Structure synthesis method for reconfigurable mechanism based on genetic optimization algorithm is proposed in this paper. Main characteristics of this method include: (1) POC matrix of the mechanism corresponding to ...
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ISBN:
(纸本)9788889007372
Structure synthesis method for reconfigurable mechanism based on genetic optimization algorithm is proposed in this paper. Main characteristics of this method include: (1) POC matrix of the mechanism corresponding to different motion stage of the reconfigurable mechanism is used as the objective function. (2) Design variables are determined based on the influence of three basic topological structure elements over POC matrix. (3) According to the genetic optimization algorithm, more than one solution may usually be obtained. The optimum reconfigurable mechanism may be selected based on other engineering requirements. An example is given to illustrate the synthesis procedure.
Ideal step signal is nonexistent in practical application and the input signals used in system identification are actually not ideal step signals. This introduced errors to the direct identification modeling method th...
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Ideal step signal is nonexistent in practical application and the input signals used in system identification are actually not ideal step signals. This introduced errors to the direct identification modeling method that based on the ideal step input assumption. Therefore, an improved algorithm based on non-ideal step signal input was proposed in this paper. A parameter represent the time of the non-ideal step signal was introduced in this algorithm, and it can be decided automatically during the model identification by using genetic optimization algorithm(GA), which means that this proposed identification modeling algorithm has higher precision and also can be used directly in the practical application. The effectiveness and applicability of this method has been demonstrated through the simulation model identification under the non-ideal step signal input.
In this paper, an aero gas turbine engine with three shafts are investigated. By employing data-driven method, a reduced-order model is obtained, which has the close output performance as the 14th-order full-order mod...
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ISBN:
(纸本)9781479943159
In this paper, an aero gas turbine engine with three shafts are investigated. By employing data-driven method, a reduced-order model is obtained, which has the close output performance as the 14th-order full-order model. Based on the reduced-order model, a fault detection filter is designed to detect actuator faults and sensor faults for the system subjected to input and output noises. genetic optimization algorithm is used to design the filter gains such that the residual signal is sensitive to the faults, but robust to process and sensor noises. Simulated results demonstrate the efficiency of the present algorithm.
Two semicrystalline thermoplastics, an isotactic polypropylene (iPP, LynedllBasell Moplen HP501L) and a polyethylene-high-density (PE-HD, LynedllBasell Hostalen GC7260), were selected to approve a new approach. The de...
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Two semicrystalline thermoplastics, an isotactic polypropylene (iPP, LynedllBasell Moplen HP501L) and a polyethylene-high-density (PE-HD, LynedllBasell Hostalen GC7260), were selected to approve a new approach. The developed approach allows the inverse determination of the amorphous and crystalline mechanical as well as the crystalline geometric constituents' properties. Commonly, these properties are unknown in structure simulations, and hence, the application of micromechanical models to the inhomogeneous microstructure of semicrystalline thermoplastics is restricted. Rather, a homogenous microstructure is assumed, and only one Young's modulus and Poisson's ratio are used in calculations. Thus, the quality and reliability of simulations are limited. In the current study, a new approach was exemplarily conducted for the inverse determination of the required properties by combining a Mori-Tanaka mean field approach with a genetic optimization algorithm. Conclusive results were achieved for both polymers. According to the results, the attained geometric parameters for the crystalline constituents resemble the aspect ratio of the spherulite diameter and the long period of the real crystalline microstructure, and the mechanical properties of the amorphous and crystalline constituents are located within reasonable bounds.
The hybrid model of products disassembly is built, and a method of generating disassembly sequence is given. The disassembly sequence optimization model based on geneticalgorithms is built based on the hybrid graph, ...
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ISBN:
(纸本)9783037858813
The hybrid model of products disassembly is built, and a method of generating disassembly sequence is given. The disassembly sequence optimization model based on geneticalgorithms is built based on the hybrid graph, and gained an optimal disassembly sequence.
Poly (vinyl alcohol) membranes were prepared by in-situ crosslinking of poly(vinyl alcohol) with glutaraldehyde as crosslinking agent and hydrochloric acid as catalyst and used for dehydration of IPA mixtures. Effects...
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Poly (vinyl alcohol) membranes were prepared by in-situ crosslinking of poly(vinyl alcohol) with glutaraldehyde as crosslinking agent and hydrochloric acid as catalyst and used for dehydration of IPA mixtures. Effects of feed composition, operating temperature, vacuum pressure, and Reynolds number on the permeation performance of the membranes were evaluated. Eighty-nine experimental data was applied to investigate ANN modeling. A multi layered feedforward neural network was applied to model the PV membranes. Two major training algorithms and optimum number of neurons and layers were investigated. As a result, Bayesian regularization successfully predicted experimental data. Different network structures were optimized, using multi object genetic optimization algorithm. The results concluded that the network with structure composing two hidden layers performs better than the other with one hidden layer, and also there is an excellent compatibility between the experimental data and the predicted values of optimum network structure (4:3:2:2). Furthermore, the optimum network was applied to predict extrapolation data and the results showed that this network can extrapolate data as well as interpolating.
This paper deals with the problem of determination of linguistic "IF-THEN" rules from available experimental data, which is inverse to the problem of identification of nonlinear dependences by fuzzy knowledg...
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