曾昕,蒋瑜,范政伟,雷武阳.包装运输试验中非平稳随机振动表征和模拟方法[J].包装工程,2021,42(9):1-10.
ZENG Xin,JIANG Yu,FAN Zheng-wei,LEI Wu-yang.Characterization and Simulation Method of Non-Stationary Random Vibration in Packaging and Transportation Test[J].Packaging Engineering,2021,42(9):1-10. |
| 包装运输试验中非平稳随机振动表征和模拟方法 |
| Characterization and Simulation Method of Non-Stationary Random Vibration in Packaging and Transportation Test |
| 投稿时间：2021-03-19 |
| DOI：10.19554/j.cnki.1001-3563.2021.09.001 |
| 中文关键词: 非平稳 非高斯 随机振动 贝塔分布 |
| 英文关键词: non-stationary non-gaussian random vibration beta distribution |
| 基金项目:国家自然科学基金(51875570) |
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| 中文摘要: |
| 目的 研究量化表征非平稳随机振动的方法，模拟包装物实际运输振动环境中的非平稳和非高斯特征。方法 通过引入“运行测试”非参数统计检验方法，对均方根值时变非平稳过程进行量化表征，利用贝塔分布随机数的幅值调制方法模拟生成非平稳非高斯随机过程。结果 通过数值验证贝塔分布方法，能够基于目标峭度和功率谱密度函数等约束条件灵活生成具有不同平稳程度的非平稳非高斯随机过程。结论 该方法可以对非平稳特征进行定量表征，并可用于真实模拟包装件的运输振动环境，避免“欠试验”和“过试验”问题的发生。 |
| 英文摘要: |
| The stationary gaussian assumption hypothesis is often used as the test condition for the traditional random vibration transportation test of packaging materials. The paper aims to study a method to quantify and characterize non-stationary random vibration, and to simulate non-stationary and non-gaussian characteristics in the actual transportation vibration environment of packaging, especially under harsh road conditions. This paper introduces the run test non-parametric statistical test method to quantitatively characterize the time-varying non-stationary process of the root mean square value. The amplitude modulation method of beta distributed random number, non-stationary and non-gaussian random processes were simulated. It is verified numerically that the beta distribution method can flexibly generate non-stationary non-gaussian random processes with different degrees of stability based on constraint conditions such as target kurtosis and power spectral density function. This method can be used to quantitatively characterize non-stationary features, and can be used to truly simulate the actual transportation vibration environment of the package, avoiding the occurrence of under-test and over-test problems. |
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