Entangled porous metallic wire material(EPMWM)has the potential as a thermal insulation material in defence and engineering.In order to optimize its thermophysical properties at the design stage,it is of great signifi...Entangled porous metallic wire material(EPMWM)has the potential as a thermal insulation material in defence and engineering.In order to optimize its thermophysical properties at the design stage,it is of great significance to reveal the thermal response mechanism of EPMWM based on its complex structural effects.In the present work,virtual manufacturing technology(VMT)was developed to restore the physics-based 3D model of EPMWM.On this basis,the transient thermal analysis is carried out to explore the contact-relevant thermal behavior of EPMWM,and then the spiral unit containing unique structural information are further extracted and counted.In particular,the thermal resistance network is numerically constructed based on the spiral unit through the thermoelectric analogy method to accurately predict the effective thermal conductivity(ETC)of EPMWM.Finally,the thermal diffusivity and specific heat of the samples were obtained by the laser thermal analyzer to calculate the ETC and thermal insulation factor of interest.The results show that the ETC of EPMWM increases with increasing temperature or reducing density under the experimental conditions.The numerical prediction is consistent with the experimental result and the average error is less than 4%.展开更多
局部均值分解方法(Local Mean Decomposition,LMD)是一种性能优越的旋转机械故障诊断的方法,它不仅可以准确地反映非平稳信号的时频分布,而且非常适合处理含有多分量成分的非平稳信号。但是由于LMD方法本身的缺陷,使得该方法存在着诸如...局部均值分解方法(Local Mean Decomposition,LMD)是一种性能优越的旋转机械故障诊断的方法,它不仅可以准确地反映非平稳信号的时频分布,而且非常适合处理含有多分量成分的非平稳信号。但是由于LMD方法本身的缺陷,使得该方法存在着诸如端点效应的处理方法、迭代终止条件的确定等问题。在介绍LMD方法的基础上,分别以改进的“自适应延拓法”和“信息熵判据”解决以上两个问题,并结合仿真软件上验证改进结果。展开更多
基金National Natural Science Foundation of China(Grant Nos.52175162,51805086 and 51975123)Natural Science Foundation of Fujian Province,China(Grant No.2019J01210)Health Education Joint Project of Fujian Province,China(Grant No.2019-WJ-01).
文摘Entangled porous metallic wire material(EPMWM)has the potential as a thermal insulation material in defence and engineering.In order to optimize its thermophysical properties at the design stage,it is of great significance to reveal the thermal response mechanism of EPMWM based on its complex structural effects.In the present work,virtual manufacturing technology(VMT)was developed to restore the physics-based 3D model of EPMWM.On this basis,the transient thermal analysis is carried out to explore the contact-relevant thermal behavior of EPMWM,and then the spiral unit containing unique structural information are further extracted and counted.In particular,the thermal resistance network is numerically constructed based on the spiral unit through the thermoelectric analogy method to accurately predict the effective thermal conductivity(ETC)of EPMWM.Finally,the thermal diffusivity and specific heat of the samples were obtained by the laser thermal analyzer to calculate the ETC and thermal insulation factor of interest.The results show that the ETC of EPMWM increases with increasing temperature or reducing density under the experimental conditions.The numerical prediction is consistent with the experimental result and the average error is less than 4%.
文摘局部均值分解方法(Local Mean Decomposition,LMD)是一种性能优越的旋转机械故障诊断的方法,它不仅可以准确地反映非平稳信号的时频分布,而且非常适合处理含有多分量成分的非平稳信号。但是由于LMD方法本身的缺陷,使得该方法存在着诸如端点效应的处理方法、迭代终止条件的确定等问题。在介绍LMD方法的基础上,分别以改进的“自适应延拓法”和“信息熵判据”解决以上两个问题,并结合仿真软件上验证改进结果。
