However, sampling data at high rates is possible which needs hardware implementation of the filter. Among others, the weighted recursive median (WRM) filter has been shown to provide greater accuracy due to its weight adaptability depending on the signal type. On the other hand, non-linear filters based on image processing methods can provide more precise results for gas turbine health signals. Linear filters are inefficient in the removal of outliers and noise because they cause smoothening of the sharp features in the signal which can indicate the onset of a fault event. Several filters have been designed and tested for this purpose, and their performance analysis has been conducted. The removal of noise from signals obtained through the health monitoring systems in gas turbines is an important consideration for accurate prognostics.
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