HOC Based Blind Identification of Hydroturbine Shaft Volterra System
In order to identify the quadratic Volterra system simplified from the hydroturbine shaft system, a blind identification method based on the third-order cumulants and a reversely recursive method are proposed. The input sequence of the system under consideration is an unobservable independent identi...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2017/6732704 |
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| _version_ | 1832560640369098752 |
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| author | Bing Bai Lixiang Zhang |
| author_facet | Bing Bai Lixiang Zhang |
| author_sort | Bing Bai |
| collection | DOAJ |
| description | In order to identify the quadratic Volterra system simplified from the hydroturbine shaft system, a blind identification method based on the third-order cumulants and a reversely recursive method are proposed. The input sequence of the system under consideration is an unobservable independent identically distributed (i.i.d.), zero-mean and non-Gaussian stationary signal, and the observed signals are the superposition of the system output signal and Gaussian noise. To calculate the third-order moment of the output signal, a computer loop judgment method is put forward to determine the coefficient. When using optimization method to identify the time domain kernels, we combined the traditional optimization algorithm (direct search method) with genetic algorithm (GA) and constituted the hybrid genetic algorithm (HGA). Finally, according to the prototype observation signal and the time domain kernel parameters obtained from identification, the input signal of the system can be gained recursively. To test the proposed method, three numerical experiments and engineering application have been carried out. The results show that the method is applicable to the blind identification of the hydroturbine shaft system and has strong universality; the input signal obtained by the reversely recursive method can be approximately taken as the random excitation acted on the runner of the hydroturbine shaft system. |
| format | Article |
| id | doaj-art-fb24488892604bf6a4284f0e28dde93b |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-fb24488892604bf6a4284f0e28dde93b2025-02-03T01:27:11ZengWileyShock and Vibration1070-96221875-92032017-01-01201710.1155/2017/67327046732704HOC Based Blind Identification of Hydroturbine Shaft Volterra SystemBing Bai0Lixiang Zhang1School of Civil Engineering and Communication, North China University of Water Resources & Electric Power, Beihuan Road No. 36, Zhengzhou, Henan 450045, ChinaDepartment of Engineering Mechanics, Kunming University of Science and Technology, South Jingming Road No. 727, Kunming, Yunnan 650500, ChinaIn order to identify the quadratic Volterra system simplified from the hydroturbine shaft system, a blind identification method based on the third-order cumulants and a reversely recursive method are proposed. The input sequence of the system under consideration is an unobservable independent identically distributed (i.i.d.), zero-mean and non-Gaussian stationary signal, and the observed signals are the superposition of the system output signal and Gaussian noise. To calculate the third-order moment of the output signal, a computer loop judgment method is put forward to determine the coefficient. When using optimization method to identify the time domain kernels, we combined the traditional optimization algorithm (direct search method) with genetic algorithm (GA) and constituted the hybrid genetic algorithm (HGA). Finally, according to the prototype observation signal and the time domain kernel parameters obtained from identification, the input signal of the system can be gained recursively. To test the proposed method, three numerical experiments and engineering application have been carried out. The results show that the method is applicable to the blind identification of the hydroturbine shaft system and has strong universality; the input signal obtained by the reversely recursive method can be approximately taken as the random excitation acted on the runner of the hydroturbine shaft system.http://dx.doi.org/10.1155/2017/6732704 |
| spellingShingle | Bing Bai Lixiang Zhang HOC Based Blind Identification of Hydroturbine Shaft Volterra System Shock and Vibration |
| title | HOC Based Blind Identification of Hydroturbine Shaft Volterra System |
| title_full | HOC Based Blind Identification of Hydroturbine Shaft Volterra System |
| title_fullStr | HOC Based Blind Identification of Hydroturbine Shaft Volterra System |
| title_full_unstemmed | HOC Based Blind Identification of Hydroturbine Shaft Volterra System |
| title_short | HOC Based Blind Identification of Hydroturbine Shaft Volterra System |
| title_sort | hoc based blind identification of hydroturbine shaft volterra system |
| url | http://dx.doi.org/10.1155/2017/6732704 |
| work_keys_str_mv | AT bingbai hocbasedblindidentificationofhydroturbineshaftvolterrasystem AT lixiangzhang hocbasedblindidentificationofhydroturbineshaftvolterrasystem |