Tractor impact detection system and detection method based on digital image processing

Abstract

A tractor impact detection system and detection method based on digital image processing relates to the technical field of tractor parameter detection, and structurally comprises an impact receptor module, a digital image acquisition module, a data processing module and a display module. The impact receptor module is used for converting impact of the tractor into deformation. The digital image acquisition module is used for acquiring digital image information of deformation. And the data processing module is used for processing the digital image information and calculating the impact force. The display module is used for displaying the detection result. The method comprises the following steps: 1, fixedly arranging the impact receptor module on a tractor to be tested; 2, the tractor is operated to generate impact; 3, a digital image acquisition module acquires a deformed digital image; 4, the data processing module processes the digital image and calculates the impact force; and 5, displaying a calculation result through a display module. According to the invention, the technical problem that the existing tractor impact detection means is difficult to realize precision and standardization can be solved.

Description

Technical Field

[0001] This invention relates to the field of tractor parameter detection technology, specifically a tractor impact detection system and method based on digital image processing. Background Technology

[0002] As a major power source in modern agriculture, tractors can be equipped with different implements to complete different types of operations. For example, they can be equipped with a hydraulic reversible plow to complete plowing operations, a rotary tiller to complete rotary tilling operations, and a seeder to complete seeding operations. In addition, they can also be used as tractor vehicles to complete transportation operations.

[0003] With changes in China's population structure, many young people are entering the agricultural sector. Reliability is no longer the sole criterion for evaluating tractor performance; vehicle comfort and fuel economy have also become important indicators. Young tractor drivers are paying more attention to tractor comfort. Meanwhile, excessive impact can cause severe discomfort to the driver, easily leading to fatigue. Furthermore, severe impacts may cause the driver to momentarily lose control of the vehicle, especially on slippery roads or slopes; impacts during steering changes can also lead to misoperation and increase safety hazards.

[0004] In addition, the impact process is often accompanied by the loss of kinetic energy, such as the conversion into vibration, noise and heat. Smooth engagement and switching help improve power transmission efficiency. Repeated strong impacts will significantly shorten the service life of key components, increase failure rate and maintenance costs. Detecting and controlling impacts is an important means to ensure the reliability and durability of the transmission system.

[0005] Reducing shock is one of the key indicators for improving tractor driving comfort, directly impacting user satisfaction and product competitiveness. Simultaneously, it protects the transmission system, improving reliability and transmission efficiency.

[0006] Existing testing methods rely on testers to conduct actual tests on vehicles. The test results are greatly affected by the testers' subjective experience and judgment, making it difficult to achieve precision and standardization. Summary of the Invention

[0007] The purpose of this invention is to provide a tractor impact detection system and method based on digital image processing, which can solve the technical problem that existing tractor impact detection methods are difficult to achieve in terms of accuracy and standardization.

[0008] To achieve the above objectives, the present invention adopts the following technical solution.

[0009] A tractor impact detection system based on digital image processing includes an impact sensor module, a digital image acquisition module, a data processing module, and a display module.

[0010] The impact sensor module is fixedly mounted on the tractor to be tested and is used to convert the impact generated when the tractor reverses power into deformation.

[0011] The digital image acquisition module is used to acquire digital image information of the deformation of the impact sensor module.

[0012] The data processing module is used to process the digital image information acquired by the digital image acquisition module and calculate the magnitude of the tractor's impact force based on the deformation generated by the impact sensor module.

[0013] The display module is used to display the test results.

[0014] Furthermore, the impact sensor module includes a base and a rigid wire. The base is used to fix it to the tractor, one end of the rigid wire is fixedly connected to the base, and the other end extends freely. A length scale is provided on the rigid wire.

[0015] Furthermore, a counterweight is provided at the free end of the rigid wire to enhance the sensitivity of the impact sensor module.

[0016] Furthermore, the digital image acquisition module includes a high-speed camera and a camera mounting bracket. The high-speed camera is fixedly connected to the tractor via the camera bracket and is used to acquire digital image information of the deformation of the impact sensor module when the tractor generates an impact.

[0017] A tractor impact detection method based on digital image processing, based on the above-mentioned detection system, includes the following steps: S1. Fix the impact sensor module and digital image acquisition module on the tractor under test; S2. Start the tractor and operate it to start and reverse, causing the tractor to generate an impact; S3, The digital image acquisition module acquires digital image data of the deformation of the impact sensor module when the tractor generates an impact; S4. The data processing module processes the acquired digital image data and calculates the magnitude of the impact force of the tractor. S5. The calculation results are displayed through the display module.

