes of fine cracks on the tire surface by precisely controlling the sensor to scan along the X, Y, and Z directions with micron-level precision. Traditional manual visual inspection or detection methods based on optical imaging cannot accurately capture fine cracks, but the present invention can achieve high-precision detection of these tiny cracks, greatly improving the sensitivity and accuracy of crack detection and significantly reducing the risk of missed detection.

[0021] 2. Strong environmental adaptability and overcoming light interference: Different from the traditional crack detection method that relies on optical images, the detection method of the present invention is based on tactile perception technology and is completely independent of changes in external light sources. Therefore, it can work stably in low light, high light, shadows or other complex environments. This feature enables the present invention to maintain consistent performance and accuracy in different detection environments, greatly improving the environmental adaptability of the tire detection system.

[0022] 3. Real-time crack expansion direction prediction: By calculating the gradient information of the X and Y direction force data of the crack area and extracting the main direction of the crack by combining Hough transform, the present invention can accurately predict the crack expansion direction. This technical effect significantly improves the intelligent level of tire crack management. By identifying the crack expansion trend in advance, operators can take appropriate measures, such as repairing or replacing tires, before the crack further expands, avoiding safety hazards and reducing unnecessary losses.

[0023] 4. Efficient and automated detection, reducing human errors: The automated detection system of the present invention does not need to rely on manual inspection one by one, and can efficiently and stably perform fully automatic tire surface crack detection and crack extension prediction. Compared with traditional manual detection methods, the present invention can significantly improve detection efficiency, reduce the impact of human factors on detection results, and at the same time improve the accuracy of data processing, ensuring the reliability of detection results.

[0024] 5. Data storage and historical tracing: The system of the present invention has a data storage function, which can store the crack data and crack extension prediction results of each detection in real time, and provide a historical data tracing function. This not only helps the long-term maintenance and management of tires, but also provides important data support for future technology optimization. The tracing and analysis of historical data can help companies identify potential quality problems and optimize tire design and production processes.

[0025] Through the above technical effects, the present invention can significantly improve the accuracy, efficiency and intelligence level of tire crack detection, provide reliable technical guarantee for the safe management and maintenance of tires, and provide strong support for the innovative development in the fields of intelligent manufacturing and industrial inspection. The present invention effectively avoids the further development of cracks during use through early detection and expansion prediction of cracks, reduces the risk of failure and accidents caused by cracks in the tire, and thus improves the safety of the tire. In addition, timely treatment and repair of cracks can extend the service life of the tire and reduce operating costs. The application of the present invention not only has broad application prospects in tire production and inspection, but also can promote the automation and intelligent development in the field of industrial inspection. The high efficiency and intelligent analysis capabilities of the system can provide technical references for other similar industrial product inspections, promote the use of advanced tactile sensing technology in more fields, and improve the overall industrial production and quality inspection level. DETAILED DESCRIPTION

[0026] The following is a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] A system for detecting small cracks on the tire surface based on tactile sensation and predicting the direction of crack propagation. The hardware of this system adopts the flexible interface detection method of the Chinese invention patent application (publication number: CN116818172A, publication date: 2023-09-29). By combining a high-precision three-dimensional displacement stage, a three-axis force sensor and advanced image processing technology, it can efficiently and accurately detect small cracks on the tire surface and effectively predict their propagation direction. The following are the specific implementation steps and their implementation methods.

[0028] 1. System hardware composition 1.1 Three-dimensional translation stage The 3D translation stage is one of the core components of the system. Its main function is to control the precise movement of the sensor in the X, Y and Z directions to ensure full coverage scanning of the tire surface. The translation stage is composed of a stepper motor, precision guide rails and a transmission screw. It has micron-level accuracy and can ensure high-precision positioning of the sensor. By precisely controlling the movement of the translation stage, line-by-line scanning of the tire surface can be achieved.

[0029] 1.2 Three-axis force sensor The three-axis force sensor can simultaneously measure the friction force in the X and Y directions and the normal pressure in the Z direction, and output the force data in real time. The sensor has high resolution and can capture the slight force changes caused by small cracks. The three-axis force sensor works with the three-dimensional translation stage to complete the tactile scanning of the tire surface and generate force data.

