ESD Affected GMR Head Detection by Using Machine Model: Wavelet Transform Technique Approach

2009 ◽  
Vol 152-153 ◽  
pp. 443-446
Author(s):  
N. Suwannata ◽  
D. Sompongse ◽  
P. Rakpongsiri ◽  
Apirat Siritaratiwat
Keyword(s):  
Wavelet Transform ◽  
Time Domain ◽  
Response Signal ◽  
Machine Model ◽  
Recording Head ◽  
Test Parameter ◽  
Recording Heads ◽  
Head Detection ◽  
Magnetic Recording Head ◽  
The Time Domain

This report proposes the wavelet transform technique using the 4th Daubechies order to detect glitches on a magnetic recording head signal in the time-domain. It is found that the glitch occurs when the electrostatic discharged (ESD) level of the machine model (MM) on giant magnetoresistive (GMR) heads is in the range of 6-9 V. The electrical test parameter and scanning electron microscope (SEM) photograph of recording heads shows no change in reader sensor. However, the parameter and SEM results clearly show the visible GMR damage when the MM-ESD voltage (VESD) is 10 V. The glitch in magnetic response signal of the GMR head occurs when the VESD is increased. Therefore, the wavelet transform technique can be a novel instrument to forecast the GMR degradation due to the MM-ESD effect.

ELECTROSTATIC DISCHARGE EFFECTS ON GMR RECORDING HEADS USING A WAVELET TRANSFORM APPROACH

2009 ◽  
Vol 23 (17) ◽  
pp. 3567-3572
Author(s):  
NATTAWOOT SUWANNATA ◽  
APIRAT SIRITARATIWAT
Keyword(s):  
Wavelet Transform ◽  
Frequency Domain ◽  
Electrostatic Discharge ◽  
Disk Drive ◽  
Human Body Model ◽  
Machine Model ◽  
Separate Model ◽  
Head Gimbal Assembly ◽  
Recording Heads ◽  
The Time Domain

Electrostatic Discharge (ESD) effects have been identified as one of the most dangerous causes of giant magnetoresistive (GMR) recording head damage. These phenomena have been studied at all levels of hard-disk drive manufacturing 1. The head gimbal assembly (HGA) is mainly studied because of its exposure to the environment. The standard models are typically based on the human body model (HBM), the machine model (MM) and the charged device model (CDM) where research and practical tests are incompatible. In production, one or more ESD models are normally effective while the other is undergone under a separate model. In addition, tests in the time domain are more accurate than those in the frequency domain. However, picosecond measurements are taken with difficulty where the frequency domain measurement provides non-real time results. Therefore, this is the first report of serial ESD detection using the new technique of wavelet transform. It has been found that the glitch occurs when the ESD level of HBM – MM and HBM – CDM serial ESD on GMR heads are in the ranges of 1.2-2.6 V and 12-15 V respectively.

Damage detection using wavelet entropy of acoustic emission waveforms in concrete under flexure

2020 ◽  
pp. 147592172095709
Author(s):  
Nitin Burud ◽  
JM Chandra Kishen
Keyword(s):  
Acoustic Emission ◽  
Wavelet Transform ◽  
Time Domain ◽  
Fracture Process ◽  
Damage Index ◽  
Relative Energy ◽  
Wavelet Entropy ◽  
Complex Fracture ◽  
The Time Domain ◽  
Entropy Formulation

This work dives into the spectral realm of acoustic emission waveforms. The acoustic emission waveforms carry a footprint of source, its mechanism, and the information of the medium through which it travels. The idiosyncrasies of these waveforms cannot be visualized from the time-domain parameters. The complex fracture process of the heterogeneous composite, such as concrete, reflects in the spectral disorder of acoustic emission signals. The use of wavelet entropy is proposed to estimate the spectral disorder. To evaluate wavelet entropy, the relative energy distribution in frequency sub-bands is determined using the wavelet transform. The Shannon entropy formulation as a wavelet entropy is utilized for discriminating spatiotemporally distributed acoustic emission events according to their respective level of disorder. The possible twofold application of the wavelet entropy as a signal discriminator and a damage index is qualitatively demonstrated. The increase in the statistical variance of wavelet entropy distribution with the increase in stress level reveals the presence of multi-sources as well as multi-mechanistic fracture process.

