Test System Image Recognition for Fixture Identification

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Solution Overview

Problem

Existing test systems face challenges in accurately identifying fixtures used in mechanical testing, leading to potential errors, damage to equipment or samples, and inefficient manual identification processes, especially when fixtures are swapped or their geometry is unknown.

Innovation Solution

Implementing image recognition technology using machine learning and neural networks to automatically identify fixtures by capturing and processing image data from cameras, allowing for precise detection and classification without requiring additional hardware on the fixtures.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual identification processes are used for fixtures, then operation simplicity is maintained, but identification accuracy and efficiency deteriorate

Engineering Contradiction:

Improvefixture identification accuracyVSAvoidmanual identification process

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The patent replaces manual visual inspection and identification of fixtures with an automated image recognition system using machine learning and neural networks. The system captures images of fixtures and automatically identifies them through computational algorithms, eliminating the need for manual identification while improving accuracy and efficiency.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If marking technologies are used on fixtures for identification, then identification accuracy is improved, but device complexity and cost increase

Engineering Contradiction:

Improvefixture identification accuracyVSAvoidfixture modification requirements

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent creates a digital copy or representation of the fixture through image capture and processing. Instead of modifying the physical fixture with marks or tags, the system uses image recognition to create a digital identifier that can be processed automatically, maintaining fixture simplicity while enabling accurate identification.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent replaces physical marking systems on fixtures with an optical-based image recognition system. This substitution eliminates the need for modifying fixtures with marks, tags, or other physical identifiers, thereby reducing device complexity while maintaining identification accuracy.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Extent of automation

If image recognition technology is implemented, then automation and identification accuracy are improved, but system complexity increases

Engineering Contradiction:

Improvefixture identification automationVSAvoidimage recognition system

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The patent implements a universal image recognition system that can identify multiple types of fixtures using the same hardware and software platform. The system is designed to handle various fixture geometries and configurations through a single automated process, reducing the need for multiple specialized identification systems and thereby managing complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The image recognition system is designed to autonomously identify fixtures without requiring external intervention or complex configuration. The machine learning models are trained to automatically recognize fixture types, and the system self-adjusts to different fixtures through automated image processing, reducing the operational complexity despite the advanced technology involved.

Inventive Principle:

Principle #25Self-service

4Adaptability or versatility

If fixtures are swapped frequently, then test system versatility is improved, but identification reliability deteriorates

Engineering Contradiction:

Improvefixture interchangeabilityVSAvoididentification accuracy

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent implements continuous image capture and processing to maintain constant monitoring of fixture identification. The system continuously acquires images of fixtures and processes them through the image recognition algorithm, ensuring that identification remains reliable even when fixtures are swapped frequently. This continuous operation eliminates gaps in identification that would occur with periodic or manual checking.

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

The image recognition system provides immediate feedback on fixture identification, allowing the test system to automatically adjust to the newly identified fixture. This real-time feedback mechanism ensures that identification reliability is maintained during fixture swaps, as the system can quickly detect and respond to changes in fixture configuration.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20240125682A1Image recognition in test systems

Publication Date: 2024.04.18 TA INSTRUMENTS WATERS LLC

AI summary

Described are systems and methods for image recognition in test systems. A method for safe operation of a test system includes capturing image data representative of a test area of the test system with an imaging device, transmitting the image data representative of the test area from the imaging device to a processor running an image recognition application, detecting, by the image recognition application, a user presence within the test area, and adjusting the test system to a safe mode in response to the detecting the user presence within the test area.