Disclosure of Invention
In order to achieve the above object, an object of the present invention is to provide a method for detecting a fine crack on a tire surface and predicting a crack propagation direction based on a tactile sense. The method can effectively detect tiny cracks which are difficult to find by naked eyes on the surface of the tire, and predicts the expansion direction of the cracks by analyzing the stress gradient of the crack area and applying Hough transformation technology, thereby providing accurate judgment basis for safety monitoring and maintenance of the tire.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
A method for tactilely detecting a fine crack in a tire surface and predicting crack propagation direction, the method comprising the steps of:
1) The three-dimensional displacement table is used for controlling the three-dimensional force sensor to slowly move downwards along the Z-axis direction and collecting the stress value of the Z-direction in real time, and when the stress value of the Z-direction reaches a preset threshold value, the displacement is stopped, and a tire surface reference plane is established;
2) On the reference plane, controlling a three-dimensional displacement table to scan line by line along the X, Y direction, and collecting the friction force of the three-way force sensor in the X, Y direction and the normal pressure data in the Z direction in real time to obtain stress data of the surface of the tire;
3) Performing image processing on the stress data, and extracting crack areas on the surface of the tire by adopting edge detection and morphological processing;
4) Calculating gradient information of X, Y-direction stress data of the crack region to obtain a stress gradient direction of the crack region;
5) Extracting the main trend of the crack by using Hough transformation on the crack area, comparing the main trend with the stress gradient direction, and predicting the expansion direction of the crack;
6) And judging the future expansion trend of the crack according to the predicted crack expansion direction and carrying out early warning.
Preferably, the reference plane is determined when the stress data reaches a set threshold value by controlling the three-dimensional displacement table to accurately move along the Z-axis direction and collecting the stress data in the Z-axis direction in real time.
Preferably, the edge detection employs a Canny edge detection algorithm, and the morphological processing includes dilation and erosion operations to eliminate noise and enhance continuity of the crack region.
Preferably, a Sobel operator is adopted in gradient calculation of the stress data, and a stress gradient graph is obtained by calculating stress changes in the X direction and the Y direction.
Preferably, the Hough transformation is used for extracting a main trend straight line from an edge image of a crack area, and the angle of the straight line is combined with the stress gradient direction to predict the crack propagation direction.
Preferably, the prediction of the crack propagation direction is calculated according to the included angle between the gradient direction and the straight line direction extracted by Hough transformation, and when the included angle is smaller than a preset threshold value, the crack is considered to be propagated along the direction.
Further, the invention also discloses a system for detecting the tiny cracks on the surface of the tire and predicting the crack propagation direction based on touch sense, and the system realizes the method, which comprises the following steps:
The three-dimensional displacement table is used for controlling the three-dimensional force sensor to accurately move along X, Y, Z directions;
The integrated acquisition control platform is used for controlling the movement of the three-dimensional displacement platform, acquiring stress data of the three-dimensional force sensor and synchronously processing the data;
the data processing unit is used for receiving the stress data of the three-dimensional force sensor, performing image processing, gradient calculation and Hough transformation processing, and accordingly extracting a crack area and predicting the expansion direction of the crack;
And the display equipment is used for displaying the crack area, the predicted crack propagation direction and the detection result of the tire surface in real time.
Preferably, the three-dimensional displacement table comprises a stepping motor, a precise guide rail and a transmission screw rod, so that precise displacement control can be provided.
Preferably, the data processing unit comprises a central processing unit and a programmable logic device (FPGA), 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.
Preferably, the display device comprises a display, an image processing unit and an alarm module, and is used for displaying the crack detection result and sending out an early warning signal according to the crack expansion prediction result.
Further, the invention also discloses a computer readable storage medium, on which a computer program or instructions is stored, which when executed by a processor, implements steps 3) -6 of the method.
Further, the invention also discloses a computer program product comprising a computer program or instructions which, when executed by a processor, implement steps 3) -6 of the method.
By adopting the technical scheme, the invention can efficiently and accurately detect the tiny cracks on the surface of the tire and effectively predict the expansion direction of the tiny cracks by combining a high-precision three-dimensional displacement table, a three-dimensional force sensor and an advanced image processing technology. The implementation of the technical scheme brings the following remarkable technical effects:
1. The invention adopts the combination of the three-dimensional displacement table and the three-dimensional force sensor, and the sensor is precisely controlled to scan in the X, Y, Z directions with micron-scale precision, so that the stress change of the fine crack on the surface of the tire is effectively captured. The traditional manual visual inspection or detection method based on optical imaging cannot accurately capture the tiny cracks, but the invention can realize high-precision detection of the tiny cracks, greatly improve the sensitivity and accuracy of crack detection and obviously reduce the detection omission risk.
