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Optimized geometric error sensitivity analysis approach based on stream-of-variation theory in multi-axis precise motion platform

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Abstract

In this paper, an optimized error sensitivity analysis (ESA) approach based on stream-of-variation (SOV) theory in multi-axis precise motion platform (MPMP) is introduced. Unlike the conventional ESA method, this approach utilizes stream-of-variation theory to establish error model firstly. By regarding each axis as a station, the error propagation and deviation accumulation processes are clear station by station. Through obtaining the deviations after each station, the sensitive stations can be developed, and corresponding error terms are collected. Thus, by analyzing the appearance frequency of the errors, a precise sensitive order can be developed, and a sensitivity results with different steps is given. Through ignoring the insensitive and irrelevant errors, the computational volume of error model can be saved, and the efficiency can be improved. A case study about a typical MPMP used in laser welding system (LWS) is carried out, and the results indicate that the optimized ESA approach is more efficient and accurate, and it is flexible as well. This ESA approach is not only accurate in developing sensitive levels, but also balancing the systematic accuracy and working efficiency, which is helpful to provide informative guide to engineers.

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Abbreviations

MPMP :

Multi-axis precise motion platform

HTM :

Homogeneous transformation matrix

X, Y, Z, A, B, C :

Axis in multi-axis system

x, y, z, u, v, w :

Geometric error

xk, yk, zk :

Kinematic error

αs, βs, γs :

Location error

Si/Sa :

Ideal state/actual state

F ∞ :

Coordinate offset matrix

T mov :

Movement matrix

E s :

Location error matrix

E k :

Kinematic error matrix

P j :

Initial state in system j

OPS:

Optoelectronic packaging system

Yo, Zo :

Coordinate offset between two adjacent systems

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Acknowledgments

This research is supported by the National Natural Science Foundation of China (Grant No. 51705149 and No. 51875198) and the Natural Science Foundation of Hunan province (Grant No.2018JJ3168).

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Authors and Affiliations

  1. School of Mechanical Engineering, Hunan University of Science and Technology, Xiangtan, Hunan, 411201, China

    Hao Tang, Changping Li, Jia Chen, Huimin Kang & Tae Jo Ko

  2. School of Mechanical Engineering, Yeungnam University, Gyeongsan, 712-749, Korea

    Tae Jo Ko

  3. ZOLIX Instruments CO., LTD, Beijing, 101102, China

    Mianke Du

Authors
  1. Hao Tang
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  2. Changping Li
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  3. Jia Chen
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  4. Huimin Kang
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Corresponding author

Correspondence to Hao Tang.

Additional information

Hao Tang was born in Changsha, Hunan, China, in 1988. He graduated from Dong Hua University, Shanghai, China, and started the M.S. degree in mechanical engineering in Central South University, Changsha, China, in 2009, and transferred into Ph.D. student in 2011. His research interests include error analysis, error modeling and precision transferring in complicated multi-axis motion system, and applications of optoelectronic packaging system and laser welding system. He, as a visiting student, went to University of Michigan, Ann Arbor, US, from Sept. 2013 to Mar. 2015, and worked in S.M. Wu Manufacture Center.

Chang Ping Li is an Assistant Professor of Mechanical Engineering at Hunan University of Science & Technology, China. He received his bachelor’s from Kumoh National Institute of Technology, South Korea. He received master’s degrees and Ph.D. in Mechanical Engineering from Yeungnam University, South Korea. His research interests include the development of machine tools; hybrid machining; nontraditional machining; the deburring process of CFRP composites.

Jia Chen is an undergraduate student of Mechanical Engineering at Hunan University of Science & Technology, China. Her research interests include error analysis, error modeling and error parameters transferring law in complicated multi-axis motion system, and the relation of Monte-Carlo method and mathematical derivation.

Huimin Kang is a Professor of Mechanical Engineering at Hunan University of Science & Technology, China. He received his bachelor’s from Shenyang Aerospace University, China. He received master’s degrees and Ph.D. from The State Key Laboratory of Mechanical Transmission, Chongqing University, China. His research interests include the dynamic evolution mechanism analysis of high speed motorized spindle’s turning accuracy under complex working conditions, dynamic stiffness analysis and active control of high speed motorized spindle.

Tae Jo Ko is a Professor of Mechanical Engineering at Yeungnam University, South Korea. He received his bachelor’s and master’s degrees from Pusan National University, South Korea. He received a Ph.D. in Mechanical Engineering from POSTECH, South Korea. His research interests include the development of machine tools; micro-cutting processes; nontraditional machining; surface texturing using piezoelectric actuators; surface texturing using grinding, bio-machining, and textured surfaces on cutting tools; and the deburring process of CFRP composites.

Mianke Du was born in Beijing of China in 1984. He graduate from Harbin Engineering University, in 2008. He has been the R & D manager of ZOLIX Instruments CO., LTD since 2008. He is mainly responsible for the research and development of precision machinery and its motion control system. He has applied for 2 invention patents and 8 utility model patents.

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Tang, H., Li, C., Chen, J. et al. Optimized geometric error sensitivity analysis approach based on stream-of-variation theory in multi-axis precise motion platform. J Mech Sci Technol 34, 4229–4237 (2020). https://doi.org/10.1007/s12206-020-0915-8

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  • DOI: https://doi.org/10.1007/s12206-020-0915-8

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