Sensor layout optimization by integrating Bayesian approach to diagnose multi-station assembly processes-Reference-Cited by-同舟云学术

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Sensor layout optimization by integrating Bayesian approach to diagnose multi-station assembly processes

Published:2019-11 Issue: Volume:146 Page:230-240
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

He Kang,Jia Minping,Liu Conghu,Zhao Zhuanzhe

Funder

National Natural Science Foundation of China

Natural Science Foundation of Anhui Province

Key Project of Natural Science Foundation of Universities of Anhui Province

Scientific Research Foundatio

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference49 articles.

1. A survey of fault diagnosis and fault-tolerant techniques—Part I: Fault diagnosis with model-based and signal-based approaches;Gao;IEEE Trans. Ind. Electron.,2015

2. Monitoring and Control of Machining, in Condition Monitoring and Control for Intelligent Manufacturing;Wang,2006

3. Intelligent Fault Diagnosis and Prognosis for Engineering Systems;Vachtsevanos,2007

4. Sensor deployment based on fuzzy graph considering heterogeneity and multiple-objectives to diagnose manufacturing system;Wu;Robot. Cim-int. Manuf.,2013

5. Optimal sensor distribution for variation diagnosis in multistation assembly processes;Ding;IEEE Trans. Rob. Auto.,2003

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