Stochastic noise identification in a stray current sensor

Abstract The Allan variance analysis method is used to identify the stochastic noise in the stray current sensor. The stray current characteristic is firstly introduced. Then the optical configuration and the signal processing method of the stray current sensor are illustrated. Moreover, the cause o...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Xu, Shao-yi [verfasserIn] Xing, Fang-fang Li, Wei Wang, Yu-Qiao

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	stochastic noise stray current optical fiber current sensor

Anmerkung:	© Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2017

Übergeordnetes Werk:	Enthalten in: Journal of Central South University of Technology - Changsha : CSUT, 1994, 24(2017), 11 vom: Nov., Seite 2596-2604
Übergeordnetes Werk:	volume:24 ; year:2017 ; number:11 ; month:11 ; pages:2596-2604

Links:	Volltext

DOI / URN:	10.1007/s11771-017-3673-8

Katalog-ID:	SPR022376186

Internformat


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520			\|a Abstract The Allan variance analysis method is used to identify the stochastic noise in the stray current sensor. The stray current characteristic is firstly introduced. Then the optical configuration and the signal processing method of the stray current sensor are illustrated. Moreover, the cause of the stochastic noise in the stray current sensor is analyzed. The calculation method of the stochastic noise coefficient is presented in detail. And the feasibility of the stochastic noise identification with the Allan variance analysis method is evaluated. Furthermore, the zero-drift signal acquisition experiment is conducted to identify the stochastic noise in the stray current sensor. According to the experimental result, the bias instability noise, the quantization noise and the white noise are identified as the major stochastic noise. Finally, the experiment on the direct-current signal acquisitions is conducted, whose results indicate that the signal drift of the measured direct-current is mainly caused by the major stochastic noise. And the suppression methods of the major stochastic noise are proposed.
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publishDate	2017
allfields	10.1007/s11771-017-3673-8 doi (DE-627)SPR022376186 (SPR)s11771-017-3673-8-e DE-627 ger DE-627 rakwb eng Xu, Shao-yi verfasserin aut Stochastic noise identification in a stray current sensor 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2017 Abstract The Allan variance analysis method is used to identify the stochastic noise in the stray current sensor. The stray current characteristic is firstly introduced. Then the optical configuration and the signal processing method of the stray current sensor are illustrated. Moreover, the cause of the stochastic noise in the stray current sensor is analyzed. The calculation method of the stochastic noise coefficient is presented in detail. And the feasibility of the stochastic noise identification with the Allan variance analysis method is evaluated. Furthermore, the zero-drift signal acquisition experiment is conducted to identify the stochastic noise in the stray current sensor. According to the experimental result, the bias instability noise, the quantization noise and the white noise are identified as the major stochastic noise. Finally, the experiment on the direct-current signal acquisitions is conducted, whose results indicate that the signal drift of the measured direct-current is mainly caused by the major stochastic noise. And the suppression methods of the major stochastic noise are proposed. stochastic noise (dpeaa)DE-He213 stray current (dpeaa)DE-He213 optical fiber current sensor (dpeaa)DE-He213 Xing, Fang-fang aut Li, Wei aut Wang, Yu-Qiao aut Enthalten in Journal of Central South University of Technology Changsha : CSUT, 1994 24(2017), 11 vom: Nov., Seite 2596-2604 (DE-627)531203670 (DE-600)2324899-3 1993-0666 nnns volume:24 year:2017 number:11 month:11 pages:2596-2604 https://dx.doi.org/10.1007/s11771-017-3673-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4753 AR 24 2017 11 11 2596-2604
