Modelling and Vibration Signal Analysis for Condition Monitoring of Industrial Robots

Huanqing Han; Dawei Shi; Lichang Gu; Nasha Wei; Fengshou Gu

doi:10.1007/978-3-030-99075-6_71

Modelling and Vibration Signal Analysis for Condition Monitoring of Industrial Robots

Huanqing Han, Dawei Shi, Lichang Gu, Nasha Wei, Fengshou Gu

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

1 Citation (Scopus)

Abstract

Industrial robots are widely used in modern factories. Robot faults and abnormal working state will lead to the shutdown of the production line inevitably. Robot condition monitoring can improve production capacity. However, due to the changes of robot in dynamic working state, this is a challenge. This paper presents a methodology of condition monitoring for industrial robots using vibration signals. The main purpose of this paper is to identify the occurrence of the fault and its different degrees. Experiments was performed on a 6-dof industrial robot (IR). Firstly, the Frequency Response Function of the IR was obtained by using the Experimental Modal Analysis method. And the characteristic frequency in each axis was found. Then, based on the Short-time Fourier Transform analysis method, the vibration data under normal conditions and different degrees of abnormal working conditions were analysed. In some characteristic frequency bands, the amplitude will increase with the increase of the binding force at the joint. Finally, this trend was further verified by the calculation of RMS value. The results show that the proposed frequency domain and model analysis method can monitor the operating condition of industrial robots.

Original language	English
Title of host publication	Proceedings of IncoME-VI and TEPEN 2021
Subtitle of host publication	Performance Engineering and Maintenance Engineering
Editors	Hao Zhang, Guojin Feng, Hongjun Wang, Fengshou Gu, Jyoti K. Sinha
Publisher	Springer, Cham
Pages	879-891
Number of pages	13
Volume	117
ISBN (Electronic)	9783030990756
ISBN (Print)	9783030990749
DOIs	https://doi.org/10.1007/978-3-030-99075-6_71
Publication status	Published - 18 Sep 2022
Event	6th International Conference on Maintenance Engineering, IncoME-VI and the Conference of the Efficiency and Performance Engineering Network, TEPEN 2021 - Hebei University of Technology, Tianjin, China Duration: 20 Oct 2021 → 23 Oct 2021 Conference number: 6 https://tepen.net/conference/tepen2021/

Publication series

Name	Mechanisms and Machine Science
Publisher	Springer
Volume	117
ISSN (Print)	2211-0984
ISSN (Electronic)	2211-0992

Conference

Conference	6th International Conference on Maintenance Engineering, IncoME-VI and the Conference of the Efficiency and Performance Engineering Network, TEPEN 2021
Abbreviated title	TEPEN-2021 and IncoME-VI
Country/Territory	China
City	Tianjin
Period	20/10/21 → 23/10/21
Internet address	https://tepen.net/conference/tepen2021/

UN SDGs

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

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10.1007/978-3-030-99075-6_71Licence: Unspecified

Cite this

Han, H., Shi, D., Gu, L., Wei, N., & Gu, F. (2022). Modelling and Vibration Signal Analysis for Condition Monitoring of Industrial Robots. In H. Zhang, G. Feng, H. Wang, F. Gu, & J. K. Sinha (Eds.), Proceedings of IncoME-VI and TEPEN 2021 : Performance Engineering and Maintenance Engineering (Vol. 117, pp. 879-891). (Mechanisms and Machine Science; Vol. 117). Springer, Cham. https://doi.org/10.1007/978-3-030-99075-6_71

Han, Huanqing ; Shi, Dawei ; Gu, Lichang et al. / Modelling and Vibration Signal Analysis for Condition Monitoring of Industrial Robots. Proceedings of IncoME-VI and TEPEN 2021 : Performance Engineering and Maintenance Engineering. editor / Hao Zhang ; Guojin Feng ; Hongjun Wang ; Fengshou Gu ; Jyoti K. Sinha. Vol. 117 Springer, Cham, 2022. pp. 879-891 (Mechanisms and Machine Science).

@inproceedings{e375d6d457344b2fa26a0e1071c888f3,

title = "Modelling and Vibration Signal Analysis for Condition Monitoring of Industrial Robots",

abstract = "Industrial robots are widely used in modern factories. Robot faults and abnormal working state will lead to the shutdown of the production line inevitably. Robot condition monitoring can improve production capacity. However, due to the changes of robot in dynamic working state, this is a challenge. This paper presents a methodology of condition monitoring for industrial robots using vibration signals. The main purpose of this paper is to identify the occurrence of the fault and its different degrees. Experiments was performed on a 6-dof industrial robot (IR). Firstly, the Frequency Response Function of the IR was obtained by using the Experimental Modal Analysis method. And the characteristic frequency in each axis was found. Then, based on the Short-time Fourier Transform analysis method, the vibration data under normal conditions and different degrees of abnormal working conditions were analysed. In some characteristic frequency bands, the amplitude will increase with the increase of the binding force at the joint. Finally, this trend was further verified by the calculation of RMS value. The results show that the proposed frequency domain and model analysis method can monitor the operating condition of industrial robots.",

keywords = "Condition monitoring, Frequency Response, Industrial robots, Model analysis, Vibration analysis",

author = "Huanqing Han and Dawei Shi and Lichang Gu and Nasha Wei and Fengshou Gu",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 6th International Conference on Maintenance Engineering, IncoME-VI and the Conference of the Efficiency and Performance Engineering Network, TEPEN 2021, TEPEN-2021 and IncoME-VI ; Conference date: 20-10-2021 Through 23-10-2021",

