Advanced Materials Research Vols. 457-458

Abstract: Hydrodynamic deep drawing (HDD) is an effective method for manufacturing complicated and thin-walled parts. Aiming at the forming process of the stainless steel part with 0.4 mm thick and complex stepped geometries, the technology scheme of multi-stage HDD assisted by conventional deep drawing (CDD) is proposed in consideration of wrinkling and destabilization in the unsupported region of the conical wall, and finite element models are built. As a key process parameter, pre-forming depth on the quality of the parts is explored with assistance of numerical simulations and verification experiments. Furthermore, the failure modes, including wrinkling and fracture during forming process are discussed; meanwhile, the optimum pre-forming depth is realized. The results indicate that the technological method is proven to be feasible for integral forming of thin-walled parts with a large drawing ratio and stepped geometries; moreover, the parts with uniform thickness distribution and high quality are successfully formed by adopting optimum pre-forming depth.

Abstract: The multivariate linear errors-in-variables (EIV) model is frequently used in computer vision for model fitting tasks. As well known, when sample data is contaminated by large numbers of awkwardly placed outliers, the least squares estimator isn’t robust. To obtain robust estimators of multivariate linear EIV model, orthogonal least trimmed square and orthogonal least trimmed absolute deviation estimators based on the subset of h cases(out of n)are proposed. However, these robust estimators possessing the exact fit property are NP-hard to compute. To tackle this problem, an integer-coded genetic algorithm that is applicable to trimmed estimators is presented. The trimmed estimators of multivariate linear EIV model on real data are provided and the results show that the integer-coded genetic algorithm is correct and effective.

Abstract: A discernibility matrix-based attribute reduction algorithm of decision table is introduced in this paper, which takes the importance of attributes as the heuristic message. This method solves the problem of the attribute selection when the frequencies of decision table attributes are equal. The result shows that this method can give out simple but effective method of attribute reduction.

Abstract: Using chaotic anti-control technology to solve the unique noise generated by ocean reconnaissance robot was proposed in this paper in order to improve robot concealment. The mathematical model of ocean reconnaissance robot which thruster device is used as permanent magnet brushless DC motor was transformed in favor of chaotic anti-control study. On this basis, applied time-delay state variable feedback exact linearization method to chaotic thruster device. So the strange attractor of thruster device changed by changing the anti-control controller parameters according to actual situation. Finally, the anti-control controller was designed and verified by computer simulation. The simulation results show that the electromagnetic torque of thruster system can be chaotication under the condition of ocean reconnaissance robot normal running using time delayed state variable feedback exact linearization method. So the electromagnetic torque chaos lead to the shaft vibration changed, and the noise of propeller unique voiceprint characteristic is changed also. As a result, achieve the purpose of confusing the enemy.

Abstract: With the development of the technology and industry of the Internet of Things, the application of the Internet of Things of government and industry has been one important subject for the further development of information construction in China. The paper presents the RFID-based vehicle security monitoring and administration system of the Internet of Things in order to assure the real-time monitoring and security administration in the process of the vehicles going and coming through the gates and the vehicle’s united administration, and designs the security implementation framework of the application of the Internet of Things, and discusses the key technology including super high frequency RFID and boundary security network gateway, and the system and the key technology can broadly apply to the united security monitoring and administration of many vehicles such as buses, cars, trains, and the system of the Internet of Things has been primary implemented and achieved good effects in actual applications.

Abstract: The optical property of near-infrared cyanine dye adsorbed on silver nanopaticals has been studied by means of UV-Vis spectrophotometer. The adsorption of near-IR cyanine dye on silver nanopaticles was highly dependent on the concentration of silver nanoparticles. As a result, in the UV-Vis spectra, it was shown that the “red-shift”, as silver nanoparticles size, increased and the “blue-shift”, as concentration of silver nanoparticle increased as well. The adsorbed spectral peaks of near-infrared cyanine dye disappeared as concentration of silver nanoparticles increased.

Abstract: An early smoke detection algorithm based on Codebook model and multiple features is presented in this paper. First, the foreground is obtained by using the Codebook algorithm. Second, the model of color distribution and the model of shape feathers of smoke are applied to detect the suspected smoke area in the foreground. Finally, the false alarm rate is reduced effectively by using dynamic features in the diffusion process of smoke. Experimental results show that our algorithm has good detection performance and achieves real-time requirement which is very important for real application.

Abstract: For NIR data has the character of high dimension, nonlinear, and high noise, we often confront the problem of dimensionality reduction when building the classification model on Near-Infrared spectra data. Traditional classification methods and linear dimensionality reduction techniques are difficult to improve the model performance. In this paper, a novel nonlinear modeling for NIR spectra analysis was proposed by combining S-Isomap and KNN. S-Isomap is a supervised manifold learning method which can effectively find out the intrinsic low dimensional structure and extract important information from the raw data. Compared with KLLE, KPCA, and other classification methods such as SVM or LDA, the results show that S-Isomap-KNN method performs the best on the modeling of cigarette brand identification. The method is also a good technique for visualization.

Abstract: The function of the elevator is to help lunar rover arrive lunar surface from the top of Lander after landing. Rocker-arm elevator makes Lander overturn easily because its arm is too long. Different compress extent of the Lander leg, complicated condition of landing location, micro-gravity and unloading acceleration have great influence to the stability of Lander. The paper set the ZMP coordinate equation and the coordinate of support polygon by D-H coordinate law, and builds the rule of the stability. Example simulation result shows that the equation and the rule meet the requirement of Lander stability analysis on all different conditions.

Abstract: In order to decrease the error of pose estimation based on image sequences, a filtering method for pose angles based on CS-STF-IMM was proposed. Firstly, current statistical (CS) model was used to establish state space model of pose transformation, which reflects the maneuver of target pose more truly. Then, strong tracking filter (STF) was introduced to overcome the shortcoming that Kalman filter can hardly track sudden maneuver. A parameters determination method based on least square fitting was proposed, which improves the performance of STF further. Based on these, CS-STF-IMM algorithm was established, which obviously improved the precision of pose estimation. Simulations showed that the proposed method has better overall performance, which is a feasible scheme for pose angles filtering.