Advanced Materials Research Vols. 219-220

Abstract: To improve the efficiency of process planning, an CAPP system is developed according to the complexity and particularity of process design for large forgings,. The feature functions of the system are analyzed. The key techniques are discussed. The application results show that the process plans of about 70% large forgings are designed by the system and the efficiency of process planning is improved 4-8 times.

Abstract: Nowadays, the condition monitoring and intelligent fault diagnosis methods research of the needling loom in our country is still a blank. How to establish the appropriate monitoring methods under different working conditions becomes an important issue. In this article, some methods in terms of the open system construction proposed to work out the problems above, which is the Needle Loom condition monitoring system based on working condition parameters. This system take full advantage of the rapid development of hardware and software technology, providing online or offline information to remote monitoring terminals for different processing conditions, enriching remote monitoring data sources, integrated with realizing the needle loom field condition monitoring and the physical state online detections.

Abstract: For the multi specification and small batch productions, because of small batch and short manufacture cycle of product, it is difficulty to get enough sample data used for setup control chart to Statistical Process Control (SPC) of manufacture process quality by traditional SPC method. A new part code system based on OPTIZ code system is proposed by coding parts, manufacturing processes and qualities according to Group Technology (GT) based on similarity theory, so characteristics of parts, manufacturing processes and qualities are transformed to code, analyzed and judged by similarity theory to enlarge sample data, to realize SPC by control chart method. A SPC program for multi specification and small batch production based on group technology is developed by Visual Basic software and verified by actual example.

Abstract: The paper mainly analyses the vibration of air compressor house in colliery, chooses the reasonable vibration-resistance measures and solving schemes and realizes the design aim in phase. It ensures the nicety of decreasing vibration instrument, damped vibration instrument, the efficiency of vibration-resistance over 80% and vibration speed less than 12mm/s, which reduces the effect of vibration for the surroundings.

Abstract: The decision models of closed loop supply chain for scrapped medical equipment that is composed of one medical equipment manufacturer and one medical equipment retailer with product remanufacturing under hybrid recycle strategy was built. The whole-sale price and transfer recycling price were considered as the decision-making variables of the medical equipment manufacturer, and the recycling price as the decision-making variable of the party undertaking the recycling effort. The optimal pricing and the optimal profit were obtained and the optimal decisions of the manufacturer were analyzed on the further. And the profits of medical equipment manufacturer, retailer and the total supply chain are also discussed under different scenario.

Abstract: The square root cubature particle filter (SRCPF) uses the square root cubature Kalman filter (SRCKF) for generating the proposal distribution. The SRCPF algorithm is easy to be implemented and has numerical stability. Moreover, the SRCKF based proposal distribution approximates the optimal importance distribution by incorporating the current measurement. Simulation results demonstrate that the SRCPF algorithm has the better performance for state estimation than the generic particle filter (GPF), extended particle filter (EPF) and unscented particle filter (UPF), and its calculation cost decreases largely.

Abstract: In response to heavy demand for emergency logistics, an approach based on hierarchical network theory is introduced to solve the complexity of highway transportation network. It groups the traffic network into subprime networks and backbone networks on which a virtual local area network is designed accordingly to fulfill such function as information exchange and road condition renewal between forwarding stations. Compared with flat networks, the hierarchical traffic network design is in a good position to speed up routing, to conduct real-time monitoring and data-exchange, and consequently enhances efficiency of emergency logistics.

Abstract: The emission of greenhouse gases leading to global climate warming has caused widespread concern on the part of governments worldwide. As one of the main sources of carbon emissions, modern logistics occupies a unique position for energy saving. But as economic entities, logistics enterprises have no real incentive to implement low-carbon logistics operations, which needs government to stimulate logistics enterprises to implement low-carbon strategy through regulations. Constructed an Evolutionary Game Model for logistics enterprises to implement low-carbon selection decision under the supervision of the government, analyzed the effcts of different regulative parameters on the implementation of low-carbon strategy in logistics business. The results show that government's regulation and strategies play a crucial role in carrying out the low-carbon strategy. Finally, according to different evolution conditions and conclusions, it proposes appropriate supervision strategies for government to promote logistics enterprises to put the low-carbon strategy into effect.

Abstract: Wheat sharp eyespot is an important plant disease of wheat roots. To improve the accuracy of prediction of this disease and to control the disease effectively, This paper presents a new prediction model by principal components analysis (PCA) and back propagation artificial neural network (BP-ANN) methods. The application of BP and PCA in forecasting plant diseases was also summarized. Application of BP Neural Network and PCA in Prediction for wheat Diseases. To build diagnosing wheat diseases based on BP neural network, and PCA was discussed. The precision of the simulation is the high, fault tolerant capacity is better, reliability, and robustness are better. The result of the forecast model is satisfied. So the model of predicting wheat disease based on adaptive neural networks has the important reference value. The test results showed to build the early warning model is effective and likely which, will provide a model to set up the effective early warning platform. Results showed that BP neural network and PCA had a strong application value in the diagnosis of plant diseases.

Abstract: In order to know about the change of concrete stress and internal forces during the construction period of one highway tunnel, to evaluate the safety of lining structure, to take precautions against early diseases and to avoid loss in result of structural instability, linear arrays of fiber Bragg grating sensor in series were used for continuous monitoring typical lining cross section based on wavelength division multiplex. A mass of initial data was acquired. Furthermore, internal forces and early concrete stress of lining were analyzed according to time stress curve and internal force diagram. It has been found that fiber Bragg grating is highly adaptable to tunnel environment and the test method is of high accuracy. Therefore, the method discussed in this paper can be used for field test of tunnel structure extensively.