Advanced Materials Research Vols. 765-767

Abstract: The purpose of this study is to describe a novel topologic technology for wireless power transmitting through external coils to multiple implantable micro-electromechanical devices inside the patient body, which is able to solve the dilemma of recharging. Wireless power transmitters are designed based on class π-type topologic structure, which improves existing Class-E power amplifier structure and impedance matching technology. Mathematical Models based on resonating chopper MOSFET and class π-type impedance matching network are introduced to optimize the design parameters. Together with proper capacitors and high-flux, low-loss inductors, an optimal wireless power transmitter with significant characteristics of high efficiency and low loss takes advantage of this brand new type of topologic structure. The author designed and developed the RF oscillator and the actual class E power resonant amplifier. During studies, with the 12V power supply, the voltage of 96.8V is generated on the 50ohm high-power RF load side, along with source current of 2.183A. The efficiency of the system reaches 89.4%, which satisfied the need for implantable micro-electromechanical device.

Abstract: The theoretical basis of the Infrared analyzer is expounded in this paper. To Lambert-Beer absorption law, the paper has made math derivation and gives introduction about Infrared absorption spectra of some common gas. The focus is on spectroscopic techniques involved in Infrared gas analyzer, optical path design of optical system and monitoring technology.

Abstract: Aiming at BP neural network algorithms limitation such as falling into local minimum easily and low convergence speed, an improved BP algorithm with two times adaptive adjust of training parameters (TA-BP algorithm) was proposed. Besides the adaptive adjust of training rate and momentum factor, this algorithm can gain appropriate permitted convergence error by adaptive adjust in the course of training. TA-BP algorithm was applied in fault diagnosis of power transformer. A fault diagnosis model for power transformer was founded based on neural network. The illustrational results show that this algorithm is better than traditional BP algorithm in both convergence speed and precision. We can realize a fast and accurate diagnosis for power transformer fault by this algorithm.

Abstract: The detection of blood glucose concentration plays an important role in diabetes treatment. This paper proposes a design which is compatible with finger blood signal acquisition and dynamic blood sugar monitoring in real time. It mainly studies different biosensors which are used to do the glucose signal acquisition. Then we discuss the processing methods of human blood glucose signal using the sensors we studied. This paper outlines the hardware implementation and software management. Based on the core of STM32 embedded microprocessor, the system can achieve glucose signal acquisition, LCD display, historical records restore, data transmission by USB and wireless transmission through Bluetooth. At last, system functions are tested. It is proved that the system is reliable and performs well.

Abstract: Currently, mine safety is the focal point in mining activity. As a new and advanced approach for geophysical prospecting, the ground penetrating radar (GPR) is used in the mine disaster detection. Aiming to solve the restriction of low resolution and limited depth of the GPR in the deep coal seam detection, the computed tomography (CT) technology is employed for deep disaster detection in this paper. A large number of coal seam digital simulation model, including different internal diseases, are established, and the simulation data are processed by using the Least Square QR-factorization (LSQR) inversion algorithm, which has the good performance in saving computational time and memory space. Additionally, the influences of iteration precision and grid size on the effect of inversion are analyzed. The inversion results show good agreements with simulation model feature configurations, and the diseases objects can be detected.

Abstract: The mineral is the important data in the Lunar Exploration. The main objective of this work is to segmentation lunar craters with the C-V Model, and to quantify the images terrain and the abundance of lunar surface minerals based on Crater distribution law and Soil Characterization Consortium data set with Hapke model and lunar surface reflectance. Actual lunar images of mare region as an example, this method analysis result of the minerals abundance are basically same with published literature. This method can be simple rapid in-time implemented in real-time lunar exploration.

Abstract: As a new high-technology with large amount of information, strong temporal resolution, high efficiency and low cost, remote sensing provided a useful tool for related researches of land use and land cover in different spatial and temporal scales. Firstly, concepts and characteristics of the remote sensing technology were introduced. Secondly, its applications were elaborated in land use and land cover such as land resources survey, land resources change monitoring, land use evaluation, overall planning of land use and land consolidation aspects. At last, future application trends and several aspects noticed were pointed out.

Abstract: Understanding the process and pattern of regional land use and land cover change was essential for intensive and highly efficient, scientific and rational utilization of land resources. Technologies of remote sensing (RS) and geographical information system (GIS) were applied to simulate and analyze the land use changes from 2000 to 2007 in Pinggu district in Beijing, China. The area of cropland decreased by 62.42 km², while the area of construction land, orchards and forests increased 17.65 km², 25.88 km² and 17.86 km², respectively. We should develop appropriate policies and measures to increase the area of cultivated land in the future. The research results provided the necessary reference for the related researches of land use and land cover change.

Abstract: The video images of road monitoring system contain noise, which blurs the difference between the lane and the background. The lane detection algorithm based on traditional Canny edge detector hardly detects the single-pixel lane accurately and it produces pseudo lane. The paper proposes an effective lane detection method based on improved Canny edge detector and least square fitting. The proposed method improves the dual-threshold selection of traditional Canny detector by using the histogram concavity analysis, which sets the optimal threshold automatically. The least square method is used to fit the feature points of detected edges to accurate and single-pixel wide lane. Experimental results show that the proposed method detects the lane of video images accurately in the noise environment.

Abstract: We develop a robust tracking method based on the structural local sparse representation and incremental subspace learning. This representation exploits both partial information and spatial information of the target. The similarity obtained by pooling across the local patches helps locate the target more accurately. In addition, we develop a template update method which combines incremental subspace learning and sparse representation. This strategy adapts the template to the appearance change of the target with less drifting and reduces the influence of the occluded target template as well. Experiments on challenging sequences with evaluation of the state-of-the-art methods show effectiveness of the proposed algorithm.