OPERATIONAL MODAL ANALYSIS can be used as a useful method for MODAL identification of rotating machinery. Response of a rotary machine contains several powerful harmonic components which make the OMA methods face several problems. In this paper, kurtosis index is used for detection of response harmonic components. Then, CFDD method is modified for removing the harmonic effects and extracting the MODAL parameters. Accuracy, applicability and computational efficiency of the proposed method are evaluated through computer simulation of a 4DOF system, an OPERATIONAL MODAL ANALYSIS experiment on a steel beam, and OPERATIONAL MODAL ANALYSIS of a large industrial fan in Mobarakeh Steel Complex.

The closely spaced modes exist in symmetric structures such as circular plates, gears or disks. Theoretically, closely spaced modes are known as two separated modes with the same amount, but these modes are often detected as only one mode in the classical MODAL methods. In this article, at the first, some classical MODAL method is introduced and the most important of their difficulties is considered. Then, OPERATIONAL MODAL ANALYSIS (OMA) is applied to abate these problems. The Stochastic Subspace Identification based on covariance (SST-COV) driven is used for this purpose. Different conditions for closely spaced modes is considered and simulated on a free-free steel plate using Matlab software. Tn order to consider the SSI-COV method in identification of closely spaced modes experimentally, classical and OPERATIONAL MODAL testing are done on a steel ring. The numerical and experimental results from simulations demonstrate the effectiveness of OMA for identifying and separating the close modes.

Estimating a structure's MODAL parameters is essential for various applications, including health monitoring, damage detection, design verification, and model updating. MODAL parameters are a structure's natural frequencies, mode shapes, and damping ratios. They can be used to understand the structure's dynamic behavior and to identify any changes that may occur over time. OPERATIONAL MODAL ANALYSIS (OMA) is a technique that uses the response of a structure to environmental loads to estimate MODAL parameters. OMA is a non-destructive testing method that can be used on structures in their operating environment. This makes it a valuable tool for health monitoring and damage detection of buildings, bridges, wind turbines, and stadiums. One of the challenges of OMA is that its methods rely on the user's judgment to separate physical modes from spurious modes and to distinguish between real modes of the structure. Spurious modes are not caused by the actual structure but by noise or other environmental factors. Real modes are caused by the structure itself. In recent years, there has been extensive research on automating OMA methods for MODAL parameter estimation. Most of these studies have attempted to minimize the need for user intervention in MODAL parameter calculation by using machine learning techniques. Machine learning techniques can be used to identify physical modes automatically and to distinguish between real modes of the structure. This research uses the Stochastic Subspace Identification (SSI) method for OMA. The DBSCAN clustering method is used to separate physical modes from spurious modes. Finally, the hierarchical clustering method is used to distinguish between real modes of the structure. The proposed algorithm was implemented on a 6-degree-of-freedom structure and a real bridge. The results show that the proposed method has a higher power to separate physical modes from spurious modes than previous methods.

Introduction An important process in grain harvesting with the combine harvester is threshing the materials using the thresher unit. An ideal thresher is one that carries out complete threshing with maximum crop input and best grain separation while saves the shape and quality of the grain and minimizes grain loss. The vibrations of this unit cause the threshing action to fail and combine harvester loss to increase; therefore, it is highly important to study the vibration produced in the threshing unit. Since measuring the vibration in all working conditions on the farm is expensive, one of the ways to achieve the mentioned objectives is to use a vibration model by the simulation methods in order to examine the effects of vibration on the machine’ s and the operator’ s performance. Using vibration modeling and dynamic ANALYSIS of the structure through a mathematical model, finite element, and MODAL ANALYSIS, the causes and effects of the vibration in different working conditions can be examined with minimum cost. The present study was aimed to carry out the dynamic ANALYSIS of combine harvester using OPERATIONAL MODAL ANALYSIS. Therefore, the nonparametric and frequency decomposition methods were used in order to extract values of natural frequencies and damping coefficients, and the information obtained from the MODAL ANALYSIS was utilized to design and update the finite element model of the thresher. Afterward, the vibration of the thresher was adjusted as much as possible by modifying the structure through the weight modification method. Materials and Methods To measure the vibration of the thresher in practical conditions, a piezoelectric accelerometer sensor DYTRAN/MODEL3255A2, an analyzer device, and a signal processing software MEscopeVES were employed. In order to carry out the ANALYSIS, the combine harvester was started in its normal conditions and all parts were set in operation. Due to the geometry of the structure, four points were chosen on the bearings of the threshing drum. Afterward, de-noising signals used in MATLAB were utilized to calculate the response power spectral matrix, and singular values decomposition method was applied to it. Finally, by drawing each singular value, resonance peaks of the system were determined with respect to different frequencies, and the system’ s damping was estimated. In order to carry out the geometric modeling and the simulation of the thresher by finite element method, ABAQUS finite element software was employed. In order to compare the analytical and the experimental results of NFD value, the predicted and measured natural frequencies were calculated. Modifying the structure as one of the applications of the MODAL ANALYSIS is a technique to consider the effect of physical parameters of a structure on its dynamic properties, i. e. natural frequencies and mode shape in order to improve the structure’ s dynamic behavior. In the present study, therefore, modification of the threshing unit was aimed to decrease its vibrations by changing the natural frequency. Due to its complexity, the process of modifying the structure can be carried out by changing the mass and hardness. As presented in the study, modification of the structure was conducted by changing the mass on the finite element model. Results and Discussion The purpose of this study is to determine the vibration characteristics and present a vibration model of the thresher. The vibration responses of the thresher were recorded in working conditions on the bearings of the thresher. Through investigating signal parameters, including root mean square, energy, and entropy in different speeds of the thresher, it was specified that these parameters had significantly higher values in the rotation speed of 1000 rpm compared to other speeds, which proved the disturbance in the rotation speed of 1000 rpm. By examining the range of the natural and excitation frequencies of the threshing unit and also considering the diagram obtained from decomposing the singular values of the power spectral density matrix and Campbell diagram, a resonance frequency was found for the given structure, which is the major cause of vibration in the thresher. Moreover, the speed of 1000 rpm was determined as the critical speed of the thresher. In order to reduce the level of vibrations, the thresher’ s excitation frequency should be far enough from the natural frequency; therefore, the process of modifying the structure is carried out by changing the mass applied to the finite element model, and it was observed that the natural frequency of the first mode changed from 16. 98 Hz to 12. 4 Hz.

It is impossible to measure the random excitation loads of structures during transportation under road excitations or satellite carriers thrown under environmental excitations in order to identify MODAL parameters; thus in this research, our challenge and purpose is to determine the MODAL properties of structures without having the input excitation load and, but only by having the response. In the studies have been performed so far in the field of MODAL ANALYSIS, less attention has been paid to comparing time and frequency methods, especially in the determination of damping. In addition, no sensitivity ANALYSIS between different excitations of white noise, sinusoidal sweep and the effect of these excitations on time and frequency domain methods of MODAL functional ANALYSIS have been performed so far. At first, these methods are implemented and validated on a 5-DOF discrete model (mass, spring, and damper), and finally they are industrially implemented on an actual structure. This paper shows that the decomposition methods are capable to extract the MODAL parameters of the primary modes of an actual sample. At the end, a comparison is made between the results and the effectiveness of each method is evaluated.