基于同步提取和时频系数模极值的瞬时频率识别
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TN911.6; TU311.3

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国家自然科学基金资助项目(51608122);中国博士后科学基金资助项目(2018M632561);福建省自然科学基金面上项目(2020J01581);福建农林大学杰出青年基金资助项目(XJQ201728);福建农林大学科技创新专项基金资助项目(CXZX2020112A)


Instantaneous Frequency Identification Based on Synchroextraction and Maximum Modulus of Time⁃Frequency Coefficients
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    摘要:

    针对时频系数模极大值脊线提取算法难以精确识别含噪响应信号瞬时频率的特点,提出一种同步提取和时频系数模极大值相结合的时变结构响应信号瞬时频率识别方法。首先,采用同步提取算法将瞬时频率锁定在一定范围内,避免了人工选择搜索范围的随意性;其次,在锁定的曲带范围内逐点搜索时频系数模极大值,最终得到高精度的时频脊线和瞬时频率曲线。通过一个单分量信号数值算例、一个多分量信号数值算例、一个刚度时变拉索试验和一个质量突变悬臂梁试验验证该方法的有效性和准确性,研究结果表明,所提方法能够有效提取时变结构响应信号的瞬时频率且识别精度优于小波系数模极大值和同步挤压小波变换方法,同时也具有良好的抗噪性。

    Abstract:

    Since it is difficult to identify instantaneous frequency (IF) of noisy response signal accurately by maximum modulus of time-frequency coefficients algorithm, a new method is proposed by combining synchroextracting transform (SET) and maximum modulus of time-frequency coefficients algorithm. At first, the IF is restricted within a range by SET and hence the randomness of searching area selection is avoided. Then, time-frequency ridges and the IF curves with high accuracy are obtained by gradually searching the modulus maxima of time-frequency coefficients in the area restricted by the SET. Two numerical simulations of a mono-component signal and a multi-component signal, a steel cable test with time-varying tension forces and an aluminum cantilever beam test with abrupt mass reduction are used to verify the effectiveness and accuracy of the proposed method. The results demonstrated that the proposed method can effectively extract the IF of time-varying response signal. Compared with the maximum modulus of wavelet coefficients algorithm and synchrosqueezing wavelet transform method, the proposed method behaves better on IF identification and has a good anti-noise property.

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  • 在线发布日期: 2021-06-25
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