scholarly journals Identification of Crack Location in Beam Structures Using Wavelet Transform and Fractal Dimension

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Yong-Ying Jiang ◽  
Bing Li ◽  
Zhou-Suo Zhang ◽  
Xue-Feng Chen
Keyword(s):  
Fractal Dimension ◽  
Wavelet Transform ◽  
Mode Shape ◽  
Practical Importance ◽  
Estimation Method ◽  
Experimental Investigations ◽  
Complex Structures ◽  
Cracked Beam ◽  
Beam Structures ◽  
Crack Location

Identification of structural crack location has become an intensely investigated subject due to its practical importance. In this paper, a hybrid method is presented to detect crack locations using wavelet transform and fractal dimension (FD) for beam structures. Wavelet transform is employed to decompose the mode shape of the cracked beam. In many cases, small crack location cannot be identified from approximation signal and detailed signals. And FD estimation method is applied to calculate FD parameters of detailed signals. The crack locations will be detected accurately by FD singularity of the detailed signals. The effectiveness of the proposed method is validated by numerical simulations and experimental investigations for a cantilever beam. The results indicate that the proposed method is feasible and can been extended to more complex structures.

Benchmark of Damage Localisation Algorithms Using Mode Shape Data

2005 ◽  
Vol 293-294 ◽  
pp. 305-312 ◽  
Author(s):  
Joseph Morlier ◽  
F. Bos ◽  
P. Castera
Keyword(s):  
Signal Processing ◽  
Fractal Dimension ◽  
Wavelet Transform ◽  
Mode Shape ◽  
Crack Detection ◽  
Singularity Detection ◽  
Local Complexity ◽  
Noise Measurements ◽  
Signal Processing Methods ◽  
Shape Data

This paper presents a comparative study of three enhanced signal processing methods to locate damage on mode shape data. The first method called curvature mode shape is used as a reference. The second tool uses wavelet transform and singularity detection theory to locate damage. Finally we introduce the windowed fractal dimension of a signal as a tool to easily measure the local complexity of a signal. Our benchmark aims at comparing the crack detection using optimal spatial sampling under different severity, beam boundary conditions (BCs) and added noise measurements.

scholarly journals Geological Stratigraphy and Spatial Distribution of Microfractures over Costa Rica Convergent Margin, Central America – A Wavelet-Fractal Analysis

2016 ◽  
Author(s):  
Upendra K. Singh ◽  
Thinesh Kumar ◽  
Rahul Prajapati
Keyword(s):  
Fractal Dimension ◽  
Wavelet Transform ◽  
Costa Rica ◽  
Central America ◽  
Gamma Ray ◽  
Total Porosity ◽  
Discrete Wavelet ◽  
Mathematical Tool ◽  
Convergent Margin ◽  
Frequency Scale

Abstract. Identification of spatial variation of lithology, as a function of position and scale, is very critical job for lithology modelling in industry. Wavelet Transform (WT) is an efficacious and powerful mathematical tool for time (position) and frequency (scale) localization. It has numerous advantages over Fourier Transform (FT) to obtain frequency and time information of a signal. Initially Continuous Wavelet Transform (CWT) is applied on gamma ray logs of two different Well sites (Well-1039 & Well-1043) of Costa Rica Convergent Margin, Central America for identifications of lithofacies distribution and fracture zone later Discrete Wavelet Transform (DWT) applied to DPHI log signals to show its efficiency in discriminating small changes along the rock matrix irrespective of the instantaneous magnitude to represent the fracture contribution from the total porosity recorded. Further the data of the appropriate depths partitioned using above mathematical tools are utilized separately for WBFA. As consequences of CWT operation it is found that there are four major sedimentary layers terminated with a concordant igneous intrusion passing through both the wells. In addition of WBFA analysis, it is clearly understanding that the fractal dimension value is persistent in first sedimentary layers and the last gabbroic sill intrusions. Inconsistent value of fractal dimension is attributed to fracture dominant in intermediate sedimentary layers it is also validate through core analysis. Fractal Dimension values suggest that the sedimentary environments persisting in that well locations bears abundant shale content and of low energy environments.

