Industrial robot rotate vector reducer fault detection based on hidden markov models

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	Industrial robot rotate vector reducer fault detection based on hidden markov models
	Zhang YL(张吟龙)2,3,4; An HB(安海博)3,4,5,6; Ding XJ(丁小健)1; Liang W(梁炜)3,4,5,6; Yuan MZ(苑明哲)2,3,4; Ji CY(季春阳)5; Tan JD(谈金东)7
	2019
会议日期	December 6-8, 2019
会议地点	Dali, China
其他题名	Industrial robot rotate vector reducer fault detection based on hidden markov models.pdf
页码	3013-3018
英文摘要	Reliable fault detection of rotate vector (RV) reducer is of paramount importance for the long-term maintenance of high-precision industrial robots. This paper proposes a Hidden Markov Model (HMM) based RV reducer fault detection using Acoustic Emission (AE) measurements. Compared with the conventional faults from the common rotating machinery (such as bearings and gears), the fault from the RV reducer is more complicated and undetectable due to its inherent inline and two-stage meshing structure. To this end, this work modifies the HMM model by taking into account not only the current observations and previous states, but also the subsequent series of observations within the posteriori probability framework. Through this way, the random and unknown disturbance, which is common in the industrial scenarios, could be reduced. Besides, the HMM is also applied to separate the AE signal bulks within one cycle that has 39 subcycles, which is a critical step for AE signal pre-processings. The proposed method has been evaluated on our collected AE signal dataset from the RV reducer in the industrial robotic platform. The experimental results and analysis validate that the proposed HMM based RV Reducer fault detection model can reliably and accurately detect reducer faults.
产权排序	1
会议录	IEEE International Conference on Robotics and Biomimetics, ROBIO 2019
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-7281-6321-5
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/26283]
专题	沈阳自动化研究所_工业控制网络与系统研究室
通讯作者	An HB(安海博); Liang W(梁炜)
作者单位	1.Fifth Electronic Instituteof MIIT, Guangzhou 510610, China 2.Shenyang Institute of Automation, Guangzhou, Chinese Academy of Sciences, Guangzhou 511548, China 3.Key Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 5.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 6.University of Chinese Academy of Sciences, Beijing 100049, China 7.Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Konxville, TN 37996, United States
推荐引用方式 GB/T 7714	Zhang YL,An HB,Ding XJ,et al. Industrial robot rotate vector reducer fault detection based on hidden markov models[C]. 见:. Dali, China. December 6-8, 2019.