A Deep Neural Network-Based Feature Fusion for Bearing Fault Diagnosis

Autor: Duy Tang Hoang, Xuan Toa Tran, Mien Van, Hee Jun Kang

Publikováno v: Sensors, Vol 21, Iss 1, p 244 (2021)

This paper presents a novel method for fusing information from multiple sensor systems for bearing fault diagnosis. In the proposed method, a convolutional neural network is exploited to handle multiple signal sources simultaneously. The most importa

Externí odkaz: https://doaj.org/article/0f6d26b87d2845b0acf54faa5fe503bd

A Motor Current Signal-Based Bearing Fault Diagnosis Using Deep Learning and Information Fusion

Autor: Duy Tang Hoang, Hee-Jun Kang

Publikováno v: IEEE Transactions on Instrumentation and Measurement. 69:3325-3333

Bearing fault diagnosis has extensively exploited vibration signals (VSs) because of their rich information about bearing health conditions. However, this approach is expensive because the measurement of VSs requires external accelerometers. Moreover

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3bb049bdf08bd6c8266505e48980b34c
https://doi.org/10.1109/tim.2019.2933119

Rolling element bearing fault diagnosis using convolutional neural network and vibration image

Autor: Duy-Tang Hoang, Hee-Jun Kang

Publikováno v: Cognitive Systems Research. 53:42-50

Detecting in prior bearing faults is an essential task of machine health monitoring because bearings are the vital components of rotary machines. The performance of traditional intelligent fault diagnosis methods depend on feature extraction of fault

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b02b1e0c7c0d0ac14d8015cbb7a474ab
https://doi.org/10.1016/j.cogsys.2018.03.002

Bearing Fault Diagnosis using a Particle Swarm Optimization-Least SquaresWavelet Support Vector Machine Classifier

Autor: Hee-Jun Kang, Duy Tang Hoang, Mien Van

Publikováno v: Van, M, Hoang, D T & Kang, H J 2020, ' Bearing Fault Diagnosis using a Particle Swarm Optimization-Least SquaresWavelet Support Vector Machine Classifier ', Sensors (Basel, Switzerland) . https://doi.org/10.3390/s20123422
Sensors
Volume 20
Issue 12
Sensors, Vol 20, Iss 3422, p 3422 (2020)
Sensors (Basel, Switzerland)

Bearing is one of the key components of a rotating machine. Hence, monitoring health condition of the bearing is of paramount importace. This paper develops a novel particle swarm optimization (PSO)-least squares wavelet support vector machine (PSO-L

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19ac9da46bc3a22b9356ced23771092a
https://pure.qub.ac.uk/en/publications/bearing-fault-diagnosis-using-a-particle-swarm-optimizationleast-squareswavelet-support-vector-machine-classifier(d79523d3-318d-47e1-afdf-86542ab8c66c).html

A Bearing Fault Diagnosis Method Using Multi-Branch Deep Neural Network

Autor: Van-Cuong Nguyen, Duy-Tang Hoang, Xuan-Toa Tran, Mien Van, Hee-Jun Kang

Publikováno v: Nguyen, V-C, Hoang, D-T, Tran, X-T, Van, M & Kang, H-J 2021, ' A Bearing Fault Diagnosis Method Using Multi-Branch Deep Neural Network ', machines, vol. 9, no. 12, e345 . https://doi.org/10.3390/machines9120345
Machines, Vol 9, Iss 345, p 345 (2021)
Nguyen, V C, Hoang, D T, Tran, X-T, Van, M & Kang, H-J 2021, ' A bearing fault diagnosis method using multi-branch deep neural network ', Machines, vol. 9, no. 12, e345 . https://doi.org/10.3390/machines9120345
Machines; Volume 9; Issue 12; Pages: 345

Feature extraction from a signal is the most important step in signal-based fault diagnosis. Deep learning or deep neural network (DNN) is an effective method to extract features from signals. In this paper, a novel vibration signal-based bearing fau

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21030c7d2c19c5d0f275089d87bc745d
https://doi.org/10.3390/machines9120345