44 E. Proner and E. Mucchi The MPMdetermined the highest reduction of the drives, while preserving the response and the fatigue damage induced in the specimen by the target. On the contrary, when controlling the tab accelerometer, the MDMrequired higher drives the MPMand determined a different response of the specimen which lead to a significant under-testing of the DUT. Moreover, when controlling the response of the DUT to match thetarget responses, theMDMwas able to replicate thetarget responses. However, the drive minimization was not successful because of the physical constrains of the DUT, which lead to an increase in the required voltage. It can be concluded that the Minimum PSDs Method allows to replicate a set of responses on the DUT while reducing the total power required to conduct the test. The methodology may allow to re-design multi-axis random control tests, reducing the drive requirements while preserving the damaging effects of a targeted vibration environment. References 1. Underwood, M.A. “Multi-exciter testing applications: theory and practice”. Proceedings-institute of environmental sciences and technology, pages 1–10 (2002) 2. Peeters, B. and Debille, J. “Multiple-input-multiple-output random vibration control: Theory and practice”. Proceedings of the 2002 International Conference on Noise and Vibration Engineering, ISMA, page 507 – 516 (2002) 3. Smallwood, D.O. “Multiple-input multiple-output (mimo) linear systems extreme inputs/outputs”. 14(2):107 – 131 (2007) 4. Smallwood, D. “A proposed method to generate a spectral density matrix for a multiple input, multiple output (mimo) vibration test”. Proc. of 80th Shock and Vibration Symposium. 5. D’Elia, G., Musella, U., Mucchi, E., Guillaume, P., and Peeters, B. “Analyses of drives power reduction techniques for multi-axis random vibration control tests”. Mechanical Systems and Signal Processing, 135:106395 (2020) 6. Musella, U., D’Elia, G., Carrella, A., Peeters, B., Mucchi, E., Marulo, F., and Guillaume, P. “A minimum drives automatic target definition procedure for multi-axis random control testing”. Mechanical Systems and Signal Processing, 107:452–468 (2018) 7. D’Elia, G., Mucchi, E., and Dalpiaz, G. “A novel methodology for dynamic response maximisation in multi-axis accelerated random fatigue testing”. Mechanical Systems and Signal Processing, 181 (2022) 8. D’Elia, G., Proner, E., and Mucchi, E. “Accelerated random fatigue testing by means of a triaxial electrodynamic shaker: solutions for combining the multiple test specifications”. page 1224 – 1232 (2022) 9. Zheng, R., Xie, W., Wei, X., and Chen, H. “Limit strategy for multi-input multi-output random vibration control”. Mechanical Systems and Signal Processing, 195 (2023) 10. Dirlik, T. “Application of computers in fatigue analysis.”. Ph.D. Thesis, University of Warwick (1985)
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