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首页> 外文会议>6th International RILEM Symposium on Performance Testing and Evaluation of Bituminous Materials, (PTEBM'03) Pt.1 Apr 14-16, 2003 Zurich, Switzerland >COMPARISON OF ANALYSIS TECHNIQUES TO OBTAIN MODULUS AND PHASE ANGLE FROM SINUSOIDAL TEST DATA
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COMPARISON OF ANALYSIS TECHNIQUES TO OBTAIN MODULUS AND PHASE ANGLE FROM SINUSOIDAL TEST DATA

机译：正弦测试数据对获得模量和相角分析技术的比较

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摘要

This paper compares different analysis techniques of computing modulus and phase angle from cyclic sinusoidal data in compressive dynamic (complex) modulus testing. Analyzed data reduction techniques were 1) localized multiple linear regressions for peak picking to define amplitude and phase angle from the peaks averaged over a group of cycles, 2) sinusoidal full waveform curve fitting for a single estimate of amplitude and phase over a group of cycles, and 3) two-step analyses over a group of cycles involving regression across peaks (Spencer's 15-point filtering) for amplitude and phase determination from the central part of the waveform. The computed modulus values were statistically less sensitive to different analysis techniques than the phase angles. The first method was the most robust but predicted phase angles that appeared to be too high at intermediate temperatures. Spencer's 15-point filtering with central waveform bracketing turned out to be a slightly more robust method than sinusoidal regression to obtain stable parameter estimates from the imperfect raw data. However, sinusoidal regression gave parameter estimates almost identical to the estimates obtained from Fast Fourier Transformation (FFT), while the other methods deviated from the FFT estimates. To make conclusive recommendations, an additional study is underway to compare Master Curves constructed using raw data analyzed with different techniques. The performed analysis though suggests that there is a need to limit the deviations of the controlling load waveform from a perfect sine wave to guarantee good quality test data.
机译：本文比较了在压缩动态（复杂）模量测试中根据循环正弦数据计算模量和相角的不同分析技术。分析的数据缩减技术是：1）局部采光的多个线性回归，以根据一组周期内平均的峰定义振幅和相位角； 2）正弦全波形曲线拟合，用于一组周期内的振幅和相位的单个估计，以及3）在一组循环中进行两步分析，其中涉及跨峰的回归（Spencer的15点滤波），以便从波形的中心部分确定幅度和相位。统计上，模量值对不同分析技术的敏感性低于相角。第一种方法是最稳健但可预测的相角，在中间温度下似乎太高。 Spencer的带有中心波形包围的15点滤波方法比从不完善的原始数据中获得稳定的参数估计值的正弦回归要强得多。但是，正弦回归给出的参数估计几乎与从快速傅里叶变换（FFT）获得的估计相同，而其他方法则与FFT估计有所不同。为了提出结论性建议，正在进行另一项研究，以比较使用不同技术分析的原始数据构建的主曲线。不过，进行的分析表明，有必要限制控制负载波形与理想正弦波之间的偏差，以确保获得高质量的测试数据。

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