Intelligent Fault Diagnosis and Health Monitoring for Pipelines

Submission Deadline: 20 July 2025 View: 87 Submit to Special Issue

Guest Editors

Prof. Cuiwei Liu

Email: 20180093@upc.edu.cn

Affiliation: China University of Petroleum (East China), China

Homepage: 

Research Interests: Pipeline engineering

Dr. Hongfang Lu

Email: luhongfang@seu.edu.cn

Affiliation: Southeast University, China

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Research Interests: Energy storage and transportation engineering

Mr. Yuanbo Yin

Email: yyuanbo@126.com

Affiliation: College of Pipeline and Civil Engineering, China University of Petroleum (Huadong), China 

Homepage:

Research Interests: Oil and gas pipeline leakage monitoring, diffusion behavior and potential consequences of leaking oil and gas, and oil and gas pipeline risk assessment

Dr. Bohong Wang

Email: wangbh@zjou.edu.cn

Affiliation: School of Petrochemical Engineering & Environment, Zhejiang Ocean University, China

Homepage:

Research Interests: Pipeline safety and reliability, Facility health monitoring

Summary

This special issue focuses on the critical area of intelligent fault diagnosis and health monitoring for pipelines, with a specific emphasis on integrating new technologies and sustainable monitoring practices such as AI, Internet of Things (IoT), smart sensors, drones, and advanced data analytics. The goal is to address the challenges associated with ensuring the safety, efficiency, and longevity of pipeline systems through innovative approaches.

This special issue aims to explore and implement advanced sensing technologies to monitor the health and condition of various components of pipeline infrastructure, including transmission lines, distribution networks, valves, and compressor stations. This will involve the utilization of cutting-edge techniques such as various types of sensors, wireless sensor networks, and remote monitoring systems. These new technologies offer the potential for continuous monitoring, enabling real-time data collection, early detection of faults or leaks, and proactive maintenance interventions.

In addition to the adoption of new technologies, the special issue underscores the importance of sustainable monitoring practices. The research will assess the environmental impact, energy efficiency, and cost-effectiveness of the monitoring systems. By incorporating sustainability considerations, the development of monitoring approaches will not only ensure the health of pipeline infrastructure but also minimize environmental impact and resource consumption. The research topic aims to cover original articles or review articles that explore innovations in structural health monitoring (SHM) of pipelines based on innovative methods. The special issue is intended to include but not be limited to the following:

· Smart sensors and monitoring methods including fiber optic sensors, and acoustic emission sensors

· Remote monitoring using UAVs (drones), satellite imaging, and wireless sensor networks

· Dynamic and static behavior analysis of pipeline components based on monitoring system data

· Application of AI, machine learning, robotics, and new technologies in pipeline SHM

· Sensor network and large-scale sensor deployment monitoring methods

· Health and damage assessment

· Inversion of structural parameters based on monitoring information

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