TY - GEN
T1 - Weak Signal Detection Method with Adaptive Three-Dimensional Coupled Bistable Stochastic Resonance System
AU - Li, Mengdi
AU - Shi, Peiming
AU - Zhang, Wenyue
AU - Gu, Fengshou
N1 - Funding Information:
Acknowledgments. The studies were funded by the National Natural Science Foundation of China (Grant numbers 61973262 and 51875500), Natural Science Foundation of Hebei Province (Grant number E2020203147) and the central government guides local science and technology development fund project (Grant numbers 216Z2102G and 216Z4301G).
Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/3/4
Y1 - 2023/3/4
N2 - Aiming at the problem that the coupled bistable stochastic resonance (CBSR) is almost always a two-dimensional potential system, a three-dimensional coupled bistable stochastic resonance (TCBSR) system is proposed, which is composed of a fixed parameter bistable system coupled with two adjustable parameter bistable systems. Firstly, the fourth-order Runge Kutta is used to calculate the system output, and the influence of noise intensity and system parameters a, b, r on the output signal-to-noise ratio (SNR) is simulated and analyzed. Then, taking SNR as the objective function, the particle swarm optimization (PSO) algorithm is applied to search the maximum SNR and its corresponding optimal parameter pair. The bearing outer race fault experiment proves that the proposed adaptive TCBSR method can better suppress the interference in high frequency band and has stronger weak signal feature enhancement and fault detection ability than adaptive CBSR system based on PSO, which is conducive to the application of SR in engineering practice.
AB - Aiming at the problem that the coupled bistable stochastic resonance (CBSR) is almost always a two-dimensional potential system, a three-dimensional coupled bistable stochastic resonance (TCBSR) system is proposed, which is composed of a fixed parameter bistable system coupled with two adjustable parameter bistable systems. Firstly, the fourth-order Runge Kutta is used to calculate the system output, and the influence of noise intensity and system parameters a, b, r on the output signal-to-noise ratio (SNR) is simulated and analyzed. Then, taking SNR as the objective function, the particle swarm optimization (PSO) algorithm is applied to search the maximum SNR and its corresponding optimal parameter pair. The bearing outer race fault experiment proves that the proposed adaptive TCBSR method can better suppress the interference in high frequency band and has stronger weak signal feature enhancement and fault detection ability than adaptive CBSR system based on PSO, which is conducive to the application of SR in engineering practice.
KW - Coupled bistable system
KW - Particle swarm optimization
KW - Signal to noise ratio
KW - Stochastic resonance
UR - http://www.scopus.com/inward/record.url?scp=85151122589&partnerID=8YFLogxK
UR - https://link.springer.com/book/10.1007/978-3-031-26193-0
U2 - 10.1007/978-3-031-26193-0_21
DO - 10.1007/978-3-031-26193-0_21
M3 - Conference contribution
AN - SCOPUS:85151122589
SN - 9783031261923
SN - 9783031261954
VL - 129
T3 - Mechanisms and Machine Science
SP - 245
EP - 254
BT - Proceedings of TEPEN 2022
A2 - Zhang, Hao
A2 - Ji, Yongjian
A2 - Liu, Tongtong
A2 - Sun, Xiuquan
A2 - Ball, Andrew David
PB - Springer, Cham
T2 - International Conference of The Efficiency and Performance Engineering Network 2022
Y2 - 18 August 2022 through 21 August 2022
ER -
