Multi-branch convolutional attention network for multi-sensor feature fusion in intelligent fault diagnosis of rotating machinery

Evaluation of manufacturing process in low variety high volume industry with the coupling of cloud model theory and TOPSIS approach

(2022) Faaiz Ahsan et al.   Quality Engineering

Gear Fault Diagnosis Method Based on Multi-Sensor Information Fusion and VGG

(2022) Dongyue Huo et al.   Entropy

Bearing fault diagnosis using normalized diagnostic feature-gram and convolutional neural network

(2022) Jaafar K Alsalaet et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Convolutional autoencoder neural network for fault diagnosis with multi-sensor data

(2022) Xin Wang et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE

Multi-Sensor Fault Diagnosis Based on Time Series in an Intelligent Mechanical System

(2022) Zhuoran Xu et al.   SENSORS

Intelligent fault diagnosis of rolling bearings based on clustering algorithm of fast search and find of density peaks

(2022) Jun Wu et al.   Quality Engineering

A Novel Discount-Weighted Average Fusion Method Based on Reinforcement Learning For Conflicting Data

(2022) Fanghui Huang et al.   IEEE Systems Journal

Intelligent fault diagnosis of rotating machinery based on continuous wavelet transform-local binary convolutional neural network

(2021) Yiwei Cheng et al.   KNOWLEDGE-BASED SYSTEMS

An intelligent fault diagnosis method for rotating machinery based on data fusion and deep residual neural network

(2021) Binsen Peng et al.   APPLIED INTELLIGENCE

Single and Multi-label Fault Classification in rotors from unprocessed multi-sensor data through deep and parallel CNN architectures

(2021) Nikhil A. Sonkul et al.   EXPERT SYSTEMS WITH APPLICATIONS

A novel approach of multisensory fusion to collaborative fault diagnosis in maintenance

(2021) Haidong Shao et al.   Information Fusion

Hierarchical diagnosis of bearing faults using branch convolutional neural network considering noise interference and variable working conditions

(2021) Kaige Su et al.   KNOWLEDGE-BASED SYSTEMS

Rolling bearing fault diagnosis based on multi-channel convolution neural network and multi-scale clipping fusion data augmentation

(2021) Ruxue Bai et al.   MEASUREMENT

A review on the application of blind deconvolution in machinery fault diagnosis

(2021) Yonghao Miao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Parallel sparse filtering for intelligent fault diagnosis using acoustic signal processing

(2021) Shanshan Ji et al.   NEUROCOMPUTING

Asymmetric inter-intra domain alignments (AIIDA) method for intelligent fault diagnosis of rotating machinery

(2021) Jinwook Lee et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

2MNet: Multi-sensor and multi-scale model toward accurate fault diagnosis of rolling bearing

(2021) Yang Guan et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Research on Intelligent Fault Diagnosis of Rolling Bearing Based on Improved Deep Residual Network

(2021) Xinyu Hao et al.   Applied Sciences-Basel

An image-based feature extraction method for fault diagnosis of variable-speed rotating machinery

(2021) Jungho Park et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A Generic Indirect Deep Learning Approach for Multisensor Degradation Modeling

(2021) Di Wang et al.   IEEE Transactions on Automation Science and Engineering

Compound fault diagnosis for a rolling bearing using adaptive DTCWPT with higher order spectra

(2020) Haidong Shao et al.   Quality Engineering

Adaptive Channel Weighted CNN With Multisensor Fusion for Condition Monitoring of Helicopter Transmission System

(2020) Tianfu Li et al.   IEEE SENSORS JOURNAL

New dynamic reliability assessment method based on process capability index and fault importance index

(2020) Guangzhong Liu et al.   Quality Engineering

Noisy parallel hybrid model of NBGRU and NCNN architectures for remaining useful life estimation

(2020) Ali Al-Dulaimi et al.   Quality Engineering

Deep multi-scale convolutional transfer learning network: A novel method for intelligent fault diagnosis of rolling bearings under variable working conditions and domains

