论文标题
使用压电传感器的隐藏马尔可夫模型用于管道损伤检测
Hidden Markov Models for Pipeline Damage Detection Using Piezoelectric Transducers
论文作者
论文摘要
石油和天然气管道泄漏不仅导致巨大的经济损失，而且导致环境灾难。如何检测包括泄漏和裂缝在内的管道损失引起了很多研究的关注。有希望的泄漏检测方法之一是使用锆钛酸铅（PZT）换能器在发生泄漏时检测负压波。 PZT换能器也可以生成和检测引导的应力波，以进行裂纹检测。但是，通过环境干扰，例如，在海上环境中的油气和天然气管道，可能无法轻易检测到负压波或引导应力波。在本文中，提出了基于高斯混合模型的隐藏模型（GMM-HMM）方法，以检测不断变化的环境和随时间变化的操作条件中的管道泄漏和裂纹深度。在隐藏的马尔可夫模型（HMM）中，不同部分或裂纹深度的泄漏被认为是不同的状态。实验室实验表明，GMM-HMM方法可以识别管道的裂纹深度和泄漏，例如是否存在泄漏，泄漏所在。
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.
