Non-overlapped random decrement technique for parameter identification in operational modal analysis

2016 ◽  
Vol 366 ◽  
pp. 528-543 ◽  
Author(s):  
Y. Zhang ◽  
H.W. Song
Keyword(s):  
Parameter Identification ◽  
Modal Analysis ◽  
Operational Modal Analysis ◽  
Random Decrement Technique ◽  
Random Decrement

A random decrement technique for operational modal analysis in the presence of periodic excitations

2009 ◽  
Vol 223 (7) ◽  
pp. 1525-1534 ◽  
Author(s):  
M Asayesh ◽  
B Khodabandeloo ◽  
A Siami
Keyword(s):  
White Noise ◽  
Modal Analysis ◽  
Degrees Of Freedom ◽  
Domain Decomposition Method ◽  
Gaussian White Noise ◽  
Operational Modal Analysis ◽  
Modal Parameters ◽  
Periodic Excitation ◽  
Random Decrement Technique ◽  
Random Decrement

Operational modal analysis (OMA) is a procedure that allows the identification of the modal parameters of a structure using measured responses to unknown excitation. OMA techniques are based on the assumption that the input to the structure is stationary white noise. One of the OMA techniques, which is based on the assumption of a zero mean Gaussian white noise excitation, is the random decrement (RD) technique. In many practical cases, however, periodic excitation is often present in addition to the white noise. In this study, a method based on the concept of RD transformation is proposed to extract the response of a structure to the random input from the measured response that is due to both random and periodic excitations. Applying the RD method to the extracted random response, RD signatures were estimated. Modal parameters were estimated from RD signatures using the Ibrahim time domain algorithm. It is assumed that the period of the periodic excitation is known a priori. To verify the applicability of the method, a numerical simulation of a discrete two-degrees-of-freedom (DOF) dynamic system with a viscous damping is carried out. The results of this method were also compared with the results obtained from the enhanced frequency domain decomposition method. The efficiency of the proposed method, in the cases where the frequencies of harmonic components of periodic excitation are located at the natural frequencies of the system, is also evaluated.

scholarly journals Non-Invasive Parameter Identification in Rotordynamics via Fluid Film Bearings: Linking Active Lubrication and Operational Modal Analysis

2016 ◽  
Author(s):  
Ilmar Ferreira Santos ◽  
Peter Kjær Svendsen
Keyword(s):  
Parameter Identification ◽  
Modal Analysis ◽  
Natural Frequencies ◽  
Transfer Functions ◽  
Injection Pressure ◽  
Operational Modal Analysis ◽  
Fluid Film ◽  
Non Invasive ◽  
Fluid Film Bearings

In recent years, theoretical and experimental efforts have transformed the conventional tilting-pad journal bearing (TPJB) into a smart mechatronic machine element. The application of electromechanical elements into rotating systems makes feasible the generation of controllable forces over the rotor as a function of a suitable control signal. The servovalve input signal and the radial injection pressure are the two main parameters responsible for dynamically modifying the journal oil film pressure and generating active fluid film forces in controllable fluid film bearings. Such fluid film forces, resulting from a strong coupling between hydrodynamic, hydrostatic and controllable lubrication regimes, can be used either to control or to excite rotor lateral vibrations. If non-invasive forces are generated via lubricant fluid film, in situ parameter identification can be carried out, enabling evaluation of the mechanical condition of the rotating machine. Using the lubricant fluid film as a non-invasive calibrated shaker is troublesome, once several transfer functions among mechanical, hydraulic and electronic components become necessary. In this framework the main original contribution of this paper is to show experimentally that the knowledge about the several transfer functions can be bypassed by using output-only identification techniques. The manuscript links controllable (active) lubrication techniques with operational modal analysis, allowing for in-situ parameter identification in rotordynamics, i.e. estimation of damping ratio and natural frequencies. The experimental analysis is carried out on a rigid rotor-level system supported by one single pair of pads. The estimation of damping and natural frequencies is performed using classical experimental modal analysis (EMA) and operational modal analysis (OMA). Very good agreements between the two experimental approaches are found. Maximum values of the main input parameters, namely servovalve voltage and radial injection pressure, are experimentally found with the objective of defining ranges of non-invasive perturbation forces.

Reliability of Extracted Modal Parameters by Random Decrement of Acceleration Signatures

2009 ◽  
Author(s):  
Babak Khodabandelou ◽  
Kaveh Abasi ◽  
Masud Asayesh
Keyword(s):  
Numerical Simulation ◽  
Free Vibration ◽  
Modal Analysis ◽  
Correlation Functions ◽  
Vibration Response ◽  
Modal Parameters ◽  
Random Decrement Technique ◽  
Random Decrement ◽  
Free Decay ◽  
Free Vibration Response

