Vol. 30,No ACTA MECHANICA SINICA Mar., 1998 , ) ,,, . Kohonen. ( L E, L V, d ,

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1 30 2 Vol 30,No ACTA MECHANICA SINICA Mar, ) 3 (, ) 3 (, ),, Kohonen,,,, [1 ], ;, ( ),,,, [2 ], Kohonen, 1 1 (a) ( L E, L V, d ) : 1) ,

2 ,, P/ P L / L P/ P = - N Q [ n 2 ( P 11-2 P 12 ) + 1 ] L / L (1) N, n, P 11 P 12,, Q Q = L ( A U - A E ) L A E + NL E ( A U - A E ) L, L E, A U, A E ( A E ), Q ; ( L E ), Q ; (1), (2) :, N,, (1) n 2 ( P 11-2 P 12 ) [3 Vaziri ] :,, 1 (a), ( 1 (b) ),, [3 ] (2) 1 (a) (b) Fig 1 Asymmetric etched fiber (a) and its lateral bending induced by axial stress (b) 211, 2 ( , ), : [ + 45 / - 45 / 90 / F 0 / 90 / 45 / 0 / F 90 / 0 / 0 / + 45 / - 45 / + 45 / - 45 / 0 / 0 / - 45 / + 45 / - 45 / + 45 / 0 / 0 / 0 / 90 / 90 / - 45 / + 45 ] ( F, ), ( 2 Fig 2 Etched optical fiber sensor array in smart composite material and structure

3 2 : 215 0, 45, 90 ) (3 4, 4 5, 5 6),,, (3 4, 5 6), [1 (4 5), ], ( 11), 1 8 ( 11) C,, : 1), ;2),,,, ;3), ( ) / ( - 11 ) 200 mm 200 mm, 150 mm 150 mm, 4 (0 ) 5 (45 ) 4 (90 ) ( 2, x, y 50 mm), 6215 m/ 125 m, 15 min ( 2515 m) ; 60 ; 015 m 115 m / ( ), 2 ( x y ) ( 200 mm 100 mm), : 1), ( ) ;2),,, 5 000, 30 %,, ( ) ( ), ( ) ( x ), ( x, y ), 45,, ( x, y, 45 ),, ( ),, ( ), ( ), ( ), x, y 16 ( ) 16,,, ( )

4 , BP Kohonen BP [5 ], BP Kohonen, Kohonen 3 (a) 3 (b) Kohonen Kohonen,, 3 Kohonen Fig13 Kohonen network N, M : 0 < W ji < 1, ( i = 1, 2,, N ; j = 1,2,, M ) X = [ X 1, X 2,, X N ], X j d j = 6 i ( X i ( t) - W ij ( t) ) 2 (3) X i ( t) t i, W ij ( t) i j t, j 3, j 3 W ij ( t + 1) = W ij ( t) + ( t) ( X i ( t) - W ij ( t) ) (4) j N E 3 j ( t),1 Φ i Φ N, 0 Φ ( t) Φ1 Kohonen,, LVQ1, LVQ2, LVQ3 [4 ] LVQ4 [2 ] 211 L VQ1 X C, W c ( t + 1) = W c ( t) + ( t) [ X ( t) - W c ( t) ] (5) X, W c ( t + 1) = W c ( t) - ( t) [ X ( t) - W c ( t) ] (6) = W j ( t), j C (7) 2 2 L VQ2

