To decrease breakdown time and improve machine operation reliability,accurate residual useful life(RUL) prediction has been playing a critical role in condition based monitoring.A data fusion method was proposed to ac...To decrease breakdown time and improve machine operation reliability,accurate residual useful life(RUL) prediction has been playing a critical role in condition based monitoring.A data fusion method was proposed to achieve online RUL prediction of slewing bearings,which consisted of a reliability based RUL prediction model and a data driven failure rate(FR) estimation model.Firstly,an RUL prediction model was developed based on modified Weibull distribution to build the relationship between RUL and FR.Secondly,principal component analysis(PCA) was introduced to process multi-dimensional life-cycle vibration signals,and continuous squared prediction error(CSPE) and its time-domain features were employed as equipment performance degradation features.Afterwards,an FR estimation model was established on basis of the degradation features and relevant FRs using simplified fuzzy adaptive resonance theory map(SFAM) neural network.Consequently,real-time FR of equipment can be obtained through FR estimation model,and then accurate RUL can be calculated through the RUL prediction model.Results of a slewing bearing life test show that CSPE is an effective indicator of performance degradation process of slewing bearings,and that by combining actual load condition and real-time monitored data,the calculation time is reduced by 87.3%and the accuracy is increased by 0.11%,which provides a potential for online RUL prediction of slewing bearings and other various machineries.展开更多
As semiconductor technologies have been shrinking,the speed of circuits,integration density,and the number of I/O interfaces have been significantly increasing.As a consequence,electromagnetic emanation(EME)becomes a ...As semiconductor technologies have been shrinking,the speed of circuits,integration density,and the number of I/O interfaces have been significantly increasing.As a consequence,electromagnetic emanation(EME)becomes a critical issue in digital system designs.Electronic devices must meet electromagnetic compatibility(EMC)requirements to ensure that they operate properly,and safely without interference.I/O buffers consume high currents when they operate.The bonding wires,and lead frames are long enough to play as efficient antennas to radiate electromagnetic interference(EMI).Therefore,I/O switching activities significantly contribute to the EMI.In this paper,we evaluate and analyze the impact of I/O switching activities on the EME.We will change the circuit configurations such as the supply voltage for I/O banks,their switching frequency,driving current,and slew rate.Additionally,a trade-off between the switching frequencies and the number of simultaneous switching outputs(SSOs)is also considered in terms of EME.Moreover,we evaluate the electromagnetic emissions that are associated with the different I/O switching patterns.The results show that the electromagnetic emissions associated I/O switching activities depend strongly on their operating parameters and configurations.All the circuit implementations and measurements are carried out on a Xilinx Spartan-3 FPGA.展开更多
基金Projects(51375222,51175242)supported by the National Natural Science Foundation of China
文摘To decrease breakdown time and improve machine operation reliability,accurate residual useful life(RUL) prediction has been playing a critical role in condition based monitoring.A data fusion method was proposed to achieve online RUL prediction of slewing bearings,which consisted of a reliability based RUL prediction model and a data driven failure rate(FR) estimation model.Firstly,an RUL prediction model was developed based on modified Weibull distribution to build the relationship between RUL and FR.Secondly,principal component analysis(PCA) was introduced to process multi-dimensional life-cycle vibration signals,and continuous squared prediction error(CSPE) and its time-domain features were employed as equipment performance degradation features.Afterwards,an FR estimation model was established on basis of the degradation features and relevant FRs using simplified fuzzy adaptive resonance theory map(SFAM) neural network.Consequently,real-time FR of equipment can be obtained through FR estimation model,and then accurate RUL can be calculated through the RUL prediction model.Results of a slewing bearing life test show that CSPE is an effective indicator of performance degradation process of slewing bearings,and that by combining actual load condition and real-time monitored data,the calculation time is reduced by 87.3%and the accuracy is increased by 0.11%,which provides a potential for online RUL prediction of slewing bearings and other various machineries.
基金Project(2018R1D1A1B07043399)supported by Basic Science Research Program through the National Research Foundation,Korea
文摘As semiconductor technologies have been shrinking,the speed of circuits,integration density,and the number of I/O interfaces have been significantly increasing.As a consequence,electromagnetic emanation(EME)becomes a critical issue in digital system designs.Electronic devices must meet electromagnetic compatibility(EMC)requirements to ensure that they operate properly,and safely without interference.I/O buffers consume high currents when they operate.The bonding wires,and lead frames are long enough to play as efficient antennas to radiate electromagnetic interference(EMI).Therefore,I/O switching activities significantly contribute to the EMI.In this paper,we evaluate and analyze the impact of I/O switching activities on the EME.We will change the circuit configurations such as the supply voltage for I/O banks,their switching frequency,driving current,and slew rate.Additionally,a trade-off between the switching frequencies and the number of simultaneous switching outputs(SSOs)is also considered in terms of EME.Moreover,we evaluate the electromagnetic emissions that are associated with the different I/O switching patterns.The results show that the electromagnetic emissions associated I/O switching activities depend strongly on their operating parameters and configurations.All the circuit implementations and measurements are carried out on a Xilinx Spartan-3 FPGA.
