Abstract
Bearing condition monitoring has become a key component in maintaining healthy operation of high-speed rotating and reciprocating machinery. The traditional fault diagnosis objects mostly focus on single-parameter measurements, which may lead to misdiagnosis. Due to the influence of background noise, it is difficult to extract and identify bearing fault signals in time. To tackle this problem, this paper proposes an external intelligent bearing system with three parameter monitoring capabilities. First, in order to accurately measure the bearing speed information in real time, Ansoft is used to perform electromagnetic simulation of the Hall sensor. Second, the finite-element software Simdroid is used to simulate the bearing structure, and the bearing is processed through the simulation results. Third, three sensors are combined to design and develop the program and display interface, which can display the monitored data in real time. Finally, the designed intelligent bearing system is manufactured to run on a bearing life testing machine; by comparing the data measured with traditional monitoring methods, the superiority of the intelligent bearing system in condition monitoring is verified. This work can provide a novel way for the research on multiparameter bearing condition monitoring.
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