The fault diagnosis model for FMS based on multi layer feedforward neural networks was discussed An improved BP algorithm,the tactic of initial value selection based on genetic algorithm and the method of network st...The fault diagnosis model for FMS based on multi layer feedforward neural networks was discussed An improved BP algorithm,the tactic of initial value selection based on genetic algorithm and the method of network structure optimization were presented for training this model ANN(artificial neural network)fault diagnosis model for the robot in FMS was made by the new algorithm The result is superior to the rtaditional algorithm展开更多
Minipump is widely used in microfluidics system, active cooling system, etc. But building a high efficiency minipump is still a challenging problem. In this paper, a systematic method was developed to design, characte...Minipump is widely used in microfluidics system, active cooling system, etc. But building a high efficiency minipump is still a challenging problem. In this paper, a systematic method was developed to design, characterize and optimize a particular mechanical minipump. The optimization work was conducted to cope with the conflict between pressure head and hydraulic efficiency by an improved back-propagation neural network （BPNN） with the non-dominated sorting genetic algorithm-II （NSGA-II）. The improved BPNN was utilized to predicate hydraulic performance and, moreover, was modified to improve the prediction accuracy. The NSGA-II was processed for minipump multi-objective optimization which is dominated by four impeller dimensions. During hydraulic optimization, the processing feasibility was also taken into consideration. Experiments were conducted to validate the above optimization methods. It was proved that the optimized minipump was improved by about 24 % in pressure head and 4.75 % in hydraulic efficiency compared to the original designed prototype. Meanwhile, the sensitivity test was used to analyze the influence of the four impeller dimensions. It was found that the blade outlet angle β2 and the impeller inlet diameter Do significantly influence the pressure head H and the hydraulic efficiency η, respec- tively. Detailed internal flow fields showed that the optimum model can relieve the impeller wake and improve both the pressure distribution and flow orientation.展开更多
文摘The fault diagnosis model for FMS based on multi layer feedforward neural networks was discussed An improved BP algorithm,the tactic of initial value selection based on genetic algorithm and the method of network structure optimization were presented for training this model ANN(artificial neural network)fault diagnosis model for the robot in FMS was made by the new algorithm The result is superior to the rtaditional algorithm
文摘Minipump is widely used in microfluidics system, active cooling system, etc. But building a high efficiency minipump is still a challenging problem. In this paper, a systematic method was developed to design, characterize and optimize a particular mechanical minipump. The optimization work was conducted to cope with the conflict between pressure head and hydraulic efficiency by an improved back-propagation neural network （BPNN） with the non-dominated sorting genetic algorithm-II （NSGA-II）. The improved BPNN was utilized to predicate hydraulic performance and, moreover, was modified to improve the prediction accuracy. The NSGA-II was processed for minipump multi-objective optimization which is dominated by four impeller dimensions. During hydraulic optimization, the processing feasibility was also taken into consideration. Experiments were conducted to validate the above optimization methods. It was proved that the optimized minipump was improved by about 24 % in pressure head and 4.75 % in hydraulic efficiency compared to the original designed prototype. Meanwhile, the sensitivity test was used to analyze the influence of the four impeller dimensions. It was found that the blade outlet angle β2 and the impeller inlet diameter Do significantly influence the pressure head H and the hydraulic efficiency η, respec- tively. Detailed internal flow fields showed that the optimum model can relieve the impeller wake and improve both the pressure distribution and flow orientation.
