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Optimizing dynamic measurement accuracy for machine tools and industrial robots with unscented Kalman filter and particle swarm optimization methods

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Xing, Kanglin, Bonev, Ilian A., Champliaud, Henri and Liu, Zhaoheng. 2024. « Optimizing dynamic measurement accuracy for machine tools and industrial robots with unscented Kalman filter and particle swarm optimization methods ». Measurement Science and Technology, vol. 35, nº 8.

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Abstract

The telescoping ballbar is widely utilized for diagnosing accuracy and identifying faults in machine tools and industrial robots. Currently, there are no established standards for determining the optimal feed rate for ballbar tests. This lack of clear guidelines results in time inefficiency in measurements and inconsistencies in dynamic measurements, which complicates the comparison of ballbar test results under various conditions or across different machine platforms. To mitigate dynamic variations in ballbar results, an updated ballbar data processing method that integrates the unscented Kalman filter (UKF) and particle swarm optimization (PSO) was developed and validated using real ballbar data measured at multiple feed rates and simulated data with varying vibration magnitudes generated through the Renishaw ballbar simulator. Experimental results revealed that the dynamic components extracted from the ballbar results were observed to increase in correlation with the vibration measured at different feed rates and from the simulations. Moreover, the variations in the results measured at different feed rates after PSO-UKF processing were significantly reduced. The findings confirm the effectiveness of the proposed method in minimizing the dynamics of the ballbar results. Ultimately, this approach enhances the efficiency and accuracy of ballbar testing and offers a general method for improved diagnostics.

Item Type: Peer reviewed article published in a journal
Professor:
Professor
Bonev, Ilian
Champliaud, Henri
Liu, Zhaoheng
Affiliation: Génie des systèmes, Génie mécanique, Génie mécanique
Date Deposited: 05 Jun 2024 18:38
Last Modified: 07 Jun 2024 16:52
URI: https://espace2.etsmtl.ca/id/eprint/28769

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