Depth Scan Classification for Tire Tread Wear

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Solution Overview

Problem

Existing methods for measuring tire tread depth are prone to inaccuracies, whether manual or imaging-based, leading to incorrect assessments of tire wear and potential premature or delayed replacement.

Innovation Solution

A computing device is used to obtain and classify depth scan data from a tire, automatically selecting regions of interest and generating indicators based on depth measurements, allowing for accurate identification and visualization of tire tread depths.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If manual tread depth gauge is used, then measurement can be obtained, but measurement accuracy deteriorates due to human error

Engineering Contradiction:

Improvemanual measurement operationVSAvoidtread depth measurement accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent replaces manual mechanical measurement with an automated imaging-based depth scanning system. The system uses depth scanning technology to capture three-dimensional surface data of the tire tread, automatically calculating tread depth without human intervention, thereby eliminating manual measurement errors while maintaining ease of operation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent creates a digital copy of the tire tread surface through depth scanning. Instead of direct physical measurement, the system captures a three-dimensional digital model of the tread, from which accurate depth measurements are derived through image processing and analysis algorithms.

Inventive Principle:

Principle #26Copying

2Extent of automation

If imaging-based mechanisms are used, then automated measurement is achieved, but detection accuracy deteriorates due to incorrect tread detection

Engineering Contradiction:

Improveautomated tread depth measurementVSAvoidtread detection accuracy

Core Design Contradiction:

Extent of automationVSMeasurement precision

Solution Approach 1:

The patent applies local quality processing by selectively analyzing different regions of the depth scan data. The system identifies and focuses on specific tread features and regions of interest, applying targeted processing algorithms to enhance detection accuracy in critical areas while maintaining overall measurement efficiency.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent implements feedback mechanisms where the system iteratively refines its detection by comparing measured features against expected tread patterns. The depth scanning system adjusts its analysis based on detected features, validating and correcting measurements to ensure accurate tread detection and reduce false positives.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS11138748B2Method and apparatus for classifying depth scans

Publication Date: 2021.10.05 ZEBRA TECHNOLOGIES CORP

AI summary

A method for classifying depth scan data at a computing device includes: obtaining, at the computing device, a set of depth measurements and a graphical representation of the depth measurements; automatically selecting, at the computing device, a subset of the depth measurements indicating a region of interest; rendering, on a display of the computing device, an image including (i) the graphical representation of the depth measurements and (ii) a graphical indication of the region of interest overlaid on the graphical representation of the depth measurements; receiving, via an input device, a selection associated with the image; and generating a region of interest indicator based on the subset of the depth measurements and the selection.