An algorithm for Morlet wavelet transform based on generalized discrete Fourier transform

2019 ◽  
Vol 17 (05) ◽  
pp. 1950030
Author(s):  
Hua Yi ◽  
Peichang Ouyang ◽  
Tao Yu ◽  
Tao Zhang
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Discrete Fourier Transform ◽  
Time Domain ◽  
Morlet Wavelet ◽  
Wavelet Function ◽  
Linear Convolution ◽  
Calculation Results ◽  
Morlet Wavelet Transform ◽  
The Time Domain

Continuous wavelet transform (CWT) is a linear convolution of signal and wavelet function for a fixed scale. This paper studies the algorithm of CWT with Morlet wavelet as mother wavelet by using nonzero-padded linear convolution. The time domain filter, which is a non-causal filter, is the sample of wavelet function. By making generalized discrete Fourier transform (GDFT) and inverse transform for this filter, we can get a geometrically weighted periodic extension of the filter when evaluated outside its original support. From this extension of the time domain filter, we can get a causal filter. In this paper, GDFT-based algorithm for CWT, which has a more concise form than that of linear convolution proposed by Jorge Martinez, is constructed by using this causal filter. The analytic expression of the GDFT of this filter, which is essential for GDFT-based algorithm for CWT, is deduced in this paper. The numerical experiments show that the calculation results of GDFT-based algorithm are stable and reliable; the running speed of GDFT-based algorithm is faster than that of the other two algorithms studied in our previous work.

Approximate Structural Response Characterization Using Parametric and Envelope Models for Multimodal Systems

1986 ◽  
Vol 108 (1) ◽  
pp. 39-43
Author(s):  
P. Davies ◽  
J. K. Hammond
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Structural Response ◽  
Parametric Models ◽  
Response Signal ◽  
Response Characteristics ◽  
Multimodal Systems ◽  
Time Domain Response ◽  
The Time Domain

In the study of the response of systems to an excitation there are circumstances when it is desirable to obtain some overall or average characterization of the system and its response rather than a detailed description. In this paper two methods are used to describe the overall features of the system: one appropriate for the frequency domain and one for the time domain. For modally dense systems the main features of the frequency response function are described in terms of low-order parametric models. While these models may be adequate for the frequency domain representation, they may not produce a good approximation to the response of the system in the time domain. The second approach relates the envelope of the input signal to the envelope of the response signal, in order to describe the overall time domain response characteristics.

Identification of Eggshell Crack using BPNN and GANN in Dynamic Frequency Analysis

2014 ◽  
Vol 10 (2) ◽  
pp. 301-306
Author(s):  
Zhenbo Wei ◽  
Jun Wang ◽  
Xiaojing Tian
Keyword(s):  
Frequency Response ◽  
Time Domain ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Maximum Magnitude ◽  
Piezoelectric Film ◽  
Fast Fourier Transform Algorithm ◽  
Response Signal ◽  
The Time Domain ◽  
Dynamic Frequency

Abstract The eggshell crack was detected using flexible piezoelectric film sensors on the basis of dynamic frequency response. The response signal was transformed from the time domain to the frequency domain using fast Fourier transform algorithm. In the normalized power spectrum, the first 10 and 20 features were extracted by interval frequency (IFM), maximum magnitude in turn (HVM), and frequencies by magnitude in turn (MVF). The discrimination between intact eggs and cracked eggs was performed using back-propagation neural network (BPNN) and combination of genetic algorithm and BPNN (GANN). The results were found that intact eggs and cracked eggs could be better identified from their dynamic frequency response using BPNN and GANN based on HVM and MVF. It is suggested that intact and cracked eggs can be distinguished using GANN based on 10 features in MVF.

