scholarly journals Variable Modal Parameter Identification for Non-Linear Mdof Systems. Part I: Formulation and Numerical Validation

2000 ◽  
Vol 7 (4) ◽  
pp. 217-227 ◽  
Author(s):  
Y.H. Chong ◽  
M. Imregun

This paper deals with the formulation of a frequency domain modal analysis technique that is applicable to weakly non-linear multi-degree of freedom (MDOF) systems with well-separated modes. The concept of linear modal superposition is combined with the normal non-linear mode technique, an approach that allows the formulation of a system identification procedure in terms of variable modal parameters. The numerical study was focused on a 4-DOF system with cubic stiffness non-linearity, and the modal parameters were obtained as functions of the modal amplitude. It was shown that the methodology was well suited to the study of practical cases for which the underlying linear model may be approximate. Similarly, the technique was found to be robust in the presence of measurement noise, though some adverse effects were observed for high noise levels. Once the variable modal parameters were extracted at some given force level, the non-linear responses were predicted at other force levels via synthesis of normal non-linear modes. The same responses were also obtained using a harmonic balance approach and very good agreement was obtained between the two sets of results. The procedure is well suited to the study of industrial cases because of its compatibility with existing finite element methods and linear modal analysis techniques.

2000 ◽  
Vol 7 (4) ◽  
pp. 229-240 ◽  
Author(s):  
Y.H. Chong ◽  
M. Imregun

The purpose of Part II is to provide an experimental validation of the methodology presented in Part I and to consider a representative engineering case, the study of which requires a relatively large numerical model. A beam system with cubic stiffness type non-linearity was used in the experimental study. The non-linear response was measured at three locations and the underlying linear system was obtained via linear modal analysis of low-excitation response data. The non-linear parameter variations were obtained as a function of the modal amplitude and the response of the system was generated for other force levels. The results were found to agree very well with the corresponding measurements, indicating the success of the non-linear modal analysis methodology, even in the presence of true experimental noise. An advanced numerical case study that included both inherent structural damping and non-linear friction damping, was considered next. The linear finite element model of a high-pressure turbine blade was used in conjunction with three local non-linear friction damper elements. It was shown that the response of the system could be predicted at any force level, provided that that non-linear modal parameters were available at some reference force level. The predicted response levels were compared against those obtained from reference simulations and very good agreement was achieved in all cases.


Author(s):  
Wenlong Yang ◽  
Lei Li ◽  
Qiang Fu ◽  
Yao Teng ◽  
Shuqing Wang ◽  
...  

Experimental modal analysis (EMA) is widely implemented to obtain the modal parameters of an offshore platform, which is crucial to many practical engineering issues, such as vibration control, finite element model updating and structural health monitoring. Traditionally, modal parameters are identified from the information of both the input excitation and output response. However, as the size of offshore platforms becomes huger, imposing artificial excitation is usually time-consuming, expensive, sophisticated and even impossible. To address this problem, a preferred solution is operational modal analysis (OMA), which means the modal testing and analysis for a structure is in its operational condition subjected to natural excitation with output-only measurements. This paper investigate the applicability of utilizing response from natural ice loading for operational modal analysis of real offshore platforms. The test platform is the JZ20-2MUQ Jacket platform located in the Bohai Bay, China. A field experiment is carried out in winter season, when the platform is excited by floating ices. An accelerometer is installed on a leg and two segments of acceleration response are employed for identifying the modal parameters. In the modal parameter identification, specifically applied is the data-driven stochastic sub-space identification (SSI-data) method. It is one of the most advanced methods based on the first-order stochastic model and the QR algorithm for computing the structural eigenvalues. To distinguish the structural modal information, stability diagrams are constructed by identifying parametric models of increasing order. Observing the stability diagrams, the modal frequencies and damping ratios of four structural modes can be successfully identified from both segments. The estimated information from both segments are almost identical, which demonstrates the identification is trustworthy. Besides, the stability diagrams from SSI-data method are very clean, and the poles associated with structural modes can become stabilized at very low model order. The research in this paper is meaningful for the platforms serving in cold regions, where the ices could be widespread. Utilizing the response from natural ice loading for modal parameter identification would be efficient and cost-effective.


2013 ◽  
Vol 744 ◽  
pp. 137-142
Author(s):  
Li Zhang ◽  
Su Bin ◽  
Feng Tao ◽  
Ye Tian ◽  
Jiang Yue Peng

In this paper, the free modal of the industrial flat sewing machine was researched, and the experimental measurement system is established. A modal analysis of industrial flat sewing machine is carried out through the method of single point exciting vibration and multipoint collecting signal. The PolyMax modal parameter identification method is applied to the modal analysis for frequency response function to get steady state diagram and then determine the modal parameters and modal shapes. According to Modal Assurance Criterion (MAC), the credibility of the calculation results is verified, and then modal parameters of industrial flat sewing machine get more reliable in order to provide the reference for further structure optimization and noise reduction of the flat sewing machine.


