Results 201 to 210 of about 242,080 (232)
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Computers in Industry, 1991
Abstract Artificial systems obtain knowledge from the real world through sensors. The nature of the transducer, the location in space and the acquisition time must be considered to define the perceived state of the environment. Example base techniques are able to learn from the system experience. They are specially adequate for a complex multi-sensor
D. Guinea, A. Ruiz, L.J. Barrios
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Abstract Artificial systems obtain knowledge from the real world through sensors. The nature of the transducer, the location in space and the acquisition time must be considered to define the perceived state of the environment. Example base techniques are able to learn from the system experience. They are specially adequate for a complex multi-sensor
D. Guinea, A. Ruiz, L.J. Barrios
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Computers in Industry, 2019
Abstract On-machine monitoring of tool wear in machining processes has found its importance to reduce equipment downtime and reduce tooling costs. As the tool wears out gradually, the contact state of the cutting edge and the workpiece changes, which has a significant influence on the vibration state of the spindle.
Xin-Cheng Cao +3 more
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Abstract On-machine monitoring of tool wear in machining processes has found its importance to reduce equipment downtime and reduce tooling costs. As the tool wears out gradually, the contact state of the cutting edge and the workpiece changes, which has a significant influence on the vibration state of the spindle.
Xin-Cheng Cao +3 more
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Study on the Identification Method of Tool Wear State Based on SLLE and SVM in NC Machining
Applied Mechanics and Materials, 2014Aiming at the nonlinear features of Acoustic Emission reflecting the tool wear state, an identification method of tool wear state is proposed based on SLLE and lib-SVM. SLLE can overcome the problems of redundant parameters of the original nonlinear algorithms, low convergence rate, and tiny local areas in the reflecting process, etc.
Rui Pan, Zheng Qiang Li, Peng Nie
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Applied Mechanics and Materials, 2014
According to the un-stationary feature of the acoustic emission signals of tool wear, a tool wear state identification method based on genetic algorithm and BP neural network was proposed. The method reconstructed the acoustic emission signals and calculated the singular spectrum.
Zheng Qiang Li +3 more
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According to the un-stationary feature of the acoustic emission signals of tool wear, a tool wear state identification method based on genetic algorithm and BP neural network was proposed. The method reconstructed the acoustic emission signals and calculated the singular spectrum.
Zheng Qiang Li +3 more
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Identification and Analysis of Tool Wear State Based on Deep Learning
2022 IEEE 8th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS), 2022Yi Sun, Luoyifan Zhong, Hao Yue, Tao Mi
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Application of Weighted Combination Model in Tool Wear State Identification
2022 International Conference on Intelligent Manufacturing, Advanced Sensing and Big Data (IMASBD), 2022Cuiya Liu +3 more
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2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS), 2023
Xuwei Lai +4 more
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Xuwei Lai +4 more
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An Innovative Rfe-Ingo-Svm-Based Approach for Tool Wear State Identification
2023Jiaqi Wang +4 more
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Metabolomics in cancer research and emerging applications in clinical oncology
Ca-A Cancer Journal for Clinicians, 2021Daniel R Schmidt +2 more
exaly
Time to add screening for financial hardship as a quality measure?
Ca-A Cancer Journal for Clinicians, 2021Cathy J Bradley +2 more
exaly