Prognostics and Health Management of an Automated Machining Process
Joint Authors
He, Cheng
Li, Jiaming
Vachtsevanos, George
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-08
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Machine failure modes are presenting a major burden to the operator, the plant, and the enterprise causing significant downtime, labor cost, and reduced revenue.
New technologies are emerging over the past years to monitor the machine’s performance, detect and isolate incipient failures or faults, and take appropriate actions to mitigate such detrimental events.
This paper addresses the development and application of novel Prognostics and Health Management (PHM) technologies to a prototype machining process (a screw-tightening machine).
The enabling technologies are built upon a series of tasks starting with failure analysis, testing, and data processing aimed to extract useful features or condition indicators from raw data, a symbolic regression modeling framework, and a Bayesian estimation method called particle filtering to predict the feature state estimate accurately.
The detection scheme declares the fault of a machine critical component with user specified accuracy or confidence and given false alarm rate while the prediction algorithm estimates accurately the remaining useful life of the failing component.
Simulation results support the efficacy of the approach and match well the experimental data.
American Psychological Association (APA)
He, Cheng& Li, Jiaming& Vachtsevanos, George. 2015. Prognostics and Health Management of an Automated Machining Process. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1074398
Modern Language Association (MLA)
He, Cheng…[et al.]. Prognostics and Health Management of an Automated Machining Process. Mathematical Problems in Engineering No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1074398
American Medical Association (AMA)
He, Cheng& Li, Jiaming& Vachtsevanos, George. Prognostics and Health Management of an Automated Machining Process. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1074398
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074398