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The Optimization Of Antenna Support Frame Based On Parallel Mechanism

Posted on:2019-06-09Degree:MasterType:Thesis
Country:ChinaCandidate:L ChenFull Text:PDF
GTID:2428330563991493Subject:Marine Engineering
Abstract/Summary:PDF Full Text Request
Antenna support frame using the six-dof parallel mechanism as the base has many advantages such as strong maneuverability,easy layout,large bearing capacity,high precision of control and economy of cost,has attracted people's attention and gradually put into application.A method is presented for the describing of the direction cosine matrix of Z-Y-Z axis.The corresponding relation between the working length of the drive tube and the azimuth angle and the pitch angle of the tracking target is given on the basis of the forward and inverse position solution.Based on the spatial vector relationship between the motion parts of the mechanism,the formula of the expression for external load and driving force,the Jacobi matrix for the mechanism is obtained.And the determination conditions of mechanical interference between moving parts is given at the same time.An optimization model is proposed to ensure the accuracy and safety of the system,which is constrained by mechanical interference,driving cylinder stiffness and working length of driving cylinder.The optimal design of the base of a type of platform is completed and the optimal solution set is obtained by the particle swarm optimization.Some other work has done for the problems existing in the manufacturing,installation and working process of the antenna support frame.The installation and control error of the mechanism are simulated and analyzed,and the error range is given based on the principle of 3?.The real-time compensation method of the error of the working length caused by spin movement in the driving process is given.The initial error of the drive cylinder may exist,the method of eliminating error is proposed after simulation.
Keywords/Search Tags:antenna support frame, parallel mechanism, multi-objective optimization, particle swarm optimization, error analysis
PDF Full Text Request
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