This research aims to identify the behavioral characteristics of a biased IPMC sensor and maximize its sensitivity by optimizing the related parameters. For this purpose, an IPMC strip was stimulated with a custom setup and the experimental data was recorded. Then, a multiple linear regression model was used to determine the basic functional factors of the biased IPMC sensor. Finally, the optimal operating point of the sensor was estimated using the partial derivative method and contour plots. Statistical analysis showed that the mechanical excitation frequency, electrical bias frequency, electrical bias amplitude, and the value of bias resistance had a significant effect on the sensitivity of the IPMC sensor. Adjusted/predicted R-squared in the proposed model was calculated 0.9498/0.9435, respectively, which indicates high accuracy in data fitting. Also, analysis of the residuals showed that the model has the required adequacy. In addition, the consistency of the optimal operating point from the optimization method with practical experiments shows the synergy of partial derivatives and plot counters can be used as an efficient method in further optimization studies.

Keywords