[0030] 1.3 Integrated acquisition and control platform The platform uses Xilinx Zynq SoC (system-on-chip), which integrates a central processing unit (ARM) and a programmable logic (FPGA) module. The central processing unit is used to coordinate system control, receive instructions from the host computer, store data, and interact with display devices; the FPGA module handles high-speed data acquisition, signal synchronization, and hardware acceleration algorithms to ensure the real-time and high efficiency of the system.

[0031] 1.4 Data Processing Unit The data processing unit is responsible for receiving force data from the three-axis force sensor and processing the data. First, the crack area is extracted through Canny edge detection and morphological processing. Then, the force gradient information in the X and Y directions of the crack area is calculated, and the main direction of the crack is extracted from the crack edge image using Hough transform. Finally, the crack extension direction is predicted by analyzing the main direction of the crack and the force gradient.

[0032] 1.5 Display Devices The display device is used to display the crack detection results and predicted crack propagation direction of the tire surface in real time. The operator can view the location information of the crack through the display interface and decide whether further maintenance or tire replacement is needed based on the predicted results.

[0033] 2. Methods and steps based on tactile detection 2.1 Establishing the reference plane Before starting the test, the 3D translation stage is first slowly moved down along the Z axis and the force data in the Z direction is collected in real time. When the force value in the Z direction reaches the preset threshold (5N), the displacement is stopped and the tire surface reference plane is established. The establishment of the reference plane ensures the height reference value of subsequent scans and guarantees the accuracy of each scan.

[0034] 2.2 Scanning force data line by line After establishing the reference plane, the 3D translation stage begins to scan the tire surface line by line along the X and Y directions, collecting the sensor's friction force in the X and Y directions and the normal pressure data in the Z direction. By scanning line by line, full coverage force data of the tire surface can be obtained, ensuring that small crack areas are not missed.

[0035] 2.3 Image processing and crack area extraction For the collected force data, the data processing unit first performs image processing, including edge detection and morphological operations. Canny edge detection is used to identify the edges in the image, while morphological processing (dilation and erosion operations) helps to remove noise and enhance the coherence of the crack area. Finally, the crack area can be extracted from the entire force data image.

[0036] 2.3.1 Edge Detection Step 1.1: Canny edge detection Canny edge detection is a commonly used edge detection method that determines the edge position by detecting the gradient change of pixel values ​​in the image. For force data images, Canny edge detection can help identify the boundaries of cracks, which is very important for subsequent crack area extraction.

[0037] Steps of Canny edge detection: 1) Smooth the image: First, apply a Gaussian filter to the input image to remove noise. The function of the Gaussian filter is to smooth the image by weighted averaging the values ​​of neighboring pixels, reducing the impact of noise on edge detection results. The Gaussian filter formula is as follows:

[0038] Among them, G(x,y) represents the Gaussian kernel function, σ is the standard deviation, which determines the width of the filter.

[0039] 2) Calculate the gradient: Use the Sobel operator to calculate the horizontal gradient G of the image x and the vertical gradient G y The Sobel operator is used to calculate the direction of the largest grayscale change in the image. The formula for calculating the gradient is:

[0040] Where I(x,y) is the pixel value in the image, Gx and Gy are the gradients in the horizontal and vertical directions respectively.

[0041] 3) Non-maximum suppression: In order to improve the accuracy of the edge, the Canny algorithm performs non-maximum suppression on the gradient amplitude in the image. The purpose of non-maximum suppression is to eliminate pixels that do not belong to the edge and only retain the pixels with the largest gradient amplitude.

[0042] 4) Double threshold segmentation: The Canny algorithm determines the edge in the image through double threshold segmentation. The specific method is: the gradient amplitude in the image is divided into strong edge, weak edge and non-edge. Strong edge is directly marked as edge, weak edge is considered as edge only when it is connected to strong edge, and non-edge is excluded. The edge detection result can be determined by the following formula:

[0043] Where T is the gradient amplitude, T high and T low are the high and low thresholds, if T low ≤T<T high Then Edge is a weak edge.

[0044] 2.3.2 Morphological processing Step 1): Expansion operation The dilation operation is a morphological processing method that is usually used to enhance the connectivity of objects in an image. Through dilation, the edges in the image will be extended to fill the gaps in the crack area and ensure that the integrity of the crack is preserved. The mathematical formula for the dilation operation is as follows: D(A)=A⊕B={z∣(B z ∩A)≠ } Among them, A is the original image, B is the structural element, and B z is the translation of the structural element on image A, and ⊕ represents the dilation operation. The dilation operation will expand the area with grayscale value 1 in the image.

