Applied Mechanics and Materials Vols. 48-49

Abstract: By constructing the exponential delay cost function, we formulate the consumer decision model based on the threshold strategies in dual-mechanism, and prove that there exists a unique symmetric Nash equilibrium in which the high-valuation consumers use a threshold policy to choose between the two selling channels. On the basis of the consumer’s threshold strategies, taking the auction length, the auctioned quantity in each period, and the posted price as the decision variables, we develop the seller’ optimal decision model in dual-mechanism, and show the optimal auction design principle and strategy by numerical analysis.

Abstract: The prioritization of E-Learning setup decision is a complex decision-making problem. The purpose of the paper is to show how to include corporate strategy in the decision-making process and use the Analytic Network Process as a multiple criteria decision-making methodology which can be used in solving E-Learning setup selection problems. In this method, relevant criteria affecting setup are split into three categories: economic criteria, cost criteria and risk criteria. Due to the interdependency between these criteria, ANP was used to generalize analytic hierarchical process by considering the interdependencies among factor. Finally, in order to show the applicability of the propose structure in practice, the structure is implemented to choose the best E-Learning setup policy among three aforementioned strategies in the real case company. Keywords: ANP approach, E-Learning, setup decision, knowledge community

Abstract: A brief introduction of the basic concepts of the classification interval, the optimal classification surface and support vector; explained derivation of SVM based on Lagrange optimization method; Sigmoid kernel function and so on. It describes three methods of C-SVM、V-SVM and least squares SVM based on Sigmoid kernel function. To a bearing failure as a example to compare three results of SVM training of the kernel linear function, polynomial kernel function, Sigmoid kernel function, The results show that satisfactory fault analysis demand the appropriate kernel function selection. Fault in the gear box, the bearing failure is 19%, In addition, the rate is as high as 30% in other rotating machinery system failure [1,2].Thus, rolling bearing condition monitoring and fault diagnosis are very important to production safety, and many scholars have done numerous studies [3,4]. Support vector machine method is a learning methods based on statistical learning theory Vapnik-Chervonenkis dimension theory and structural risk minimization [5,6].

Abstract: Application of amorphous alloy in highly efficient and power dense motors is increasingly being adopted, helping to solve global warming and energy-saving problems. Compared with conventional silicon steel materials, amorphous alloy shows faster flux reversal, lower magnetic loss and more versatile property modification, which result in the possible application in power electronics, telecommunication equipment, electronic article surveillance systems in the future. Some fundamental problems associated with materials processing and device fabrication technology remain to be further improved.

Abstract: Rotor rub-impact fault may be diagnosed through several kind signal such as rotor vibration, stator vibration and rotor transient speed, and every signal include fault features of different side, so it is possible to improve diagnosis successful probability by mul-information fusing method. The fault identifying frame and combination diagnosis rules are determined using stator vibration and rotor transient speed signals. It is adopted to determine mass function by the S-function, and the deducing method is put up. After peak value of stator resonance demodulation and rotor transient speed fluctuation amplitude information are fused, the method is applied to diagnose rotor rub-impact fault successfully.

Abstract: Next generation of Geometrical Product Specifications (GPS) is the foundation of the technology standards and metrology specifications of mechanical and electric products. GPS estimation of measurement uncertainty can improve the reliability of the verification result. In the indirect measurement, the transfer characteristic is very complex. So, it is very difficult to estimate the uncertainty in the indirect measurements according to the transfer formula given by GUM. For the indirect measuring of an inside cone angle, the mathematical relation between the measurand and measurement results is established firstly. Then Monte Carlo method was adopted to conduct the sampling and synthesis of measurement uncertainty contributors. At last, the measurement method was evaluated and improved according to Procedure for Uncertainty Management. Experimental result shows that Monte Carlo Simulation method has a good application foreground in the uncertainty estimation and measurement program design.

Abstract: In order to improve reliability of the excavator’s hydraulic system, an online fault detection approach based on dynamic principal component analysis (PCA) was proposed. With this approach, normal samples were used as training data to develop a dynamic PCA model online with new data. Secondly, T2 statistic and Q statistic performed as indexes of online fault respectively. Several experimental faults were introduced to validate the approach, and the dynamic PCA model developed were able to detect overall faults using T2 statistic and Q statistic. By experiment analysis, the proposed approach achieved an accuracy of 95% for 20 test samples. Experimental results shows that the online fault detection approach could effectively applied to the excavator’s hydraulic system.

Abstract: This paper develops a structured low rank approximation (SLRA) method for noise elimination from a noisy impulsive response function (IRF). Cadzow’s algorithm is implemented for the SLRA on the Hankel matrix constructed by measured IRF in order to obtain a filtered IRF. Using the proposed noise elimination scheme, some important factors, such as the size of a Hankel matrix and the quantification of the noise reduction performance are evaluated. Synthesized IRFs are applied to demonstrate the performance, and illustrate the procedure as well, of the proposed scheme in the numerical study. The results indicate that this method can eliminate noise from measured IRFs efficiently.

Abstract: In order to carry out non-destructive testing on standing trees, explore the propagation characteristics and the influence factors of the ultrasonic wave spreading in the standing trees. Take simon poplar as the research object, Resistograph were employed to test 30 sample (simon polar) standing trees and it gave a preliminary estimate of the internal defects in the samples, and RSM-SYS5 ultrasonic device were employed to test the ultrasonic propagation velocity spreading in simon poplar standing trees, with the statistics of the ultrasonic propagation velocity spreading separately in the health trees and standing trees with defects, and did a regression analysis of the relationship between the size of the defacts and the ultrasonic propagation velocity. The results show that: 1) When the diameter of sample trees are between 30 and 55cm, the radial velocity of ultrasonic spreading in healthy simon poplar standing trees are in the range of 1029.96m/s ~ 1200m/s, all more than 1000m/s; however, when there are defects in simon poplar standing trees, the ultrasonic radial velocity are less than 1000m/s. 2) The defacts in standing trees have an significant influence on the ultrasonic radial propagation velocity spreading in simon poplar standing trees, defect size and the radial velocity is significantly negatively correlated, and the correlation coefficient R is 0.887.

Abstract: Greenhouse is used to produce vegetables in winter, the parameter of environment which suit vegetables grow is a complex and ill-defined problem. Furthermore, burning coal to heat greenhouse is expensive than carry vegetables from south region enormously, so at northeast, most greenhouse cannot produce. On the other hand, there are more than several hundred million ton biomass be burned in field. Not only waste natural resources greatly, but also caused pollution seriously. This paper presents an artificial intelligence control system of northeast region greenhouse base on biomass, peasants can use this system produce vegetables automatically by simple intervening. This system also can learn new vegetables growth data and representation it to control vegetable producing.