[0018] Further, in step S4, the data processing module processes the acquired digital image data, including the following steps: S41. Input digital image data; S42, Image Preprocessing; S43, Image edge extraction and edge fitting; S44, Calculation of pixel values ​​for deformation; S45. Through camera calibration, the pixel values ​​of the deformation variables are converted into actual deformation variables; S46. Calculate the impact force based on the actual value of the variable.

[0019] Furthermore, image preprocessing includes grayscale conversion, Gaussian filtering for noise reduction, and contrast enhancement.

[0020] Furthermore, image edge extraction includes gradient calculation, non-maximum constraint, double threshold detection, and edge connection of the preprocessed image.

[0021] By adopting the above technical solution, the present invention has the following beneficial effects: 1. This invention converts the impact of a tractor into the deformation of an impact sensor module and uses digital image processing technology to calculate the deformation, thereby calculating the magnitude of the impact force. It has the characteristics of being highly sensitive and providing accurate calculation results. 2. The detection device and method of this invention are used to detect the impact of tractors. The process is standardized, which avoids the influence of the testers' subjective experience and judgment on the test results. 3. The present invention also proposes to classify the impact according to the impact test results and display the results using a display module, making the results more intuitive. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the overall process of the present invention.

[0023] Figure 2 This is a schematic diagram of the detection system in this invention.

[0024] Figure 3 This is a flowchart illustrating the deformation calculation process in this invention.

[0025] Figure 4 This is a schematic diagram of the image preprocessing process in this invention.

[0026] Figure 5 This is a schematic diagram of the image edge extraction process in this invention.

[0027] Figure 6 This is a schematic diagram of the deformation state of the impact sensor module in this invention.

[0028] Figure 7 This is a schematic diagram of the impact level classification process in this invention.

[0029] Attached diagram description: 1. Base, 2. Rigid wire, 3. Counterweight. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the present invention clearer, the features and performance of a tractor impact detection system and detection method based on digital image processing according to the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0031] Please see the appendix Figures 1-7 A tractor impact detection system based on digital image processing includes an impact sensor module, a digital image acquisition module, a data processing module, and a display module, such as... Figure 2 As shown.

[0032] The impact sensor module is fixedly mounted on the tractor under test and is used to convert the impact generated when the tractor reverses power into deformation. The impact sensor module includes a base 1 and a rigid wire 2. The base 1 is used to fix it to the tractor. One end of the rigid wire 2 is fixedly connected to the base, and the other end extends freely. The rigid wire 2 is equipped with a length scale. In particular, in order to improve the sensitivity of the impact sensor module, a counterweight 3 can be set at the free end of the rigid wire 2.

[0033] The digital image acquisition module is used to acquire digital image information of the deformation of the impact sensor module. The digital image acquisition module includes a high-speed camera and a camera mounting bracket. The high-speed camera is fixedly connected to the tractor via the camera bracket and is used to acquire digital image information of the deformation of the impact sensor module when the tractor generates an impact.

[0034] The data processing module is used to process the digital image information acquired by the digital image acquisition module and calculate the magnitude of the tractor's impact force based on the type variables generated by the impact sensor module.

[0035] The display module is used to display the test results.

[0036] A tractor impact detection method based on digital image processing, based on the above-mentioned detection system, includes the following steps.

[0037] S1. Fix the impact sensor module and digital image acquisition module on the tractor under test.

[0038] S2. Start the tractor and operate it to start and reverse, causing the tractor to generate an impact.

[0039] S3, the digital image acquisition module acquires digital image data of the deformation of the impact sensor module when the tractor generates an impact.

[0040] S4. The data processing module processes the acquired digital image data and calculates the magnitude of the impact force of the tractor.

[0041] Processing acquired digital image data includes the following steps, such as: Figure 3 As shown.

[0042] S41. Input digital image data.

[0043] S42. Image preprocessing, including image grayscale conversion, Gaussian filtering for noise reduction, and contrast enhancement, such as... Figure 4 As shown.

[0044] S43. Image edge extraction and edge fitting. Image edge extraction includes gradient calculation, non-maximum constraint, double threshold detection, and edge connection of the preprocessed image, such as... Figure 5 As shown.

[0045] S44, Calculation of pixel values ​​for deformation.

[0046] S45. Through camera calibration, the pixel values ​​of the deformation variables are converted into actual deformation variables.

[0047] S46. Calculate the impact force based on the actual value of the variable.

[0048] S5. The calculation results are displayed through the display module.

