The Frequency Spectrum and Time Frequency Analysis of Different Violins Classification as Tools for Selecting a Good-Sounding Violin

This work evaluates four violins from three distinct manufacturers, notably Eurostring, Stentor, and Suzuki, using a scientific approach. Eurostring1 and Eurostring2 were the names given to the two Eurostring units. The purpose of this study is to identify elements in various violins that could be used as tools for selecting a pleasantsounding violin by having them classified by a professional violinist. The signal’s time varying frequency was evaluated using a frequency spectrum and a time frequency plane, and the combination of frequency spectrum and time frequency domain is utilised. PicoScope oscilloscopes and Adobe Audition version 3 were used to record the acoustic spectra in terms of time and frequency. The time frequency plane is identified, and time frequency analysis (TFA) is produced by Adobe Audition spectrograms. The sound was processed in order to generate Fast Fourier Transform analysis: Fourier spectra (using PicoScope) and spectrograms (using Adobe Audition). Fourier spectra identify the intensity of the fundamental frequency and the harmonic spectra of the overtone frequencies. The highest frequencies that can be read are up to and including the 9th overtone. All violins have a constant harmonic overtone pattern with an uneven acoustic spectrum pattern. Eurostring1 showed inconsistent signal in the string G with 6th and 7th overtone missing, whereas Eurostring2 lack of the 6th overtone. Among the string D, only Eurostring1 display an exponential decay for the overtone. All the string A except for Suzuki showed nice and significant peak of fundamental and overtone. Stentor displays up to the 5th overtone. Among the string E, Suzuki showed inconsistent harmonic peak intensity. TFA revealed that the fundamental frequency of string E for Eurostring1 was lower than the first overtone. Only Eurostring1 has an uneven decay for the overtone frequency, whereas Eurostring2 exhibits a large exponential decay for the overtone frequency.

Download Full-text

Fundamental frequency estimation based on the joint time-frequency analysis of harmonic spectral structure

IEEE Transactions on Speech and Audio Processing ◽

10.1109/89.943339 ◽

2001 ◽

Vol 9 (6) ◽

pp. 609-621 ◽

Cited By ~ 22

Author(s):

Der-Jenq Liu ◽

Chin-Teng Lin

Keyword(s):

Fundamental Frequency ◽

Frequency Analysis ◽

Frequency Estimation ◽

Spectral Structure ◽

Time Frequency Analysis ◽

Time Frequency ◽

Fundamental Frequency Estimation

Download Full-text

An Investigation of Tooth Wear Diagnosis of Gear Based on Process Systems Modeling

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.549.834 ◽

2012 ◽

Vol 549 ◽

pp. 834-838

Author(s):

Feng Li Wang ◽

Hui Xing

Keyword(s):

Energy Distribution ◽

Frequency Spectrum ◽

Frequency Analysis ◽

Vibration Signal ◽

Tooth Wear ◽

Time Frequency Analysis ◽

Time Frequency ◽

Gear Fault ◽

Local Wave ◽

Instantaneous Energy

Targeting the advantages of local wave analysis(LWA) and the characteristics of gear fault vibration signals, LWA is introduced into gear fault diagnosis. The concept of the instantaneous energy in time- frequency analysis, based on local wave time-frequency spectrum, was used to measure the energy distribution of the signal in time-frequency domain. Furthermore, when tooth wear occurs in gear, the energy of the gear vibration signal would change correspondingly, whilst local wave time-frequency spectrum can exactly provide the instantaneous energy distribution of the signal with the change of the time and frequency. Thus, the fault information of the gear vibration signal can be extracted effectively from the local wave time-frequency spectrum. The analysis results from the experimental signals show that local wave time-frequency analysis could extract the characteristics information of the gear fault vibration signal effectively.

Download Full-text