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Sensitivity analysis of factors affecting motion reliability of manipulator and fault diagnosis based on kernel principal component analysis

Published online by Cambridge University Press:  10 December 2021

Jing Yang Open the ORCID record for Jing Yang [Opens in a new window] ,
Lingyan Jin ,
Zejie Han ,
Deming Zhao  and
Ming Hu
Jing Yang
Affiliation:
Faculty of Mechanical Engineering & Automation, Zhejiang Sci-Tech University, Hangzhou, Zhejiang Province, China
Lingyan Jin
Affiliation:
Faculty of Mechanical Engineering & Automation, Zhejiang Sci-Tech University, Hangzhou, Zhejiang Province, China
Zejie Han
Affiliation:
Faculty of Mechanical Engineering & Automation, Zhejiang Sci-Tech University, Hangzhou, Zhejiang Province, China
Deming Zhao
Affiliation:
Faculty of Mechanical Engineering & Automation, Zhejiang Sci-Tech University, Hangzhou, Zhejiang Province, China
Ming Hu*
Affiliation:
Faculty of Mechanical Engineering & Automation, Zhejiang Sci-Tech University, Hangzhou, Zhejiang Province, China
*
*Corresponding author. E-mail: [email protected]
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Abstract

As an important index to quantitatively measure the motion performance of a manipulator, motion reliability is affected by many factors, such as joint clearance. The present research utilized a UR10 manipulator as the research object. A factor mapping model for influencing the motion reliability was established. The link flexibility factor, joint flexibility factor, joint clearance factor, and Denavit–Hartenberg (DH) parameters were comprehensively considered in this model. The coupling relationship among the various factors was concisely expressed. Subsequently, the nonlinear response surface method was used to calculate the reliability and sensitivity of the manipulator, which provided an applicable reference for its trajectory planning and motion control. In addition, a data-driven fault diagnosis method based on the kernel principal component analysis (KPCA) was used to verify the motion accuracy and sensitivity of the manipulator, and joint rotation failure was considered as an example to verify the accuracy of the KPCA method. This study on the motion reliability of the manipulator is of great significance for the current motion performance, adjusting the control strategy and optimizing the completion effect of the motion task of a manipulator.

Keywords

manipulatormotion reliabilitysensitivity analysisfault diagnosiskernel principal component analysis
Type
Research Article
Information
Robotica , Volume 40 , Issue 8 , August 2022 , pp. 2547 - 2566
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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