In modern cities most pipelines such as those for oil, gas, and water supply networks are buried underground. In order to prevent these lifeline infrastructures from being broken accidentally, monitoring systems are becoming indispensable. Recent reports show that most pipeline damage is caused by third-party activities. In this paper, a novel automatic pipeline monitoring system is proposed in order to prevent accidental third-party damage. In this study, potential threat to pipeline integrity is recognized by detecting the existence of road cutters, which actually prelude ground construction. Sound recognition technologies are used to identify road cutters by sound, which can easily be captured by small sensors installed along the pipelines. A pattern classification method based on the Mel frequency cepstral coefficient (MFCC) feature is used in this study to identify cutter sounds. The location of the potential threat can be well detected by knowing which sensor is sounding an alarm and relevant measures can then be expediently executed. Experiments were conducted and the resulting data were analyzed. Results showed that cutters can be effectively recognized by the MFCC distance. This pipeline monitoring system can be deployed easily along pipelines with low cost and poses no significant privacy problems to nearby residents. It can help prevent accidental pipeline breakage thus ensuring the longevity of those underground lifeline infrastructures.
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