Principle Of Deconvolution Research Articles

Accurate detection method of voltage traveling-wave-based on waveform inversion

Aiming at the serous waveform distortion caused by the traveling wave passing through the voltage traveling wave sensor, an accurate method based on waveform inversion is proposed in order to accurately detect the voltage traveling wave. First, the transfer function model, which is suitable for the waveform inversion, is selected by analyzing the high frequency transmission characteristic and comparing the transfer function model. Second, the deconvolution principle is used to establish the inversion model, and stochastic resonance-deconvolution algorithm is used to solve the ill-conditioned problem. Finally, the inversion model is used to accurately invert the voltage traveling wave and to realize accurate waveform detection. The simulation and experimental results show that the proposed method can obtain accurate primary traveling wave from the measured secondary waveform, and it can effectively detect power grid voltage traveling wave. Compared with the results of traveling wave protection directly using secondary signals, it has higher reliability, which can promote the practical application of traveling-wave-based distance protection.

Kinetic study of the multistep thermal behaviour of barium titanyl oxalate prepared via chemical precipitation method

This study describes the physico-geometrical mechanism and overall kinetics for the multistep thermal dehydration of barium titanyl oxalate tetrahydrate (BTO). The thermal dehydration kinetics of BTO was studied at four different linear heating rates under non-isothermal conditions. The reaction kinetics was performed using differential scanning calorimetry (DSC) and the curves obtained were analysed using different isoconversional model-free equations and the values are found to be compatible with each other. The kinetic deconvolution principle is used for identifying the partially overlapped kinetic processes of the thermal dehydration of BTO, and it occurs in two stages. The overall reaction kinetics parameters calculated via kinetic deconvolution of the sample indicate the multistep nature of the process and the kinetic analysis of the non-isothermal data of this reaction model shows that the reaction is best described by Sestak–Berggren (m, n) empirical kinetic model. The prepared sample was identified and characterized by means of FT-IR, XRD, SEM, and TEM.

A new method for quantifying the nanoscale magnetic domains

Abstract In this work, a signal transformation method to quantitatively analyze fine magnetic structures in nanometer length scales measured by magnetic force microscopy has been developed. Nanosized magnetic domains, magnetic charges with reconstructed polarity as well as quantified magnetic field contours of samples (such as ordered FePt dot arrays, hard magnetic thin films and polycrystalline La0.7Sr0.3 MnO3 (LSMO) films ) were investigated based on the basic principles of deconvolution and micromagnetics. The present technique is crucial for the analysis of fine magnetic structures, and is important for the development of next generation magnetic recording industry.

Adaptive Minimum Entropy Equalization Algorithm

We employ minimum entropy deconvolution principle for blind equalization of complex digital signals. In essence, we maximize the output energy, constrain the equalizer output not to exceed certain level and obtain an adaptive solution capable of opening a closed-eye with the recovery of true energy of signal. We provide evidence of good performance in comparison to existing adaptive methods, like CMA and its variants, through simulations.

A study on the stacking fault in GaN crystals by high-resolution electron microscope imaging

The stacking fault in crystals of GaN was studied by high-resolution electron microscope images in combination with image deconvolution. The principle of deconvolution for high-resolution electron microscope images is briefly introduced. It is demonstrated that an image originally does not intuitively reflect the examined crystal structure can be transformed into the structure image. The stacking faults in crystals of GaN were observed with the high-resolution microscope. The image deconvolution was performed for the image, and the atomic configuration in the defect core is seen clearly in the deconvoluted image. Based on this, the type of stacking fault has been determined. Besides, the effectiveness of image deconvolution in studying crystal defects is discussed.

Analysis of Pressure/Flow-Rate Data With the Pressure-History-Recovery Method

Summary This study presents a new way to integrate flow rate history and pressure history data in well-test analysis. The method used is an extension of the deconvolution principle to a chosen period of time before the well test. It is based on the recovery of missing parts of the pressure history by taking into account the flow rate history and the available sections of measured pressure history. The method has the advantage of working without making any assumption about the reservoir by using the data itself to define the "model." A real example with 71 pressure points and 70 corresponding flow rate points shows how it is possible to recover the first 20 pressure points correctly considering that only the flow rate history and the last 51 pressure points are known. The main purpose of this procedure is to have an alternative to treat the problem of flow rate variations both before and during the well test. In such a case, neither the usual deconvolution (only applicable for flow rate variations during the well test, when flow rate and pressure are both known), nor the multirate superposition plots (which assume specific reservoir behavior) can be applied properly. In addition, the principle of the method enables us to extend its use to the analysis of well tests with pressure recording errors or missing pressure recording. Examples show that it is possible to make a good analysis of a well test with missing pressure regions when current methods give only parts of the information.

Principles of Practical Advantages and Limitations of Light Microscopic 3d Deconvolution

There has been much provocative discussion over the past few years about the advantages and limitations of deconvolution methods. In this tutorial we will provide a reasonable understanding of the underlying theoretical principles of deconvolution, with an aim at understanding expected advantages and limitations. These principles will be presented for a mixed audience composed of biologists, neuroscientists, engineers, physicists and other scientists and graduate students. These principles will be presented in the context of both widefield and confocal microscopy deconvolution.The basic principles of Fourier optics will be presented. From these principles, we can explain why it is that the confocal microscope provides a superior in-plane and axial (z-axis) resolving power, compared to the widefield microscope. In particular, for example, the Fourier transform of a 3D widefield image contains a missing cone region (to be explained in the tutorial), and this missing cone region effectively spoils the axial resolution of unprocessed widefield data.

Error analysis by simulation studies in renography deconvolution

The renogram, defined as the time-activity curve obtained from measurements with a gamma detector over the kidneys after a prior injection of a radioactive tracer, can be quantified using the deconvolution method. Essentially all the inherent information in the renogram, the estimated relative renal intake function and transit time spectrum through the kidney, can be derived from the computed renal retention function. This study shows how statistical and physiological noise and different backgrounds affect the accuracy of the derived parameters. Confidence intervals for the estimated relative renal function and mean transit time (MTT) are presented. The principal source of error in relative renal function was due to extrarenal background. It was found that the error in mean transit time due to statistical noise was proportional to MTT, that the presence of extrarenal background strongly affected the accuracy of the MTT, whereas the vascular background in the renogram was of minor importance. Physiological noise, interpreted as periodic changes in transit times does, strictly speaking, invalidate the deconvolution principle, but it was possible to calculate a valid mean value of the different actual transit times.