Advanced Materials Research Vols. 108-111

Abstract: With the shortage of the gasoline resource day by day, the adjustment of county’s energy strategy, environment protect requirement and the continuous progress of the automobile technology, more and more automobiles were designed on the CNG as their fuel and corresponding CNG stations were increasing at the same time. But the consequential accident such as the leakage of the gas and the fire disaster made the security of the CNG station became a serious problem a problem which people pay more and more attention on it. if the gas was not fired immediately it may construct the gas cloud cluster and will explode when it comes out a fire, and people in a certain distance may wounded by the shockwave also the architectures in the dangerous range will be destroyed. This paper will contribute to formulate the evacuate conditions for pedestrian after the explode accident happening and also will provide the basis for evaluating the new constructed CNG stations.

Abstract: H.264/AVC video coding standard inherited the quadratic rate-distortion model of VM8, and proposed a linear tracking model to predict Mean Absolute Difference of the current frame. Since Rate-Distortion Optimization is introduced, the frame coding complexity MAD is predicted in H.264/AVC rate control. However, any single-mode prediction approach of frame coding complexity has its shortages due to unexpected changes of video source. In this paper, we induct the frame coding complexity based on extensive experiments, and propose an optimized choice approach to predict the frame coding complexity. Simulation results demonstrate that the novel approach for frame coding complexity gains better precision than that of joint model in H.264/AVC reference software.

Abstract: Power quality is the most important problems in power system automation. Aim to analysis and improve the power quality, many types of power quality events, such as voltage unbalanced, harmonic, frequency offset and multiple short time power quality disturbances, should be recorded accurately. This paper proposed a new design proposal of a novel digital fault recorder which could record the power quality waveform signals in 24 hours a day. The original power quality signals are transformed by fast Fourier transforms (FFT) and the waveform distortion is determined by the amplitude spectrum. In order to compression the data of power quality signals, the waveform without distortion is described by the first circle’s waveform. Hence, every power quality events signals and stationary signals will be recorded by one circle signal of each time. Then, the first circle signals of each event are compressed by wavelet transform so as to get higher compression ratio. The signal compressed by DFR will be stored in the Flash or RAM chips and transferred to principal computer. The data will be used for power quality analysis.

Abstract: Diagnosis of condenser abnormality is very important for turbine generator reliability. This paper presents a novel approach for condenser fault diagnosis based on kernel principle component analysis (KPCA) and probabilistic neural network (PNN). KPCA is applied to PNN for feature extraction. It firstly maps data from the original input space into high dimensional feature space via nonlinear kernel function and then extract optimal feature vector as the inputs of PNN to solve condenser fault classification problems. A global optimizer, particle swarm optimizer (PSO), is employed to optimize the parameters of PNN to improve fault classification accuracy. The experimental results show that the proposed approach has a better ability in terms of diagnosis accuracy and computational efficiency compared with a number of popular fault diagnosis techniques.

Abstract: This paper is concerned with the H∞ sampled-data control for a class of fuzzy neutral systems. Employing Lyapunov-Krasovskii functional, the input delay approach, the descriptor system method, Barbalat lemma and the LMI approach, a design method of sampled-data state feedback controller for the fuzzy neutral systems is proposed.

Abstract: This paper discusses the problem of loan portfolio in fuzzy random environment, in real life, because of the influence of random and fuzzy factors, the return rates of loan in bank often have fuzzy random characteristic. Mean chance is a measure of fuzzy random variable, based on mean chance, a new optimization model of loan portfolio is provided. To give a general solution to the new model, a hybrid intelligent algorithm is designed. The algorithm integrates fuzzy random simulation, neural network and genetic algorithm. Neural network is employed to calculate the expected value and the mean chance value, it greatly reduce the computational work. At last, a numerical example is presented to illustrate the new model and the proposed new algorithm.

Abstract: This work was focused on the compressive deformation behavior of 42CrMo steel at temperatures from 1123K to 1348K and strain rates from 0.01s-1 to 10s-1 on a Gleeble-1500 thermo-simulation machine. The true stress-strain curves tested exhibit peak stresses at small strains, after them the flow stresses decrease monotonically until high strains, showing a dynamic flow softening. And the stress level decreases with increasing deformation temperature and decreasing strain rate. The values of strain hardening exponent n, and the strain rate sensitivity exponent m were calculated the method of multiple linear regression, the results show that the two material parameters are not constants, but changes with temperature and strain rate. Then the two variable material parameters were introduced into Fields-Backofen equation amended. Thus the constitutive mechanical discription of 42CrMo steel which can accurately describe the relationships among flow stress, temperature, strain rate, strain offers the basic model for plastic forming process simulation.

Abstract: Automatic obstacle avoidance and road detection for the Automation Guiding Vehicle (AGV) need to calculate the distance, object shape parameter. This paper presents a new obstacle distance calculating method based on monocular vision. Through scene in the two different images corresponding feature points are accurately matched, according two different video frame images disparity to compute distance between AGV and obstacle. In order to accurately find feature points, this paper uses a detection algorithm based on Harris corner, combines epipolar constraint and disparity gradient for image matching. These steps accelerate measure computing results. The basis of known structural characteristics of the road presents a road image morphology algorithm to filter road image noise, combines fast threshold algorithm to achieve a set of structured road recognition guiding system. Experimental results show that the detection method can correctly recognize the structured road of interference with certain obstacle, and achieve a visual robot guiding system.

Abstract: This paper presents an interactive method of using ink diffusion, and gradually approaching simulation brush character with style of Chinese painting and calligraphy. Try to use materials based on the Chinese ink painting: ink and rice paper, according to their characteristics to build the diffusion rules to simulate text ink. Although the initial can show the phenomenon of ink rendering, they can only show diffusion of the ink with black lines, Can not rendering a complete ink diffusion behavior, it is difficult to form a sense of artistic calligraphy. It proposes Interactive model to amend the power of the brush pen and puts forward a binding behavior of ink broken down. The results show that based on the pratice physical meaning, considering the interaction of the two materials(ink and rice paper), appropriate to improve the mathematical equation model to render the calligraphy image more in line with Chinese ink painting style.

Abstract: In order to study the interactive relationships between house price with marc-economy in China and reveal the transmission mechanism, this paper specifies a six dimensional VAR model to identify the forces driving house prices fluctuations in China over the period 1999-2009. By employing quarterly time series for real house prices, gross domestic product, money, consumer price index, market capitalization of tradable shares and labor remuneration of persons employed in all units, the author found that: (1) there is a stable and significant relationship of mutual causality between house price with these three factors including GDP, M2, CPI. (2) house price is quickly responses to the growth or falling of market capitalization of tradable shares .in other words ,it is a single causal relationship between them (3) There is not a significant causal relation between house price with labor remuneration .It may appear surprising. Yet this phenomenon accurately reflects the real estate bubble today. This paper deeply study the transmission mechanism of house price.