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Research progress of rolling bearing life and reliability application
发布时间:2021-07-29浏览次数:6

Rolling bearing is one of the key components to determine the mechanical health state and life. The research on bearing life and health state has the characteristics of many influencing factors, large life dispersion, time-consuming test, difficult data accumulation, difficult theoretical modeling and so on. With the accumulation of data during processing, manufacturing and operation, the development and popularization of Internet of things, cloud computing, intelligent algorithms and other technologies, the production environment has gradually established the foundation of big data environment. On this basis, the bearing health management and life prediction can enable the bearing to realize mutual comparison with its own state, accumulation of data and empirical models, and collaborative fault diagnosis, And then become an intelligent system with the ability of self-learning and self-growth. In such a system, the bearing system is no longer an independent individual. The prognosis of all equipment in the whole manufacturing and operation system is analyzed through the information network system, so that the control and decision-making end can see the state and operation capacity of the bearing. At present, each type of bearing is managed by its professional sensors and analysis equipment, and there is no unified platform to integrate the common features of bearing fault and its corresponding general and reconfigurable algorithm. On the other hand, although sensors and analyzers can complete basic monitoring and prediction tasks, they can not adapt well to the mining of root causes of faults, high response prediction methods, large-scale equipment clusters and cooperative management of multiple bearings. It will face harsh requirements in bearing health monitoring and life prediction. Therefore, this paper will introduce the achievements of bearing big data health monitoring and life prediction in detail, and look forward to its development direction.

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