In this paper,two lifting mechanism models with opposing placements,which use the same hydraulic hoist model and have the same angle of 50°,have been developed.The mechanical and hydraulic simulation models are e...In this paper,two lifting mechanism models with opposing placements,which use the same hydraulic hoist model and have the same angle of 50°,have been developed.The mechanical and hydraulic simulation models are established using MATLAB Simscape to analyze their kinetics and dynamics in the lifting and holding stages.The simulation findings are compared to the analytical calculation results in the steady state,and both methods show good agreement.In the early lifting stage,Model 1 produces greater force and discharges goods in the container faster than Model 2.Meanwhile,Model 2 reaches a higher force and ejects goods from the container cleaner than its counterpart at the end lifting stage.The established simulation models can consider the effects of dynamic loads due to inertial moments and forces generated during the system operation.It is crucial in studying,designing,and optimizing the structure of hydraulic-mechanical systems.展开更多
Numerical simulation plays an important role in the dynamic analysis of multibody system.With the rapid development of computer science,the numerical solution technology has been further developed.Recently,data-driven...Numerical simulation plays an important role in the dynamic analysis of multibody system.With the rapid development of computer science,the numerical solution technology has been further developed.Recently,data-driven method has become a very popular computing method.However,due to lack of necessary mechanism information of the traditional pure data-driven methods based on neural network,its numerical accuracy cannot be guaranteed for strong nonlinear system.Therefore,this work proposes a mechanism-data hybrid-driven strategy for solving nonlinear multibody system based on physics-informed neural network to overcome the limitation of traditional data-driven methods.The strategy proposed in this paper introduces scaling coefficients to introduce the dynamic model of multibody system into neural network,ensuring that the training results of neural network conform to the mechanics principle of the system,thereby ensuring the good reliability of the data-driven method.Finally,the stability,generalization ability and numerical accuracy of the proposed method are discussed and analyzed using three typical multibody systems,and the constrained default situations can be controlled within the range of 10^(-2)-10^(-4).展开更多
The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with ...The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with large deformation and large rotation remains rare.In this investigation,a state estimator based on multiple nonlinear Kalman filtering algorithms was designed for the flexible multibody systems containing large flexibility components that were discretized by absolute nodal coordinate formulation(ANCF).The state variable vector was constructed based on the independent coordinates which are identified through the constraint Jacobian.Three types of Kalman filters were used to compare their performance in the state estimation for ANCF.Three cases including flexible planar rotating beam,flexible four-bar mechanism,and flexible rotating shaft were employed to verify the proposed state estimator.According to the different performances of the three types of Kalman filter,suggestions were given for the construction of the state estimator for the flexible multibody system.展开更多
基金Ho Chi Minh City University of Technology(HCMUT)Vietnam National University Ho Chi Minh City(VNU-HCM)for supporting this study。
文摘In this paper,two lifting mechanism models with opposing placements,which use the same hydraulic hoist model and have the same angle of 50°,have been developed.The mechanical and hydraulic simulation models are established using MATLAB Simscape to analyze their kinetics and dynamics in the lifting and holding stages.The simulation findings are compared to the analytical calculation results in the steady state,and both methods show good agreement.In the early lifting stage,Model 1 produces greater force and discharges goods in the container faster than Model 2.Meanwhile,Model 2 reaches a higher force and ejects goods from the container cleaner than its counterpart at the end lifting stage.The established simulation models can consider the effects of dynamic loads due to inertial moments and forces generated during the system operation.It is crucial in studying,designing,and optimizing the structure of hydraulic-mechanical systems.
基金supported by the National Natural Science Foundation of China(Grant No.U2241263)the fellowship of China Postdoctoral Science Foundation(Grant No.2024M750310).
文摘Numerical simulation plays an important role in the dynamic analysis of multibody system.With the rapid development of computer science,the numerical solution technology has been further developed.Recently,data-driven method has become a very popular computing method.However,due to lack of necessary mechanism information of the traditional pure data-driven methods based on neural network,its numerical accuracy cannot be guaranteed for strong nonlinear system.Therefore,this work proposes a mechanism-data hybrid-driven strategy for solving nonlinear multibody system based on physics-informed neural network to overcome the limitation of traditional data-driven methods.The strategy proposed in this paper introduces scaling coefficients to introduce the dynamic model of multibody system into neural network,ensuring that the training results of neural network conform to the mechanics principle of the system,thereby ensuring the good reliability of the data-driven method.Finally,the stability,generalization ability and numerical accuracy of the proposed method are discussed and analyzed using three typical multibody systems,and the constrained default situations can be controlled within the range of 10^(-2)-10^(-4).
基金supported by the National Natural Science Foundation of China(Grant Nos.12272123 and 12302047)the Natural Science Foundation of Jiangsu Province(Grant No.BK20231185)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.SJCX24_0192).
文摘The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with large deformation and large rotation remains rare.In this investigation,a state estimator based on multiple nonlinear Kalman filtering algorithms was designed for the flexible multibody systems containing large flexibility components that were discretized by absolute nodal coordinate formulation(ANCF).The state variable vector was constructed based on the independent coordinates which are identified through the constraint Jacobian.Three types of Kalman filters were used to compare their performance in the state estimation for ANCF.Three cases including flexible planar rotating beam,flexible four-bar mechanism,and flexible rotating shaft were employed to verify the proposed state estimator.According to the different performances of the three types of Kalman filter,suggestions were given for the construction of the state estimator for the flexible multibody system.