2. The method has strong environmental adaptability, overcomes illumination interference, and is based on the touch perception technology and completely independent of the change of an external light source, unlike the traditional crack detection method which relies on optical images. Thus, stable operation in low light, high light, shadows, or other complex environments is possible. The invention can maintain consistent performance and accuracy under different detection environments, and greatly improves the environment adaptability of the tire detection system.
3. And predicting the propagation direction of the crack in real time, namely calculating gradient information of X, Y-direction stress data of the crack region, and extracting the main trend of the crack by combining Hough transformation. The technical effect of the method is that the intelligent level of tire crack management is remarkably improved. By identifying the crack propagation trend in advance, operators can take appropriate measures, such as repairing or replacing tires, before the crack propagates further, so that potential safety hazards are avoided, and unnecessary losses are reduced.
4. The automatic detection system does not need to rely on manual work to check one by one, and can efficiently and stably detect and predict the crack growth of the surface of the tire in full automation. Compared with the traditional manual detection mode, the invention can obviously improve the detection efficiency, reduce the influence of human factors on the detection result, improve the accuracy of data processing and ensure the reliability of the detection result.
5. The system has the data storage function, can store the crack data and the crack expansion prediction result detected each time in real time, and provides the historical data tracing function. This not only facilitates long-term maintenance and management of the tire, but also provides important data support for future technical optimizations. The traceability and analysis of historical data can help enterprises identify potential quality problems and optimize tire design and production processes.
Through the technical effects, the invention can obviously improve the precision, efficiency and intelligent level of tire crack detection, provide reliable technical guarantee for the safety management and maintenance of tires, and simultaneously provide powerful support for innovation and development in the fields of intelligent manufacturing and industrial detection. According to the invention, through early detection and expansion prediction of cracks, further development of the cracks in the use process is effectively avoided, and faults and accident risks caused by the cracks of the tire are reduced, so that the safety of the tire is improved. In addition, timely treatment and maintenance of cracks can prolong the service life of the tire, and reduce the operation cost. The application of the invention not only has wide application prospect in the production and detection of tires, but also can promote the automation and intelligent development of the industrial detection field. The system has high efficiency and intelligent analysis capability, can provide technical reference for detection of other similar industrial products, promotes more fields to adopt advanced tactile perception technology, and improves the overall industrial production and quality detection level.
Detailed Description
The technical solutions in the embodiments are clearly and completely described below in connection with the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
A system for detecting fine cracks on the surface of a tire and predicting crack propagation direction based on touch. The hardware of the system adopts the flexible interface detection method of Chinese invention patent application (publication No. CN116818172A, publication No. 2023-09-29), and can efficiently and accurately detect the tiny cracks on the surface of the tire and effectively predict the expansion direction of the tire by combining a high-precision three-dimensional displacement table, a three-dimensional force sensor and an advanced image processing technology. The following are specific implementation steps and implementations thereof.
1. System hardware composition
1.1 Three-dimensional displacement table
The three-dimensional displacement table is one of the core components of the system, and the main function is to control the sensor to precisely move along the directions X, Y and Z so as to ensure full coverage scanning of the surface of the tire. The displacement table consists of a stepping motor, a precise guide rail and a transmission screw rod, has micron-level precision and can ensure the high-precision positioning of the sensor. By precisely controlling the movement of the displacement table, progressive scanning of the tire surface can be achieved.
1.2 Three-way force sensor
The three-way force sensor can simultaneously measure the friction force in the X, Y direction and the normal pressure in the Z direction, and output stress data in real time. The sensor has high resolution and can capture tiny stress changes caused by tiny cracks. The three-dimensional force sensor and the three-dimensional displacement table work cooperatively to finish the touch scanning of the tire surface and generate stress data.
1.3 Integrated acquisition control platform
The platform adopts an Xilinx Zynq SoC (System on a chip), and integrates a central processing unit (ARM) and a programmable logic (FPGA) module. The central processor is used for coordinating system control, receiving the instruction of the upper computer, storing data and interacting with the display device, and the FPGA module is used for processing high-speed data acquisition, signal synchronization and hardware acceleration algorithm, so that the real-time performance and high efficiency of the system are ensured.
