Experimental Modal Analysis of Motorized Spindle Based on Stochastic Subspace Identification

2011 ◽  
Vol 103 ◽  
pp. 469-474
Author(s):  
Jie Meng ◽  
Xiao An Chen
Keyword(s):  
Modal Analysis ◽  
Dynamic Characteristics ◽  
Time Domain ◽  
Experimental Modal Analysis ◽  
Modal Parameters ◽  
Vibration Velocity ◽  
Subspace Identification ◽  
Motorized Spindle ◽  
Stochastic Subspace Identification ◽  
The Time Domain

Experimental modal analysis is done to the grinding motorized spindle under 36000r/min. The corresponding theory and experimental plan are introduced. The time domain waveform is gained and the maximum vibration velocity is worked out. Stochastic Subspace Identification (SSI) is applied to study dynamic characteristics of motorized spindle which is running idle, then modal parameters are extracted. The correctness of the experimental method is validated, which has certain referential importance.

scholarly journals Modal Parameter Identification of Structures Using Reconstructed Displacements and Stochastic Subspace Identification

2021 ◽  
Vol 11 (23) ◽  
pp. 11432
Author(s):  
Xiangying Guo ◽  
Changkun Li ◽  
Zhong Luo ◽  
Dongxing Cao
Keyword(s):  
Parameter Identification ◽  
Modal Analysis ◽  
Moving Average ◽  
Random Fluctuation ◽  
High Frequency Component ◽  
Modal Parameters ◽  
Subspace Identification ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Stochastic Subspace Identification

A method of modal parameter identification of structures using reconstructed displacements was proposed in the present research. The proposed method was developed based on the stochastic subspace identification (SSI) approach and used reconstructed displacements of measured accelerations as inputs. These reconstructed displacements suppressed the high-frequency component of measured acceleration data. Therefore, in comparison to the acceleration-based modal analysis, the operational modal analysis obtained more reliable and stable identification parameters from displacements regardless of the model order. However, due to the difficulty of displacement measurement, different types of noise interferences occurred when an acceleration sensor was used, causing a trend term drift error in the integral displacement. A moving average low-frequency attenuation frequency-domain integral was used to reconstruct displacements, and the moving time window was used in combination with the SSI method to identify the structural modal parameters. First, measured accelerations were used to estimate displacements. Due to the interference of noise and the influence of initial conditions, the integral displacement inevitably had a drift term. The moving average method was then used in combination with a filter to effectively eliminate the random fluctuation interference in measurement data and reduce the influence of random errors. Real displacement results of a structure were obtained through multiple smoothing, filtering, and integration. Finally, using reconstructed displacements as inputs, the improved SSI method was employed to identify the modal parameters of the structure.

Modal Characterization of MEMS Switches via Output Only and Input/Output Identification Methods

2011 ◽  
Author(s):  
Joel M. Book ◽  
Samuel F. Asokanthan
Keyword(s):  
Modal Analysis ◽  
Noise Signal ◽  
Experimental Modal Analysis ◽  
Modal Parameters ◽  
Identification Algorithm ◽  
Base Excitation ◽  
Mems Devices ◽  
Stochastic Subspace Identification ◽  
Output Only

MEMS devices typically have moving or oscillating mechanical parts, and characterization of their dynamics, including their modal parameters, is highly desirable. This paper is concerned with experimental implementation of a Stochastic Subspace Identification (SSI) algorithm as well a base excitation based identification algorithm for experimental modal analysis of a micro-cantilever switch. A white noise signal applied to the built-in electrostatic actuator in the switches excited a response measured using microscanning Laser Doppler Vibrometry (LDV). In the case of identification via the SSI, only the output response was used while the base excitation based algorithm employed the input and the output signals. The modal parameters found using MACEC matched well with those predicted by theory, and the results obtained via the two experimental identification approaches are in good agreement, thus providing confidence in using the SSI approach for experimental modal analysis of MEMS structures.