[0049] In specific implementation, such as Figure 1 and 2 As shown, the impact sensor module can convert the magnitude of the impact force, which is difficult to observe, into the deformation of the rigid wire 2. When the tractor starts and reverses direction, the rigid wire 2 will deform due to inertia: when the impact of the tractor starting and reversing is large, the deformation of the rigid wire 2 is large; conversely, when the impact of the tractor starting and reversing is small, the deformation of the rigid wire 2 is small. By detecting the deformation of the rigid wire 2, the magnitude of the impact force can be calculated.

[0050] Since deformation is difficult to measure effectively and accurately using general tools, this invention uses digital image processing technology to measure the deformation of rigid wire 2, which includes two parts: digital image acquisition and data processing, implemented by a digital image acquisition module and a data processing module, respectively.

[0051] The hardware components of the digital image acquisition module include a high-speed camera, a data transmission cable, and a high-performance computer, while the acquisition software is the driver software for the high-speed camera.

[0052] The data processing module is the core of the invention, capable of calculating the deformation of the impact sensor module, calculating the impact force, and classifying the impact level. The deformation calculation is performed using digital image processing technology. The acquired video is parsed into frame-by-frame image data, and the image data is preprocessed. The impact sensor module is located using target recognition methods. Then, edge extraction and edge fitting are performed, the pixel values ​​of the deformation are calculated, and combined with a scale and camera calibration, the pixel values ​​of the deformation are converted into actual deformation. After calculating the deformation of the impact sensor module, a force analysis and idealized assumptions are made, simplifying it to an equivalent of a simple cantilever beam. The impact force is calculated based on the extended Huke's law.

[0053] During testing, the impact sensor module and high-speed camera were first installed on the tractor under test, and the high-performance computer, data processing module and other components were connected through a data transmission cable and inspected.

[0054] The tester operated the tractor to start and change direction. The impact of the tractor was converted into the deformation of the rigid wire 2, which was recorded by a high-speed camera and the captured digital image information was transmitted to the data processing module for processing.

[0055] Data processing includes deformation calculation based on digital image processing technology and impact force calculation based on extended Hooke's law, which is the core content of this invention. The deformation calculation of the impact sensor module includes digital image preprocessing, edge extraction and fitting, deformation pixel value calculation, camera calibration, and actual deformation value calculation, etc. Figure 3 As shown.

[0056] Image preprocessing mainly includes three parts: image grayscale conversion, Gaussian filtering for noise reduction, and image contrast enhancement. Figure 4 As shown.

[0057] Since subsequent edge detection is based on brightness gradients, and each of the RGB channels in a color image has its own gradient, direct processing can lead to inconsistencies or complex fusion problems. Converting the image to grayscale compresses the information into a single channel, simplifying computation and allowing focus on brightness variations.

[0058] The grayscale formula used in this invention is: , in, This represents the pixel value in the red channel of the image. The pixel values ​​of the image to be changed in the green channel. This represents the pixel value of the image in the blue channel. This represents the pixel value of the image after grayscale conversion.

[0059] After image grayscale conversion, Gaussian filtering is used to reduce noise in the image and its impact on subsequent edge extraction. Utilizing the weight distribution characteristics of the Gaussian function, a weighted average is applied to each pixel and its neighborhood pixels, assigning the highest weight to the central pixel and lower weight to pixels farther from the center. This effectively suppresses noise (especially Gaussian white noise) while preserving as many of the image's main features as possible.

[0060] After Gaussian filtering for noise reduction, this invention further enhances image contrast to more accurately extract edge information. The contrast enhancement process employs an adaptive histogram equalization algorithm, which locally enhances contrast, ensuring that each region of the image receives appropriate processing.

[0061] After image preprocessing, in order to calculate the deformation of the impact sensor module, edge extraction of the image is required to extract the rigid wire 2 of the impact sensor module in the image, so as to facilitate the calculation of the pixel value of the deformation.

[0062] Image edge extraction includes processes such as gradient calculation, non-maximum suppression, double threshold detection, and edge connection. Figure 5 As shown.

[0063] The pixel values ​​of the deformation are calculated based on the Euclidean distance, using the following formula: , in, , These are the pixel horizontal / vertical coordinates of the initial position of the free end of rigid wire 2. , The x / y coordinates of the pixels at the position of maximum deformation at the free end of rigid wire 2. The distance is the pixel distance in terms of shape.

