An adaptive data fusion strategy for fault diagnosis based on the convolutional neural network

A two-stage method based on extreme learning machine for predicting the remaining useful life of rolling-element bearings

(2020) Zuozhou Pan et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Intelligent Fault Diagnosis for Rotary Machinery Using Transferable Convolutional Neural Network

(2019) Zhuyun Chen et al.   IEEE Transactions on Industrial Informatics

A Novel Weighted Sparse Representation Classification Strategy Based on Dictionary Learning for Rotating Machinery

(2019) Huaqing Wang et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Step-by-Step Compound Faults Diagnosis Method for Equipment Based on Majorization-Minimization and Constraint SCA

(2019) Yansong Hao et al.   IEEE-ASME TRANSACTIONS ON MECHATRONICS

Speech Enhancement Based on Teacher–Student Deep Learning Using Improved Speech Presence Probability for Noise-Robust Speech Recognition

(2019) Yan-Hui Tu et al.   IEEE-ACM Transactions on Audio Speech and Language Processing

An Enhanced Intelligent Diagnosis Method Based on Multi-Sensor Image Fusion via Improved Deep Learning Network

(2019) Huaqing Wang et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Research on Remaining Useful Life Prediction of Rolling Element Bearings Based on Time-Varying Kalman Filter

(2019) Lingli Cui et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method

(2018) Long Wen et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

(2018) Liang-Chieh Chen et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Development and trend of condition monitoring and fault diagnosis of multi-sensors information fusion for rolling bearings: a review

(2018) Zhihe Duan et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Machinery health prognostics: A systematic review from data acquisition to RUL prediction

(2018) Yaguo Lei et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A novel convolutional neural network based fault recognition method via image fusion of multi-vibration-signals

(2018) Huaqing Wang et al.   COMPUTERS IN INDUSTRY

Bayesian Networks in Fault Diagnosis

(2017) Baoping Cai et al.   IEEE Transactions on Industrial Informatics

An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox

(2017) Luyang Jing et al.   SENSORS

An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis

(2017) Shaobo Li et al.   SENSORS

An Improved Evidential-IOWA Sensor Data Fusion Approach in Fault Diagnosis

(2017) et al.   SENSORS

A novel fault diagnosis technique for photovoltaic systems based on artificial neural networks

(2016) W. Chine et al.   RENEWABLE ENERGY

Simultaneous Sensor and Process Fault Detection and Isolation in Multiple-Input–Multiple-Output Systems

(2015) Ganesh Krishnamoorthy et al.   IEEE Systems Journal

Full-life dynamic identification of wear state based on on-line wear debris image features

(2013) Tonghai Wu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Automatic diagnosis method for structural fault of rotating machinery based on distinctive frequency components and support vector machines under varied operating conditions

(2012) Hongtao Xue et al.   NEUROCOMPUTING

The combined use of vibration, acoustic emission and oil debris on-line monitoring towards a more effective condition monitoring of rotating machinery

(2010) T.H. Loutas et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING