Modeling the Voltage Produced by Ultrasound in Seawater by Stochastic and Artificial Intelligence Methods
Experiments have proved that an electrical signal appears in the ultrasonic cavitation field; its properties are influenced by the ultrasound frequency, the liquid type, and liquid characteristics such as density, viscosity, and surface tension. Still, the features of the signals are not entirely kn...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/3/1089 |
| _version_ | 1797484689480482816 |
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| author | Alina Bărbulescu Cristian Ștefan Dumitriu |
| author_facet | Alina Bărbulescu Cristian Ștefan Dumitriu |
| author_sort | Alina Bărbulescu |
| collection | DOAJ |
| description | Experiments have proved that an electrical signal appears in the ultrasonic cavitation field; its properties are influenced by the ultrasound frequency, the liquid type, and liquid characteristics such as density, viscosity, and surface tension. Still, the features of the signals are not entirely known. Therefore, we present the results on modeling the voltage collected in seawater, in ultrasound cavitation produced by a 20 kHz frequency generator, working at 80 W. Comparisons of the Box–Jenkins approaches, with artificial intelligence methods (GRNN) and hybrid (Wavelet-ARIMA and Wavelet-ANN) are provided, using different goodness of fit indicators. It is shown that the last approach gave the best model. |
| first_indexed | 2024-03-09T23:08:00Z |
| format | Article |
| id | doaj.art-8f6e36e24ad74795aabfb5135aff45dd |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T23:08:00Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8f6e36e24ad74795aabfb5135aff45dd2023-11-23T17:50:19ZengMDPI AGSensors1424-82202022-01-01223108910.3390/s22031089Modeling the Voltage Produced by Ultrasound in Seawater by Stochastic and Artificial Intelligence MethodsAlina Bărbulescu0Cristian Ștefan Dumitriu1Department of Civil Engineering, Transylvania University of Brașov, 5 Turnului Str., 900152 Brasov, RomaniaDepartment of Installations for Constructions, Transylvania University of Brașov, 5 Turnului Str., 900152 Brasov, RomaniaExperiments have proved that an electrical signal appears in the ultrasonic cavitation field; its properties are influenced by the ultrasound frequency, the liquid type, and liquid characteristics such as density, viscosity, and surface tension. Still, the features of the signals are not entirely known. Therefore, we present the results on modeling the voltage collected in seawater, in ultrasound cavitation produced by a 20 kHz frequency generator, working at 80 W. Comparisons of the Box–Jenkins approaches, with artificial intelligence methods (GRNN) and hybrid (Wavelet-ARIMA and Wavelet-ANN) are provided, using different goodness of fit indicators. It is shown that the last approach gave the best model.https://www.mdpi.com/1424-8220/22/3/1089cavitationvoltageGeneralized Regression Neural Network (GRNN)autoregressive integrated moving average (ARIMA)Wavelet-ARIMAwavelet-artificial neural network (ANN) |
| spellingShingle | Alina Bărbulescu Cristian Ștefan Dumitriu Modeling the Voltage Produced by Ultrasound in Seawater by Stochastic and Artificial Intelligence Methods Sensors cavitation voltage Generalized Regression Neural Network (GRNN) autoregressive integrated moving average (ARIMA) Wavelet-ARIMA wavelet-artificial neural network (ANN) |
| title | Modeling the Voltage Produced by Ultrasound in Seawater by Stochastic and Artificial Intelligence Methods |
| title_full | Modeling the Voltage Produced by Ultrasound in Seawater by Stochastic and Artificial Intelligence Methods |
| title_fullStr | Modeling the Voltage Produced by Ultrasound in Seawater by Stochastic and Artificial Intelligence Methods |
| title_full_unstemmed | Modeling the Voltage Produced by Ultrasound in Seawater by Stochastic and Artificial Intelligence Methods |
| title_short | Modeling the Voltage Produced by Ultrasound in Seawater by Stochastic and Artificial Intelligence Methods |
| title_sort | modeling the voltage produced by ultrasound in seawater by stochastic and artificial intelligence methods |
| topic | cavitation voltage Generalized Regression Neural Network (GRNN) autoregressive integrated moving average (ARIMA) Wavelet-ARIMA wavelet-artificial neural network (ANN) |
| url | https://www.mdpi.com/1424-8220/22/3/1089 |
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