Variational Mode Decomposition-Informed Empirical Wavelet Transform for Electric Vibrator Noise Analysis

Electric vibrators find wide applications in reliability testing, waveform generation, and vibration simulation, making their noise characteristics a topic of significant interest. While Variational Mode Decomposition (VMD) and Empirical Wavelet Transform (EWT) offer valuable support for studying signal components, they also present certain limitations. This article integrates the strengths of both methods and proposes an enhanced approach that integrates VMD into the frequency band division principle of EWT. Initially, the method decomposes the signal using VMD, determining the mode count based on residuals, and subsequently employs EWT decomposition based on this information. This addresses mode aliasing issues in the original method while capitalizing on VMD’s adaptability. Feasibility was confirmed through simulation signals and ultimately applied to noise signals from vibrators. Experimental results demonstrate that the improved method not only resolves EWT frequency band division challenges but also effectively decomposes signal components compared to the VMD method.

Use of the Wavelet Transform for Digital Terrain Model Edge Detection (Special Issue—Wavelet Analysis)

The purpose of this work is to analyze the feasibility of using the wavelet transform in the edge detection of digital terrain models (DTM) obtained by Laser Scanner. The Haar wavelet transform and the edge detection method called Wavelet Transform Modulus Maxima (WTMM), both implemented in Matlab language, were used. In order to validate and verify the efficiency of WTMM, the edge detection of the same DTM was performed by the Roberts, Sobel-Feldman and Canny methods, chosen due to the wide use in the scientific community in the area of Image Processing and Remote Sensing. The comparison of the results showed superior performance of WTMM in terms of processing time.

Application and Analysis of Wavelet Transform in Image Edge Detection

For the image processing technology, technicians have been looking for a convenient and simple detection method for a long time, especially for the innovation research on image edge detection technology. Because there are a lot of original information at the edge during image processing, thus, we can get the real image data in terms of the data acquisition. The usage of edge is often in the case of some irregular geometric objects, and we determine the contour of the image by combining with signal transmitted data. At the present stage, there are different algorithms in image edge detection, however, different types of algorithms have divergent disadvantages so It is diffi cult to detect the image changes in a reasonable range. We try to use wavelet transformation in image edge detection, making full use of the wave with the high resolution characteristics, and combining multiple images, in order to improve the accuracy of image edge detection.

Landsat Image-Based Spatiotemporal Variation Analysis of Erosion and Deposition off the Qingshuigou of the Yellow River Delta from 1984 to 2021

Owing to climate change and human activity,the Qingshuigou of the Yellow River Delta(YRD)has undergone dynamic changes in erosion and deposition.Therefore,studying these changes is important to ensure ecological protection and sustainable development.In this study,the trend of erosion-deposition evolution in the Qingshuigou was investigated based on 38 coastline phases extracted from Landsat series images of the YRD at one-year intervals from 1984 to 2021.The periodicity of the scouring and deposition evolution was also analyzed using wavelet analysis.Results showed that the total area of the Qingshuigou was affected by deposition and erosion and that the fluctuation first increased and then decreased.The total area reached a maximum in 1993.The depositional area first increased and then decreased,whereas the overall erosion area decreased.Deposition and erosion areas showed periodic changes to some extent;however,the periodic signal intensity decreased.Furthermore,factors including channel morphological evolution and variations in water and sediment discharge affect the spatiotemporal dynamics of erosion and deposition processes.The application of nonconsistency tests finally revealed that deposition area and flushing magnitude exhibited non-stationarities,which are potentially attributed to impacts from climatic change drivers.

When Edge Computing Meets IoT Systems: Analysis of Case Studies

On a macroscopic level,an edge computing architecture looks like a distributed and decentralized IT(Information Technology)architecture.More in detail,it could be defined as a mesh network of micro data centers capable of processing and storing critical data locally,and to transmit all data received and/or processed to a central data center or a cloud storage repository.This network topology,also taking advantage of the availability on the market of cost-effective small form factor(SFF)electronic components and systems decreasing,brings the essential components of processing,storage,and networking closer to the sources that generate the data.The typical use case is that of Internet of Things(IoT)devices and implementations,which often face latency problems,lack of bandwidth,reliability,which cannot be addressed through the conventional cloud model.In this context,the edge computing architecture can reduce the size of data to be sent to the cloud,processing critical data,sensitive to latency,at the point of origin,via a smart device,or sending it to an intermediate server,located nearby.The aim of this paper is to report some of the main aspects and significant features of edge computing and analyzing several popular case studies.

User Profile System Based on Sentiment Analysis for Mobile Edge Computing

Emotions of users do not converge in a single application but are scattered across diverse applications.Mobile devices are the closest media for handling user data and these devices have the advantage of integrating private user information and emotions spread over different applications.In this paper,we first analyze user profile on a mobile device by describing the problem of the user sentiment profile system in terms of data granularity,media diversity,and server-side solution.Fine-grained data requires additional data and structural analysis in mobile devices.Media diversity requires standard parameters to integrate user data from various applications.A server-side solution presents a potential risk when handling individual privacy information.Therefore,in order to overcome these problems,we propose a general-purposed user profile system based on sentiment analysis that extracts individual emotional preferences by comparing the difference between public and individual data based on particular features.The proposed system is built based on a sentiment hierarchy,which is created by using unstructured data on mobile devices.It can compensate for the concentration of single media,and analyze individual private data without the invasion of privacy on mobile devices.

IMAGE ANALYSIS BASED ON EDGE DETECTION TECHNIQUES

A method that incorporates edge detection technique, Markov Random field (MRF), watershed segmentation and merging techniques was presented for performing image segmentation and edge detection tasks. It first applies edge detection technique to obtain a Difference In Strength (DIS) map. An initial segmented result is obtained based on K means clustering technique and the minimum distance. Then the region process is modeled by MRF to obtain an image that contains different intensity regions. The gradient values are calculated and then the watershed technique is used. DIS calculation is used for each pixel to define all the edges (weak or strong) in the image. The DIS map is obtained. This help as priority knowledge to know the possibility of the region segmentation by the next step (MRF), which gives an image that has all the edges and regions information. In MRF model, gray level l , at pixel location i , in an image X , depends on the gray levels of neighboring pixels. The segmentation results are improved by using watershed algorithm. After all pixels of the segmented regions are processed, a map of primitive region with edges is generated. The edge map is obtained using a merge process based on averaged intensity mean values. A common edge detectors that work on (MRF) segmented image are used and the results are compared. The segmentation and edge detection result is one closed boundary per actual region in the image.

Real-time Forward Vehicle Detection Method Based on Edge Analysis

This paper proposes a method which uses the extended edge analysis to supplement the inaccurate edge information for better vehicle detection during vehicle detection. The extended edge analysis method detects two vertical edge items, which are the borderlines of both sides of the vehicle, by extending the horizontal edges inaccurately due to the illumination or noise existing on the image. The proposed method extracts the horizontal edges with the method of merging edges by using the horizontal edge information inside the Region of Interest （ROI）, which is set up on the pre-processing step. The bottona line is determined by detecting the shadow regions of the vehicle from the extracted hoodzontal edge one. The general width of the vehicle detecting and the extended edge analyzing methods are carried out side by side on the bottom line of the vehicle to determine width of the vehicle. Finally, the finmal vehicle is detected through the verification step. On the road image with conaplicate background, the vehicle detecting method based on the extended edge analysis is more efficient than the existing vehicle detecting method which uses the edge information. The excellence of the proposed vehicle detecting method is confirmed by carrying out the vehicle detecting experiment on the complicate road image.

NUMERICAL-PERTURBATION ANALYSIS OF EDGE EFFECT IN BENDING LAMINATED PLATE

In this paper, we consider a bending laminated plate. At first, the dimensionless variables are used to transform the equilibrium equations of any layer to perturbation differential equations. Secondly, the composite expansion is used and the solution domain is divided into interior and boundary layer regions and the mathematical models for the outer solution and the inner solution are yielded respectively. Then, the inner solution is expressed with the boundary intergral equation.

A New Method of Color Edge Detection Based on Local Structure Analysis

Human's real life is within a colorful world. Compared to the gray images, color images contain more information and have better visual effects. In today's digital image processing, image segmentation is an important section for computers to "understand" images and edge detection is always one of the most important methods in the field of image segmentation. Edges in color images are considered as local discontinuities both in color and spatial domains. Despite the intensive study based on integration of single-channel edge detection results, and on vector space analysis, edge detection in color images remains as a challenging issue.