1.4 Data processing unit
The data processing unit is responsible for receiving stress data from the three-way force sensor and processing the data. First, a crack region is extracted by Canny edge detection and morphological processing. Then, X, Y-direction stress gradient information of the crack region is calculated, and Hough transformation is applied to extract the main trend of the crack from the crack edge image. Finally, the crack propagation direction is predicted by analyzing the main trend and the stress gradient of the crack.
1.5 Display apparatus
The display device is used for displaying the crack detection result and the predicted crack propagation direction of the tire surface in real time. An operator can check the position information of the crack through the display interface and decide whether further maintenance or tire replacement is required according to the prediction result.
2. Method steps based on haptic detection
2.1 Reference plane establishment
Before starting detection, firstly, slowly downwards moving along the Z-axis direction through a three-dimensional displacement table, and collecting stress data in the Z-axis direction in real time. And stopping displacement when the stress value in the Z direction reaches a preset threshold value (5N), and establishing a tire surface reference plane. The establishment of the reference plane ensures the height reference value of the subsequent scanning and ensures the accuracy of each scanning.
2.2 Progressive scanning stress data
After the reference plane is established, the three-dimensional displacement table starts scanning the tire surface line by line along the X, Y direction, and the friction force of the sensor in the X, Y direction and the normal pressure data in the Z direction are acquired. By progressive scanning, full coverage stress data of the tire surface can be obtained, and the tiny crack area is ensured not to be missed.
2.3 Image processing and crack region extraction
For the acquired stress data, the data processing unit firstly performs image processing, including edge detection and morphological operation. Canny edge detection is used to identify edges in the image, while morphological processing (dilation and erosion operations) helps remove noise and enhance the consistency of the crack region. Eventually, the crack region can be extracted from the entire stress data image.
2.3.1 Edge detection
Step 1.1 canny edge detection
Canny edge detection is a common edge detection method that determines edge position by detecting gradient changes in pixel values in an image. For the stress data image, canny edge detection can help identify crack boundaries, which is important for subsequent crack region extraction.
Canny edge detection:
1) Smoothing the image-first, a gaussian filter is applied to the input image to remove noise. The gaussian filter acts to smooth the image by weighted averaging of adjacent pixel values, reducing the effect of noise on edge detection results. The gaussian filter formula is as follows:
Where G (x, y) represents a gaussian kernel and σ is the standard deviation, which determines the width of the filter.
2) Gradient calculation horizontal gradient Gx and vertical gradient Gy of the image were calculated using Sobel operator. The Sobel operator is used to calculate the direction of the maximum gray change in the image. The formula for calculating the gradient is:
where I (x, y) is the pixel value in the image and Gx and Gy are the gradients in the horizontal and vertical directions, respectively.
3) Non-maximum suppression in order to improve the edge accuracy, 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 edges, leaving only the pixel points where the gradient magnitude is greatest.
4) Double threshold segmentation-the Canny algorithm determines edges in the image by double threshold segmentation. The method includes dividing gradient amplitude values in an image into strong edges, weak edges and non-edges, wherein the strong edges are directly marked as edges, the weak edges are considered as edges only when the strong edges are connected, and the non-edges are eliminated. The edge detection result may be determined by the following formula:
Where T is the gradient magnitude, Thigh and Tlow are the high and low thresholds, edge is the weak Edge if Tlow≤T＜Thigh.
2.3.2 Morphological treatments
Step 1) expansion operation
The dilation operation is a morphological processing method that is commonly used to enhance connectivity of objects in an image. By expanding, the edges in the image will be expanded, filling in the gaps in the crack area, ensuring that the integrity of the crack is preserved. The mathematical formula for the expansion operation is as follows:
D(A)=A⊕B={z∣(Bz∩A)≠}
Where A is the original image, B is the structural element, and Bz is the translation of the structural element over image A, representing the dilation operation. The expansion operation will expand the region of the image with a gray value of 1.
Step 2) etching operation
Corrosion operations are typically used with dilation operations, the primary function of which is to remove small noise from the image, maintaining consistency in the crack area. The mathematical formula for the corrosion operation is as follows:
E(A)=AB={z∣(BzA)
wherein, theRepresenting a corrosion operation, a is the original image, B is the structural element, and Bz is the translation of the structural element over image a. The etching operation will remove edge noise in the image, refining the crack area.
