DocumentCode
1546745
Title
Hysteresis shaping in stochastic driven systems
Author
Andò, Bruno ; Graziani, Savatore ; Pitrone, Nicola
Author_Institution
Dipt. Elettrico, Elettronico, e Sisternistico, Catania Univ., Italy
Volume
50
Issue
5
fYear
2001
fDate
10/1/2001 12:00:00 AM
Firstpage
1264
Lastpage
1269
Abstract
A large set of sensors (SQUID, piezoelectric, etc.) show a nonlinear calibration curve due to the hysteresis phenomenon. Moreover, sensors usually work in the presence of noise that very often compromises the sensitivity of the device in the low-level range. A useful way to investigate the behavior of such a complex system is to model the hysteresis with the well-known quartic double well (QDW) potential subjected to noise-driven fluctuations along with a periodic signal. The authors have previously discussed the analysis of such a system in the case when a deterministic signal is forced in. In this paper, an analysis of the QDW potential subjected to both dissipation and stochastic fluctuation along with an external deterministic forcing signal is performed to investigate the possibility of optimizing the system sensitivity, by a suitable shaping of the hysteresis, as the forcing term characteristics change. This study can help to improve the feature of a general class of devices forced with a low-amplitude signal, located in a noisy environment. Moreover, suitable issues useful during the design phase of the devices can be obtained
Keywords
calibration; fluctuations; hysteresis; measurement theory; modelling; noise; resonance; sensitivity; sensors; stochastic systems; QDW potential; dissipation fluctuation; external deterministic forcing signal; hysteresis phenomenon; hysteresis shaping; low-amplitude signal; noise-driven fluctuations; noisy environment; nonlinear calibration curve; periodic signal; quartic double well potential; sensor characterization; stochastic driven systems; stochastic resonance; system sensitivity optimisation; Calibration; Fluctuations; Hysteresis; Noise shaping; Potential well; SQUIDs; Sensor phenomena and characterization; Signal analysis; Stochastic resonance; Stochastic systems;
fLanguage
English
Journal_Title
Instrumentation and Measurement, IEEE Transactions on
Publisher
ieee
ISSN
0018-9456
Type
jour
DOI
10.1109/19.963195
Filename
963195
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