Adaptive Digital Filtering and Its Algorithms for Acoustic Echo Canceling

2011 ◽  
pp. 225-285
Author(s):  
Mohammad Reza Asharif ◽  
Rui Chen
Keyword(s):  
Correlation Function ◽  
Wavelet Transform ◽  
Computational Complexity ◽  
Frequency Domain ◽  
Time Domain ◽  
Digital Filtering ◽  
Wiener Filtering ◽  
Acoustic Echo ◽  
The Time Domain ◽  
New System

In this chapter, we shall study adaptive digital filtering (ADF) and its application to acoustic echo canceling (AEC). At first, Wiener filtering and algorithms such as LMS in the time domain for ADF are explained. Then, to decrease the computational complexity, the frequency domain algorithms such as FDAF and FBAF will be studied. To challenge the double-talk problem in AEC, we will also introduce various algorithms by processing the correlation function of the signal. The proposed algorithms here are CLMS, ECLMS, and using frequency domain is FECLMS, and using wavelet transform is WECLMS. Each of these algorithms has its own merits, and they will be evaluated. At the end of this chapter a new system for room-acoustic partitioning is proposed. This new system is called smart acoustic room (SAR). The SAR will also be used in AEC with double-talk condition. The authors wish to gather all aspects in studying ADF and their use in AEC by going very deep into theoretical details as well as considering more practical and feasible applications considering real-time implementation.

Application of Wavelet Analysis in the Virtual Measurement of Roundness/Cylindricalness for Shaft-Like Components

2008 ◽  
Vol 392-394 ◽  
pp. 69-73
Author(s):  
Li Zhi Gu ◽  
Chun Jiang Xiang
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Time Domain ◽  
Least Square Method ◽  
Virtual Manufacturing ◽  
Least Square ◽  
Time Saving ◽  
Individual Step ◽  
The Time Domain

Wavelet analysis was applied to detect the greatest deviation from the perfect circle for the roundness and cylindricalness of shaft-like components in the virtual manufacturing engineering. Based on the concepts of the roundness and cylindricalness, the least square method was adopted into the determination of the reference—the least square circle from which the deviation was calculated. In order to obtain the extremum of the errors, wavelet transform was carried out with binary wavelet from the time domain to frequency domain. A virtual probe was used to have the signals for the measured point by using WTnode_gettranslation() function. The accuracy of the measurement depends, to a large extent, on the length of individual step along the axis and the density of the measured points on the sections. Experiments have shown that the measuring processing was time-saving and the results from the wavelet analysis were much reliable.

scholarly journals Damping of inter-area oscillations by combining control strategies in hydropower plants

2021 ◽  
Author(s):  
Daniel Fank ◽  
Herwig Renner
Keyword(s):  
Time Domain ◽  
Control Strategies ◽  
Power System Stabilizer ◽  
Machine Model ◽  
Hydropower Plants ◽  
Single Machine Infinite Bus ◽  
The Time Domain ◽  
System Stabilizer ◽  
Water Hammer Effect ◽  
Damping Capability

AbstractThis paper examines how the damping capability can be improved if inter-area oscillations occur by combining control strategies in hydropower plants. First, the control challenges of hydropower plants, such as the water hammer effect, are discussed. In a single-machine infinite bus system (SMIBS), the use of a Power System Stabilizer (PSS) in the generator excitation and in the governor control path as well as the combination of both strategies are examined for their effectiveness in terms of their damping capability. In addition, these results are compared with an optimal state space controller with an observer as a damping element. The Heffron-Phillips model is the design model for the PSS as well as for the model-based controller. The verification of the damping capability through the PSS variants is evaluated by using a three-machine model in the time domain and by using modal analysis.

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