Fault Feature Extraction of Rotating Machinery Based on Wavelet Transformation and Multi-resolution Analysis

This paper expounded in detail the principle of energy spectrum analysis based on discrete wavelet transformation and multiresolution analysis. In the aspect of feature extraction method study, with investigating the feature of impact factor in vibration signals and considering the non-placidity and non-linear of vibration diagnosis signals, the authors import wavelet analysis and fractal theory as the tools of faulty signal feature description. Experimental results proved the validity of this method. To some extent, this method provides a good approach of resolving the wholesome problem of fault feature symptom description.

Application of multi-resolution analysis in sonar image denoising

Sonar images have complex background, low contrast, and deteriorative edges; these characteristics make it difficult for researchers to dispose the sonar objects. The multi-resolution analysis represents the signals in different scales efficiently, which is widely used in image processing. Wavelets are successful in disposing point discontinuities in one dimension, but not in two dimensions. The finite Ridgelet transform （FRIT） deals efficiently with the singularity in high dimension. It presents three improved denoising approaches, which are based on FRIT and used in the sonar image disposal technique. By experiment and comparison with traditional methods, these approaches not only suppress the artifacts, but also obtain good effect in edge keeping and SNR of the sonar image denoising.

MULTI-RESOLUTION MOTION ESTIMATION AND COMPENSATION BASED ON ADJACENT PREDICTION OF FRAME DIFFERENCE IN WAVELET DOMAIN

Aiming at the higher bit-rate occupation of motion vector encoding and more time load of full-searching strategies, a multi-resolution motion estimation and compensation algorithm based on adjacent prediction of frame difference was proposed.Differential motion detection was employed to image sequences and proper threshold was adopted to identify the connected region.Then the motion region was extracted to carry out motion estimation and motion compensation on it.The experiment results show that the encoding efficiency of motion vector is promoted, the complexity of motion estimation is reduced and the quality of the reconstruction image at the same bit-rate as Multi-Resolution Motion Estimation(MRME) is improved.

Online Test and Fault Diagnosis of Yarn Quality Using Wavelet Analysis and FFT

A new online system of monitoring yarn quality and fault diagnosis is presented. This system integrates the technologies of sensor, signal process, communication, network, computer, control, instrument structure and mass knowledge of experts. Comparing with conventional off-line yarn test, the new system can find the quality defects of yarn online in time and compensate for the lack of expert knowledge in manual analysis. It can save a lot of yarn wasted in off-line test and improve product quality. By using laser sensor to sample the diameter signal of yarn and doing wavelet analysis and FFT to extract fault characteristics, a set of reasoning mechanism is established to analyze yarn quality and locate the fault origination. The experimental results show that new system can do well in monitoring yarn quality online comparing with conventional off-line yarn test. It can test the quality of yarn in real-time with high efficiency and analyze the fault reason accurately. It is very useful to apply this new system to upgrade yarn quality in cotton textile industry at present.

Conformal Wavelet Finite-difference Time-domain Algorithm for Analysis of Milimeter Wave Attenuation on Coplanar Waveguide

Addressed is the calculation of millimeter wave attenuation on coplanar waveguide(CPW). A novel conformal wavelet finite-difference time-domain(CWFDTD) algorithm is proposed with emphasis on its application in calculation of millimeter wave attenuation on CPW, which is the combination of conformal algorithm dealing with the deformed cell with Wavelet-FDTD using multi-resolution analysis(MRA). Derived is the difference formulation for multi-resolution time domain(MRTD) based on Daubechies wavelets, and also given is the stability conditions for wavelet-FDTD algorithm. To validate its accuracy and efficiency, this novel method is applied to calculate the millimeter wave attenuation on lithium niobate CPW. Numerical results demonstrate that this new CWFDTD algorithm has the same accuracy with the conformal finite-difference time-domain(CFDTD) and conformal finite-difference time-domain based on alternating-direction implicit method(ADI-CFDTD), but saves computational time and computer memory.

