Optimal sensor placement for strain sensing of a beam of high-speed EMU

Aiming at the strain sensing of a beam of high-speed EMU, optimal sensor placement (OSP) is studied based on the information gain and modal expansion method within the Bayesian framework. In addition, the role of the prediction error in OSP and strain reconstruction is investigated in detail. Two new prediction errors are proposed: the measurement error weighted by modal strain energy and the modeling error based on the change of element stiffness. The covariance matrix of prediction error is obtained by probability method, which improves the calculation efficiency. Also, a method to determine the number of modes based on the change rate of modal strain energy is proposed. With reference to a case study of a beam, the effect of the prediction error on OSP and strain sensing is described and the reliability and the robustness of the proposed method are tested. Finally, the proposed method is further validated through a case study of full-scale beam monitoring systems based on Fiber Bragg grating (FBG) sensors. The errors between the real and reconstructed strains are compared through the measured data. The results show that the errors between the reconstructed strain and the real strain are very small, which illustrates that this method can be used for strain sensing.

Automated summary

In this study, optimal sensor placement (OSP) for strain sensing of a high-speed EMU beam is investigated using the information gain and modal expansion method within the Bayesian framework. The role of prediction error in OSP and strain reconstruction is studied in detail, and two new prediction errors are proposed. The method is validated through a case study of a beam and full-scale beam monitoring systems based on Fiber Bragg grating (FBG) sensors.