Of 324.5469 7.8081 N/(m/s) using a probability of 99 . Consequently, it truly is necof 324.5469 7.8081 N/(m/s) having a probability of 99 . Consequently, it really is essential to evaluate evaluate the influence with the uncertainty of structural damping and contact essary towards the influence of the uncertainty of structural damping and contact damping on the sensitivity of parameter identification. In this study, it really is proposed is input the to indamping around the sensitivity of parameter identification. In this study, it to proposed upper and lower limits from the self-confidence Lanabecestat Technical Information interval of damping into Approach three into Technique three in place the upper and reduce limits from the confidence interval of dampingin order to analyze the parameter sensitivity. The sensitivity. F statistics for Table shown in Table five. order to analyze the parameterstatistics for Theare shown in F are5.Table five. The worth of F when the damping is inside the self-assurance = 99). Table five. The value of F when the damping is within the confidence interval (P = 99). Damping is of mean in the interval Damping could be the meanthe the confidenceconfidence interval 0.049 Damping could be the upper limit of your self-assurance confidence interval0.051 Damping may be the upper limit from the interval Damping is the reduced limit with the confidence self-confidence interval0.048 Damping could be the lower limit from the interval’ S” 33 33 0.0490.085 0.051 0.084 0.048 0.S” 33 0.085 0.084 0.d” d33”0.029 0.029 0.031 0.031 0.027 0.From Table five, the uncertainty of damping has pretty much no impact onon the sensitivitythe From Table the uncertainty of damping has virtually no impact the sensitivity of from the imaginary partsthethe material complex parameters. imaginary components of of material complex parameters.four.two. Comparison amongst Simulation and Experiments 4.two. Comparison involving Simulation and Experiments DMPO Chemical Figure 13a could be the comparison of the experimental impedance modulus data as well as the Figure 13a is definitely the comparison in the experimental impedance modulus data and the simulationdata in the transducer (Figure 1) at ten Mpa, and Figure 13b is definitely the comparison simulation data of the transducer (Figure 1) at 10 Mpa, and Figure 13b could be the comparison on the experimental phase data and also the simulation information. Table 6 shows the RMSE and in the experimental phase information and also the simulation information. Table 6 shows the RMSE and determination coefficient (R2 between the experimental data and simulation data. determination coefficient (R2))amongst the experimental information and simulation information.(a)(b)Figure 13. Comparison in the experimental information and simulation information under pre-stress conditions of Figure 13. Comparison of the experimental data and simulation data beneath pre-stress circumstances of 10 Mpa (a) impedance modulus and (b) phase. ten Mpa (a) impedance modulus and (b) phase.Micromachines 2021, 12, x FOR PEER Review Micromachines 2021, 12,16 of 21 15 of2 Table 6. The RMSE and R2 involving the experimental data and simulation data. Table 6. The RMSE and R involving the experimental data and simulation information.RMSE of impedance modulus information RMSE of impedance modulus data RMSE of phase data RMSE of phase information R2 of impedance modulus data R2 of impedance modulus information R2 of phase R2 of phase data dataMethodMethod 1 Strategy two Approach two 1.8589 3.2979 1.8589 6.2623 3.2979 2.5243 six.2623 2.5243 0.9963 0.9887 0.9963 0.9887 0.9170 0.4573 0.4573 0.MethodMethod 3 1.3377 1.3377 1.6748 1.6748 0.9981 0.9981 0.9746 0.Strategy 1 is according to the impedance modulus information for parameter extraction. When Process 1 is according to the impedance modu.
