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Statistical energy analysis for a compact refrigeration compressor and model improvement.

机译:紧凑型制冷压缩机的统计能量分析和模型改进。

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摘要

Traditionally the prediction of the vibrational energy levels of the components in a compressor is accomplished by using a deterministic model such as a finite element model. While a complete dynamic analysis based on a deterministic approach requires much detail and computational time, an analysis performed using 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 work, SEA was applied to a compact refrigeration compressor for the prediction of dynamic behavior of each subsystem. Since the compressor used in this application was compact and stiff, the modal densities of its various components were low, especially in the low frequency ranges, and much energy in these ranges transmits through indirect coupling paths instead of via direct coupling. Indirect coupling is usually significant in systems that are not well matched with the assumptions on which the development of classical SEA is based. For this reason, experimental SEA (ESEA), a good tool for the consideration of the indirect coupling, was used to derive the SEA formulation in this case. Direct comparison of SEA results and experimental data for an operating compressor will be shown. The power transfer path analysis at certain frequencies made possible by using SEA will also be described to show the advantage of SEA in this application.;Even though a system can be modeled without error in terms of being able to reproduce measured results, it does not always guarantee an ideal SEA model for diagnostic purposes. For this reason, model quality indices were introduced to check an experimental SEA model, and random weighting factors were directly applied to the components in the SEA model to obtain an ideal model. The presence of strong coupling in an SEA model can cause the SEA parameters to take undesirable values, and this effect usually prevents clear interpretation of SEA results in a physical sense. To overcome this problem, it was proposed that strongly coupled subsystems should be combined and modeled as one in an SEA model. Applications and verifications of the latter point were demonstrated with the help of finite element analyses, and the concept was applied to the experimental SEA model of an actual compressor in the final stage.
机译:传统上,通过使用确定性模型(例如有限元模型)来完成对压缩机中组件振动能量水平的预测。尽管基于确定性方法的完整动态分析需要大量细节和计算时间,但使用统计能量分析(SEA)执行的分析所需的信息和计算时间却少得多。通过使用在频域和空间域上平均的数据而不是直接使用确定性数据,可以获得所有这些好处。在这项工作中,将SEA应用于紧凑型制冷压缩机,以预测每个子系统的动态行为。由于此应用中使用的压缩机紧凑且坚固,因此其各个组件的模态密度很低,尤其是在低频范围内,并且这些范围内的大量能量通过间接耦合路径而不是直接耦合传递。在与经典SEA的开发所基于的假设不完全匹配的系统中,间接耦合通常很重要。因此,在这种情况下,实验性SEA(ESEA)是考虑间接耦合的一种很好的工具,用于推导SEA公式。将显示SEA结果与运行中的压缩机的实验数据的直接比较。还将描述通过使用SEA在某些频率下进行的功率传输路径分析,以显示SEA在此应用中的优势。;即使可以对系统进行建模,但在能够重现测量结果方面没有错误,但它并没有始终保证用于诊断目的的理想SEA模型。因此,引入模型质量指标来检查实验性SEA模型,并将随机加权因子直接应用于SEA模型中的组件以获得理想模型。 SEA模型中强耦合的存在会导致SEA参数取不希望的值,并且这种效果通常会阻止从物理意义上清楚地解释SEA结果。为了克服这个问题,有人建议将强耦合子系统组合在一起并在SEA模型中建模为一个子系统。在有限元分析的帮助下,对后一点的应用和验证进行了演示,并将该概念应用于最后阶段的实际压缩机的实验SEA模型。

著录项

  • 作者

    Lim, Jimin.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 214 p.
  • 总页数 214
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机械、仪表工业;
  • 关键词

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