机械系统动力学特性的综合分析及其工程应用

发布时间：2018-06-04 17:14

本文选题：实验模态分析 + 工作模态分析　；参考：《太原理工大学》2013年博士论文

【摘要】：随着计算机技术、网络技术、通信技术等为代表的信息技术广泛应用于机械工程的各个领域,使得机电产品发生了重大变化。当然,这些变化也包括为产品的设计提供支撑的机械学科理论与应用技术的发展。近年来,上述研究取得了一系列重要成果,这些成果在机电产品的创新开发与设计中发挥重要作用。根据系统辨识与结构动力学的基本原理以及相应的试验技术发展起来的实验模态分析(EMA)与工作模态分析(OMA)技术取得长足的发展,从而帮助设计人员根据辨识模型更好地领悟对象机理,并将这些机理应用于产品设计,有力地促进产品的原创性开发与设计,并不断地扩大它的应用领域。近年来工作模态分析在机械系统与结构的动态分析与设计以及运行监测与故障诊断等方面获得广泛应用,在应用中也暴露出这些方法存在的问题与缺点,必须解决这些问题才能使这种方法得到有效的工业应用。本文研究适用于大型机械装备与结构的工作模态分析以及消除现有工作模态分析某些缺点的方法。研究的目的是：减少模态试验时间；允许最大限度地利用试验数据；减少分析的复杂性,可以较容易地处理数据；适用于大型机械结构模态试验存在的大量的传感器、大阻尼、带噪声数据、短的数据记录等情况；提高模态参数估计精度。为了达到上述目的,作者从模态试验与模态参数估计方法两方面入手解决工作模态分析的有关问题,取得了重要成果,并成功应用于大型工业装备。本文回顾了模态分析的基本理论与方法,包括实验模态分析(EMA)、工作模态分析(OMA)以及有外加输入的模态分析方法(OMAX)。在OMAX架构中讨论了确定性贡献的频响函数估计和随机贡献的正功率谱估计。在此基础上指出这些方法的局限与缺点,作为展开本文研究的背景。提出了一种基于循环倒谱的工作模态分析方法。该方法解除了输入信号为白噪声的假设,提高了模态参数的辨识精度。使用循环平稳信号的处理技术来分离响应中由于循环平稳输入信号引起的成分,非常有效地将多输入多输出(MIMO)系统降低为单输入多输出(SIMO)系统,在倒谱域进行曲线拟合,将输入和传递函数分离开,识别出系统的谐振和反谐振,进而得到系统的传递函数。通过钢梁试验对该方法进行验证,并与EMA分析结果进行比较。在这个试验中,精确估计了谐振频率和振型,并且通过增加平均次数来降低估计的不精确性。为了解决当输入激励不是白噪声时OMA过程中尺度丢失的问题,本文提出一种恢复模态振型之间的相对比例(尺度)和所有模态振型的全局比例(尺度)的简单方法,该方法建立在循环倒谱的基础之上。这种方法包括通过响应谱识别谐振与反谐振,并用以有限元模型。然后,通过有限元模型得到等效曲线,从而恢复频率响应函数的尺度。针对大型机械结构常常出现的由于工作或环境激励的频带较窄,致使工作模态过程中丢失模态以及计算速度慢等问题,提出准工作模态分析方法,即在大结构的部分区域结合使用可测量激励力(类似于实验模态分析)的外加局部辅助激励输入的工作模态分析方法,并提出了适合于准工作模态的基于参考的确定性随机子空间混合辨识算法,提高了模态辨识的精度和速度。为验证基于参考的确定性随机的准工作模态分析方法,将其应用于工业振动筛工作模态的综合分析,精确地辨识了振动筛的模态参数,得到很好的效果,证明了该方法的鲁棒性与可靠性。
[Abstract]:Information technology, such as computer technology, network technology, communication technology and so on, is widely used in various fields of mechanical engineering, making great changes in mechanical and electrical products. Of course, these changes also include the development of mechanical theory and application technology that support the design of products. In recent years, the above research has obtained a series of research. These achievements play an important role in the innovative development and design of mechanical and electrical products. According to the basic principles of system identification and structural dynamics and the development of experimental modality analysis (EMA) and work mode analysis (OMA) technology developed by the corresponding test technology, the development of the experimental mode analysis (OMA) technology is made to help the designers to be based on the identification model. It understands the mechanism of the object better, and applies these mechanisms to product design, promotes the original development and design of the product, and expands its application field.
In recent years, the work modal analysis has been widely used in the dynamic analysis and design of mechanical systems and structures as well as operation monitoring and fault diagnosis. The problems and shortcomings of these methods have been exposed in the application. These problems must be solved to make this method get effective industrial application. This paper is applied to large scale in this paper. Working mode analysis of mechanical equipment and structure and methods to eliminate some shortcomings of existing working mode analysis. The purpose of this study is to reduce modal test time, allow maximum use of test data, reduce the complexity of the analysis, and can easily handle data; suitable for large mechanical structural modal tests. In order to achieve the above purpose, the author solved the related problems of working modal analysis from two aspects of modal test and modal parameter estimation method to achieve the above purpose, and successfully applied it to large industrial equipment.
This paper reviews the basic theory and methods of modal analysis, including experimental modal analysis (EMA), working mode analysis (OMA) and modal analysis method (OMAX) with additional input. The estimation of the frequency response function of the deterministic contribution and the positive work rate spectrum estimation of the deterministic contribution are discussed in the OMAX framework. The limitations of these methods are pointed out on this basis. The shortcoming is the background of this study.
A working mode analysis method based on cyclic cepstrum is proposed. This method relieves the assumption that the input signal is white noise and improves the identification precision of the modal parameters. Using the processing technique of cyclostationary signal to separate the components caused by the cyclostationary input signal in the response, it is very effective to use the multi input and multi output (MIMO) system. The system is reduced to a single input and multiple output (SIMO) system, the curve fitting is carried out in the cepstrum domain, the input and transfer functions are separated, the resonance and anti resonance of the system are identified, and the transfer function of the system is obtained. The method is verified by the steel beam test and compared with the result of the EMA analysis. In this experiment, the resonant frequency is accurately estimated. Rate and mode of vibration, and increase the average number of times to reduce the estimation accuracy.
In order to solve the problem of scale loss in the OMA process when the input excitation is not white noise, a simple method is proposed to restore the relative proportion (scale) and the global proportionality (scale) of all modal modes. This method is based on the cyclic cepstrum. This method includes the recognition of resonance and the resonance of the response spectrum. Then, the equivalent curve is obtained through the finite element model, thus restoring the scale of the frequency response function.
In view of the narrow frequency band of the working or environmental excitation that often occurs in large mechanical structures, resulting in the loss of mode and the slow calculation speed in the working mode process, a quasi working mode analysis method is proposed, which combines the applied local auxiliary excitation of the measurable excitation force (similar to the experimental modal analysis) in the part of the large structure. The working mode analysis method of excitation input is proposed, and a reference based deterministic stochastic subspace identification algorithm is proposed for the quasi working mode, which improves the accuracy and speed of modal identification.
In order to verify the deterministic and random quasi working modal analysis method based on the reference, it is applied to the comprehensive analysis of the working mode of the industrial vibrating screen, and the modal parameters of the vibrating screen are identified accurately, and the good results are obtained, and the robustness and reliability of the method are proved.
【学位授予单位】：太原理工大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：TH113

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