Finger Vein Recognition Based on a Personalized Best Bit Map

Finger vein patterns have recently been recognized as an effective biometric identifier. In this paper, we propose a finger vein recognition method based on a personalized best bit map (PBBM). Our method is rooted in a local binary pattern based method and then inclined to use the best bits only for matching. We first present the concept of PBBM and the generating algorithm. Then we propose the finger vein recognition framework, which consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PBBM achieves not only better performance, but also high robustness and reliability. In addition, PBBM can be used as a general framework for binary pattern based recognition

Influence of Ignition Channel on the Ignition Performance of Ignition Device

Based on relative theories of gas dynamics and computational fluid dynamics, the flow field computation software ANSYS Fluent was used to simulate the steady flow field of the solid type ignition device of liquid-propellant rocket engine in two working conditions (condition I: without ignition channel, condition II: with ignition channel). On this basis, the influence of ignition channel on the working characteristics of the solid type ignition device of the liquid-propellant rocket engine was analyzed and experimentally tested. The results showed that when the pressure in the combustion chamber was atmospheric pressure, under condition II, the gas velocity at the throat of the ignition device did not reach the sonic velocity, and the position of sonic velocity moved to the downstream section of the ignition channel. Compared to condition I, the gas velocity and energy at the ignition outlet increased, which would be beneficial for initial ignition, and the gas pressure and temperature at the throat increased as well, indicating that the structural strength at the throat should be evaluated. The gas flow, gas pressure, and gas temperature at the ignition outlet decreased compared to working condition I, yet the changes were small and would have minimal effect on the ignition performance. During the pressure increase process in the combustion chamber, the gas pressure, velocity, temperature, flow, and energy at the ignition outlet experienced a steady stage in both working conditions before coming to an inflection point. The inflection point under condition II is smaller than that under condition I. To improve the ignition reliability, the working pressure of the ignition device should be further increased

A Robot Hybrid Hierarchical Network for Sensing Environmental Variables of a Smart Grid

With the rapid development of the social economy, high-voltage transmission lines as power supply infrastructure are increasing, subsequently presenting a new challenge to the effective monitoring of transmission lines. The dynamic sensor network integrated with robots can effectively solve the elastic monitoring of transmission lines, but the problems of real-time performance, energy consumption and economy of the network need to be solved. To solve this problem, a dynamic network deployment method based on the hybrid hierarchical network (HHN) is proposed to realize a low-cost, energy-saving and real-time dynamic sensing system for overhead high-voltage transmission lines. Through case analysis and simulation, combined with the vague set multi-attribute decision-making method (MADM) with scheme preference, the network deployment and optimization results under multi-parameter constraints are obtained

Detecting Inspection Objects of Power Line from Cable Inspection Robot LiDAR Data

Power lines are extending to complex environments (e.g., lakes and forests), and the distribution of power lines in a tower is becoming complicated (e.g., multi-loop and multi-bundle). Additionally, power line inspection is becoming heavier and more difficult. Advanced LiDAR technology is increasingly being used to solve these difficulties. Based on precise cable inspection robot (CIR) LiDAR data and the distinctive position and orientation system (POS) data, we propose a novel methodology to detect inspection objects surrounding power lines. The proposed method mainly includes four steps: firstly, the original point cloud is divided into single-span data as a processing unit; secondly, the optimal elevation threshold is constructed to remove ground points without the existing filtering algorithm, improving data processing efficiency and extraction accuracy; thirdly, a single power line and its surrounding data can be respectively extracted by a structured partition based on a POS data (SPPD) algorithm from “layer” to “block” according to power line distribution; finally, a partition recognition method is proposed based on the distribution characteristics of inspection objects, highlighting the feature information and improving the recognition effect. The local neighborhood statistics and the 3D region growing method are used to recognize different inspection objects surrounding power lines in a partition. Three datasets were collected by two CIR LIDAR systems in our study. The experimental results demonstrate that an average 90.6% accuracy and average 98.2% precision at the point cloud level can be achieved. The successful extraction indicates that the proposed method is feasible and promising. Our study can be used to obtain precise dimensions of fittings for modeling, as well as automatic detection and location of security risks, so as to improve the intelligence level of power line inspection