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Number of results: 6
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Abstract

The main purpose of the presented research is to investigate the partial discharge (PD) phenomenon variability under long-term AC voltage with particular consideration of the selected physical quantities changes while measured and registered by the acoustic emission method (AE). During the research a PD model source generating surface discharges is immersed in the brand new insulation mineral oil. Acoustic signals generated by the continuously occurred PDs within 168 hours are registered. Several qualitative and quantitative indicators are assigned to describe the PD variability in time. Furthermore, some longterm characteristics of the applied PD model source in mineral oil, are also presented according to acoustic signals emitted by the PD. Finally, various statistical tools are applied for the results analysis and presentation. Despite there are numerous contemporary research papers dealing with long-term PD analysis, such complementary and multiparametric approach has not been presented so far, regarding the presented research. According to the presented research from among all assigned indicators there are discriminated descriptors that could depend on PD long-term duration. On the grounds of the regression models analysis there are discovered trends that potentially allow to apply the results for modeling of the PD variability in time using the acoustic emission method. Subsequently such an approach may potentially support the development and extend the abilities of the diagnostic tools and maintenance policy in electrical power industry.
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Abstract

Although the emotions and learning based on emotional reaction are individual-specific, the main features are consistent among all people. Depending on the emotional states of the persons, various physical and physiological changes can be observed in pulse and breathing, blood flow velocity, hormonal balance, sound properties, face expression and hand movements. The diversity, size and grade of these changes are shaped by different emotional states. Acoustic analysis, which is an objective evaluation method, is used to determine the emotional state of people’s voice characteristics. In this study, the reflection of anxiety disorder in people’s voices was investigated through acoustic parameters. The study is a case-control study in cross-sectional quality. Voice recordings were obtained from healthy people and patients. With acoustic analysis, 122 acoustic parameters were obtained from these voice recordings. The relation of these parameters to anxious state was investigated statistically. According to the results obtained, 42 acoustic parameters are variable in the anxious state. In the anxious state, the subglottic pressure increases and the vocalization of the vowels decreases. The MFCC parameter, which changes in the anxious state, indicates that people can perceive this situation while listening to the speech. It has also been shown that text reading is also effective in triggering the emotions. These findings show that there is a change in the voice in the anxious state and that the acoustic parameters are influenced by the anxious state. For this reason, acoustic analysis can be used as an expert decision support system for the diagnosis of anxiety.
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Abstract

A computer measurement system, designed and built by authors, dedicated to location and description of partial discharges (PD) in oil power transformers examined by means of the acoustic emission (AE) method is presented. The measurement system is equipped with 8 measurement channels and ensures: monitoring of signals, registration of data in real time within a band of 25–1000 kHz in laboratory and real conditions, basic and advanced analysis of recorded signals. The basic analysis carried out in the time, frequency and time-frequency domains deals with general properties of the AE signals coming from PDs. The advanced analysis, performed in the discrimination threshold domain, results in identification of signals coming from different acoustic sources as well as location of these sources in the examined transformers in terms of defined by authors descriptors and maps of these descriptors on the side walls of the tested transformer tank. Examples of typical results of laboratory tests carried out with the use of the built-in measurement system are presented.
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Abstract

The purpose of this work is to distinguish between Acoustic Emission (AE) signals coming from mechanical friction and AE signals coming from concrete cracking, recorded during fourteen seismic simulations conducted with the shaking table of the University of Granada on a reinforced concrete slab supported on four steel columns. To this end, a particular criterion is established based on the Root Mean Square of the AE waveforms calculated in two different temporal windows. This criterion includes a parameter calculated by optimizing the correlation between the mechanical energy dissipated by the specimen (calculated by means of measurements with accelerometers and displacement transducers) and the energy obtained from the AE signals recorded by low-frequency piezoelectric sensors located on the specimen. The final goal of this project, initiated four years ago, is to provide a reliable evaluation of the level of damage of Reinforced Concrete specimens by means of AE signals to be used in future Structural Health Monitoring strategies involving RC structures.
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Abstract

This article discusses a system of recognition of acoustic signals of loaded synchronous motor. This software can recognize various types of incipient failures by means of analysis of the acoustic signals. Proposed approach uses the acoustic signals generated by loaded synchronous motor. A plan of study of the acoustic signals of loaded synchronous motor is proposed. Studies include following states: healthy loaded synchronous motor, loaded synchronous motor with shorted stator coil, loaded synchronous motor with shorted stator coil and broken coil, loaded synchronous motor with shorted stator coil and two broken coils. The methods such as FFT, method of selection of amplitudes of frequencies (MSAF-5), Linear Support Vector Machine were used to identify specific state of the motor. The proposed approach can keep high recognition rate and reduce the maintenance cost of synchronous motors.
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Abstract

It is assumed in the paper that the signals in the enclosure in a transient period are similar to a noise induced by vehicles, tracks, cars, etc. passing by. The components of such signals usually points out specific dynamic processes running during the observation or measurements. In order to choose the best method of analysis of these phenomena, an acoustic field in a closed space with a sound source inside is created. Acoustic modes of this space influence the sound field. Analytically, the modal analyses describe the above mentioned phenomena. The experimental measurements were conducted in the room that might comprise the closed space with known boundary conditions and the sound source Brüel & Kjær Omni-directional type 4292 inside. To record sound signals before the field's steady state was reached, the microphone type 4349 and the 4-channel frontend 3590 had been used. The obtained signals have been analysed by using two approaches, i.e. Fourier and the wavelet analysis, with the emphasis on their efficiency and the capability to recognise important details of the signal. The results obtained for the enclosure might lead to the formulation of a methodology for an extended investigation of a rail track or vehicles dynamics.
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