Fluid pipe network intelligent detection and warning

Jin-ge Lv; Yajun Han; Yuyuan Chi; Yilun Han

doi:10.1117/12.2625275

12 December 2021 Fluid pipe network intelligent detection and warning

Jin-ge Lv, Yajun Han, Yuyuan Chi, Yilun Han

Proceedings Volume 12127, International Conference on Intelligent Equipment and Special Robots (ICIESR 2021); 1212709 (2021) https://doi.org/10.1117/12.2625275
Event: International Conference on Intelligent Equipment and Special Robots (ICIESR 2021), 2021, Qingdao, China

Abstract

With the construction of smart mines, intelligent detection methods and technologies have become particularly important. An intelligent detection and early warning system has been proposed for leaks caused by factors such as corrosion, aging, and unintentional destruction of underground coal mine pipe networks. The negative pressure wave detection method was used to solve the difficult detection of complex environmental background, and MATLAB was used to extract noise features to improve operational efficiency. The generalized cross-correlation time delay estimation was not used to improve positioning accuracy. use the theoretical basis of deep sparse filter learning to identify leaks, and achieve accurate classification and identification of leaks by quickly and effectively extracting data features; use fixed base stations under mines as points to implement rapid LAN publish, So that relevant persons in charge can grasp the leaked information and take different response measures in a timely manner.

Citation Download Citation

Jin-ge Lv, Yajun Han, Yuyuan Chi, and Yilun Han "Fluid pipe network intelligent detection and warning", Proc. SPIE 12127, International Conference on Intelligent Equipment and Special Robots (ICIESR 2021), 1212709 (12 December 2021); https://doi.org/10.1117/12.2625275

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