Results 31 to 40 of about 35,178 (215)

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

, 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
Byeongil Kim, Dongwoo Hong, Taehwan Son
core   +1 more source

Generator Fault Classification Method Based on Multi-Source Information Fusion Naive Bayes Classification Algorithm

Energies, 2022
The existing motor fault classification methods mostly use sensors to detect a single fault feature, which makes it difficult to ensure high diagnostic accuracy.
Yi Wang, Yuhao Huang, Kai Yang, Zhihan Chen, Cheng Luo   +4 more
doaj   +1 more source

Classification of Aircraft Maneuvers for Fault Detection [PDF]

, 2003
Ensemble classifiers tend to outperform their component base classifiers when the training data are subject to variability. This intuitively makes ensemble classifiers useful for application to the problem of aircraft fault detection. Automated fault detection is an increasingly important problem in aircraft maintenance and operation.
Nikunj C. Oza, Kagan Tumer, Irem Y. Tumer, Edward M. Huff   +3 more
openaire   +1 more source

A Monitoring System for Online Fault Detection and Classification in Photovoltaic Plants [PDF]

, 2020
Photovoltaic (PV) energy use has been increasing recently, mainly due to new policies all over the world to reduce the application of fossil fuels. PV system efficiency is highly dependent on environmental variables, besides being affected by several ...
Clayton Hilgemberg da Costa, Marcelo Paludetto Rodrigues, Guilherme Dan Yamada, Rodrigo Braun dos Santos, Paulo Cézar Stadzisz, Robson Ribeiro Linhares, Elder Oroski, André Eugênio Lazzaretti, Gilberto Lexinoski, Rafael Eleodoro de Goes, Júlio Shigeaki Omori, Guilherme Luiz Moritz   +11 more
core   +1 more source

A Novel Multimode Fault Classification Method Based on Deep Learning

Journal of Control Science and Engineering, 2017
Due to the problem of load varying or environment changing, machinery equipment often operates in multimode. The data feature involved in the observation often varies with mode changing.
Funa Zhou, Yulin Gao, Chenglin Wen
doaj   +1 more source

Design of remote fault prediction system for coal preparation equipments

Gong-kuang zidonghua, 2019
In view of problems existing in current coal preparation equipments fault prediction, such as equipments monitoring data conversion method was not unified, single fault classification model cannot meet requirements of multiple fault types prediction, and
FU Xiang, WANG Ranfeng, PANG Liang
doaj   +1 more source

Construction of a Sensitive and Speed Invariant Gearbox Fault Diagnosis Model Using an Incorporated Utilizing Adaptive Noise Control and a Stacked Sparse Autoencoder-Based Deep Neural Network

Sensors, 2020
Gearbox fault diagnosis based on the analysis of vibration signals has been a major research topic for a few decades due to the advantages of vibration characteristics.
Cong Dai Nguyen, Alexander E. Prosvirin, Cheol Hong Kim, Jong-Myon Kim   +3 more
doaj   +1 more source

A Hybrid Gearbox Fault Diagnosis Method Based on GWO-VMD and DE-KELM

Applied Sciences, 2021
In this paper, a vibration signal-based hybrid diagnostic method, including vibration signal adaptive decomposition, vibration signal reconstruction, fault feature extraction, and gearbox fault classification, is proposed to realize fault diagnosis of ...
Gang Yao, Yunce Wang, Mohamed Benbouzid, Mourad Ait-Ahmed   +3 more
doaj   +1 more source

Bispectrum Analysis of Motor Current Signals for Fault Diagnosis of Reciprocating Compressors [PDF]

, 2009
The induction motor is the most common driver in industry and has been previously proposed as a means of inferring the condition of an entire equipment train, predominantly through the measurement and processing of power supply parameters.
Gu, Fengshou, Ball, Andrew, Feng Shou Gu, Salem Al-Arbi, Naid, A., Abdelhamid Naid, Yi Min Shao, Naid, Abdelhamid, Al-Arbi, Salem, Shao, Yimin, Andrew Ball   +10 more
core   +1 more source

Intelligent Early Fault Diagnosis of Space Flywheel Rotor System [PDF]

, 2023
Three frequently encountered problems—a variety of fault types, data with insufficient labels, and missing fault types—are the common challenges in the early fault diagnosis of space flywheel rotor systems.
Sier Deng, Hengdi Wang, Hui Liao, Pengfei Xie   +3 more
core   +1 more source