Towards Prevention of Oil/Gas Pipelines Vandalism

Simulation of the detection, identification and classification of the vibration signature of oil/gas pipelines in response to acts of vandalism is presented in this paper. In a real experimental field work, vibration signal data were acquired from a sample oil/gas steel pipe subjected to different excitation forces from human traffic, vehicular traffic, and impact on the pipe by separately using a hammer and a drilling machine. The data acquired from the use of a drilling machine were used as the reference input data to an intelligent system modelled to classify the vibration data during a simulation process by the use of the MATLAB fuzzy logic toolbox. During the simulation process, the frequency and power components of the vibration data were fuzzified into five linguistic variables each. Results from the simulation shows that the triangular membership function is most appropriate for use in the intelligent system. Results from the simulation also show that a relatively uniform vibration output value of 1.0 (on a scale of 0 to 1), being the desired output, was achieved. This value serves as an ideal value that can be used for the design of a system to detect and diagnose an act of vandalism on oil/gas pipelines. Any values outside of this would not be regarded as a force due to an act of vandalism.© 2018 EIJES