Comparing torsional and lateral vibration data for deep learning-based drive train gear diagnosis

A Review on Vibration-Based Condition Monitoring of Rotating Machinery

(2022) Monica Tiboni et al.   Applied Sciences-Basel

Intelligent fault diagnosis and visual interpretability of rotating machinery based on residual neural network

(2022) Shihang Yu et al.   MEASUREMENT

Torque estimation in marine propulsion systems

(2022) Mikael Manngård et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Theoretical and experimental study of wind turbine drivetrain fault diagnosis by using torsional vibrations and modal estimation

(2021) Farid K. Moghadam et al.   JOURNAL OF SOUND AND VIBRATION

Deep morphological convolutional network for feature learning of vibration signals and its applications to gearbox fault diagnosis

(2021) Zhuang Ye et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Towards better benchmarking using the CWRU bearing fault dataset

(2021) Jacob Hendriks et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Applications of machine learning to machine fault diagnosis: A review and roadmap

(2020) Yaguo Lei et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Latest developments in gear defect diagnosis and prognosis: A review

(2020) Anil Kumar et al.   MEASUREMENT

Torque and rotational speed sensor based on resistance and capacitive grating for rotational shaft of mechanical systems

(2020) Changxin Chen et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep convolutional neural network based planet bearing fault classification

(2019) Dezun Zhao et al.   COMPUTERS IN INDUSTRY

Motor Current Signal Analysis Using Deep Neural Networks for Planetary Gear Fault Diagnosis

(2019) Feng Li et al.   MEASUREMENT

An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings

(2019) Bin Yang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Gear Pitting Fault Diagnosis Using Integrated CNN and GRU Network with Both Vibration and Acoustic Emission Signals

(2019) Xueyi Li et al.   Applied Sciences-Basel

A Deep Learning Method for Bearing Fault Diagnosis through Stacked Residual Dilated Convolutions

(2019) Zilong Zhuang et al.   Applied Sciences-Basel

Crack detection of plastic gears using a convolutional neural network pre-learned from images of meshing vibration data with transfer learning

(2019) B. H. Kien et al.   FORSCHUNG IM INGENIEURWESEN-ENGINEERING RESEARCH

Fault diagnostics between different type of components: A transfer learning approach

(2019) Xudong Li et al.   APPLIED SOFT COMPUTING

An intelligent fault diagnosis approach for planetary gearboxes based on deep belief networks and uniformed features

(2018) Xin Wang et al.   JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

Artificial intelligence for fault diagnosis of rotating machinery: A review

(2018) Ruonan Liu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Dynamic modeling of gearbox faults: A review

(2018) Xihui Liang et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Torsional vibration signal analysis as a diagnostic tool for planetary gear fault detection

(2018) Song Xue et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN

(2018) Chang Liu et al.   SENSORS

Preprocessing-Free Gear Fault Diagnosis Using Small Datasets With Deep Convolutional Neural Network-Based Transfer Learning

(2018) Pei Cao et al.   IEEE Access

Deep learning and its applications to machine health monitoring

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

A survey on Deep Learning based bearing fault diagnosis

(2018) Duy-Tang Hoang et al.   NEUROCOMPUTING

A novel adversarial learning framework in deep convolutional neural network for intelligent diagnosis of mechanical faults

(2018) Te Han et al.   KNOWLEDGE-BASED SYSTEMS

Information Fusion and Semi-Supervised Deep Learning Scheme for Diagnosing Gear Faults in Induction Machine Systems

(2018) Roozbeh Razavi-Far et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data

(2018) Liang Guo et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals

(2017) Wei Zhang et al.   SENSORS

Deep learning for automated drivetrain fault detection

(2017) Martin Bach-Andersen et al.   WIND ENERGY

Detection of Pitting in Gears Using a Deep Sparse Autoencoder

(2017) Yongzhi Qu et al.   Applied Sciences-Basel

Time-Frequency Analysis of Torsional Vibration Signals in Resonance Region for Planetary Gearbox Fault Diagnosis Under Variable Speed Conditions

(2017) Xiaowang Chen et al.   IEEE Access

Condition Monitoring Parameters for Fault Diagnosis of Fixed Axis Gearbox: A Review

(2016) Deepam Goyal et al.   ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks

(2016) Turker Ince et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data

(2016) Feng Jia et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Gear fault diagnosis based on support vector machine optimized by artificial bee colony algorithm

(2015) Dalian Yang et al.   MECHANISM AND MACHINE THEORY