Paper
12 April 2005 Development of an automated ultrasonic testing system
Jiao Shuxiang, Brian Stephen Wong
Author Affiliations +
Proceedings Volume 5852, Third International Conference on Experimental Mechanics and Third Conference of the Asian Committee on Experimental Mechanics; (2005) https://doi.org/10.1117/12.621735
Event: Third International Conference on Experimental Mechanics and Third Conference of the Asian Committee on Experimental Mechanics, 2004, -, Singapore
Abstract
Non-Destructive Testing is necessary in areas where defects in structures emerge over time due to wear and tear and structural integrity is necessary to maintain its usability. However, manual testing results in many limitations: high training cost, long training procedure, and worse, the inconsistent test results. A prime objective of this project is to develop an automatic Non-Destructive testing system for a shaft of the wheel axle of a railway carriage. Various methods, such as the neural network, pattern recognition methods and knowledge-based system are used for the artificial intelligence problem. In this paper, a statistical pattern recognition approach, Classification Tree is applied. Before feature selection, a thorough study on the ultrasonic signals produced was carried out. Based on the analysis of the ultrasonic signals, three signal processing methods were developed to enhance the ultrasonic signals: Cross-Correlation, Zero-Phase filter and Averaging. The target of this step is to reduce the noise and make the signal character more distinguishable. Four features: 1. The Auto Regressive Model Coefficients. 2. Standard Deviation. 3. Pearson Correlation 4. Dispersion Uniformity Degree are selected. And then a Classification Tree is created and applied to recognize the peak positions and amplitudes. Searching local maximum is carried out before feature computing. This procedure reduces much computation time in the real-time testing. Based on this algorithm, a software package called SOFRA was developed to recognize the peaks, calibrate automatically and test a simulated shaft automatically. The automatic calibration procedure and the automatic shaft testing procedure are developed.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiao Shuxiang and Brian Stephen Wong "Development of an automated ultrasonic testing system", Proc. SPIE 5852, Third International Conference on Experimental Mechanics and Third Conference of the Asian Committee on Experimental Mechanics, (12 April 2005); https://doi.org/10.1117/12.621735
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Ultrasonics

Neural networks

Nondestructive evaluation

Autoregressive models

Pattern recognition

Detection and tracking algorithms

Filtering (signal processing)

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