resonance system
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2022 ◽  
Vol 154 ◽  
pp. 111642
Author(s):  
Zuanbo Zhou ◽  
Wenxin Yu ◽  
Junnian Wang ◽  
Meiting Liu

Machines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 275
Author(s):  
Di Xu ◽  
Jianghua Ge ◽  
Yaping Wang ◽  
Junpeng Shao

In engineering practice, the bearing fault signal is composed of a series of complex multi-component signals containing multiple fault characteristics information. In the early stage of fault sprouting and evolution, the fault features are easily disturbed by noise and irrelevant signals, eliminating the fault signals in the strong background noise. To overcome the influence of noise on the signal, this study proposes multi-frequency weak signal decomposition and reconstruction of rolling bearing based on adaptive cascaded stochastic resonance. First, the original signal is passed through the Hilbert transform to obtain the envelope signal. The envelope signal is high-pass filtered to eliminate the interference of low-frequency components on the response of the stochastic resonance system. Secondly, cascaded stochastic resonance system parameters are adaptively optimized by the quantum particle swarm algorithm (QPSO). The high-pass filtered signal input to the adaptive cascaded stochastic resonance system (ACSRS) can further enhance the weak fault characteristics, allowing the gradual transfer of high-frequency noise energy to the low-frequency fault characteristic components. Finally, the signal is decomposed using the variational mode decomposition (VMD) method to jointly determine the location of the fault characteristic frequencies in the intrinsic mode functions (IMF) component by the energy loss coefficient and correlation coefficient to achieve the reconstruction of multi-frequency weak signals. Through simulation and experimental validation, the effectiveness and superiority of the method for multi-frequency weak signal detection in bearings are verified. The results show that the method not only achieves the adaptive optimization of the stochastic resonance system parameters gradually removing the high-frequency noise in the signal and improving the energy of the low-frequency signal but also reduces the number of decomposition layers of the VMD, enhances the fault characteristic information in the weak signal, and effectively identifies the early weak fault characteristics of rolling bearings.


2021 ◽  
Author(s):  
Zhongyan Liu ◽  
Yujing Xu ◽  
Wang Liu ◽  
Qi Zhang ◽  
Jiafei Hu ◽  
...  

2021 ◽  
Vol 2021 (8) ◽  
Author(s):  
K.P. Gaikovich ◽  
◽  
A.I. Smirnov ◽  

In this paper, methods of near-field microwave tomography of the subsurface structure of dielectric inhomogeneities are proposed and studied based on the use of resonance probes with pieces of twin-wire lines as sensors. In frameworks of the quasi-static approximation, the integral equation of the inverse problem that relates measured variations of the complex capacity of the resonance system of probes placed above a medium with the inhomogeneous distribution of the complex permittivity. Based on this equation, methods and algorithms of tomography and holography have been proposed and worked out that used data of 2D scanning with variable offset between the sensor wires: (a) with the fixed direction of wires of sensor; (b) in two orthogonally related directions of sensor wires; (c) with the sensor of crossed twin-wire lines. Results of the numerical simulation demonstrate the efficiency of developed algorithms of subsurface tomography and holography.


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