Abstract
This paper introduces real time filtering method based on linear least squares fitted line. Method can be used in case that a filtered signal is linear. This constraint narrows a band of potential applications. Advantage over Kalman filter is that it is computationally less expensive. The paper further deals with application of introduced method on filtering data used to evaluate a position of engraved material with respect to engraving machine. The filter was implemented to the CNC engraving machine control system. Experiments showing its performance are included.
Highlights
The problem of real-time signal filtering is addressed extensively in technical society
In this paper the real time filtering method based on linear regression has been introduced
The filter is based on the idea of fitting a curve on a set of already measured data, supposing that a mathematical model of the signal is available
Summary
The problem of real-time signal filtering is addressed extensively in technical society. We can mention simple averaging or median filter; highpass, lowpass, bandpass filters [1] or widely used Kalman filter [2], [3] The superiority of the latter comes out of fact that it relies on measured data, and on prior knowledge of a measured signal in the form of a mathematical model. The idea of filtering lies in fitting a curve to already measured data, given the mathematical description of a curve. This basically means that if we know what kind of signal we expect we can interpolate a measured data by a curve of expected shape in real-time, filtering the noised data
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