Abstract
A new approach to gas leakage detection in high pressure distribution networks is proposed, where two leakage detectors are modelled as a linear parameter varying (LPV) system whose scheduling signals are, respectively, intake and offtake pressures. Running the two detectors simultaneously allows for leakage location. First, the pipeline is identified from operational data, supplied by REN-Gasodutos and using an LPV systems identification algorithm proposed in[1]. Each leakage detector uses two Kalman filters where the fault is viewed as an augmented state. The first filter estimates the flow using a calculated scheduling signal, assuming that there is no leakage. Therefore it works as a reference. The second one uses a measured scheduling signal and the augmented state is compared with the reference value. Whenever there is a significant difference, a leakage is detected. The effectiveness of this method is illustrated with an example where a mixture of real and simulated data is used.
| Original language | American English |
|---|---|
| Pages (from-to) | 4657-4665 |
| Number of pages | 9 |
| Journal | Communications in Nonlinear Science and Numerical Simulation |
| Volume | 16 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 1 2011 |
Funding
This work was supported in part by FCT, Fundação para a Ciência e Tecnologia .
| Funders |
|---|
| Fundação para a Ciência e Tecnologia |
| Fundação para a Ciência e a Tecnologia |
ASJC Scopus Subject Areas
- Numerical Analysis
- Modeling and Simulation
- Applied Mathematics
Keywords
- Gas networks
- Kalman filter
- LPV subspace identification
- Leakage detection
Disciplines
- Computer Sciences
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