Abstract
Leaks in gas pipelines cause unnecessary waste of limited resources and produce danger factors, thus leak testing is necessary. Acoustic emission (AE) technology is one of the promising methods for pipeline leak testing. AE signals of pipeline leak carry the feature information of structure integrity (the dimension and location of leak source, etc.), which are stochastic and uncertain, and belongs to non-stationary signals. Because of the noise and the complexity of AE signal transmission, the identification of AE source is very difficult. On the basis of analyzing the characteristics of AE signal and background noise, we established a gas leak identification model for city gas pipeline in this paper. A leak identification method is presented based on spatial-temporal data fusion. The multi-data segments are fused in time and space will decrease incertitude in the process of identification. Experimental result shows that the inspection range can be up to 87m, and the identification rate can be up to 95% for Φ 1mm pinhole leak.
| Original language | English |
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| Title of host publication | 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06 |
| DOIs | |
| State | Published - 2006 |
| Externally published | Yes |
| Event | 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06 - Singapore, Singapore Duration: 5 Dec 2006 → 8 Dec 2006 |
Publication series
| Name | 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06 |
|---|
Conference
| Conference | 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06 |
|---|---|
| Country/Territory | Singapore |
| City | Singapore |
| Period | 5/12/06 → 8/12/06 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- Acoustic emission testing
- Data fusion
- Identification technique
- Pipeline leak
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