As the differences of sensor's precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machin...As the differences of sensor's precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn't require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor's own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.展开更多
High-k metal gate stacks are being used to suppress the gate leakage due to tunneling for sub-45 nm technology nodes.The reliability of thin dielectric films becomes a limitation to device manufacturing,especially to ...High-k metal gate stacks are being used to suppress the gate leakage due to tunneling for sub-45 nm technology nodes.The reliability of thin dielectric films becomes a limitation to device manufacturing,especially to the breakdown characteristic.In this work,a breakdown simulator based on a percolation model and the kinetic Monte Carlo method is set up,and the intrinsic relation between time to breakdown and trap generation rate R is studied by TDDB simulation.It is found that all degradation factors,such as trap generation rate time exponent m,Weibull slope β and percolation factor s,each could be expressed as a function of trap density time exponent α.Based on the percolation relation and power law lifetime projection,a temperature related trap generation model is proposed.The validity of this model is confirmed by comparing with experiment results.For other device and material conditions,the percolation relation provides a new way to study the relationship between trap generation and lifetime projection.展开更多
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2007AA04Z433)Hunan Provincial Natural Science Foundation of China (Grant No. 09JJ8005)Scientific Research Foundation of Graduate School of Beijing University of Chemical and Technology,China (Grant No. 10Me002)
文摘As the differences of sensor's precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn't require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor's own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.
基金supported by the National High Technology Research and Development Program of China(Grant No.SS2015AA010601)the National Natural Science Foundation of China(Grant Nos.61176091 and 61306129)the Opening Project of Key Laboratory of Microelectronics Devices&Integrated Technology,Institute of Micro Electronics of Chinese Academy of Sciences
文摘High-k metal gate stacks are being used to suppress the gate leakage due to tunneling for sub-45 nm technology nodes.The reliability of thin dielectric films becomes a limitation to device manufacturing,especially to the breakdown characteristic.In this work,a breakdown simulator based on a percolation model and the kinetic Monte Carlo method is set up,and the intrinsic relation between time to breakdown and trap generation rate R is studied by TDDB simulation.It is found that all degradation factors,such as trap generation rate time exponent m,Weibull slope β and percolation factor s,each could be expressed as a function of trap density time exponent α.Based on the percolation relation and power law lifetime projection,a temperature related trap generation model is proposed.The validity of this model is confirmed by comparing with experiment results.For other device and material conditions,the percolation relation provides a new way to study the relationship between trap generation and lifetime projection.
