【作者】 赵坚；

【导师】 王太勇；

【作者基本信息】 天津大学 ， 机械制造及其自动化， 2007， 博士

【摘要】 系统动态特性参数的时频域辨识方法作为模态分析领域的新进展和时频分析理论的新应用,正在逐渐引起国际学术界的重视。在总结了国内外模态分析发展历程,归纳了时频域参数辨识技术存在的问题的基础上,本文就机械系统动态特性参数的时频域辨识新方法以及参数辨识中的关键问题展开研究。全文主要完成了以下几个方面的工作:1)为了解决时频图像脊识别问题,提出一种基于标准微粒群算法的单条脊识别方法。在改进微粒群进化方程基础上,又提出一种基于改进多目标微粒群算法的多条脊线识别方法。实验证明了基于微粒群算法的脊提取方法具有运算速度快,结构简单,识别精度高,迭代次数少,抗噪声干扰等优点。2)构建了一种蚂蚁爬山算法识别多条脊线。实验证明了这种算法能有效提取出变换域平面的多条脊,且精度高。并通过设定脊线能量阈值和设定连线间距的方式,有效剔除伪脊。3)从多自由度系统时域脉冲响应函数模型入手,构建了一种系统动态特性参数的核函数辨识法。在对该方法进行理论研究的基础上,建立了“CWD-能量重心转移-改进Hough变换”方法提取脊,然后计算固有频率的完整的辨识过程。仿真实验证明该方法不仅有较高的分辨率,对噪声不敏感,而且运算时间短。4)为了扩大小波辨识的应用范围,提出把NExT法与连续小波变换法相结合的综合辨识方法。推导了小波辨识法参数估计的公式,给出了参数估计的完整过程。分析了Gabor小波在减少边缘效应和提高密集模态辨识能力方面的优势。还仿真研究了Gabor小波形状因子对模态参数辨识精度的影响,给出了选择形状因子的建议。通过仿真实验,证明了小波辨识法对噪声的鲁棒性。5)构建了一种EMD与自适应特征匹配协同识别的参数辨识法。并把微粒群算法引入自适应特征匹配算法中,提出基于PSO算法的自适应匹配法;建立了完整的辨识过程。仿真验证了经过EMD预处理之后,参数匹配速度明显提高,匹配精度也有所提高。6)借助悬臂梁对几种方法做了对比实验,并结合工程实例验证了几种方法的可行性。更多还原

【Abstract】 The time-frequency domain identification method of system dynamic characteristic parameters as new progress in the field of modal analysis and application of the time-frequency analysis theory is gradually attracting the attention of the international academia. On the basis of summing up the development of the modal analysis and the existing problems of the time-frequency domain parameters identification technique, this dissertation deals with the new identification methods of mechanical system dynamic characteristic parameters in time-frequency domain and the key issues in the process of parameter identification. The following contributions have been made.1) In order to solve the problem of detecting a time-frequency image ridge, the particle swarm optimization (PSO) algorithm is introduced. A method of single ridge detection based on the standard PSO algorithm is proposed. Furthermore, a method of multi-ridge detection based on the improved multi-objective PSO algorithm is presented by modifying the PSO evolutionary equations. The simulation experiment results prove that these methods are fast and simple, with high accuracy, less iterations and small noise.2) A hill-climbing algorithm is proposed for detecting multi-ridge. Experiment results show that the method is effective and accurate for multi-ridge detection, and those virtual ridges are eliminated by setting up the ridge energy threshold and the distance among ridges.3) Starting from the model of impulse response of multi-degrees of freedom (MDOF) system, an identification method for the system modal parameters with the time-frequency kernel is formulated. By firstly detecting the ridge using the CWD (Choi-Williams Distribution)-Time-frequency Reassignment and the improved Hough transform and then evaluating the inherent frequency, the integrated identification process is established. The integrated identification process of the method is established. The simulation results show the identification method not only has a higher resolution and is not sensitive to noise, but also is characterized with short time of computation.4) To expand the scope of the application of the wavelet identification, an identification method combining the NExT (Natural Excitation Technique) and the continuous wavelet transform is proposed. The equations of the parameters estimation using the wavelet identification method are derived, and the whole process of the parameters estimation is given. The selection of basic wavelet is fully studied. The advantages, with which the Gabor wavelet can minimize the edge-effects and improve the capability of identifying the heavily coupled modes, are systematically analyzed. Thereafter, the influences of Gabor mother wavelets with different shaping factors on the accuracy of the modal parameter identification are evaluated. The robustness of this method is proved by simulation.5) An EMD (Empirical Mode Decomposition) cooperated with adaptive matched pursuit identification method is proposed. The Laplace wavelet is selected for time-frequency atom to formulate the four parameters time-frequency atom dictionary. The adaptive feature matching algorithm based on PSO algorithm is presented. The simulation results show that after the pretreatment of the EMD, the speed and accuracy of parameter matching are significantly upgraded.6) These algorithms are applied separately to socle beam testing, and the feasibility as well as accuracy of these methods are justified by technical practice.更多还原