Concrete crane beam on a rock wall on a new structure used in underground building has become more common in recent year. But the concrete beam cracking problem always perplexes scientists and engineers. In order to solve this, the construction information inversion and feedback analysis method is applied. A beam section was taken as a prototype experiment. The temperature and construction data was collected to inverse some necessary thermal parameters. According to the characteristics of concrete temperature field, the basic accelerating genetic algorithm was improved. The improved accelerating genetic algorithm has the merits of high precision and fast calculation. With this algorithm, the calculation temperature and measured value are very close, which shows the method is efficiency. Then inversed parameters were applied in the feedback simulation. According to the simulation results, the proper temperature control method was suggested. By this way, the concrete temperature was controlled well and the beams appear no crack in recent two year. The successful application shows that the inversion and feedback analysis of concrete temperature field can reflect the factual performance of concrete and give important direction to engineering construction.

Under the background of the deficiencies and shortcomings in traditional diesel engine fault diagnostic, the naïve Bayesian classifier method which built on the basis of the probability density function is adopted to diagnose the fault of diesel engine. A new approach is proposed to weight the super-parent one dependence estimators. To verify the validity of the proposed method, the experiments are performed using 16 datasets collected by University of California Irvine (UCI) and 5 diesel engine datasets collected by our lab. The comparison experimental results with other algorithms demonstrate the effectiveness of the proposed method.

The mechanistic analysis presented in this paper is only the beginning of new approach for understanding the real joint load transfer capability on airport and highway concrete pavements. It gives up the two major assumptions those have been popularly adopted by hundreds of published papers: the load is transferred under a wheel with zero speed and with fixed position. The real load transfer in field is always under wheels with non-zero speed and with varied position at any moment. The objective of this study focuses on quantifying the dynamic effects of a moving wheel while it is crossing a joint on a pavement. The analysis is conducted using a model of two-slab system on Kelvin foundation under a moving wheel with variable speed v, different pavement damping Cs, foundation reaction modulus k and foundation damping Ck. The dynamic joint load transfer efficiency is temporarily and empirically defined by the peak strain ratio LTE(S) on the two sides of a joint. The primary findings include: (1) The higher speed of a moving wheel leads to the higher LTE(S);(2) The larger the pavement damping Cs leads to the higher LTE(S);(3) The numerical ratio c(=LTE(S)dynamic/ LTE(S)static) varies in the range 1 to 2 mainly depending on speed v and damping Cs;(4) The LTE(S)dynamic is not sensitive to foundation reaction modulus k and foundation damping Ck. Further researches are needed for appropriate applications of the new model in practice.

If the natural scenes decomposed by basic ICA which simulates visual perception then the arrangement in space of its basis functions are in disorder. This result is contradicted with physiological mechanisms of vision. So, a new compute model is proposed to simulate two important mechanisms of vision which are visual cortex receptive field topology construct and synchronous oscillation among neuron group. To solve the problem of train image fault detection, a novel algorithm was proposed based on above compute model. The experiment results show that, the algorithm can increase fault detection rate effectively compared with traditional methods which absence of above two important mechanisms of vision.

Clustering belief functions is not easy because of uncertainty and the unknown number of clusters. To overcome this problem, we extend agglomerative algorithm for clustering belief functions. By this extended algorithm, belief distance is taken as dissimilarity measure between two belief functions, and the complete-link algorithm is selected to calculate the dissimilarity between two clusters. Before every merging of two clusters, consistency test is executed. Only when the two clusters are consistent, they can merge, otherwise, dissimilarity between them is set to the largest value, which prevents them from merging and assists to determine the number of final clusters. Typical illustration shows same promising results. Firstly, the extended algorithm itself can determine the number of clusters instead of needing to set it in advance. Secondly, the extended algorithm can deal with belief functions with hidden conflict. At last, the algorithm extended is robust.

In irrigation of a farm well, the power factor of the load is low when the motor operates, because of the long low voltage lines. Long-term use will cause a lot of energy waste. To this question, this paper presents a new type intelligent controller to save irrigation water and energy. The principle of the new type field irrigation intelligent controller that based on AT89LV52 single chip is introduced in this paper. The integration of the low pressure electrical energy reactive compensation control and IC card prepaid multi-user three-phase watt-hour meter management is realized in the system. The energy conservation control, using the low pressure electrical energy reactive compensation, and prepaid multi-user three-phase watt-hour meter are used to realize the saving water management. Who inserts the card who irrigates. The design of hardware circuit, software flow, and experiment results are presented in detail. The results of testing and preproduction in Zibo Billion Electron Co., Ltd show that the design technique of integration controller is novel, and the system has the characteristics of controlling efficiency by reactive compensation, accurate measurement of electrical energy, flexible power consumption management with IC card prepaid multi-users, saving water , low cost, and so on. Therefore, it is especially suitable for power consumption and water resources management in rural well irrigation. The new type intelligent controller can effectively reduce the cost of irrigation and promote rural economic development.

Edge detection is the most basic problem in the process of image processing. The precision of traditional edge detection algorithm is not very high, it unable to meet the high precision need of modern industrial test technology. In order to overcome the deficiency, this text proposed subpixel edge detection algorithm based on the function curve fitting-Gauss fitting of gradient direction sub-pixel edge detection algorithm. According to the gradient distribution of the image, this text use gauss curve fitting the edge in order to realize the sub-pixel location. This text compared this algorithm with sub-pixel edge detection based on the LOG operator and sub-pixel edge detection based on the quadratic, and draw that this algorithm not only have the short running time and high efficiency, but also has proved that the algorithm has rotation invariant through the experiment. It is that pattern recognition and picture measure the important pretreatment means in the course to follow the method at the border, contradiction at accuracy and speed that but follow the method and exist at the traditional border. To above-mentioned problems, this text proposes following algorithms at the border based on model, and then try to get the diameter of the cutter. The experiment shows this algorithm at the realization border that can be very good and follows, measure the comparison of the algorithm through two kinds of diameters, drawing the running time of least square method shorter, efficiency is relatively high.

The dynamics of a small solid launch vehicle has been investigated. This launcher consists of a liquid upper stage and three fundamental solid rocket boosters aligned in series. During the ascent flight phase, lateral jets and grid fins are adopted by the flight control system to stable the attitude of the launcher. The launcher is a slender and aerodynamically unstable vehicle with sloshing tanks. A complete set of six-degrees-of-freedom dynamic models of the launcher, incorporation its rigid body, aerodynamics, gravity, sloshing, mass change, actuator, and elastic body, is developed. Dynamic analysis results of the structural modes and the bifurcation locus are calculated on the basis of the presented models. This complete set of dynamic models is used in flight control system design. A methodology for employing numerical optimization to develop the attitude filters is presented. The design objectives include attitude tracking accuracy and robust stability with respect to rigid body dynamics, propellant slosh, and flex. Later a control approach is presented for flight control system of the launcher using both State Dependent Riccati Equation (SDRE) method and Fast Output Sampling (FOS) technique. The dynamics and kinematics for attitude stable problem are of typical nonlinear character. SDRE technique has been well applied to this kind of highly nonlinear control problems. But in practice the system states needed in the SDRE method are sometimes difficult to obtain. FOS method, which makes use of only the output samples, is combined with SDRE to accommodate the incomplete system state information. Thus, the control approach is more practical and easy to implement. The resulting autopilot can provide stable control systems for the vehicle.