19 research outputs found
Hidden Markov Models for Pipeline Damage Detection Using Piezoelectric Transducers
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
Measurement of CO2 leakage from pipelines under CCS conditions through acoustic emission detection and data driven modeling
CO2 leakage from carbon capture and storage (CCS) networks may lead to ecological hazards, bodily injury and economic losses. In addition, captured CO2 often contains impurities which affect the leakage behavior of CO2. This paper presents a method for continuous and quantitative measurements of CO2 leakage flowrate and the volume fraction of impurities by combining data-driven models with acoustic emission (AE) and temperature sensors. Three data-driven models based on artificial neural network (ANN), random forest (RF), and least squares support vector machine (LS-SVM) algorithms are established. The outputs from the three data-driven models are then integrated to give improved results. Experimental work was conducted on a purpose-built CO2 leakage test rig under a range of conditions. N2 was injected to the CO2 gas stream as an impurity medium. Results show that the integrated model yields a relative error within ±4.0% for leakage flowrate and ±3.4% for volume fraction of N2