Machine vision model for drip leakage detection of pipeline

Cong Xiao, Yiyuan Zhou, Yanwen Wu and Guodong Zhang

PLOS ONE, 2025, vol. 20, issue 1, 1-20

Abstract: The prevailing trend in industrial equipment development is integration, with pipelines as the lifeline connecting system components. Given the often harsh conditions of these industrial equipment pipelines, leakage is a common occurrence that can disrupt normal operations and, in severe cases, lead to safety accidents. Early detection of even minor drips at the onset of leakage can enable timely maintenance measures, preventing more significant leaks and halting the escalation of pipeline failures. In light of this, our study investigates a method for monitoring pipe drips in industrial equipment using machine vision technology. We propose a machine vision model specifically designed for pipe drip detection, aiming to facilitate monitoring of pipe system drips. The system designed to collect the image of the droplet side cross-section with a Charge charge-coupled device (CCD) industrial camera, is aided by the computer image processing system used to analyze and process the collected images. Image enhancement technology is applied to improve the visibility of the image and image filtering technology is applied to remove the noise of the image. With the help of image segmentation technology, target droplet identification and division are achieved. Morphological reconstruction and region-filling techniques are used to remove the noise caused by shooting in the side cross-section image, such as hollow, reflection, and irregular droplet edge, to upgrade the quality of the solution droplet edge. The mathematical model is established for boundary position points extracted from the droplet side cross-section image. Then, the fitting droplet image is drawn. The droplet volume is obtained by calculating the volume of the rotating body. The two-dimensional image of the target droplet is obtained dynamically through the camera capture technology. The droplet boundary extraction algorithm is proposed, and the three-dimensional model of the target droplet is established, so the volume calculation problem of the droplet is solved, which provides a way of thinking for drip leakage detection of the pipeline.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0316951 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 16951&type=printable (application/pdf)

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:plo:pone00:0316951

DOI: 10.1371/journal.pone.0316951

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().