Wavelet denoising method of temperature signal in the process of coal gas absorption and desorption

The study on the temperature evolutionary trend under both the ground stress and gas pressure is significant in the process of coal gas absorption and desorption. However, the valid signal is difficult to gain because of much noise in the experimental data, so according to the characteristics of the temperature signal gained under different experimental conditions of coal gas absorption and desorption, this essay filtrates noise and restores the valid signal by using the wavelet denoising of MATLAB to obtain the valid temperature evolutionary curve. Through contrasting and analyzing wavelet basis function and different decomposition levels, the essay chooses the sym8 wavelet basis function which has a higher order of vanishing moments and better smoothness. The reconstructed signal filtrates most of high frequency signal, and keep low frequency, as well as smooth signal. The result shows that the de-noising effect is good and the temperature evolution rule can be well reflected in the process of the coal gas absorption and desorption.     

Real time monitoring for multivariate statistical process with on line multiscale filtering

By analyzing shortages of current MSPCA model, an on line multi variable statistical process monitoring method is proposed, which uses some concepts from online multi scale filtering and can be applied to sensor fault diagnosis. In the method, wavelet decomposition is employed to the signals using edge correction filter in a fixed length data window, and then wavelet denoising is conducted with wavelet threshold filtering. Next, an on line multi scale model is constructed for data combining wavelet transformation and adaptive PCA in the previous data window. This model avoids time waste in direct signal denoising and reduces time cost in multi scale data with conventional PCA, which eventually increases accuracy in fault diagnosis. Experiments on eight vibration signals of 6135D diesel engine under severe leak condition prove the practicability and feasibility of the proposed method.     

A Virtual Wavelet Transform Analyzer for the Signal Analysis Based on the Direct Algorithm

A virtual wavelet transform analyzer for the signal analysis based on the direct algorithm is introduced so that the discrete wavelet transform and continuous wavelet transform is maken to signal in the direct algorithm. The authors first introduce the direct algorithm of the WT, which is numerical algorithm obtained from the original formula of the wavelet transform by directly numericalizing. Then some conclusions are drawn on the direct algorithm. The examples are the sampling principle and technology for the wavelets, the limitation of the scale range of the wavelets and the measures to solve the edge phenomenal in the direct algorithm of the discrete wavelet transform, and some conclusions in the direct algorithm of the continuous wavelet transform. The virtual wavelet transform analyzer for the signal analysis based on the direct algorithm explored based on these studies and combined with virtual instrument technique can make the discrete wavelet transform and continuous wavelet transform to signal with any basic wavelet. It can be applied in studying the property of any basic wavelet and learning the theory on the wavelet transform, and also in making some engineering signal analysis. In the end, the authors give some typical examples for the application of the virtual analyzer. These examples show that the analyzer can be applied in many situations.     

Suppression of Periodic Narrowband Interferences in Cable Partial Discharge Detections

There are background noises and interferences in the signal acquired,due to partial discharge(PD) detection system covers a broad frequency band.To suppress periodic narrowband signal which is a quite serious interference in PD measurement,the existing suppression method is introduced,the new method of wavelet packet transform is mainly studied to de-noise the periodic narrowband in XLPE cable PD detection system,which is based on the db4 basic wavelet using soft threshold.The results of the experiment show that wavelet packet transform is effective in restraining the periodic narrowband interferences to extract the PD pulses in XLPE cable PD monitoring system.     

General Construct Method & Software of Wavelet Base's Filter

Wavelet analyses have been used for many fields deeply, especially , the wavelet transforms on compact support sets have been applied to signal dealing and image compression etc. However, the constructing of wavelet base is a hard work to do. In this paper, for N=2k the analysis structure of wavelet base on compact support sets are found successful. That is the general solutions structure of equations which fits to the wavelet base orthogonal conditions, Those formulas or algorithms make it very easily construct many filters of wavelet base, at the same time , Daubechies's filters and some other filters which are important in apllications have been tested correct; With the aid of our formulas , it is very easy to dynamically choose the wavelet bases.     

Choosing Method of Wavelet Neuron Based on ECG Data Compression

The paper discusses a wavelet network for the ECG data compression and proposes the method for choosing its wavelet neuron.According to the spectrum range of the ECG data,we decide the time-frequency field of ECG.And the time-frequency field of wavelet is also determined by the spectrum range of it.The wavelet neuron is fixed preliminarily by the first two steps.Then the preliminary wavelet neuron is screened by using OLS algorithm.We choose Morlet as the mother wavelet,and use the ECG signal to validate by the method.The result demonstrates that the number of Morlet whose spectrums locate at the ECG's is up to 152.But after screening by the OLS algorithm,it reduces sharply.This method can make the size of the wavelet network driving to optimum and also reduce the training time of the wavelet network sharply.     