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doi = "10.1007/978-3-030-99075-6_71",

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Han, H, Shi, D, Gu, L, Wei, N & Gu, F 2022, Modelling and Vibration Signal Analysis for Condition Monitoring of Industrial Robots. in H Zhang, G Feng, H Wang, F Gu & JK Sinha (eds), Proceedings of IncoME-VI and TEPEN 2021 : Performance Engineering and Maintenance Engineering. vol. 117, Mechanisms and Machine Science, vol. 117, Springer, Cham, pp. 879-891, 6th International Conference on Maintenance Engineering, IncoME-VI and the Conference of the Efficiency and Performance Engineering Network, TEPEN 2021, Tianjin, China, 20/10/21. https://doi.org/10.1007/978-3-030-99075-6_71

Modelling and Vibration Signal Analysis for Condition Monitoring of Industrial Robots. / Han, Huanqing; Shi, Dawei; Gu, Lichang et al.

Proceedings of IncoME-VI and TEPEN 2021 : Performance Engineering and Maintenance Engineering. ed. / Hao Zhang; Guojin Feng; Hongjun Wang; Fengshou Gu; Jyoti K. Sinha. Vol. 117 Springer, Cham, 2022. p. 879-891 (Mechanisms and Machine Science; Vol. 117).

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

TY - GEN

T1 - Modelling and Vibration Signal Analysis for Condition Monitoring of Industrial Robots

AU - Han, Huanqing

AU - Shi, Dawei

AU - Gu, Lichang

AU - Wei, Nasha

AU - Gu, Fengshou

N1 - Conference code: 6

PY - 2022/9/18

Y1 - 2022/9/18

N2 - Industrial robots are widely used in modern factories. Robot faults and abnormal working state will lead to the shutdown of the production line inevitably. Robot condition monitoring can improve production capacity. However, due to the changes of robot in dynamic working state, this is a challenge. This paper presents a methodology of condition monitoring for industrial robots using vibration signals. The main purpose of this paper is to identify the occurrence of the fault and its different degrees. Experiments was performed on a 6-dof industrial robot (IR). Firstly, the Frequency Response Function of the IR was obtained by using the Experimental Modal Analysis method. And the characteristic frequency in each axis was found. Then, based on the Short-time Fourier Transform analysis method, the vibration data under normal conditions and different degrees of abnormal working conditions were analysed. In some characteristic frequency bands, the amplitude will increase with the increase of the binding force at the joint. Finally, this trend was further verified by the calculation of RMS value. The results show that the proposed frequency domain and model analysis method can monitor the operating condition of industrial robots.

AB - Industrial robots are widely used in modern factories. Robot faults and abnormal working state will lead to the shutdown of the production line inevitably. Robot condition monitoring can improve production capacity. However, due to the changes of robot in dynamic working state, this is a challenge. This paper presents a methodology of condition monitoring for industrial robots using vibration signals. The main purpose of this paper is to identify the occurrence of the fault and its different degrees. Experiments was performed on a 6-dof industrial robot (IR). Firstly, the Frequency Response Function of the IR was obtained by using the Experimental Modal Analysis method. And the characteristic frequency in each axis was found. Then, based on the Short-time Fourier Transform analysis method, the vibration data under normal conditions and different degrees of abnormal working conditions were analysed. In some characteristic frequency bands, the amplitude will increase with the increase of the binding force at the joint. Finally, this trend was further verified by the calculation of RMS value. The results show that the proposed frequency domain and model analysis method can monitor the operating condition of industrial robots.

KW - Condition monitoring

KW - Frequency Response

KW - Industrial robots

KW - Model analysis

KW - Vibration analysis

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UR - https://link.springer.com/book/10.1007/978-3-030-99075-6

U2 - 10.1007/978-3-030-99075-6_71

DO - 10.1007/978-3-030-99075-6_71

M3 - Conference contribution

AN - SCOPUS:85138769177

SN - 9783030990749

VL - 117

T3 - Mechanisms and Machine Science

SP - 879

EP - 891

BT - Proceedings of IncoME-VI and TEPEN 2021

A2 - Zhang, Hao

A2 - Feng, Guojin

A2 - Wang, Hongjun

A2 - Gu, Fengshou

A2 - Sinha, Jyoti K.

PB - Springer, Cham

T2 - 6th International Conference on Maintenance Engineering, IncoME-VI and the Conference of the Efficiency and Performance Engineering Network, TEPEN 2021

Y2 - 20 October 2021 through 23 October 2021

ER -

Han H, Shi D, Gu L, Wei N, Gu F. Modelling and Vibration Signal Analysis for Condition Monitoring of Industrial Robots. In Zhang H, Feng G, Wang H, Gu F, Sinha JK, editors, Proceedings of IncoME-VI and TEPEN 2021 : Performance Engineering and Maintenance Engineering. Vol. 117. Springer, Cham. 2022. p. 879-891. (Mechanisms and Machine Science). Epub 2022 Sep 18. doi: 10.1007/978-3-030-99075-6_71

Modelling and Vibration Signal Analysis for Condition Monitoring of Industrial Robots

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