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Article . 2022
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Electrical and Mechanical Characteristics Assessment of Wind Turbine System Employing Acoustic Sensors and Matrix Converter

Authors: Thiyagarajan Rameshkumar; Perumal Chandrasekar; Raju Kannadasan; Venkatraman Thiyagarajan; Mohammed H. Alsharif; James Hyungkwan Kim;

Electrical and Mechanical Characteristics Assessment of Wind Turbine System Employing Acoustic Sensors and Matrix Converter

Abstract

Permanent magnet synchronous generator (PMSG)-based wind turbine systems have a wide range of applications, notably, for higher-rated wind energy conversion systems (WECS). A WECS involves integrating several components to generate electrical power effectively on a large scale due to the advanced wind turbine model. However, it offers several glitches during operation due to various factors, notably, mechanical and electrical stresses. This work focuses on evaluating the mechanical and electrical characteristics of the WECS using two individual schemes. Firstly, wind turbines were examined to assess the vibrational signatures of the drive train components for different wind speed profiles. To apply this need, acoustic sensors were employed that record the vibration signals. However, due to substantial environmental impacts, several noises are logged with the observed signal from sensors. Therefore, this work adapted the acoustic signal and empirical wavelet transform (EWT) to assess the vibration frequency and magnitude to avoid mechanical failures. Further, a matrix converter (MC) with input filters was employed to enhance the efficiency of the system with reduced harmonic contents injected into the grid. The simulated results reveal that the efficiency of the matrix converter with input filter attained a significant scale of about 95.75% and outperformed the other existing converting techniques. Moreover, the total harmonic distortion (THD) for voltage and current were examined and found to be at least about 8.24% and 3.16%, respectively. Furthermore, the frequency and magnitude of the vibration signals show a minimum scale for low wind speed profile and higher range for medium wind profile rather than higher wind profile. Consolidating these results from both mechanical and electrical characteristics, it can be perceived that the combination of these schemes improves the efficiency and quality of generated power with pre-estimation of mechanical failures using acoustic signal and EWT.

Keywords

input filter, vibrational assessment, Environmental effects of industries and plants, TJ807-830, power quality, TD194-195, Renewable energy sources, Environmental sciences, acoustic sensors, empirical wavelet transform (EWT), matrix converter, GE1-350, acoustic sensors; empirical wavelet transform (EWT); matrix converter; input filter; power quality; vibrational assessment

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
gold