Placement optimization of distributed-sensing fiber-optic sensors using genetic algorithms

In this paper, we present methodology for the placement optimization of both discretely and continuously distributed fiber-optic sensors in which many point or quasi-point sensors can be multiplexed along a single optical fiber. A unified sensor performance metric is defined for vibration monitoring and fault detection as the integration/summation of a weighted functional of some strain measure over the optical fiber length for both discretely and continuously distributed fiber-optic sensors. The optical fiber is represented by a, nonuniform rational B-splines curve. The design variables include the control point coordinates of the nonuniform rational B-splines curve and the arclength coordinates of the point sensing element positions along the fiber. The constraints common to all kinds of optical sensors include the maximum fiber length and maximum allowed initial curvature. The constraints are treated as the exact penalty functions in the fitness function for any genetic algorithm. For discretely distributed fiber-optic sensors, we briefly show by an example how to use a genetic algorithm-based traveling salesman problem solver to optimally connect those optimally distributed sensors using one single optical fiber by minimizing the total fiber length. For continuously distributed fiber-optic sensors, two sets of examples are given as applications to fluttering or vibrating panels in aerospace engineering and a clinical smart bed for patient vital signal monitoring in biomedical engineering. In both cases, the integrating bend-sensing fiber-optic sensors are used.