Machine-Vision Axle Detection for Heavy-Vehicle Wheel Alignment

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing vehicle wheel alignment systems for heavy-duty vehicles require manual identification of axle count and configuration, which is time-consuming and prone to errors due to the wide variety of possible configurations, often necessitating additional operator intervention.

Innovation Solution

A machine-vision system with optical sensors and processing software automatically identifies axle count and configuration by analyzing images of optical targets on vehicle wheels, using relative spatial positions and orientations to determine axle counts and spacings.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual identification of axle count and configuration is used, then the system can handle various heavy-duty vehicle configurations, but the process is time-consuming and prone to human error

Engineering Contradiction:

Improveaxle identification accuracyVSAvoidaxle identification time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical identification process with an automated optical sensing and image processing system. Cameras capture images of the vehicle, and software automatically detects wheel positions, identifies axles, and determines axle configurations, eliminating human intervention in the measurement process.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system performs self-identification of axle configurations by automatically processing images and determining vehicle geometry without operator input. The software autonomously counts wheels, pairs them into axles, calculates spacing, and identifies vehicle types, making the system self-sufficient in the identification task.

Inventive Principle:

Principle #25Self-service

2Reliability

If manual identification of axle count and configuration is used, then the operator can review multiple options, but the process requires significant operator intervention and custom configuration

Engineering Contradiction:

Improveaxle configuration identification reliabilityVSAvoidsystem operation simplicity

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The patent replaces manual operator review and selection with automated image analysis. The system processes captured images through algorithms that automatically detect wheel positions, determine axle configurations, and identify vehicle types, eliminating the need for operators to manually review multiple configuration options.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system autonomously performs the complete identification process without requiring operator expertise or manual configuration. The software self-configures by automatically analyzing vehicle geometry from images and determining the appropriate axle configuration, making operation simple regardless of vehicle complexity.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If the system provides comprehensive vehicle configuration choices, then it can accommodate all heavy-duty vehicle types, but the numerous variations make manual selection time-consuming

Engineering Contradiction:

Improvevehicle configuration coverageVSAvoidaxle identification speed

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent replaces manual configuration selection with automated optical detection and image processing. The system captures vehicle images, automatically processes them to identify wheel positions and axle arrangements, and rapidly determines the correct configuration from comprehensive vehicle type databases without operator intervention.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system pre-processes vehicle configuration data and maintains comprehensive vehicle type databases in advance. When a vehicle is scanned, the system quickly matches detected features against pre-configured vehicle profiles, enabling rapid identification across all heavy-duty vehicle types without time-consuming manual selection.

Inventive Principle:

Principle #10Preliminary action

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

Automates the axle identification process, reducing human error and time consumption, enabling efficient and accurate vehicle wheel alignment procedures without manual operator intervention.

Implementation Method 1

at least one optical sensor to acquire images of optical targets disposed on vehicle wheels within an operative field of view

Methodology Applied

Scientific EffectOptical imaging: Photography

Data Source

PatentUS12553713B2System and method for detecting axle configuration on a multi-axle vehicle

Publication Date: 2026.02.17 HUNTER ENGINEERING COMPANY

AI summary

A machine-vision vehicle wheel alignment measurement system configured with at least one optical sensor to acquire images of optical targets disposed within an operative field of view. The system further includes a processing system configured with software instructions to determine relative spatial positions and orientations of one or more optical targets visible within images acquired by the optical sensor. The processing system is further configured with software instructions to automatically identify an axle count and axle configuration for a vehicle undergoing an alignment inspection or service using the determined relative spatial positions and orientations of the visible optical targets.