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Vibration Based Gear Fault Diagnosis under Empirical Mode Decomposition and Power Spectrum Density Analysis

Akram M. Ammar, Khushnood Shahab, Tariq Syeda Laraib, Ali Hafiz Muhammad, Nizam Luqman Ahmad

Advances in Science and Technology. Research Journal

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2019

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Vol. 13, no 3

192--200

EN

Rotating machinery plays a significant role in industrial applications and covers a wide range of mechanical equipment. A vibration analysis using signal processing techniques is generally conducted for condition monitoring of rotary machinery and engineering structures in order to prevent failure, reduce maintenance cost and to enhance the reliability of the system. Empirical mode decomposition (EMD) is amongst the most substantial non-linear and non-stationary signal processing techniques and it has been widely utilized for fault detection in rotary machinery. This paper presents the EMD, time waveform and power spectrum density (PSD) analysis for localized spur gear fault detection. Initially, the test model was developed for the vibration analysis of single tooth breakage of spur gear at different RPMs and then specific fault was introduced in driven gear under different damage conditions. The data, recorded by means of a wireless tri-axial accelerometer, was then analyzed using EMD and PSD techniques and the results were plotted. The results depicted that EMD algorithms are found to be more functional than the ordinarily used PSD and time waveform techniques.

2

The time and power spectrum density analysis of different lightning components based on electric field waveforms from 2014 thunderstorm season recorded in the south-eastern part of Poland

Karnas G., Barański P., Masłowski G., Sobolewski K.

Przegląd Elektrotechniczny

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2016

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R. 92, nr 2

144--147

EN

This paper is focused on the Power Spectrum Density analysis of the lightning electric field signatures collected in Subcarpathian part of Poland, in 2014. Lightning records were carried out in two different ways. The slow electric field sensor (TLF-ELF), the mill, was used for observation of lightning activity during entire thunderstorm lifetime. The second recording mode was the acquisition of fast electric field changes (0.3 Hz to 3 MHz) associated with different types of cloud-to-ground (CG) and inter-, intra-cloud (IC) type discharges. The registration process was synchronized with microsecond time precision. This allowed to relate lightning stroke detections to these reported by the LINET, the commercial lightning location system. Different lightning stroke components, as e.g. the preliminary breakdown (PB), the return stroke (RS) and the continuing current (CC) were identified with application of the Short-Time Fourier Transform. The spectral analysis might be adapted to improve in future some detection algorithms used in lightning location systems. Such lightning CG stroke discrimination is not applied as yet by any lightning location system routinely operated in Europe.

PL

W artykule skupiono się na analizie spektrogramów widmowej gęstości mocy wyznaczonych dla różnych przebiegów piorunowego pola elektrycznego zebranych w południowo-wschodniej części Polski w 2014 roku. Dane zostały zebrane z wykorzystaniem dwóch sensorów pola elektrycznego. Sensor pola elektrycznego pracujący w zakresie TLF-ELF umożliwił obserwację aktywności burzowej w długofalowym okresie czasu. Drugi typ rejestracji obejmował akwizycję szybkich zmian pola elektrycznego (0.3 Hz do 3 MHz) pochodzących of różnych typów wyładowań doziemnych oraz wewnątrz-, między-chmurowych. Proces rejestracji został zsynchronizowany z mikrosekundową precyzją. Pozwoliło to na porównanie własnych rejestracji z detekcjami LINET-u – komercyjnego systemu lokalizacji wyładowań. Różne składowe wyładowania takie jak wyładowania wstępne, udar główny oraz prąd długotrwały zostały zidentyfikowane z wykorzystaniem krótkoczasowej transformaty Fouriera. Analiza spektralna może w przyszłości zostać wykorzystana w usprawnieniu algorytmów detekcji wyładowań. Taki rodzaj identyfikacji wyładowań doziemnych nie został jak dotąd zaimplementowany w żadnym systemie lokalizacji wyładowań atmosferycznych pracującym regularnie w obszarze Europy.

3

Spectral analysis by a video camera in a holographic optical tweezers setup

Drobczynski S, Dus-Szachniewicz K, Symonowicz K., Glogocka D

Optica Applicata

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2013

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Vol. 43, nr 4

739--746

EN

We discuss the basic parameters of the holographic tweezers equipped with a diode laser and cheap video camera. We compare these parameters with the system using a fast camera and high power Nd:YAG laser. The measured parameters are: the power spectra density calculated from tracing the position of the micron polystyrene beads and the trap stiffness. We show that this cheap optical tweezers system is sufficient for experiments in microbiology.

4

Intelligent identification of cutting states by utilising Power Spectrum Density

Tangjitsitcharoen S.

Journal of Achievements in Materials and Manufacturing Engineering

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2008

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Vol. 31, nr 2

580-587

EN

Purpose: This paper presents an in-process monitoring and identification of cutting states in turning process in order to realize the intelligent machine tools. Design/methodology/approach: The developed method utilizes the power spectrum density, or PSD of dynamic cutting force measured during the cutting. The experimentally obtained results suggested that there are basically three types of patterns of PSD when the cutting states are the continuous chip formation, the broken chip formation, and the chatter. The broken chip formation is desired to realize safe and reliable machining. The method proposed introduces three ratios, which are calculated and obtained by taking the ratios of cumulative PSD for a certain frequency range of three dynamic cutting force components corresponding to those three states of cutting, to classify the cutting states. The algorithm was developed to calculate the values of three ratios during the process in order to obtain the proper threshold values for classification of the cutting states. Findings: The method developed has been proved by series of cutting experiments that the states of cutting are well identified regardless of the cutting conditions. The broken chips are easily obtained by changing the cutting conditions during the processes referring to the algorithm developed. Practical implications: There are still not many systems being used in practice mainly due to the lack of general applicability such as a requirement of automated machining systems regardless of the cutting conditions. The aim of this research is to develop an in-process monitoring system for identification of continuous chip, broken chip, and chatter regardless of the cutting conditions by spectrum analysis based on the power spectrum density, or PSD of dynamic cutting force measured during the cutting. Originality/value: The largest potential advantage of the method proposed in this paper is that the states of cutting can be readily identified during the in-process cutting under any cutting conditions by simply mapping the experimentally obtained values of parameters referring to the proper threshold values in the reference feature spaces.

5

Identification of steam-water two-phase flow regimes in vertical upward tube

Bai B., Guo L., Zhao L.

Zeszyty Naukowe Politechniki Świętokrzyskiej. Mechanika

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1999

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Z. 67

173--183

EN

Both the fluctuating static pressures on the tube wall and the differential pressure fluctuation were measured to obtain the objective identification of steam-water two-phase flow regimes in a vertical upward tube of 20.0-mm interior diameter. The test pressures were 1.0MPa, 2.0MPa and 3.0MPa and the mass flux ranged from 100 to 900kg/m2s. The fluctuating mechanisms were studied by the statistical theory. The root mean square (RMS) of the pressure fluctuation can not be used to discriminate the flow regime transition under the condition of the high pressure, which was used successfully by Wambsganss in air-liquid loop. The frequency of differential pressure fluctuation ranged from 0 to 5 Hertz, and the shapes of the PDF and PSD concerned the various flow regimes. The flow regimes can be identified based on the RMS of the differential pressure fluctuation. The results by the method agreed well with the flow regimes provided by McQuillan and Whalley.