PDF and Breakdown Time Prediction for Unobservable Wear Using Enhanced Particle Filters in Precognitive Maintenance-Reference-Cited by-同舟云学术

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PDF and Breakdown Time Prediction for Unobservable Wear Using Enhanced Particle Filters in Precognitive Maintenance

Published:2015-03 Issue:3 Volume:64 Page:649-659
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Chee Khiang Pang ,Jun-Hong Zhou ,Heng-Chao Yan

Funder

Singapore Ministry of Education through the Academic Research Funding Tier 1

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/7031980/06899617.pdf?arnumber=6899617

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. On-line tool wear monitoring under variable milling conditions based on a condition-adaptive hidden semi-Markov model (CAHSMM);Mechanical Systems and Signal Processing;2023-10

2. Hybrid Fuzzy Time Series Model and Data Fusion for Predicting Remaining Useful Life;Russian Journal of Nondestructive Testing;2022-12

3. A hybrid remaining useful life prediction method for cutting tool considering the wear state;The International Journal of Advanced Manufacturing Technology;2022-06-23

4. Process Monitoring, Diagnosis and Control of Additive Manufacturing;IEEE Transactions on Automation Science and Engineering;2022

5. Tool Condition Monitoring with Sparse Decomposition;Springer Series in Advanced Manufacturing;2021-11-24

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