2021 ◽  
Vol 11 (23) ◽  
pp. 11432
Author(s):  
Xiangying Guo ◽  
Changkun Li ◽  
Zhong Luo ◽  
Dongxing Cao

A method of modal parameter identification of structures using reconstructed displacements was proposed in the present research. The proposed method was developed based on the stochastic subspace identification (SSI) approach and used reconstructed displacements of measured accelerations as inputs. These reconstructed displacements suppressed the high-frequency component of measured acceleration data. Therefore, in comparison to the acceleration-based modal analysis, the operational modal analysis obtained more reliable and stable identification parameters from displacements regardless of the model order. However, due to the difficulty of displacement measurement, different types of noise interferences occurred when an acceleration sensor was used, causing a trend term drift error in the integral displacement. A moving average low-frequency attenuation frequency-domain integral was used to reconstruct displacements, and the moving time window was used in combination with the SSI method to identify the structural modal parameters. First, measured accelerations were used to estimate displacements. Due to the interference of noise and the influence of initial conditions, the integral displacement inevitably had a drift term. The moving average method was then used in combination with a filter to effectively eliminate the random fluctuation interference in measurement data and reduce the influence of random errors. Real displacement results of a structure were obtained through multiple smoothing, filtering, and integration. Finally, using reconstructed displacements as inputs, the improved SSI method was employed to identify the modal parameters of the structure.


2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Tianxu Zhu ◽  
Chaoping Zang ◽  
Gengbei Zhang

The measured frequency response functions (FRFs) in the modal test are usually contaminated with noise that significantly affects the modal parameter identification. In this paper, a modal peak-based Hankel-SVD (MPHSVD) method is proposed to eliminate the noise contaminated in the measured FRFs in order to improve the accuracy of the identification of modal parameters. This method is divided into four steps. Firstly, the measured FRF signal is transferred to the impulse response function (IRF), and the Hankel-SVD method that works better in the time domain rather than in the frequency domain is further applied for the decomposition of component signals. Secondly, the iteration of the component signal accumulation is conducted to select the component signals that cover the concerned modal features, but some component signals of the residue noise may also be selected. Thirdly, another iteration considering the narrow frequency bands near the modal peak frequencies is conducted to further eliminate the residue noise and get the noise-reduced FRF signal. Finally, the modal identification method is conducted on the noise-reduced FRF to extract the modal parameters. A simulation of the FRF of a flat plate artificially contaminated with the random Gaussian noise and the random harmonic noise is implemented to verify the proposed method. Afterwards, a modal test of a flat plate under the high-temperature condition was undertaken using scanning laser Doppler vibrometry (SLDV). The noise reduction and modal parameter identification were exploited to the measured FRFs. Results show that the reconstructed FRFs retained all of the modal features we concerned about after the noise elimination, and the modal parameters are precisely identified. It demonstrates the superiority and effectiveness of the approach.


2019 ◽  
Vol 11 (2) ◽  
pp. 324-337
Author(s):  
Sk Abdul Kaium ◽  
Sayed Abul Hossain ◽  
Jafar Sadak Ali

