Papers by Keyword: Bispectrum

Abstract: Through researching the fault vibration signal characteristics of planetary gearbox, various forms of quadratic phase coupling phenomenon were found in the signals. Bispectrum has properties such as detecting the quadratic coupling phenomena and restraining gaussian noise signal, and it can be well used in the planetary gearbox fault diagnosis. Meanwhile, the sun gear distributed fault (gear wear) and partial fault (root crack, partial broken teeth) are simulated in the wind turbine test bench built in the laboratory. By analyzing the structure characteristics of its frequency through bispectrum, the fault of the gear is effectively diagnosed.

Abstract: Mechanical system degradation always leads to the unstable and nonlinear characteristics in the dynamic responses of the system to some extent. Conventional spectral methods based on Fourier transform have limited value in showing up fault information deviating from linearity. Higher order spectral analysis (HOSA) had been reported to be effective in providing information on nonlinear response. Bispectrum as one of higher order signal analysis tools found to be a useful tool in identifying nonlinear behavior of mechanical system due to vibration faults. This paper provides an introductory treatise of to Bispectrum, and reviews its applications in machinery vibration faults detection that includes misalignment, bearing and gear faults, and cracked shafts. The effectiveness and limitation of this technique are also reported for these faults based on published literature.

Abstract: The time delay estimation (TDE) is one of the most important techniques of characterization signal parameter. Delay parameter estimation is active in the field of signal processing. In this paper, On the basis of the basic theory method of time delay, the correlated time delay estimation, mutual-cumulants estimation and bispectrum estimation are analysed and discussed. Theoretical analysis and experimental results show that three methods is effectively used in time delay test, but higher order statistics (HOS) method can achieve the best effect. The HOS estimation method has many advantages, such as time delay estimation accuracy, high relative error small for Gaussian noise elimination ability.

Abstract: The measurement of anesthetic depth is necessary in anesthesiology. NN10 is very simple method among the RR intervals analysis methods. NN10 parameter means the numbers of above the 10 ms intervals of the normal to normal RR intervals. Bispectrum analysis is defined as 2D FFT. EEG signal reflected the non-linear peristalsis phenomena according to the change brain function. After analyzing the bispectrum of the 2 dimension, the most significant power spectrum density peaks appeared abundantly at the specific area in awakening and anesthesia state. These points are utilized to create the new index since many peaks appeared at the specific area in the frequency coordinate. The measured range of an index was 0-100. An index is 20-50 at an anesthesia, while the index is 90-60 at the awake.In this paper, the relation between NN10 parameter using ECG and bisepctrum index using EEG is observed to estimate the depth of anesthesia during anesthesia and then we estimated the utility of the anesthetic.

Abstract: Independent components analysis (ICA) with constraint of seismic wavelet estimated from bispectrum of seismic traces is combined with short time Fourier transforms (STFT) to improve the traditional frequency domain seismic deconvolution. Neglecting noise, the seismic record is changed from time domain to frequency domain with STFT in order to transform the common seismic model to the basic ICA model. By applying FastICA algorithm with constraint of seismic wavelet estimated from bispectrum of seismic traces, reflectivity series and the seismic wavelet can be produced in frequency domain and changed back to the time domain subsequently. The model and real seismic data numerical examples all show the algorithm valid.

Abstract: The paper proposed the fault diagnosis of elevator based on the autoregressive(AR) model and the support vector machine. At first, build the AR model with the processing signals. The AR coefficient was used as the input of the support vector machine, the normal condition and the fault condition were used as output. By studying and predicting of the support vector machine(SVM) can reaching automatic identification. This method has high accuracy of diagnosis while resolved the problem of lacking samples.

Abstract: Used the high order spectrum and slice analysis method, studied the elevator running vibration acceleration signals and calculated the trispectrum two dimensional slices, bispectrum and theirs diagonal slices, under different running conditions. The results show that: when the elevator normal operation the acceleration signal spectrum peaks concentration, otherwise the acceleration signal peaks dispersion; in fault condition, compared to bispectrum peaks trispectrum peaks is sharper. High order spectrum contains abundant information of different fault elevator running details. It is a suitable analysis tool for diagnosing the faults of elevator.

Abstract: Moving load could enhance damage-structural nonlinear character. High-order statistical analysis described character of non-stationary signal more exactly than traditional fourier spectrum based on second-order statistics analysis. The result of high-order spectrum analysis was two-dimensional，and spectrum entropy of different frequency can extract its intrinsic information and characters from it. Using these characters, the structural damage pattern could be recognized by neural network. The validity of this method was reviewed by a beam under moving load. When structure has damage, its state information can be extracted availably from high-order spectrum entropy of structural vibration, and it isn’t sensitive to noise. It can be used as eigenvectors of pattern recognition based on neural network.

Abstract: Compared with bispectrum, three-order cumulants have a lower computing complexity, in the experiment, features of fault signals and normal signals are fetched by 2-D wavelet in different directions, then these features are used to diagnose fault. The experiment shows, that the method can achieve satisfactory result through different selections in fault diagnosis. the results prove that the method in the experiment is necessary.

Abstract: Bispectrum produced by third order cumulant contains the asymmetric and nonlinear information of signal, which can be used to describe the nonlinear phase coupling, especially the quadratic phase coupling, has been widely applied in fault diagnosis. The features of fault signals and normal signals are fetched by 2-D wavelet in different directions, then these features are used to diagnose fault. The experiment shows that the method can achieve satisfactory result.