A Multiple Model Prediction Algorithm for CNC Machine Wear PHM

Huimin Chen
Publication Target: 
IJPHM
Publication Issue: 
2
Submission Type: 
Technical Brief
Supporting Agencies (optional): 
NASA, ARO, ONR
AttachmentSizeTimestamp
ijPHM_11_011.pdf183.15 KBNovember 23, 2011 - 3:00pm

The 2010 PHM data challenge focuses on the remaining useful life (RUL) estimation for cutters of a high speed CNC milling machine using measurements from dynamometer, accelerometer, and acoustic emission sensors. We present a multiple model approach for wear depth estimation of milling machine cutters using the provided data. The feature selection, initial wear estimation and multiple model fusion components of the proposed algorithm are explained in details and compared with several alternative methods using the training data. The final submission ranked #2 among professional and student participants and the method is applicable to other data driven PHM problems.

Publication Year: 
2011
Publication Volume: 
2
Publication Control Number: 
011
Page Count: 
5
Submission Keywords: 
multiple model fusion
PHM data challenge
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
Submitted by: 
  
 
 
 

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