Applied Mechanics and Materials Vols. 128-129

Abstract: A mini permanent magnet synchronous generator (PMSG) for wind power with 24/8 poles was designed, and the mathematic model combining field equation and circuit equations was established. Based on the model, the transient process was analyzed by finite element simulation, and phase voltage, electromagnetic torque both on condition of no-load and load were investigated. Then the characteristics of load voltage, output power, and transfer efficiency under different loads were obtained, which could provide load matching reference for maximum power controllability of the various speed wind turbine. The investigation of the proposed PMSG shows that the rated load voltage is about to be 56 V, the rated power 450 W.

Abstract: The operation control strategies of free-piston engine are investigated in this paper. To start the engine, it needs to adjust the compression pressure and the reset valves should cooperate with the frequency control valve to avoid squirm of the piston for hydraulic leakages. The reset valves should be closed before frequency control valve is opened. A piston position feedback modulation control method which can make sure the piston accelerated continuously is presented. It has fixed frequency control valves open signal moment but no fixed frequency control valves closed signal moment, and the closed signal was activated by piston position feedback.

Abstract: As for shortcomings of PID and modern control method in crane anti-swing system, we introduce the fuzzy theory to the crane anti-swing on base of analyzing the crane trolley’s moving dynamic model. The cooperation between the position fuzzy controller and swing fuzzy controller achieve the goal. We use the fuzzy control system of self-adjustable quantization factors and scale factors to solve the problem that have the oscillation in limit areas causing the load lasting swing during the trolley moving position control. According to the simulation, it can solve the problem and eliminate the steady-state error completely and improve enhance the adaptivity of system. It can make the trolley reach the designation in 15s and keep the load steady.

Abstract: For the domestic food safety problem that caused by the pesticide residues in food, it’s very important to find a convenient and cost-appropriate detection technology. At present, spectroscopy absorption technology has been used for detection of pesticide residues in food. However, there are some deficiencies such as the quantitative detection and the measurement precision. This experiment that based on differential absorption is completed by using miniature fiber optic spectrometer and spectrophotometer, and then the pesticide DDVP is also measured quantitatively. Thus the pesticide residue detection technology that based on spectroscopy absorption is improved to adjust to the practical application.

Abstract: To solve the problem that outlet water index Biochemistry Oxygen Demand (BOD) of the Biological Fluidized Bed (BFB) sewage treatment process is difficult to online measure and optimization control of sewage treatment process, Water quality index neural network soft measurement method and the fuzzy control strategy was put forward in this paper. Considering the sewage treatment process exists nonlinear and time-varying characteristic, the effluent water BOD soft sensor model was established employing the process neural network. On the base of this, the optimization control was realized adopting Dissolved Oxygen (DO) for fuzzy control variable Through the soft measurement and fuzzy control model’s simulation training, Shows that the effectiveness and feasibility of these models, an effective soft measurement and optimization control way for BFB sewage treatment have been provided.

Abstract: Coal-fired power plants are facing a rapid developing tide toward supercritical and ultra-supercritical boiler units with higher parameters and bigger capacity. Due to the large inertia, large time delay and nonlinear characteristics of a boiler’s superheater system, the widely-used conventional cascade PID control scheme is often difficult to obtain satisfactory steam temperature control effect under wide-range operating condition. In this paper, a predictive optimization control method based on improved mixed-structure recurrent neural network model and a simpler Particle Swarm Optimization (sPSO) algorithm is presented for superheated steam temperature control. Control simulation tests on the full-scope simulator of a 600 MW supercritical power unit showed that the proposed predictive optimization control scheme can greatly improve the superheated steam temperature control quality with good application prospect.

Abstract: In this paper, control problem of networked control system with multi-rate input sampling is considered. By lifting technique, the system is transformed into a single-rate sampling system. Channel transmission strategies for both output and input channel are presented in view of the limited communication capacity. Such strategies lead to a switched system configuration. Then, switched control strategy is implemented and control algorithm that guarantees the stability of the systems is presented.

Abstract: Multisource image fusion technology is widely applied in a variety of fields such as remote sensing, computer vision, medical diagnosis and military surveillance. In most instances, multi-spectral and panchromatic images can provide more complementary information for feature extraction. Two kinds of images are used for target recognition. Algorithms based on gradient for image fusion only consider high-frequency information changes of the images, and neglect the richness of high-frequency information. To solve this problem, a new kind of self-adaptive rule and algorithm based on gradient and energy is proposed in this paper by analyzing the internal relations between the statistics and the content of the images. The rule and algorithm take into account the changes in high-frequency information and the richness of high-frequency information, and guarantees the richness of image information. Experiments show that the fusion rule and algorithm can significantly preserve all useful information from primitive images and effectively recognize targets with higher recognition accuracy.

Abstract: In order to process target tracking approximation with unknown motion state models beforehand in a two-dimensional field of binary proximity sensors, the algorithms based on cost functions of particle filters and near-linear curve simple optimization are proposed in this paper. Through moving target across detecting intersecting fields of sensors sequentially, cost functions are introduced to solve target tracking approximation and velocity estimation which is not similar to traditional particle filters that rely on probabilistic assumptions about the motion states. Then a near-linear curve geometric approach is used to simplify and easily describe target trajectories that are below a certain error measure. The validity of our algorithms is demonstrated through simulation results.

Abstract: We present a novel multiscale dynamic methodology for automatic machine vision inspection aiming at characterizing temporal features of tobacco leaves. The image sequences of tobacco leaves are transformed from RGB color space to L*a*b* color space, which provides a uniform perceptual difference measure. The image sequences are then represented by a multiscale Dynamic Hidden Markov tree (DHMT), which models not only inter and intra scale dependences of wavelet coefficients, but also temporal dependences of foreground/background observational properties. Experimental results demonstrate temporal consistent mean and covariance values of model coefficients in a* color channel.