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A 7-DOF half-car dynamic model which includes the cab mounting system and seat suspension system was established to study the performance of active seat suspension. The optimal control method was applied to design the active control system. Two dynamic simulation models of the passive seat suspension and the active seat suspension were set up by Matlab/Simulink, and the performance of the passive and active seat system was simulated in the time and frequency domain. The simulation results show that the active seat suspension can greatly improve the vehicle seat performance and the study has supplied the academic reference in the applications of the active seat suspension.

In recent years, the rapid growth of the air conditioning load has become the most important reason of the seasonal power shortage. It has great significance to adjust the air conditioning load for changing the load curve of commercial users and realizing the power grid load shifting. In order to achieve the optimal allocation of resources and improve efficiency of using electricity that make the central air conditioning run efficiently, it needs to study the key technologies of load regulation and management of energy efficiency about the central air-conditioning.

To get an effective way of monitoring the diesel engine vibration signal, the author puts forward an optimized method based on rough set attribute dependency. Decision table formed by different data collection form, their decision attribute dependence of condition is different, by comparing the different points of attribute dependence and take it as the quality criteria of measuring points, we can realize the optimization of measuring points. Take a high power diesel engine as an example, the site of rough set theory are used to calculate the typical attribute dependence, the results show that the method can effectively distinguish between different measuring point position and the sensitive degree of different fault types, the vibration signal monitoring position, with better effect is obtained at the same time reducing the effects of noise on fault diagnosis, to improve the accuracy and efficiency of fault diagnosis.

The response surface method (RSM) is widely used to alleviate the computational burden of engineering analyses. For reliability analysis, the common approach in the RSM is to use a linear interpolation technique. However, the experimental points are all arranged using the classical RSM in each process of interpolation. Therefore, the number of experimental points is large that resulting in the efficiency is lower. In this study, an improvement of the RSM for structural reliability analysis has been proposed based on the technique of successive linear interpolation. As seen from the example, the proposed method yields better results than those of the classical RSM, and the number of experimental points using the proposed method is less than that of classical RSM. It seems that the proposed method improves the convergence speed and reduces the computational effort.

Hard and brittle materials such as WC, SiC, and single crystal silicon or germanium are widely used in die/moulds for very high accuracy glass products, medical devices, and sensors for MEMS. Mechanical ductile-mode micro/nano milling is an effective method to create three dimensional geometries on these materials. One of the key factors affecting successfully ductile-mode machining is micro tooling. Due to limitations of commercially available micro tools, custom micro tooling is brought forward to give an active solution to this issue. This paper is a further study on custom micro tooling by the author, and several aspects associated with custom micro tooling have been discussed. Experimental results show the feasibility and effectiveness of the successful ductile-mode machining of hard and brittle materials by custom micro tooling. At last, this paper summarizes the techniques associated with custom micro tooling and point out the key aspects for further research on custom micro tooling.

This Base on the the field data of water and sediment of Yangtze River estuary bifurcation in 2004 fiood season and 2005 dry season, the features and process of water and sediment transport Was analyzed by decomposition mechanism.The law of velocity of residual currentsediment transport rate per unit width and tidal punping effect,which in different season and tide,are focused on.The relationship between the features of water and sediment and channel wvolution was discussed through the results of the discharge of water and sediment,which is a basis in the future study of discharge of water and sediment in estuary.

The material constants calculation models for hyperbolic-sine creep model were proposed. The material constants used in hyperbolic-sine creep model for 316 stainless steel were calculated due to the models proposed and experimental data in the temperature range from 873K to 1023K. The relationships between material constants of 316 stainless steel creep model and temperature were obtained by curve fitting. The creep rate predict model of 316 stainless steel with only stress and temperature was also developed, the creep rates predicted were in good agreement with experimental data.

For evaluation indicators are dependent on each other and contradictory, difficult to conduct a comprehensive evaluation in the oil-gas production management program, the paper uses the fuzzy mathematics method to establish calculation model, selects out a best solution from a number of programs to help field managers to make the right decisions and judgments by the fuzzy comprehensive evaluation.

Design automation is always one of research focuses in the field of industry practices. With the development of computer science and technology, speech recognition technology attracts increasing researchers, and it is widely applied to industrial production. Around design automation, we propose a geometry modeling method through design intent using speech recognition, which is an automatic and efficient geometry modeling method. This paper discusses the speech recognition for design intent of geometry modeling using Hidden Markov Model, HMM. In this paper, firstly, the research framework is explained in detail; Secondly, analysis on the related theory and technology about the speech recognition are conducted, including speech signal collection, technology of data processing, technology of training and recognition of model, etc.; Thirdly, some experiments are carried out to validate above discussions; Finally, recognition efficiency comparisons between HMM and DTW are discussed. Experiments show that using HMM for the speech recognition of design intent is feasible and reasonable.

This paper deals with the testing, isolating and diagnosis of construction machinery. Subsequently, the analysis of operating status, faulty mode and running parameter is carried out. The equipment implements the detection, processing, storage and alarming of the operating status parameters, such as temperature of cooling system, oil temperature, oil pressure, engine rotation speed, oil temperature of torque converter as well as oil level of sump and etc. Meanwhile, the real time fault alarm and historical data analysis results can also be performed and illustrated by vivid graphical interface. The embedded ARM microcontroller, which is the core module of the system, manipulates the data acquisition of operating parameters for the construction machinery. Application software of ARM chip processes the operating status parameters and accomplishes alarm and control operations under failure pattern of the machine. The failure data can not only be displayed and alarmed synchronously, but also can be stored for further fault analysis. The equipment can record various types of operating parameters, and is applicable to many different types of engineering vehicles.