Vibration Analysis Based Condition Monitoring for Industrial Robots

Huanqing Han; Yubin Lin; Lichang Gu; Yuandong Xu; Fengshou Gu

doi:10.1007/978-3-030-75793-9_19

Vibration Analysis Based Condition Monitoring for Industrial Robots

Huanqing Han, Yubin Lin, Lichang Gu, Yuandong Xu, Fengshou Gu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

Abstract

The position of an industrial robot in manufacturing has become more and more important. The monitoring of its condition is an urgent problem to be solved, because it is related to the safety and stability of production. Traditional monitoring methods mainly use external tools (such as acoustic emission sensor) or sensors (encoder, motor current sensor) inside industrial robot. In this paper, a condition monitoring method for industrial robots based on vibration analysis is proposed. Firstly, in the case of no fault, the three-axis acceleration data of the working point of the industrial robot is obtained by using a triaxial MEMS accelerometer. Based on experimental studies, it is shown that the vibration characteristics of each joint of the industrial robot have different characteristics, the differences being presented for different joints according to the characteristics of the frequency response. Then, different degrees of seal ring fault are simulated on the elbow of the robot. And the frequency and time domain responses are obtained based on different data. Through analysis, the fault location and degree of faults can be obtained according to vibration analysis. In addition, the accuracy of this conclusion is verified by calculating the RMS value of each axis. The results show that it is feasible to monitor the condition of industrial robots by vibration analysis.

Original language	English
Title of host publication	Proceedings of IncoME-V & CEPE Net-2020
Subtitle of host publication	Condition Monitoring, Plant Maintenance and Reliability
Editors	Dong Zhen, Dong Wang, Tianyang Wang, Hongjun Wang, Baoshan Huang, Jyoti K. Sinha, Andrew David Ball
Place of Publication	Cham
Publisher	Springer Nature Switzerland AG
Pages	186-195
Number of pages	10
Volume	105
Edition	1st
ISBN (Electronic)	9783030757939
ISBN (Print)	9783030757922
DOIs	https://doi.org/10.1007/978-3-030-75793-9_19
Publication status	Published - 16 May 2021
Event	5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network - Zhuhai, China Duration: 23 Oct 2020 → 25 Oct 2020 Conference number: 5 https://link.springer.com/book/10.1007/978-3-030-75793-9#about

Publication series

Name	Mechanisms and Machine Science
Volume	105
ISSN (Print)	2211-0984
ISSN (Electronic)	2211-0992

Conference

Conference	5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network
Abbreviated title	IncoME-V and CEPE Net-2020
Country/Territory	China
City	Zhuhai
Period	23/10/20 → 25/10/20
Internet address	https://link.springer.com/book/10.1007/978-3-030-75793-9#about

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Cite this

Han, H., Lin, Y., Gu, L., Xu, Y., & Gu, F. (2021). Vibration Analysis Based Condition Monitoring for Industrial Robots. In D. Zhen, D. Wang, T. Wang, H. Wang, B. Huang, J. K. Sinha, & A. D. Ball (Eds.), Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability (1st ed., Vol. 105, pp. 186-195). (Mechanisms and Machine Science; Vol. 105). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-75793-9_19

Han, Huanqing ; Lin, Yubin ; Gu, Lichang et al. / Vibration Analysis Based Condition Monitoring for Industrial Robots. Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. editor / Dong Zhen ; Dong Wang ; Tianyang Wang ; Hongjun Wang ; Baoshan Huang ; Jyoti K. Sinha ; Andrew David Ball. Vol. 105 1st. ed. Cham : Springer Nature Switzerland AG, 2021. pp. 186-195 (Mechanisms and Machine Science).

@inproceedings{7ed94ab3b5b44feeb868984ffd0cd53d,

title = "Vibration Analysis Based Condition Monitoring for Industrial Robots",

abstract = "The position of an industrial robot in manufacturing has become more and more important. The monitoring of its condition is an urgent problem to be solved, because it is related to the safety and stability of production. Traditional monitoring methods mainly use external tools (such as acoustic emission sensor) or sensors (encoder, motor current sensor) inside industrial robot. In this paper, a condition monitoring method for industrial robots based on vibration analysis is proposed. Firstly, in the case of no fault, the three-axis acceleration data of the working point of the industrial robot is obtained by using a triaxial MEMS accelerometer. Based on experimental studies, it is shown that the vibration characteristics of each joint of the industrial robot have different characteristics, the differences being presented for different joints according to the characteristics of the frequency response. Then, different degrees of seal ring fault are simulated on the elbow of the robot. And the frequency and time domain responses are obtained based on different data. Through analysis, the fault location and degree of faults can be obtained according to vibration analysis. In addition, the accuracy of this conclusion is verified by calculating the RMS value of each axis. The results show that it is feasible to monitor the condition of industrial robots by vibration analysis.",

keywords = "Condition monitoring, Industrial robots, Seal fault, Vibration analysis, Vibration characteristics",

author = "Huanqing Han and Yubin Lin and Lichang Gu and Yuandong Xu and Fengshou Gu",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network, IncoME-V and CEPE Net-2020 ; Conference date: 23-10-2020 Through 25-10-2020",