Purpose The purpose of this paper is to highlight that the need for improved system identification methods within the domain of modal analysis increases under the impulse of the broadening field of applications, e.g., damage detection and vibro-acoustics, and the increased complexity of today’s structures. Although significant research efforts during the last two decades have resulted in an extensive number of parametric identification algorithms, most of them are certainly not directly applicable for modal parameter extraction. So, based on this, the aim of the present work is to develop a technique for modal parameter extraction from the measured signal. Design/methodology/approach A survey and classification of the different modal analysis methods are made; however, the focus of this thesis is placed on modal parameter extraction from measured time signal. Some of the methods are examined in detail, including both single-degree-of-freedom and multi-degree-of-freedom approaches using single and global frequency-response analysis concepts. The theory behind each of these various analysis methods is presented in depth, together with the development of computer programs, theoretical and experimental examples and discussion, in order to evaluate the capabilities of those methods. The problem of identifying properties of structures that possess close modes is treated in particular detail, as this is a difficult situation to handle and yet a very common one in many structures. It is essential to obtain a good model for the behavior of the structure in order to pursue various applications of experimental modal analysis (EMA), namely: updating of finite element models, structural modification, subsystem-coupling and calculation of real modes from complex modes, to name a few. This last topic is particularly important for the validation of finite element models, and for this reason, a number of different methods to calculate real modes from complex modes are presented and discussed in this paper. Findings In this paper, Modal parameters like mode shapes and natural frequencies are extracted using an FFT analyzer and with the help of ARTeMiS, and subsequently, an algorithm has been developed based on frequency domain decomposition (FDD) technique to check the accuracy of the results as obtained from ARTeMiS. It is observed that the frequency domain-based algorithm shows good agreement with the extracted results. Hence the following conclusion may be drawn: among several frequency domain-based algorithms for modal parameter extraction, the FDD technique is more reliable and it shows a very good agreement with the experimental results. Research limitations/implications In the case of extraction techniques using measured data in the frequency domain, it is reported that the model using derivatives of modal parameters performed better in many situations. Lack of accurate and repeatable dynamic response measurements on complex structures in a real-life situation is a challenging problem to analyze exact modal parameters. Practical implications During the last two decades, there has been a growing interest in the domain of modal analysis. Evolved from a simple technique for troubleshooting, modal analysis has become an established technique to analyze the dynamical behavior of complex mechanical structures. Important examples are found in the automotive (cars, trucks, motorcycles), railway, maritime, aerospace (aircrafts, satellites, space shuttle), civil (bridges, buildings, offshore platforms) and heavy equipment industry. Social implications Presently structural health monitoring has become a significantly important issue in the area of structural engineering particularly in the context of safety and future usefulness of a structure. A lot of research is being carried out in this area incorporating the modern sophisticated instrumentations and efficient numerical techniques. The dynamic approach is mostly employed to detect structural damage, due to its inherent advantage of having global and location-independent responses. EMA has been attempted by many researchers in a controlled laboratory environment. However, measuring input excitation force(s) seems to be very expensive and difficult for the health assessment of an existing real-life structure. So Ambient Vibration Analysis is a good alternative to overcome those difficulties associated with the measurement of input excitation force. Originality/value Three single bay two storey frame structure has been chosen for the experiment. The frame has been divided into six small elements. An algorithm has been developed to determine the natural frequency of those frame structures of which one is undamaged and the rest two damages in single element and double element, respectively. The experimental results from ARTeMIS and from developed algorithm have been compared to verify the effectiveness of the developed algorithm. Modal parameters like mode shapes and natural frequencies are extracted using an FFT analyzer and with the help of ARTeMiS, and subsequently, an algorithm has been programmed in MATLAB based on the FDD technique to check the accuracy of the results as obtained from ARTeMiS. Using singular value decomposition, the power Spectral density function matrix is decomposed using the MATLAB program. It is observed that the frequency domain-based algorithm shows good consistency with the extracted results.


2011 ◽  
Vol 50-51 ◽  
pp. 828-832
Author(s):  
Xing Xian Bao ◽  
Cui Lin Li

Measured vibration response signals are inevitably contaminated with noise when a data acquisition system is used for an experimental measurement. This situation often leads to serious difficulties in identifying the modal parameters with proper accuracy. This paper presents a noise cancellation method for measured impulsive response functions (IRFs) based on structured low rank approximation (SLRA) so as to improve the accuracy of the modal parameters identification. Numerical study of a cantilever beam model is carried out to demonstrate the performance of the proposed method. The results show that this method can remove noise from measured IRFs efficiently, and the modal parameter identifications based on the filtered IRFs are very good.


2013 ◽  
Vol 819 ◽  
pp. 38-42
Author(s):  
Jin Bao Ma ◽  
Jian Yu Zhang ◽  
Xin Bo Liu

With the evolution and degradation of mechanical fault, changes of the structural inherent characteristics will directly affect the overall response of system. Spur gear, which worked as the research object, is to be explored on the changes of modal parameters under different damage state. Optimum driving-point mobility and modal parameter identification is achieved by comprehensive utilization of experimental modal analysis and finite element analysis. is used to determine the experiment results is whether accurate or not. Then comparing with the differences of modal parameters, the preliminary judgment of gear damage can be made. According to the experimental data of different gears, theis taken to complete the correlation analysis and to judge the degree of the damage. The results shows that provide an effective basis for the identification of vibration mechanism and vibration characteristic of fault gear.


2014 ◽  
Vol 1065-1069 ◽  
pp. 3400-3405
Author(s):  
Qian Zhang ◽  
Zhi Cheng Lu ◽  
Yu Han Sun ◽  
Min Zhong

In this paper the feasibility of natural excitation method which uses cross-correlation function instead of impulse response function of the response to identify the modal parameter of 500kV SF6 current transformer was discussed .Four different algorithms were used to extract the modal parameter of 500kV SF6 current transformer with the measured cross-correlation function obtained by natural excitation method. The results of modal parameter identification using natural excitation method and experimental modal analysis were compared in the experimental way.


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