An analysis on the formation mechanism of the distributionof high content of chlorophyll-a in the continentalshelf edge waters of East China Sea

On the basis of the data obtained from the comprehensive Kuroshio surveys in 1987-1988,this paper analyses the oceanographic characteristics in the area (125°-130° E,27°-31° N) of the continental shelf edge of the East China Sea (E. C. S. ) and its adjacent waters and discusses the effects of the Kuroshio front,thermocline and upwelling of the Kuroshio subsurface water on the distribution of standing stock of phytoplankton (chlorophyll-a). The distribution of high content of chlorophylly-a has been detected at 20-50 in depth in the water body on the left side of the Kuroshio front in the continental shelf edge waters of the E. C. S. The high content of chlorophyll-a spreads from the shelf area to the Kuroshio area in the form of a tongue and connects with the maximum layer of subsurface chlorophyll-a of the Kuroshio and pelagic sea. The author considers that the formation of the distribution of high content chlorophyll-a in this area results from the bottom topography and oceanic environment and there are close correlations between the high content of chlorophyll-a and the light-nutrient environment.

Theoretical research on structural damage alarming of long-span bridges using wavelet packet analysis

The state equation and observation equation of the structural dynamic systems under various analysis scales are derived based on wavelet packet analysis. The time-frequency properties of structural dynamic response under various scales are further formulated. The theoretical analysis results reveal that the wavelet packet energy spectrum （WPES） obtained from wavelet packet decomposition of structural dynamic response will detect the presence of structural damage. The sensitivity analysis of the WPES to structural damage and measurement noise is also performed. The transfer properties of the structural system matrix and the observation noise under various analysis scales are formulated, which verify the damage alarming reliability using the proposed WPES with preferable damage sensitivity and noise robusticity.

Robust edge detection based on stationary wavelet transform

By combining multiscale stationary wavelet analysis with fuzzy c-means, a robust edge detection algorithm is presented. Based on the translation invafiance built in multiscale stationary wavelet transform, components in different transformed sub-images corresponding to a pixel are employed to form a feature vector of the pixel. All the feature vectors are classified with unsupervised fuzzy c-means to segment the image, and then the edge pixels are checked out by the Canny detector. A series of images contaminated with different intensive Gaussian noises are used to test the novel algorithm. Experiments show that fairly precise edges can be checked out robustly from those images with fairly intensive noise by the proposed algorithm.

Integrated interpretation of dual frequency induced polarization measurement based on wavelet analysis and metal factor methods

In mineral exploration, the apparent resistivity and apparent frequency （or apparent polarizability） parameters of induced polarization method are commonly utilized to describe the induced polarization anomaly. When the target geology structure is significantly complicated, these parameters would fail to reflect the nature of the anomaly source, and wrong conclusions may be obtained. A wavelet approach and a metal factor method were used to comprehensively interpret the induced polarization anomaly of complex geologic bodies in the Adi Bladia mine. Db5 wavelet basis was used to conduct two-scale decomposition and reconstruction, which effectively suppress the noise interference of greenschist facies regional metamorphism and magma intrusion, making energy concentrated and boundary problem unobservable. On the basis of that, the ore-induced anomaly was effectively extracted by the metal factor method.

Automated Registration for Infrared Image Based on Wavelet Analysis

To develop a quick, accurate and antinoise automated image registration technique for infrared images, the wavelet analysis technique was used to extract the feature points in two images followed by the compensation for input image with angle difference between them. A hi erarchical feature matching algorithm was adopted to get the final transform parameters between the two images. The simulation results for two infrared images show that the method can effectively, quickly and accurately register images and be antinoise to some extent.

Study on Rhizome Crops by Fourier Transform Infrared Spectroscopy Combined with Wavelet Analysis

In order to distinguish 8 kinds of rhizome crops, the 40 samples were studied by Fourier transform infrared spectroscopy （FTIR） combined with wavelet transform （WT）, principal component analysis （PCA） and hieramhical cluster analysis （HCA）. The results showed that the infrared spectra were similar on the whole, but there were differences in peak position, peak shape and peak absorption intensity in the range of 1 800-700 cm-1. The infrared spectra in the range of 1 800-700 cm-1 were selected to perform continuous wavelet transform （CWT） and discrete wavelet transform （DWT）. The 15th-Ievel decomposition coefficients of CWT and the 5=-level detail coefficients of DWT were classified by PCA and HCA. The cumulative contri- bution rates of the first three principal components of CWT and DWT were 93.12% and 89.78%, respectively. The accurate recognition rates of PCA and HCA were all 100%. It is proved that FTIR combined with WT can be used to distinguish different kinds of rhizome crops.

