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Advisor(s)
Abstract(s)
The progressive degradation of presently operating electro-mechanical systems is a certain future fact.
To minimize losses, maintenance costs and eventual replacements, condition monitoring should be
applied to critical equipment (Condition Based Maintenance – CBM). The state of equipment can be
predicted at any moment using statistical methods to analyze condition monitoring data. In this paper,
collected data are vibration values, obtained at p points (p = 4 for instance) of an experimental equipment,
forming p variables. When independence condition does not hold, it is suggested modeling data
with Auto-Regressive Integrated Moving Average (ARIMA) models, and using the residues of the estimated
model for Phase I. In Phase I, the estimation of parameters is achieved using the Hotelling T
control chart; only after applying the defined ARIMA model, the p variables are treated. In Phase II,
equipment state is artificially degraded through induced failures and failure prediction obtained using
special multivariate control charts for data statistical treatment. Assuming data independence and
normality, Multivariate Exponentially Weighted Moving Average Modified (MEWMAM) control charts
are applied in Phase II to data collected from an electric pump, controlling the behavior of data using
this procedure. In Phase II, for non-independent data the prediction errors from the adjusted model are
used instead of original data. To show that the suggested methodology can be applied to propulsion
systems, simulated data from a gas turbine are used. Using these methodologies it is possible to run
online condition monitoring, and act in time, to minimize maintenance costs and maximize equipment
performance.
Description
Keywords
Condition monitoring, Vibration detection and analysis, Statistical process control, Multivariate Exponential Weighted Moving Average (MEWMA) control chart
Citation
Lampreia, S., et al..., (2015). Implementation of MEWMA Control Chart in Equipment Condition Monitoring.Journal of Vibration Engineering & Technologies, Vol. 3, No. 6: 667-677
Publisher
Krishtel eMaging Solutions Pvt. Ltd.,