By a combination of expansion and corrosion operations, morphological treatments can enhance the consistency of crack regions and remove small noise. Eventually, the crack region can be extracted from the entire stress data image. Through the morphological operations, the crack edges are clearer, and the subsequent crack analysis and propagation prediction are convenient.
Through the edge detection and morphological processing steps, the data processing unit can extract the area with cracks on the surface of the tire. Extraction of these crack regions is critical for subsequent crack propagation direction prediction. On the basis, the expansion trend of the crack can be further predicted by calculating the stress gradient direction of the crack area and extracting the main trend straight line by Hough transformation. Finally, the extraction and expansion direction prediction results of the crack area are displayed on a display device, and a timely maintenance decision basis is provided for operators.
2.4 Stress gradient calculation
After the crack region is extracted, the data processing unit calculates the stress gradient of the crack region in the X, Y direction by using a Sobel operator. The process can obtain the stress change direction in the crack area, thereby helping to judge the propagation direction of the crack. The stress gradient direction reflects the concentration degree of the surface stress of the material and is a key factor of crack propagation.
2.4.1 Calculating the force gradient in X, Y directions
Step 1) Sobel operator
The Sobel algorithm is used to calculate gradients in each direction in the image. The Sobel operator can calculate gradient values of each pixel in the horizontal direction (X direction) and the vertical direction (Y direction) by performing convolution operation in an image.
The Sobel operator calculates the gradient by the following convolution kernel:
sobel convolution kernel in X direction (detect gradient in horizontal direction):
sobel convolution kernel in Y direction (detect gradient in vertical direction):
Wherein Gx and Gy represent gradient computation cores in the horizontal direction and the vertical direction, respectively.
Step 2) calculating the gradient value of each pixel point
And carrying out convolution operation on the stress image and the Sobel convolution kernel to obtain stress gradients of each pixel point in the image in the horizontal direction (X direction) and the vertical direction (Y direction). For each pixel point (X, Y), the force gradient in the X direction and the Y direction are calculated as follows:
Stress gradient in X direction:
where I (x+i, y+j) represents the pixel value of position (x+i, y+j) in the image, and Kx (I, j) is an element of the Sobel X-direction convolution kernel.
Stress gradient in Y direction:
where I (x+i, y+j) represents the pixel value of position (x+i, y+j) in the image, and Ky (I, j) is an element of the Sobel Y-direction convolution kernel.
Step 3) calculating the gradient amplitude and direction
After calculating the gradients in the X-direction and the Y-direction, the gradient magnitude and direction of each pixel point can be calculated next.
The gradient amplitude G (x, y) reflects the strength of the force variation, and the calculation formula is as follows:
The gradient direction θ (x, y) reflects the direction of the force change, and the calculation formula is as follows:
where atan2 (Gy (x, y) is an arctangent function that calculates the direction of the gradient, and the angle of return is typically in radians, representing the direction of force change.
2.4.2 Crack propagation direction prediction Using stress gradient
Step 1) relation between gradient direction and crack propagation direction
The crack generally propagates along the direction in which the force applied to the surface of the material changes most severely, and thus, by analyzing the direction of the force gradient, the propagation tendency of the crack can be predicted. The force gradient direction (i.e., the calculated gradient direction) provides the primary direction in which the crack may propagate.
Step 2) predicting crack propagation direction by combining Hough transformation
The Hough transform is used for extracting the main trend straight line of the crack from the edge image of the crack area, and comparing the main trend straight line with the stress gradient direction. When the stress gradient direction of the crack is close to the angle of the main trend of the crack obtained by Hough transformation, the crack can be predicted to be expanded along the direction.
Step 3) calculating the included angle and judging the expansion direction
In order to more accurately predict the crack propagation direction, the included angle between the gradient direction and the main trend of the crack extracted by Hough transformation can be calculated. If the included angle is less than a predetermined threshold (e.g., 10), then it is believed that the crack will propagate in that direction. If the included angle is large, a large deviation between the crack propagation direction and the main trend is indicated, and the crack propagation trend may need to be re-analyzed.
The calculation formula of the included angle is as follows:
angle(x,y)=∣θ(x,y-θline∣
wherein, θline is the angle of the main trend of the crack extracted by Hough transformation, and θ (x, y) is the angle of the stress gradient direction.
