KLI

A Novel Pipeline Leak Detection Technique Based on Acoustic Emission Features and Two-Sample Kolmogorov?Smirnov Test

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Alternative Title
A Novel Pipeline Leak Detection Technique Based on Acoustic Emission Features and Two-Sample Kolmogorov?Smirnov Test
Abstract
Pipeline leakage remains a challenge in various industries. Acoustic emission (AE) technology
has recently shown great potential for leak diagnosis. Many AE features, such as root mean
square (RMS), peak value, standard deviation, mean value, and entropy, have been suggested to
detect leaks. However, background noise in AE signals makes these features ineffective. The present
paper proposes a pipeline leak detection technique based on acoustic emission event (AEE) features
and a Kolmogorov?Smirnov (KS) test. The AEE features, namely, peak amplitude, energy, rise-time,
decay time, and counts, are inherent properties of AE signals and therefore more suitable for recognizing
leak attributes. Surprisingly, the AEE features have received negligible attention. According
to the proposed technique, the AEE features are first extracted from the AE signals. For this purpose,
a sliding window was used with an adaptive threshold so that the properties of both burst- and
continuous-type emissions can be retained. The AEE features form distribution that change its shape
when the pipeline condition changes from normal to leakage. The AEE feature distributions for
leak and healthy conditions were discriminated using the two-sample KS test, and a pipeline leak
indicator (PLI) was obtained. The experimental results demonstrate that the developed PLI accurately
distinguishes the leak and no-leak conditions without any prior leak information and it performs
better than the traditional features such as mean, variance, RMS, and kurtosis.
Author(s)
Akhand Rai아흐마드 자후르주나예드 엠디김종면
Issued Date
2021
Type
Article
Keyword
acoustic emissionAcousticsKolmogorov-Smirnov testleak detectionNoisepipelineStatisticsNonparametric
DOI
10.3390/s21248247
URI
https://oak.ulsan.ac.kr/handle/2021.oak/9185
https://ulsan-primo.hosted.exlibrisgroup.com/primo-explore/fulldisplay?docid=TN_cdi_doaj_primary_oai_doaj_org_article_247a9aaf76bf4939a48f81993474b881&context=PC&vid=ULSAN&lang=ko_KR&search_scope=default_scope&adaptor=primo_central_multiple_fe&tab=default_tab&query=any,contains,A%20Novel%20Pipeline%20Leak%20Detection%20Technique%20Based%20on%20Acoustic%20Emission%20Features%20and%20Two-Sample%20Kolmogorov%3FSmirnov%20Test&offset=0&pcAvailability=true
Publisher
SENSORS
Location
스위스
Language
영어
ISSN
1424-8220
Citation Volume
21
Citation Number
24
Citation Start Page
8247
Citation End Page
8247
Appears in Collections:
Engineering > IT Convergence
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