Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/64715
Title: Development of an intelligent data analytics system for real-time condition monitoring of gas pipes
Authors: Wong, Yuen Leng
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems
Issue Date: 2015
Abstract: The most economical and safest mode of transporting energy sources are through Gas and Oil pipeline network. In the aspect of transportation, it is a requirement for pipeline to fulfill high demands of safety, reliability, and efficiency. Hence, it led to the importance of Leak detection in transmission pipelines for safe operation. The failure to detect leaks will cause loss of property, human life in human hazards, as well as loss of valuable materials. Gas, such as methane and hydrocarbon gas leakage will cause negative impacts, such as air pollution and global warming. In order to minimize the probability of occurrence of leaks and their impacts, pipeline leak detection plays a crucial role. Today, there are many available technologies in the domain of leak detection. Leak detection methods can be categorized into two groups, optic and non-optic techniques. In this study, we will only look into non-optic as it provide better performance and efficiency. One of the leakage location technique is known as acoustic technique, where in this study, time difference of arrivals (TDOAs) is implemented. In this study, the chosen leak detection technique will be investigate in the area of performance, sensitivity, reliability and accuracy.
URI: http://hdl.handle.net/10356/64715
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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