Leakage detection of tailing pipeline based on multisensor and multientropy fusion

Changqian Chen; Zuoshi Liu; Yufeng Luo

doi:10.1117/12.3014856

4 March 2024 Leakage detection of tailing pipeline based on multisensor and multientropy fusion

Changqian Chen, Zuoshi Liu, Yufeng Luo

Proceedings Volume 12981, Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023); 129810W (2024) https://doi.org/10.1117/12.3014856
Event: 9th International Symposium on Sensors, Mechatronics, and Automation (ISSMAS 2023), 2023, Nanjing, China

Abstract

In view of the low leakage detection rate of tailings pipeline, a method of tailing pipeline leakage detection based on multisensor and multi-entropy fusion was proposed. Firstly, the parameters of VMD algorithm were optimized by Sparrow Search Algorithm. The signal is decomposed by an optimized VMD algorithm, and the decomposed modal components are screened and reconstructed by kurtosis analysis. After that, the leakage experiment platform is built, the signal is collected by infrasound and negative pressure wave sensors, and the singular spectrum entropy and sample entropy of the pipeline signal are calculated, and the threshold interval of the two are obtained as the basis for judgment. Leakage experiments show that this method can accurately judge the leakage signal, and compared with the single sensor and single entropy fusion method, the accuracy is significantly improved.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Changqian Chen, Zuoshi Liu, and Yufeng Luo "Leakage detection of tailing pipeline based on multisensor and multientropy fusion", Proc. SPIE 12981, Ninth International Symposium on Sensors, Mechatronics, and Automation System (ISSMAS 2023), 129810W (4 March 2024); https://doi.org/10.1117/12.3014856

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available