Accurately determining the loads acting on a structure is critical for simulation tasks, especially in fatigue analysis. However, current methods for determining component loads using load cascade techniques and multi-body dynamics (MBD) simulation models have intrinsic accuracy constraints because of approximations and measurement uncertainties. Moreover, constructing precise MBD models is a time-consuming process, resulting in long turnaround times. Consequently, there is a pressing need for a more direct and precise approach to component load estimation that reduces efforts and time while enhancing accuracy.
A novel solution has emerged to tackle these requirements by leveraging the structure itself as a load transducer [1]. Previous efforts in this direction faced challenges associated with cross-talk issues, but those obstacles have been overcome with the introduction of the "pseudo-inverse" concept. By combining the pseudo-inverse technique with the D-optimal algorithm, researchers have devised a robust and versatile method for identifying optimal sensor positions (e.g., strain gauges) on the structure where its response can be accurately measured. The pseudo-inverse facilitates the pre-calculation of a calibration matrix, which, when combined with the measured responses, enables the reverse calculation of the loads acting on the structure. This approach offers several advantages over conventional load cascading methods, including higher accuracy in load calculation by minimizing sources of error and the ability to estimate potential errors beforehand.
In summary, the integration of the pseudo-inverse technique and the D-optimal algorithm provides an innovative and efficient solution to enhance the accuracy and turnaround time of component load estimations in structural analysis. By utilizing the structure as a load transducer, this method offers a more direct, accurate, and error-aware approach to load calculations, leading to the emergence of robust design solutions.