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Article

Defect Detection using Power Spectrum of Torsional Waves in Guided-Wave Inspection of Pipelines

1
Department of Electronic and Computer Engineering, Brunel University London, Uxbridge UB8 3PH, UK
2
NSIRC, Granta Park, Cambridge CB21 6AL, UK
3
TWI, Granta Park, Cambridge CB21 6AL, UK
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(7), 1449; https://doi.org/10.3390/app9071449
Received: 24 January 2019 / Revised: 28 March 2019 / Accepted: 1 April 2019 / Published: 6 April 2019
(This article belongs to the Special Issue Ultrasonic Guided Waves)
Ultrasonic Guided-wave (UGW) testing of pipelines allows long-range assessment of pipe integrity from a single point of inspection. This technology uses a number of arrays of transducers separated by a distance from each other to generate a single axisymmetric (torsional) wave mode. The location of anomalies in the pipe is determined by inspectors using the received signal. Guided-waves are multimodal and dispersive. In practical tests, nonaxisymmetric waves are also received due to the nonideal testing conditions, such as presence of variable transfer function of transducers. These waves are considered as the main source of noise in the guided-wave inspection of pipelines. In this paper, we propose a method to exploit the differences in the power spectrum of the torsional wave and flexural waves, in order to detect the torsional wave, leading to the defect location. The method is based on a sliding moving window, where in each iteration the signals are normalised and their power spectra are calculated. Each power spectrum is compared with the previously known spectrum of excitation sequence. Five binary conditions are defined; all of these need to be met in order for a window to be marked as defect signal. This method is validated using a synthesised test case generated by a Finite Element Model (FEM) as well as real test data gathered from laboratory trials. In laboratory trials, three different pipes with defects sizes of 4%, 3% and 2% cross-sectional area (CSA) material loss were evaluated. In order to find the optimum frequency, the varying excitation frequency of 30 to 50 kHz (in steps of 2 kHz) were used. The results demonstrate the capability of this algorithm in detecting torsional waves with low signal-to-noise ratio (SNR) without requiring any change in the excitation sequence. This can help inspectors by validating the frequency response of the received sequence and give more confidence in the detection of defects in guided-wave testing of pipelines. View Full-Text
Keywords: signal processing; defect detection; torsional wave; power spectrum; sliding window; pipeline inspection; ultrasonic guided-waves (UGWs) signal processing; defect detection; torsional wave; power spectrum; sliding window; pipeline inspection; ultrasonic guided-waves (UGWs)
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MDPI and ACS Style

Nakhli Mahal, H.; Yang, K.; Nandi, A.K. Defect Detection using Power Spectrum of Torsional Waves in Guided-Wave Inspection of Pipelines. Appl. Sci. 2019, 9, 1449. https://doi.org/10.3390/app9071449

AMA Style

Nakhli Mahal H, Yang K, Nandi AK. Defect Detection using Power Spectrum of Torsional Waves in Guided-Wave Inspection of Pipelines. Applied Sciences. 2019; 9(7):1449. https://doi.org/10.3390/app9071449

Chicago/Turabian Style

Nakhli Mahal, Houman, Kai Yang, and Asoke K. Nandi. 2019. "Defect Detection using Power Spectrum of Torsional Waves in Guided-Wave Inspection of Pipelines" Applied Sciences 9, no. 7: 1449. https://doi.org/10.3390/app9071449

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