Acoustic Emission Frequency Analysis for Structural Change Detection
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Solution Overview
Problem
Existing methods struggle to accurately and efficiently identify multiple simultaneous structural changes in objects, such as composite materials, using acoustic emissions analysis, as they often mask signal features and fail to correlate acoustic waveforms with specific modes of structural change.
Innovation Solution
An apparatus and method utilizing an acoustic sensing system and analyzer module to generate frequency distribution functions from acoustic waveform data, applying learning algorithms to identify and classify multiple structural events, enabling accurate assessment of structural integrity by correlating acoustic waveforms with load history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If currently available acoustic emissions detection methods are used, then the detection process can be performed, but the identification of multiple simultaneous structural changes is difficult, tedious, and time-consuming
Solution Approach 1:
The patent transforms acoustic waveform data into frequency distribution functions, changing the parameter domain from time to frequency. This transformation enables multiple structural events to be distinguished based on their unique frequency signatures, simultaneously improving identification speed and accuracy
Solution Approach 2:
The patent replaces manual analysis of acoustic waveforms with an automated computer-based system that performs frequency domain transformation and pattern recognition. This substitution eliminates the tedious manual process while maintaining high identification accuracy through algorithmic analysis
2Adaptability or versatility
If currently available acoustic emissions methods are used, then single type of structural event can be detected, but multiple simultaneous structural changes cannot be identified
Solution Approach 1:
The patent segments the complex acoustic signal into multiple frequency distribution functions, each representing different structural events. By dividing the frequency spectrum into distinct bands and analyzing each separately, the system can identify multiple simultaneous structural changes without signal features being masked
Solution Approach 2:
The patent adds a frequency dimension to the analysis by transforming time-domain acoustic waveforms into frequency-domain representations. This dimensional transformation allows simultaneous structural events to be distinguished based on their unique frequency characteristics, preventing information loss
3Measurement precision
If detailed frequency analysis is performed on acoustic waveform data, then structural changes can be identified, but the analysis becomes complex and time-consuming
Solution Approach 1:
The patent extracts only the relevant frequency distribution characteristics from the complex acoustic waveform data, discarding unnecessary time-domain details. This extraction process simplifies the analysis while maintaining the ability to identify structural changes with high precision
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 efficiently identifies previously undetectable structural changes, reducing testing costs and cycle time, and provides a reliable method for assessing structural integrity in composite materials by correlating acoustic emissions with specific modes of change.
Implementation Method 1
Acoustic emission is the radiation of acoustic waves in an object or material when the material undergoes a structural change
Data Source
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AI summary
An apparatus comprises an acoustic sensing system and an analyzer module. The acoustic sensing system is positioned relative to an object, wherein the acoustic sensing system detects acoustic emissions and generates acoustic waveform data for the acoustic emissions detected. The analyzer module is implemented in a computer system that receives load data and the acoustic waveform data for the object, generates a plurality of frequency distribution functions using the acoustic waveform data, and generates a frequency distribution function time evolution image containing a plurality of points of each of the plurality of frequency distribution functions.