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The development of manufacturing engineer for aeroengine demands that the monitoring equipment be able to perform in good status, including vibration signal analysis and fault diagnosis. In order to acquire the decisions in accordance with experiment result, one must have a powerful tool of signal feature extraction for fault pattern recognition, which has significant effect on sampled data processing...
To solve the problem of fault diagnosis for engine, due to the complexity of the equipments and the particularity of the operating environments, generally speaking, there is no one-to-one correspondence between the characteristic parameters and status, so, the methods of diagnosis are very complicated. A novel fault diagnosis method based on empirical mode decomposition (EMD) and wavelet packet BP...
This paper brings forward a new method of detection of fabric defect, namely image distance difference arithmetic. The system permit user to set appropriate control parameter of fabric defect defection based on the type of the fabric. It can detect more than 30 kinds of common defects, which has advantages of high identification correctness and fast inspection speed. Finally, using some image processing...
Wavelet theory has been the focus of active research for twenty years, both in theory and applications. In this paper, the notion of orthogonal vector-valued multivariate wavelet packets with five-scale is proposed. A novel procedure for constructing them is developed. Their orthogonal properties are characterized by virtue finite group theory, time-frequency analysis method and matrix theory. Orthogonality...
In this article, the notion of biorthogonal two-direction compactly supported wavelet packets with a positive integer dilation factor ?? is introduced. A new approach for constructing biorthogonal two-direction wavelet packets is developed and their properties is investigated by means of time-frequency analysis method, matrix theory and operator theory. The formulas for performing iterations and decomposition...
The notion of matrix-valued multiresolution analysis of space of matrix-valued multivariate functions is proposed. An approach for constructing orthogonal matrix-valued multivariate wavelet packets is developed and their properties are discussed by means of time-frequency analysis method, matrix theory and functional analysis method. Three orthogonality formulas concerning these wavelet packets are...
Vehicles detection base on the magnetic effect is a major hot spot in the field of vehicles detection. This paper has studied and realized a wireless magneto-resistive sensor based vehicles detection system, and improved the vehicle detection algorithm. The thesis has used a testing algorithm based on iterative optimal wavelet threshold used to focus on testing whether vehicles passing by. For the...
Accurate traffic flow forecasting is the key to the development of intelligent transportation systems (ITS). However, the classical forecasting method using the support vector regression (SVR) based on RBF kernel does not support online learning and has the problems of information loss, long processing time, low robustness and so on. An effective Marr Wavelet kernel which we combine the wavelet theory...
A new double Zero-watermarking method based on frequency domain is proposed in this paper. It uses the main message of an image to construct the watermark, hence keep the best invisibility. In the method, DCT and DWT are applied to enhance the quality for resisting attacks. It solves the problem that one type of watermarks can not detect all the attacks and increases the safety by encrypting a chaotic...
This paper proposes a new method for load forecasting - the wavelet neural network model for load forecasting. The neural call function is basis of nonlinear wavelets. A wavelet network is composed by the wavelet basis function. The global optimum solution is got. We overcome the intrinsic defects of a artificial neural network that its learning speed is slow, its network structure is difficult to...
In life detection radar echo signal is very weak and hard to extract. For solve this problem, weak life signal de-noising based on wavelet transform is studied. Through the studies of wavelet threshold de-noising method, the use of it in weak life signal de-noising in strong noise background, and the verification of simulation by Matlab, the results shows that wavelet threshold de-noising method can...
Traffic flow is a fundamental measure in transportation. Accurate traffic flow prediction also is crucial to the development of intelligent transportation systems and advanced traveler information systems. A novel multiscale wavelet support vector regression method (MW-SVR) is proposed for traffic flow prediction. Based on wavelet multi-resolution analysis, a scaling kernel function with multi-resolution...
A robust digital image watermarking algorithm in wavelet transform domain is proposed. In the algorithm the original gray image is decomposed into some coefficients in different spatial and frequency sub-bands. Using the characteristic that father node is associated with its child nodes, watermark is embedded in the father nodes by establishing a relationship between father node and the average value...
Motor's abnormal vibration signal includes its fault information, effective testing and analysis of its vibration signal is the key to realize motor fault diagnosis. Vibration testing and analysis system was put up to realize the acquisition, display, analysis, storage and replay of vibration signal by using NI-WLS9234 Data Acquisition Card in this paper. Call the analysis function of wavelet in MATLAB...
One of the main issues of face recognition is to decide what features to represent a face. In this paper, we present a new algorithm that extracts facial features on some fiducial points. 17 fiducial points are automatically located by Active Appearance Models (AAMs) and characterized with Gabor wavelet analysis. The features are evaluated by a face database, which includes more than 400 images of...
The Directionlet is an anisotropic multi-direction method with perfect reconstruction and critical sampling based on lattice, and it has obvious advantages in image edges. Based on analysing different EPMA image features, this paper starts extracting edges based on integral lattice, setting corresponding windows to compare mean value and standard deviation, and then begin weighted fusion based on...
Optical fiber communication signal classification is to identify modulation style of signal with much noise. wavelet transformation has a good localization characteristic in time-frequency domain, and the neural network has characteristics of self-study, self-adaptation, and high stabilization, which can improve the automatization and intelligence of recognition, so we combined the advantages of wavelet...
In this paper, a novel image denosing scheme is proposed by applying 2D dual-tree complex wavelet transform (DTCWT) to the second bandelet transform. Compared with traditional discrete wavelet transform (DWT), the DTCWT has nearly shift invariant and directionally selective in two and higher dimensions important properties, which are suitable for image denoising. The bandelet transform has offer an...
In this paper, a Legendre neural network (LNN) combined with multi-scale stationary wavelet decomposition is used to improve the prediction accuracy and parsimony of monthly anchovy catches forecasting in area north of Chile. The general idea behind this approach is to decompose the observed anchovy catches data into low frequency (LF) component and high frequency (HF) component using the multi-scale...
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