scholarly journals A new automated procedure of modal identification in operational conditions

2018 ◽  
Vol 211 ◽  
pp. 21003 ◽  
Author(s):  
Gabriele Marrongelli ◽  
Carmelo Gentile
Keyword(s):  
Parametric Identification ◽  
Modal Identification ◽  
Mode Shapes ◽  
Parameter Estimates ◽  
Reference List ◽  
Modal Parameter ◽  
Operational Conditions ◽  
Historic Masonry ◽  
Stabilization Diagram ◽  
Using Data

Structural Health Monitoring (SHM) strategies are aimed at the assessment of structural performance, using data acquired by sensing systems. Among the different available approaches, vibration-based methods - involving the automation of the modal parameter estimation (MPE) and modal tracking (MT) procedures - are receiving increasing attention. In the context of vibration-based monitoring, this paper presents an automated procedure of modal identification in operational conditions. The presented algorithms can be used to effectively manage the results obtained by any parametric identification method that involves the construction and the interpretation of stabilization diagrams. The implemented approach introduces improvements related to both the MPE and the MT tasks. The MPE procedure consists of three key steps aimed at: (1) filtering a high number of spurious poles in the stabilization diagram; (2) clustering the remaining poles that share same characteristics in term of modal parameters; (3) improving the accuracy of the modal parameter estimates. In the MT procedure the use of a simple statistical approach to define adaptive thresholds together with continuously updated dynamic reference list guarantee an efficient tracking of the most representative structural modes. The advantages obtained through the proposed procedures are exemplified using data continuously collected on the historic masonry tower of San Gottardo in Corte, located in the centre of Milan, Italy. In addition, the ability of the automated algorithms to identify contributions inherent to different vibration modes, even if they are characterized by closely-spaced frequencies and a low discriminant between mode shapes, will be described in details.

scholarly journals Automated band selection for Bayesian FFT modal identification Based on RetinaNet

2021 ◽  
Vol 2078 (1) ◽  
pp. 012058
Author(s):  
Chen Wang ◽  
Zhilin Xue ◽  
Yipeng Su ◽  
Binbin Li
Keyword(s):  
Operation Time ◽  
Modal Identification ◽  
Ambient Vibration ◽  
Mode Shapes ◽  
Band Selection ◽  
Data Sets ◽  
Civil Structures ◽  
Frequency Bands ◽  
Operational Conditions ◽  
Vibration Data

Abstract Bayesian FFT algorithm is a popular method to identify modal parameters, e.g., modal frequencies, damping ratios, and mode shapes, of civil structures under operational conditions. It is efficient and provides the identification uncertainty in terms of posterior distribution. However, in utilizing the Bayesian FFT algorithm, it is tedious to manually select frequency bands and initial frequencies. This step requires professional knowledge and costs most of time, which prevents the automation of Bayesian FFT algorithm. Regarding the band selection as an object detection problem, we design a band selection network based on the RetinaNet to automatically select frequency bands and a peak prediction network to predict the initial frequencies. The designed networks are trained using the singular value spectrum of measured ambient vibration data and verified by various data sets. It can achieve the human accuracy with much less operation time, and thus provides a corner stone for the automation of Bayesian FFT algorithm.

scholarly journals OUTPUT-ONLY MODAL IDENTIFICATION OF TENSEGRITY STRUCTURES

2016 ◽  
Vol 8 (2) ◽  
pp. 52-64 ◽  
Author(s):  
Miniar Attig ◽  
Maher Abdelghani ◽  
Nabil ben Kahla
Keyword(s):  
Natural Frequencies ◽  
Modal Identification ◽  
Mode Shapes ◽  
Subspace Identification ◽  
Balanced Realization ◽  
Stochastic Subspace Identification ◽  
Tensegrity Systems ◽  
Stabilization Diagram ◽  
Subspace Algorithms ◽  
Output Only

Tensegrity systems are a special class of spatial reticulated structures that are composed of struts in compression and cables in tension. In this paper, the performance of stochastic subspace algorithms for modal identification of complex tensegrity systems is investigated. A sub-class algorithm of the Stochastic Subspace Identification family: the Balanced Realization Algorithm is investigated for modal identification of a tripod simplex structure and a Geiger dome. The presented algorithm is combined with a stabilization diagram with combined criteria (frequency, damping and mode shapes). It is shown that although the studied structures present closely spaced modes, the Balanced Realization Algorithm performs well and guarantees separation between closely-spaced natural frequencies. Modal identification results are validated through comparisons of the correlations (empirical vs. model based) showing effectiveness of the proposed methodology.

scholarly journals Cluster Analysis for Automated Operational Modal Analysis: A Review

2019 ◽  
Vol 255 ◽  
pp. 02012 ◽  
Author(s):  
M. Danial A. Hasan ◽  
Z. A. B. Ahmad ◽  
M. Salman Leong ◽  
L. M. Hee ◽  
M. Haffizzi Md. Idris
Keyword(s):  
Cluster Analysis ◽  
Modal Analysis ◽  
Clustering Algorithm ◽  
Operational Modal Analysis ◽  
Modal Identification ◽  
Modal Parameter ◽  
Essential Information ◽  
Clustering Techniques ◽  
Stabilization Diagram ◽  
Recent Developments

