CN-121977468-A - Method, device, equipment and storage medium for detecting tire tread depth

CN121977468ACN 121977468 ACN121977468 ACN 121977468ACN-121977468-A

Abstract

The invention relates to the technical field of tire tread detection and discloses a tire tread depth detection method, a tire tread depth detection device, electronic equipment and a storage medium, wherein the method comprises the steps of obtaining point cloud data of the surface of a tire, and extracting continuous point cloud segments from the point cloud data to obtain the continuous point cloud segments; the method comprises the steps of carrying out coordinate change rate analysis on each point cloud data in the continuous point cloud segment to obtain the coordinate change rate of each point cloud data, identifying the maximum gradient change point cloud data in the continuous point cloud segment according to the coordinate change rate, and calculating the tire tread depth measurement value corresponding to the tire surface according to the maximum gradient change point cloud data. According to the method and the device for detecting the tire tread depth, the continuous point cloud segments are subjected to coordinate change rate analysis, so that accurate distinction of different structural areas of the tire tread is realized, meanwhile, the tire tread depth measured value is calculated according to the maximum gradient change point cloud data, the limitation of single point cloud data measurement is avoided, and the reliability of a detection result is improved.

Inventors

ZHAN WEI
Lu Jialuo

Assignees

深圳市易检车服科技有限公司

Dates

Publication Date: 20260505
Application Date: 20251201

Claims (10)

1. A method for detecting the depth of a tire tread, the method comprising: acquiring point cloud data of the tire surface, and extracting continuous point cloud segments from the point cloud data to obtain continuous point cloud segments; Carrying out coordinate change rate analysis on each point cloud data in the continuous point cloud segment to obtain the coordinate change rate of each point cloud data; identifying maximum gradient change point cloud data in the continuous point cloud segment according to the coordinate change rate; And calculating a tire tread depth measurement value corresponding to the tire surface according to the maximum gradient change point cloud data.
2. The method for detecting the tire tread depth according to claim 1, wherein the extracting the continuous point cloud segment from the point cloud data to obtain the continuous point cloud segment comprises: Calculating Euclidean distance between the point cloud data to obtain Euclidean distance between the points; generating a clustering condition according to the Euclidean distance between the points; performing point cloud data clustering on the point cloud data according to the clustering condition to obtain a plurality of point cloud clusters; and extracting a plurality of point cloud clusters to generate continuous point cloud segments.
3. The method for detecting the tire tread depth according to claim 1, wherein the performing the coordinate change rate analysis on each point cloud data in the continuous point cloud segment to obtain the coordinate change rate of each point cloud data includes: carrying out coordinate arrangement on each point cloud data in the continuous point cloud segment to obtain a one-dimensional coordinate sequence; Performing adjacent coordinate difference operation on the one-dimensional coordinate sequence to obtain a difference value between adjacent coordinates; And determining the coordinate change rate of each point cloud data according to the difference value.
4. The method for detecting the depth of a tire tread according to claim 1, wherein the identifying the maximum gradient change point cloud data in the continuous point cloud segment according to the coordinate change rate includes: Performing region classification on each point cloud data in the continuous point cloud segment according to a preset threshold value and the coordinate change rate to obtain a classification region of each point cloud data; Searching the associated characteristic point cloud data pairs of the continuous point cloud segments according to the classification areas to obtain associated characteristic point cloud data pairs; and screening the point cloud data with the maximum gradient change for the correlated characteristic point cloud data to obtain the point cloud data with the maximum gradient change in the continuous point cloud segment.
5. The method for detecting the tire tread depth according to claim 4, wherein the searching the continuous point cloud segment for the associated feature point cloud data pair according to the classification area to obtain the associated feature point cloud data pair includes: Extracting rising point cloud data of the continuous point cloud segments according to the classification areas to obtain rising point cloud data; extracting descending point cloud data of the continuous point cloud segments according to the classification areas to obtain descending point cloud data; Performing associated point cloud data searching on the ascending point cloud data according to the descending point cloud data to obtain ascending associated point cloud data corresponding to the descending point cloud data; and splicing the descending point cloud data and the ascending associated point cloud data into an associated characteristic point cloud data pair.
6. The method for detecting the tire tread depth according to claim 4, wherein the filtering the associated feature point cloud data pair for the maximum gradient change point cloud data to obtain the maximum gradient change point cloud data in the continuous point cloud segment comprises: dividing the point cloud data in the correlated characteristic point cloud data pair into point cloud data of a significant descending region and point cloud data of a significant ascending region; Screening the point cloud data with the maximum negative gradient change according to the coordinate change rate, so as to obtain the point cloud data with the maximum negative gradient change; Screening the point cloud data with the maximum positive gradient change according to the coordinate change rate, so as to obtain the point cloud data with the maximum positive gradient change; and splicing the point cloud data with the maximum negative gradient change and the point cloud data with the maximum positive gradient change into the point cloud data with the maximum gradient change in the continuous point cloud segment.
7. The method for detecting the tire tread depth according to claim 1, wherein the calculating the tire tread depth measurement corresponding to the tire surface according to the maximum gradient change point cloud data comprises: Performing reference straight line fitting on the maximum gradient change point cloud data to obtain a reference straight line; performing vertical distance calculation on each point cloud data in the point cloud data preset range according to the reference straight line to obtain the vertical distance of each point cloud data in the point cloud data preset range; And determining a tire tread depth measurement corresponding to the tire surface according to the vertical distance.
8. A tire tread depth detection device, the device comprising: The acquisition and extraction module is used for acquiring point cloud data of the tire surface, and extracting continuous point cloud segments of the point cloud data to obtain continuous point cloud segments; the change rate analysis module is used for carrying out coordinate change rate analysis on each point cloud data in the continuous point cloud segment to obtain the coordinate change rate of each point cloud data; the identification module is used for identifying the maximum gradient change point cloud data in the continuous point cloud segment according to the coordinate change rate; And the calculation module is used for calculating the tire tread depth measured value corresponding to the tire surface according to the maximum gradient change point cloud data.
9. An electronic device, the electronic device comprising: at least one processor, and A memory communicatively coupled to the at least one processor, wherein, The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of tread depth detection as claimed in any one of claims 1 to 7.
10. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements a method of tread depth detection according to any one of claims 1 to 7.

Description

Method, device, equipment and storage medium for detecting tire tread depth Technical Field The present invention relates to the field of tire tread detection technology, and in particular, to a method, apparatus, device, and storage medium for tire tread depth detection. Background The tyre is used as the only part of the automobile contacting with the road surface, the tyre tread depth is directly related to the ground gripping performance, braking distance, drainage efficiency and even running safety of the automobile, the proper tyre tread depth can ensure that enough friction force is formed between the tyre and the road surface, particularly on wet and slippery road surfaces, the tyre tread grooves can effectively remove water on the road surface and avoid the phenomenon of water drift, when the tyre tread depth is insufficient, the tyre drainage capacity can be greatly reduced, the braking distance is obviously prolonged, sideslip easily occurs during sharp turning or emergency avoidance, and the running risk is obviously increased. At present, the traditional tire tread depth detection method still has a plurality of defects, on one hand, the partial tire tread depth detection method mainly depends on manual measurement by using a hand-held depth gauge or a tire tread gauge by an operator, but the mode is low in efficiency and is easily influenced by subjective factors, and is more difficult to realize large-scale and standardized detection requirements, on the other hand, the partial tire tread depth detection method usually takes the single-point height difference between the bottom of a groove and a tire tread as depth, but does not consider the overall shape of a tire section, and when the tire tread is locally worn unevenly, the single-point difference cannot reflect the real average depth, so that the accuracy of a detection result is easily insufficient. Therefore, in order to solve the problems of low efficiency and insufficient accuracy of the detection result of the existing method, the current tire tread depth detection method needs to be improved in order to meet the increasing demand of tire tread depth detection. Disclosure of Invention The invention provides a method, a device, equipment and a storage medium for detecting the depth of a tire tread, and mainly aims to solve the problem of low accuracy of a tire tread depth detection result. In order to achieve the above object, the present invention provides a method for detecting a tire tread depth, comprising: Acquiring point cloud data of the tire surface, and extracting continuous point cloud segments from the point cloud data to obtain continuous point cloud segments; Carrying out coordinate change rate analysis on each point cloud data in the continuous point cloud segment to obtain the coordinate change rate of each point cloud data; Identifying maximum gradient change point cloud data in the continuous point cloud segment according to the coordinate change rate; And calculating a tire tread depth measurement value corresponding to the tire surface according to the maximum gradient change point cloud data. The invention also provides a device for detecting the depth of the tire tread, which comprises: the acquisition and extraction module is used for acquiring point cloud data of the tire surface, and carrying out continuous point cloud segment extraction on the point cloud data to obtain continuous point cloud segments; The change rate analysis module is used for carrying out coordinate change rate analysis on each point cloud data in the continuous point cloud segment to obtain the coordinate change rate of each point cloud data; the identification module is used for identifying the maximum gradient change point cloud data in the continuous point cloud segment according to the coordinate change rate; and the calculation module is used for calculating the tire tread depth measurement value corresponding to the tire surface according to the maximum gradient change point cloud data. The present invention also provides an electronic device including: at least one processor, and A memory communicatively coupled to the at least one processor, wherein, The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the tread depth detection method described above. The present invention also provides a computer readable storage medium having stored therein at least one computer program that is executed by a processor in an electronic device to implement the above-described method of tire tread depth detection. According to the embodiment of the invention, invalid point cloud data are filtered, effective point cloud data capable of reflecting the shape of a tire main body are reserved, interference of irrelevant point cloud data is avoided, accurate distinction of different structural areas of the tire pattern is realized by carrying out coordinate change rate analysis on th