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Hybrid Adaptive Fault-Tolerant Control for Compound Faults of Hypersonic Vehicle

open access: yesIEEE Access, 2021
This study investigates the hybrid fault-tolerant control (FTC) for hypersonic flight vehicles (HFVs) under the rudder structure fault (RSF) and rudder angle deviation fault (RADF).
Kai-Yu Hu, Wenhao Li, Zian Cheng
doaj   +2 more sources

Compound Fault Characteristic Analysis for Fault Diagnosis of a Planetary Gear Train

open access: yesSensors
The carrier eccentricity error and gear compound faults are most likely to occur simultaneously in an actual planetary gear train (PGT). Various faults and errors are coupled with each other to generate a complex dynamic response, which makes the ...
Yulin Ren   +5 more
doaj   +3 more sources

ResGRU: A Novel Hybrid Deep Learning Model for Compound Fault Diagnosis in Photovoltaic Arrays Considering Dust Impact [PDF]

open access: yesSensors
With 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

Coordination Control Strategy for Compound Fault of MMC-HVDC [PDF]

open access: yesMATEC Web of Conferences, 2016
Single-line to ground fault of DC side and sub-module fault are typical faults of MMC-HVDC. When each of the above faults occurs, the system will give a signal for circuit-breaker releasing, this will result in interruption of power delivery, the ...
Zhang Ming Guang   +3 more
doaj   +2 more sources

Harmonic adaptive fault-tolerant control for incipient and multiple faults of high mobility fighter [PDF]

open access: yesScientific Reports
This 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

Multi-domain vibration dataset with various bearing types under compound machine fault scenarios [PDF]

open access: yesData in Brief
In modern complex mechanical systems, machine faults typically occur in multiple components simultaneously, and the domain of collected sensor data changes continuously due to variations in operating conditions.
Seongjae Lee, Taewan Kim, Taehyoun Kim
doaj   +2 more sources

Diagnosis of Compound Fault Using Sparsity Promoted-Based Sparse Component Analysis [PDF]

open access: yesSensors, 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

Compound mechanical fault diagnosis based on CMDE [PDF]

open access: yesAdvances 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

open access: yesSensors, 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

Multi–Output Classification Based on Convolutional Neural Network Model for Untrained Compound Fault Diagnosis of Rotor Systems with Non–Contact Sensors

open access: yesSensors, 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

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