A Simplified Denoising Algorithm with Wavelet Transform

This article explains the mathematical characterization of singularities with Lipschitz exponents and how to compute Lipschitz exponents.The principle and advantage of denoising with wavelet are reviewed.At last,a new simplified practical denoising algorithm is given.     

Denoise Based On Translation Invariance Wavelet TransformAnd Its Applications

De_noising algorithm based on traditional wavelet transform may produce artifacts on discontinuities of the signal. The reason is that the de_noising algorithm lacks of wavelet translation invariant. This paper proposes a de_noising method based on translation invariant. The method performs the cycle_spinning for the signal to be analyzed. And then, the soft (hard) thresholding is used to shrink the wavelet coefficient of the signal and reconstruct the signal. Consequently, the shift dependence of wavelet basis is eliminated. This method can suppress the artifacts effectively so that de_noised signal is more smooth and has better approximation to original signal.     

Framework of M-channel Systems and the Best Symmetric Extension

In image compression based on wavelet transform, the borders of images have to be processed in advance so as to reduce the distortions around the borders. An efficient way for this problem is symmetric extension. There are different types of symmetric extension methods. The paper presents the best symmetric extension and gives a design algorithm. Using the algorithm, we obtain the scheme of extending and windowing the signals in general best M-channel analysis/synthesis system.     

R-factor Pseudo-circular Extension Method

The extension methods of finite length signals for sub band coding associated with wavelet transformation are investigated.Considering the weakness of the existing extension methods,an extension method is presented which is named r factor pseudo circular extension method.It turns out theoretically that the input signal can be reconstructed exactly from the truncated section of the analyzed signals by our method and the method is better than other existing extension methods,as shown in many examples.A new valid way is provided for wavelet transform application in data compression.     

Pulse Signal Analysis of Druggers with the Wavelet and Neural Network

The most significant difference between the human pulse signals collected from heroin druggers and healthy persons is at their amplitude waveforms as time functions. That is, the amplitude values and change rates of two types of signals, within a particular time range, appear different features. However, the partial components of the scaling and wavelet coefficients of the pulse signals obtained by using wavelet transform can reveal such key features. The pulse signals of 15 heroin druggers and 15 healthy persons are analyzed through using the muhiresolution analysis of wavelet transform. By using db2 orthogonal wavelet, every pulse signal is decomposed into three levels and the absolute values of the sixth component of scaling coefficients and the second component of the wavelet coefficients in the third level are combined to form a feature vector. A probabilistic neural network with good detection performance is successfully designed for automatically detecting 30 feature vectors. During the network design, 20 feature vectors are used as training samples. The remained 10 feature vectors are used as testing samples. Based on these steps, 15 heroin druggers and 15 healthy persons are all correctly identified. In other words, the detection rate arrives at 100%. druggers.     

Video Compression of Vector Coding based on Wavelet Transform

It is possible to get high compression rate for the interrelationship between neighboring frames of moving pictures. The kernel of research on video compression is that the efficient image compression algorithm is adopted while the interrelationship between neighboring frames and time consumption is concerned to improve the compression efficiency. It is significant that motion compensation is applied to video compression, nevertheless it is too time consuming. A vector coding method based on wavelet transform is presented to avoid searching procedure of motion compensation. Simulation shows that high compression rate is achieved with less time consumption.     

Audio blind watermarking scheme combined DWT DCT QR

In order to protect the copyright of digital audio and video in Internet, we propose a novel audio blind watermarking scheme combined discrete wavelets transform, discrete cosine transform, QR decomposition and audio characteristics. In this algorithm, the audio are split into blocks, and each block are decomposed on two dimensional discrete wavelet transform (DWT), then the approximate sub band coefficients are decomposed on discrete cosine transform (DCT), and the first quarter of the DCT coefficients are decomposed on QR decomposition and get a triangle matrix. At last, the watermarking information is embedded into the triangle matrix. The experiments show that the algorithm can get better balance between transparency and robustness of watermark, and it has strong robustness against the common audio signal processing such as additive white Gaussian noise, re sampling, re quantization, low pass filter, MP3 compression and cutting replacement.     

