An EKF-Based Method and Experimental Study for Small Leakage Detection and Location in Natural Gas Pipelines
Autor: | Weihang Zhu, Qingmin Hou |
---|---|
Rok vydání: | 2019 |
Předmět: |
State variable
Computer science Pipeline (computing) Flow (psychology) extended Kalman filter 02 engineering and technology lcsh:Technology 01 natural sciences lcsh:Chemistry Extended Kalman filter natural gas pipeline Control theory Natural gas General Materials Science lcsh:QH301-705.5 Instrumentation Leakage (electronics) Fluid Flow and Transfer Processes lcsh:T business.industry pipeline leakage detection Process Chemistry and Technology 010401 analytical chemistry General Engineering small leaks 021001 nanoscience & nanotechnology lcsh:QC1-999 0104 chemical sciences Computer Science Applications Noise lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 Transient (oscillation) lcsh:Engineering (General). Civil engineering (General) 0210 nano-technology business lcsh:Physics |
Zdroj: | Applied Sciences, Vol 9, Iss 15, p 3193 (2019) Applied Sciences Volume 9 Issue 15 |
ISSN: | 2076-3417 |
Popis: | Small leaks in natural gas pipelines are hard to detect, and there are few studies on this problem in the literature. In this paper, a method based on the extended Kalman filter (EKF) is proposed to detect and locate small leaks in natural gas pipelines. First, the method of a characteristic line is used to establish a discrete model of transient pipeline flow. At the same time, according to the basic idea of EKF, a leakage rate is distributed to each segment of the discrete model to obtain a model with virtual multi-point leakage. As such, the virtual leakage rate becomes a component of the state variables in the model. Secondly, system noise and measurement noise are considered, and the optimal hydraulic factors such as leakage rate are estimated using EKF. Finally, by using the idea of an equivalent pipeline, the actual leakage rate is calculated and the location of leakage on the pipeline is assessed. Simulation and experimental results show that this method can consistently predict the leakage rate and location and is sensitive to small leakages in a natural gas pipeline. |
Databáze: | OpenAIRE |
Externí odkaz: |