[0045] Step 2): Corrosion operation The erosion operation is usually used together with the dilation operation. Its main function is to remove small noise in the image and maintain the coherence of the crack area. The mathematical formula of the erosion operation is as follows: E(A)=A B={z|(B z A) in, represents the corrosion operation, A is the original image, B is the structural element, and B zis the translation of the structural element on image A. The erosion operation will remove the noise at the edge of the image and refine the crack area.

[0046] Through the combination of dilation and erosion operations, morphological processing can enhance the coherence of the crack area and remove small noise points. Finally, the crack area can be extracted from the entire force data image. Through these morphological operations, the crack edge is clearer, which is convenient for subsequent crack analysis and expansion prediction.

[0047] Through the above-mentioned edge detection and morphological processing steps, the data processing unit can extract the areas where cracks exist on the tire surface. The extraction of these crack areas is crucial for the subsequent prediction of the crack propagation direction. On this basis, by calculating the force gradient direction of the crack area and applying Hough transform to extract the main strike line, the crack propagation trend can be further predicted. Finally, the crack area extraction and propagation direction prediction results will be displayed on the display device, providing operators with timely maintenance decision-making basis.

[0048] 2.4 Force gradient calculation After extracting the crack area, the data processing unit uses the Sobel operator to calculate the force gradient in the X and Y directions of the crack area. This process can obtain the direction of force change in the crack area, which helps to determine the direction of crack expansion. The force gradient direction reflects the degree of stress concentration on the material surface and is a key factor in crack expansion.

[0049] 2.4.1 Calculation of force gradients in the X and Y directions Step 1): Sobel operator The Sobel operator is used to calculate the gradients in each direction of the image. The Sobel operator can calculate the gradient value of each pixel in the horizontal direction (X direction) and the vertical direction (Y direction) by performing convolution operations in the image.

[0050] The Sobel operator calculates the gradient through the following convolution kernel: Sobel convolution kernel in the X direction (detecting the gradient in the horizontal direction):

[0051] Sobel convolution kernel in the Y direction (detecting the gradient in the vertical direction):

[0052] in, G x and G y Represent the gradient calculation kernel in the horizontal and vertical directions respectively.

[0053] Step 2): Calculate the gradient value of each pixel By convolving the force image with the Sobel convolution kernel, the force gradients of each pixel in the image in the horizontal direction (X direction) and the vertical direction (Y direction) are obtained. For each pixel (x, y), the force gradients in the X direction and the Y direction are calculated as follows: Force gradient in X direction:

[0054] in, I(x+i,y+j) Indicates the position in the image ( x+i,y+j ), K x (i,j) is the element of the Sobel X-direction convolution kernel.

[0055] Force gradient in Y direction:

[0056] Among them, I( x+i,y+j ) represents the position in the image ( x+i,y+j ) pixel value, K y (i,j) is the element of the Sobel Y-direction convolution kernel.

[0057] Step 3): Calculate the gradient magnitude and direction After calculating the gradients in the X and Y directions, we can then calculate the gradient magnitude and direction of each pixel.

[0058] The gradient amplitude G(x,y) reflects the intensity of the force change, and the calculation formula is as follows:

[0059] The gradient direction θ(x,y) reflects the direction of force change, and the calculation formula is as follows:

[0060] Among them, atan2(G y (x,y) is the inverse tangent function that calculates the direction of the gradient. The angle returned is usually in radians and indicates the direction of the force change.

[0061] 2.4.2 Application of stress gradient to predict crack propagation direction Step 1): Relationship between gradient direction and crack extension direction Cracks usually propagate along the direction where the stress on the material surface changes most dramatically. Therefore, by analyzing the stress gradient direction, the crack propagation trend can be predicted. The stress gradient direction (i.e. the calculated gradient direction) provides the main direction in which the crack may propagate.

[0062] Step 2): Combine Hough transform to predict crack propagation direction Hough transform is used to extract the main strike straight line of the crack from the edge image of the crack area and compare it with the force gradient direction. When the force gradient direction of the crack is close to the angle of the main strike straight line of the crack obtained by Hough transform, it can be predicted that the crack will extend in this direction.

[0063] Step 3): Calculate the angle and determine the expansion direction In order to more accurately predict the crack propagation direction, the angle between the gradient direction and the main crack direction extracted by Hough transform can be calculated. If the angle is less than a predetermined threshold (e.g. 10°), it is considered that the crack will propagate in this direction. If the angle is large, it means that the crack propagation direction deviates greatly from the main direction, and the crack propagation trend may need to be re-analyzed.