Detection of Short-Circuited Turns in Transformer Vibration Signals using MUSIC-Empirical Wavelet Transform and Fractal Dimension

2021 ◽  
Author(s):  
Jose R. Huerta-Rosales ◽  
Martin Valtierra-Rodriguez ◽  
Juan P. Amezquita-Sanchez ◽  
David Granados-Lieberman
Keyword(s):  
Fractal Dimension ◽  
Wavelet Transform ◽  
Vibration Signals ◽  
Empirical Wavelet Transform

scholarly journals SOC Estimation of Lead Carbon Batteries Based on the Operating Conditions of an Energy Storage System in a Microgrid System

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 33
Author(s):  
Yuanyuan Chen ◽  
Zilong Yang ◽  
Yibo Wang
Keyword(s):  
Wavelet Transform ◽  
Energy Storage ◽  
Storage System ◽  
Estimation Method ◽  
Energy Storage System ◽  
Operating Conditions ◽  
Estimation Methods ◽  
Extend Kalman Filter ◽  
Practical Applications ◽  
Soc Estimation

The environment for practical applications of an energy storage system (ESS) in a microgrid system is very harsh, and therefore actual operating conditions become complex and changeable. In addition, the signal of the ESS sampling process contains a great deal of system and measurement noise, the sampled current fluctuates significantly, and also has high frequency. In this case, under such conditions, it is difficult to accurately estimate the state of charge (SOC) of the batteries in the ESS by common estimation methods. Therefore, this study proposes a compound SOC estimation method based on wavelet transform. This algorithm is very suitable for microgrid systems with large current, frequent fluctuating conditions, and high noise interference. The experimental results and engineering data show that the relative error of the method is 0.5%, which is much lower than the extend Kalman filter (EKF) based on wavelet transform.

A two-step damage identification approach for beam structures based on wavelet transform and genetic algorithm

Meccanica ◽  
2015 ◽  
Vol 51 (3) ◽  
pp. 635-653 ◽  
Author(s):  
Seyed Alireza Ravanfar ◽  
Hashim Abdul Razak ◽  
Zubaidah Ismail ◽  
S. J. S. Hakim
Keyword(s):  
Genetic Algorithm ◽  
Wavelet Transform ◽  
Damage Identification ◽  
Beam Structures ◽  
Identification Approach

On Blade Damping Technology Using Passive Piezoelectric Dampers

2012 ◽  
Author(s):  
Sebastian M. Schwarzendahl ◽  
Jaroslaw Szwedowicz ◽  
Marcus Neubauer ◽  
Lars Panning ◽  
Jörg Wallaschek
Keyword(s):  
Mode Shape ◽  
Mechanical Strain ◽  
Piezoelectric Element ◽  
Measured Data ◽  
Experimental Investigations ◽  
Response Functions ◽  
Ambient Conditions ◽  
Optimal Position ◽  
Measured Frequency Response ◽  
Good Agreement

This paper deals with a new damping concept for turbine blade vibrations utilizing piezoelectric material. A passive piezo damper consists of a piezoelectric element and a passive electric network connected to its electrodes. The damping performance depends on the size and location of the piezoelectric element with respect to the mode shape of the mechanical strain. Numerical and experimental investigations are carried out on a rigidly clamped simplified compressor blade at stand still and ambient conditions. An optimization process incorporating electromechanical finite element calculations determines the optimal position of the piezo damper in regard to the mode shape of interest. By applying the computed and measured Frequency Response Functions, the damping performance with and without piezo-damper are compared and referred to the measured material damping. The obtained numerical results are in very good agreement with the measured data, leading to a promising damping performance in real application.

Study on Method to Extract Feature Parameter of Wear Particle Group in Ferrographic Image for the Diesel Engine Lubricants

2011 ◽  
Vol 55-57 ◽  
pp. 1530-1534
Author(s):  
Hong Zhi Wang ◽  
Guo Bin Li ◽  
De Lin Guan
Keyword(s):  
Fractal Dimension ◽  
Wavelet Transform ◽  
Diesel Engine ◽  
Fractal Theory ◽  
Wear Test ◽  
Wear Particle ◽  
Feature Parameter ◽  
Marine Diesel ◽  
Nano Lubricant ◽  
Particle Group

According to the consistency between multi-scale decompositions and self-similarity in both wavelet transform and fractal theory, a new method has been developed to extract the feature parameter of wear particle group on the ferrographic image for diesel engine lubricants. The algorithm of minutiae extraction have been carried out by wavelet transform approach and the fractal dimension, and then the feature parameter can be obtained for the wear particle group on the ferrographic image. The fractal dimension D reflects the ferrographic image character in the scale and the amount of wear particle group, which can be used as a comprehensive feature parameter. The metal-ceramic nano-lubricant, which has been applied in the wear test of cylinder and piston-ring material from MAN B&WS50MC marine diesel engine, represent that the wear is speedup suitably, and then the fractal dimension D has consistency with the results of ferrographic analysis.

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