研究论文
Data-model linkage prediction of tool remaining useful life based on deep feature fusion and Wiener process
Xuebing Li, Xianli Liu, Caixu Yue, Lihui Wang, Steven Y. Liang
Harbin University of Science and Technology KTH Royal Institute of Technology Georgia Institute of Technology
来源Journal of Manufacturing Systems
年份2024
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逐年被引趋势
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关键指标
86
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11.69
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同类平均 = 1
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学术脉络
学科主题
工程Advanced machining processes and optimization
Advanced Machining and Optimization Techniques · Metal Alloys Wear and Properties
参考文献 63
A Wiener-process-based degradation model with a recursive filter algorithm for remaining useful life estimation
被引 461Xiaosheng Si, Wenbin Wang, Chang-Hua Hu · Mechanical Systems and Signal Processing · 2012
Adaptive resampling-based particle filtering for tool life prediction
被引 75Peng Wang, Robert X. Gao · Journal of Manufacturing Systems · 2015
Tool wear monitoring by machine learning techniques and singular spectrum analysis
被引 138Bovic Kilundu, Pierre Dehombreux, Xavier Chiementin · Mechanical Systems and Signal Processing · 2010
此处列出前 3 条
引用本文 86
DCAGGCN: A novel method for remaining useful life prediction of bearings
被引 112Deqiang He, Jiayang Zhao, Zhenzhen Jin · Reliability Engineering & System Safety · 2025
A Review of Physics-Based, Data-Driven, and Hybrid Models for Tool Wear Monitoring
被引 74Haoyuan Zhang, Shanglei Jiang, Defeng Gao · Machines · 2024
Tool wear monitoring based on physics-informed Gaussian process regression
被引 71Mingjian Sun, Xianding Wang, Kai Guo · Journal of Manufacturing Systems · 2024
按被引量排序，此处列出前 3 条