[0064] The angle calculation formula is as follows: angle(x,y)=|θ(x,y-θ line ∣ Among them, θline is the angle of the main direction of the crack extracted by Hough transform, and θ(x,y) is the angle of the force gradient direction.

[0065] 2.5 Hough transform and expansion direction prediction Apply Hough transform to the crack area to extract the main strike line of the crack. By comparing the force gradient direction of the crack area with the direction of the straight line extracted by Hough transform, the possible crack extension direction is predicted. If the gradient direction is close to the main strike angle, it is inferred that the crack will extend in this direction.

[0066] 2.6 Crack propagation prediction and early warning Based on the prediction results of the crack extension direction, the system will make further judgments. If the crack is predicted to extend to the dangerous area, an early warning signal will be issued. The early warning information will be notified to the operator through the display device to take necessary measures to prevent further crack extension or fracture.

[0067] 2.6.1 Determine whether the crack extends to the dangerous area Step 1): Define the danger zone First, it is necessary to define the scope of the "dangerous area". The dangerous area usually refers to the area where crack propagation may cause tire failure or rupture. This area can be determined based on the design and use conditions of the tire, such as the tire's load-bearing pressure area, thermal stress concentration area, etc.

[0068] Assume that the danger zone is the tire surface with a radius of R danger The circular area is centered at the center axis of the tire. The definition of the danger zone can be expressed by the following formula: R danger = Radius of the danger zone (measured in distance with the centre of the tyre as reference point).

[0069] Step 2): Crack Growth Prediction In the crack propagation prediction process, the system predicts the crack propagation direction and possible propagation distance through the force gradient and the main crack direction extracted by Hough transform. The propagation direction and propagation distance are obtained based on the combination of the predicted crack direction and the force gradient.

[0070] Assume that the predicted crack growth direction is θ expand , and the possible extension distance of the crack is d expand (This value can be obtained through simulation calculation or empirical data), then the coordinates of the crack end (x end ,y end ) can be calculated according to the following formula:

[0071] Among them, (x start ,y start ) is the current starting position of the crack, d expand is the distance the crack extends, θ expand is the direction of crack propagation.

[0072] Step 1.3: Determine whether the crack has entered the danger zone In order to determine whether the crack will enter the danger zone, it is necessary to calculate the predicted position of the crack end (x end ,y end ) is in the danger zone. end ,y end ) in the danger zone, i.e. , then it is considered that the crack will extend to the dangerous area. This condition can be judged by the following formula: if , An alarm is sounded to notify the operator.

[0073] 2.6.2 Issuance of early warning signals Step 1): Early warning mechanism When the predicted crack position enters the danger zone, the system triggers an early warning mechanism, which notifies the operator through a display device to remind them to take appropriate measures, such as stopping the use of the tire, repairing it, or replacing it.

[0074] Step 2): Warning signal output Warning signals can be output in the following ways: Sound and light alarm: The system emits an audible alarm and flashing light signals; Display device warning: A warning notification pops up on the display device interface, and the crack location and predicted expansion direction are highlighted; Automatic reporting: The system automatically generates reports and sends them to relevant staff via the network or wireless communication, or performs remote monitoring via the cloud platform.

[0075] Specific warning information may include: The current location and propagation direction of the crack; The final location where the crack may extend; Whether the vehicle has entered a dangerous area and provide treatment suggestions (for example, whether it is necessary to stop using, repair or replace the tire).

[0076] Step 3): Automated Response (Optional) To improve the intelligence level of the system, an automatic response function can be set. For example, when a crack enters a dangerous area, the system not only sends a warning signal, but also automatically triggers certain actions, such as shutting down, locking the system, or starting emergency procedures.

[0077] 2.6.3 Comprehensive evaluation and subsequent processing Step 1): Evaluation of crack growth tendency In addition to simply judging whether a crack has entered a dangerous area, the system can also comprehensively evaluate the trend of crack expansion through historical data and real-time data. For example, by combining factors such as crack expansion speed, stress concentration, and material fatigue, the system can evaluate the possibility of crack expansion in the next few days or weeks. In the case of a fast crack expansion or a situation that may cause major safety hazards, the system can notify the operator in advance to take preventive measures.

