کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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480830 | 1446104 | 2011 | 7 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: An approximate algorithm for prognostic modelling using condition monitoring information An approximate algorithm for prognostic modelling using condition monitoring information](/preview/png/480830.png)
Established condition based maintenance modelling techniques can be computationally expensive. In this paper we propose an approximate methodology using extended Kalman-filtering and condition monitoring information to recursively establish a conditional probability density function for the residual life of a component. The conditional density is then used in the construction of a maintenance/replacement decision model. The advantages of the methodology, when compared with alternative approaches, are the direct use of the often multi-dimensional condition monitoring data and the on-line automation opportunity provided by the computational efficiency of the model that potentially enables the simultaneous condition monitoring and associated inference for a large number of components and monitored variables. The methodology is applied to a vibration monitoring scenario and compared with alternative models using the case data.
Journal: European Journal of Operational Research - Volume 211, Issue 1, 16 May 2011, Pages 90–96