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Open Access

Leak detection method for pneumatic systems: a short review

Jiaqi CHANGaHuan SONGbShaoqiang YOUbJianfu CHENaZhiguo YANGaLei LIa,c( )Yixuan WANGc,dZhibo SUNc,dShaofeng XUcXiangkai SHENa,c( )Yan SHIa,c
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
China Railway 14th Bureau Group Co., Ltd., Jinan 250101, China
Liupanshan Lab, Yinchuan 750000, China
Engineering Training Center, Beihang University, Beijing 100191, China
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Abstract

Pneumatic systems are important fluid power transmission mechanisms in industrial automation. They use compressed air to transfer energy and signals. However, leaks, which are mainly from seal failures or degrading pipelines, cause many problems. These include unstable pressure, equipment failures, and lower production quality. To offset leaks, air compressors often run harder, wasting energy and raising costs. So, timely and reliable leak detection is crucial for system reliability, cost savings, and safety. This review systematically examines current pneumatic leak detection technologies. First, it covers system basics and common leak points. Then, it evaluates detection methods, from traditional sensors to advanced intelligent algorithms. These are judged on accuracy, speed, and ability to handle environmental interference. The article also discusses challenges in complex environments, the shift toward remote monitoring via multi-sensor fusion, and the Industrial Internet of Things (IIoT). This review provides a foundation for selecting the most effective detection methods and offers key insights for intelligent, energy-saving pneumatic maintenance systems.

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Journal of Advanced Manufacturing Science and Technology

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Cite this article:
CHANG J, SONG H, YOU S, et al. Leak detection method for pneumatic systems: a short review. Journal of Advanced Manufacturing Science and Technology, 2026, 6(2). https://doi.org/10.51393/j.jamst.2026010

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Received: 01 October 2025
Revised: 21 October 2025
Accepted: 23 November 2025
Published: 02 April 2026
© 2026 JAMST

This is an Open Access article distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.