An intelligent grinding burn detection system based on two-stage feature selection and stacked sparse autoencoder

High-speed grinding of HIP-SiC ceramics on transformation of microscopic features

(2019) Chongjun Wu et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Electric Locomotive Bearing Fault Diagnosis Using a Novel Convolutional Deep Belief Network

(2018) Haidong Shao et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Softmax regression based deep sparse autoencoder network for facial emotion recognition in human-robot interaction

(2018) Luefeng Chen et al.   INFORMATION SCIENCES

Detection of a casting defect tracked by deep convolution neural network

(2018) Jinhua Lin et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Distributed ReliefF-based feature selection in Spark

(2018) Raul-Jose Palma-Mendoza et al.   KNOWLEDGE AND INFORMATION SYSTEMS

A two-stage feature selection and intelligent fault diagnosis method for rotating machinery using hybrid filter and wrapper method

(2018) Xiaolong Zhang et al.   NEUROCOMPUTING

Real-time safety monitoring in the induction motor using deep hierarchic long short-term memory

(2018) Adlen Kerboua et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A hybrid feature selection method based on binary state transition algorithm and ReliefF

(2018) Zhaoke Huang et al.   IEEE Journal of Biomedical and Health Informatics

Deep learning and its applications to machine health monitoring

(2018) Rui Zhao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Induction Hardened Layer Characterization and Grinding Burn Detection by Magnetic Barkhausen Noise Analysis

(2017) Aitor Lasaosa et al.   JOURNAL OF NONDESTRUCTIVE EVALUATION

A novel deep autoencoder feature learning method for rotating machinery fault diagnosis

(2017) Haidong Shao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery

(2017) Yumei Qi et al.   IEEE Access

Surface integrity investigation including grinding burns using barkhausen noise (BNA)

(2017) Azhar Thanedar et al.   Journal of Manufacturing Processes

Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images

(2016) Jun Xu et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

A sparse auto-encoder-based deep neural network approach for induction motor faults classification

(2016) Wenjun Sun et al.   MEASUREMENT

Novel segmented stacked autoencoder for effective dimensionality reduction and feature extraction in hyperspectral imaging

(2016) Jaime Zabalza et al.   NEUROCOMPUTING

A two-stage feature selection method with its application

(2015) Xuehua Zhao et al.   COMPUTERS & ELECTRICAL ENGINEERING

Text classification using genetic algorithm oriented latent semantic features

(2014) Alper Kursat Uysal et al.   EXPERT SYSTEMS WITH APPLICATIONS

Experimental study of burn classification and prediction using indirect method in surface grinding of AISI 1045 steel

(2013) Zhensheng Yang et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Application of Hilbert–Huang Transform to acoustic emission signal for burn feature extraction in surface grinding process

(2013) Zhensheng Yang et al.   MEASUREMENT

Fault diagnosis and prognosis using wavelet packet decomposition, Fourier transform and artificial neural network

(2012) Zhenyou Zhang et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Burn threshold prediction for High Efficiency Deep Grinding

(2011) A. Bell et al.   INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE

Development of Barkhausen noise calibration blocks for reliable grinding burn detection

(2011) Suvi Santa-aho et al.   JOURNAL OF MATERIALS PROCESSING TECHNOLOGY

Quantitative prediction of residual stress and hardness in case-hardened steel based on the Barkhausen noise measurement

(2011) Aki Sorsa et al.   NDT & E INTERNATIONAL

Condition-based shaft fault diagnosis with the empirical mode decomposition method

(2011) W-Y Lin et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE

Generalized practical models of cylindrical plunge grinding processes

(2007) T.J. Choi et al.   INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE