Hong Tiansheng

High-Performance Humidity Sensors Based on Double-Layer ZnO-TiO2 Nanofibers via Electrospinning

ZnO and TiO2 nanofibers are synthesized via electrospinning methods and characterized by x-ray diffraction, scanning electron microscopy, and transmission electron microscopy. Humidity sensors with double-layer sensing films are fabricated by spinning the ZnO and TiO2 nanofibers on ceramic substrates sequentially. Compared with sensors loading only one type of nanofiber, the double-layer sensors exhibit much better sensing properties. The corresponding impedance changes more than four orders of magnitude within the whole humidity range from 11% to 95% relative humidity, and the response and recovery times are about 11 and 7s, respectively. Maximum hysteresis is around 1.5% RH, and excellent stability is also observed after 180 days. The humidity sensing mechanism is discussed in terms of the sensor structure. The experimental results provide a possible route for the design and fabrication of high performance humidity sensors based on one-dimensional nanomaterials.

High Performance Micro CO Sensors Based on ZnO-SnO2 Composite Nanofibers with Anti-Humidity Characteristics

ZnO-SnO2 composite nanofibers are synthesized via an electrospinning method and characterized by x-ray diffraction, scanning electron microscopy, and transmission electron microscopy. Micro sensors are fabricated by spinning the nanofibers on Si substrates with Pt signal and heater electrodes. The sensors with small areas (600 μm × 200 μm) can detect CO down to 1ppm at 360 °C. The corresponding sensitivity, response time, and recovery time are 3.2, 6s, and 11s, respectively. Importantly, the sensors can operate at high humidity conditions. The sensitivity only decreases to 2.3 when the sensors are exposed to 1 ppm CO at 95% relative humidity. These excellent sensing properties are due to combining the benefits of one-dimensional nanomaterials and the ZnO-SnO2 grain boundary in the nanofibers.

Nondestructive Detection of Pesticide Residue on Longan Surface Based on Near Infrared Spectroscopy

In this research, nondestructive detection of a slathered pesticides trichlorfon on longan surface based on near infrared spectroscopy was studied. Firstly, principal component analysis (PCA) was applied to analyze the spectra data within the wavelength range from 500nm to 1000nm. Satisfied results were achieved from clustering based on the scores of PC1 and PC2. Then a BP artificial neural network (ANN) was built to detect the pesticide residue with the scores of PC1 and PC2 as inputs. The results indicated that the ratio of correct detection was 93%. This study may provide a novel way for fast and nondestructive fruit surface pesticide residue detection.

A System for Fruit Tree Canopy Characters Measuring Based on CAN-bus

Measuring of fruit tree canopy parameters were required for site-specific management of fruit orchard such as estimation of fruit yield, variable rate application of fertilizer and pesticides precisely on each tree. For riding the effect cased by tractor deviation in driving path between two rows of trees and uneven ground, measuring was designed based on CAN bus, combined robot navigation technology, including AHRS and DGPS-RTK, with the measuring of fruit tree canopy characters, and used C8051F040 micro controller as node ECU. The hardware circuit was introduced in detail, the forming of CAN transmission information frame and software were also analyzed. Experiment with litchi trees in orchard using four ultrasonic sensors showed that system was stable, having highly repeatability (R2=0.9341, RMSE=1.22m3) and accuracy (R2=0.8972, RMSE=1.766m3) of canopy volume measuring.

The Application of Ant Colony Algorithm in Combined Power Load Forecasting

The ant colony algorithm also named ACO method, Artificial ants have memory function, it in the process of movement through a pheromone path to release, finally found a road from their nests to food source through the shortest, called the catalytic processes of ants, which is a positive feedback mechanism, it has good robustness, fast convergence speed, easy to get the global optimal solution. Based on random increase and nonlinear wave -- residual series, grey prediction can reflect the increasing and support vector machine can show the nonlinear relationship. The improving ACO method can make the optimization weight to achieve the goal of accuracy, consistency to the prediction values, finally precision of the series can be improved obviously. Through computation of power load in a province, the experimental results show that this method can greatly improve the accuracy of the load forecasting.

Precision Man-made Fruiter Modeling and Application

Man-made fruiters provides a fixed and standard object in the ground-based leaf area index(LAI) and biomass measurement for avoiding time and space effect on the real fruiter in the real environment. Firstly, the coordinates of the real guavas leaves and branches were gained by 3D digitalizer named Fastrak. Secondly, a man-made guava was made with a kind of special simulating techniques which has been applied for Chinese patent. By means of digital pictures, coordinates of leaves and braches and virtual guava, the man-made tree has been adjusted many times over 3 months to reach the simulating effect. Finishing the work, the man-made tree was compared and analyzed with the real one in parts such as coordinates, height, area, shadow area and so forth. As a result of analysis by SPSS, for the man-made guava the R square between tree height and accumulative leaf area is 0.9892, and the R square between shadow area and accumulative leaf area is 0.9973. Additionally, for error analysis between the real one and the man-made one, the profile is basically the same by comparing digital pictures in different visions and the profile size error is less than 3%; the coordinates of leaves obey the normal school after analyzing 3014 leaf points and 9042 coordinate points; the accumulative leaf area error is less than 5% and shadow area error is less than 20% from 0 to 65 cm of the tree height.

Method of indirect measurement of fruiter biomass

Fruiter biomass is one of the crucial parameters for precision spraying. This paper is to research measurement method for ground-based fruiter biomass by integrating direct and virtual plant technology based on real guava. Firstly, a real guava fruiter with 274 leaves and 228 branch segments was selected and its leaves and branch segments were encoded. Secondly, the coordinates of the guavas leaves and branches were gained by 3D digitalizer named Fastrak produced by Phohelmes and then a virtual guava model with a virtual direct beam environment was built by VC++ with OpenGL. Meanwhile, the guavas leaf parameters such as length, area, wet weight, and dry weight and branch segment parameters such as length, diameter, wet weight, and dry weight were measured by direct methods. Hereinto, a kind of useful leaf area process method was outlined for dealing area detection with different sides and holes .Using a kind of shadowing method, virtual guava could be shadowed in different horizontal height or in different vertical width and its shaded area, total biomass and so forth in different layers were calculated by integrating real guavas parameters. After regression analysis using SPSS, for the real guava the R2 between total leaf area and leaf dry weight is beyond 0.988 with the near regression formula between direct method and virtual plant method, the R2 between total leaf dry weight and branch dry weight is 0.89, the R2 between branch diameter and leaf dry weight is 0.80, the R2 between branch D2H(diameters square multiply height) and leaf dry weight is 0.97. And in the virtual fruiter, the R2 between leaf area and leaf dry weight is beyond 0.95, which proved the relation in the real tree. Additionally, more detail relations like height and leaf area, leaf shadowed area and leaf area were analyzed in the virtual fruiter data which provided important information to build a LAI and biomass calculation model.