Weld Tool Audio Monitoring for Real-Time Defect Shutdown
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Solution Overview
Problem
Existing welding processes lack real-time monitoring and control mechanisms to detect defects such as burn through, leading to potential damage and subpar quality in welded products.
Innovation Solution
A system utilizing a microphone to capture audio signals, processed by an AI agent to identify sound signatures indicative of welding defects, issuing cease commands or initiating telework sessions to prevent defects, and providing real-time feedback through a vocational mask.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If real-time audio monitoring is implemented to detect weld defects, then welding quality is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical sensing systems with acoustic field-based detection. A microphone captures sound signatures during welding, and an AI agent analyzes these acoustic signals to detect defects like burn through. This substitution of mechanical/physical sensing with acoustic monitoring simplifies the overall system while maintaining high detection accuracy for weld quality.
2Measurement precision
If AI-based sound signature analysis is used to detect weld defects, then defect detection precision is improved, but loss of time in processing increases
Solution Approach 1:
The system implements real-time feedback by continuously monitoring audio signals during welding and immediately analyzing sound signatures for defect indicators. The AI agent processes acoustic data streamingly rather than in batches, providing instantaneous defect detection. This feedback loop ensures high detection precision while maintaining real-time operation without significant time delays.
Solution Approach 2:
The AI agent is pre-trained on extensive welding sound data to recognize defect patterns. This preliminary training enables the system to quickly identify defects during actual welding operations without requiring complex real-time computation. The pre-processed knowledge base of sound signatures accelerates defect detection while maintaining high precision.
3Reliability
If automated cease commands are issued upon defect detection, then reliability of welding process is improved, but productivity decreases due to operation interruptions
Solution Approach 1:
The system issues cease commands proactively when defect indicators are detected in sound signatures, preventing defective welds from completing. This preliminary anti-action stops the welding process before significant defects occur, ensuring high reliability. The automated response eliminates human reaction delays, maintaining both reliability and acceptable productivity by preventing rework.
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
Enhances welding quality by promptly detecting and mitigating defects, ensuring product integrity and providing educational opportunities for apprentices through real-time intervention and haptic feedback.
Implementation Method 1
a microphone configured to generate audio signals associated with a weld tool being used by a user to perform a welding operation on an object
Data Source
AI summary
A system includes a microphone configured to generate audio signals associated with a weld tool being used by a user to perform a welding operation on an object. A processing device executes an artificial intelligence agent trained to perform several functions to determine certain information. These functions include processing the audio signals to identify sound signatures indicative of a weld defect occurring during the welding operation, determining the presence of the weld defect based on the identified sound signatures, and issuing cease commands to cease operation of the weld tool in response to the determined presence of the weld defect. The system may also include a welding robot, peripheral haptic devices, and network interfaces to support remote interaction and haptic feedback between users. The system aims to enhance welding quality control through real-time audio monitoring and immediate intervention capabilities.