Wavelet Transform for Image Compression Using Multi-Resolution Analytics: Application to Wireless Sensors Data

The aggregation of data in recent years has been expanding at an exponential rate. There are various data generating sources that are responsible for such a tremendous data growth rate. Some of the data origins include data from the various social media, footages from video cameras, wireless and wired sensor network measurements, data from the stock markets and other financial transaction data, supermarket transaction data and so on. The aforementioned data may be high dimensional and big in Volume, Value, Velocity, Variety, and Veracity. Hence one of the crucial challenges is the storage, processing and extraction of relevant information from the data. In the special case of image data, the technique of image compressions may be employed in reducing the dimension and volume of the data to ensure it is convenient for processing and analysis. In this work, we examine a proof-of-concept multiresolution analytics that uses wavelet transforms, that is one popular mathematical and analytical framework employed in signal processing and representations, and we study its applications to the area of compressing image data in wireless sensor networks. The proposed approach consists of the applications of wavelet transforms, threshold detections, quantization data encoding and ultimately apply the inverse transforms. The work specifically focuses on multi-resolution analysis with wavelet transforms by comparing 3 wavelets at the 5 decomposition levels. Simulation results are provided to demonstrate the effectiveness of the methodology.

NEW TECHNOLOGY FOR FAULT DIAGNOSIS BASED ON WAVELET DENOISING AND MODIFIED EXPONENTIAL TIME-FREQUENCY DISTRIBUTION

Fast wavelet multi-resolution analysis (wavelet MRA) provides a effective tool for analyzing and canceling disturbing components in original signal. Because of its exponential frequency axis, this method isn't suitable for extracting harmonic components. The modified exponential time-frequency distribution ( MED) overcomes the problems of Wigner distribution( WD) ,can suppress cross-terms and cancel noise further more. MED provides high resolution in both time and frequency domains, so it can make out weak period impulse components fmm signal with mighty harmonic components. According to the 'time' behavior, together with 'frequency' behavior in one figure,the essential structure of a signal is revealed clearly. According to the analysis of algorithm and fault diagnosis example, the joint of wavelet MRA and MED is a powerful tool for fault diagnosis.

Multi-Focus Image Fusion Based on Wavelet Transformation

In the fusion of image,how to measure the local character and clarity is called activity measurement. According to the problem,the traditional measurement is decided only by the high-frequency detail coefficients, which will make the energy expression insufficient to reflect the local clarity. Therefore,in this paper,a novel construction method for activity measurement is proposed. Firstly,it uses the wavelet decomposition for the fusion resource image, and then utilizes the high and low frequency wavelet coefficients synthetically. Meantime,it takes the normalized variance as the weight of high-frequency energy. Secondly,it calculates the measurement by the weighted energy,which can be used to measure the local character. Finally,the fusion coefficients can be got. In order to illustrate the superiority of this new method,three kinds of assessing indicators are provided. The experiment results show that,comparing with the traditional methods,this new method weakens the fuzzy and promotes the indicator value. Therefore,it has much more advantages for practical application.

Intelligently Tuned Wavelet Parameters for GPS/INS Error Estimation

This paper presents a new algorithm for de-noising global positioning system （GPS） and inertial navigation system （INS） data and estimates the INS error using wavelet multi-resolution analysis algorithm （WMRA）-based genetic algorithm （GA） with a well-designed structure appropriate for practical and real time implementations because of its very short training time and elevated accuracy. Different techniques have been implemented to de-noise and estimate the INS and GPS errors. Wavelet de-noising is one of the most exploited techniques that have been recently used to increase the precision and reliability of the integrated GPS/INS navigation system. To ameliorate the WMRA algorithm, GA was exploited to optimize the wavelet parameters so as to determine the best wavelet filter, thresholding selection rule （TSR）, and the optimum level of decomposition （LOD）. This results in increasing the robustness of the WMRA algorithm to estimate the INS error. The proposed intelligent technique has overcome the drawbacks of the tedious selection for WMRA algorithm parameters. Finally, the proposed method improved the stability and reliability of the estimated INS error using real field test data.

