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

Abstract

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.

A Review of Signal Processing Techniques for Ultrasonic Guided Wave Testing

“…In each iteration, the signal is normalised, and its corresponding power spectrum is generated to detect the Torsional wave. However, due to significant changes in the excitation sequences, it is not recommended to use this algorithm with frequencies higher than 42 kHz [5].…”

“…The multi-modal and dispersive nature of guided waves makes the signal processing particularly challenging, which has been the subject of several studies over the years [4][5][6]. The used techniques are not necessary only for the interpretation of the received ultrasonic signals but also for procedure automation, which improves the non-destructive testing and evaluation, along with their reliability and replicability.…”

Circumferential Damage Monitoring of Steel Pipe Using a Radar Map Based on Torsional Guided Waves

“…The results show that the reflection coefficient of axisymmetric cracks increases monotonically with depth. Houman [16] proposed a method using the power spectrum difference between torsional waves and flexural waves to detect the torsional waves and determine the defect location. Kim and Park [17,18] used the basic torsional Sensors 2023, 23, 8734 2 of 12 mode to characterize the axial and inclined defects in the pipe and found that at a fixed depth of the defect, the reflection coefficient is a linear function of the ratio of the equivalent circumference range of the defect to the outer circumference of the pipe, and is almost independent of the axial range.…”

An analytical approach to reconstruction of axisymmetric defects in pipelines using T(0, 1) guided waves

“…Performance degradation of pipelines will undoubtedly affect normal operation and cause serious accidents like explosions and leakages. In order to check the working state of pipelines, many researchers have proposed various effective methods, by which defects have been successfully detected [1][2][3][4][5][6][7][8] .…”