Linsheng Huo
Papers
1
Total Citations
40
H-Index
1
About
Linsheng Huo is a leading researcher in pipeline integrity and non-destructive evaluation, with a focus on intelligent monitoring systems for energy infrastructure. His work centers on developing innovative methods to detect and manage solid deposits—such as sand and wax—in pipelines, combining acoustic sensing, voice recognition, and machine learning to enable real-time, non-invasive diagnostics. One of his most cited contributions, "Detection of sand deposition in pipeline using percussion, voice recognition, and support vector machine" (2020, 40 citations), introduces a novel approach that leverages percussion-induced acoustic signals and support vector machine classification to identify deposit composition and mass, optimizing removal timing to reduce operational costs and improve efficiency. This work has significant implications for the oil and gas industry, where deposit buildup poses risks to flow assurance and pipeline safety. Huo’s research bridges mechanical engineering and data science, offering practical solutions for preventive maintenance. His achievements underscore a commitment to advancing pipeline health monitoring, making him a valuable resource for students and researchers exploring smart infrastructure and condition-based maintenance.
Research Focus
Key Achievements
Top Papers
- 1