采用频域多参考点模态识别法进行工作状态下的模态识别

针对工程实际情况 ,从实测响应间的互相关函数入手 ,推导出适用于工作状态下的频域多参考点模态识别法 ,然后采用一飞机模型对该方法进行了试验验证。

用实验模态分析法识别汽车悬挂系统振动参数

汽车悬挂系统振动参数是汽车结构动态特性的重要参数。精确测量这些参数对预估或改善汽车动力学特性是十分重要的。用实验模态分析法识别这些参数是比较精确的。

电机整机结构振动模态试验与参数识别研究

为提高电机运行的稳定性,降低振动噪声对其使用性能和寿命的影响,利用随机子空间模态识别方法对某型号电动机整机进行了模态分析。详细阐述了随机子空间模态识别法的数学原理,采用锤击法完成电机整机的模态测试,进一步识别出电机的四阶模态参数,固有频率、阻尼比及振型,根据分析结果找出电机的风扇罩和定子外壳中间位置为结构的薄弱环节,进而提出了相应的改进设计方法与减振措施。分析结果表明随机子空间法可用于电机整机结构的模态参数识别,分析结果为电机的结构动力修改与优化设计提供了参考数据。

考虑边界弹性约束刚度的拉索参数识别

提出了由拉索实测振动频率同时识别出拉索索力和抗弯刚度的模态参数识别法。首先,在考虑边界弹性约束刚度基础上研究了拉索索力、抗弯刚度和频率之间的关系。然后,根据振动模态特点,得到索的等效长度。进而以拉索索力和抗弯刚度为模态参数,采用最小二乘法对模态参数进行识别,保证理论模型和实测模型之间的总误差最小。最后,通过算例进行验证,表明使用模态参数识别法能够精确的识别出索力和抗弯刚度。

结构模态参数识别的随机子空间法

随机子空间法(SSI)是时域识别的模态参数识别法,该法根据加权方法的不同可以有3种算法．通过 处理实桥动载实测数据,研究了这3种算法识别真实结构模态参数的问题．

用几何最小二乘法改进 ITD 法的阻尼识别精度

ＩＴＤ（ＩｂｒａｈｉｍＴｉｍｅＤｏｍａｉｎ）模态识别方法可不用输入系统的信息就识别系统的模态参数，但识别的模态参数常常很不精确，且阻尼比的识别精度很差。当激励信号不是独立白噪声信号时，不应该采用ＩＴＤ法进行模态识别。推导了ＩＴＤ法识别的模态频率和阻尼比的相对误差公式，由此分析了造成阻尼比识别结果很差的原因，并且引入了Ｉ－ｂｒａｈｉｍ提出的双最小二乘算法（ＤＬＳ），在此基础上，提出了几何最小二乘法（ＧＬＳ）。通过理论推导和算例验证得到：一般情况下，ＧＬＳ和ＤＬＳ算法均可提高阻尼比的识别精度，且前者的识别结果优于后者。

Application of extension neural network to safety status pattern recognition of coalmines

In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of network,the rationale of recognition algorithm and the performance of proposed method were discussed in detail.The safety status pattern recognition problem of coalmines can be regard as a classification problem whose features are defined in a range,so using the ENN is most appropriate for this problem.The ENN-based recognition method can use a novel extension distance to measure the similarity between the object to be recognized and the class centers.To demonstrate the effectiveness of the proposed method,a real-world application on the geological safety status pattern recognition of coalmines was tested.Comparative experiments with existing method and other traditional ANN-based methods were conducted.The experimental results show that the proposed ENN-based recognition method can identify the safety status pattern of coalmines accurately with shorter learning time and simpler structure.The experimental results also confirm that the proposed method has a better performance in recognition accuracy,generalization ability and fault-tolerant ability,which are very useful in recognizing the safety status pattern in the process of coal production.

Squaring the Dialectic of Inference and Chance

Instead of merely inferring that our beliefs are in a correlation to the facts, I will contend that what matters is the logic of their inferential structure. This will reveal what is actually true for their relation and not just real for experience. Given one and two-sided inferences, the conditions of their functional relation will be consistent within a square of opposition; for contraries, contradictions and sub-contraries in a way that probability theory is not. Within this model of inferences, the two-sided concept of inferences will also have a modal value for its relation to the one-sided concept of inferences. Proposing that empirical, formal, speculative, and an Intuitionist Speculative understanding of logic will have a modal identity within a dialectical principle.

减速器箱体模态分析与试验验证

建立了减速器箱体有限元模型,提取了箱体低阶固有频率及相应振型。根据试验模态理论,对减速器箱体进行了脉冲锤击法模态试验,采用多输入多输出(MIMO)时域模态方法对减速器箱体进行模态分析,通过对采集数据分析处理,求得传递函数;采用ERA模态识别法,确定减速器箱体低阶固有频率及振型。通过对比数据表明,所选低阶固有频率振型基本一致,频率误差在5%范围内,相互证明了理论模型与试验方法的正确性,为研究箱体动态结构特性分析提供了理论依据和试验支撑。

Operational Modal Analysis of a Ship Model in the Presence of Harmonic Excitation

A ship is operated under an extremely complex environment, and waves and winds are assumed to be the stochastic excitations. Moreover, the propeller, host and mechanical equipment can also induce the harmonic responses. In order to reduce structural vibration, it is important to obtain the modal parameters information of a ship. However, the traditional modal parameter identification methods are not suitable since the excitation information is difficult to obtain. Natural excitation technique-eigensystem realization algorithm （NExT-ERA） is an operational modal identification method which abstracts modal parameters only from the response signals, and it is based on the assumption that the input to the structure is pure white noise. Hence, it is necessary to study the influence of harmonic excitations while applying the NExT-ERA method to a ship structure. The results of this research paper indicate the practical experiences under ambient excitation, ship model experiments were successfully done in the modal parameters identification only when the harmonic frequencies were not too close to the modal frequencies.

Damage identification method of girder bridges based on finite element model updating and modal strain energy

A timely and accurate damage identification for bridge structures is essential to prevent sudden failures/collapses and other catastrophic accidents.Based on response surface model(RSM)updating and element modal strain energy(EMSE)damage index,this paper proposes a novel damage identification method for girder bridge structures.The effectiveness of the proposed damage identification method is investigated using experiments on four simply supported steel beams.With Xiabaishi Bridge,a prestressed continuous rigid frame bridge with large span,as the engineering background,the proposed damage identification method is validated by using numerical simulation to generate different bearing damage scenarios.Finally,the efficiency of the method is justified by considering its application to identifying cracking damage for a real continuous beam bridge called Xinyihe Bridge.It is concluded that the EMSE damage index is sensitive to the cracking damage and the bearing damage.The locations and levels of multiple cracking damages and bearing damages can be also identified.The results illuminate a great potential of the proposed method in identifying damages of real bridge structures.

Fuzzy finite element model updating of bridges by considering the uncertainty of the measured modal parameters

It is significant to consider the effect of uncertainty of the measured modal parameters on the updated finite element(FE) model,especially for updating the FE model of practical bridges,since the uncertainty of the measured modal parameters cannot be ignored owing to the application of output-only identification method and the existence of the measured noise.A reasonable method is to define the objective of the FE model updating as the statistical property of the measured modal parameters obtained by conducting couples of identical modal tests,however,it is usually impossible to implement repeated modal test due to the limit of practical situation and economic reason.In this study,a method based on fuzzy finite element(FFM) was proposed in order to consider the effect of the uncertainty of the measured modal parameters on the updated FE model by using the results of a single modal test.The updating parameters of bridges were deemed as fuzzy variables,and then the fuzzification of objective of the FE model updating was proposed to consider the uncertainty of the measured modal parameters.Finally,the effectiveness of the proposed method was verified by updating the FE model of a practical bridge with the measured modal parameters.

Improved polyreference time domain method for modal identification using local or global noise removal techniques

Modal identification involves estimating the modal parameters, such as modal frequencies, damping ratios, and mode shapes, of a structural system from measured data. Under the condition that noisy impulse response signals associated with multiple input and output locations have been measured, the primary objective of this study is to apply the local or global noise removal technique for improving the modal identification based on the polyreference time domain (PTD) method. While the traditional PTD method improves modal parameter estimation by over-specifying the computational model order to absorb noise, this paper proposes an approach using the actual system order as the computational model order and rejecting much noise prior to performing modal parameter estimation algorithms. Two noise removal approaches are investigated: a "local" approach which removes noise from one signal at a time, and a "global" approach which removes the noise of multiple measured signals simultaneously. The numerical investigation in this article is based on experimental measurements from two test setups: a cantilever beam with 3 inputs and 10 outputs, and a hanged plate with 4 inputs and 32 outputs. This paper demonstrates that the proposed noise-rejection method outperforms the traditional noise-absorption PTD method in several crucial aspects.