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The Application and Research of Bayesian Algorithm in a Trajectory Measuring Meter

Author: LiPeng
Tutor: WangBinZuo
School: Harbin Engineering University
Course: Mechanical and Electronic Engineering
Keywords: Trajectory measuring instrument Shaft encoder Neural Networks Bayesian regularization
CLC: TP274
Type: Master's thesis
Year: 2009
Downloads: 40
Quote: 0
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Abstract


A trajectory measuring instrument is a conventional measuring instruments ( a ) of the photoelectric theodolite , widely used in military , construction and many other industries , and is mainly used for measuring space target azimuth and elevation angle . With the rapid development of China's aviation , aerospace and defense technology cause a large amount of test data is measured by a measuring instrument , therefore increasing the precision of the measurement data of the measuring instrument . In order to further improve the accuracy of the measuring instrument measurement data , the need for the design of the measuring instrument system of hardware and software improvements program for further discussion . The the trajectory measuring instrument goniometer axis angle encoder , and data processing software of the the trajectory measuring instrument system has been redesigned , Rigid-Flex to explore to improve the measurement of the measuring instrument system data accuracy of the method . First , the analysis of the composition of the system structure and operating principle of the measuring instrument , the goniometer axis angle encoder segments device based on the improved program design, including the breakdown of the device multiplication multiplier circuit and the A / D converter circuit improvements , in order to improve the resolution of the shaft encoder and processing speed . Second, focus on the combination of Bayesian algorithms and neural networks involved in this topic , the objective function of optimization parameters derived by Bayesian inference , and purpose to improve the network generalization ability . Finally, the error of the measuring instrument in the work , especially the shafting rotating dynamic hysteresis of servo system to various causes measurement data analysis , and to establish the number of measurements dug error decomposition model . Bayesian regularization neural network error correction experiment the trajectory measuring instrument measured data , and the experimental results were analyzed and summarized . Experimental results show that Bayesian regularization neural network can achieve the the trajectory measuring instrument measurement data error correction , and achieved good results can be achieved to improve the accuracy of the trajectory measuring instrument measurement data purposes .

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