[0078] Step 2): Regular monitoring and feedback The system can also perform crack detection regularly and update crack propagation predictions based on new detection data, forming a closed-loop monitoring system. After each detection, the system will automatically evaluate the current crack status and decide whether a new early warning signal needs to be issued.

[0079] Furthermore, the present invention also provides a computer-readable storage medium, including one or more programs for execution by one or more processors of an electronic device, wherein the one or more programs include instructions for executing the method described in this specific embodiment.

[0080] It should be noted that computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media such as modulated data signals and carrier waves.

[0081] The present invention may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0082] The above is a description of the embodiments of the present invention. Through the above description of the disclosed embodiments, professionals and technicians in the field can implement or use the present invention. Various modifications to these embodiments will be apparent to professionals and technicians in the field. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown in this article, but will conform to the widest range consistent with the principles and novelties disclosed herein.

Claims

1. A method for detecting fine cracks on a tire surface and predicting the direction of crack propagation based on tactile sensation, characterized in that: The method comprises the following steps: 1) Using a three-dimensional translation stage to control the three-axis force sensor to slowly move downward along the Z-axis direction and collect the force value in the Z-direction in real time. When the force value in the Z-direction reaches a preset threshold, the displacement is stopped to establish a tire surface reference plane; 2) On the reference plane, control the three-dimensional displacement stage to scan line by line along the X and Y directions, collect the friction force data of the three-axis force sensor in the X and Y directions and the normal pressure data in the Z direction in real time, and obtain the force data of the tire surface; 3) Perform image processing on the force data, and use edge detection and morphological processing to extract the crack area on the tire surface; 4) Calculate the gradient information of the force data in the X and Y directions of the crack area to obtain the force gradient direction of the crack area; 5) Apply Hough transform to the crack area to extract the main direction of the crack, and compare it with the force gradient direction to predict the crack expansion direction; 6) According to the predicted crack expansion direction, judge the future expansion trend of the crack and issue an early warning.

2. The method according to claim 1, characterized in that The reference plane is determined by controlling the precise movement of the three-dimensional translation stage along the Z-axis direction and collecting the force data in the Z-direction in real time, and when the force data reaches a set threshold.

3. The method according to claim 1, characterized in that The edge detection adopts the Canny edge detection algorithm, and the morphological processing includes dilation and erosion operations to eliminate noise and enhance the coherence of the crack area.

4. The method according to claim 1, characterized in that: The Sobel operator is used to calculate the gradient of the force data, and the force gradient diagram is obtained by calculating the force changes in the X direction and the Y direction.

5. The method according to claim 1, characterized in that The Hough transform is used to extract the main strike straight line from the edge image of the crack area, and the angle of the straight line is combined with the force gradient direction to predict the crack propagation direction.

6. The method according to claim 1, characterized in that The prediction of the crack propagation direction is calculated based on the angle between the gradient direction and the straight line direction extracted by Hough transform. When the angle is less than a predetermined threshold, it is considered that the crack will propagate along this direction.

7. A system for detecting small cracks on the tire surface and predicting the direction of crack propagation based on tactile sensation, characterized in that: The system implements the method according to any one of claims 1 to 6, including: Three-dimensional translation stage, used to control the precise movement of the three-axis force sensor along the X, Y, and Z directions; The three-axis force sensor can simultaneously detect the friction force in the X and Y directions and the normal pressure in the Z direction, and output the force signal; the integrated acquisition control platform is used to control the movement of the three-dimensional translation stage, collect the force data of the three-axis force sensor, and process the data synchronously; A data processing unit, used to receive the force data of the three-axis force sensor, perform image processing, gradient calculation and Hough transform processing, so as to extract the crack area and predict the crack extension direction; The display device is used to display the crack area on the tire surface, the predicted crack propagation direction and the detection result in real time.

8. The system according to claim 7, characterized in that The three-dimensional displacement platform includes a stepper motor, a precision guide rail and a transmission screw, which can provide precise displacement control; and / or, the data processing unit includes a central processing unit and a programmable logic device, wherein the central processing unit is responsible for system control and data storage, and the programmable logic device is responsible for efficient data acquisition and processing; and / or, the display device includes a display, an image processing unit and an alarm module, which are used to display crack detection results and issue a warning signal based on crack extension prediction results.

9. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, steps 3) to 6) of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, steps 3) to 6) of the method according to any one of claims 1 to 6 are implemented.

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