In this study, we considered accuracy evaluation indices for operational transfer path analysis (TPA) that employs the principal component regression method, and we verified their reliability. To evaluate the accuracy of TPA, the consistency of the response signals, in which the calculated response signal from the TPA model is compared with the measured response signal, has been frequently used in the past. Also, some cases use the condition number that indicates the inverse matrix condition used in the calculation procedure of the acceleration transfer function. In addition to these accuracy evaluation indices, a correlated principal component number (CPCN), which indicates the number of principal components that correlate with the response signal generated at the running test, has been proposed. The reliability of these accuracy evaluation indices has been verified through a simple simulation. The results show that the two conventional indices (the consistency method and the condition number) do not satisfactorily evaluate the accuracy. However, a CPCN can indicate the frequency bands where the TPA accuracy is high or low. Consequently, the new index was found to be a suitable index for evaluating the accuracy of the operational TPA.
In this study, an accuracy evaluation index for running transfer path analysis (TPA) employing principal component regression method was considered and the reliability was verified. To evaluate the TPA accuracy, the consistency of response signals in which the calculated response signal from the TPA model was compared with the measured response signal was used frequently until now. Also, the condition number that indicates the inverse matrix condition used in the calculation procedure of acceleration transfer function was employed in some cases. In addition to these accuracy evaluation methods, correlated principal component number (CPCN), that indicates the number of principal component correlating with the response signal generated at the running test, was proposed. The reliabilities of these accuracy evaluation methods were verified through simulation. As a result, the conventional two methods (consistency method and condition number) could not evaluate the accuracy well. However, CPCN index could indicate the frequency bands where the TPA accuracy was high or low. Consequently, the new index was found to be a suitable index for accuracy evaluation of the running TPA.
In this study , we verified accuracies of tw kinds of transfor path analysis methods by perferming a simple structure test . Inverse matrix method using transfer functions and principal c 。mponcnt analysis method using only running data were exarnined . As the result of experiments , the accuracies ofthese methods were clarified to drop occasionally in some f 卜 equencies , but the frequencies are different each other . These results indicato that it is necessary to select suitable transfer path analysis method accerding to the target frequency fbr obtaining contribution ofnoise and vibration accurately. Key we rds :Transfer path analysis , Inverse matrix method , Principa 且component regression method
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