A new tool wear condition monitoring method based on deep learning under small samples

An edge-labeling graph neural network method for tool wear condition monitoring using wear image with small samples

(2021) Gaofeng Zhi et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Tool wear condition monitoring in milling process based on data fusion enhanced long short-term memory network under different cutting conditions

(2021) Guoxiao Zheng et al.   Eksploatacja i Niezawodnosc-Maintenance and Reliability

A hybrid attention improved ResNet based fault diagnosis method of wind turbines gearbox

(2021) Kai Zhang et al.   MEASUREMENT

Fuzzy c-means clustering based colour image segmentation for tool wear monitoring in micro-milling

(2021) Jitin Malhotra et al.   PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY

A Fuzzy System of Operation Safety Assessment Using Multimodel Linkage and Multistage Collaboration for In-Wheel Motor

(2021) Hongtao Xue et al.   IEEE TRANSACTIONS ON FUZZY SYSTEMS

Investigated iterative convergences of neural network for prediction turning tool wear

(2020) Wen-Yang Chang et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Estimation of tool wear and optimization of cutting parameters based on novel ANFIS-PSO method toward intelligent machining

(2020) Longhua Xu et al.   JOURNAL OF INTELLIGENT MANUFACTURING

The mRMR-CNN based influential support decision system approach to classify EEG signals

(2020) Duygu Kaya   MEASUREMENT

A cyber physical system for tool condition monitoring using electrical power and a mechanistic model

(2020) Paul Goodall et al.   COMPUTERS IN INDUSTRY

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

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

Improved deep convolution neural network (CNN) for the identification of defects in the centrifugal pump using acoustic images

(2020) Anil Kumar et al.   APPLIED ACOUSTICS

Tool wear mechanism and prediction in milling TC18 titanium alloy using deep learning

(2020) Junyan Ma et al.   MEASUREMENT

Intelligent analysis of tool wear state using stacked denoising autoencoder with online sequential-extreme learning machine

(2020) Jiayu Ou et al.   MEASUREMENT

A tool condition monitoring method based on two-layer angle kernel extreme learning machine and binary differential evolution for milling

(2020) Yuqing Zhou et al.   MEASUREMENT

Investigation on universal tool wear measurement technique using image-based cross-correlation analysis

(2020) Ka Mun Fong et al.   MEASUREMENT

Development of tool condition monitoring system in end milling process using wavelet features and Hoelder’s exponent with machine learning algorithms

(2020) T. Mohanraj 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

Tool wear classification using time series imaging and deep learning

(2019) Giovanna Martínez-Arellano et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Deep heterogeneous GRU model for predictive analytics in smart manufacturing: Application to tool wear prediction

(2019) Jinjiang Wang et al.   COMPUTERS IN INDUSTRY

An intrinsic timescale decomposition-based kernel extreme learning machine method to detect tool wear conditions in the milling process

(2019) Zhi Lei et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Online Tool Wear Monitoring Via Hidden Semi-Markov Model With Dependent Durations

(2018) Kunpeng Zhu et al.   IEEE Transactions on Industrial Informatics

Review of tool condition monitoring methods in milling processes

(2018) Yuqing Zhou et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

In-process tool condition monitoring in compliant abrasive belt grinding process using support vector machine and genetic algorithm

(2018) Vigneashwara Pandiyan et al.   Journal of Manufacturing Processes

A novel algorithm for tool wear online inspection based on machine vision

(2018) Qiulin Hou et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Deep learning and its applications to machine health monitoring

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

A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings

(2018) Biao Wang et al.   IEEE TRANSACTIONS ON RELIABILITY

Geometric Deep Learning: Going beyond Euclidean data

(2017) Michael M. Bronstein et al.   IEEE SIGNAL PROCESSING MAGAZINE

An integrated wireless vibration sensing tool holder for milling tool condition monitoring

(2017) Zhengyou Xie et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Tracking recurrence of correlation structure in neuronal recordings

(2017) Samuel A. Neymotin et al.   JOURNAL OF NEUROSCIENCE METHODS

Wear mechanisms of PVD-coated cutting tools during continuous turning of Ti-6Al-4V alloy

(2017) Shuho Koseki et al.   PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY

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

Application of acoustic emission sensor to investigate the frequency of tool wear and plastic deformation in tool condition monitoring

(2016) M.S.H. Bhuiyan et al.   MEASUREMENT

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

An investigation of tool wear using acoustic emission and genetic algorithm

(2014) G Vetrichelvan et al.   JOURNAL OF VIBRATION AND CONTROL

Monitoring and processing signal applied in machining processes – A review

(2014) C.H. Lauro et al.   MEASUREMENT

The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web]

(2012) Li Deng   IEEE SIGNAL PROCESSING MAGAZINE

Complex network from time series based on phase space reconstruction

(2009) Zhongke Gao et al.   CHAOS