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After the primary exploration of the preparation procedure of phenolic foam, we studied the modification of phenolic foam by graphene oxide. According to our researches we found that the influence of modifier to the percentage of close area was very little, but it can greatly decrease the thermal conductivity of phenolic foam. In this way, phenolic foam thermal conductivity can be reduced to 0.025 W/m.K.

The effects of oxidized copper ores which came from Yunnan province were carried out by using ammonialeaching methods in the laboratory.In order to seek the optimum leaching conditions under normal temperature and pressure,we conducted a series of validation experiments. Theoptimum conditions were obtained as follows: ammonia concentration 2.5mol/L, ammonium sulfateconcentration 2.5mol/L,grinding fineness about 80% -0.074mm, liquid-solid ratio 2.5:1and leaching time was 2.5h. Under these experimental conditions, the copper leaching rate could reach 69.91%.

For the comprehensive recovery of copper, zinc, silver and iron from the zinc volatile kiln slag in Xining, exploratory experiments were conducted by adopting single flotation, magnetic separation and combined process of magnetic separation and flotation. The results showed that the above process cannot effectively recover copper, zinc and silver from the ore. The recovery of iron is better by single magnetic separation. The grade of iron concentrate reaches 69.05% and the recovery is 41.86%.

Certain type of microwave range finder has been designed by adopting the technologies of DDS (direct digital frequently synthesis) digital signal synthesis and online signal detection, synthetically applying equal-accuracy frequency measuring method, automatic control of frequncy drift and quick interpolation method, combining WINDOWS API programming, Labview programing and fault disgnosis expert system. Eventually, accuracy verification and fault defect of microwave range finder are accomplished.

According to such problems as complicated structure, too many circuit module and online difficult detection of vehicle-mounted platform inertial navigation system, the detector adopts the detection mode of platform + adapter to realize the universalization and modularization of the detection equipment. It reduced circuit scale and the difficulty of design, strengthened systems scalability, at the same time made equipment carry and use more flexible. It realized inertial navigation board level to device level detection by using intelligent fault diagnosis technology to automatic fault diagnosis of circuit. Meanwhile, with the effective optimization of lesser detection procedures, the high efficiency and accurateness of fault isolation and location had been guaranteed, detection equipments automation, integrated, accuracy greatly raised, and detection time greatly shortened.

TiO2 nanotubes were obtained by calcining at various temperatures. The influence of calcination temperature on the degradation activity of TiO2 nanotubes for Cr (VI) was investigated under UV light irradiation. It was found that the photocatalytic activity of TiO2 nanotubes calcinated at 350 °C was the highest. Furthermore, the photocatalytic activity of TiO2 nanotubes was higher than that of the P25 TiO2 nanoparticles. Importantly, the stability of TiO2 nanotubes for the degradation of Cr (VI) was high, and degradation efficiency can still reach 72.4% after 8 recycles. Consequently, a highly stable and active photocatalyst for degradation of Cr (VI) was achieved.

In this paper, a kind of transform has been given for an image that switches to a matrix. A Radar image is an RGB image. An RGB image is usually represented to three layers: Red, Green, and Blue. Each layer can be changed to a matrix. We give a way to transform the three layers to one matrix. All image information will be remained. According to this way, the hail cloud radar image had been transformed to a matrix. The information of hail will been remain in this matrix.

Road quality information detect system is an important component in architecture quality detect system, also is the basement of successfully working of other related project for the whole country. The study of detecting the road crack is the key to insure the security of accurately detect the road quality in transportation system. In this paper, we come up with a fixed way of road undersized rift image detection by using cellular neural networks. By image processing, building rift networks and details networks and adding the model of similarity undersized rift networks. It can avoid the problem that can not accurately detect undersized crack by only taking the crack feature value. The experiment proved that fixed crack detect computing is easy to do, more accurate to detect the undersized cracks on the road and can reach the standard level of current detect technique.

The definition of the cold chain logistics and the problem of the agricultural cold chain logistics are introduced. According to the characteristics of cold chain logistics, exploring the cold chain logistics distribution path optimization method. Based on the model of the agricultural products cold chain logistics distribution routing optimization, particle swarm optimization algorithm is constructed to solve the optimization problem. Taking an example, the results have been conducted finally to demonstrate the effectiveness of the algorithm for agricultural products cold chain logistics distribution routing optimization problem.

This paper presents the results of a study on the early-age cracking behavior of diaphragm in long-span prestressed concrete box girder bridge with cracking control techniques. Based on the three-dimensional hydration heat temperature conduction and humidity diffusion theory, and according to the similarity of differential equation between the humidity diffusion theory and temperature conduction theory, the early-age cracking of diaphragm was simulated by a three-dimensional finite element model with consideration of concrete shrinkage, creep, cement hydration heat and variation of temperature. The numerical simulation accurately predicts the cracking region and size and stress time history of diaphragm, and provides load standard for cracking control techniques of prestressing force. The cracking control techniques of prestressing force effectively avoid the early-age cracking of diaphragm by application of practical engineering.