spelling	10.1007/s11771-017-3673-8 doi (DE-627)SPR022376186 (SPR)s11771-017-3673-8-e DE-627 ger DE-627 rakwb eng Xu, Shao-yi verfasserin aut Stochastic noise identification in a stray current sensor 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2017 Abstract The Allan variance analysis method is used to identify the stochastic noise in the stray current sensor. The stray current characteristic is firstly introduced. Then the optical configuration and the signal processing method of the stray current sensor are illustrated. Moreover, the cause of the stochastic noise in the stray current sensor is analyzed. The calculation method of the stochastic noise coefficient is presented in detail. And the feasibility of the stochastic noise identification with the Allan variance analysis method is evaluated. Furthermore, the zero-drift signal acquisition experiment is conducted to identify the stochastic noise in the stray current sensor. According to the experimental result, the bias instability noise, the quantization noise and the white noise are identified as the major stochastic noise. Finally, the experiment on the direct-current signal acquisitions is conducted, whose results indicate that the signal drift of the measured direct-current is mainly caused by the major stochastic noise. And the suppression methods of the major stochastic noise are proposed. stochastic noise (dpeaa)DE-He213 stray current (dpeaa)DE-He213 optical fiber current sensor (dpeaa)DE-He213 Xing, Fang-fang aut Li, Wei aut Wang, Yu-Qiao aut Enthalten in Journal of Central South University of Technology Changsha : CSUT, 1994 24(2017), 11 vom: Nov., Seite 2596-2604 (DE-627)531203670 (DE-600)2324899-3 1993-0666 nnns volume:24 year:2017 number:11 month:11 pages:2596-2604 https://dx.doi.org/10.1007/s11771-017-3673-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4753 AR 24 2017 11 11 2596-2604
allfields_unstemmed	10.1007/s11771-017-3673-8 doi (DE-627)SPR022376186 (SPR)s11771-017-3673-8-e DE-627 ger DE-627 rakwb eng Xu, Shao-yi verfasserin aut Stochastic noise identification in a stray current sensor 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2017 Abstract The Allan variance analysis method is used to identify the stochastic noise in the stray current sensor. The stray current characteristic is firstly introduced. Then the optical configuration and the signal processing method of the stray current sensor are illustrated. Moreover, the cause of the stochastic noise in the stray current sensor is analyzed. The calculation method of the stochastic noise coefficient is presented in detail. And the feasibility of the stochastic noise identification with the Allan variance analysis method is evaluated. Furthermore, the zero-drift signal acquisition experiment is conducted to identify the stochastic noise in the stray current sensor. According to the experimental result, the bias instability noise, the quantization noise and the white noise are identified as the major stochastic noise. Finally, the experiment on the direct-current signal acquisitions is conducted, whose results indicate that the signal drift of the measured direct-current is mainly caused by the major stochastic noise. And the suppression methods of the major stochastic noise are proposed. stochastic noise (dpeaa)DE-He213 stray current (dpeaa)DE-He213 optical fiber current sensor (dpeaa)DE-He213 Xing, Fang-fang aut Li, Wei aut Wang, Yu-Qiao aut Enthalten in Journal of Central South University of Technology Changsha : CSUT, 1994 24(2017), 11 vom: Nov., Seite 2596-2604 (DE-627)531203670 (DE-600)2324899-3 1993-0666 nnns volume:24 year:2017 number:11 month:11 pages:2596-2604 https://dx.doi.org/10.1007/s11771-017-3673-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4753 AR 24 2017 11 11 2596-2604
allfieldsGer	10.1007/s11771-017-3673-8 doi (DE-627)SPR022376186 (SPR)s11771-017-3673-8-e DE-627 ger DE-627 rakwb eng Xu, Shao-yi verfasserin aut Stochastic noise identification in a stray current sensor 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2017 Abstract The Allan variance analysis method is used to identify the stochastic noise in the stray current sensor. The stray current characteristic is firstly introduced. Then the optical configuration and the signal processing method of the stray current sensor are illustrated. Moreover, the cause of the stochastic noise in the stray current sensor is analyzed. The calculation method of the stochastic noise coefficient is presented in detail. And the feasibility of the stochastic noise identification with the Allan variance analysis method is evaluated. Furthermore, the zero-drift signal acquisition experiment is conducted to identify the stochastic noise in the stray current sensor. According to the experimental result, the bias instability noise, the quantization noise and the white noise are identified as the major stochastic noise. Finally, the experiment on the direct-current signal acquisitions is conducted, whose results indicate that the signal drift of the measured direct-current is mainly caused by the major stochastic noise. And the suppression methods of the major stochastic noise are proposed. stochastic noise (dpeaa)DE-He213 stray current (dpeaa)DE-He213 optical fiber current sensor (dpeaa)DE-He213 Xing, Fang-fang aut Li, Wei aut Wang, Yu-Qiao aut Enthalten in Journal of Central South University of Technology Changsha : CSUT, 1994 24(2017), 11 vom: Nov., Seite 2596-2604 (DE-627)531203670 (DE-600)2324899-3 1993-0666 nnns volume:24 year:2017 number:11 month:11 pages:2596-2604 https://dx.doi.org/10.1007/s11771-017-3673-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4753 AR 24 2017 11 11 2596-2604
