Applied Mechanics and Materials Vols. 284-287

Abstract: The main objective of this investigation is to improve the tracking accuracy of a piezo-actuated positioning stage using an iterative learning control. First, to compensate for the tracking error of the piezo-actuated positioning stage that is caused by nonlinear hysteresis, the dynamics of the hysteresis is modeled using the Bouc-Wen model. The particle swarm optimization (PSO) is used to determine the parameters of the inverse-hysteresis model. Second, the design of an iterative learning control is presented. Based on the simulation, the appropriate value of the learning rate is determined. Finally, the efficacy of the approach is demonstrated to achieve high accuracy positioning via the real-time experiments. The experimental result of the piezo-actuated positioning stage is measured by the laser interferometer (HP-5529A). The experimental results show that the iterative learning control can compensate the hysteresis-caused tracking error and the positional accuracy of better than 100 nano-meter is readily achieved.

Abstract: The present study proposes a windshield warning system for vehicles that marks potential hazardous objects in front via marks on the windshield. The target is identified by the camera and the software system and then used to construct the line-of-sight equation based on the coordinate system of the moving vehicle. The explicit equation of the intersection point of the line of sight and the windshield surface is derived using an algebraic method. A warning mark is then projected at the intersection point on the windshield by a two-degree-of-freedom laser projector, allowing the driver to easily identify the obstacle. The feasibility of the proposed system was verified using an actual vehicle. Results show that the system can perform the required function in real time.

Abstract: This paper describes an image-based visual servo tracking control scheme using CMAC neural network as object recognition feedback methodology. A web camera based image capture system is mounted on the slider robot to capture the desired object and a CMAC (Cerebellar Model Articulation Controller) based object recognition scheme is developed to recognize the captured object image. Comparing the relative location of the recognized object and the web camera, then the position feedback signal can be obtained. Using the feedback signal, a PID (Proportional-Integral-Derivative) controller is designed to track the desired object by moving a single-axis slider robot, such that the captured object image located on the center of the captured frame always.

Abstract: The mixing behavior of two fluids in a passive micromixer with a Y-type inlet and helical fluid channels with herringbone grooves etched into the bottom was studied in a numerical simulation and experiments. The mixing of the pure water and acetone solution prepared with different Reynolds numbers and acetone concentrations was investigated. An image inspection method using the variance in contrast of the image gray level as the measurement parameter was adopted to calculate the mixing efficiency distribution. Inspection results show that the mixing efficiency decreased with the increase in the concentration of the acetone solution, although the mixing efficiency around the outlet reached to a value of 90%, even when the Reynolds numbers of the fluids were as low as Re = 1, and the best efficiency achieved for the case of Re = 10 was over 98%. The results show that it should be possible to apply the proposed micromixer in the field of biomedical diagnosis.

Abstract: Train detection, as part of the railway signaling system, is important for safe operation of high-speed railway. The recent flourishing development of high-speed railway stimulates the research need of train detection technology to enhance the safety and reliability of train operation. This paper proposes a new technique for train detection through magnetic field measurement by giant magnetoresistive sensors. This technology was studied by the analysis of magnetic field distribution in the high-speed rail system obtained from modeling and simulation. The results verify the feasibility for detection of train presence, number of rolling stocks, speed, and length. It can overcome the limitations of track circuits and provide additional measurement capabilities to the signaling system. This detection system can be built with low cost and minimal maintenance load as well as compacted construction. Therefore, it may serve as a new train detection system to help improve the current systems, enhancing and promoting the safety and reliability of high-speed rail system.

Abstract: In this paper, a block-edge based Single-Pass Perceptual Embedded Zero-tree Coding (SPPEZC) method is proposed and implemented on the DSP-based platform. SPPEZC combines two novel compression concepts which are Block-Edge Detection (BED) and Low-Complexity and Low-Memory Entropy Coder (LLEC) for the coding efficiency and quality. Besides, the proposed SPPEZC is implemented as fixed-point version and optimized on the DSP-based platform based on both the presented platform-independent and platform-dependent optimization technologies. The performance including compression quality and efficiency is validated by experimental results.

Abstract: In this paper, the Box–Cox transformation-based annealing robust fuzzy neural networks (ARFNNs) are proposed for identification of the nonlinear Magneto-rheological (MR) damper with outliers and skewness noises. Firstly, utilizing the Box-Cox transformation that its object is usually to make residuals more homogeneous in regression, or transform data to be normally distributed. Consequently, a support vector regression (SVR) method with Gaussian kernel function has the good performance to determine the number of rule in the simplified fuzzy inference systems and initial weights in the fuzzy neural networks. Finally, the annealing robust learning algorithm (ARLA) can be used effectively to adjust the parameters of the Box-Cox transformation-based ARFNNs. Simulation results show the superiority of the proposed method for the nonlinear MR damper systems with outliers and skewness noises.

Abstract: Forward looking collision avoidance radar has been extensively researched by domestic and external. Two-dimensional scanning and controlling method can be applied to front-visual automobile collision avoidance lidar to acquire intensity image and range profile of the targets. But it has some disadvantages of complex system, large volume, high cost and it is difficult in practical applications. In comparison to two-dimensional scanning image system, one-dimensional scanning image lidar cannot reconstruct 3D image of target, whereas the imaging speed is much more rapid due to less scanning points. In this work, a one-dimensional scanning semiconductor imaging lidar system was developed, which was composed of laser system, optical system, scanning system, detecting system and signal processing system. Real-time intensity images of black and white stripe targets were obtained in the laboratory. The study results provided foundation for further practical application. This lidar system owns the advantages of simple structure, high speed imaging, low cost, etc. It can be promisingly applied in forward looking automotive collision avoidance lidar system.

Abstract: A radial basis function neural networks (RBFNs) mobile robot control system is automatically developed with the image processing and learned by the bacterial foraging particle swarm optimization (BFPSO) algorithm in this paper. The image-based architecture of robot model is self-generated to travel the routing path in the dynamical and complicated environments. The visible omni-directional image sensors capture the surrounding environment to represent the behavior model of the mobile robot system. Three parameterize RBFNs model with the centers and spreads of each radial basis function, and the connection weights to solve the mobile robot path traveling and routing problems. Several free parameters of radial basis functions can be automatically tuned by the direct of the specified fitness function. In additional, the proper number of radial basis functions of the constructed RBFNs can be chosen by the defined fitness function which takes this factor into account. The desired multiple objectives of the RBFNs control system are proposed to simultaneously approach the shorter path and avoid the unexpected obstacles. Evaluations of PSO and BFPSO show that the developed RBFNs robot systems skip the obstacles and efficiently achieve the desired targets as soon as possible.

Abstract: Micro catalytic combustors are studied experimentally. Microchannels, coated with Pt catalytic walls and columns were fabricated to investigate microscale catalytic reaction. This microscale reaction enhancement by Pt catalytic surface area is characterized by increasing outlet gas temperature with the increase of surface-to-volume ratio. It is found that the reaction efficiency improvement by Pt catalytic columns will extend the operation conditions especially for smaller microchannel size.