A bearing fault and severity diagnostic technique using adaptive deep belief networks and Dempster–Shafer theory

A novel unsupervised deep learning model for global and local health condition assessment of structures

(2018) Mohammad Hossein Rafiei et al.   ENGINEERING STRUCTURES

Multi-synchrosqueezing Transform

(2018) Gang Yu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Enhanced probabilistic neural network with local decision circles: A robust classifier

(2018) Mehran Ahmadlou et al.   INTEGRATED COMPUTER-AIDED ENGINEERING

A survey on Deep Learning based bearing fault diagnosis

(2018) Duy-Tang Hoang et al.   NEUROCOMPUTING

An adaptive sensitive frequency band selection method for empirical wavelet transform and its application in bearing fault diagnosis

(2018) Kun Yu et al.   MEASUREMENT

Atomic decomposition and sparse representation for complex signal analysis in machinery fault diagnosis: A review with examples

(2017) Zhipeng Feng et al.   MEASUREMENT

Application of time series analysis and PSO–SVM model in predicting the Bazimen landslide in the Three Gorges Reservoir, China

(2016) Chao Zhou et al.   ENGINEERING GEOLOGY

Deep learning approach for active classification of electrocardiogram signals

(2016) M.M. Al Rahhal et al.   INFORMATION SCIENCES

Detection and diagnosis of bearing faults using shift-invariant dictionary learning and hidden Markov model

(2016) Haitao Zhou et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Construction of hierarchical diagnosis network based on deep learning and its application in the fault pattern recognition of rolling element bearings

(2016) Meng Gan et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings

(2016) Akhand Rai et al.   TRIBOLOGY INTERNATIONAL

Hybrid HSA and PSO algorithm for energy efficient cluster head selection in wireless sensor networks

(2016) T. Shankar et al.   Swarm and Evolutionary Computation

Determining Basic Probability Assignment Based on the Improved Similarity Measures of Generalized Fuzzy Numbers

(2015) Wen Jiang et al.   International Journal of Computers Communications & Control

Rolling bearing fault diagnosis using an optimization deep belief network

(2015) Haidong Shao et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Fault diagnosis of automobile hydraulic brake system using statistical features and support vector machines

(2015) R. Jegadeeshwaran et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

An approach to fault diagnosis of reciprocating compressor valves using Teager–Kaiser energy operator and deep belief networks

(2014) Van Tung Tran et al.   EXPERT SYSTEMS WITH APPLICATIONS

Low-complexity sinusoidal-assisted EMD (SAEMD) algorithms for solving mode-mixing problems in HHT

(2013) Wen-Chung Shen et al.   DIGITAL SIGNAL PROCESSING

Failure diagnosis using deep belief learning based health state classification

(2013) Prasanna Tamilselvan et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Wavelets for fault diagnosis of rotary machines: A review with applications

(2013) Ruqiang Yan et al.   SIGNAL PROCESSING

An approach using Dempster–Shafer theory to fuse spatial data and satellite image derived crown metrics for estimation of forest stand leading species

(2012) Brice Mora et al.   Information Fusion

Multi-fault classification based on wavelet SVM with PSO algorithm to analyze vibration signals from rolling element bearings

(2012) Zhiwen Liu et al.   NEUROCOMPUTING

Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool

(2010) Ingrid Daubechies et al.   APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

Deep Learning and Its Applications to Signal and Information Processing [Exploratory DSP

(2010) Dong Yu et al.   IEEE SIGNAL PROCESSING MAGAZINE

Multisensor data fusion for fire detection

(2009) E. Zervas et al.   Information Fusion

Research on fault diagnosis for reciprocating compressor valve using information entropy and SVM method

(2009) Houxi Cui et al.   JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES