Tire Damage Detection Using Rim Diameter Reference
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Solution Overview
Problem
Existing methods for detecting tire damage on construction vehicles traveling on uneven ground face challenges, as imaging a scale with the vehicle is impractical due to dirt accumulation and the difficulty in accurately detecting damage without a reference scale.
Innovation Solution
A tire damage detection system and program that acquires image data of the tire and rim wheel, uses rim information to detect damage size based on the rim wheel's diameter, and outputs damage information, eliminating the need for a reference scale by employing image data acquisition, rim information acquisition, and deep learning-based damage detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a scale is installed on the construction vehicle to detect crack width, then measurement precision is improved, but the scale surface becomes dirty quickly reducing reliability
Solution Approach 1:
The reference object (scale) is extracted from the vehicle body and placed on the ground instead. This removes the scale from the harsh environment where it would accumulate dirt, while still allowing it to serve as a reference for measuring crack widths in tire images captured during vehicle operation.
Solution Approach 2:
A reference object (scale or ruler) is introduced as an intermediary element placed on the ground to provide a known measurement reference. This intermediary allows the system to calculate real-world dimensions of tire cracks by comparing pixel measurements in images against the known dimensions of the reference object, eliminating the need for direct contact between the scale and the vehicle.
2Difficulty of detecting and measuring
If image processing is performed to detect tire damage, then detection capability is improved, but accuracy is reduced without a reference scale
Solution Approach 1:
A reference object with known dimensions is introduced as an intermediary to bridge the gap between pixel measurements and real-world dimensions. The reference object appears in the same image as the tire damage, allowing the system to calculate scaling factors and convert pixel-based measurements into accurate real-world measurements of crack widths and damage areas.
Solution Approach 2:
The system changes the parameter used for measurement from direct pixel counting to scaled pixel measurements. By capturing images that include both the tire damage and a reference object, the system can calculate a scaling factor (pixels per unit length) and use this to convert image measurements into accurate real-world dimensions, thereby improving measurement precision.
Data Source
AI summary
A tire damage detection system (10) is provided with an image data acquisition unit (120) which acquires image data including a rim wheel and a tire side part of a tire assembled to the rim wheel, a rim information acquisition unit (130) which acquires rim information including a radial size of the rim wheel associated with the tire, an damage detection unit (140) which detects an damage portion of the tire side part on the basis of the image data and detects a size of the damage portion with reference to a diameter of the rim wheel based on the rim information, and an output unit (150) which outputs information on the damage portion detected by the damage detection unit (140).