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Impact Localization System for Composite Barrel Structure using Fiber Bragg Grating Sensors
摘要： Composite barrel structures are widely used in manufacturing of aircrafts and spacecrafts, the localization of impact on composite barrel structures are essential for structure health monitoring and safety assurance. In this paper, an LVI localization system was established on a composite barrel structure with fiber Bragg grating sensors, by analyzing the relationship between the wavelet packet energy spectrum of LVI response signals monitored by FBG sensors and corresponding impact locations on composite barrel structure, the zeroth node’s energy was found to be sensitive to LVI location, and an impact localization method for composite barrel structure which use the zeroth node’s energies as LVI feature values to predict the LVI locations by means of support vector regression (SVR) was proposed. The performance of the zeroth node’s energy based localization method were compared with localization methods that based on the energy of the fourth node which covers the natural frequency of the composite barrel structure or the total energy of frequency domain. The proposed localization method based on the zeroth node’s energy and SVR demonstrates an effective and practical means for localization of LVI on composite barrel structure with low sampling rate fiber bragg grating sensors and small computation.
关键词： Composite barrel structure,Wavelet analysis,Fiber Bragg gratings.,Impact localization
更新于2025-09-23 15:22:29
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Combining Faraday Tomography and Wavelet Analysis
摘要： We present a concept for using long-wavelength broadband radio continuum observations of spiral galaxies to isolate magnetic structures that were only previously accessible from short-wavelength observations. The approach is based on combining the RM Synthesis technique with the 2D continuous wavelet transform. Wavelet analysis helps to isolate and recognize small-scale structures which are produced by Faraday dispersion. We ?nd that these structures can trace galactic magnetic arms as illustrated by the case of the galaxy NGC 6946 observed at λ = 17–22 cm. We support this interpretation through the analysis of a synthetic observation obtained using a realistic model of a galactic magnetic ?eld.
关键词： wavelet analysis,RM-synthesis,faraday depolarization,galactic magnetic field
更新于2025-09-19 17:15:36
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A Novel Fault Classification Approach for Photovoltaic Systems
摘要： Photovoltaic (PV) energy has become one of the main sources of renewable energy and is currently the fastest-growing energy technology. As PV energy continues to grow in importance, the investigation of the faults and degradation of PV systems is crucial for better stability and performance of electrical systems. In this work, a fault classification algorithm is proposed to achieve accurate and early failure detection in PV systems. The analysis is carried out considering the feature extraction capabilities of the wavelet transform and classification attributes of radial basis function networks (RBFNs). In order to improve the performance of the proposed classifier, the dynamic fusion of kernels is performed. The performance of the proposed technique is tested on a 1 kW single-phase stand-alone PV system, which depicted a 100% training efficiency under 13 s and 97% testing efficiency under 0.2 s, which is better than the techniques in the literature. The obtained results indicate that the developed method can effectively detect faults with low misclassification.
关键词： feature extraction,radial basis function networks (RBFN),fault classification,photovoltaic system,wavelet analysis,kernels
更新于2025-09-19 17:13:59
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Photovoltaic active power control based on BESS smoothing
摘要： The power fluctuation of photovoltaic (PV) is harmful to power systems, so the battery energy storage system (BESS) was applied to smooth power fluctuation in PV. At present, the main ways to get configuration of BESS are low-pass filter and spectrum compensation, which have some drawbacks. In this paper, a method that combines empirical mode decomposition (EMD) with wavelet analysis (WA) is proposed to get grid-connected active power expectation of PV properly. Based on simulation of PV output, the minimum sizing of BESS is determined by different batteries’ state-of-charging (SOC) and efficiency. Comparing traditional low-pass filter and spectrum compensation, this method not only acquires the capacity of BESS accurately, but also improves the effect to smoothing power fluctuation of PV effectively. Finally, a case is proposed to verify correctness of the theory.
关键词： Sizing energy storage capacity,Empirical mode decomposition (EMD),Wavelet analysis,Photovoltaic output
更新于2025-09-12 10:27:22
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Discrete Wavelet Transform (DWT) Assisted Partial Least Square (PLS) Analysis of Excitation-Emission Matrix Fluorescence (EEMF) Spectroscopic Data Sets: Improving the Quantification Accuracy of EEMF Technique
摘要： In the present work, it is shown that quantitative estimation efficiency of the partial least square (PLS) calibration model can be significantly improved by pre-processing the EEMF with discrete wavelet transform (DWT) analysis. The application of DWT essentially reduces the volume of data sets retaining all the analytically relevant information that subsequently helps in establishing a better correlation between the spectral and concentration data matrices. The utility of the proposed approach is successfully validated by analyzing the dilute aqueous mixtures of four fluorophores having significant spectral overlap with each other. The analytical procedure developed in the present study could be useful for analyzing the environmental, agricultural, and biological samples containing the fluorescent molecules at low concentration levels.
