Fault Diagnosis Based on Physics-Guided Multifractal Detrended Fluctuation Analysis for Marine Electric Thrusters

IF 4.5 2区 综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
IEEE Sensors Journal Pub Date : 2026-10-15 Epub Date: 2026-08-31 DOI:10.1109/JSEN.2026.3727069
Tao Xie;Yuan Gao;Xin Dong;Mengmeng Song;Jie Zhang;Feng Li
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引用次数: 0

Abstract

This article presents a physics-guided multifractal detrended fluctuation analysis (PMFDFA) method for bearing fault diagnosis in marine electric thrusters (METs). Phase-current signals acquired from the MET are used to construct physically interpretable multifractal features for noninvasive diagnosis. Bearing fault characteristic frequencies guide both VMD mode localization and period-synchronized multifractal detrended fluctuation analysis (MFDFA) box-length construction, thereby replacing empirical feature-extraction choices with physically traceable criteria. The method offers three main benefits: 1) phase-current sensing enables noninvasive monitoring while multifractal detrending suppresses low-frequency trends caused by marine load fluctuations; 2) multiscale descriptors capture fault-related nonlinear fluctuations for subsequent classification; and 3) the selected VMD modes and MFDFA box lengths have an explicit physical origin. In the within-platform closed-set experiments on the evaluated MET prototype, PMFDFA outperformed the implemented reference methods.
基于物理引导多重分形无趋势波动分析的船舶电推力器故障诊断
提出了一种基于物理指导的多重分形去趋势波动分析(PMFDFA)的船用电动推力器轴承故障诊断方法。从MET获得的相电流信号用于构建物理可解释的多重分形特征,用于无创诊断。轴承故障特征频率指导VMD模式定位和周期同步多重分形去趋势波动分析(MFDFA)盒长构建,从而用物理可追溯的标准取代经验特征提取选择。该方法具有三个主要优点:1)相电流传感实现无创监测,而多重分形趋势抑制了海洋负载波动引起的低频趋势;2)多尺度描述符捕获与故障相关的非线性波动,用于后续分类;3)所选择的VMD模式和MFDFA盒长具有明确的物理来源。在评估的MET原型的平台内闭集实验中,PMFDFA优于实现的参考方法。
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来源期刊
IEEE Sensors Journal
IEEE Sensors Journal 工程技术-工程:电子与电气
CiteScore
7.70
自引率
14.00%
发文量
2058
审稿时长
5.2 months
期刊介绍: The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice
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