Application Of Wavelet Analysis Research Articles

3D polarization-interference holographic histology for wavelet-based differentiation of the polycrystalline component of biological tissues with different necrotic states. Forensic applications.

The interference-holographic method of phase scanning of fields of scattered laser radiation is proposed. The effectiveness of this method for the selection of variously dispersed components is demonstrated. This method made it possible to obtain polarization maps of biological tissues at a high level of depolarized background. The scale-selective analysis of such maps was used to determine necrotic changes in the optically anisotropic architectonics of biological tissues. Development and experimental approbation of layered phase polarimetry of repeatedly scattered fields in diffuse layers of biological tissues. Application of scale-selective processing of the found coordinate distributions of polarization states in various phase sections of object fields. Determination of criteria (markers) for histological differential diagnosis of the causes of necrotic changes in optical anisotropy of biological tissues. We used a synthesis of three instrumental and analytical methods. Polarization-interference registration of laser radiation scattered by a sample of biological tissue. Digital holographic reconstruction and layered phase scanning of distributions of complex amplitudes of the object field. Analytical determination of polarization maps of various phase cross-sections of repeatedly scattered radiation. Application of wavelet analysis of the distributions of polarization states in the phase plane of a single scattered component of an object field. Determination of criteria (markers) for differential diagnosis of necrotic changes in biological tissues with different morphological structure. Two cases are considered. The first case is the myocardium of those who died as a result of coronary heart disease and acute coronary insufficiency. The second case is lung tissue samples of deceased with bronchial asthma and fibrosis. A method of polarization-interference mapping of diffuse object fields of biological tissues has been developed and experimentally implemented. With the help of digital holographic reconstruction of the distributions of complex amplitudes, polarization maps in various phase sections of a diffuse object field are found. The wavelet analysis of azimuth and ellipticity distributions of polarization in the phase plane of a single scattered component of laser radiation is used. Scenarios for changing the amplitude of the wavelet coefficients for different scales of the scanning salt-like MHAT function are determined. Statistical moments of the first to fourth orders are determined for the distributions of the amplitudes of the wavelet coefficients of the azimuth maps and the ellipticity of polarization. As a result, diagnostic markers of necrotic changes in the myocardium and lung tissue were determined. The statistical criteria found are the basis for determining the accuracy of their differential diagnosis of various necrotic states of biological tissues. Necrotic changes caused by "coronary artery disease-acute coronary insufficiency" and "asthma-pulmonary fibrosis" were demonstrated by the method of wavelet differentiation with polarization interference with excellent accuracy.

Wavelet Analysis and Forecasting using Open-Access Lumber Market Indices for Assessing the Impact of Hurricanes on Southern US Stumpage Prices

Abstract In the aftermath of events such as hurricanes, the economic impact of downed timber can reach billions of dollars. Accurate forecasting of stumpage prices after such events is crucial for maximizing recovery value while minimizing salvage costs. However, this poses challenges because of the inherent nature of the data. This study addresses these challenges by exploring the application of wavelet analysis, a novel approach in the field of forestry economic analysis. Wavelet analysis offers a unique framework for studying periodic phenomena in time series data, particularly when frequency changes over time are present. By leveraging wavelet analysis, this study uncovers relationships between timber market indices and hurricane seasons. The combination of traditional correlation analysis and wavelet coherence analysis enhances the statistical analysis in this study, offering a comprehensive examination of the relationship between the Timber Market Survey data and market indices. This innovative analytical approach enables a deeper understanding of the dynamics of the timber market and the potential effects of hurricanes on timber prices. Furthermore, this research highlights the recent advancements in wavelet methodology and the availability of open-source packages in the programming language R, such as WaveletComp and WaveletArima, that facilitate wavelet analysis and time series forecasting. The Wavelet-ARIMA model used in this study demonstrates its effectiveness in reducing noise and improving prediction accuracy. The study incorporates an extensive data set consisting of 10 Consumer Price Indices, 7 Producer Price Indices, 30 state-wide Timber Market Survey indices, 54 TMS subregions, and 6 open market series.