Modal parameters provide important information on dynamic properties of structures. In operating condition, since it is difficult to measure input loadings, methods should be applied where don’t require measuring inputs. Such methods which identify modal parameters of structures by measuring their responses are called Operational- or Output Only- Modal Analysis (OMA) techniques. There are many time and frequency domain operational modal analysis techniques. Generally a form of impulse or free vibration response is required to use most of these techniques. However, in practice structures are usually subjected to some immeasurable or unknown random inputs. In these situations Random Decrement (RD) transformation can reduce these responses to equivalent free decay or correlation functions. Therefore, RD technique coupled with those methods, which require a form of impulse or free vibration response offer a valuable tool for identifying the dynamic characteristics of structures from operational or ambient responses. Unfortunately, in the literature there are some constrains on using random decrement signatures. For example by complicated mathematical relations it is shown that random decrement technique is applicable only if the inputs are uncorrelated zero mean Gaussian white noises. In addition, it is proved that only random decrement of displacement and velocity is equivalent to the corresponding free decay responses or correlation functions the random decrement of acceleration response is never equivalent to the corresponding free decay responses or correlation functions. However, there are many papers which have used random decrement of acceleration responses and extracted modal parameters accurately! In this paper it is tried to show simply and clearly whether it is possible to obtain modal parameters from random decrement acceleration signatures or not. To do that, a numerical simulation of a discrete dynamic system with viscous damping is carried out and the results of numerical methods are compared with those come from analytical solution. Numerical simulation is used since it is completely controllable. Finally, it is tried to identify power and the Applicability cases of random decrement method.

Identify Modal Parameters of a Real Offshore Platform From the Response Excited by Natural Ice Loading

2016 ◽  
Author(s):  
Wenlong Yang ◽  
Lei Li ◽  
Qiang Fu ◽  
Yao Teng ◽  
Shuqing Wang ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Modal Analysis ◽  
Offshore Platform ◽  
Operational Modal Analysis ◽  
Modal Parameters ◽  
Offshore Platforms ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Stability Diagrams ◽  
The Stability

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.

Preliminary Simulation Study Combining Operational Modal Analysis and a Two Step Parameter Identification Method on 6-SPS Parallel Manipulator for Machining Purposes

2018 ◽  
Author(s):  
Kasper Ringgaard ◽  
Ole Balling
Keyword(s):  
Dynamic Response ◽  
Parameter Identification ◽  
Modal Analysis ◽  
Dynamic Models ◽  
Operational Modal Analysis ◽  
Machining Process ◽  
Mode Shapes ◽  
Attractive Alternative ◽  
Parallel Kinematic ◽  
Six Degree Of Freedom

Machining of large components, such as multi-megawatt wind turbine parts, is currently done using large expensive CNC machines. Using small parallel kinematic machines can provide an economical attractive alternative. Optimization of the conditions for a stable and accurate machining process is necessary. Knowledge of position dependent dynamic response is key when performing such optimization. This contribution is a part of current research striving towards efficient parameter identification for dynamic models of 6-SPS parallel kinematic manipulators for machining purposes. Stiffness and damping are updated for a small set of manipulator poses using Operational Modal Analysis and a two step parameter identification routine. The model obtained contains information of the dynamic response for all poses in the workspace. In this study a six degree of freedom 6-SPS model is derived and operational modal analysis experiments are simulated. The obtained modal parameters are used for parameter identification. It is concluded that the operational modal analysis performs well in estimating frequencies and mode shapes of the symmetric structure, but damping estimates are poor. Parameter identification routine performance is satisfactory, but the poor damping estimates from modal analysis causes incorrect and uncertain parameter identification.

Consistent Multilevel RDT-ERA for Output-Only Ambient Modal Identification of Structures

2017 ◽  
Vol 17 (09) ◽  
pp. 1750106 ◽  
Author(s):  
Zhouquan Feng ◽  
Wenai Shen ◽  
Zhengqing Chen
Keyword(s):  
Parameter Identification ◽  
Modal Identification ◽  
Ambient Vibration ◽  
Weighted Averaging ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Consistency Analysis ◽  
Modal Parameter Identification ◽  
Random Decrement Technique ◽  
Random Decrement

This paper presents an improved method called the consistent multilevel random decrement technique in conjunction with eigensystem realization algorithm (RDT-ERA) for modal parameter identification of linear dynamic systems using the ambient vibration data. The conventional RDT-ERA is briefly revisited first and the problem of triggering level selection in the RDT is thoroughly studied. Due to the use of a single triggering level by the conventional RDT-ERA, an inappropriate triggering level may produce poor random decrement (RD) functions, thereby yielding a poor estimate of modal parameters. In the proposed consistent multilevel RDT-ERA, multiple triggering levels are used and a consistency analysis is proposed to sift out the RD functions that deviate largely from the majority of the RD functions. Then the ERA is applied to the retained RD functions for modal parameter identification. Subsequently, a similar consistency analysis is conducted on the identified modal parameters to sift out the outliers. Finally, the final estimates of the modal parameters are calculated using weighted averaging with the weights set proportional to the number of RD segments extracted from the corresponding triggering levels. The proposed method is featured by the fact that the information from the signal is fully utilized using multiple triggering levels and the outliers are sifted out using consistency analysis, thus making the identified result more accurate and reliable. The effectiveness and accuracy of the method have been demonstrated in the examples using the simulated data and experimental data.

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