Experimental Modal Characterization of MEMS Switches

2011 ◽  
Vol 403-408 ◽  
pp. 4598-4605
Author(s):  
Joel M. Book ◽  
Samuel F. Asokanthan ◽  
Tian Fu Wang
Keyword(s):  
Modal Analysis ◽  
Mechanical Systems ◽  
Noise Signal ◽  
Experimental Modal Analysis ◽  
Modal Parameters ◽  
Mems Devices ◽  
Micro Electro Mechanical Systems ◽  
Mems Switches ◽  
Stochastic Subspace Identification

MEMS devices, Micro Electro-Mechanical Systems, are electrical and mechanical systems with characteristic dimensions on the order of microns. Since these systems have moving mechanical parts, characterization of their dynamics, including their modal parameters, is highly desirable. This paper describes the validation of an existing implementation of the Stochastic Subspace Identification (SSI) algorithm, called MACEC, for experimental modal analysis of a micro-cantilever switch. A white noise signal applied to the built-in electrostatic actuator in the switches excited a response measured using microscanning Laser Doppler Vibrometry (LDV). The modal parameters found using MACEC matched well those predicted by theory, thus validating this combination for experimental modal analysis of MEMS structures.

Effect of Bass Bar Tension on Modal Parameters of a Violin's Top Plate

2015 ◽  
Vol 39 (1) ◽  
pp. 145-149 ◽  
Author(s):  
Ewa B. Skrodzka ◽  
Bogumił B.J. Linde ◽  
Antoni Krupa
Keyword(s):  
Modal Analysis ◽  
Experimental Modal Analysis ◽  
Mode Shapes ◽  
Modal Parameters ◽  
Normal Value ◽  
Modal Damping

Abstract Experimental modal analysis of a violin with three different tensions of a bass bar has been performed. The bass bar tension is the only intentionally introduced modification of the instrument. The aim of the study was to find differences and similarities between top plate modal parameters determined by a bass bar perfectly fitting the shape of the top plate, the bass bar with a tension usually applied by luthiers (normal), and the tension higher than the normal value. In the modal analysis four signature modes are taken into account. Bass bar tension does not change the sequence of mode shapes. Changes in modal damping are insignificant. An increase in bass bar tension causes an increase in modal frequencies A0 and B(1+) and does not change the frequencies of modes CBR and B(1-).

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.

Servo System Identification Using Relay Feedback: A Time-Domain Approach

2012 ◽  
Vol 134 (6) ◽  
Author(s):  
Jia Liu ◽  
Jianhua Wu ◽  
Zhenhua Xiong ◽  
Xiangyang Zhu
Keyword(s):  
System Identification ◽  
Dynamic Characteristics ◽  
Time Domain ◽  
Oscillation Amplitude ◽  
Servo System ◽  
Time Domain Method ◽  
Relay Feedback ◽  
Servo Systems ◽  
Domain Method ◽  
The Time Domain

In servo systems, the dynamic characteristics may not only differ between axes but may also vary with moving directions for a single axis. The direction dependent characteristics would result in additional tracking or positioning error and degrade the performance of the system. In this paper, relay feedback tests are successfully applied to identify the dynamic characteristics in servo systems. A time-domain method is used to analyze the relay feedback other than the conventional describing function (DF) method. The time-domain method utilizes the same oscillation parameters (oscillation amplitude and half period) as the DF method for system identification. However, the time-domain method takes several advantages: First, the direction dependent characteristics of the system can be properly revealed; second, no approximation is made in this method, so that the exact expressions of the amplitudes and the periods of the limit cycles under relay feedback can be derived. A feedforward compensator is then designed using the estimated values of the system parameters. Simulation results show that the identification results through the time-domain method are more accurate than the DF method and are more robust under different relay parameters. Real time experiments show that the feedforward compensator designed by the proposed method compensates disturbances related to the direction and hence improves the tracking and positioning performance of the servo system.

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