Intelligent state assessment of complex autonomous objects based on wavelet analysis

The evolutionary development of complex autonomous technical objects (CATOs), which include bodynets, unmanned vehicles, aircraft, and other robotic systems, is characterized by increased requirements for the quality of their functioning, security, and reliability under the influence of various kinds of destabilizing factors. This determines the importance of the problem of assessing their technical state, including monitoring degradation (aging) and supporting the dynamic adaptation of CATOs. To solve this problem, the article proposes a new method for intelligent assessment of the CATO technical state. The method is based on the representation of knowledge about the results of interval estimation of controlled parameters in the knowledge base of the system for assessing the CATO technical state. In this case, the process of estimating the controlled parameters is based on the application of wavelet analysis. The article discusses the architecture and implementation issues of the intelligent system for assessing the CATO technical state. A special place in this system is occupied by the knowledge base containing information about the emergency and normal states of controlled parameters. An experimental evaluation of the proposed assessment method showed that the joint use of knowledge representation processes in the knowledge base and wavelet analysis for the formation of CATO operability regions increases the accuracy and credibility of the state identification results. In addition, this approach expands the possibilities of applying technical means of control and diagnostics concerning evolving CATO.

Wavelet analysis of laser Doppler microcirculatory signals: Current applications and limitations.

Laser Doppler flowmetry (LDF) has long been considered a gold standard for non-invasive assessment of skin microvascular function. Due to the laser Doppler (LD) microcirculatory signal's complex biological and physiological context, using spectral analysis is advisable to extract as many of the signal's properties as feasible. Spectral analysis can be performed using either a classical Fourier transform (FT) technique, which has the disadvantage of not being able to localize a signal in time, or wavelet analysis (WA), which provides both the time and frequency localization of the inspected signal. So far, WA of LD microcirculatory signals has revealed five characteristic frequency intervals, ranging from 0.005 to 2Hz, each of which being related to a specific physiological influence modulating skin microcirculatory response, providing for a more thorough analysis of the signals measured in healthy and diseased individuals. Even though WA is a valuable tool for analyzing and evaluating LDF-measured microcirculatory signals, limitations remain, resulting in a lack of analytical standardization. As a more accurate assessment of human skin microcirculation may better enhance the prognosis of diseases marked by microvascular dysfunction, searching for improvements to the WA method is crucial from the clinical point of view. Accordingly, we have summarized and discussed WA application and its limitations when evaluating LD microcirculatory signals, and presented insight into possible future improvements. We adopted a novel strategy when presenting the findings of recent studies using WA by focusing on frequency intervals to contrast the findings of the various studies undertaken thus far and highlight their disparities.

TESTING OF BRIDGES DAMAGED AS A RESULT OF COMBAT ACTIONS

The work examines the application of methods of static and dynamic testing of bridges damaged as a result of hostilities. Penetration by projectiles and damage by explosions of structural elements, in addition to obvious damage, also form a series of hidden defects, the determination of which according to norms and regulatory documents is regulated to be carried out by means of tests with calculated loads. For testing bridges in accordance with the requirements of construction standards and regulatory documents, the equipment developed by the author of the article was used for digital registration and processing of signals of acoustic emission and mechanical vibrations. The results of static tests of three span overpasses made of precast concrete with a length of 63.20 m along the street are presented. Kvitneva in the city of Chernihiv and a four-span pedestrian bridge with a length of 263.1 m across the Desna River in the park zone of the city of Chernihiv. The peculiarities of the application of the acoustic emission method for determining the state of the span structures of the bridge during static tests with step loading are considered. During the analysis of the results of the dynamic tests of the pedestrian bridge, the results of the application of wavelet analysis were translated to reveal the characteristics of the oscillations of a non-separable steel three-span structure that received dynamic load impulses and determine the natural frequency of oscillations of the span structures. The results of the work are recommended for use during the examination and testing of bridges, the girder structures of which have hidden defects and damage, as well as for constant monitoring of the structures.

Wavelet transform-based cross-correlation in the time-delay estimation applications

The article discusses the application of wavelet analysis for the time-frequency time-delay estimation. The proposed algorithm is wavelet transform-based cross-correlation time delay estimation that applies discrete time wavelet transform to filter the input signal prior to computation of cross-correlation function. The distinguishing feature of the algorithm that it uses the variation of continuous wavelet transform to process the discrete signals instead of dyadic wavelet transform that is normally applied to the case. Another feature that the implication of convolution theorem is used to compute coefficients of the wavelet transform. This makes possible to omit redundant discrete Fourier transforms and significantly reduce the computational complexity. The principal applicability of the proposed method is shown in the course of a computational experiments with artificial and real-world signal. So the method demonstrated expected selectivity for the signals localized in the different frequency bands. The application of the method to practical case of pipeline leak detection was also successful. However, the study concluded that this method provides no specific advantages in comparison with the conventional one. In the future, alternative applications in biological signal processing will be considered.

