By Topic

Research on monitoring and pre-warning system for security of pipelines based on multi-seismic sensors

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jiedi Sun ; Dept. of Inf. Sci. & Eng., Yanshan Univ., Qinhuangdao, China ; Jiangtao Wen

Aiming at the increasingly serious pipeline damages because of the artificial factors, we investigate the characteristic of seismic signals and develop a monitoring and pre-warning system for security of pipelines based on multi-seismic sensors. There were many sensors and processing modules to acquire the seismic signals generated by the ground targets. The non-stationary signal analysis method based on empirical mode decomposition was used to process the seismic signals. The target feature vectors were composed of the normalized kurtosis extracted from the decomposition results. The single sensor's judgment was made by the main normalized kurtosis values in the important decomposed frequency bands. In this system there are many same sensors and modules, this D-S evidence reasoning was to fuse the recognition results for improving the target recognition accuracy. Then the last judgment was made. For target localization, it proposed a novel passive localization method based on TDOA (time difference of arrival). The seismic signals generated by different targets were acquired by many geophones and detection modules. As a new time-frequency method, Hilbert-Huang transform was used to process the signals and obtained the characteristic frequencies and appearance time. The arrival time difference, the sensor location and the relative position of target and sensors were analyzed and the target localization can be achieved. The processing methods above were proved effective by the experiment data analysis.

Published in:

Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on

Date of Conference:

16-19 Aug. 2009