Angular velocity dynamics identification of small unmanned helicopter using fuzzy model

Attitude identification method for unmanned helicopter based on fuzzy model at hovering is presented.The dynamical attitude model is considered as basis for attitude control and it is very complex.To reduce the complexity of model,nonlinear model of unmanned helicopter with unknown parameters are to be determined by fuzzy system first and then derivative based gradient method is used to identify unknown parameters of model.Gradient method is used due to ability that fuzzy system is not necessarily to be linear in parameters,therefore all fuzzy sets for input and output can be adjusted.The validity of the proposed model was verified using experimental data obtained by the commercially available flight simulator X-Plane.The simulation results showed high accuracy of the modeling method and attitude dynamics data matched well with experimental data.     

Study and application of time series forecasting based on rough set and Kernel method

A support vector machine time series forecasting model based on rough set data preprocessing was proposed by combining rough set attribute reduction and support vector machine regression algorithm. First, remove the redundant attribute for forecasting from condition attribute by rough set method; then use the minimum condition attribute set obtained after the reduction and the corresponding initial data, reform a new training sample set which only retain the important attributes influencing the forecasting accuracy; study and train the support vector machine with the training sample obtained after reduction, and then input the reformed testing sample set according to the minimum condition attribute and corresponding initial data. The model was tested and the mapping relation was got between the condition attribute and forecasting variable. Eventually, power supply and demand were forecasted in this model. The average absolute error rates of power consumption of the whole society and yearly maximum load are respectively 14.21% and 13.23%. It shows that RS-SVM time series forecasting model has high forecasting accuracy.     

The Boiler Tube Wall Thickness Quantitative Evaluation Fusing the Magnetic and Ultrasonic Technique

Wall thickness is always a key index for boiler tube inspection in power plant,in order to improve the inspection efficiency and accuracy,a new method fusing the magnetic and ultrasonic technique was proposed.The magnetic technique was used to do full inspection and locate the flaws,and the ultrasonic was employed to implement further quantitative inspection accu- rately.After comparing the precision of the polynomial,exponential and logarithmic function,the polynomial model was selected to fit the relations between the wall thickness and the peak value of magnetic signals,and the data measured by ultrasonic thickness meter was used to calibrate the model parameters online,the defect depth can be sized quickly.The experimental results demon- grate that the model used in this system has better accuracy than the statistics relation model clearly,and it is also suitable for defect evaluation real-time.Moreover,it is unnecessary to have much more experimental data for the curve fitting technology,so it has better practicability than the other methods.     

Neural network based on adaptive chaotic gradient descending optimization algorithm and its application in matte converting process

An adaptive chaotic gradient descending optimization algorithm for single objective optimization was presented. A local minimum judged by two rules was obtained by an improved mutative-step gradient descending method. A new optimal minimum was obtained to replace the local minimum by mutative-scale chaotic search algo-rithm whose scales are magnified gradually from a small scale in order to escape local minima. The global optimal value was attained by repeatedly iterating. At last, a BP (back-propagation) neural network model for forecasting slag output in matte converting was established. The algorithm was used to train the weights of the BP neural net-work model. The simulation results with a training data set of 400 samples show that the training process can be fin-ished within 300 steps to obtain the global optimal value, and escape local minima effectively. An optimization sys-tem for operation parameters, which includes the forecasting model, is achieved, in which the output of converter increases by 6.0%, and the amount of the treated cool materials rises by 7.8% in the matte converting process.     

Identification on rock and soil parameters for vibration drilling rock in metal mine based on fuzzy least square support vectormachine简

A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibration drilling based on the fuzzy least squares （FLS）-support vector machine （SVM） was developed, in which the fuzzy membership function was set by using linear distance, and its parameters, such as penalty factor and kernel parameter, were optimized by using adaptive genetic algorithm. And FLS-SVM identification on rock and soil parameters for vibration drilling was made by changing the input/output data from single freedom degree model of drilling bit-rock. The results of identification simulation and resonance column experiment show that relative error of natural frequency for some hard sand from identification simulation and resonance column experiment is 1.1% and the identification precision based on the fuzzy least squares-support vector machine is high.     

Evolution algorithm for water storage forecasting response to climate change with little data sets:the Wolonghu Wetland,China

An attempt of applying a novel genetic programming(GP) technique,a new member of evolution algorithms,has been made to predict the water storage of Wolonghu wetland response to the climate change in northeastern part of China with little data set.Fourteen years(1993-2006) of annual water storage and climatic data set of the wetland were taken for model training and testing.The results of simulations and predictions illustrated a good fit between calculated water storage and observed values(MAPE=9.47,r=0.99).By comparison,a multilayer perceptron(MLP)(a popular artificial neural network model) method and a grey model(GM) with the same data set were applied for performances estimation.It was found that GP technique had better performances than the other two methods both in the simulation step and predicting phase and the results were analyzed and discussed.The case study confirmed that GP method is a promising way for wetland managers to make a quick estimation of fluctuations of water storage in some wetlands under condition of little data set.     