Prospects for the Application of Wavelet Analysis to the Results of Thermal Conductivity Express Control of Thermal Insulation Materials

This article discusses an express control method that allows in situ measurements of the thermal conductivity of insulation materials. Three samples of the most common thermal insulation materials, such as polyurethane, extruded polystyrene, and expanded polystyrene, were studied. Additionally, optical and organic glasses were investigated as materials with a stable value of thermal conductivity. For the measurement of thermal conductivity, the express control device, which implements the differential method of local heat influence, was used. The case studies were focused on the reduction of fluctuations of the measured signals caused by different influencing factors using wavelet transform. The application of wavelet transform for data processing decreased the thermal conductivity measurement’s relative error for organic glass SOL and optical glasses TF-1 and LK-5. The application of wavelet transform thermal conductivity measurement data for polyurethane, extruded polystyrene, and expanded polystyrene allowed to reduce twice the duration of express control while maintaining the same level of measurement error. The results of the investigation could be used to increase the accuracy in express control of the thermal conductivity of insulation materials by improving the data processing. This approach could be implemented in software and does not require a change in the design of the measuring equipment or the use of additional tools.

Analysis of Denoising Methods of Underwater Acoustic Pulse Signal Based on Wavelet and Wavelet Packet

Underwater acoustic countermeasures include active sonar countermeasures and passive sonar countermeasures. In order to achieve the best operational efficiency of jamming equipment, the generation of jamming signals must adapt to the development trend of underwater acoustic detection technology-nonlinear time-varying and broadband characteristics. Feature extraction is to map the high-dimensional original data to the low-dimensional transformation space through a certain mapping relationship, which can suppress a large amount of redundant information in the data and highlight the category information of the data. One of the applications of wavelet analysis in signal analysis and processing is to remove noise components from signals. In practical engineering applications, sampled signals are inevitably polluted by various noises and interferences. Through the analysis of noise characteristics, it can be seen that the wavelet denoising method is very effective in removing signal noise. In this paper, aiming at the signals with different spectrum distribution, we use various methods to de-noise in order to find the de-noising methods suitable for underwater acoustic pulse signals with different frequency characteristics, and thus find an effective means to detect signals.

Coupling the Xinanjiang model and wavelet-based random forests method for improved daily streamflow simulation

AbstractDaily streamflow modeling is an important tool for water resources management and flood mitigation. This study compared the performance of the Xinanjiang (XAJ) model and random forests (RF) method in a daily streamflow simulation, and proposed several hybrid models based on the XAJ model, wavelet analysis, and RF method (including XAJ-RF model, WRF model, and XAJ-WRF model). The proposed methods were applied to Shiquan station, located in the Upper Han River basin in China. Five performance measures (NSE, RMSE, PBIAS, MAE, and R) were adopted to evaluate the modeling accuracy. Results showed that XAJ-RF model had a relatively higher level of accuracy than that of the XAJ model and the RF model. Compared to the RF and XAJ-RF models, the performance statistics of WRF and XAJ-WRF were better. The results indicated that the coupled XAJ-RF model can be effectively applied and provide a useful alternative for daily streamflow modeling and the application of wavelet analysis contributed to the increasing accuracy of streamflow modeling. Moreover, 14 wavelet functions from various families were tested to analyze the impact of various mother wavelets on the XAJ-WRF model.

Dam-Induced Alteration in Seasonal Fluvial Discharge Time Series in Kali Gandaki Hydropower Dam, Syangja, Nepal: An Application of Wavelet Analysis

Dam-Induced Alteration in Seasonal Fluvial Discharge Time Series in Kali Gandaki Hydropower Dam, Syangja, Nepal: An Application of Wavelet Analysis

Combining application of wavelet analysis and genetic algorithm in wind tunnel simulation of unidirectional natural wind field near a sand ground surface.

