科研之友
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摘要
During transportation, protective packaging is subjected to random dynamic compressive loads that arise from random vibrations generated by the vehicle. The ability of the protective packaging to withstand these dynamic compressive loads depends on the environmental vibration levels, the nominal stresses and the material's characteristics. Previous research has shown that cumulative damage, in the packaging system under random dynamic compression, will result in a change in the overall stiffness of the system. This change is manifested as a shift in the system's fundamental resonant frequency. Natural frequency estimates are often extracted using a least squares regression curve fit applied to an estimate of the system's frequency response function. Frequency response function estimates are generally obtained using the Fourier transform with a single input/single output (SISO). This approach is suitable for many applications; however, it is not well suited to non-linear systems subjected to non-stationary excitation where the vibration level (overall root-mean-square value) can vary. This paper investigates the use of an optimised reverse multiple input/single output algorithm for reliably tracking variations in the condition of packaging elements subjected to excitation with varying magnitude (root-mean-square). Results are presented from the analysis of physical experiments performed on expanded polystyrene cushions as well as empty corrugated paperboard containers. The experiments performed using the polystyrene samples were designed to limit natural variation in the system's natural frequency; whereas the paperboard samples were allowed to naturally damage under dynamic loading.
- 出版日期2015-8
