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An Ultra-precision Electronic Clinometer for Measurement of Small Inclination Angles
Tan, Siew-Leng,Kataoka, Satoshi,Ishikawa, Tatsuya,Ito, So,Shimizu, Yuuki,Chen, Yuanliu,Gao, Wei,Nakagawa, Satoshi The Korean Society of Manufacturing Technology Eng 2014 한국생산제조학회지 Vol.23 No.6
This paper describes an ultra-precision electronic clinometer, which is based on the capacitive-based fluid type, for detection of small inclination angles. The main parts of the clinometer low-noise electronics are two capacitance measurement circuits for converting the capacitances of the capacitors of the clinometer into voltages, and a differential amplifier for obtaining the difference of the capacitances, which is proportional to the input inclination angle. A 16 bit analog to digital (AD) converter is also embedded into the same circuit board, whose output is sent to a PC via RS-232C, for achieving a small noise level down to tens of ${\mu}v$. A compensation method, which is referred to as the delay time method for shortening the stabilization time of the sensor was also discussed. Experimental results have shown the possibility of achieving a measurement resolution of $0.0001^{\circ}$ as well as the quick measurement with the delay time method.
Improved DV-Hop Localization Algorithm Based on Bat Algorithm in Wireless Sensor Networks
( Yuan Liu ),( Junjie Chen ),( Zhenfeng Xu ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.1
Obtaining accurate location information is important in practical applications of wireless sensor networks (WSNs). The distance vector hop (DV-Hop) is a frequently-used range-free localization algorithm in WSNs, but it has low localization accuracy. Moreover, despite various improvements to DV-Hop-based localization algorithms, maintaining a balance between high localization accuracy and good stability and convergence is still a challenge. To overcome these shortcomings, we proposed an improved DV-Hop localization algorithm based on the bat algorithm (IBDV-Hop) for WSNs. The IBDV-Hop algorithm incorporates optimization methods that enhance the accuracy of the average hop distance and fitness function. We also introduce a nonlinear dynamic inertial weight strategy to extend the global search scope and increase the local search accuracy. Moreover, we develop an updated solutions strategy that avoids premature convergence by the IBDV-Hop algorithm. Both theoretical analysis and simulation results show that the IBDV-Hop algorithm achieves higher localization accuracy than the original DV-Hop algorithm and other improved algorithms. The IBDV-Hop algorithm also exhibits good stability, search capability and convergence, and it requires little additional time complexity and energy consumption.
A Collaborative and Predictive Localization Algorithm for Wireless Sensor Networks
( Yuan Liu ),( Junjie Chen ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.7
Accurate locating for the mobile target remains a challenge in various applications of wireless sensor networks (WSNs). Unfortunately, most of the typical localization algorithms perform well only in the WSN with densely distributed sensor nodes. The non-localizable problem is prone to happening when a target moves into the WSN with sparsely distributed sensor nodes. To solve this problem, we propose a collaborative and predictive localization algorithm (CPLA). The Gaussian mixture model (GMM) is introduced to predict the posterior trajectory for a mobile target by training its prior trajectory. In addition, the collaborative and predictive schemes are designed to solve the non-localizable problems in the two-anchor nodes locating, one-anchor node locating and non-anchor node locating situations. Simulation results prove that the CPLA exhibits higher localization accuracy than other tested predictive localization algorithms either in the WSN with sparsely distributed sensor nodes or in the WSN with densely distributed sensor nodes.