Abstract
In the paper, the spread of intensity of linear positioning table system vibrations is examined and an analysis of their parameters upon applying the theory of covariance functions is carried out. For the investigation, two linear positioning tables were chosen; for them, different lubricants were used: universal lubricant Loctite 8103 and lubricant Braycote 601EF for working in vacuum. The results of measurements of the vibration intensity in four fixed points upon varying the speed of the carriage were recorded on the time scale in form of arrays (matrices). The estimates of cross-covariance functions of the arrays of results of measurements of the digital vibration intensity were calculated. The estimates of auto-covariance functions of single arrays upon changing the quantization interval on the time scale were calculated too. For the calculations, the software developed upon using Matlab7 package of procedures was applied.
Highlights
Demands for machining and metrology over a relatively large range have recently increased in a variety of industries and sciences such as aerospace, electronics, energy, and astronomy [1], [2] and [3]
The said works are relevant because guides and other structural elements used in CNC milling machines are assembled of different elements connected with each other by threaded junctions
Researchers Narasimhan, Jordache and Crowe considered steady-state data reconciliation which functional on a realtime basis [22, 23]. They have determined that, despite the solution’s simplicity, the assessment precision maybe be less than measurement accuracy itself depending on plant dynamics
Summary
Demands for machining and metrology over a relatively large range have recently increased in a variety of industries and sciences such as aerospace, electronics, energy, and astronomy [1], [2] and [3]. An analysis of dynamic parameters of a linear positioning table system upon applying the theory of random functions is carried out. Researchers Narasimhan, Jordache and Crowe considered steady-state data reconciliation which functional on a realtime basis [22, 23]. They have determined that, despite the solution’s simplicity, the assessment precision maybe be less than measurement accuracy itself depending on plant dynamics. Researchers Ekstrom and McEwen [27] improved adaptive box-filtering measures to eliminate random bit faults (pixel values in case if they are not related to the picture) and even noise data, i.e. pixels of the picture related with an adulterant or multiplicative noise element. For treatment of the numerical signals, discrete Fourier transform described by researchers Ekstrom, McEwen [27] and the theory of wavelets were applied in scientific papers of Antoine [28], Berczynski and Wroblewski [29]
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