Calibration of an interferometric on-machine probing system on an ultra-precision turning machine

Duo Li, Zhen Tong, Xiangqian Jiang, Liam Blunt, Feng Gao

Research output: Contribution to journalArticlepeer-review

40 Citations (Scopus)


Surface measurement is fundamental to further enhance accuracy and efficiency in ultra-precision machining. Advanced on-machine measurement (OMM) is evolving as the key enabling technology for autonomous and intelligent manufacturing. The present work integrates an interferometric probing system on an ultra-precision turning machine. However, due to relatively harsh environment in the machine tools, metrology characteristics of surface measuring instrument would deviate from those tested in laboratories. In order to improve the performance of on-machine measurement system, it is necessary to calibrate the OMM system and compensate the systematic errors. Three major error sources, including on-machine vibration, machine tool kinematic errors, and linearity errors are investigated according to the characteristics of interferometric single point OMM. For on-machine vibration, a theoretical study of the relationship between sampling frequency, scanning parameters, vibration frequency and topography frequencies of interest is first presented. Static and scanning vibration tests are performed in order to select the proper sampling frequency. Machine scanning error is mapped for OMM correction with the proposed kinematic error modelling measurement and compensation method. Calibration of the response curve and linearity error correction is conducted by measuring a radially distributed step height sample on the machine. Experimental investigation is conducted which proves the validity of proposed calibration methodology and the effectiveness of OMM. After the calibration process, OMM results agree well with calibrated offline measurements.
Original languageEnglish
Pages (from-to)96-104
Number of pages9
JournalMeasurement: Journal of the International Measurement Confederation
Early online date5 Jan 2018
Publication statusPublished - 1 Mar 2018


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