Results 21 to 30 of about 4,524,731 (322)
Harmonic adaptive fault-tolerant control for incipient and multiple faults of high mobility fighter [PDF]
Scientific ReportsThis paper proposes a harmonic adaptive fault-tolerant control (FTC) designed to handle multiple disturbances and faults, including incipient faults, in high-mobility fighter aircraft.
Kaiyu Hu, Zhaoyang Wang, Jia Wang
doaj +2 more sources
A Tensor-Based Approach for Identification of Multi-Channel Bearing Compound Faults
IEEE Access, 2019 Vibration signal analysis is one of the most effective approaches for detecting faults in bearings. A bearing compound-fault signal always consists of multiple signatures and stochastic noise.
Chaofan Hu, Yanxue Wang, Tangbo Bai
doaj +2 more sources
Diagnosis of Compound Fault Using Sparsity Promoted-Based Sparse Component Analysis [PDF]
Sensors, 2017 Compound faults often occur in rotating machinery, which increases the difficulty of fault diagnosis. In this case, blind source separation, which usually includes independent component analysis (ICA) and sparse component analysis (SCA), was proposed to ...
Yansong Hao +4 more
doaj +3 more sources
ResGRU: A Novel Hybrid Deep Learning Model for Compound Fault Diagnosis in Photovoltaic Arrays Considering Dust Impact [PDF]
SensorsWith the widespread deployment of photovoltaic (PV) power stations, timely identification and rectification of module defects are crucial for extending service life and preserving efficiency.
Xi Liu +7 more
doaj +2 more sources
Compound mechanical fault diagnosis based on CMDE [PDF]
Advances in Mechanical Engineering, 2022 The fault diagnosis technique is of important for the safety operation of the rotating machinery. In the fault diagnosis framework, the entropy-based method is a promising tool for the feature extraction and signal processing. Among the entropy-based methods, the diversity entropy has arisen increasing attention due to its merits of high consistency ...
Guangwei Yu, Xianzhi Wang, Chunlin Da
openaire +2 more sources
An Improved Convolutional Capsule Network for Compound Fault Diagnosis of RV Reducers
Sensors, 2022 In fault diagnosis research, compound faults are often regarded as an isolated fault mode, while the association between compound faults and single faults is ignored, resulting in the inability to make accurate and effective diagnoses of compound faults ...
Qitong Xu +3 more
doaj +1 more source
An intelligent compound gear-bearing fault identification approach using Bessel kernel-based time-frequency distribution [PDF]
Metrology and Measurement Systems, 2023 The most crucial transmission components utilized in rotating machinery are gears and bearings. In a gearbox, the bearings support the force acting on the gears.
Athisayam Andrews, Kondal Maniseka
doaj +1 more source
Sensors, 2023 Fault diagnosis is important in rotor systems because severe damage can occur during the operation of systems under harsh conditions. The advancements in machine learning and deep learning have led to enhanced performance of classification. Two important
Taehwan Son, Dongwoo Hong, Byeongil Kim
doaj +1 more source
Improved DCNN Based on Multi-Source Signals for Motor Compound Fault Diagnosis
Machines, 2022 Induction motors, the key equipment for rotating machinery, are prone to compound faults, such as a broken rotor bars and bearing defects. It is difficult to extract fault features and identify faults from a single signal because multiple fault features ...
Xiaoyun Gong +4 more
doaj +1 more source
Sensors, 2023 Gearboxes are one of the most widely used speed and power transfer elements in rotating machinery. Highly accurate compound fault diagnosis of gearboxes is of great significance for the safe and reliable operation of rotating machinery systems.
Qinghong Xu +4 more
doaj +1 more source