Leak detection in liquefied gas pipelines by artificial neural networks

Journal Article · Tue Dec 01 04:00:00 EST 1998 · AIChE Journal

DOI:https://doi.org/10.1002/aic.690441209· OSTI ID:321088

Belsito, S; Lombardi, P; Andreussi, P; Banerjee, S ^[1]

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1. Consorzio Pisa Ricerche (Italy). Center for Energy and Environmental Technologies

A leak detection system for pipelines was developed by using artificial neural networks (ANN) for leak sizing and location and by processing the field data. This system can detect and locate leaks down to 1% of flow rates in pipelines carrying hazardous materials in about 100 s. A reference pipeline was considered for practical implementation of the package. The ability of the package to withstand spurious alarms in the event of operational transients was tested. The compressibility effect, due to packing of the liquid in the pipeline, causes many such spurious alarms. Adequate preprocessing of the data was performed by using a computer code in conjunction with the ANN to compensate for the operational variations and to prevent spurious alarms. The package detects leaks as small as 1% of the inlet flow rate and correctly predicts the leaking segment of pipeline with a probability of success that is greater than 50% for the smallest leak. In all cases, the timely response of the system was seen as a major advantage.

• OSTI ID: 321088
• Journal Information: AIChE Journal, Journal Name: AIChE Journal Journal Issue: 12 Vol. 44; ISSN 0001-1541; ISSN AICEAC
• Country of Publication: United States
• Language: English

Related Subjects

02 PETROLEUM
03 NATURAL GAS
LEAK DETECTORS
LEAK TESTING
LIQUEFIED NATURAL GAS
LIQUEFIED PETROLEUM GASES
NEURAL NETWORKS
PIPELINES