Acoustic Leak Rate Determination Using Frequency Filtering
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Solution Overview
Problem
Existing leak detection systems using acoustic emission sensors suffer from inaccuracy in converting acoustic signals to leak rates, with errors ranging from +100/-50% at low confidence and up to 10 times the calculated value at higher confidence levels, which is inadequate for nuclear safety applications.
Innovation Solution
The method involves filtering acoustic signals into low and high frequency components, calculating their ratio, and applying modal analysis techniques, such as Fourier transforms, to improve accuracy in determining leak rates through structures like valves or couplings, using a testing apparatus to correlate signal ratios with known leak rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If broadband acoustic emission sensors and simple signal processing are used, then device complexity is reduced and ease of operation is improved, but measurement precision deteriorates with errors up to +100/-50%
Solution Approach 1:
The patent divides the broadband acoustic signal into multiple frequency bands (low frequency component and high frequency component) using filters. This segmentation allows separate analysis of different frequency components, improving measurement precision by capturing distinct leak characteristics while maintaining manageable processing complexity through modular filter banks.
Solution Approach 2:
The patent transforms the acoustic signal from time domain to frequency domain using Fourier Transform, adding a frequency dimension to the analysis. This dimensional transformation enables differentiation of leak signatures across frequency bands, significantly improving measurement precision without substantially increasing operational complexity.
2Measurement precision
If extended time domain recording and manual Fourier Transform analysis are used, then measurement precision can be improved, but productivity decreases due to manual analysis requirements
Solution Approach 1:
The patent replaces manual mechanical analysis with automated electronic signal processing. Fourier Transforms and frequency component calculations are performed automatically by processing circuits, eliminating manual analysis while maintaining high measurement precision and significantly improving productivity through rapid automated leak rate determination.
Solution Approach 2:
The system performs self-analysis by automatically processing acoustic signals through filter banks and Fourier Transforms without requiring external manual intervention. The processing circuits autonomously calculate frequency components, determine ratios, and compute leak rates, enabling both high precision and rapid productivity.
3Measurement precision
If simple average signal level algorithms are used, then device complexity is minimized, but measurement precision deteriorates requiring lookup tables and manual calibration
Solution Approach 1:
The patent changes the analysis parameter from simple average signal level to frequency component ratios. By calculating the ratio between low and high frequency components, the system achieves superior measurement precision that captures physical leak characteristics. The automated ratio calculation maintains ease of operation despite the sophisticated parameter analysis.
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
This approach enhances the accuracy of leak rate calculations, reducing errors and providing reliable data suitable for high-standard industries like nuclear safety by establishing empirical relationships between acoustic signals and leak characteristics.
Implementation Method 1
Acoustic emission (AE) sensors are used widely to capture and record stress waves in materials. These stress waves may be caused by changes in material loads or due to physical changes to the materials
Implementation Method 2
receiving and separating through filters a low frequency component and a high frequency component of the acoustical signal
Implementation Method 3
conversion to the frequency domain using Fourier Transform processes
Data Source
AI summary
Disclosed herein are various implementations of systems and methods for improving the process and accuracy of converting acoustical signals to leak rates through a structure, such as a closed valve or coupling, using filtering techniques and modal analysis. These systems and methods may be useful for verifying the accuracy of the conventional approaches and inventive processes and systems for improving leak rate quantification using acoustic emissions. For example, a testing apparatus for simulating a leak through a structure and methods for correlating an acoustical signal with a leak rate are disclosed. The information gathered from the testing apparatus and/or correlation methods may be used in the field to determine more accurately the leak rate of a fluid or gas through the structure.