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Variable Amplitude Loading Strains Data Distribution using ProbabilityDensity Function and Power Spectral Density

机译:可变幅度加载应变数据分布使用概率密度函数和功率谱密度

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This paper presents a relative study on variable amplitude (VA) strain data distribution using the approach of probability density function (PDF) and power spectral density (PSD). PDF is a technique to identify the probability of the value falling within a particular interval, and a PSD is to measure the power of a signal by converting it from the time domain to the frequency domain. The objective of this study is to observe the applicability of both techniques in detecting the pattern behaviour in terms of energy and probability distribution. For this reason, a set of case study data consist of nonstationary VA pattern with a random behaviour was used. This kind of data was measured by fixing a strain gauge that connected to the strain data acquisition on the lower suspension arm of a mid-sized sedan car. The data was measured for 60 seconds at the sampling rate of 500 Hz, which gave 30,000 discrete points. The distribution of collected data was then calculated and analysed in the form of both PDF and PSD, and they were then compared for further analysis. The findings from this study are expected for determining the pattern behaviour that exists in VA strain signals.
机译:本文介绍了使用概率密度函数(PDF)和功率谱密度(PSD)的方法的可变幅度(VA)应变数据分布的相对研究。 PDF是识别落在特定间隔内的值的概率的技术,并且PSD是通过将其从时域转换为频域来测量信号的功率。本研究的目的是遵守两种技术在能量和概率分布方面检测模式行为的适用性。因此,使用一组案例研究数据包括具有随机行为的非间断VA模式。通过固定连接到中型轿车的下悬架臂上的应变数据采集的应变仪来测量这种数据。以500Hz的采样率测量数据60秒,从而提供30,000个离散点。然后计算收集数据的分布并以PDF和PSD的形式进行分析,然后比较它们以进一步分析。该研究的发现预计用于确定VA应变信号中存在的模式行为。

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