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Applied Sciences
Volume 14
Issue 10
10.3390/app14104284
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Open AccessArticle
by Shuqin Sun SciProfilesScilitPreprints.orgGoogle Scholar Xin Qi SciProfilesScilitPreprints.orgGoogle Scholar Zhenghai Yuan SciProfilesScilitPreprints.orgGoogle Scholar Xiaojun Tang SciProfilesScilitPreprints.orgGoogle Scholar Zaihua Li SciProfilesScilitPreprints.orgGoogle Scholar
Shuqin SunXin QiZhenghai YuanXiaojun TangZaihua Li
1
College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, China
2
Key Laboratory of Geophysical Exploration Equipment, Ministry of Education, Jilin University, Changchun 130061, China
3
China Electric Power Research Institute, Beijing 100192, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(10), 4284; https://doi.org/10.3390/app14104284 (registeringDOI)
Submission received: 12 April 2024/Revised: 15 May 2024/Accepted: 17 May 2024/Published: 18 May 2024
(This article belongs to the Section Applied Physics General)
Abstract
The classical bistable stochastic resonance algorithm has an inherent output saturation defect that restricts the amplitude of the output signal. This paper examines the causes of this phenomenon and its negative impact on the detection of weak signals. Proposing the Unsaturated Bistable Stochastic Resonance (UBSR) detection algorithm involves constructing a segmented potential function using a linear function to eliminate the effect of higher-order terms in the classical stochastic resonance algorithm. A new type of segmented potential function has been created by combining exponential and linear functions. This new function helps to eliminate the impact of higher-order terms in classical algorithms while also improving the noise immunity of the stochastic resonance system. This results in the development of the accelerated stochastic resonance (ASR) detection algorithm. In this paper, the Kramers escape rate and output signal-to-noise ratio of two improved stochastic resonance algorithms are theoretically derived and compared with the classical bistable stochastic resonance algorithms, and the proposed algorithms are able to effectively avoid the output saturation phenomenon and have more excellent detection performance under strong background noise.
Keywords: stochastic resonance; multistage potential well; correlation number; harmonic detection; voltage dips detection
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MDPI and ACS Style
Sun, S.; Qi, X.; Yuan, Z.; Tang, X.; Li, Z.Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle. Appl. Sci. 2024, 14, 4284.https://doi.org/10.3390/app14104284
AMA Style
Sun S, Qi X, Yuan Z, Tang X, Li Z.Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle. Applied Sciences. 2024; 14(10):4284.https://doi.org/10.3390/app14104284
Chicago/Turabian Style
Sun, Shuqin, Xin Qi, Zhenghai Yuan, Xiaojun Tang, and Zaihua Li.2024. "Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle" Applied Sciences 14, no. 10: 4284.https://doi.org/10.3390/app14104284
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
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MDPI and ACS Style
Sun, S.; Qi, X.; Yuan, Z.; Tang, X.; Li, Z.Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle. Appl. Sci. 2024, 14, 4284.https://doi.org/10.3390/app14104284
AMA Style
Sun S, Qi X, Yuan Z, Tang X, Li Z.Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle. Applied Sciences. 2024; 14(10):4284.https://doi.org/10.3390/app14104284
Chicago/Turabian Style
Sun, Shuqin, Xin Qi, Zhenghai Yuan, Xiaojun Tang, and Zaihua Li.2024. "Power System Signal-Detection Method Based on the Accelerated Unsaturated Stochastic Resonance Principle" Applied Sciences 14, no. 10: 4284.https://doi.org/10.3390/app14104284
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
Appl. Sci.,EISSN 2076-3417,Published by MDPI
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