Parameter Estimation of Time-Varying ARMA Model

The auto-regressive moving-average (ARMA) model with time-varying parameters is analyzed. The time-varying parameters are assumed to be a linear combination of a set of basis time-varying functions, and the feedback linear estimation algorithm is used to estimate the time-varying parameters of the ARMA model. This algorithm includes 2 linear least squares estimations and a linear filter. The influence of the order of basis time-varying functions on parameters estimation is analyzed. The method has the advantage of simple, saving computation time and storage space. Theoretical analysis and experimental results show the validity of this method.     

Cooling hot rolling steel strip using combined tactics

The coiling temperature control of a typical steel strip mill was investigated.Due to the high speed of a strip and complex circumstance,it is very hard to set up a cooling model with high accuracy.A simplified dynamic model was proposed,based on which a cooling control scheme with combined feedforward,feedback and adaptive algorithms was developed.Meanwhile,the ge- netic algorithms were used for the optimization of model parameters.Simulations with a model validated using actual plant data were conducted,and the results have confirmed the effectiveness of the proposed control methods.At last,a simulation system for coiling temperature control was developed.It can be used for new product trials and newcomer training.     

Simulation of the Ultrasonic Precipitation Process of Nano-hydroxyapatite by an Artificial Neural Network

The ultrasonic precipitation technique for preparing hydroxyapatite nanoparticles is a complex process that was strongly influenced by temperature, reaction time and ultrasonic power. The use of a modified artificial neural network （ANN） was proposed to model the non-linear relationship between ultrasonic precipitation parameters and the hydroxyapatite content. The improved model for processing dataset and selecting its topology was developed using the Levenberg-Marquardt training algorithm and was trained with comprehensive dataset of hydroxyapatite nanoparticles collected from experimental data. A basic repository on the domain knowledge of ultrasonic precipitation process for the preparation of hydroxyapatite is established via sufficient data mining by the network. With the help of the repository stored in the trained network, the influence of preparation temperature, preparation time and ultrasonic sonicating power on the hydroxyapatite content can be analyzed and predicted. The results show that the ANN system is effective and successful in analyzing the influence of ultrasonic precipitation parameters on the preparation of hydroxyapatite nanoparticles.     

Fault diagnosis of power-shift steering transmission based on multiple outputs least squares support vector regression

A method of multiple outputs least squares support vector regression (LS-SVR) was developed and described in detail, with the radial basis function (RBF) as the kernel function. The method was applied to predict the future state of the power-shift steering transmission (PSST). A prediction model of PSST was gotten with multiple outputs LS-SVR. The model performance was greatly influenced by the penalty parameter γ and kernel parameterσ2 which were optimized using cross validation method. The training and prediction of the model were done with spectrometric oil analysis data. The predictive and actual values were compared and a fault in the second PSST was found. The research proved that this method had good accuracy in PSST fault prediction, and any possible problem in PSST could be found through a comparative analysis.     

Numerical evaluation of buckling behavior in space structure considering geometrical parameters with joint rigidity简

The buckling behavior of single layer space structure is very sensitive. The joint rigidity, moreover, is one of the main factors of stability which may determine the entire failure behavior. Thus, the reasonable stiffness of joint system, which is neither total pin assumption nor perfect fix condition, is very important to apply to the real single layer space one. Therefore, the purpose of this work was to investigate the buckling behavior of single layer space structure, using the development of the upgraded stiffness matrix for the joint rigidity. To derive tangential stiffness matrix, a displacement function was assumed using translational and rotational displacement at the node. The geometrical nonlinear analysis was simulated not only with perfect model but also with imperfect one. As a result, the one and two free nodal numerical models were investigated using derived stiffness matrix. It was figured out that the buckling load increases in proportion to joint rigidity with rise-span ratio. The stability of numerical model is very sensitive with the initial imperfection, responding of bifurcation in the structure.     

Matched glass-to-Kovar seals in N2 and Ar atmospheres

The oxidation of Kovar alloy was investigated, the wetting and spreading behavior of hard and soft glasses on Kovar alloy were studed by using the sessile drop method, and the quality and the seal strength of glass-Kovar seals were tested. The experimental results indicated that the preoxidation of Kovar alloy for approximately 10 min at 700℃ in air resulted in excellent adherence in glass-Kovar seals. The wetting and spreading behavior of glass on preoxidized Kovar alloy were superior to that on nonoxidized Kovar alloy. The wetting ability of ASF110 glass, at 950℃ and 980℃ in Ar and N2 atmospheres, was significantly superior to that of ASF200R and ASF700 glasses. The seal quality of the glass-preoxidized Kovar seal was superior to that of the glass-nonoxidized Kovar seal. The shear strength of the ASFll0 glass-preoxidized Kovar seal, which was prepared at 980℃ for 20 min in an Ar atmosphere, was approximately 3.9 MPa.     

Recent developments on applications of sequential loop closing and diagonal dominance control schemes to industrial multivariable system

With a focus on an industrial multivariable system, two subsystems including the flow and the level outputs are analysed and controlled, which have applicability in both real and academic environments. In such a case, at first, each subsystem is distinctively represented by its model, since the outcomes point out that the chosen models have the same behavior as corresponding ones. Then, the industrial multivariable system and its presentation are achieved in line with the integration of these subsystems, since the interaction between them can not actually be ignored. To analyze the interaction presented, the Gershgorin bands need to be acquired, where the results are used to modify the system parameters to appropriate values. Subsequently, in the view of modeling results, the control concept in two different techniques including sequential loop closing control （SLCC） scheme and diagonal dominance control （DDC） schemes is proposed to implement on the system through the Profibus network, as long as the OPC （OLE for process control） server is utilized to communicate between the control schemes presented and the multivariable system. The real test scenarios are carried out and the corresponding outcomes in their present forms are acquired. In the same way, the proposed control schemes results are compared with each other, where the real consequences verify the validity of them in the field of the presented industrial multivariable system control.     

Corrosion behavior of ferritic stainless steel with 15wt% chromium for the automobile exhaust system

The effect of chloride ion concentration, pH value, and grain size on the pitting corrosion resistance of a new ferritic stainless steel with 15wt% Cr was investigated using the anodic polarization method. The semiconducting properties of passive films with different chloride ion concentrations were performed using capacitance measurement and Mott-Schottky analysis methods. The aging precipitation and intergranular corrosion behavior were evaluated at 400- 900℃. It is found that the pitting potential decreases when the grain size increases. With the increase in chloride ion concentration, the doping density and the flat-bland potential increase but the thickness of the space charge layer decreases. The pitting corrosion resistance increases rapidly with the decrease in pH value. Precipitants is identified as Nb（C,N） and NbC, rather than Cr-carbide. The intergranular corrosion is attributed to the synergistic effects of Nb（C,N） and NbC precipitates and Cr segregation adjacent to the precipitates.     

Interfacial intermetallic compound growth and shear strength of low-silver SnAgCuBiNi//Cu lead-free solder joints

The growth rule of the interfacial intermetallic compound （IMC） and the degradation of shear strength of Sn-0.SAg-0.5Cu-2.0Bi-0.05Ni （SACBN）/Cu solder joints were investigated in comparison with Sn-3.0Ag-0.5Cu （SAC305）/ Cu solder joints aging at 373, 403, and 438 K. The results show that （Cul-x,Nix）6Sn5 phase forms between the SACBN solder and Cu substrate during soldering. The interracial IMC thickens constantly with the aging time increasing, and the higher the aging temperature, the faster the IMC layer grows. Compared with the SAC305/Cu couple, the SACBN/Cu couple exhibits a lower layer growth coefficient. The activation energies of IMC growth for SACBN/Cu and SAC305/Cu couples are 111.70 and 82.35 kJ/mol, respectively. In general, the shear strength of aged solder joints declines continuously. However, SACBN/Cu solder joints exhibit a better shear strength than SAC305/Cu solder joints.     

Cadmium in agricultural soils,vegetables and rice and potential health risk in vicinity of Dabaoshan Mine in Shaoguan,China

Soil cadmium （Cd） contamination resulted from mining and smelting is a major environmental concern,and health risk associated with Cd exposure to multi-media through muti-pathway is increasing.Cd concentrations in soils,vegetables and paddy rice were investigated,and potential non-carcinogenic and carcinogenic health risks exposure to Cd were estimated at six villages around the Dabaoshan Mine,South China.A total of 87 soil samples were found to exceed the China＇s maximum permission level （MPL） for Cd,while the highest value of 4.42 mg/kg was found near irrigation ditch associated with Hengshi River in Xinyi （XY） Village.Cd contents in vegetables and rice exceeded the maximum permissible concentration by more than five times in every village.Cadmium accumulation in plants is in the order of celery 〉 lactuca sativa L 〉 Chinese cabbage 〉 Romaine lettuce 〉 asparagus lettuce 〉 mustard 〉 cabbage mustard 〉 cabbage.The mean hazard quotient （HQ） of all villages is in the range of [5.29,25.75],and the mean values of cancer risk for investigated areas are more than 10 times greater than the USEPA （2009） threshold limit value of 10-4.Moreover,human non-carcinogenic and carcinogenic risks are mainly attributable to paddy rice intake,followed by vegetables intake,soil ingestion,inhalation,and dermal contact.The results indicate that Cd has a huge potential risk on human health for the local residents.     