The research on relationship between wavelet transform on vertical deformation and moderate earthquakes in Hexi region,Gansu Province

n this paper, the possibility of wavelet transform applied to compute the vertical deformation is discussed. Both two dimension plane equation of wavelet transform and B-wavelet based on basic spline function are deduced. According to the equation and B-wavelet, multi-periods vertical deformation data which were measured from 1971 to 1995 in Hexi-Qilian Mountain region, Gansu Province are calculated. The results are: ① The multi-resolution analysis of wavelet transform can filter the different spatial wavelength in vertical deformation information on different scales effectively and let us to see the heterogeneous in distribution of vertical deformation clearly, therefore, it is an important tool in investigating the relationship between the vertical deformation and the seismicity; ② The main variation of both the first and second results in wavelet transform mainly takes place along the main faults which explains that the short wave variation of vertical deformation is caused by the faults activities; ③ The wavelet transform of vertical deformation in Hexi-Qilian Mountain area shows that the vertical deformation in southeast parts of Hexi region was larger than that in other parts and there were several moderate earthquakes such as Menyuan Ms=6.4 earthquake in 1986, Jingtai Ms=6.2 earthquake in 1990, Yongdeng Ms=5.8 earthquake in 1995. The vertical deformation in the northwest part of the region was not so large as that in southeast part where ware no strong earthquakes.

POINTWISE CONVERGENCE OF THE WAVELET SOLUTION TO THE PARABOLIC EQUATION WITH VARIABLE COEFFICIENTS

We consider the parabolic equation with variable coefficients k（x）Uxx = ut, 0,x ≤1, t≥ 0, where 0 〈 α ≤ k（x） 〈 ＋∞, the solution on the boundary x = 0 is a given function g and ux（0,t） = 0. We use wavelet Galerkin method with Meyer multi-resolution analysis to obtain a wavelet approximating solution, and also get an estimate between the exact solution and the wavelet approximating solution of the problem.

Extraction of MHD Signal Based on Wavelet Transform

Mirnov signals mixed with interferences are a kind of non-stationary signal. It cannot obtain satisfactory effects to extract MHD signals from mirnov signals by Fourier Transform. This paper suggests that the wavelet transform can be used to treat mirnov signals. Theoretical analysis and experimental result have indicated that using the time-frequency analysis characteristics of the wavelet transform to filter mirnov signals can remove effectively interferences and extract useful MHD signals.

Wavelets as Basis Functions in the Adaptation＇s Methods： Author＇s Model for Forecasting Short-Term

The aim of this article is to present author＇s application of wavelets to predict short-term macroeconomic indicators Proposed to predict short-term time series （in particular for predicting macroeconomic indicators）, proprietary model is based on wavelet analysis with Haar wavelets, Daubechies wavelets, and adaptive models; they are the trend crawling model and alignment exponential model. Adaptive models have been modified through the introduction of wavelet function and combined into a single forecast model. Obtained from conducted research results, it shows the model an effective instrument to predict the short-term.

Novel Adaptive Beamforming Algorithm Based on Wavelet Packet Transform

An analysis of the received signal of array antennas shows that the received signal has multi-resolution characteristics, and hence the wavelet packet theory can be used to detect the signal. By emplying wavelet packet theory to adaptive beamforming, a wavelet packet transform-based adaptive beamforming algorithm (WP-ABF) is proposed . This WP-ABF algorithm uses wavelet packet transform as the preprocessing, and the wavelet packet transformed signal uses least mean square algorithm to implement the ~adaptive beamforming. White noise can be wiped off under wavelet packet transform according to the different characteristics of signal and white under the wavelet packet transform. Theoretical analysis and simulations demonstrate that the proposed WP-ABF algorithm converges faster than the conventional adaptive beamforming algorithm and the wavelet transform-based beamforming algorithm. Simulation results also reveal that the convergence of the algorithm relates closely to the wavelet base and series; that is, the algorithm convergence gets better with the increasing of series, and for the same series of wavelet base the convergence gets better with the increasing of regularity.

