The nonlinear properties of rotating machinery vibration signals are presented. The relationship between faults and quadratic phase coupling is discussed. The mechanism that gives rise to quadratic phase coupling is a...The nonlinear properties of rotating machinery vibration signals are presented. The relationship between faults and quadratic phase coupling is discussed. The mechanism that gives rise to quadratic phase coupling is analyzed, and the coupling models are summarized. As a result, higher order spectra analysis is introduced into fault diagnosis of rotors. A brief review of the properties of higher order spectra is presented. Furthermore, the bicoherence spectrum is employed to extract the features that signify the machinery condition. Experiments show that bicoherence spectrum patterns of different faults are quite different, so it is proposed to identify the faults in rotors.展开更多
Epilepsy is the most common neuropathology. Statistical studies related to the disease reported that 20% - 25% of epileptic patients with occurrence of seizures were even under treatment with drugs. This article prese...Epilepsy is the most common neuropathology. Statistical studies related to the disease reported that 20% - 25% of epileptic patients with occurrence of seizures were even under treatment with drugs. This article presents a strategy for improved detection of the neuropathology, based on electroencephalogram (EEG), using a classifier built with support vector machines (SVC). The SVC is designed based on feature extraction of higher order spectra of time series derived from the EEG applied to epileptic patients and control patients. As demonstrated in the study presented, the EEG time series are highly nonlinear and non-Gaussian, therefore, exhibit higher order spectra, which are extracted features that improve the accuracy in the performance of SVC. The results of this study suggest the development of highly accurate computational tools for the diagnosis of this dreaded neuropathology.展开更多
On the basis of an introduction of the Wigner Higher-Order spectra (WHOS) and a general class of time-frequency higher-order moment spectra, the geophysical signal was analyzed using the higher order time-frequency di...On the basis of an introduction of the Wigner Higher-Order spectra (WHOS) and a general class of time-frequency higher-order moment spectra, the geophysical signal was analyzed using the higher order time-frequency distributions (TFD). Simulation results obtained in this paper show that the higher-order TFD (Wigner Bispectrum, Wigner Trispectrum and Choi-Williams Trispectrum) have much better Time-Frequency Concentration than the second-order TFD, and the reduced interference higher-order TFD such as CWT can effectively reduce the cross-term in multicomponent signals and simultaneously obtain high time-frequency concentration.展开更多
This paper addresses the problem of adaptively estimating the consistent parameters for non Gaussian nonminimum MA processes with symmetric PDF using the fourth order cumulant of the underlying processes. The process...This paper addresses the problem of adaptively estimating the consistent parameters for non Gaussian nonminimum MA processes with symmetric PDF using the fourth order cumulant of the underlying processes. The processes may be corrupted by additive noise.展开更多
文摘The nonlinear properties of rotating machinery vibration signals are presented. The relationship between faults and quadratic phase coupling is discussed. The mechanism that gives rise to quadratic phase coupling is analyzed, and the coupling models are summarized. As a result, higher order spectra analysis is introduced into fault diagnosis of rotors. A brief review of the properties of higher order spectra is presented. Furthermore, the bicoherence spectrum is employed to extract the features that signify the machinery condition. Experiments show that bicoherence spectrum patterns of different faults are quite different, so it is proposed to identify the faults in rotors.
文摘Epilepsy is the most common neuropathology. Statistical studies related to the disease reported that 20% - 25% of epileptic patients with occurrence of seizures were even under treatment with drugs. This article presents a strategy for improved detection of the neuropathology, based on electroencephalogram (EEG), using a classifier built with support vector machines (SVC). The SVC is designed based on feature extraction of higher order spectra of time series derived from the EEG applied to epileptic patients and control patients. As demonstrated in the study presented, the EEG time series are highly nonlinear and non-Gaussian, therefore, exhibit higher order spectra, which are extracted features that improve the accuracy in the performance of SVC. The results of this study suggest the development of highly accurate computational tools for the diagnosis of this dreaded neuropathology.
基金Supported by the National Natural Science Foundation of China( 4 990 40 10 )
文摘On the basis of an introduction of the Wigner Higher-Order spectra (WHOS) and a general class of time-frequency higher-order moment spectra, the geophysical signal was analyzed using the higher order time-frequency distributions (TFD). Simulation results obtained in this paper show that the higher-order TFD (Wigner Bispectrum, Wigner Trispectrum and Choi-Williams Trispectrum) have much better Time-Frequency Concentration than the second-order TFD, and the reduced interference higher-order TFD such as CWT can effectively reduce the cross-term in multicomponent signals and simultaneously obtain high time-frequency concentration.
文摘This paper addresses the problem of adaptively estimating the consistent parameters for non Gaussian nonminimum MA processes with symmetric PDF using the fourth order cumulant of the underlying processes. The processes may be corrupted by additive noise.