Database technology as the data management technology, has become the main mean in the extraction methods of computer information management. This paper is focus on the information extraction and puts forward an inaccurate method of statistical model structure of planning database to carry on the information extraction method. For information database technology, it can record text address and cited as an example to have information extraction method. And it establishes a conditional probability distribution of the automatic extraction model of information and data, and gives input sequence, establishes the target demand curve, at last has best segmentation of the data information, to seek out information extraction path and the algorithm formula.

Aiming at the problem of calibrating the INS in non-laboratory conditions, this thesis proposes the calibration methods by as the core and combined use of double-position directional gyro calibration, four-position horizontal gyro calibration and Schuler circuit accelerometer calibration etc. It builds up the model for scale factor calibrating, controls the inertial platform by the embedded control technique to make it the three-axis turntable state, and uses the Linux OS and C language design control software to design and develop the automatic calibration equipment for the INS. This equipment is simple in operation, easy in use and portable, and therefore can realize automatic calibration in non-laboratory conditions. And the results meet the requirements for guarantee the precision of the system in use.

This article based on Real measurement data of mine, then use Probability integration and Numerical Simulation that most commonly used methods in movement and deformation prediction to compute. By comparing the final sinking graph of the two methods and the actual data, to achieve the applicability and accuracy of two ways. The research have certain reference significance and revelatory effect on the selection of different methods of the surface subsidence prediction.

Based on the analysis of the early shrinkage mechanism of concrete, shrinkage experiment of new concrete restrained by old concrete were conducted to analyze the impact of the different interface roughness on shrinkage stress of new concrete and bonding surface. It is shown that the inner tensile stress of new concrete decreases with increasing of interface roughness, and increase restrained thickness of the new concrete, but it is not significant effect of interface roughness on the shrinkage at bonding surface; the shrinkage strain of section reduces with reduction of the distance of section to bonding surface and reaches minimum on bonding surface, which reflecte significant nonuniformity and increases gradually with age.

Talcum is a common gangue with which sulphide ores are associated, it has an adverse impact on sulphide ores flotation and product index due to its high natural floatability. In this paper it takes talcum-bearing copper sulphide ores from DongChuan in Yunnan province as experimental samples, and a series of tests on depressing talcum in the copper suphide ore flotation were carried out. Results show that when took the composed CMC and sodium hexametaphosphate as depressant with respective dosage 200g/t and 300g/t, it obtained a favourableeffect. In addition, depression effect can get improved with the dosage of collector increasing properly, it shows that when took the composed CMC and sodium hexametaphosphate as depressant, it can make the flotation process stable.It employed rougher-scavenger-three cleaners system as the closed-circuit flowsheet, and attained a Cu concentrate product of whom grade and recovery is 16.16%, 78.78% respectively.The results might contribute to dispose some similar talcum-bearing sulphide ores in the future.

To overcome the difficult in modeling the mode theory for magnetic flywheel, by non-parametric frequency domain identification method for identification of system model, this paper select the PID neural network nonlinear intelligent control methods based on GA. Used a method based on iterative process to suppress the resonance, combined with zero-pole theory, this research designed a GA-based PID neural network identification controller to address the modal vibration suppression problems in the external rotor flywheel .The experiments for this paper proved the effectiveness of iterative process, and the controller can restrain the system mode vibration well.

The magnetic flywheel is widely used in energy storage and spacecraft, and it needs to reduce the system’s power consumption effectively when designing the controller. Always, the magnetic bearing system’s performance depends on the tracking performance of the desired force signal. In order to balance the two goals between reducing magnetic system’s power consumption and guaranteeing its performance, a current power allocation way was proposed, and a static current optimization was given based on the way. According to the simulation and experimental results, this method can reduce the magnetic bearing system’s power consumption significantly and keep the tracking performance of force signal well on the same time.

This paper analyzes the operational principle of airborne radio system on unmanned aerial vehicle, puts forward a design plan for excitation source of airborne radio system on unmanned aerial vehicle based on USB bus, realizes the performance detection and failure isolation of airborne radio system on unmanned aerial vehicle, and provides the detailed introduction for the key units. The experiments show that the excitation source can meet the maintenance and training requirements of airborne radio system on unmanned aerial vehicle.