2.5 Hough transform and extension direction prediction
And (3) applying Hough transformation to the crack area to extract a main trend straight line of the crack. And predicting the possible expansion direction of the crack by comparing the stress gradient direction of the crack area with the straight line direction extracted by Hough transformation. If the gradient direction is close to the angle of the main trend, it is assumed that the crack will propagate in this direction.
2.6 Crack growth prediction and early warning
And according to the prediction result of the crack propagation direction, the system further judges, and if the predicted crack propagates to the dangerous area, an early warning signal is sent out. The warning information will inform the operator via the display device that measures are necessary to prevent further propagation or breaking of the crack.
2.6.1 Judging whether the crack propagates to the dangerous area
Step 1) defining a dangerous area
First, the scope of the "dangerous area" needs to be defined. The hazardous area is generally referred to as the area where crack propagation may initiate tire failure or cracking. This region may be determined according to the design and use conditions of the tire, such as the bearing pressure region of the tire, the thermal stress concentration region, and the like.
The dangerous area is assumed to be a circular area with the radius Rdanger of the tire surface, and the central position is the central axis of the tire. The definition of the hazard zone can be expressed by the following formula:
rdanger = radius of the hazard zone (measured in distance, reference point in the centre of the tyre).
Step 2) crack growth prediction
In the crack propagation prediction process, the system predicts the propagation direction and possible propagation distance of the crack through the stress gradient and the main trend of the crack extracted through Hough transformation. The propagation direction and the propagation distance are obtained according to the combination of the predicted crack trend and the stress gradient.
Assuming that the predicted crack propagation direction is θexpand and the possible propagation distance of the crack is dexpand (this value can be obtained by analog calculation or empirical data), the coordinates (xend,yend) of the predicted crack tip can be calculated according to the following formula:
Where (xstart,ystart) is the current starting position of the crack, dexpand is the distance of crack propagation, and θexpand is the direction of crack propagation.
Step 1.3, judging whether the crack enters into the dangerous area
To determine if a crack will enter a dangerous area, it is necessary to calculate if the predicted location (xend,yend) of the crack end is within the dangerous area. If (xend,yend) is in the hazardous area, i.eIt is believed that the crack will propagate to the dangerous area. This condition can be determined by the following formula:
If it is ,
An alarm is issued to notify the operator.
2.6.2 Emission of Pre-alarm Signal
Step 1) early warning mechanism
When the crack prediction position enters a dangerous area, the system can trigger an early warning mechanism. The early warning mechanism can inform an operator through the display device to remind the operator to take corresponding measures, such as stopping using the tire, maintaining or replacing the tire.
Step 2) outputting early warning signals
The early warning signal may be output by:
Audible and visual alarm, namely, the system sends out audible alarm and a flashing light signal;
The display device warns that an early warning notice is popped up on the interface of the display device, and the position of the crack and the predicted expansion direction are highlighted;
And the system automatically generates a report and sends the report to related staff through a network or wireless communication mode, or remotely monitors through a cloud platform.
Specific pre-warning information may include:
The current position and the propagation direction of the crack;
the final location where the crack may propagate;
whether a dangerous area is entered and a treatment recommendation is given (e.g., whether the tire needs to be taken out of service, serviced, or replaced).
Step 3) automated response (optional)
To increase the level of intelligence of the system, an automated response function may be provided. For example, when a crack enters a dangerous area, the system not only emits an early warning signal, but also can automatically trigger certain operations, such as stopping, locking the system, or starting an emergency treatment program.
2.6.3 Comprehensive evaluation and subsequent processing
Step 1) evaluation of crack propagation tendency
In addition to simply determining whether a crack enters a dangerous area, the system can also comprehensively evaluate the trend of crack propagation through historical data and real-time data. For example, in combination with factors such as the propagation speed of the crack, the stress concentration degree, and the material fatigue, the possibility of propagation of the crack within days or weeks in the future is evaluated. For situations where crack propagation is rapid or may result in significant safety hazards, the system may notify the operator in advance to take precautions.
Step 2) periodic monitoring and feedback
The system can also periodically detect cracks, and update crack growth prediction according to new detection data to form closed-loop monitoring. After each detection, the system will automatically evaluate the state of the current crack and decide if a new warning signal needs to be issued.
Further, 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, the one or more programs including instructions for performing the methods of the present embodiments.
It should be noted that computer-readable media, including both permanent and non-permanent, removable and non-removable media, may be used to implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer 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 disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media, such as modulated data signals and carrier waves.
The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art. The generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.