Chapter 9
Burst Analysis for Multi-Level Leakage
Detection in Water-Filled Pipeline Based
on Acoustic Emission Signal
Bach Phi Duong, Jaeyoung Kim, Inkyu Jeong, and Jong-Myon Kim
Abstract This paper establishes a methodology to exploit the characteristics of
burst waveform in acoustic emission (AE) signals and combine with the signal analysis process to enhance the accuracy of multi-level leak detection in steel pipelines.
The AE bursts are signal waveforms that contain the continual imbrication transients
with variable strengths in the form of impulses and these impulses include the pivotal
information of the leakage syndromes. Capturing and isolation of a burst waveform
against the background signal strengthen the capability of a pipeline’s fault diagnosis system. First, this research employs a method using the Enhanced Constant
False Alarm Rate (ECFAR) to identify the bursts. Then, the information which is
extracted from the burst waveform segment is used to recognize their various sizes of
leakage in a laboratory simulated leak system. The training multi-class support vector
machine in the one-against-all strategy is responsible for the leak categorization. The
result of classification from the proposed method is compared with another algorithm
utilizing the wavelet threshold-based burst detection algorithm, which demonstrates
the ECFAR method gives an outperforms the wavelet threshold-based algorithm in
classification with the accuracy of 93% for different sizes of leakage.
9.1 Introduction
Metropolitan piping systems are popularly used to supply water, gas, and petroleum
for human lifestyle activities. The huge pipe systems, which are larger, longer, and
more complex, have become important assets of the government when they are used
in large-scale industrial factories for conducting different types of liquids, such as
chemicals, petroleum, oil, and spread over a long-range distance. In the water supply
system, approximately 20–30% of the water has been lost every year, some of the
loss quantity can be even up to 50% [1]. A pipeline leak not only wastes resources
but also increases risks of collapse or explosion and environmental pollution. Since
leaks are unavoidable consequence over a long-time using, the condition monitoring
B. P. Duong · J. Kim · I. Jeong · J.-M. Kim (B)
School of Electrical Engineering, University of Ulsan, Ulsan 680-749, South Korea
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
G. Shen et al. (eds.), Advances in Acoustic Emission Technology, Springer Proceedings
in Physics 259, https://doi.org/10.1007/978-981-15-9837-1_9
93
Burst Analysis for Multi-Level Leakage
Detection in Water-Filled Pipeline Based
on Acoustic Emission Signal
Bach Phi Duong, Jaeyoung Kim, Inkyu Jeong, and Jong-Myon Kim
Abstract This paper establishes a methodology to exploit the characteristics of
burst waveform in acoustic emission (AE) signals and combine with the signal analysis process to enhance the accuracy of multi-level leak detection in steel pipelines.
The AE bursts are signal waveforms that contain the continual imbrication transients
with variable strengths in the form of impulses and these impulses include the pivotal
information of the leakage syndromes. Capturing and isolation of a burst waveform
against the background signal strengthen the capability of a pipeline’s fault diagnosis system. First, this research employs a method using the Enhanced Constant
False Alarm Rate (ECFAR) to identify the bursts. Then, the information which is
extracted from the burst waveform segment is used to recognize their various sizes of
leakage in a laboratory simulated leak system. The training multi-class support vector
machine in the one-against-all strategy is responsible for the leak categorization. The
result of classification from the proposed method is compared with another algorithm
utilizing the wavelet threshold-based burst detection algorithm, which demonstrates
the ECFAR method gives an outperforms the wavelet threshold-based algorithm in
classification with the accuracy of 93% for different sizes of leakage.
9.1 Introduction
Metropolitan piping systems are popularly used to supply water, gas, and petroleum
for human lifestyle activities. The huge pipe systems, which are larger, longer, and
more complex, have become important assets of the government when they are used
in large-scale industrial factories for conducting different types of liquids, such as
chemicals, petroleum, oil, and spread over a long-range distance. In the water supply
system, approximately 20–30% of the water has been lost every year, some of the
loss quantity can be even up to 50% [1]. A pipeline leak not only wastes resources
but also increases risks of collapse or explosion and environmental pollution. Since
leaks are unavoidable consequence over a long-time using, the condition monitoring
B. P. Duong · J. Kim · I. Jeong · J.-M. Kim (B)
School of Electrical Engineering, University of Ulsan, Ulsan 680-749, South Korea
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021
G. Shen et al. (eds.), Advances in Acoustic Emission Technology, Springer Proceedings
in Physics 259, https://doi.org/10.1007/978-981-15-9837-1_9
93