Abstract
Pipeline plays an important role in various systems of the ship. However, due to the harsh environment, leakage often occurs in ship pipeline. This paper proposes a method to identity and locate the pipeline leakage. Using the variational mode decomposition (VMD) algorithm, the vibration signal is decomposed into band-limited intrinsic mode functions (BIMFs). The effective BIMFs are then selected by the correlation coefficient. Center frequency and energy value of the effective BIMFs are extracted as feature vector. Radial Basis Function (RBF) neural network is then used as a tool to identify and locate the leakage. The proposed method is finally verified by experiments.
Highlights
Pipeline is used to transport liquid or gas and is an important part of various systems in the ship
Ship pipeline leakage occurs frequently due to the harsh working environment and insufficient maintenance
In order to reasonably select the effective band-limited intrinsic mode functions (BIMFs), this paper introduces the concept of Pearson correlation coefficient
Summary
Pipeline is used to transport liquid or gas and is an important part of various systems in the ship. There are few methods for pipeline leakage detection in ship. A large number of studies have been conducted regarding the methods of detecting and locating pipeline leaks based on vibration signals. Continuously monitored the leakage signal of the furnace pipe They used self-adaptive filter to eliminate the noise, and recognized the leakage by the spectrum analysis of the leakage signal [3]. Gu Xiaohong divided the signal into different frequency bands with the method of wavelet packet decomposition They extracted the energy characteristics and selected the useful frequency bands for the cross-correlation analysis, which reduced the noise interference and improved the positioning accuracy [6].
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