Rolling bearing and Squeeze Film Damper(SFD)are used in rotor support structures,and most researches on the nonlinear rotor-bearing system are focused on the simple rotor-bearing *** work emphasizes the comparative an...
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Rolling bearing and Squeeze Film Damper(SFD)are used in rotor support structures,and most researches on the nonlinear rotor-bearing system are focused on the simple rotor-bearing *** work emphasizes the comparative analysis of the influence of SFD on the nonlinear dynamic behavior of the dual-rotor system supported by rolling ***,a reduced dynamic model is established by combining the Finite Element(FE)method and the freeinterface method of component mode *** proposed model is verified by comparing the natural characteristics obtained from an FE model with those from the ***,the steady-state vibration responses of the system with or without SFD are solved by the numerical integration *** influences of the ball bearing clearance,unbalance,centralizing spring stiffness and oil film clearance of SFD on the nonlinear steady-state vibration responses of the dual-rotor system are *** show that SFD can effectively suppress the amplitude jump of the dual rotor system sustaining two rotors unbalance *** the ball bearing clearance or unbalance increases,the amplitude jump phenomenon becomes more obvious,the resonance hysteresis phenomenon strengthens or weakens,the resonant peaks shift to the left or the right,*** with unreasonable parameters will aggravate the system vibration,the smaller the oil film clearance,the better the damping performance of the SFD,the larger the centralizing spring stiffness is,the larger resonance amplitudes are.
Multi-camera vehicle tracking (MCVT) system is a key technology to build an intelligent city and intelligent transportation system. The MCVT system utilizes roadside monitoring devices and computing platforms to achie...
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Piezoresistive pressure sensors (PPS) are widely used in various microelectronic devices applied in modern technologies. The performance of these sensors are highly dependent on the ambient temperature. Unfortunately,...
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ISBN:
(数字)9798350393316
ISBN:
(纸本)9798350393323
Piezoresistive pressure sensors (PPS) are widely used in various microelectronic devices applied in modern technologies. The performance of these sensors are highly dependent on the ambient temperature. Unfortunately, known methods of PPS calibration do not allow measuring pressure with the required accuracy in the wide temperature range typical, for instance, in aviation from −60 to 140 °C. In this paper, a conventional approach is used, when the dependence of the output voltage on pressure is represented using a polynomial of a relatively low order, and the dependences of the coefficients of this polynomial on temperature are specified by the cubic splines. The paper describes in detail the identification method of the polynomial model under consideration and obtains expressions for correcting the readings of the pressure gauge during pressure measurements in wide temperature ranges, when the temperature dependence model is specified using cubic splines. The results of experimental studies of specific pressure sensors are presented.
This paper investigates the robustness and optimality of the multi-kernel correntropy (MKC) on linear regression. We first derive an upper error bound for a scalar regression problem in the presence of arbitrarily lar...
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This paper investigates the robustness and optimality of the multi-kernel correntropy (MKC) on linear regression. We first derive an upper error bound for a scalar regression problem in the presence of arbitrarily large outliers and state that the kernel bandwidth plays an important role in minimizing the lowest upper error bound. Then, we find that the proposed MKC is related to a specific heavy-tail distribution, where its head shape is consistent with the Gaussian distribution but its tail shape is heavy-tailed, and the extent of heavy-tail is controlled by the kernel bandwidth. It becomes a Gaussian distribution when the bandwidth is infinite, which allows one to tackle both Gaussian and non-Gaussian problems without explicitly investigating the noise distributions. To explore the optimal underlying distribution parameters, an expectation-maximization-like (EM) algorithm is developed to estimate the parameter vectors and the distribution parameters in an alternating manner. The results show that our algorithm can achieve equivalent performance compared with the traditional linear regression under Gaussian noise, and it significantly outperforms the conventional method under heavy-tailed noise. Both numerical simulations and experiments on a magnetometer calibration application verify the effectiveness of the proposed method. Note to Practitioners-The goal of this paper is to enhance the accuracy of conventional linear regression in handling outliers while maintaining its optimality under Gaussian assumptions. Our algorithm is formulated under the maximum likelihood estimation (MLE) framework, assuming the regression residuals follow a type of heavy-tailed noise distribution with an extreme case of Gaussian. The degree of the heavy tail is explored alternatingly using an Expectation-Maximization (EM) algorithm which converges very quickly. The robustness and optimality of the proposed approach are investigated and compared with the traditional approaches. Both th
This paper presents two computationally efficient algorithms for the orientation estimation of inertial measurement units (IMUs): the multi-kernel correntropy-based gradient descent (CGD) and the multi-kernel correntr...
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Meticulous 3D environment representations have been a longstanding goal in computer vision and robotics fields. The recent emergence of neural implicit representations has introduced radical innovation to this field a...
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Mold level stability is a very important factor in the continuous casting process. To effectively control the liquid level at the set value, solve the problems of disturbance, nonlinearity, and time-varying in the sys...
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This paper proposes a new Siamese network model for fault diagnosis with limited training samples. We introduce residual blocks to the Siamese network model for few-shot learning. By using the same or different types ...
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Dynamic control of secondary cooling in continuous casting is the key technology to improve the quality and efficiency of the slab. In order to improve the quality and efficiency of the slab, a new control strategy of...
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Robotics has been widely used in the field of non-destructive testing in recent years. However, for complex surfaces, manual teaching or offline programming is time-consuming and difficult to ensure high precision for...
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