This paper focuses on the linear dynamic responses of a piezoelectric semiconductor (PS) sandwich cylindrical shell covered with functionally graded piezoelectric semiconductor (FGPS) layers. The PS sandwich cylindric...
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Piecewise linear systems are prevalent in engineering practice,and can be categorized into symmetric and asymmetric piecewise linear *** that symmetry is a special case of asymmetry,it is essential to investigate the ...
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Piecewise linear systems are prevalent in engineering practice,and can be categorized into symmetric and asymmetric piecewise linear *** that symmetry is a special case of asymmetry,it is essential to investigate the broader model,namely the asymmetric piecewise linear *** traditional averaging method is frequently used for studying nonlinear systems,particularly symmetric piecewise linear systems,with the harmonic response of the oscillator serving as a key prerequisite for calculating steady-state ***,asymmetric systems inherently exhibit nonharmonic,asymmetric responses,rendering the traditional averaging method *** overcome this limitation,this paper introduces an improved averaging method tailored for an oscillator characterized by asymmetric gaps and *** the traditional method,which assumes a purely harmonic response,the improved averaging method redefines the system response as a superposition of a direct current(DC)term and a first harmonic ***,the DC term can be regarded as the offset induced by model ***,the DC term is treated as a slow variable function of time,with its time derivative assumed to be zero when calculating the steady-state solution,akin to the amplitude and phase in the traditional averaging *** validation demonstrates that the responses computed in both time and frequency domains with the improved averaging method exhibit greater accuracy compared with those derived from the traditional *** these improved results,the study also examines the parameter effect,stability,and bifurcation phenomena within the amplitude-frequency responses.
The vehicle-road coupling dynamics problem is a prominent issue in transportation,drawing significant attention in recent *** dynamic equations are characterized by high-dimensionality,coupling,and time-varying dynami...
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The vehicle-road coupling dynamics problem is a prominent issue in transportation,drawing significant attention in recent *** dynamic equations are characterized by high-dimensionality,coupling,and time-varying dynamics,making the exact solutions challenging to *** a result,numerical integration methods are typically ***,conventional methods often suffer from low computational *** address this,this paper explores the application of the parameter freezing precise exponential integrator to vehicle-road coupling *** model accounts for road roughness irregularities,incorporating all terms unrelated to the linear part into the algorithm's inhomogeneous *** general construction process of the algorithm is *** validity of numerical results is verified through approximate analytical solutions(AASs),and the advantages of this method over traditional numerical integration methods are *** parameter freezing precise exponential integrator schemes are constructed based on the Runge-Kutta framework,with the fourth-order four-stage scheme identified as the optimal *** study indicates that this method can quickly and accurately capture the dynamic system's vibration response,offering a new,efficient approach for numerical studies of high-dimensional vehicle-road coupling systems.
Infrared thermography (IRT) is a reliable method for detecting defects in composites with advantages of full field, non-contact, easy operation and good visualization. Nevertheless, interpretation by experts is requir...
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Pulse thermography is a reliable method for detecting defects in composites with advantages of full field, non-contact and easy operation. However, the size determination of subsurface defects with low width-to-depth ...
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Blind deconvolution (BD) methods have shown significant promise in machinery fault diagnosis, yet their performance remains constrained by fixed filter length and susceptibility to local optima. To tackle this problem...
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To address the issue of high-order polygonal wear in high-speed trains operating at 300 km/h, this paper investigates the influence of bogie modal vibration on the initiation and progression of such wear phenomen...
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To explore the acquisition, analysis, and visualization applications of subway passenger flow data in the context of big data, and to uncover the patterns behind passenger travel data, this paper utilizes subway IC ca...
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To investigate generation causes of rail corrugation on metro lines, a new analysis method applicable to explain the formation mechanism of rail corrugation is proposed from micro creepage saturation and macro structu...
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In the parallel steering coordination control strategy for path tracking, it is difficult to match the current driver steering model using the fixed parameters with the actual driver, and the designed steering coordin...
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In the parallel steering coordination control strategy for path tracking, it is difficult to match the current driver steering model using the fixed parameters with the actual driver, and the designed steering coordination control strategy under a single objective and simple conditions is difficult to adapt to the multi-dimensional state variables’ input. In this paper, we propose a deep reinforcement learning algorithm-based multi-objective parallel human-machine steering coordination strategy for path tracking considering driver misoperation and external disturbance. Firstly, the driver steering mathematical model is constructed based on the driver preview characteristics and steering delay response, and the driver characteristic parameters are fitted after collecting the actual driver driving data. Secondly, considering that the vehicle is susceptible to the influence of external disturbances during the driving process, the Tube MPC (Tube Model Predictive Control) based path tracking steering controller is designed based on the vehicle system dynamics error model. After verifying that the driver steering model meets the driver steering operation characteristics, DQN (Deep Q-network), DDPG (Deep Deterministic Policy Gradient) and TD3 (Twin Delayed Deep Deterministic Policy Gradient) deep reinforcement learning algorithms are utilized to design a multi-objective parallel steering coordination strategy which satisfies the multi-dimensional state variables’ input of the vehicle. Finally, the tracking accuracy, lateral safety, human-machine conflict and driver steering load evaluation index are designed in different driver operation states and different road environments, and the performance of the parallel steering coordination control strategies with different deep reinforcement learning algorithms and fuzzy algorithms are compared by simulations and hardware in the loop experiments. The results show that the parallel steering collaborative strategy based on a deep
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