A systematic literature review of cutting tool wear monitoring in turning by using artificial intelligence techniques
In turning operations, the wear of cutting tools is inevitable. As workpieces produced with
worn tools may fail to meet specifications, the machining industries focus on replacement …
worn tools may fail to meet specifications, the machining industries focus on replacement …
[图书][B] From prognostics and health systems management to predictive maintenance 1: Monitoring and prognostics
This book addresses the steps needed to monitor health assessment systems and the
anticipation of their failures: choice and location of sensors, data acquisition and processing …
anticipation of their failures: choice and location of sensors, data acquisition and processing …
Using multiple-feature-spaces-based deep learning for tool condition monitoring in ultraprecision manufacturing
C Shi, G Panoutsos, B Luo, H Liu… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Tool condition monitoring is critical in ultraprecision manufacturing in order to optimize the
performance of the overall process, while maintaining the desired part quality. Recently …
performance of the overall process, while maintaining the desired part quality. Recently …
Tool wear monitoring and prognostics challenges: a comparison of connectionist methods toward an adaptive ensemble model
In a high speed milling operation the cutting tool acts as a backbone of machining process,
which requires timely replacement to avoid loss of costly workpiece or machine downtime …
which requires timely replacement to avoid loss of costly workpiece or machine downtime …
A physically segmented hidden Markov model approach for continuous tool condition monitoring: Diagnostics and prognostics
O Geramifard, JX Xu, JH Zhou… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
In this paper, a temporal probabilistic approach based on the hidden Markov model (HMM),
named physically segmented HMM with continuous output, is introduced for continuous tool …
named physically segmented HMM with continuous output, is introduced for continuous tool …
Using the machine vision method to develop an on-machine insert condition monitoring system for computer numerical control turning machine tools
WH Sun, SS Yeh - Materials, 2018 - mdpi.com
This study uses the machine vision method to develop an on-machine turning tool insert
condition monitoring system for tool condition monitoring in the cutting processes of …
condition monitoring system for tool condition monitoring in the cutting processes of …
Review of empirical modelling techniques for modelling of turning process
The most widely and well known machining process used is turning. The turning process
possesses higher complexity and uncertainty and therefore several empirical modelling …
possesses higher complexity and uncertainty and therefore several empirical modelling …
A robust and reliable data-driven prognostics approach based on extreme learning machine and fuzzy clustering
K Javed - 2014 - theses.hal.science
Prognostics and Health Management (PHM) aims at extending the life cycle of engineerin
gassets, while reducing exploitation and maintenance costs. For this reason, prognostics is …
gassets, while reducing exploitation and maintenance costs. For this reason, prognostics is …
Differential evolution-based feature selection and parameter optimisation for extreme learning machine in tool wear estimation
WA Yang, Q Zhou, KL Tsui - International Journal of Production …, 2016 - Taylor & Francis
Cutting tool wear degrades the product quality in manufacturing processes. Hence, real-time
online estimation of tool wear is important for suggesting a tool replacement before the wear …
online estimation of tool wear is important for suggesting a tool replacement before the wear …
Classification-driven model selection approach of genetic programming in modelling of turning process
Turning is a widely used machining process, but the process complexity and uncertainty
lead to empirical modelling techniques being preferred over physics-based models for …
lead to empirical modelling techniques being preferred over physics-based models for …