Ultrasonic Gas Leak Detector ANN Discrimination
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Solution Overview
Problem
Conventional ultrasonic gas leak detectors struggle to differentiate between real gas leaks and false alarms from manmade or natural sources, leading to unnecessary shutdowns and delayed remedial actions, and lack effective means for performance verification during proof testing.
Innovation Solution
An ultrasonic gas leak detection system employing a pre-polarized or fiber optical microphone, digital signal processing, and an artificial neural network (ANN) for signal pre-processing and classification, which distinguishes between real gas leaks and false alarms, allowing for improved discrimination and quantification of gas leaks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the alarm threshold level is raised several decibels above the background ultrasonic level to mitigate false alarms, then false alarm reduction is improved, but detection distance and total area of coverage are reduced
Solution Approach 1:
The system changes the parameter of threshold setting from a fixed high threshold to a dynamic threshold that adapts to background noise levels. By continuously monitoring and adjusting the threshold based on actual background ultrasonic levels, the system maintains both false alarm reduction and detection area coverage.
Solution Approach 2:
The system implements feedback by continuously monitoring background ultrasonic levels and using this information to dynamically adjust the alarm threshold. This closed-loop approach allows the threshold to self-optimize based on environmental conditions, resolving the contradiction between false alarm reduction and detection coverage.
2Reliability
If lengthy time delays are used to prevent false alarms, then false alarm reduction is improved, but remedial action time is delayed
Solution Approach 1:
The system changes the parameter of response timing from fixed lengthy delays to adaptive response based on signal characteristics. By analyzing the temporal patterns and persistence of ultrasonic signals, the system can distinguish between transient false alarms and sustained gas leaks, enabling timely remedial action while preventing false alarms.
Solution Approach 2:
The system uses feedback from continuous signal analysis to dynamically determine when to trigger alarms. By monitoring the persistence and pattern of ultrasonic signals in real-time, the system can confidently distinguish between false alarms and actual gas leaks, eliminating the need for lengthy fixed delays while maintaining false alarm reduction.
3Device complexity
If conventional threshold-based detection is used, then device complexity is reduced, but the ability to verify performance in the field and conduct functional safety checks is lost
Solution Approach 1:
The system achieves multi-functionality by enabling the same ultrasonic detection system to perform both gas leak detection and performance verification through a single interface. The ability to distinguish between remote ultrasonic test sources and actual gas leaks allows the system to conduct functional safety checks without requiring separate testing equipment or bypassing critical proof testing.
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 reduces false alarms, extends detection range and area coverage, and enables timely remedial actions by accurately identifying gas leaks, thereby enhancing industrial safety and reducing operational costs.
Implementation Method 1
Ultrasonic gas leak detectors measure the sound pressure waves generated by the turbulent flow when gas escapes from higher pressures to the ambient atmosphere
Implementation Method 2
An ultrasonic gas leak detection system employing a pre-polarized or fiber optical microphone
Data Source
AI summary
An ultrasonic gas leak detector is configured to discriminate the ultrasound generated by a pressurized gas leak into the atmosphere from false alarm ultrasound. An exemplary embodiment includes a sensor for detecting ultrasonic energy and providing sensor signals, and an electronic controller responsive to the sensor signals. In one exemplary embodiment, the electronic controller is configured to provide a threshold comparator function to compare a sensor signal value representative of sensed ultrasonic energy to a gas detection threshold value, and an Artificial Neural Network (ANN) function for processing signals derived from the digital sensor signals and applying ANN coefficients configured to discriminate false alarm sources from gas leaks. An output function generates detector outputs in dependence on the threshold comparator output and the ANN output.