Error analysis of the application of combined subspace identification to the modal analysis of railway vehicles

2017 ◽  
Vol 407 ◽  
pp. 144-169 ◽  
Author(s):  
L.M. Erviti ◽  
J.G. Giménez ◽  
A. Alonso
Keyword(s):  
Error Analysis ◽  
Modal Analysis ◽  
Subspace Identification ◽  
Railway Vehicles

A Dynamic Identification of a Historical Building Using Accelerometers with Interface Modules and a Digital Synchronization Method

2014 ◽  
Vol 628 ◽  
pp. 204-211 ◽  
Author(s):  
Luigi Spedicato ◽  
Iro Armeni ◽  
Nicola Ivan Giannoccaro ◽  
Markos Avlonitis ◽  
Sozon Papavlasopoulos
Keyword(s):  
Experimental Data ◽  
Modal Analysis ◽  
Monitoring System ◽  
Low Cost ◽  
Subspace Identification ◽  
Dynamic Identification ◽  
Historical Building ◽  
Stochastic Subspace Identification ◽  
Innovative Method ◽  
Interface Modules

This paper describes a study about the San Giacomo building for testing the dynamic identification applicability of a low-cost monitoring system, consisting of accelerometers and acquisition modules. The Stochastic Subspace Identification (SSI), a well-known technique of Operational Modal Analysis (OMA), is applied to the experimental data to evaluate the possibility of identifying the first frequencies of the building. Moreover, in order to solve the lack of synchronization of the monitoring system, an innovative method based on the phase delay of each signal is presented and used for digitally synchronizing the data.

Analysis of Instabilities in Railway Vehicles Employing Operational Modal Analysis

2015 ◽  
Author(s):  
Lara Erviti Calvo ◽  
Gorka Agirre Castellanos ◽  
Germán Gimenez
Keyword(s):  
Numerical Model ◽  
Modal Analysis ◽  
Mode Shape ◽  
Operational Modal Analysis ◽  
Mode Shapes ◽  
Correct Identification ◽  
Unstable Condition ◽  
Static Tests ◽  
Railway Vehicles ◽  
Damping Rate

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.

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