tory burch outlet Fiber laser source based real-ti

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Fiber laser source based real-time monitoring software design smart structures


, And finally back to the input layer, this algorithm is called X1X2Y1Y2Y3 input layer hidden layer output layer network structure diagram 3BP establish BP neural network,tory burch outlet, by entering the training samples to train the network,mbt shoes ireland, the last use of the network has been trained to analyze the experimental data to determine the location of fiber-optic smart structure damage. The system has eight sensing fiber, so these eight fiber transmission intensity as 8 input; the same time, fiber-optic smart structures, a total of 16 intersections, the number of network output designed for 4, with the E00001 a rl111] that this 16 position, as shown in Table 1. A 197 - Table 1 and the output code corresponding to the damage location experiments in Table 4 and Figure 4 is a software to draw conclusions fiber light curve. Software can also display the curve, reflecting the changing light intensity. Return - of the intensity FlF2F3F4F5F6F7F8 optical fiber 4 real-time light curve can be seen from Figure 4, F1, F6 intensity almost to 0, F7, F8 light intensity is also higher than F2, F3, F4, F5 is smaller . Before the comparison, the system will be working a normal curve graph; so get real-time monitoring of the curve drawn for comparison with the standard curve, intuitive intelligence on the status of optical fiber can be changes in the region, or the damage location. If you can see from the graph F1, F6 light intensity than normal decline in big situations, you can determine the initial location of the intersection of F1 and F6 attachments injury, that position 5, as shown in Figure 2 to determine the course of this graph has some objective and intuitive. At the same time, we use the method of BP neural network results compared, it is smart structural damage in fiber identification and positioning of a widely used method. With F1, F2,, F4, F5, F6, F7, F8 8 fiber identification, as shown in Figure 2. The experimental value of the input light intensity have been trained BP network, observing the network output, get the results, as shown in Table 2. The four experimental results and the actual structure of a given fiber] 98 an intelligent load-bearing position consistent with the experiment were given 1,2,3,4 is indeed the location 1,6,ghd planchas, ¨, 16 load. 5 Conclusion This paper describes the preparation of their own fiber-optic laser light source based real-time monitoring software smart structures. Experimentally verified the feasibility of monitoring software. The results show that the structure of software for real-time monitoring and analysis of the structure of the bearing position, with good performance, the actual monitoring of the status of fiber optic smart structure provides a way. References E1] Li Chuan, Zhang Mo, Ding Yongkui. Fiber-optic smart structures Sensing [J]. NeoPhotonics, 2001,1 (4) :193-197. [2] GuoLinfeng,tory burch outlet, ZhaoZhimin, GaoMingjuan, Studyofthecompatibilitybetweenlight-curedrepairmaterialsandcompositematerialyholograph icinterferometry [J], OpticalEngineering, 2005,44 (10) :105602-1-3. [3] Guolin Feng, Zhao Zhimin, Li Wei. A fiber-optic smart structure control system design [J]. Sensors and Microsystems ,2008,4:118-120. [4] Guolin Feng, Zhao Zhimin, high Mingjuan. New fiber-optic intelligent monitoring system design [J]. Optical Engineering, 2006,33 (3) :133-136. [5] Guolin Feng, Zhao Zhimin, Hou Yongfei and so on. Special fiber parameter detection and analysis of bearing performance [J]. Journal of Zhejiang University (Engineering Science), 2007,41 (10) :1647-1649. [6] Guolin Feng, Zhao Zhimin, Macheng Li. Fiber-optic smart structures based on monitoring and analysis of the bearing position [J]. Laser, 2007,27 (5) :274-276. [7], Zhao Zhimin, Hong Xiaoqin. New rapid self-healing fiber optic sensor design and performance [J]. China Laser, 2008,35 (4) :573-576. E8] TU Ya-Qing, Liu long. Fiber-optic smart structures EM]. Beijing, Higher Education Press, 2005. [9] Lee is brave. VisualC + + serial communication technology and engineering practice [M]. Beijing, Posts & Telecom Press, 2002. [1O] Liu Songqing. MATLAB neural network BP network research and application [J]. Computer Engineering and Design, 2003,4 (11) :81-83.
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