A fault diagnostic approach based on PSO-HMM for underwater thrusters-Reference-Cited by-同舟云学术

A fault diagnostic approach based on PSO-HMM for underwater thrusters

Published:2022 Issue:12 Volume:19 Page:12617-12631
ISSN:1551-0018
Container-title:Mathematical Biosciences and Engineering
language:
Short-container-title:MBE

Author:

Chu Zhenzhong¹²,Gu Zhenhao¹,Li Zhiqiang¹,Chen Yunsai³,Zhang Mingjun⁴

Affiliation:

1. Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China

2. School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

3. College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China

4. College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China

Abstract

<abstract> <p>In this paper, we describe an approach based on improved Hidden Markov Model (HMM) for fault diagnosis of underwater thrusters in complex marine environments. First, considering the characteristics of thruster data, we design a three-step data preprocessing method. Then, we propose a fault classification method based on HMMs trained by Particle Swarm Optimization (PSO) for better performance than methods based on vanilla HMMs. Lastly, we verify the effectiveness of the proposed approach using thruster samples collected from a fault emulation experimental platform. The experiments show that the PSO-based training method for HMM improves the accuracy of thruster fault diagnosis by 17.5% compared with vanilla HMMs, proving the effectiveness of the method.</p> </abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

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