Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of th...Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of this cycle.In this paper,the remaining useful life of the equipment is calculated using the combination of sensor information,determination of degradation state and forecasting the proposed health index.The combination of sensor information has been carried out using a new approach to determining the probabilities in the Dempster-Shafer combination rules and fuzzy c-means clustering method.Using the simulation and forecasting of extracted vibration-based health index by autoregressive Markov regime switching(ARMRS)method,final health state is determined and the remaining useful life(RUL)is estimated.In order to evaluate the model,sensor data provided by FEMTO-ST Institute have been used.展开更多
Grease life refers to the time it takes for the grease to lose its ability to keep the lubrication due to grease degradation. As grease life is generally shorter than fatigue life of bearing, the service life of greas...Grease life refers to the time it takes for the grease to lose its ability to keep the lubrication due to grease degradation. As grease life is generally shorter than fatigue life of bearing, the service life of grease-lubricated rolling bearings is often dominated by grease life. When designing a bearing systemolecular weightith grease lubrication, it is necessary to define the operating conditions limits of the bearing, for which grease life becomes a determining factor. Prolongation of grease life becomes an especially important challenge when the bearing is to be operated trader high-speed, high-temperature, and other severe conditions. Selecting a number of commercially sold greases composed of varying base oils, the author evaluated their properties and analyzed how each property affected the grease life by performing a multiple regression analysis. The optimum grease composition to best exploit each property was also examined. The results revealed among others that one would need to first determine the base oil type and then maximize ultimate bleeding while minimizing the evaporation rate.展开更多
文摘Condition assessment is one of the most significant techniques of the equipment’s health management.Also,in PHM methodology cycle,which is a developed form of CBM,condition assessment is the most important step of this cycle.In this paper,the remaining useful life of the equipment is calculated using the combination of sensor information,determination of degradation state and forecasting the proposed health index.The combination of sensor information has been carried out using a new approach to determining the probabilities in the Dempster-Shafer combination rules and fuzzy c-means clustering method.Using the simulation and forecasting of extracted vibration-based health index by autoregressive Markov regime switching(ARMRS)method,final health state is determined and the remaining useful life(RUL)is estimated.In order to evaluate the model,sensor data provided by FEMTO-ST Institute have been used.
文摘Grease life refers to the time it takes for the grease to lose its ability to keep the lubrication due to grease degradation. As grease life is generally shorter than fatigue life of bearing, the service life of grease-lubricated rolling bearings is often dominated by grease life. When designing a bearing systemolecular weightith grease lubrication, it is necessary to define the operating conditions limits of the bearing, for which grease life becomes a determining factor. Prolongation of grease life becomes an especially important challenge when the bearing is to be operated trader high-speed, high-temperature, and other severe conditions. Selecting a number of commercially sold greases composed of varying base oils, the author evaluated their properties and analyzed how each property affected the grease life by performing a multiple regression analysis. The optimum grease composition to best exploit each property was also examined. The results revealed among others that one would need to first determine the base oil type and then maximize ultimate bleeding while minimizing the evaporation rate.
