Statistical energy analysis for a compact refrigeration compressor

Abstract

Traditionally the prediction of the vibrational energy level of the components in a compressor is accomplished by using a deterministic model such as a finite element model. While a deterministic approach requires much detail and computational time for a complete dynamic analysis, statistical energy analysis (SEA) requires much less information and computing time. All of these benefits can be obtained by using data averaged over the frequency and spatial domains instead of the direct use of deterministic data. In this paper, SEA will be applied to a compact refrigeration compressor for the prediction of dynamic behavior of each subsystem. Since the compressor used in this application is compact and stiff, the modal densities of its various components are low, especially in the low frequency ranges, and most energy transfers in these ranges are achieved through the indirect coupling paths instead of via direct coupling. For this reason, experimental SEA (ESEA), a good tool for the consideration of the indirect coupling, was used to derive an SEA formulation. Direct comparison of SEA results and experimental data for an operating compressor will be introduced. The power transfer path analysis at certain frequencies made possible by using SEA will be also described to show the advantage of SEA in this application.