5 2 : 217 X C j C i, C j C i ; X W i W j W i W j 20 %, W i ( t + 1) = W i ( t) - ( t) [ X ( t) - W i ( t) ] (8) = W j ( t) + ( t) [ X ( t) - W j ( t) ] (9) W k ( t + 1) = W k ( t), k i, j (10) 2 3 L VQ3 W i W j X, X W j W i, X W i W j W i W j 20 %, W i ( t + 1) = W i ( t) - ( t) [ X ( t) - W i ( t) ] (11) = W j ( t) + ( t) [ X ( t) - W j ( t) ] (12) W K ( t + 1) = W K ( t) + ( t) [ X ( t) - W K ( t) ], K { i, j} (13) LVQ1, LVQ2 LVQ3 ( t) = 0 01 (1 - t/ ), ( t) = 0 02 (1 - t/ ) 2 4 L VQ4 X C j C i, W i ( t + 1) = W i ( t) - ( t) ( i, i 3 ) [ X ( t) - W i ( t) ], i N E 3 i ( t) (14) = W j ( t) + ( t) ( j, j 3 ) [ X ( t) - W j ( t) ], j N E 3 j ( t) (15) N E 3 i ( t) N E 3 j ( t) i 3 j 3, ; ( i, i 3 ) ( j, j 3 ), i i 3 j j 3, 4, e - d cos (2 d) ( t) = 0 01 (1 - t/ 5 000) ( t) = 0 02 (1 - t/ 5 000) 4 Fig 4 Limited function of modifying weight coefficients, Kohonen ( ), 2 13, 16 C Kohonen ( ) Kohonen 64, ( 13

6 ) : ( ), 1 2 : (, 20 %), 100 % LVQ1 LVQ4, LVQ1 LVQ3, LVQ4, 2 Training of Kohonen network 1 Table 1 Damage detection of one point Testing of Kohonen network Input : X 1, X 2,, X 13 Output Input : X 1, X 2,, X 13 Output Training of Kohonen network 2 Table 2 Damage detection of two point Testing of Kohonen network Input : X 1, X 2,, X 13 Output Input : X 1, X 2,, X 13 Output ,,,, Measure RM Advances toward fiber optic based smart structures Optic Engineering, 1992, 31 (1) : 34 47

7 2 : 219 2, ( Tu YQ Study of fiberoptic sensing and signal processing system for state detection in smart structures Ph D Thesis, University of Chongqing, (in Chinese) ) 3 Masoud V, Chen CL Optical - fiber strain sensors with asymmetric etched structures A pplied Optics, 1993, 32 (31) : Measure RM Progress toward fiber optic based smart structures at V TIAS S PI E, 1990, 1370 : ,1996, 9 (4) : ( Yang JL Feasi2 bility of neural network processing for etched optical fiber sensor array Journal of Transduction Technology, 1996, 9 (4) : (in Chinese) ) STRUCTURAL STATE DETECTION WITH FIBEROPTIC SENSING ARRAY AND NEURAL NETWORK SIGNAL PROCESSING TECHNIQUES 1) Yang Jianliang Guo Zhaohua 3 Xiang Qing Huang Dexiu ( Huaz hong University of Science and Technology, W uhan , China) 3 ( Xiangtan U niversity, Xiangtan , China ) Abstract In t his paper, a type of simple and excellent crank2type etched fiberoptic intensity sensor is presented A t hree dimension sensing network, which is composed of etched fiberoptic sensors, is embedded in t he laminated composite material structure of vertical tail2wing of training211 plane for t he purpose of nondestructive evaluation of structural states in smart composite material and struc2 tures The composite specimens in which sensing network is embedded are tested wit h stretch and bending in t hree points The experimental results have shown t he feasibility of embedded fiberoptic sensor network to be used to measure the structural states such as strain, stress and damage It is also shown in experiment that the changes of optical power are highly dependent on the strain paral2 lel to optical fiber axis and independent on the strain vertical to optical fiber axis ; the responses of fiberoptic sensor are linear, repeatable, have a high sensitivity and no measurable hysteresis ; t he break t hreshold of etched optical fiber can be controlled by changing t he etched time, and it is useful to promote t he sensing sensitivity For above fiberoptic smart structures where sensing and actua2 tion is distributed over large areas or consists ofdozens to thousands of discrete elements, the pro2 cessing task is computationally intensive Artificial neural networks offer an opportunity to imple2 ment a massively parallel architecture with near real time processing speed and the ability to learn the desired response In this paper, the Kohonen network and its changes which are suitable for distributing sensing signal processing in smart structures are described The simulation results have shown that their ability for identifying the position of stress, strain or damage is above 90 % Key words fiberoptic sensing,smart material and structure,artificialneural network 1) The project supported by the Foundation for Pre - research of Defense Science Research of China and the National Natural Science Foundation of China Received 24 October 1996, revised 16 March 1997

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