As the support structures of building for crossing river, piers of bridge and/or aqueduct are generally arranged in tandem along the river direction, the fluid dynamic forces are main lateral loads acting on the Piers. Two-dimensional fluid computations have been performed using LES model to investigate the flows around three circular piers in tandem arrangements at a supercritical Reynolds number, Re =8.76×106. Both center-to-center spaces are L/D=2.6. The flows and fluid-dynamic forces obtained from the simulations are analyzed. The results can provide the basis for the dynamic design of the supporting structures of the aqueducts.

Cell Nerve Network (CNN) has been used to process the cloudy radar image. And then we use mathematic to diagnose the cloudy is hail or not. Veins is useful in diagnose the hail cloudy in weather forecast. The veins of the radar image have been picking up according the CNN. And then find the regular polynomial to processed radar image .Then analysis the image with polynomial fitting. We enlarge eight times of the key part of the radar image, and then detect the edge of the image. Dug some data as information .At last we find some regular to distinguish the cloud with hail or not. We find those are useful way for forecasting of hail.

The vehicle flexible coefficient and the center of carbody sway movement are deduced. Based on the deduced equations, the influence of some critical parameters is studied for Motor Cars. In order to get the influence of the primary suspension on the dynamic performance, a vehicle model considered as a multiple rigid body system composed of wheelsets , bogie frames, carbody, primary and secondary suspensions is set up. Dynamic simulation results show that the primary suspension has a large influence on the vehicle.

In allusion to research status that structure stability performance of Self-balanced prestressed latticed shell assembled with elements is not explicit, using the finite element analysis method study structure stability to a large span latticed shell. The eigenvalue buckling analysis of latticed shell use Block-Lanczos method, and nonlinear analysis adopt consistent mode imperfection method. Through the contrast analysis from buckling load, buckling modes, degree of prestress, different initial disfigurement in latticed shell structure, obtaining the disciplines that structure stability properties of the large span prestressed latticed shell, related conclusions to the engineering design of new latticed shell are instructive.

Aiming at the problem of NewMoment algorithm frequently do leftcheck operation in the data mining process, which leads to the low efficiency of algorithm. In this paper, a new method, called LevelMoment, is proposed to improve the NewMoment algorithm which mines frequent closed itemsets over data streams. In this process, a new data structure that added in level node, called LevelCET, is proposed. On this structure, using level checking strategy and optimum frequent closed items checking strategy can quickly tap all the frequent closed itemsets over data streams. The experiments and analysis show that the algorithm has good performance.

Self-balanced prestressed shell structure assembled with elements is a new spatial system composed by prestressed cable and strut elements. The structure can achieve the latticed shell design that the large span without the center column by the rational use of high strength bars and prestressed technology. This paper illustrates the design idea, stress mechanism and structure characteristics of the self-balance prestressed latticed shell. The current research status of self-balanced prestressed shell structure assembled with elements on structure form, shaping method, static and dynamic performances are briefly described in the presented work; It is seen that the research on test of structure mechanical properties, molding technology and structure dynamic performance is an urgent work to be solved in the development of the self-balanced pre-stressed latticed shell structure theory.

The normalization method is utilized in this paper for gait planning of small humanoid robot, and hence generating the normalized trajectory curves for parameters such as three dimensional coordinates and rotation angle and achieving omni-directional legged locomotion of robot. The advantages of this method include less computational complexity of controller, on-line real-time planning of robot, and better stability in motion and flexibility in control. Test results demonstrate that the robot can walk stably towards all directions at the walking speed of 0.8km/h.

The visible-light photocatalytic activity of titanate nanotubes (TiNTs) sensitized by 5,10,15,20-tetraphenylporphyrin (TPP), 5,10,15,20-tetraphenylporphyrin manganese (MnTPP), 5,10,15,20-tetraphenylporphyrin nickel (NiTPP) and 5,10,15,20-tetraphenylporphyrin zinc (ZnTPP), respectively, was investigated by the photocatalytic degradation of methyl orange (MO) as a probe reaction. The results showed that the central ions of porphyrins had an important influence on the photocatalytic activity of the samples. The activity was in the order of TiNTs-ZnTPP > TiNTs-TPP > TiNTs-NiTPP > TiNTs-MnTPP. Combined the result of absorption spectra with that of fluorescence spectra, it was demonstrated that various visible-light absorption and photoelectron transfer caused by the central ions of porphyrins were the decisive factor for the visible-light photocatalytic activity of the sensitized TiNTs.

In order to overcome the system nonlinear instability and uncertainty inherent in magnetic bearing systems, two PID neural network controllers (BP-based and GA-based) are designed and trained to emulate the operation of a complete system. Through the theoretical deduction and simulation results, the principles for the parameters choice of two neural network controllers are given. The feasibility of using the neural network to control nonlinear magnetic bearing systems with un-known dynamics is demonstrated. The robust performance and reinforcement learning capability in controlling magnetic bearing systems are compared between two PID neural network controllers.