An algorithm of image processing based on discrete wavelet transform compression and chaotic scrambling

An algorithm was proposed in view of the combination of image compression and encryption. We got the approximate part and three detail parts after transforming the image with discrete wavelet transform (DWT), and compressed the image by modifying the detail parts by a given threshold value based on human visual systems. And then, we encrypted the image by scrambling the approximate part because this part held mostly of the energy. Last, a compressed and encrypted image can be achieved after DWT. Simulation result shows a good effect on the combination of compression and encryption.     

QRS complexes detection using quadratic b-spline wavelet transform algorithm

Aiming at the low accuracy and low adaptability of wave detection, a QRS complexes detection algorithm is proposed based on quadratic b-spline wavelet, while combined with binary search algorithm and arc approximating curve algorithm. The signal is decomposed with quadratic b-spline wavelet through Mallat algorithm and the R wave is detected by adjusting the threshold with binary search and modulus maximumizing. The T wave and P wave are detected by using arc approximating curve algorithm based on the least square. This algorithm is certified with the ECG signals from MIT-BIH database and is demonstrated that the algorithm enhanced the adaptability of R wave detection and improved the accuracy of T wave and P wave detection. The simulation experiment shows that the improved algorithm can effectively improve the automatic detection capabilities of ECG signals.     

Filter Design of Wavelet Transform for 2-D Image

The filter design is the key to 2-D image wavelet transform. Based on the studying of image properties and 1-D wavelet theory,the authors describe a parasymmetry boundary extension method and realize 2-D discrete wavelet transform by means of 1-D wavelet transform according to correlation of adjacent pixels. Also,it is proved that the discrete wavelet transform of inverse data stream in row and the sign of discrete detail signal will be inversed,and that a filter of wavelet transform based on symmetry of bi_orthogonal filter is constructed. The test has proved the fine reconstruction and perfect SNR.     

A Vector Quantification Image Coding Scheme Based on Wavelet Transform

The paper proposes an image compression and coding scheme based on discrete wavelet transform (DWT), which makes the best of the relativities among original image and coefficients of wavelet, the relativities among pixels of subimages, the relativities among directions of subimages. Human visual specialities were considered, so the compression scheme leads up to make full use of the statistical redundancy and visual redundancy of image. To get high compression ratio and good quality of image, the coefficients of image working on the quality of image greatly were reserved accurately, but the coefficients of image working on the quality of image slightly were quantified roughly. Also, the regrouping and coding of the coefficients could be used universally. The experimental results show that the compression method is provided with simply calculating, little time for coding and decoding and satisfying quality companied with high compression ratio.     

The Extended Kalman Filter Data Fusion Algorithm Based on Discrete Stationary Wavelet Transformation

It is difficult to establish precise mathematical model in extended Kalman filter data fusion algorithm for GPS/ DR integrated vehicle navigation system, an improved extended Kalman filter data fusion algorithm is put forward based on Discrete stationary wavelet transformation. The simulation results show that the algorithm is better than the extended Kalman filter data fusion algorithm, and is available for GPS/DR integrated vehicle navigation system.     

Parameter optimized Morlet wavelet de noising method based on cross validation method

A new de noising method based on parameter optimized Morlet wavelet is put forward. The Morlet wavelet is chosen as the mother wavelet because its shape is similar to the mechanical shock signals. The mother Morlet wavelet is improved by adding two parameters which decide the shape of the mother wavelet in time domain. The added parameters and the appropriate scale parameter for the wavelet transformation are designed by the cross validation method. Finally, the useful components of the signal can be obtained by the improved Morlet wavelet de noising method. The gear fault diagnosis experimental result shows that the proposed method has a good de nosing performance and it is effective in fault feature extraction.     

On line tool breakage monitoring method based on power information and cross-correlation algorithm

In order to reliably monitor unexpected tool failure and prevent workpiece or machine tool from possible damages in batch machining, a tool breakage on-line monitoring method based on power information and cross-correlation algorithm is proposed. In this method, wavelet coefficients of spindle-power signal are used as the characteristic vector of machining information, and then the vector sequence extracted from a normal machining process via Mallat wavelet is defined as the reference template for monitoring cutting tool condition. In batch machining, real-time characteristic vector of the workpiece in machining process is extracted via an improved real-time wavelet algorithm. The correlation of two vector sub-sequences within a sampling time window, which is described by generalized cross-correlation coefficient, decreases apparently when the tool is broken. The generalized cross-correlation coefficient is defined as tool condition index (TCI), and tool breakage can be detected by monitoring the TCI with a threshold value. Experiments show that the method can accurately identify tool breakage failures in normal machining condition, and thus it is practical.