Papers by Author: Guo Dong Gao

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Authors: Guo Dong Gao, Wen Xiao Zhang, Gong Zhi Yu, Jiang Hua Sui
Abstract: With the rapid development of computer technology and Internet, all kinds of distant educations based on Internet have been coming out constantly. To reduce the cost of exam and alleviate the burden of teachers, the crew examination system was designed and implemented. This system is an online examination system which integrates computer network technology, database technology and ASP technology. The B/S model was adopted in this system and using ASP visit ODBC accesses database. This system includes two functions: examination system and management system. Test library management, random questions, online testing, automatic scoring, scores query and other functions were achieved. Crew examination system realizes the change from traditional test’s way to the way based on Internet.
Authors: Guo Dong Gao, Wen Xiao Zhang, Jiang Hua Sui, Guang Yu Mu
Abstract: In order to solve the fault diagnosis problem of diesel engine, Elman neural network (ENN) was applied to build a fault diagnosis model of diesel engine. The training algorithm is in introduced and at the same time, the process of diesel engine fault diagnosis is also expatiated. The diagnosis results indicate the reliability. So a contingent fault of diesel engine can be identified effectively.
Authors: Guo Dong Gao, Wen Xiao Zhang, Gong Zhi Yu, Jiang Hua Sui
Abstract: The structure, characteristics and principles of BP neural network model are described in this paper. First, three impact factors of the dissolved oxygen are selected as the sample input of network, and then the parameters of BP neural network are selected, such as network structure, learning algorithm, output layer transfer function, learning rate and so on. Finally, the BP neural network model is established and trained, in order to approach compensate the effects of improves non-linearity. The simulation results show that BP neural network is practical and dependable in the field of dissolved oxygen modeling and has nice applied prospect.
Authors: Guang Yu Mu, Li Li, Wen Xiao Zhang, Guo Dong Gao
Abstract: This paper addresses on quality improvement of expanded food. The five stages of six sigma implementation process are applied to define the problem and set a target for improvement. Then possible causes to the quality problems in expanded food are investigated, and the capabilities of the measuring system are evaluated and improved. Based on the results, the experiment scheme is conducted to find and optimize the key factors. Improvement result shows that sigma level of production process increased to 4.6, which is beyond the expectation and can save the cost.
Authors: Guo Dong Gao, Wen Xiao Zhang, Wang Zheng
Abstract: The analysis of the residual life of high temperature low cycle fatigue of 30CrMnSiA steel plays important roles in improving security and avoiding accidents. In this paper, the RBF neural network method is used to predict the residual life of high temperature low cycle fatigue of 30CrMnSiA steel base on data from the thermo-mechanical fatigue test. The feasibility of the method is proved by a practice example, and the learning results are in good agreement with the experimental data.
Authors: Wen Xiao Zhang, Guo Dong Gao, Guang Yu Mu
Abstract: The in-phase and out-of-phase thermal fatigue of aluminum alloy were experimentally studied. The fatigue life was evaluated analytically by using the elastic-plastic fracture mechanics method (mainly J integral). The results of experiments and calculations showed that the life of out-of-phase fatigue was longer than that of in-phase fatigue within the same strain range. This is the same as the results of other materials such as medium and low carbon steel. On the other hand, the predicted life was consistent with experimental results. This suggests that J integral as a mechanics parameter for characterizing the thermal fatigue strength of aluminum alloy and the calculation method developed here is efficient. A parameter ΔW was proposed from energy aspect to characterize the capacity of crack propagation. The in-phase thermal fatigue life was the same as the out-of-phase thermal fatigue life for identical ΔW values.
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