Research on industrial robot reducer state monitoring cloud platform

Tielin Lu; Zitian Fan; Xiaowen Li; Rui Cao; Shuo Wang; Xiaojing Liu; Lu Ding; Wei Wei; Zhang Bin

doi:10.1117/12.2575117

5 November 2020 Research on industrial robot reducer state monitoring cloud platform

Tielin Lu, Zitian Fan, Xiaowen Li, Rui Cao, Shuo Wang, Xiaojing Liu, Lu Ding, Wei Wei, Zhang Bin

Proceedings Volume 11565, AOPC 2020: Display Technology; Photonic MEMS, THz MEMS, and Metamaterials; and AI in Optics and Photonics; 115650E (2020) https://doi.org/10.1117/12.2575117
Event: Applied Optics and Photonics China (AOPC 2020), 2020, Beijing, China

Abstract

In this paper we proposed a method of monitoring industrial robot reducer online cloud platform. Based on the theory of cyber physical model, a cloud state monitoring system is designed due to the problems of complex objects, massive failure information, high stable demand and poor real-time control ability in the modern industrial robot maintain. It includes intelligent sensor and edge computing to network cloud technology. With data model, the system uses deep learning and over-limit learning algorithm on the cloud management center server. The deep learning method trains and predicts the collected fault data, and can predict the malfunction of vector reducer. Further, the intelligent optimization scheduling algorithm is used in the cloud to obtain real-time fault in industrial robot reducer. The problem of distribution and the dynamic running performance of cloud system is monitored and improved.

Citation Download Citation

Tielin Lu, Zitian Fan, Xiaowen Li, Rui Cao, Shuo Wang, Xiaojing Liu, Lu Ding, Wei Wei, and Zhang Bin "Research on industrial robot reducer state monitoring cloud platform", Proc. SPIE 11565, AOPC 2020: Display Technology; Photonic MEMS, THz MEMS, and Metamaterials; and AI in Optics and Photonics, 115650E (5 November 2020); https://doi.org/10.1117/12.2575117

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