Leakage detection method of underground heating pipeline based on improved wavelet threshold function

Ziqiang Xu, Cheng Li, Lianbo Mu, Suilin Wang, Junhui Lu and Yuncheng Lan

Energy, 2024, vol. 295, issue C

Abstract: For urban heating pipeline network, the intelligent and precise detection is an important guarantee for urban heating infrastructure of the safe and low-carbon operation. Heating pipe network was directly buried in the soil and difficult to detect the leakage point due to lack of non-excavation detection method for rapid repair. An improved noise reduction algorithm of the wavelet threshold function coupled with the acoustic method was used for the directly buried pipe leakage detection. Large-scale leakage experimental tests were used to validate the reliability. The influences of temperature, pressure, flowrates and leakage distance on the frequency and time domains were then investigated. Results show that the improved threshold function could well detect the leakage for directly buried hot water heating pipes. When the temperature increases, the leakage frequency domain spreads from 200 - 800 Hz to 50–1500 Hz. The pressure, flow rate, and leak point location could affect the amplitude feature. The accuracy ranges of the improved method in the different location, temperature and pressure and flowrates are separately 0.11–2.36%, 0.11–1.96%,0.11–3.49% and 0.16–1.55%, respectively.

Keywords: Efficient heating; Directly buried hot water pipeline; Leakage; Positioning; Improved wavelet threshold function (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544224008235
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:295:y:2024:i:c:s0360544224008235

DOI: 10.1016/j.energy.2024.131051

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().