Research On The Key Technologies Of Smart Bearing Based On The Embedded Sensor

As a key component in machinery, bearing's working condition directly affect the reliability and security of machinery systems, so bearing monitoring is one effective way to avoid disastrous incidents caused by faults in bearing. In recent years,"smart bearing"based on the embedded sensor has been studied as one kind of bearing with the capability of on-line monitoring by itself. Smart bearing is obtained by integrating micro-sensors and microprocessors into a traditional bearing and all of them form one unique structural unit. In this way, smart bearings itself can capture the fault symptoms and it can be used for on-line monitoring.In this paper, taking the rolling bearing as an object, the key technologies on smart bearing are studied, which include the structural analysis of finite element model, designing micro-sensor and wireless signal transmission. The detailed contents and innovative work can be summarized as follows:1. To testify the affect of slot on the carrying capacity of bearing, the structural analysis of bearing with a slot is needed. At first, the load model of bearing is presented based on the theory of Stribeck and Hertz-contact. Then the simplified finite element model of the bearing is established and analyzed. According to simulation results, main factors on the carrying capacity of bearing are obtained and it provides the basis for structure design of smart bearing.2. To sample and transmit the condition signal of the bearing with a micro-sensing and micro-processing unit, a micro-sensor model is needed to be designed. First, the whole scheme is proposed; then the components are selected based on the requirements of functions, miniature volume and low power consumption and a MEMS sensor (LIS3l02AL) and a wireless transmit chip (nRF24E1) are used. At last the micro-sensor model is realized.3. The software of micro-sensor model is designed, which includes wireless signal transmission and receiving. In the part of signal transmission, A/D sampling, signal preprocessing and wireless signal transmissions are realized. In the part of signal receiving, wireless signal receiving, process and serial communication with PC are realized.4. To evaluate the performance of the micro-sensor model in sampling condition signals of bearing, at first the experimental set-up is designed. Secondly the whole experimental scheme is proposed, including simulating the inner-race bearing fault, choosing measurement points and sampling the condition signals. Then both the original signals under fault condition and one-order energy spectrum of Hilbert-Huang Transform are compared respectively and the results demonstrate that it is more able to capture the fault symptoms of bearing using embedded micro-sensor model than traditional sensors.