Condition Monitoring using Machine Learning: A Review of Theory, Applications, and Recent Advances

Marine dual fuel engines monitoring in the wild through weakly supervised data analytics

(2021) Andrea Coraddu et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

An intelligent fault diagnosis method of rolling bearings based on Welch power spectrum transformation with radial basis function neural network

(2020) Zhihao Jin et al.   JOURNAL OF VIBRATION AND CONTROL

Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network

(2020) Alex Sherstinsky   PHYSICA D-NONLINEAR PHENOMENA

Technical data-driven tool condition monitoring challenges for CNC milling: a review

(2020) Shi Yuen Wong et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A Novel Order Analysis and Stacked Sparse Auto-Encoder Feature Learning Method for Milling Tool Wear Condition Monitoring

(2020) Jiayu Ou et al.   SENSORS

Review of tool condition monitoring in machining and opportunities for deep learning

(2020) G. Serin et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

1D-CNN based real-time fault detection system for power asset diagnostics

(2020) Imene Mitiche et al.   IET Generation Transmission & Distribution

Tool condition monitoring in milling process using multifractal detrended fluctuation analysis and support vector machine

(2020) Jingchao Guo et al.   The International Journal of Advanced Manufacturing Technology

Reliable state of health condition monitoring of Li-ion batteries based on incremental support vector regression with parameters optimization

(2020) Jaouher Ben Ali et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING

Fault detection and diagnosis of large-scale HVAC systems in buildings using data-driven methods: A comprehensive review

(2020) Maryam Sadat Mirnaghi et al.   ENERGY AND BUILDINGS

Data-Driven Methods for Predictive Maintenance of Industrial Equipment: A Survey

(2019) Weiting Zhang et al.   IEEE Systems Journal

A survey on ensemble learning

(2019) Xibin Dong et al.   Frontiers of Computer Science

Wind Turbine Condition Monitoring Based on Assembled Multidimensional Membership Functions Using Fuzzy Inference System

(2019) Fuming Qu et al.   IEEE Transactions on Industrial Informatics

A Bayesian Network Approach for Condition Monitoring of High-Speed Railway Catenaries

(2019) Hongrui Wang et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

Nested SVDD in DAG SVM for induction motor condition monitoring

(2018) Slaheddine Zgarni et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Non-invasive Kalman Filter based Permanent Magnet Temperature Estimation for Permanent Magnet Synchronous Machines

(2018) Guodong Feng et al.   IEEE TRANSACTIONS ON POWER ELECTRONICS

Wind Turbine Fault Detection Using a Denoising Autoencoder With Temporal Information

(2018) Guoqian Jiang et al.   IEEE-ASME TRANSACTIONS ON MECHATRONICS

Bearing failure prediction using Wigner-Ville distribution, modified Poincare mapping and fast Fourier transform

(2018) Pravin Singru et al.   Journal of Vibroengineering

Genetic algorithm-based wrapper approach for grouping condition monitoring signals of nuclear power plant components

(2018) Piero Baraldi et al.   INTEGRATED COMPUTER-AIDED ENGINEERING

Review on hydrogen fuel cell condition monitoring and prediction methods

(2018) Rong-Heng Lin et al.   INTERNATIONAL JOURNAL OF HYDROGEN ENERGY

Fault detection and pathway analysis using a dynamic Bayesian network

(2018) Md. Tanjin Amin et al.   CHEMICAL ENGINEERING SCIENCE

Machine learning methods for wind turbine condition monitoring: A review

(2018) Adrian Stetco et al.   RENEWABLE ENERGY

Features-clustering-based earth fault detection using singular-value decomposition and fuzzy c-means in resonant grounding distribution systems

(2017) Mou-Fa Guo et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Fuzzy logic based tool condition monitoring for end-milling

(2017) Besmir Cuka et al.   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

Fault detection and diagnosis of chiller using Bayesian network classifier with probabilistic boundary

(2016) Suowei He et al.   APPLIED THERMAL ENGINEERING

Robust one-class SVM for fault detection

(2016) Yingchao Xiao et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

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

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

Tool condition monitoring by SVM classification of machined surface images in turning

(2015) Nagaraj N. Bhat et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Tool wear monitoring using naïve Bayes classifiers

(2014) Jaydeep Karandikar et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A Diagnostic System for Speed-Varying Motor Rotary Faults

(2014) Chwan-Lu Tseng et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Bagging support vector data description model for batch process monitoring

(2013) Zhiqiang Ge et al.   JOURNAL OF PROCESS CONTROL

Rolling element bearing fault detection in industrial environments based on a K-means clustering approach

(2010) C.T. Yiakopoulos et al.   EXPERT SYSTEMS WITH APPLICATIONS

Fault detection method with PCA and LDA and its application to induction motor

(2010) D. Y. Jung et al.   JOURNAL OF CENTRAL SOUTH UNIVERSITY OF TECHNOLOGY

Optimal MLP neural network classifier for fault detection of three phase induction motor

(2009) Vilas N. Ghate et al.   EXPERT SYSTEMS WITH APPLICATIONS

A systematic analysis of performance measures for classification tasks

(2009) Marina Sokolova et al.   INFORMATION PROCESSING & MANAGEMENT

Gear fault detection and diagnosis under speed-up condition based on order cepstrum and radial basis function neural network

(2009) Hui Li et al.   Journal of Mechanical Science and Technology

Principal Component and Hierarchical Cluster Analyses as Applied to Transformer Partial Discharge Data With Particular Reference to Transformer Condition Monitoring

(2008) T. Babnik et al.   IEEE TRANSACTIONS ON POWER DELIVERY