year = "2021",

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language = "English",

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pages = "186--195",

editor = "Dong Zhen and Dong Wang and Tianyang Wang and Hongjun Wang and Baoshan Huang and Sinha, {Jyoti K.} and Ball, {Andrew David}",

booktitle = "Proceedings of IncoME-V & CEPE Net-2020",

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Han, H, Lin, Y, Gu, L, Xu, Y & Gu, F 2021, Vibration Analysis Based Condition Monitoring for Industrial Robots. in D Zhen, D Wang, T Wang, H Wang, B Huang, JK Sinha & AD Ball (eds), Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. 1st edn, vol. 105, Mechanisms and Machine Science, vol. 105, Springer Nature Switzerland AG, Cham, pp. 186-195, 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network, Zhuhai, China, 23/10/20. https://doi.org/10.1007/978-3-030-75793-9_19

Vibration Analysis Based Condition Monitoring for Industrial Robots. / Han, Huanqing; Lin, Yubin; Gu, Lichang et al.

Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. ed. / Dong Zhen; Dong Wang; Tianyang Wang; Hongjun Wang; Baoshan Huang; Jyoti K. Sinha; Andrew David Ball. Vol. 105 1st. ed. Cham : Springer Nature Switzerland AG, 2021. p. 186-195 (Mechanisms and Machine Science; Vol. 105).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Vibration Analysis Based Condition Monitoring for Industrial Robots

AU - Han, Huanqing

AU - Lin, Yubin

AU - Gu, Lichang

AU - Xu, Yuandong

AU - Gu, Fengshou

N1 - Conference code: 5

PY - 2021/5/16

Y1 - 2021/5/16

N2 - The position of an industrial robot in manufacturing has become more and more important. The monitoring of its condition is an urgent problem to be solved, because it is related to the safety and stability of production. Traditional monitoring methods mainly use external tools (such as acoustic emission sensor) or sensors (encoder, motor current sensor) inside industrial robot. In this paper, a condition monitoring method for industrial robots based on vibration analysis is proposed. Firstly, in the case of no fault, the three-axis acceleration data of the working point of the industrial robot is obtained by using a triaxial MEMS accelerometer. Based on experimental studies, it is shown that the vibration characteristics of each joint of the industrial robot have different characteristics, the differences being presented for different joints according to the characteristics of the frequency response. Then, different degrees of seal ring fault are simulated on the elbow of the robot. And the frequency and time domain responses are obtained based on different data. Through analysis, the fault location and degree of faults can be obtained according to vibration analysis. In addition, the accuracy of this conclusion is verified by calculating the RMS value of each axis. The results show that it is feasible to monitor the condition of industrial robots by vibration analysis.

AB - The position of an industrial robot in manufacturing has become more and more important. The monitoring of its condition is an urgent problem to be solved, because it is related to the safety and stability of production. Traditional monitoring methods mainly use external tools (such as acoustic emission sensor) or sensors (encoder, motor current sensor) inside industrial robot. In this paper, a condition monitoring method for industrial robots based on vibration analysis is proposed. Firstly, in the case of no fault, the three-axis acceleration data of the working point of the industrial robot is obtained by using a triaxial MEMS accelerometer. Based on experimental studies, it is shown that the vibration characteristics of each joint of the industrial robot have different characteristics, the differences being presented for different joints according to the characteristics of the frequency response. Then, different degrees of seal ring fault are simulated on the elbow of the robot. And the frequency and time domain responses are obtained based on different data. Through analysis, the fault location and degree of faults can be obtained according to vibration analysis. In addition, the accuracy of this conclusion is verified by calculating the RMS value of each axis. The results show that it is feasible to monitor the condition of industrial robots by vibration analysis.

KW - Condition monitoring

KW - Industrial robots

KW - Seal fault

KW - Vibration analysis

KW - Vibration characteristics

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SN - 9783030757922

VL - 105

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BT - Proceedings of IncoME-V & CEPE Net-2020

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A2 - Wang, Dong

A2 - Wang, Tianyang

A2 - Wang, Hongjun

A2 - Huang, Baoshan

A2 - Sinha, Jyoti K.

A2 - Ball, Andrew David

PB - Springer Nature Switzerland AG

CY - Cham

T2 - 5th International Conference on Maintenance Engineering and the 2020 Annual Conference of the Centre for Efficiency and Performance Engineering Network

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Han H, Lin Y, Gu L, Xu Y, Gu F. Vibration Analysis Based Condition Monitoring for Industrial Robots. In Zhen D, Wang D, Wang T, Wang H, Huang B, Sinha JK, Ball AD, editors, Proceedings of IncoME-V & CEPE Net-2020: Condition Monitoring, Plant Maintenance and Reliability. 1st ed. Vol. 105. Cham: Springer Nature Switzerland AG. 2021. p. 186-195. (Mechanisms and Machine Science). Epub 2021 May 16. doi: 10.1007/978-3-030-75793-9_19

Vibration Analysis Based Condition Monitoring for Industrial Robots

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UN SDGs

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