Leak Detection Algorithm for Pipelines in Noisy Environments

Papastavrou, Georgios-Napoleon; Kousiopoulos, Georgios-Panagiotis; Kampelopoulos, Dimitrios; Karagiorgos, Nikolaos; Porlidas, Dimitrios; Nikolaidis, S.

doi:10.1109/melecon48756.2020.9140558

Cited by 3 publications

(1 citation statement)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Among various approaches, 33,34 the method wherein the cross-correlation function is adopted is known to be effective for TDoA estimation in an environment with noise. [35][36][37] Because the crosscorrelation function estimates the TDoA according to the correlation characteristics of the two signals, the noise signals, which are uncorrelated, do not contribute to the results of TDoA estimation.…”

Section: Theoretical Background Of Source Locationmentioning

confidence: 99%

Source location and anomaly detection for damage identification of buried pipelines using kurtosis-based transfer function

Lee,

Park,

Yoon

2023

Structural Health Monitoring

View full text Add to dashboard Cite

The failure of buried pipelines can lead to serious consequences such as explosions, environmental pollution, settlement, as well as economic loss. To prevent these outcomes, it is crucial to identify the causes of failure and monitor their signs. One of the main causes of failure is unexpected third-party interference (TPI), which is particularly challenging to detect. Regarding to this issue, this study proposes a new algorithm for monitoring impact damage, which can be used for prompt response and damage prevention. The algorithm is integrated into the system using two approaches. The first approach focuses on detecting the location of the damage (referred to as source location). A kurtosis-based transfer function was newly proposed to selecting the optimal frequency band for time-difference-of-arrival based source location, resulting in accurate pinpointing of damage, even in a noisy environment. The second approach is used to determine whether impact damage has actually occurred by observing newly suggested features in both the time and frequency domains (referred to as anomaly detection). These features evaluate the presence of damage and the similarity between signals. As a result, it was evaluated that the field applicability was higher than that of conventional methods, and the superiority of the proposed method was also verified through field experiments. The method proposed in this study is expected to enable immediate response when the integrity of the buried pipelines is on the line of failure due to TPI.

show abstract