(2020) Bo Zhao et al.   NEUROCOMPUTING

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

(2020) Shi Li et al.   MEASUREMENT

Intelligent monitoring and diagnostics using a novel integrated model based on deep learning and multi-sensor feature fusion

(2020) Xingwei Xu et al.   MEASUREMENT

Fault diagnosis of rolling bearings using an Improved Multi-Scale Convolutional Neural Network with Feature Attention mechanism

(2020) Zifei Xu et al.   ISA TRANSACTIONS

Multiscale Convolutional Attention Network for Predicting Remaining Useful Life of Machinery

(2020) Biao Wang et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Bearing performance degradation assessment using long short-term memory recurrent network

(2019) Bin Zhang et al.   COMPUTERS IN INDUSTRY

A Generic Health Index Approach for Multisensor Degradation Modeling and Sensor Selection

(2019) Minhee Kim et al.   IEEE Transactions on Automation Science and Engineering

Sensor Data-Driven Bearing Fault Diagnosis Based on Deep Convolutional Neural Networks and S-Transform

(2019) Guoqiang Li et al.   SENSORS

Transfer fault diagnosis of bearing installed in different machines using enhanced deep auto-encoder

(2019) He Zhiyi et al.   MEASUREMENT

Deep Residual Shrinkage Networks for Fault Diagnosis

(2019) Minghang Zhao et al.   IEEE Transactions on Industrial Informatics

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

(2018) Duy-Tang Hoang et al.   Cognitive Systems Research

Degradation Data-Driven Time-To-Failure Prognostics Approach for Rolling Element Bearings in Electrical Machines

(2018) Jun Wu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Multiscale Convolutional Neural Networks for Fault Diagnosis of Wind Turbine Gearbox

(2018) Guoqian Jiang et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Machine Health Monitoring Using Local Feature-Based Gated Recurrent Unit Networks

(2018) Rui Zhao et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Regrouping particle swarm optimization based variable neural network for gearbox fault diagnosis

(2018) Yixiao Liao et al.   JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

A data-level fusion approach for degradation modeling and prognostic analysis under multiple failure modes

(2018) Abdallah Chehade et al.   JOURNAL OF QUALITY TECHNOLOGY

Highly-Accurate Machine Fault Diagnosis Using Deep Transfer Learning

(2018) Siyu Shao et al.   IEEE Transactions on Industrial Informatics

A Time-Distributed Spatiotemporal Feature Learning Method for Machine Health Monitoring with Multi-Sensor Time Series

(2018) Huihui Qiao et al.   SENSORS

Application of Bandwidth EMD and Adaptive Multiscale Morphology Analysis for Incipient Fault Diagnosis of Rolling Bearings

(2017) Yongbo Li et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

A New Deep Transfer Learning Based on Sparse Auto-Encoder for Fault Diagnosis

(2017) Long Wen et al.   IEEE Transactions on Systems Man Cybernetics-Systems

Multiple Sensor Data Fusion for Degradation Modeling and Prognostics Under Multiple Operational Conditions

(2016) Hao Yan et al.   IEEE TRANSACTIONS ON RELIABILITY

A Diagnosis Method for Rotation Machinery Faults Based on Dimensionless Indexes Combined withK-Nearest Neighbor Algorithm

(2015) Jianbin Xiong et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Rolling bearing fault diagnosis using an optimization deep belief network

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

A Data-Level Fusion Model for Developing Composite Health Indices for Degradation Modeling and Prognostic Analysis

(2013) Kaibo Liu et al.   IEEE Transactions on Automation Science and Engineering

P3DFFT: A Framework for Parallel Computations of Fourier Transforms in Three Dimensions

(2012) Dmitry Pekurovsky   SIAM JOURNAL ON SCIENTIFIC COMPUTING

Multi-fault classification based on support vector machine trained by chaos particle swarm optimization

(2010) Xianlun Tang et al.   KNOWLEDGE-BASED SYSTEMS