Recent developments in the field of modal-based damage detection and vibration-based monitoring have led to a renewed interest in automated procedures for the operational modal analysis (OMA). The development of automated operational modal analysis (OMA) procedures marked a fundamental step towards the elimination of any user intervention since traditional modal identification requires a lot of interaction by an expert user. A key for effective automation of OMA is depended on well- defined modal indicators for a clear indication about which modes are to be selected as the physical modes. In all modal analysis, the construction of stabilization diagrams is necessary in order to illustrate, and decide, if a mode is physical or not for predefined range of the model order. On the other hand, the use of stabilization diagram tools involves a large amount of user interaction, costly, time-consuming process and certainly unsuited for online applications. Therefore, the development of automatic procedures for the analysis of stabilization diagrams by resembling decision-making process of a human has been carried out in recent years. For the sake of clearness, the automation of the interpretation of stabilization diagrams can generally be divided into two steps in order to speed up the process: a) elimination of noise modes and b) clustering of physical modes in order to obtain the most representative values of the estimated parameters of each clustered mode. In recent years, several alternative procedures have been proposed for clustering techniques. Therefore, this review aims to provide relevant essential information on the recent developments of cluster analysis in automated OMA. A literature review of existing clustering algorithm has been carried out to find best practice criteria for automated modal parameter identification which involving the general concepts of these techniques as well as the pro and cons of applying these clustering techniques are also discussed and summarised.

scholarly journals Indirect Measurements of Bridge Vibrations as an Experimental Tool Supporting Periodic Inspections

2021 ◽  
Vol 6 (3) ◽  
pp. 39
Author(s):  
Stefano Ercolessi ◽  
Giovanni Fabbrocino ◽  
Carlo Rainieri
Keyword(s):  
Information And Communication Technologies ◽  
Low Cost ◽  
Structural Response ◽  
Parameter Estimates ◽  
Modal Parameter ◽  
Vibration Measurements ◽  
Operational Conditions ◽  
Instrumented Vehicle ◽  
Periodic Inspections ◽  
The Impact

Recent collapses and malfunctions of European bridges threatened the service conditions of road networks and pointed out the need for robust procedures to mitigate the impact of material degradation and overloading of existing bridges. Condition assessment of bridges remains a challenging task, which could take advantage of cost-effective and reliable inspection strategies. The advances in sensors as well as Information and Communication Technologies (ICT) ensure a significant enhancement of the capabilities in recording and processing physical and mechanical data. The present paper focuses on the paradigm of indirect vibration measurements for modal parameter identification in operational conditions. It is very attractive because of the related opportunities of application of dynamic tests as a tool for periodic inspections while significantly mitigating their impact on the traffic flow. In this framework the instrumented vehicle acts as a dynamic measurement device for periodic inspections and provides valuable information on the structural response of the bridge at a low-cost. Vehicle-bridge interaction models are here applied to realistically simulate the traffic-induced vibration response of bridges and assess the accuracy of modal parameter estimates obtained from indirect vibration measurements characterized by different noise levels.

scholarly journals Perspectives of Second-Order Blind Identification for Operational Modal Analysis of Civil Structures

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
C. Rainieri
Keyword(s):  
Modal Analysis ◽  
Second Order ◽  
Modal Identification ◽  
Computational Time ◽  
Parameter Estimates ◽  
Blind Identification ◽  
Modal Parameter ◽  
Civil Structures ◽  
Key Issues ◽  
Output Only

Innovative methods for output-only estimation of the modal properties of civil structures are based on blind source separation techniques. In the present paper attention is focused on the second-order blind identification (SOBI) algorithm and the influence of its analysis parameters on computational time and accuracy of modal parameter estimates. These represent key issues in view of the automation of the algorithm and its integration within vibration-based monitoring systems. The herein reported analyses and results provide useful hints for reduction of computational time and control of accuracy of estimates. The latter topic is of interest in the case of single modal identification tests, too. A criterion for extraction of accurate modal parameter estimates is identified and applied to selected experimental case studies. They are representative of the different levels of complexity that can be encountered during real modal tests. The obtained results point out that SOBI can provide accurate estimates and it can also be automated, confirming that it represents a profitable alternative for output-only modal analysis and vibration-based monitoring of civil structures.

scholarly journals Output-Only Modal Estimation Using Eigensystem Realization Algorithm with Nonstationary Data Correlation

2021 ◽  
Vol 11 (7) ◽  
pp. 3088
Author(s):  
Chang-Sheng Lin ◽  
Ming-Hsien Lin
Keyword(s):  
Nonstationary Process ◽  
Modal Identification ◽  
Structural System ◽  
Modal Parameter ◽  
Data Correlation ◽  
Eigensystem Realization Algorithm ◽  
Product Model ◽  
Modal Assurance Criterion ◽  
Stabilization Diagram ◽  
Output Only

The conventional eigensystem realization algorithm with data correlation (ERA/DC) combines the impulse response or free response data of a structural system with the concept of correlation function to identify the modal parameter of the structural system. Previous studies have shown that the modal parameters of structural systems subjected to stationary white noise excitation can be estimated by ERA/DC from the ambient response without excitation data. This concept is extended in this paper for output-only modal identification for the structural system with complex modes under ambient excitation as a nonstationary process in the form of a product model. Numerical simulations and experimental verification are used to validate the effectiveness of the proposed method for response-only modal estimation, and the stabilization diagram is used with modal assurance criterion (MAC) to distinguish structural modes from fictitious modes.

A comparative study on in-flight modal identification of an aircraft using time- and frequency-domain techniques

2020 ◽  
Vol 26 (21-22) ◽  
pp. 1920-1934
Author(s):  
Cagri Kocan
Keyword(s):  
Frequency Domain ◽  
Flight Test ◽  
Modal Identification ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Operational Conditions ◽  
Stochastic Subspace Identification ◽  
Vibration Data ◽  
Output Only ◽  
Frequency Domain Decomposition

In this study, in-flight modal identification analyses are made based on vibration data collected during a flight test of an aircraft, by using two different output-only identification techniques: frequency domain decomposition and data-driven stochastic subspace identification. The purpose of this study was to evaluate and compare the efficacy of the two methods in modal parameter estimation and to validate their capability in dealing with some challenging tasks such as time tracking of modal parameters and estimating modal damping ratios. In addition, the effects of different environmental conditions and maneuvers are investigated by separating the flight-test data, such as static engine start, taxi, takeoff, cruise, roll, climb, descend, and yaw maneuvers. It is demonstrated that the selection of operational conditions and maneuvers plays a crucial role in identifying the modal parameters of the aircraft.

Tracking Modal Parameter Evolution of Different Cultural Heritage Structure Damaged by Central Italy Earthquake of 2016

2019 ◽  
Vol 817 ◽  
pp. 334-341 ◽  
Author(s):  
Elisa Ribilotta ◽  
Ersilia Giordano ◽  
Angela Ferrante ◽  
Francesco Clementi ◽  
Stefano Lenci
Keyword(s):  
Structural Parameters ◽  
Central Italy ◽  
Modal Identification ◽  
Ambient Vibration ◽  
Assessment Procedure ◽  
Modal Parameter ◽  
Historic Masonry ◽  
Central Italy Earthquake ◽  
Ambient Vibration Testing ◽  
Vibration Responses

The preliminary results of an ambient-vibration based investigation conducted on a large sample of historic masonry towers in the Marche region (Central Italy) are presented, with a focus on the belfry of Collegiata of Santa Maria in Visso (Italy). The assessment procedure includes full-scale ambient vibration testing, modal identification from ambient vibration responses, finite element modeling and dynamic-based identification of the uncertain structural parameters of the model. As the most doubtful parameters, the modulus of elasticity of the masonry is adjusted to achieve the experimental results with numerical model by simple operations.

scholarly journals Identifying Temporal Aggregation Effect on Crash-Frequency Modeling

2021 ◽  
Vol 13 (11) ◽  
pp. 6214
Author(s):  
Bumjoon Bae ◽  
Changju Lee ◽  
Tae-Young Pak ◽  
Sunghoon Lee
Keyword(s):  
Traffic Safety ◽  
Negative Binomial ◽  
Random Effect ◽  
Temporal Correlation ◽  
Negative Binomial Regression ◽  
Spatiotemporal Analysis ◽  
Parameter Estimates ◽  
Crash Frequency ◽  
Crash Frequency Modeling ◽  
Using Data

Aggregation of spatiotemporal data can encounter potential information loss or distort attributes via individual observation, which would influence modeling results and lead to an erroneous inference, named the ecological fallacy. Therefore, deciding spatial and temporal resolution is a fundamental consideration in a spatiotemporal analysis. The modifiable temporal unit problem (MTUP) occurs when using data that is temporally aggregated. While consideration of the spatial dimension has been increasingly studied, the counterpart, a temporal unit, is rarely considered, particularly in the traffic safety modeling field. The purpose of this research is to identify the MTUP effect in crash-frequency modeling using data with various temporal scales. A sensitivity analysis framework is adopted with four negative binomial regression models and four random effect negative binomial models having yearly, quarterly, monthly, and weekly temporal units. As the different temporal unit was applied, the result of the model estimation also changed in terms of the mean and significance of the parameter estimates. Increasing temporal correlation due to using the small temporal unit can be handled with the random effect models.

scholarly journals Looseness localization for bolted joints using Bayesian operational modal analysis and modal strain energy

2018 ◽  
Vol 10 (11) ◽  
pp. 168781401880869 ◽  
Author(s):  
Yu-Jia Hu ◽  
Wei-Gong Guo ◽  
Cheng Jiang ◽  
Yun-Lai Zhou ◽  
Weidong Zhu
Keyword(s):  
Modal Analysis ◽  
Strain Energy ◽  
Damage Index ◽  
Operational Modal Analysis ◽  
Modal Identification ◽  
Bolted Joints ◽  
Mode Shapes ◽  
Bolted Connections ◽  
Modal Strain Energy ◽  
Beam Structures

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.

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