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Henan’an, China

Dong Y.,Zhongyuan University of Technology | Zhu Y.-S.,Zhongyuan University of Technology | Li Q.,Jiyuan Power Supply Company
Advanced Materials Research | Year: 2012

The information capacity of the characters on the license plate images affects the accuracy of recognition directly. To improve the recognition rate of vehicle license, considering the low cost of installing cameras nowadays, this thesis put forwards that, adopting images from two cameras in different angles. the license plate location, character division and feature extraction process are done separately, and then information fusion technique is used to confirm the more reliable recognition result, which can reduce the error recognition rate of characters. The contrast experiments show that this method can improve the accuracy of license plate recognition. © (2012) Trans Tech Publications, Switzerland.

Suonan J.-L.,Xian Jiaotong University | Wu S.-H.,Xian Jiaotong University | Hou Z.,Xian Jiaotong University | Hou Y.-W.,Jiyuan Power Supply Company | Zhou Z.-P.,XJ Electrical Co.
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2012

Due to the series compensation capacitor, high-voltage transmission line impedance presents non-continuous performance which has an impact on the widely used relay principle. This paper establishes a simulation model of 750 kV series compensated line by EMTP software, and presents the free frequencies distribution and the decaying characteristics of current under transmission line fault by the least square matrix pencil method. The simulation results show that the method can accurately compute the frequencies and decaying factors and present the actual harmonic changes in the point of protection. This algorithm is suitable for transient harmonic analysis and provides guidance for transient protection.

Jiang J.,Zhengzhou University | Cheng Z.,Zhengzhou University | Zhu M.,Jiyuan Power Supply Company
Dianli Zidonghua Shebei/Electric Power Automation Equipment | Year: 2011

The quantitative formula of accumulated temperature effect is given and the load forecast combining wavelet transform and neural network is proposed with the accumulated temperature effect. The load series is decomposed into the trend load series under different frequency bands and the detailed load series by wavelet transform, which are modeled and forecasted by BP neural network. The characteristic parameters, such as the accumulated temperature coefficients are added into the trend load series. The final forecasting result of load series is obtained by wavelet reconstruction. Case study shows the proposed method improves the load forecast accuracy effectively.

Zheng X.-F.,Henan Mechanical and Electrical Engineering College | Wei H.,Henan Mechanical and Electrical Engineering College | Qi S.-C.,Henan Mechanical and Electrical Engineering College | Hou Y.-W.,Jiyuan Power Supply Company
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2011

Battery status network monitoring system uses classification management mode, and the bottom monitoring base stations use the improved four-stage charging method, dynamically adjusting the conversion point value of the charging phase, and uploading real-time monitoring data. Upper management software uses LABVIEW programming with functions of battery failure detection, charge and discharge, temperature detection and parameter realtime disply. It online analyses various battery status data to achieve real-time online alarm when battery out of order. Remote monitoring can be achieved using Web Publishing controls in LABVIEW. Long-range battery input and removal can be realized by monitoring the base station. Through testing, the system can work reliably in large battery-powered systems.

Liu Z.,China Institute of Technology | Dong Y.,China Institute of Technology | Li Q.,Jiyuan Power Supply Company
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

In this paper, a novel fabric skew detection method based on DFT and multi-projection analysis is proposed. First, perform DFT for the fabric image, then use the image binaryzation which is to remove redundant information. Rotate the binary spectrum of the image from -5° to +5° in small step. After each rotation, project the image to the transverse axis. Then detect the skew angle of the fabric image based on that a maximum of projection pixels appears in the center of the spectrum if the longitudinal centerline of the spectrum is vertical to the transverse axis. Experimental results show that this algorithm has high accuracy in detecting small amount of fabric skew and better adaptability of the fabric density. © 2012 Springer-Verlag.

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