Physically based analytical model for plateau in gate C-V characteristics of strained silicon pMOSFET

A physically based analytical model was developed to predict the performance of the plateau observed in the gate C-V characteristics of strained-Si/SiGe pMOSFET.Experimental results were used to validate this model.The extracted parameters from our model were tox=20 nm,ND=1×1016 cm-3,tssi=13.2 nm,consistent with the experimental values.The results show that the simulation results agree with experimental data well.It is found that the plateau can be strongly affected by doping concentration,strained-Si layer thickness and mass fraction of Ge in the SiGe layer.The model has been implemented in the software for strained silicon MOSFET parameter extraction,and has great value in the design of the strained-Si/SiGe devices.     

Dynamic response of cylindrical cavity to anti-plane impact load by using analytical approach简

The transient response of an unlimited cylindrical cavity buried in the infinite elastic soil subjected to an anti-plane impact load along the cavern axis direction was studied. Using Laplace transform combining with contour integral of the Laplace inverse transform specifically, the general analytical expressions of the soil displacement and stress are obtained in the time domain, respectively. And the numerical solutions of the problem computed by analytical expressions are presented. In the time domain, the dynamic responses of the infinite elastic soil are analyzed, and the calculation results are compared with those from numerical inversion proposed by Durbin and the static results. One observes good agreement between analytical and numerical inversion results, lending the further support to the method presented. Finally, some valuable shear wave propagation laws are gained： the displacement of the soil remains zero before the wave arrival, and after the shear wave arrival, the stress and the displacement at this point increase abruptly, then reduce and tend to the static value gradually at last. The wave attenuates along the radial, therefore the farther the wave is from the source, the smaller the stress and the displacement are, and the stress and the displacement are just functions of the radial distance from the axis.     

Integrated evaluation system under randomness and fuzziness for groundwater contamination risk assessment in a little town,Central China简

An integrated evaluation system under randomness and fuzziness was developed in this work to systematically assess the risk of groundwater contamination in a little town, Central China. In this system, randomness of the parameters and the fuzziness of the risk were considered simultaneously, and the exceeding standard probability of contamination and human health risk due to the contamination were integrated. The contamination risk was defined as a combination of ＂vulnerability＂ and ＂hazard＂. To calculate the value of ＂vulnerability＂, pollutant concentration was simulated by MODFLOW with random input variables and a new modified health risk assessment （MRA） model was established to analyze the level of ＂hazard＂. The limit concentration based on environmental-guideline and health risk due to manganese were systematically examined to obtain the general risk levels through a fuzzy rule base. The ＂vulnerability＂ and ＂hazard＂ were divided into five categories of ＂high＂, ＂medium-high＂, ＂medium＂, ＂low-medium＂ and ＂low＂, respectively. Then, ＂vulnerability＂ and ＂hazard＂ were firstly combined by integrated evaluation. Compared with the other two scenarios under deterministic methods, the risk obtained in the proposed system is higher. This research illustrated that ignoring of uncertainties in evaluation process might underestimate the risk level.     

Biodegradable starch/poly （vinyl alcohol） film reinforced with tita- nium dioxide nanoparticles

Biodegradable starch/poly （vinyl alcohol）/nano-titanium dioxide （ST/PVA/nano-Ti02） nanocomposite films were prepared via a solution casting method. Their biodegradability, mechanical properties, and thermal properties were also studied in this paper. A general full factorial experimental approach was used to determine effective parameters on the mechanical properties of the prepared films. ST/PVA/TiO2 nanocomposites were characterized by scanning electron microscopy （SEM） and X-ray diffraction （XRD）. The results of mechanical analysis show that ST/PVA films with higher contents of PVA have much better mechanical properties. In thermal analysis, it is found that the addition of Ti02 nanoparticles improves the thermal stability of the films. SEM micrographs, taken from the fracture surface of samples, illustrate that the addition of PVA makes the film softer and more flexible. The results of soil burial biodegradation indicate that the biodegradability of ST/PVA/TiO2 films strongly depends on the starch proportion in the film matrix. The degradation rate is increased by the addition of starch in the films.