关键词： Partial least square analysis,Discrete wavelet analysis,Fluorophores,Wavelet analysis,Excitation-emission matrix fluorescence
更新于2025-09-09 09:28:46
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[SPIE Biomedical Applications in Molecular, Structural, and Functional Imaging - Houston, United States (2018.2.10-2018.2.15)] Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging - Automatic quantification framework to detect cracks in teeth
摘要： Studies show that cracked teeth are the third most common cause for tooth loss in industrialized countries. If detected early and accurately, patients can retain their teeth for a longer time. Most cracks are not detected early because of the discontinuous symptoms and lack of good diagnostic tools. Currently used imaging modalities like Cone Beam Computed Tomography (CBCT) and intraoral radiography often have low sensitivity and do not show cracks clearly. This paper introduces a novel method that can detect, quantify, and localize cracks automatically in high resolution CBCT (hr-CBCT) scans of teeth using steerable wavelets and learning methods. These initial results were created using hr-CBCT scans of a set of healthy teeth and of teeth with simulated longitudinal cracks. The cracks were simulated using multiple orientations. The crack detection was trained on the most significant wavelet coefficients at each scale using a bagged classifier of Support Vector Machines. Our results show high discriminative specificity and sensitivity of this method. The framework aims to be automatic, reproducible, and open-source. Future work will focus on the clinical validation of the proposed techniques on different types of cracks ex-vivo. We believe that this work will ultimately lead to improved tracking and detection of cracks allowing for longer lasting healthy teeth.
关键词： High-resolution Cone Beam Computed Tomography,Machine learning,Wavelet analysis,Tooth fracture detection
更新于2025-09-09 09:28:46
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Wavelet Method for Automatic Detection of Eye-Movement Behaviors
摘要： With the rapid development of eye tracking technology, eye movements have become more and more important in human-computer interaction. Generally, eye movements are classified into fixation, saccade and smooth pursuit. Since the eye movements are natural and fast, contain important cues for human cognitive state and visual attention, the eye movement behaviors are difficult to detect and classify. In this study, the novel eye-movement data filtering and eye-movement classification algorithm are proposed. The nonlinear wavelet threshold denoising method was used to the eye-movement data and detect saccades in the presence of smooth pursuit movements, according to different eye-movement behaviors related to the different characteristics of wavelet detail coefficients. Experiments were conducted to compare the eye-movement signal analyzing algorithm based on wavelet with other algorithms. The results showed that the eye-movement data filtering algorithm based on wavelet performed better than the other eye-movement filters. Moreover, the classification algorithm based on wavelet can classify different eye-movement behaviors more accurately. Then we used eye tracking technology to record and analyze the user’s eye movement during the test, so as to get the user's psychological and cognitive state.
关键词： Wavelet analysis,Eye tracking,Eye-Movement Detection and Classification
更新于2025-09-04 15:30:14
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Determination of Degree of Damage on Building Roofs Due to Wind Disaster from Close Range Remote Sensing Images Using Texture Wavelet Analysis
摘要： In the current era of increasing natural disasters, especially wind disasters such as tropical cyclones, tornadoes, thunder storms etc., the need for a rapid damage assessment and mitigation action became inevitable. Detecting damages on a wider perspective using remote sensing images makes the damage investigation much faster. The current work introduces the technology of texture-wavelet analysis for detection of roof damages due to cyclones and tornadoes from close range remote sensing imageries. Degree of Damage (DoD) is quantified by calculating the percentage of damaged portion of the building roofs. A positive correlation factor ranging from 0.75 to 0.80 for remote imagery with respect to the visually measured data as well as field investigation data validates the accuracy of the method. Thus depending on severity measured from the percentage area of damage determined, emergency aid and medication can be prioritized thereby aiding disaster mitigation process.
关键词： Degree of Damage,Remote Sensing Images,Natural Disaster,Texture-Wavelet analysis,Correlation Factor
更新于2025-09-04 15:30:14