allfieldsSound	10.1007/s11771-017-3673-8 doi (DE-627)SPR022376186 (SPR)s11771-017-3673-8-e DE-627 ger DE-627 rakwb eng Xu, Shao-yi verfasserin aut Stochastic noise identification in a stray current sensor 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2017 Abstract The Allan variance analysis method is used to identify the stochastic noise in the stray current sensor. The stray current characteristic is firstly introduced. Then the optical configuration and the signal processing method of the stray current sensor are illustrated. Moreover, the cause of the stochastic noise in the stray current sensor is analyzed. The calculation method of the stochastic noise coefficient is presented in detail. And the feasibility of the stochastic noise identification with the Allan variance analysis method is evaluated. Furthermore, the zero-drift signal acquisition experiment is conducted to identify the stochastic noise in the stray current sensor. According to the experimental result, the bias instability noise, the quantization noise and the white noise are identified as the major stochastic noise. Finally, the experiment on the direct-current signal acquisitions is conducted, whose results indicate that the signal drift of the measured direct-current is mainly caused by the major stochastic noise. And the suppression methods of the major stochastic noise are proposed. stochastic noise (dpeaa)DE-He213 stray current (dpeaa)DE-He213 optical fiber current sensor (dpeaa)DE-He213 Xing, Fang-fang aut Li, Wei aut Wang, Yu-Qiao aut Enthalten in Journal of Central South University of Technology Changsha : CSUT, 1994 24(2017), 11 vom: Nov., Seite 2596-2604 (DE-627)531203670 (DE-600)2324899-3 1993-0666 nnns volume:24 year:2017 number:11 month:11 pages:2596-2604 https://dx.doi.org/10.1007/s11771-017-3673-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_121 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2036 GBV_ILN_2037 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2119 GBV_ILN_2129 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2700 GBV_ILN_2817 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4393 GBV_ILN_4753 AR 24 2017 11 11 2596-2604
language	English
source	Enthalten in Journal of Central South University of Technology 24(2017), 11 vom: Nov., Seite 2596-2604 volume:24 year:2017 number:11 month:11 pages:2596-2604
sourceStr	Enthalten in Journal of Central South University of Technology 24(2017), 11 vom: Nov., Seite 2596-2604 volume:24 year:2017 number:11 month:11 pages:2596-2604
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	stochastic noise stray current optical fiber current sensor
isfreeaccess_bool	false
container_title	Journal of Central South University of Technology
authorswithroles_txt_mv	Xu, Shao-yi @@aut@@ Xing, Fang-fang @@aut@@ Li, Wei @@aut@@ Wang, Yu-Qiao @@aut@@
publishDateDaySort_date	2017-11-01T00:00:00Z
hierarchy_top_id	531203670
id	SPR022376186
language_de	englisch
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author	Xu, Shao-yi
spellingShingle	Xu, Shao-yi misc stochastic noise misc stray current misc optical fiber current sensor Stochastic noise identification in a stray current sensor
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topic_title	Stochastic noise identification in a stray current sensor stochastic noise (dpeaa)DE-He213 stray current (dpeaa)DE-He213 optical fiber current sensor (dpeaa)DE-He213
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title	Stochastic noise identification in a stray current sensor
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title_full	Stochastic noise identification in a stray current sensor
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title_sort	stochastic noise identification in a stray current sensor
title_auth	Stochastic noise identification in a stray current sensor
abstract	Abstract The Allan variance analysis method is used to identify the stochastic noise in the stray current sensor. The stray current characteristic is firstly introduced. Then the optical configuration and the signal processing method of the stray current sensor are illustrated. Moreover, the cause of the stochastic noise in the stray current sensor is analyzed. The calculation method of the stochastic noise coefficient is presented in detail. And the feasibility of the stochastic noise identification with the Allan variance analysis method is evaluated. Furthermore, the zero-drift signal acquisition experiment is conducted to identify the stochastic noise in the stray current sensor. According to the experimental result, the bias instability noise, the quantization noise and the white noise are identified as the major stochastic noise. Finally, the experiment on the direct-current signal acquisitions is conducted, whose results indicate that the signal drift of the measured direct-current is mainly caused by the major stochastic noise. And the suppression methods of the major stochastic noise are proposed. © Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2017
