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Research article

First published 2025-10

Morphological segmentation of wear zones on cutting inserts for tool condition monitoring

Suzana Petrovic Savic, Andjelija Mitrovic, Aleksandar Djordjevic [...]

Advances in Mechanical Engineering

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Research article

First published 2024-1

Development of tool wear condition on-line monitoring method for impeller milling based on new data processing approach and DAE-BP-ANN-integrated modeling

Zheng Zou, Xu Gao, Sicong Lei [...]

Proceedings of the Institution of Mechanical Engineers,Part B: Journal of Engineering Manufacture

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Research article

First published 2009-6

Fractal analysis of vibration signals for monitoring the condition of milling tool wear

Xu Chuangwen, C Hualing

Proceedings of the Institution of Mechanical Engineers,Part J: Journal of Engineering Tribology

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Research article

First published 2020-3

Tool wear condition monitoring based on wavelet transform and improved extreme learning machine

Soufiane Laddada, Med. Ouali Si-Chaib, Tarak Benkedjouh [...]

Proceedings of the Institution of Mechanical Engineers,Part C: Journal of Mechanical Engineering Science

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Research article

First published 2000-7

Assessment of machining features for tool condition monitoring in face milling using an artificial neural network

R K Dutta, G Kiran, S Paul [...]

Proceedings of the Institution of Mechanical Engineers,Part B: Journal of Engineering Manufacture

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Research article

First published 2025

Robot milling tool wear monitoring based on variational autoencoder with multidomain depth features

Jiawei Xu, Jianguo Chen, Lei Yang [...]

Proceedings of the Institution of Mechanical Engineers,Part E: Journal of Process Mechanical Engineering

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Research article

First published 2020-11

An intelligent prediction model of the tool wear based on machine learning in turning high strength steel

Minghui Cheng, Li Jiao, Xuechun Shi [...]

Proceedings of the Institution of Mechanical Engineers,Part B: Journal of Engineering Manufacture

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Research article

First published 2012-11

A support vector machine-based online tool condition monitoring for milling using sensor fusion and a genetic algorithm

Bulent Kaya, Cuneyt Oysu, Huseyin M Ertunc [...]

Proceedings of the Institution of Mechanical Engineers,Part B: Journal of Engineering Manufacture

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Research article

First published 2024-5

Time-frequency analysis-based impulse feature extraction method for quantitative evaluation of milling tool wear

MingAng Guo, Xiaotong Tu, Saqlain Abbas [...]

Structural Health Monitoring

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Review article

First published 2019-5

Lubrication in hot die forging processes

Marek Hawryluk, Jacek Ziemba

Proceedings of the Institution of Mechanical Engineers,Part J: Journal of Engineering Tribology

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