FBG is a kind of promising high precision strain sensor, and it can not only detect the homogeneous strain, but also identify non-uniform strain distribution. In the application of FBG in inhomogeneous strain sensing, genetic algorithm is an important method to reconstruct the non-uniform strain from reflection spectra of FBG. However, the practical reconstruction of genetic algorithm demonstrates its shortcomings such as low computational efficiency, easily falling into local optimal solution, etc , and it is well known that there is a great relationship between computational efficiency and population initialization of genetic algorithm. In general genetic algorithm employed in FBG strain reconstruction, the initialized population is randomly distributed strain along FBG axial direction, which ignores the continuity between neighbor strains. To reduce the number of population parameters and make the original population more close to the real strain distribution, a new method of population initialization is proposed here, that is using polynomial function parameters to be the initialized population instead of the randomly distributed strain, supposed that the FBG axial strains can be described as a polynomial function with independent variable of axial position. In simulation experiments, the reflection spectrums of a 10mm-long FBG are obtained from T-Matrix method in four cases of strain-free, linear-distributed strain, parabola-distributed strain and exponential –distributed strain, and then the general genetic algorithm and the new genetic algorithm with simplified population initialization were applied to reconstruct the strain distribution from the reflection spectrums respectively. The experiment results verify the supposition of the polynomial function of the FBG, and show clearly that the new method can improve the computational efficiency of genetic algorithm in FBG inhomogeneous strain demodulation greatly. From the results, it is found that with the same calculation accuracy, the computing time of the new population initialization method is reduced to about 1/5 of the general on average.
As a sensing cell, Fiber Bragg grating (FBG) can transduce physical quantities like strain, temperature, etc, having
attractive merits of being small and light, resistance to corrosion and immunity to electromagnetic interference, etc.
Commercial FBG strain sensor has a sensing range of no more than 9000 με (0.9%), however, larger-range strain sensor
is demanded in industry such as heavy structural distortion and crack-happening. A new kind of large strain sensor based
on FBG is studied here. The sensing element has a metal trapezoidal frame. The two feet of the frame can sense a large
strain of the body, which is converted to a small strain on the surface of the frame' beam. The attached FBG senses this
small strain, and then the body's strain can be known from the FBG's wavelength shift. The trapezoidal frame is taken
theoretically analysis adopting the 'unit load method' and numerical simulation by finite element method. The
sensitivity model of the sensor between the body's strain and the FBG's wavelength shift is deduced and verified. Real
large strain sensors are homemade, with verifying sizes. The large strain is controlled by a motorized translation stage,
and the FBG's wavelength shift is interrogated by MOI sm125 interrogator. The experimental results show an
outstanding large-strain sensing ability of the sensors, having the sensing range of -20~40%, with the linearity of less
than 1%, the hysterisis error of less than 1% and the repeatability of less than 0.9%.