Combining Cyclostationarity and the Frequency Domain Subspace Technique for Operational Modal Analysis

2007 ◽  
Vol 347 ◽  
pp. 473-478
Author(s):  
Jerome Antoni ◽  
David Hanson ◽  
Bob Randall

An underlying assumption of many operational modal analysis techniques is that the excitation is evenly distributed over the system, i.e. the inputs are spatially white, and is constant with frequency, i.e. frequentially white. This paper investigates the use of cyclostationarity, in combination with the Frequency Domain Subspace identification technique, to relax these constraints. Such a technique is suitable for application on systems which are excited by at least one cyclostationary input with a unique cyclic frequency, such as an internal combustion engine in a car or locomotive. The cyclostationary properties of this input are employed to reduce a multiple-inputmultiple- output system to a single-input-multiple-output system by extracting the component of each response measurement which is attributable to the cyclostationary input alone. The system modal properties; the resonances, damping and mode shapes, are then identified using the frequency domain subspace algorithm. The effectiveness of the technique is demonstrated through experiments on a laboratory test rig and a passenger train, and compared with results obtained using the knowledge of the inputs.

As natural frequencies and mode shapes are often a key to understanding dynamic characteristics of structural elements, modal analysis provides a viable means to determine these properties. This paper investigates the dynamic characteristics of a healthy and unhealthy condition of a commercially used helical gear using the Frequency Domain Decomposition (FDD) identification algorithm in Operational Modal Analysis (OMA). For the unhealthy condition, a refined range of percentage of defects are introduced to the helical gear starting from one (1) tooth being defected (1/60 teeth) to six (6) teeth being defected (6/60 teeth). The specimen is tested under a free-free boundary condition for its simplicity and direct investigation purpose. Comparison of the results of these varying conditions of the structure will be shown to justify the validity of the method used. Acceptable modal data are obtained by considering and accentuating on the technical aspects in processing the experimental data which are critical aspects to be addressed. The natural frequencies and mode shapes are obtained through automatic and manual peak-picking process from Singular Value Decomposition (SVD) plot using Frequency Domain Decomposition (FDD) technique and the results are validated using the established Modal Assurance Criterion (MAC) indicator. The results indicate that OMA using FDD algorithm is a good method in identifying the dynamic characteristics and hence, is effective in detection of defects in this rotating element


2007 ◽  
Vol 353-358 ◽  
pp. 1195-1198 ◽  
Author(s):  
Y.B. Chen ◽  
J.G. Han ◽  
D.Q. Yang

Structural operating conditions may significantly differ from those applied during laboratory tests where the structure is well known, well installed and properly excited. For structures under their natural loading conditions, or excited by random forces, excitations cannot be measured and are usually non stationary. Hence, an improvement operational modal analysis is a useful complement to the traditional modal analysis approach. The aim of this paper is to present the application of a new identification procedure, named wavelet-based identification technique of structural modal parameters. Wavelet-based identification that works in time-frequency domain is used to identify the dynamic characteristics of the structural system in terms of natural frequencies, damping coefficients and mode shapes. The paper has shown how the amplitude and the phase of the wavelet transform of operational vibration measurements are related to eigenfrequencies and damping coefficients, and the wavelet-based spectrum analysis is used to identify the mode shapes of the structure. Those modal parameters can be used to detect damage of structures. A simulation example has demonstrated that current identified results are comparable with those previously obtained from the peak pick method in frequency domain and stochastic subspace identification in time domain.


2018 ◽  
Vol 7 (4.27) ◽  
pp. 78
Author(s):  
M. Fadhil Shazmir ◽  
N. Ayuni Safari ◽  
M. Azhan Anuar ◽  
A. A.Mat Isa ◽  
Zamri A.R

Obtaining a good experimental modal data is essential in modal analysis in order to ensure accurate extraction of modal parameters. The parameters are compared with other extraction methods to ascertain its consistency and validity. This paper demonstrates the extraction of modal parameters using various identification algorithms in Operational Modal Analysis (OMA) on a 3D scaled model of a 3-storey aluminium structure. Algorithms such as Frequency Domain Decomposition (FDD), Enhanced Frequency Domain Decomposition (EFDD) and Stochastic Subspace Identification (SSI) are applied in this study to obtain modal parameters. The model test structure is fabricated of aluminium and assembled using bolts and nuts. Accelerometers were used to collect the responses and the commercial post processing software was used to obtain the modal parameters. The resulting natural frequencies and mode shapes using FDD method are then compared with other OMA parametric technique such as EFDD and SSI algorithm by comparing the natural frequencies and Modal Assurance Criterion (MAC). Comparison of these techniques will be shown to justify the validity of each technique used and hence confirming the accuracy of the measurement taken.    


