Vibration acceleration signals are often measured from case surface of arunning machine to monitor its condition. If the measured vibration signals display to have periodicimpulse components with a certain frequency, ...Vibration acceleration signals are often measured from case surface of arunning machine to monitor its condition. If the measured vibration signals display to have periodicimpulse components with a certain frequency, there may exist a corresponding local fault in themachine, and if further extracting the periodic impulse components from the vibration signals, theseverity of the local fault can be estimated and tracked. However, the signal-to-noise ratios (SNRs)of the vibration acceleration signals are often so small that the periodic impulse components aresubmersed in much background noises and other components, and it is difficult or inconvenient for usto detect and extract the periodic impulse components with the current common analyzing methods forvibration signals. Therefore, another technique, called singular value decomposition (SVD), istried to be introduced to solve the problem. First, the principle of detecting and extracting thesignal periodic components using singular value decomposition is summarized and discussed. Second,the infeasibility of the direct use of the existing SVD based detecting and extracting approach ispointed out. Third, the approach to construct the matrix for SVD from the signal series is improvedlargely, which is the key program to improve the SVD technique; Other associated improvement is alsoproposed. Finally, a simulating application example and a real-life application example ondetecting and extracting the periodic impulse components are given, which showed that the introducedand improved SVD technique is feasible.展开更多
Ventricular fibrillation (VF) caused by myo-cardial ischemia is one of the leading factors of death attrib-uted to cardiovascular diseases. It is particularly significantto predict VF and gain valuable time for clinic...Ventricular fibrillation (VF) caused by myo-cardial ischemia is one of the leading factors of death attrib-uted to cardiovascular diseases. It is particularly significantto predict VF and gain valuable time for clinic therapy. Five dogs are taken as the research objects and a VF model is introduced. The nonlinear characteristics of the ECGs before and after VF are investigated with nonlinear multi-parame-ter analysis methods, Gaussian kernel (GK) correlation es-timation algorithm and Lyapunov exponent estimation algo-rithm. Correlation entropy h2 is also presented. The results indicate that there are three parameters which will change at the same time with the conditions of myocardial ischemia,and any changes of a single parameter may be caused byother factors and mislead the judgment. Multi-parameter analysis is more reliable to reveal the heart conditions, and to predict VF without misjudgments.展开更多
Mesa-structured intrinsic Josephson junctionsare fabricated in Bi2Sr2CaCu2O8+x single crystals. Typicalcurrent-voltage characteristics of intrinsic Josephson junc-tions are observed, which include multiple quasi-parti...Mesa-structured intrinsic Josephson junctionsare fabricated in Bi2Sr2CaCu2O8+x single crystals. Typicalcurrent-voltage characteristics of intrinsic Josephson junc-tions are observed, which include multiple quasi-particle branches, surface junction with critical current lower than those of inner junctions, and subgap structures on quasi-particle branches. The corresponding physical explanationsare also given. The energy gap voltage of the intrinsicJosephson junctions at 30 K is about 20 mV. Besides, themeasured Ic-T relationship agrees quite well with thetheoretical computations based on -22-wavexyd supercon-ductor. Our measured dI/dV-V relationship shows theV-shaped gap structure, obviously differing from theU-shaped gap structure of the s-wave superconductor.展开更多
基金This project is supported by National Natural Science Foundation of China (No.59905011, 60275041).
文摘Vibration acceleration signals are often measured from case surface of arunning machine to monitor its condition. If the measured vibration signals display to have periodicimpulse components with a certain frequency, there may exist a corresponding local fault in themachine, and if further extracting the periodic impulse components from the vibration signals, theseverity of the local fault can be estimated and tracked. However, the signal-to-noise ratios (SNRs)of the vibration acceleration signals are often so small that the periodic impulse components aresubmersed in much background noises and other components, and it is difficult or inconvenient for usto detect and extract the periodic impulse components with the current common analyzing methods forvibration signals. Therefore, another technique, called singular value decomposition (SVD), istried to be introduced to solve the problem. First, the principle of detecting and extracting thesignal periodic components using singular value decomposition is summarized and discussed. Second,the infeasibility of the direct use of the existing SVD based detecting and extracting approach ispointed out. Third, the approach to construct the matrix for SVD from the signal series is improvedlargely, which is the key program to improve the SVD technique; Other associated improvement is alsoproposed. Finally, a simulating application example and a real-life application example ondetecting and extracting the periodic impulse components are given, which showed that the introducedand improved SVD technique is feasible.
文摘Ventricular fibrillation (VF) caused by myo-cardial ischemia is one of the leading factors of death attrib-uted to cardiovascular diseases. It is particularly significantto predict VF and gain valuable time for clinic therapy. Five dogs are taken as the research objects and a VF model is introduced. The nonlinear characteristics of the ECGs before and after VF are investigated with nonlinear multi-parame-ter analysis methods, Gaussian kernel (GK) correlation es-timation algorithm and Lyapunov exponent estimation algo-rithm. Correlation entropy h2 is also presented. The results indicate that there are three parameters which will change at the same time with the conditions of myocardial ischemia,and any changes of a single parameter may be caused byother factors and mislead the judgment. Multi-parameter analysis is more reliable to reveal the heart conditions, and to predict VF without misjudgments.
基金This work was partially done in Research Institute of Elec-trical Communication Tohoku University+1 种基金 Japan and supported by the Ministry of Science and Technology of China (Grant No. G19990646).
文摘Mesa-structured intrinsic Josephson junctionsare fabricated in Bi2Sr2CaCu2O8+x single crystals. Typicalcurrent-voltage characteristics of intrinsic Josephson junc-tions are observed, which include multiple quasi-particle branches, surface junction with critical current lower than those of inner junctions, and subgap structures on quasi-particle branches. The corresponding physical explanationsare also given. The energy gap voltage of the intrinsicJosephson junctions at 30 K is about 20 mV. Besides, themeasured Ic-T relationship agrees quite well with thetheoretical computations based on -22-wavexyd supercon-ductor. Our measured dI/dV-V relationship shows theV-shaped gap structure, obviously differing from theU-shaped gap structure of the s-wave superconductor.
