Implementation of Neural Networks for Prediction of Location and Orientation of Pipe Defects in Guided Wave Ultrasonic Testing

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Tayebi Siavash; YAGHOOTIAN AMIN; Fatahi Laleh

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Paper Information

Journal: Non-Destructive Testing Technology Year:2021 | Volume:2 | Issue:8 Page(s): 8-17

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Information Journal Paper

Title

Implementation of Neural Networks for Prediction of Location and Orientation of Pipe Defects in Guided Wave Ultrasonic Testing

Author(s)

Tayebi Siavash | YAGHOOTIAN AMIN | Fatahi Laleh | Issue Writer Certificate

Keywords

Nondestructive test

Wavelet Transform

Feature Extraction

Firefly Algorithm

Artificial Neural Network

Abstract

In this research, a method based on the classification and prediction of the neural network to determine the location and orientation of cracks in pipes is presented. For this purpose, first, the finite element method is used to model wave propagation and crack modeling in different locations and orientations. In this regard, two types of longitudinal and torsional guided excitation waves have been used. The obtained signals are processed to calculate the appropriate characteristics. In the present study, reflection echoes were measured, and five features were extracted at six levels from discrete wavelet decomposition of raw signals. Selected properties of the signals are processed to limit the size of the neural network model without losing information. For this purpose, the Firefly Algorithm method was used and fed to an Artificial Neural Network that predicts the location and orientation of the crack. In this study, conventional multilayer perceptron diffusion networks have been used. According to the obtained results, it is observed that the proposed method shows good accuracy in predicting the location and orientation of the crack, and the percentage of neural network errors is less than 7%.

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APA: Copy

Tayebi, Siavash, YAGHOOTIAN, AMIN, & Fatahi, Laleh. (2021). Implementation of Neural Networks for Prediction of Location and Orientation of Pipe Defects in Guided Wave Ultrasonic Testing. NONDESTRUCTIVE TESTING TECHNOLOGY, 2(8 ), 8-17. SID. https://sid.ir/paper/416179/en

Vancouver: Copy

Tayebi Siavash, YAGHOOTIAN AMIN, Fatahi Laleh. Implementation of Neural Networks for Prediction of Location and Orientation of Pipe Defects in Guided Wave Ultrasonic Testing. NONDESTRUCTIVE TESTING TECHNOLOGY[Internet]. 2021;2(8 ):8-17. Available from: https://sid.ir/paper/416179/en

IEEE: Copy

Siavash Tayebi, AMIN YAGHOOTIAN, and Laleh Fatahi, “Implementation of Neural Networks for Prediction of Location and Orientation of Pipe Defects in Guided Wave Ultrasonic Testing,” NONDESTRUCTIVE TESTING TECHNOLOGY, vol. 2, no. 8 , pp. 8–17, 2021, [Online]. Available: https://sid.ir/paper/416179/en

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