A Quotient Space Approximation Model of Multiresolution Signal Analysis

In this paper, we present a quotient space approximation model of multiresolution signal analysis and discuss the properties and characteristics of the model. Then the comparison between wavelet transform and the quotient space approximation is made. First, when wavelet transform is viewed from the new quotient space approximation perspective, it may help us to gain an insight into the essence of multiresolution signal analysis. Second, from the similarity between wavelet and quotient space approximations, it is possible to transfer the rich wavelet techniques into the latter so that a new way for multiresolution analysis may be found.

多分辨率小波分析在GIS线状要素简化中的应用

线要素化简一直是自动制图综合中的重要研究内容。利用小波分析的多分辨率原理和Douglas算法,对线状要素进行平滑和综合,实现了线状要素的空间多尺度表达。并对实际数据进行实验,结果表明,此方法不仅能够达到曲线化简的目的,而且能够保持化简前后的视觉效果和原始数据的特征。

A Kind of Edge Detection Algorithm with Edge-Preserving Characteristics

Traditional Sobel algorithm is deeply influenced by Gaussian noise,therefore,before boundary extraction,mean filter should be done. But the filtering process is always over-smooth images'details of certain directions,so that images'edges will not be extracted correctly. Aiming at this problem,this paper puts forward a detection algorithm based on edge-preserving characteristics,by matching edge mould of different directions to definite edge preserving directions. Instead of the mean filter process,this algorithm improves the performance of traditional algorithms,and provides the simulation results. The experiment results prove that this algorithm preserves more images'edge information when canceling noise.

A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting

Short-term water demand forecasting provides guidance on real-time water allocation in the water supply network, which help water utilities reduce energy cost and avoid potential accidents. Although a variety of methods have been proposed to improve forecast accuracy, it is still difficult for statistical models to learn the periodic patterns due to the chaotic nature of the water demand data with high temporal resolution. To overcome this issue from the perspective of improving data predictability, we proposed a hybrid Wavelet-CNN-LSTM model, that combines time-frequency decomposition characteristics of Wavelet Multi-Resolution Analysis (MRA) and implement it into an advanced deep learning model, CNN-LSTM. Four models - ANN, Conv1D, LSTM, GRUN - are used to compare with Wavelet-CNN-LSTM, and the results show that Wavelet-CNN-LSTM outperforms the other models both in single-step and multi-steps prediction. Besides, further mechanistic analysis revealed that MRA produce significant effect on improving model accuracy.

Effective Ultra-High-Speed Identification Scheme of Lightning Strikes Suitable for VSC-Based DC Grids

To ensure their sound and continuous operation to the greatest extent,VSC-based DC girds have extremely stringent requirements for transmission line relay protection.In terms of guaranteeing their reliability,accurate identification of lightning strikes on DC transmission lines is one of the urgent key problems to be solved.An effective ultra-high-speed identification scheme of lightning strikes suitable for the VSC-based DC grid is proposed in this paper.First,an 1-mode reverse voltage traveling wave(RVTW)is constructed applying the pole-mode transformation theory.Next,fault traveling wave propagation characteristics along the DC transmission line are analyzed in depth utilizing Peterson's law.Then,differences of time-frequency electromagnetic transient characteristics of 1-mode RVTWs between disturbances and faults caused by lightning strikes are distinguished in detail by means of the classical wavelet transformation multi-resolution analysis theory.Finally,extensive simulations are carried out to evaluate the performance of the proposed identification scheme,and by which its excellent rapidity,reliability and robustness are validated.Index Terms-Lightning-strike identification,Multi-resolution analysis,Relay protection,Traveling-wave protection,VsC-based DC grid,Wavelet transformation.

Minimum-energy wavelet frame on the interval

The construction and properties of interval minimum-energy wavelet frame are systematically studied in this paper. They are as follows： 1） give the definition of interval minimum-energy wavelet frame; 2） give the necessary and sufficient conditions for the minimum-energy frames for L^2[0,1]; 3） present the construction algorithm for minimum-energy wavelet frame associated with refinable functions on the interval with any support y; 4） give the decomposition and reconstruction formulas of the minimum-energy frame on the interval [0,1],