다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

https://opus.lib.uts.edu.au/bitstream/10453/114834/4/OCC-90253_AM.pdf

A review of clustering techniques and developments

Time--frequency feature representation using energy concentration: An overview of recent advances

Requirement of green supply with higher quality has been consumers’ demand around the globe The electrical power system is expected to deliver undistorted sinusoidal rated voltage and current continuously at rated frequency to the consumers This paper presents a comprehensive review of signal processing and intelligent techniques for automatic classification of the power quality (PQ) events and an effect of noise on detection and classification of disturbances It is intended to provide a wide spectrum on the status of detection and classification of PQ disturbances as well as an effect of noise on detection and classification of PQ events to the researchers, designers and engineers working on power quality More than 150 research publications on detection and classification techniques of PQ disturbances have been critically examined, classified and listed for quick reference

A critical review of detection and classification of power quality events

Recent Trends in the Condition Monitoring of Transformers

In this work a new approach based on cross-wavelet transform towards identification of noisy Partial Discharge (PD) patterns has been proposed. Different partial discharge patterns are recorded from the various samples prepared with known defects. A novel cross-wavelet transform based technique is used for feature extraction from raw noisy partial discharge signals. Noise is a significant problem in PD detection. The proposed method eliminates the requirement of denoising prior to processing and therefore it can be used to develop an automated and intelligent PD detector that requires minimal human expertise during its operation and analysis. A rough-set theory (RST) based classifier is used to classify the extracted features. Results show that the partial discharge patterns can be classified properly from the noisy waveforms. The effectiveness of the feature extraction methodology has also been verified with two other commonly used classification techniques: Artificial Neural Network (ANN) based classifier and Fuzzy classifier. It is found that the type of defect within insulation can be classified efficiently with the features extracted from cross-wavelet spectra of PD waveforms by all of these methods with a reasonable degree of accuracy.

/pdf/cross-wavelet-transform-as-a-new-paradigm-for-feature-2vhqey69zl.pdf

Cross-wavelet transform as a new paradigm for feature extraction from noisy partial discharge pulses

The present work represents a methodology to detect the location of single as well as multiple Partial Discharge (PD) sources by optical method and to investigate the performance of optical sensors for this purpose. An experimental setup has been arranged in the laboratory for generation of PDs, optical sensing and analysis of the recorded signals obtained from multiple optical sensors. The analysis results prove the effectiveness of the methodology using optical sensors to find whether PD is occurring at single location or multiple locations. For identification of PD locations pattern recognition technique has been utilized by considering the received optical energy as a feature. For feature selection and classification two techniques have been evaluated, viz. Gaussian Mixture Model (GMM) and Support Vector Machine (SVM), and both have shown promising performance. SVM in regression mode was used for identification of unknown PD location/locations. In this case average accuracy obtained was 92.6% when PD is occurring at one location and 80.1% when PD is occurring at two locations. The obtained results indicate that, the proposed methodology can be used to locate partial discharges in high voltage equipment where the optical signals due to discharges find a path to get radiated towards the outer surface.

A methodology for identification and localization of partial discharge sources using optical sensors

Accumulation of interfacial space charge in oil-paper interface is a critical issue in insulation diagnostics of transformers. This interfacial charge mainly accumulates due to the conductivity difference of oil and paper. Accumulation of interfacial charge leads to localized field enhancement, which further leads to partial discharges and acceleration in the aging of insulation. Therefore, from the point of view of transformer insulation diagnostics, assessment of interfacial charge is very important. However, it is not easy to estimate interfacial space charge behavior from the transformer diagnostics methods currently in use. In case of Polarization-Depolarization Current (PDC) measurement, a well known method for transformer condition monitoring, the effect of interfacial charge is reflected in the non-linearity of current response during polarization and de-polarization. During de-polarization process, a part of the interfacial charge accumulated during polarization period is absorbed by the electrodes producing a current, which is difficult to separate using conventional linear dielectric theory. In this paper, an attempt has been made to separate this current component from de-polarization current through considering charge de-trapping mechanism. Terming this current component as de-trapping current, its relationship with other parameters of transformer insulation is discussed. The developed methodology has been applied on several practical transformers. It was observed that the time constant of de-trapping current is related to the paper conductivity, oil conductivity, dissipation factor and age of the insulation.

Assessment of interfacial charge accumulation in oil-paper interface in transformer insulation from polarization-depolarization current measurements

The presence of insulation failure in the transformer winding is detected using the voltage and current oscillograms recorded during the impulse test. Fault diagnosis in transformers has several parameters such as the severity of fault, the kind of fault and the location of the fault. Detection of major faults involving a large section of the coils have never been a big issue and several visual and computational methods have already been proposed by several researchers. The present paper describes an expert system based on re-confirmative method for the diagnosis of minor insulation failures involving small number of turns in transformers during impulse tests. The proposed expert system imitates the performance of an experienced testing personnel. To identify and locate a fault, an inference engine is developed to perform deductive reasoning based on the rules in the knowledge base and different statistical techniques. The expert system includes both the time-domain and frequency-domain analyses for fault diagnosis. The basic aim of the expert system is to provide a non-expert with the necessary information and interaction in order to make fault diagnosis in a friendly windowed environment. The rules for fault diagnosis have been so designed that these are valid for the range of power transformers used in practice up to a voltage level of 33 kV. The fault diagnosis algorithm has been tested using experimental results obtained for a 3 MVA transformer and simulation results obtained for 5 and 7 MVA transformers.

/pdf/time-and-frequency-domain-analyses-based-expert-system-for-16d9h2mbmo.pdf

Sivaji Chakravorti

Papers

Recent Trends in the Condition Monitoring of Transformers

Cross-wavelet transform as a new paradigm for feature extraction from noisy partial discharge pulses

A methodology for identification and localization of partial discharge sources using optical sensors

Assessment of interfacial charge accumulation in oil-paper interface in transformer insulation from polarization-depolarization current measurements

Time and frequency domain analyses based expert system for impulse fault diagnosis in transformers