A novel method for gamma spectrum analysis of low-level and intermediate-level radioactive waste

The uncertainty of nuclide libraries in the analysis of the gamma spectra of low-and intermediate-level radioactive waste(LILW)using existing methods produces unstable results.To address this problem,a novel spectral analysis method is proposed in this study.In this method,overlapping peaks are located using a continuous wavelet transform.An improved quadratic convolution method is proposed to calculate the widths of the peaks and establish a fourth-order filter model to estimate the Compton edge baseline with the overlapping peaks.Combined with the adaptive sensitive nonlinear iterative peak,this method can effectively subtracts the background.Finally,a function describing the peak shape as a filter is used to deconvolve the energy spectrum to achieve accurate qualitative and quantitative analyses of the nuclide without the aid of a nuclide library.Gamma spectrum acquisition experiments for standard point sources of Cs-137 and Eu-152,a segmented gamma scanning experiment for a 200 L standard drum,and a Monte Carlo simulation experiment for triple overlapping peaks using the closest energy of three typical LILW nuclides(Sb-125,Sb-124,and Cs-134)are conducted.The results of the experiments indicate that(1)the novel method and gamma vision(GV)with an accurate nuclide library have the same spectral analysis capability,and the peak area calculation error is less than 4%;(2)compared with the GV,the analysis results of the novel method are more stable;(3)the novel method can be applied to the activity measurement of LILW,and the error of the activity reconstruction at the equivalent radius is 2.4%;and(4)The proposed novel method can quantitatively analyze all nuclides in LILW without a nuclide library.This novel method can improve the accuracy and precision of LILW measurements,provide key technical support for the reasonable disposal of LILW,and ensure the safety of humans and the environment.

AN EDGE DETECTOR BA SED ON WAVELET TRANSFORM FOR SAR IMAGE

Edge detecting is a f undamental issue in image analysis and image processing. In this paper, based on wavelet transform, an edge detector of SAR image is studied to serve the image aided navigation. Though wavelet transform is efficient as an edge detector, a l ot of false edges will be extracted from a SAR image, especially in areas of hig h reflectivity, with wavelet transform and a fixed threshold because SAR images are always contaminated by speckle. Therefore, this paper develops an algorithm by using a variable threshold with constant false alarm rates to help suppressin g the speckle in SAR images. Finally, two simulating tests are given and the res ults show that the effect of the multiplicative speckle is controlled and there are few false edges in the gotten edge images. Moreover, owing to the threshold from the wavelet transform coefficients, the algorithm can assure the real time of SAR image aided navigation.

Numerical Study on the Duct Noise Control of Single-Stage Axial Flow Fan with Wave Leading Edge Stator Blade Configurations

This study focuses on a single-stage axial flow fan, investigating the effect of three kinds of wave leading edge stator blades on its noise reduction. The DDES method and the duct acoustic analogy theory based on the penetrable data surface were used for noise prediction. The results showed that the three kinds of wave leading edge blades were effective in reducing the rotor-stator interaction tonal noise and also have a certain inhibitory effect on broadband noise. The A10W15 stator blade can effectively reduce broadband noise in the frequency range of 2200 - 4200 Hz. When the amplitude is increased to 20, the noise reduction effect is further enhanced. However, when the amplitude is increased to 30, the broadband noise reduction effect is no longer significant. Further research shows that the wave leading edge stator blades can significantly change the pressure fluctuation distribution on the leading edge and suction surface, which control the modal energy distribution. Finally, this paper analyzed multiple factors affecting the broadband noise reduction, such as the noise source cut-off and cut-on effect and correlation. The purpose of this paper is to explore the laws of the influence of wave leading edge blades on the duct noise of real fan, and to reveal its noise control mechanism. .

Research on Auto-detection for Remainder Particles of Aerospace Relay Based on Wavelet Analysis

Aerospace relay is one kind of electronic components which is used widely in national defense system and aerospace system. The existence of remainder particles induces the reliability declining, which has become a severe problem in the development of aerospace relay. Traditional particle impact noise detection （PIND） method for remainder detection is ineffective for small particles, due to its low precision and involvement of subjective factors. An auto-detection method for PIND output signals is proposed in this paper, which is based on direct wavelet de-noising （DWD）, cross-correlation analysis （CCA） and homo-filtering （HF）, the method enhances the affectivity of PIND test about the small particles. In the end, some practical PIND output signals are analysed, and the validity of this new method is proved.