Resonance Inspection of Aircraft Components Using Structural Modes
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Solution Overview
Problem
Existing non-destructive testing methods for aircraft propulsion system components are inadequate in accurately identifying internal defects such as cracks and voids, particularly in rotor disks, due to limitations in detecting structural modes and interpreting vibratory response signatures.
Innovation Solution
A resonance inspection system utilizing a control assembly with a processing system that generates multiple resonance spectra waveforms from vibratory responses, identifying structural modes by peaks and slope points within specific frequency ranges, and detecting internal defects by analyzing these waveforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional non-destructive testing methods are used, then inspection can be performed on aircraft propulsion system components, but the accuracy in detecting internal defects such as cracks and voids is insufficient
Solution Approach 1:
The patent segments the vibratory response signature into multiple resonance spectra waveforms (magnitude spectra, phase spectra, real spectra, imaginary spectra) to analyze different characteristics separately. This segmentation allows for more precise defect detection by examining specific waveform features that indicate internal defects, thereby improving measurement precision while maintaining reliability through comprehensive analysis of multiple waveform components.
Solution Approach 2:
The patent transitions from analyzing a single vibratory response signature to analyzing multiple resonance spectra waveforms that represent different dimensions of the component's dynamic response. By examining magnitude, phase, real, and imaginary spectra simultaneously, the system gains additional analytical dimensions that improve both defect detection accuracy and structural mode identification reliability.
2Measurement precision
If multiple resonance spectra waveforms are generated and analyzed, then internal defects can be accurately detected, but the complexity of the inspection system increases
Solution Approach 1:
The patent employs a multi-functional processing system that simultaneously generates and analyzes multiple resonance spectra waveforms (magnitude, phase, real, imaginary spectra) using a unified approach. This universal system performs multiple functions—structural mode identification, defect detection, and characterization—through integrated signal processing algorithms, thereby improving defect detection accuracy while managing system complexity through functional consolidation.
Solution Approach 2:
The patent transforms the vibratory response signature into multiple resonance spectra waveforms by changing the analytical parameters (magnitude, phase, real, imaginary components). This parameter transformation allows the system to extract different types of information from the same raw data, improving defect detection accuracy while avoiding the need for multiple separate measurement systems, thus controlling complexity.
3Reliability
If structural modes are identified using peak and slope point analysis, then internal defects can be detected, but the inspection process requires advanced signal processing capabilities
Solution Approach 1:
The patent replaces complex manual signal processing and interpretation with automated digital signal processing algorithms that systematically analyze resonance spectra waveforms. The processing system automatically identifies peaks and slope points, calculates their frequencies, and compares them against predetermined thresholds to identify structural modes and detect defects, thereby improving identification accuracy while reducing the practical difficulty of implementation.
Solution Approach 2:
The processing system performs self-service by automatically generating multiple resonance spectra waveforms, identifying structural modes through peak and slope point analysis, and detecting internal defects without requiring extensive manual intervention. The system uses predetermined frequency range thresholds and automated comparison algorithms to independently determine the presence of defects, reducing the operational difficulty while maintaining high reliability.
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
Enables accurate detection of internal defects in aircraft propulsion system components with minimal downtime and cost, facilitating efficient inspection of installed components using piezoelectric transducers and advanced signal processing.
Implementation Method 1
The probe may include at least one piezoelectric transducer electrically connected with the control assembly. The instructions, when executed by the processor, may further cause the processor to control the at least one piezoelectric transducer to apply a vibration to the component and measure the vibratory response signature of the component with the at least one piezoelectric transducer.
Implementation Method 2
The processing system includes a processor in communication with a non-transitory memory storing instructions, which instructions when executed by the processor, cause the processor to process resonance data including a vibratory response signature of a component over a portion of a frequency range of the vibratory response signature to generate a plurality of different resonance spectra waveforms of the vibratory response signature.
Data Source
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AI summary
A resonance inspection system includes a processing system (94). The processing system (94) is configured to process resonance data including a vibratory response signature of a component (66) to generate a plurality of different resonance spectra waveforms. The plurality of different resonance spectra waveforms includes a first resonance spectra waveform (1020) and a second resonance spectra waveform (1022). The processing system (94) is further configured to identify a presence or an absence of a structural mode of the component (66) using the first resonance spectra waveform (1020) and the second resonance spectra waveform (1022). The presence of the structural mode is identified by determining the first resonance spectra waveform (1020) includes a peak at a first frequency of the portion of the frequency range and the second resonance spectra waveform (1022) includes a maximum or a minimum slope point at a second frequency of the portion of the frequency range. The first frequency and the second frequency are within a predetermined frequency range threshold.