Adaptive Tire Tread Scanning for Accurate Depth Profiles
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Solution Overview
Problem
Existing methods for measuring tire tread depth, such as manual gauges and imaging-based systems, are prone to errors and inefficiencies, particularly for inexperienced operators or varying tire sizes, leading to incomplete or inaccurate tire tread profiles.
Innovation Solution
A computing device equipped with a light emitter and image sensor that adaptsively scans the tire tread by detecting boundaries and dynamically determining scan trigger points, allowing for the generation of accurate tread profiles regardless of operator experience or tire size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If imaging-based tread depth measurement devices are used, then measurement accuracy is improved, but suitability is limited to specific operators and tire types
Solution Approach 1:
The system dynamically adjusts scan parameters including scan duration, trigger point selection, and boundary detection thresholds based on real-time sensor data analysis. This allows the imaging device to adapt to different tire sizes, tread patterns, and operator scanning speeds, resolving the contradiction between measurement precision and adaptability
Solution Approach 2:
The system changes operational parameters such as scan length, trigger points, and data acquisition timing based on detected boundary conditions and tire characteristics. By dynamically modifying these parameters, the system maintains high measurement accuracy across diverse tire types and operator skill levels
2Ease of operation
If fixed scan duration is used for tread depth measurement, then device operation is simplified, but measurement completeness deteriorates for varying tire sizes
Solution Approach 1:
The system continuously monitors sensor data during scanning and uses feedback from boundary detection algorithms to dynamically adjust scan termination. This feedback mechanism ensures complete tread profiles are captured for tires of varying sizes while maintaining simple operator interaction, as the system automatically adapts scan duration based on detected tire boundaries
3Device complexity
If manual tread depth gauge is used, then device complexity is reduced, but measurement accuracy and efficiency deteriorate
Solution Approach 1:
The system replaces manual mechanical gauge measurements with automated optical imaging and sensor-based depth measurement. This substitution eliminates operator error and mechanical wear issues while providing higher precision measurements, with the added benefit of automated boundary detection and adaptive scanning that compensates for the increased device complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution enables precise and efficient tire tread depth measurement, accommodating a range of operator skills and tire sizes, by dynamically adjusting scan duration and discarding non-contributory data, resulting in complete and accurate tread profiles.
Implementation Method 1
one or more representations of a treaded surface captured by a sensor
Data Source
AI summary
A method includes: monitoring sensor data including one or more representations of a treaded surface captured by a device; detecting, based on the sensor data, that the device has traversed a boundary of the treaded surface; in response to detecting that the device has traversed the boundary, determining a scan trigger point within the one or more representations; and generating a profile of the treaded surface from the one or more representations based on the scan trigger point.