Based on the Singular Value Decomposition (SVD) of time series, this contribution addresses an innovative approach to provide essential information about the condition of servo systems for servo fault location or servo parameters tuning during diagnosing and calibrating CNC machine tools. When carrying out circular interpolation, the displacements of two involved axes are sampled as two independent time series. We adopt SVD algorithm to process the sampled data. A special matrix called attractor is constructed. By applying the Singular Value Ratio (SVR) spectrum, we have proposed the similarity ratio and then the similarity of two series is compared. The similarity ratio reflects the degree of mismatch between the coordinated axes.

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