abstractGer	Abstract The Allan variance analysis method is used to identify the stochastic noise in the stray current sensor. The stray current characteristic is firstly introduced. Then the optical configuration and the signal processing method of the stray current sensor are illustrated. Moreover, the cause of the stochastic noise in the stray current sensor is analyzed. The calculation method of the stochastic noise coefficient is presented in detail. And the feasibility of the stochastic noise identification with the Allan variance analysis method is evaluated. Furthermore, the zero-drift signal acquisition experiment is conducted to identify the stochastic noise in the stray current sensor. According to the experimental result, the bias instability noise, the quantization noise and the white noise are identified as the major stochastic noise. Finally, the experiment on the direct-current signal acquisitions is conducted, whose results indicate that the signal drift of the measured direct-current is mainly caused by the major stochastic noise. And the suppression methods of the major stochastic noise are proposed. © Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2017
abstract_unstemmed	Abstract The Allan variance analysis method is used to identify the stochastic noise in the stray current sensor. The stray current characteristic is firstly introduced. Then the optical configuration and the signal processing method of the stray current sensor are illustrated. Moreover, the cause of the stochastic noise in the stray current sensor is analyzed. The calculation method of the stochastic noise coefficient is presented in detail. And the feasibility of the stochastic noise identification with the Allan variance analysis method is evaluated. Furthermore, the zero-drift signal acquisition experiment is conducted to identify the stochastic noise in the stray current sensor. According to the experimental result, the bias instability noise, the quantization noise and the white noise are identified as the major stochastic noise. Finally, the experiment on the direct-current signal acquisitions is conducted, whose results indicate that the signal drift of the measured direct-current is mainly caused by the major stochastic noise. And the suppression methods of the major stochastic noise are proposed. © Central South University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2017
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title_short	Stochastic noise identification in a stray current sensor
url	https://dx.doi.org/10.1007/s11771-017-3673-8
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author2	Xing, Fang-fang Li, Wei Wang, Yu-Qiao
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up_date	2024-07-04T02:51:40.751Z
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The stray current characteristic is firstly introduced. Then the optical configuration and the signal processing method of the stray current sensor are illustrated. Moreover, the cause of the stochastic noise in the stray current sensor is analyzed. The calculation method of the stochastic noise coefficient is presented in detail. And the feasibility of the stochastic noise identification with the Allan variance analysis method is evaluated. Furthermore, the zero-drift signal acquisition experiment is conducted to identify the stochastic noise in the stray current sensor. According to the experimental result, the bias instability noise, the quantization noise and the white noise are identified as the major stochastic noise. Finally, the experiment on the direct-current signal acquisitions is conducted, whose results indicate that the signal drift of the measured direct-current is mainly caused by the major stochastic noise. And the suppression methods of the major stochastic noise are proposed.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">stochastic noise</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">stray current</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">optical fiber current sensor</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Xing, Fang-fang</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Li, Wei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, Yu-Qiao</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield 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