IMPROVING PEDESTRIAN DETECTION USING OPTICAL FLOW

Pedestrian detection, which has wide applications on surveillance, automatic driving and robotics, plays a significant role in computer vision. Among all kinds of pedestrian detection methods, stereo based method achieves an accurate and efficient detection result by exploiting depth and color information. However, many stereo based systems fail at considering motion information which is important in locating and detecting an object. For many pedestrian detection systems, adding extra data like motion is one of the most effective ways to improve the performance. Therefore, this thesis proposes a multi-cue pedestrian detection system which integrates optical flow based and stereo based modules for combining motion, depth and color information. In the proposed system, optical flow and disparity value are estimated by using the frames which obtained from a stereo camera. In order to obtain accurate pedestrian motion, ego motion is compensated by using motion clustering, affine model and RANSAC. After that, the motion and the depth information are exploited for ROI generation. Finally, SVM is trained by the combination of motion feature and HOG feature. Experimental results show that the use of high-accuracy optical flow along with depth and color information improves the performance of multi-cue pedestrian detection system.M.S. in Electrical Engineering, December 201

Application of flow field decomposition and reconstruction in studying and modeling the characteristics of a cartridge valve

In modeling the characteristics of a cartridge valve with traditional methods, it is commonly required to determine the value of flow area and other coefficients such as discharge coefficient and jet angle, etc. However, these parameters often rely heavily on empirical or experimental data and often involve some uncertainties, especially with the variation of the spool displacement (valve opening). To avoid these uncertainties, this paper proposes a modeling method which calculates spool force and flow rate directly through the distribution of fluid field. Transient 3D flow field simulation with dynamic mesh technique is conducted using commercial code FLUENT, and Proper Orthogonal Decomposition (POD) method is introduced to simplify fluid field data. The results showed that the POD method can capture the main features of the fluid field while significantly reducing the amount of data. With reconstructed pressure field and velocity field, spool force and flow rate can be calculated directly without using traditional formulas which contain uncertain coefficients. Valve characteristics calculated with this method agree with Computational Fluid Dynamics (CFD) and experimental data well, which confirms the validity and effectiveness of this method

Wind Turbine Load Optimization Control Strategy Based on LIDAR Feed-Forward Control for Primary Frequency Modulation Process with Pitch Angle Reservation

Because wind power is connected to the grid on a large scale, frequency fluctuation in the power grid, which is defined as a system safety risk to the power grid, occurs from time to time. According to the grid code rules of China, wind turbines are required to be equipped with primary frequency modulation or inertia response control capability, which are used to support the safe and stable operation of the power grid. During the traditional frequency modulation process of the wind turbine, power limiting operation or pitch angle reservation is generally adopted to ensure that the reserved energy can be released at any time to support the frequency change in the power grid. However, the frequency support method leads to a large loss of power generation, and does not consider the coordination between mechanical load characteristics control and primary frequency modulation. In this paper, a mechanical load optimization control strategy for a wind turbine during the primary frequency modulation process, based on LIDAR (light detection and ranging) feed forward control technology, is proposed and verified. Through LIDAR feed forward control, the characteristics of incoming wind speed can be sensed in advance, with the consequence that the wind turbine can participate in, and actively control, the primary frequency modulation procedure. According to the characteristics of incoming wind, for instance the amplitude and turbulence, simultaneously, the size of the reserved pitch angle can be adjusted in real time. This kind of method, coordinating with the mechanical load of the wind turbine, can be used to reduce both the ultimate load and fatigue damage as much as possible. Finally, the mechanical load characteristics of the wind turbine with and without the control strategy are compared and studied through simulation. The research results show that the load optimization control strategy based on LIDAR feed-forward control technology can effectively reduce the fatigue and ultimate loads of the wind turbine while supporting the frequency change in the power grid; especially for the fatigue load of tower base tilt and roll bending moments, the reducing proportion will be about 4.3% and 6.3%, respectively