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Technique of ultra wideband radar target discrimination using natural frequencies and cumulant preprocessing

100%

Baev A. B. , Kuznetsov Y. V.

2004

tom Vol. 50, z. 4

605-616

A modification of ultra wideband aspect independent radar target discrimination method using fourth-order cumulant preprocessing is introduced. It based on the natural frequencies of the objects. The increasing of the accuracy of parameter estimation can be achieved if the correct choice of one-dimensional slice of 3-D fourth-order cumulant sequence is made. The usage of this technique with signature algorithm leads to the increasing of the true discrimination probability if the space of attributes includes the most informative parameters of the objects. The results of experimental research of the signals scattered by the scaled aircraft models by using the signature algorithm with fourth-order cumulant preprocessing are presented.

Identification of inability states of rotating subsystems of vehicles and machines

75%

Pająk M. , Lisjak D. , Kolar D.

Journal of KONES

2019

tom Vol. 26, No. 1

111--118

One of the most important subsystems of the vehicles and machines operating currently in industry and transportation are the rotating subsystems. During the subsystems operation, due to the forcing factors influence, the technical state of them is changing and the failure can occur. In order to avoid such a situation the technical state should be identified online. To do this the analysis of the subsystems vibrations is performed. The identified technical state should be considered in a context of the ability and different inability states. Therefore, the first step of the diagnostic procedure is the ability and different inability states identification. In the article, it is proposed to accomplish this goal by the vibrations analysis in time domain. The described research started with the vibration signals acquisition using the experimental stand. In this way, the vibration signals for ability and different inability states were obtained. Afterwards, the signals were divided into learning and testing data sets. For each signal from learning data set, several characteristics were calculated, and they selected the most significant among them. Using the selected characteristics, the signals from the testing data set were analysed. Thanks to it, the testing vibrations signals were counted among the signals collected on the rotating subsystem operating in ability or selected inability state. The result of the performed studies and the accuracy of the technical state of the tested system identification can be found at the end of the article.

Investigation on the applicability of the time domain analysis of discharges in gases for the defect identification at AC voltage

75%

Lühring U. , Wienold D. , Jenau F.

tom Vol. 2, No. 1

34--41

The partial discharge diagnosis is an established instrument for the condition assessment of high voltage insulations and equipment. Under AC voltage stress the phase resolved pattern is of great significance in order to become aware of the type of fault. As a result of the inapplicability for DC voltage stress, approaches for alternative interpretation techniques such as the time domain analysis of partial discharges were identified in recent investigations. In these different types of fault are taken into account as well as different insulating media. The purpose of this paper is to investigate whether an analysis of the pulse shape is also applicable for the defect identification under AC voltage stress. By focussing on gaseous insulating media, contact noise and surface discharges are emulated in ambient air, whereas corona discharges are emulated in ambient air and oxygen. A method for analysing discharges, occurring in the negative and the positive half-wave of the test voltage, is proposed and discussed.

Pitch period’s properties and the new method used for finding them

63%

Dulas J.

Przegląd Elektrotechniczny

2012

tom R. 88, nr 7a

297-300

This article describes the pitch’s periods interesting properties. These periods are included in each vowel and voiced consonant. It also describes the new method of pitch period finding and their duration counting. These parameters are very important elements of the automatic speech recognition algorithm worked out by the author.

Artykuł przedstawia interesujące właściwości okresów podstawowych tonu krtaniowego występującego we wszystkich samogłoskach i spółgłoskach dźwięcznych oraz nową metodę ich odnajdywania i wyznaczania ich długości. Poprawne odnajdywanie okresów podstawowych i wyznaczanie czasu ich trwania jest ważnym elementem algorytmu automatycznej identyfikacji słów opracowanego przez autora.