Welding Fire Monitoring Using IR Baselines and Thermal Imaging
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Solution Overview
Problem
Current welding processes lack effective monitoring systems to detect and predict fire states during and after welding events, which can lead to safety hazards due to the high energy nature of welding and potential for false noise signals from IR technology.
Innovation Solution
A system utilizing IR sensors and cameras to capture and analyze thermal signatures before, during, and after welding, with a processor to differentiate noise from actual fire indicators, and alert mechanisms for early detection and prevention of fire states, considering material types and welding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If IR sensors are used to detect fire states during welding, then fire detection capability is improved, but false noise signals increase
Solution Approach 1:
The system performs preliminary actions by capturing baseline IR images of the work area before welding begins, storing these as reference signatures. During welding, real-time IR images are compared against these pre-established baselines to distinguish actual fire conditions from normal welding-related thermal variations, thereby reducing false noise signals while maintaining fire detection capability
Solution Approach 2:
The system implements feedback mechanisms by continuously comparing real-time IR sensor readings against baseline signatures and providing algorithmic analysis. The system processes sequential images, evaluates thermal patterns, and provides feedback on whether detected thermal anomalies represent actual fire conditions or normal welding variations, enabling dynamic adjustment and reduction of false positives
2Reliability
If IR image capture is used to monitor welding events, then fire state detection is improved, but system complexity increases
Solution Approach 1:
The system achieves multi-functionality by using the same IR imaging system for both weld quality inspection and fire state detection. The processor analyzes thermal signatures to evaluate weld characteristics while simultaneously monitoring for fire conditions, eliminating the need for separate dedicated systems and reducing overall complexity while maintaining reliable fire detection
Solution Approach 2:
The system merges previously separate functions of weld monitoring and fire detection into a single integrated system. By combining IR image capture, processing, and analysis for both purposes, the system reduces device complexity while improving reliability through cross-validation of thermal data for both weld quality and fire state assessment
3Measurement precision
If sensors are placed close to welding event, then detection accuracy is improved, but exposure to high energy and noise increases
Solution Approach 1:
The system transitions from point-based temperature sensing to area-based thermal imaging. By capturing two-dimensional IR images of the work area, the system achieves comprehensive detection accuracy while maintaining a safer distance from the welding arc, as the distributed sensor array in the camera detects thermal patterns across the entire field of view rather than requiring close proximity
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 system effectively monitors and predicts fire states near welding events, reducing the risk of fires by providing timely alerts and enabling remedial actions, while minimizing false positives through empirical baseline comparisons and noise signal discrimination.
Implementation Method 1
an IR image capture sensor to memorialize conditions related to a welding event and quantify variables that may be used to detect a state of fire
Implementation Method 2
Comparison of IR images between a hot weld surface and a steady state signature may be used to analyze a performed weld
Data Source
AI summary
The present invention relates to methods and apparatus for detection of fire states in the presence of welding activities. In some examples, the welding detection system may algorithmically calculate a risk of a fire state developing. In some embodiments, the welding fire detection and prevention system may communicate warning states to users, supervisors, equipment and/or building monitoring systems.