[0064] The actual value of the deformation is determined through camera calibration. The rigid wire 2 of the impact sensor module is equipped with a scale that displays the standard actual length value. The pixel distance value corresponding to the standard scale is calculated from the acquired images, and the corresponding mapping ratio is calculated. Then, based on this mapping ratio and the pixel distance of the deformation... It can calculate the actual value of the deformation.

[0065] After calculating the actual value of the deformation, the magnitude of the impact force and the classification and display of the impact level can be calculated based on the extended Hooke's Law.

[0066] Impact force calculation includes model stress analysis and impact force calculation. Within the elastic deformation range of rigid wire 2, the stress model of the impact sensor module can be equivalently represented as a simple cantilever beam for stress analysis, such as... Figure 6 As shown.

[0067] Based on force analysis and the extended Hooke's law, we can obtain: , in, For deformable variables, For impact force, The elastic modulus of the material, Let be the moment of inertia of the cross section of rigid wire 2. The length of rigid wire 2, This refers to the distance from the reference point on the cantilever beam to the fixed end. In this embodiment, the reference point is the free end of rigid wire 2. .

[0068] The formula for calculating the moment of inertia I of the cross section is: , in, Pi The diameter of rigid wire 2 is given.

[0069] Calculate impact force The results are displayed through the display module.

[0070] This invention can also classify impact levels, such as... Figure 7 As shown, firstly, N vehicles of the same model are adjusted to different levels of impact. M tractor drivers (age distribution following a Poisson distribution) are selected to drive each vehicle in a tractor starting and reversing impact test. The magnitude of the impact force and the driver's perception of the corresponding impact are calculated. Finally, the data from multiple testers are summarized and analyzed to determine the impact level classification. Subsequently, starting and reversing impact tests can be performed on new vehicles.

[0071] It should be noted that the parts not described in detail in this solution are all prior art. The above embodiments are only used to illustrate the present invention, but the present invention is not limited to the above embodiments. Any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A tractor impact detection system based on digital image processing, characterized in that: It includes an impact sensor module, a digital image acquisition module, a data processing module, and a display module. The impact sensor module is fixedly mounted on the tractor under test and is used to convert the impact generated when the tractor reverses power into deformation. The digital image acquisition module is used to acquire digital image information of the deformation of the impact sensor module. The data processing module processes the digital image information acquired by the digital image acquisition module and calculates the magnitude of the tractor's impact force based on the type variables generated by the impact sensor module. The display module is used to display the test results.

2. The tractor impact detection system based on digital image processing as described in claim 1, characterized in that: The impact sensor module includes a base (1) and a rigid wire (2). The base (1) is used to fix it on the tractor. One end of the rigid wire (2) is fixedly connected to the base (1), and the other end extends freely. A length scale is provided on the rigid wire (2).

3. The tractor impact detection system based on digital image processing as described in claim 2, characterized in that: The free end of the rigid wire (2) is equipped with a counterweight (3) to enhance the sensitivity of the impact sensor module.

4. The tractor impact detection system based on digital image processing as described in claim 1, characterized in that: The digital image acquisition module includes a high-speed camera and a camera mounting bracket. The high-speed camera is fixedly connected to the tractor via the camera bracket and is used to acquire digital image information of the deformation of the impact sensor module when the tractor generates an impact.

5. A tractor impact detection method based on digital image processing, based on the detection system as described in claim 2, characterized in that: Includes the following steps, S1. Fix the impact sensor module and digital image acquisition module on the tractor under test; S2. Start the tractor and operate it to start and reverse, causing the tractor to generate an impact; S3, The digital image acquisition module acquires digital image data of the deformation of the impact sensor module when the tractor generates an impact; S4. The data processing module processes the acquired digital image data and calculates the magnitude of the impact force of the tractor. S5. The calculation results are displayed through the display module.

6. The tractor impact detection method based on digital image processing as described in claim 5, characterized in that: In step S4, the data processing module processes the acquired digital image data, including the following steps: S41. Input digital image data; S42, Image Preprocessing; S43, Image edge extraction and edge fitting; S44, Calculation of pixel values ​​for deformation; S45. Through camera calibration, the pixel values ​​of the deformation variables are converted into actual deformation variables; S46. Calculate the impact force based on the actual value of the variable.

7. The tractor impact detection method based on digital image processing as described in claim 6, characterized in that: Image preprocessing includes grayscale conversion, Gaussian filtering for noise reduction, and contrast enhancement.

8. The tractor impact detection method based on digital image processing as described in claim 6, characterized in that: Image edge extraction includes gradient calculation of the preprocessed image, non-maximum constraint, double threshold detection, and edge connection.

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