This study proposes a method for the approximate simulation of field gust in an atmospheric boundary layer wind tunnel driven by an axial fan. Wavelet analysis and genetic algorithm have been adopted to convert actual field gust data into a series of simplified and smooth control signals. One frequency converter is used to receive the signals via a programmable logic controller and change the fan speed correspondingly. Results show that the low-frequency energetic part of field gust on top of a saltation layer has been almost reproduced in the wind tunnel with energy fluctuations ±3.26% from the mean compared with the field data in terms of energy. The appropriate filter frequency for field gust velocity history is 1/32Hz. A unidirectional natural wind field near a sand bed surface can be approximately simulated in the tunnel by adjusting carefully the roughness element arrangement. The time-averaged velocity profile of the simulated wind, which satisfies the logarithmic law, is nearly equivalent to the steady flow with the same average velocity.

Fault Diagnosis in Belt Transmission Using Wavelet Enveloped Spectrum

In the recent years, there is a need for the evolution of methodologies for vibrational analysis by condition monitoring. In this regard, wavelet analysis has become a tool to efficiently detect the features of any vibration signal. The application of wavelet analysis for finding fault in the belt drive is presented in this paper. Vibration signal has been obtained from a healthy and faulty belt drive using a belt drive testing apparatus for experimental studies. The fault diagnostic capability of wavelet analysis has been compared by processing an experimental data. The experiment is done for various working conditions of belt drive. The advantages of wavelet analysis is shown in comparison with Fast Fourier Transform.

Application of wavelet analysis for processing tomograms of narrow cracks

The previously proposed method of increasing the visibility of cracks on tomograms obtained from X-ray sensing of sections of metal elements of building structures has been developed. A multiscale decomposition of tomogram lines is performed using the Haar wavelet basis. The detailed decomposition coefficients corresponding to the level of the assumed crack width are multiplied by a constant, the value of which is determined based on the noise level and the difference between the amplitude of the crack image and the surrounding background. In contrast to the previous work, where these parameters were assumed to be set, here we suggest the methods for its evaluating from the measurements. In particular, a simple formula is obtained that relates the variance of uncorrelated noise in the projection data to that of noise in the tomogram. The method is implemented as a computational algorithm based on which a computer program is developed. Numerical modeling was performed. The errors of the first and second kind were used toevaluate the effectiveness of the method determining whether a pixel belongs to a crack image. Binary classification was used for their calculation. Dependences of errors on the number of projections and the noise level on them were obtained. The results of the simulations showed that the use of the proposed method can reduce errors by 1.7-2.5 times.

Wavelet analysis of static deflections for multiple damage identification in beams

Wavelet analysis can be used in local damage detection due to its ability of revealing discontinuities induced by damage in the displacement field. This paper focuses on the application of wavelet analysis to detect and identify multiple damages using the static deflection of beams. The local damages are located by the wavelet maxima lines and their severity are evaluated from a damage index obtained from the wavelet coefficients along the corresponding maxima lines. A series of experimental tests were conducted to examine the performance of the methodology for multiple damage scenarios. The static deflections of the beam were measured by a Digital Image Correlation system. As an application, a l1 regularization based filter is adopted to diminish the measurement noise which is critical in the application of wavelet analysis. The paper shows the capability of using wavelet analysis for closely spaced notch-type damage detection. It also analyzes the limits of the method in estimating damage with relative small severity in the presence of severe ones.

Application of wavelet analysis of X-Ray computed tomography histogram for phase segmentation

With the development of unconventional resources, the standard task of evaluation the porosity and oil saturation needs a new approach. Heavy oil and bitumen can act as the cement in many sand reservoirs, which excludes the use of standard measuring techniques. A method for phase segmentation and estimating the porosity and oil saturation of heavy oil reservoirs, based on wavelet analysis of X-ray computed tomography histogram was proposed. Its advantages are reducing human influence on phase thresholding and the ability to work with loose sand reservoirs, for which it is not possible to use standard assessment methods. The main problem found for this method is the need for high detailing of segmentation objects since a large amount of noise and transition voxels adversely affect class recognition and quantitative interpretation. The application of wavelet analysis approach for naturally heavy oil saturated samples requires high-resolution microCT (less than 5 µm) and high oil saturation of the samples.

