Concurrent Estimation of Time-to-Failure and Effective Wear

Abstract

We propose a novel algorithm for the estimation of remaining lifetime of a generic device based on an intuitive and widely-applicable model of failure due to accumulation of effective wear. The simultaneous quantification of an abstract, multivariate wear function is achieved by a new learning algorithm which we term "cumulative effect regression". We develop the theory of the algorithm and compare its performance to traditional anomaly and pattern detection tools. Experimental results from X-ray tubes strongly validate the algorithm and demonstrate the utility of Operating Charactersitics (OC) curves as a powerful evaluation tool.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2003
Accession Number
ADA575045

Entities

People

  • Christian J. Darken
  • Markus Loecher

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Anomaly Detection
  • Change Detection
  • Computer Science
  • Condition Based Maintenance
  • Data Sets
  • Data Storage Systems
  • Detection
  • Errors
  • Failure Mode And Effect Analysis
  • High Voltage
  • Maintenance
  • Measurement
  • Preventive Maintenance
  • X Ray Tubes
  • X Rays

Readers

  • Computational Modeling and Simulation
  • Neural Network Machine Learning.
  • Statistical inference.