Machine condition monitoring using discontinuity detection

Details Machine condition monitoring using discontinuity detection Machine condition monitoring using discontinuity detection

2011-05-24

2011-05-24

Barbee, Manuel L (Department: 2857)

Data processing: measuring, calibrating, or testing

Measurement system

Performance or efficiency evaluation

C700S108000

Reexamination Certificate

active

07949497

ABSTRACT:
Condition signals of machines are observed and one or more discontinuities are detected in the condition signals. The discontinuities in the condition signals are compensated for (e.g., by applying a shifting factor to models of the signals) and trends of the compensated condition signals are determined. The trends are used to predict future fault conditions in machines. Kalman filters comprising observation models and evolution models are used to determine the trends. Discontinuity in observed signals is detected using hypothesis testing.

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Dethlefsen, C., et al., “Formulating State Space Models in R with Focus on Longitudinal Regression Models”, Journal of Statistical Software, 2006, p. 1-15, 16(1).

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