A bad data detection approach to EPS state estimation based on fuzzy sets and wavelet analysis

The paper offers an algorithm for detection of erroneous measurements (bad data) that occur at cyberattacks against systems for data acquisition, processing and transfer and cannot be detected by conventional methods of measurement validation at EPS state estimation. Combined application of wavelet analysis and theory of fuzzy sets when processing the SCADA and WAMS measurements produces higher accuracy of the estimates obtained under incomplete and uncertain data and demonstrates the efficiency of proposed approach for practical computations in simulated cyberattacks.

Methods of determination of spatial distribution of minor-amplitude faults and fissures in thin-layered coal-bearing geological medium

A problem of determining location of faults and fissured in geological medium which appear in the process of formation of the main types of geological structures: shears, nappes, faults, grabens, axes of folding and compression zones is considered. Areal seismic records of MCDP 3D obtained in the mine field of “Krasnolimanskaya” mine (Donetsk district) were used as initial data. It is located on the monocline of the southwestern part of Kalmius-Torets basin in the hanging wing of the Central nappe with amplitude up to 310m. Monocline occurrence of rocks is complicated by numerous disjunctive faults of the faulting type with amplitudes up to 95m. The main marker for identification for presence of a fault on the seismic records of MCDP 3D under conditions of horizontally-layered medium is interruption and (or) displacement of the axis of reflected waves phase synchronism. In some cases a diffracted wave appears in the place of horizon rupture. Provided that in the case of complicated geology it seems impossible to identify minor-amplitude displacements and discordant occurrence of reflecting margins related to faults. For spatial identification of the fault structures position the results of solving the inverse seismic problem are proposed – logarithmic decrements of fading (LDF) with their method of calculation that was put forward by the author previously. Temporal cross-sections of LDF have the same permissive ability as seismic data of MCDP 3D. Such a detail allows separating out minor-amplitude derangements related to faults and fissures. Special feature of temporal data of LDF is in the point that the identifiers of discordant occurrence of reflecting margins are their absorbing properties. The examples of vertical and horizontal LDF sections of a seismic cube 3D where a lot of deep and surface faults can be traced are given in the paper. Taking into account the complexity of mapping the planes of faults in three-dimensional space a method of automatic determination of the point of drastic change of absorbing properties of the medium (on each of horizontal cuts of the cube) with application of wavelet analysis has been proposed. A matrix of attributes is created of such points by which the planes of faults are plotted.

Denoising of Electrocardiogram Based on Norm Parameter using Wavelet Packet Transform

The electrocardiogram is an electrical activity of the human heart and it is mainly used in the diagnosis of different diseases associated with the human heart. In the medical field, it is also known as electrophysiological activity of the human heart. During its recording an unwanted noise known as artifacts is getting contaminated into it, this creates an obstruction in its clinical analysis. As for application of wavelet analysis is concerned, it is then fit to mention that denoising of ECG is effectively done by wavelet tools, so that identification of hidden diseases of the patient becomes possible. In this research article an algorithm is proposed for denoising ECG signal by applying a wavelet transform popularly known as wavelet packet transformation and three wavelet functions: Haar Wavelet, Db-3 Wavelet and Coiflet-3 Wavelet. The performance of this algorithm is studied on the basis of constraints popularly known in the mathematical field as Signal to Noise ratio (SNR), Norm 1 and Norm 2. This algorithm is first applied in deciding the optimum level of decomposition applied to the ECG recording No. S10m.mat, then a comparative study is laid down for a sample of 10 ECG recordings obtained from MIT-BIH database available on www.physio.net.

Możliwości zastosowania transformaty falkowej do oceny stanu powierzchni ściernych narzędzi nasypowych

Issues regarding the application of wavelet analysis to the description of the surface condition of abrasive tools differing in grain size and construction method are presented. New tools were tested and after the specified grinding time.

Application of wavelet analysis to differences in modal rotations for damage identification

Shearography is an effective non-destructive testing method which already found numerous applications in structural damage identification and for various industrial branches. This method, however, consider the detection and localization based on the irregularities found on rotation fields. This paper presents the concept of non-destructive damage identification in structural elements using modal rotation together with advanced signal processing for the enhancement of its sensitivity, thus allowing for overcoming the problem of small damage detectability. The presented approach uses a set modal rotations fields of a beam, initially processed from shearographic phase maps, for undamaged and damage states. The difference in modal rotations, between the two damages states, is initially calculated and afterward is subjected to a wavelet transform. The presented results show the effectiveness of the presented approach in tasks of structural damage identification.