Extraction the unbalance features of spindle system using wavelet transform and power spectral density

Identification of the spindle unbalance is very important for the ultra-precision machining tools. In the first part, the frequency information for the spindle system is computed by two methods. In the second part, the results between the modal information of the spindle and the error frequency of the measured workpiece surface which processed by wavelet transform and power spectral density is compared, the signal feature in the waviness which is consistent with the spindle unbalance frequency is extracted. In the last part, the identified result is compared, it proves the extraction and identification method for the spindle unbalance of the machine tool is correctness and validity.

► Dynamic behavior of the hydrostatic spindle is analyzed with two methods.
► The choose basis of wavelet is researched and provided.
► Spectrum characteristics analyzed by power spectral density.
► Errors for the unbalance of the spindle from the waviness are identified.