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The skin and skeleton of aircraft are connected by adhesives or rivets to bear and transfer aerodynamic load. It is easy for crack and fracture damage to occur under the action of cyclic load, thus reducing aircraft bearing capacity/integrity and causing serious security risks. Therefore, it is particularly important that passive wireless radio frequency identification (RFID) sensors be used for the health monitoring of aircraft skin in its whole life cycle. This paper aims to investigate the influence of miniaturization on the coupling effect between RFID tag sensors.

Two groups of crack sensing systems based on RFID tags were designed. Gain and mutual impedance of sensor tags were analyzed via mode analysis. The reliability of crack detection of both sensing systems was compared using a preset experimental scheme.

Miniaturized antennas can reduce edge influence and the coupling effect. Gain and mutual impedance decrease with the increase in distance between dual tags. Backscatter power shows a decreasing trend and threshold power to activate tags in reader antenna increases. Results show that the miniaturization of size is more suitable for the application of multiple sensors.

By comparing two groups of sensing systems, the consistency of crack detection sensitivity is better when small tags are placed in parallel, which provides a theoretical basis for the application of small, passive and densely distributed crack sensors in the future.

For many optimization problems such as optimal techniques, compositions, producing process, the optimizing objectives in systems are complex relations with respect to a great deal of parameters. Generally, the objective function is hardly obtained, even the searching objective is unquantifiable. So it is difficult to model and optimize the complex systems to some extent.

To the above purpose, a novel approach is presented in this paper. It firstly utilizes the excellent fitting performance of neural network (NN) combined with expert knowledge (EK) to obtain the objective function, and secondly searches the optimal influential parameters with genetic algorithm (GA).

Peaks function inside Matlab and the acural application of comprehensive performance optimization in analog PID control system are studied, respectively. The results of simulation and the actual experiment both show that the modeling and optimizing method presented in the paper are effective.

Expert knowledge is needed for the fuzzy/unquantifiable objective.

The paper presents a useful way to model and optimize complex systems.

The combined approach based on NN, EK and GA is firstly presented and is effectively used in modeling and optimizing complex systems.