2003 ◽  
Vol 36 (16) ◽  
pp. 1609-1614 ◽  
Author(s):  
Patrick Guillaume ◽  
Peter Verboven ◽  
Bart Cauberghe ◽  
Steve Vanlanduit ◽  
Eli Parloo ◽  
...  

2018 ◽  
Vol 10 (11) ◽  
pp. 168781401880869 ◽  
Author(s):  
Yu-Jia Hu ◽  
Wei-Gong Guo ◽  
Cheng Jiang ◽  
Yun-Lai Zhou ◽  
Weidong Zhu

Bayesian operational modal analysis and modal strain energy are employed for determining the damage and looseness of bolted joints in beam structures under ambient excitation. With this ambient modal identification technique, mode shapes of a damaged beam structure with loosened bolted connections are obtained based on Bayesian theory. Then, the corresponding modal strain energy can be calculated based on the mode shapes. The modal strain energy of the structure with loosened bolted connections is compared with the theoretical one without bolted joints to define a damage index. This approach uses vibration-based nondestructive testing of locations and looseness of bolted joints in beam structures with different boundary conditions by first obtaining modal parameters from ambient vibration data. The damage index is then used to identify locations and looseness of bolted joints in beam structures with single or multiple bolted joints. Furthermore, the comparison between damage indexes due to different looseness levels of bolted connections demonstrates a qualitatively proportional relationship.


Author(s):  
Lara Erviti Calvo ◽  
Gorka Agirre Castellanos ◽  
Germán Gimenez

The application of Operational Modal Analysis (OMA) in the railway sector opens a broad field of opportunities. The validation of the numerical model employed in the design phase is usually performed employing data obtained in static tests. The drawback is that some suspension parameters, such as dampers, only have an influence in the dynamic behavior and not in the static behavior. Because of that, the use of the mode shapes identified from track measurements in combination with the static tests leads to a more accurate validation of the numerical model. Apart from that, most passenger comfort and dynamic problems are associated to slightly damped modes. A correct identification of the modal parameters can be used as a continuous design improvement tool to improve the comfort and dynamic characteristics of future designs. Another valuable application of OMA techniques is the identification of the mode shapes corresponding to instabilities, due to the safety impact that they have. In railway vehicles, instabilities are associated to mode shapes that present a damping rate which decreases with the increase of the running speed. Above a certain speed value, the excitation coming from track cannot be damped by the vehicle and it reaches an unstable condition. This unstable condition leads to high acceleration levels experienced by the passengers and high interaction forces between the wheel and the rail that may lead to safety hazards. The speed above which the vehicle is unstable is known as critical speed, and has to be greater than the maximum speed of the vehicle with a reasonable safety margin. The use of OMA techniques allows identifying the mode shape that causes the instability. This paper presents the application of OMA techniques to measurements performed on a passenger vehicle, in which the speed was increased until the vehicle was unstable. The mode shape that caused the instability was identified as well as its corresponding natural frequency and damping rate.


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.


Energies ◽  
2016 ◽  
Vol 9 (11) ◽  
pp. 870 ◽  
Author(s):  
Carlo Ruzzo ◽  
Giuseppe Failla ◽  
Maurizio Collu ◽  
Vincenzo Nava ◽  
Vincenzo Fiamma ◽  
...  

Author(s):  
Bruna Nabuco ◽  
Sandro D. Amador ◽  
Evangelos I. Katsanos ◽  
Ulf T. Tygesen ◽  
Erik Damgaard Christensen ◽  
...  

Abstract Aiming to ensure the structural integrity of an offshore structure, wave-induced responses have been measured during normal operating conditions. Operational Modal Analysis is applied to the data obtained from continuously monitoring the structure. Sensors placed only on the topside of an offshore platform are sufficient to provide information to identify the modal properties of the structure, such as natural frequencies, damping ratios, and mode shapes. A finite element model is created and updated in line with the identified dynamic properties for applying a modal expansion technique in the interest of accessing information at any point of the structure. Wave radars are also placed at the platform from which the wave forces are calculated based on basic industrial standard models. In this way, the wave kinematics are estimated according to the linear wave theory associated with Wheeler stretching. Since this study is related to offshore structures composed by slender elements, the wave forces are estimated using Morison formulation. By assigning typical values to the drag and inertia coefficients, wave loads are estimated and applied to the updated finite element model. For the diffraction effect, the wave load has also been evaluated according to MacCamy and Fuchs theory. The responses obtained from this procedure are compared with measured responses. In addition to describing the process, this paper presents a case study to verify the theory using monitoring data from a tripod jacket. Results indicate realistic response estimation that contributes to the knowledge about the state of the structure.


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