Acoustic Emission Analyzer for Composite Structural Integrity
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Solution Overview
Problem
Current methods for detecting acoustic emissions from objects struggle to accurately identify and classify multiple simultaneous structural changes, particularly in composite objects, as they often require signals from a single type of structural event and are unable to efficiently process data from multiple modes of change occurring during a given time interval.
Innovation Solution
An apparatus comprising an acoustic sensing system and an analyzer module that generates frequency distribution functions from acoustic waveform data and applies learning algorithms to correlate load data with specific modes of structural change, enabling quick and accurate assessment of structural integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If currently available acoustic emissions detection methods are used, then the detection process is simple, but the ability to identify multiple simultaneous structural changes is insufficient and time-consuming
Solution Approach 1:
The patent segments the acoustic emissions signal processing by dividing the frequency spectrum into multiple bands and applying different Hilbert envelope detection parameters to each band. This segmentation allows simultaneous analysis of multiple structural change modes that occur at different frequencies, enabling rapid identification of multiple concurrent events without time-consuming sequential analysis.
Solution Approach 2:
The patent transforms the time-domain acoustic signals into the frequency domain using Fourier transforms, then applies Hilbert envelope detection in the frequency domain. This dimensional transformation from time to frequency domain enables the simultaneous detection and classification of multiple structural change modes that would be difficult to distinguish in the time domain alone, thereby improving identification accuracy while maintaining speed.
2Loss of information
If acoustic sensors detect acoustic emissions from multiple simultaneous structural changes, then comprehensive data is obtained, but currently available methods cannot easily determine when multiple modes of structural change are occurring
Solution Approach 1:
The patent applies different Hilbert envelope detection parameters specifically to different frequency bands of the acoustic emissions signal. Each frequency band is processed with parameters optimized for detecting specific types of structural changes, allowing the system to preserve and identify information about multiple simultaneous structural change modes while using a systematic approach that manages analytical complexity.
Solution Approach 2:
The patent changes the detection parameters (Hilbert envelope parameters) based on the frequency band being analyzed. By adapting the detection parameters to match the characteristic frequencies of different structural change modes, the system can distinguish between multiple simultaneous events without requiring overly complex analysis methods, thus reducing information loss while controlling complexity.
3Measurement precision
If currently available methods require signals from a single type of structural event, then analysis is straightforward, but they cannot identify specific modes when multiple structural changes occur simultaneously
Solution Approach 1:
The patent creates a universal analysis framework that can handle both single-type and multi-type structural events using the same basic methodology. The multi-band Hilbert envelope detection approach with adaptive parameters provides a unified method that automatically adapts to detect and classify various structural change modes, whether one or multiple events occur simultaneously, thereby improving classification accuracy while maintaining versatility.
Solution Approach 2:
The patent employs dynamic parameter selection where the Hilbert envelope detection parameters are adjusted based on the frequency band and the characteristics of the acoustic emissions being analyzed. This dynamic adaptation allows the system to maintain high classification accuracy for different structural change modes while preserving the ability to handle diverse event types, effectively combining precision with versatility.
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 solution allows for the efficient identification and classification of multiple simultaneous structural events, providing a rapid and accurate assessment of an object's structural integrity by processing acoustic emissions data in conjunction with load history, even when multiple modes of change occur simultaneously.
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
A method and apparatus for analyzing an object (102, 200) using acoustic emissions (206). Load data (218) is received for the object (102, 200). Acoustic waveform data (212) is received for the object (102, 200) from an acoustic sensing system (104, 204). The acoustic waveform data (212) represents acoustic emissions (206) emanating from the object (102, 200) and is detected using the acoustic sensing system (104, 204). A plurality of bins (224) is created for the load data (218). A plurality of frequency distribution functions (228) is generated for the plurality of bins (224) using the acoustic waveform data (212). A set of learning algorithms is applied to the plurality of frequency distribution functions (228) and the acoustic waveform data (212) to generate an output that allows an operator to more easily and quickly assess a structural integrity of the object (102, 200).