Deep learning-based tool wear prediction and its application for machining process using multi-scale feature fusion and channel attention mechanism

Modeling and analysis of tool wear prediction based on SVD and BiLSTM

(2020) Xiaoqiang Wu et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A hybrid information model based on long short-term memory network for tool condition monitoring

(2020) Weili Cai et al.   JOURNAL OF INTELLIGENT MANUFACTURING

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

(2020) Xingwei Xu et al.   MEASUREMENT

Combining translation-invariant wavelet frames and convolutional neural network for intelligent tool wear state identification

(2019) Xin-Cheng Cao et al.   COMPUTERS IN INDUSTRY

Research on the Milling Tool Wear and Life Prediction by Establishing an Integrated Predictive Model

(2019) Yinfei Yang et al.   MEASUREMENT

Tool wear evaluation under minimum quantity lubrication by clustering energy of acoustic emission burst signals

(2019) Chengdong Wang et al.   MEASUREMENT

A Deep Convolutional Neural Networks Model for Intelligent Fault Diagnosis of a Gearbox under Different Operational Conditions

(2019) Guangqi Qiu et al.   MEASUREMENT

Study of a tap failure at the internal threads machining

(2019) Peter Monka et al.   ENGINEERING FAILURE ANALYSIS

Investigation of progressive tool wear for determining of optimized machining parameters in turning

(2019) Mustafa Kuntoğlu et al.   MEASUREMENT

Relevance vector machine for tool wear prediction

(2019) Dongdong Kong et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Time varying and condition adaptive hidden Markov model for tool wear state estimation and remaining useful life prediction in micro-milling

(2019) Weijian Li et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep residual network based fault detection and diagnosis of photovoltaic arrays using current-voltage curves and ambient conditions

(2019) Zhicong Chen et al.   ENERGY CONVERSION AND MANAGEMENT

A novel method for tool condition monitoring based on long short-term memory and hidden Markov model hybrid framework in high-speed milling Ti-6Al-4V

(2019) Zhengrui Tao et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Milling Tool Wear State Recognition by Vibration Signal Using a Stacked Generalization Ensemble Model

(2019) Yang Hui et al.   SHOCK AND VIBRATION

A novel deep learning method based on attention mechanism for bearing remaining useful life prediction

(2019) Yuanhang Chen et al.   APPLIED SOFT COMPUTING

Data-driven smart manufacturing: Tool wear monitoring with audio signals and machine learning

(2019) Zhixiong Li et al.   Journal of Manufacturing Processes

Deep diagnostics and prognostics: An integrated hierarchical learning framework in PHM applications

(2018) Yanhui Lin et al.   APPLIED SOFT COMPUTING

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

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

Tool condition monitoring using spectral subtraction and convolutional neural networks in milling process

(2018) Fatemeh Aghazadeh et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Predicting tool wear with multi-sensor data using deep belief networks

(2018) Yuxuan Chen et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

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

(2018) Huihui Qiao et al.   SENSORS

A generic tool wear model and its application to force modeling and wear monitoring in high speed milling

(2018) Kunpeng Zhu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep learning and its applications to machine health monitoring

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

Force-based tool wear estimation for milling process using Gaussian mixture hidden Markov models

(2017) Dongdong Kong et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Tool condition monitoring in interrupted cutting with acceleration sensors

(2017) Juho Ratava et al.   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

Multisensory fusion based virtual tool wear sensing for ubiquitous manufacturing

(2017) Jinjiang Wang et al.   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

Tool wear monitoring based on kernel principal component analysis and v-support vector regression

(2016) Dongdong Kong et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Tool wear monitoring and prognostics challenges: a comparison of connectionist methods toward an adaptive ensemble model

(2016) Kamran Javed et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Monitoring of tool wear using measured machining forces and neuro-fuzzy modelling approaches during machining of GFRP composites

(2015) A.I. Azmi   ADVANCES IN ENGINEERING SOFTWARE

Using artificial neural networks for the prediction of dimensional error on inclined surfaces manufactured by ball-end milling

(2015) Álvar Arnaiz-González et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Force based tool wear monitoring system for milling process based on relevance vector machine

(2014) Guofeng Wang et al.   ADVANCES IN ENGINEERING SOFTWARE

Health assessment and life prediction of cutting tools based on support vector regression

(2013) T. Benkedjouh et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Effect of SVM kernel functions on classification of vibration signals of a single point cutting tool

(2011) M. Elangovan et al.   EXPERT SYSTEMS WITH APPLICATIONS

Multi-category micro-milling tool wear monitoring with continuous hidden Markov models

(2008) Kunpeng Zhu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING