  Oil and gas pipeline leakages lead to not only enormous economic loss but
also environmental disasters. How to detect the pipeline damages including
leakages and cracks has attracted much research attention. One of the promising
leakage detection method is to use lead zirconate titanate (PZT) transducers to
detect the negative pressure wave when leakage occurs. PZT transducers can
generate and detect guided stress waves for crack detection also. However, the
negative pressure waves or guided stress waves may not be easily detected with
environmental interference, e.g., the oil and gas pipelines in offshore
environment. In this paper, a Gaussian mixture model based hidden Markov model
(GMM-HMM) method is proposed to detect the pipeline leakage and crack depth in
changing environment and time-varying operational conditions. Leakages in
different sections or crack depths are considered as different states in hidden
Markov models (HMM). Laboratory experiments show that the GMM-HMM method can
recognize the crack depth and leakage of pipeline such as whether there is a
leakage, where the leakage is.
