Statistical estimated parameter for pipeline condition monitoring using acoustic emission

This paper describes the application of acoustic emission for pipeline condition monitoring using pre-processed AE parameter and Gaussian distribution to establish characteristic features relating to each pipeline condition. In the experiments, two types of pipeline operating conditions were investigated: a normal pipe and a defective pipe. The results show that with the pre-processed statistical estimated parameter, (1/sigma) is very capable for revealing the microscopic failure occurred in the defected pipeline. The micro structure test is also performed in order to verify the sensitivity of the proposed method. The depth of the microscopic cracks is about 103 microns.