Operational Mode Identification Based on Sliding Time Window Method and Eigensystem Realization Algorithm

The identification result of operational mode is eurychoric while operational mode identification is investigated under ambient excitation,which is influenced by the signal size and the time interval.The operational mode identification method,which is based on the sliding time window method and the eigensystem realization algorithm(ERA),is investigated to improve the identification accuracy and stability.Firstly,the theory of the ERA method is introduced.Secondly,the strategy for decomposition and implementation is put forward,including the sliding time window method and the filtration method of modes.At last,an example is studied,where the model of a cantilever beam is built and the white noise exciting is input.Results show that the operational mode identification method can realize the modes,and has high robustness to the signal to noise ratio and signal size.

AN ACCELERATION FOR THE EIGENSYSTEM REALIZATION ALGORITHM WITH PARTIAL SINGULAR VALUES DECOMPOSITION

The real-time identification of dynamic parameters is importantfor the control system of spacecraft. The eigensystme realizationalgorithm (ERA) is currently the typical method for such applica-tion. In order to identify the dynamic parameter of spacecraftrapidly and accurately, an accelerated ERA with a partial singularvalues decomposition (PSVD) algorithm is presented. In the PSVD, theHankel matrix is reduced to dual diagonal form first, and thentransformed into a tridiagonal matrix.

Modal Identification of Offshore Platforms Using Statistical Method Based on ERA

Identification of modal parameters of a linear structure with output-only measurements has received much attention over the past decades. In the paper, the Natural Excitation Technique (NExT) is used for acquisition of the impulse signals from the structural responses. Then Eigensystem Realization Algorithm (ERA) is utilized for modal identification. For disregarding the fictitious ‘computational modes', a procedure, Statistically Averaging Modal Frequency Method (SAMFM), is developed to distinguish the true modes from noise modes, and to improve the precision of the identified modal frequencies of the structure. An offshore platform is modeled with the finite element method. The theoretical modal parameters are obtained for a comparison with the identified values. The dynamic responses of the platform under random wave loading are computed for providing the output signals used for identification with ERA. Results of simulation demonstrate that the proposed method can determine the system modal frequency with high precision.

Modal parameter identification for a roof overflow powerhouse under ambient excitation

Modal parameter identification is a core issue in health monitoring and damage detection for hydraulic structures. For a roof overflow hydropower station with a bulb tubular unit under ambient excitation, a complex unit-powerhouse-dam coupling vibration system increases the difficulties of modal parameter identification. In this study, in view of the difficulties of modal order determination and the noise jamming caused by ambient excitation, along with false mode identification and elimination problems, the ensemble empirical mode decomposition （EEMD） method was used to decrease noise, the singular entropy increment spectrum was used to determine system order, and multiple criteria were used to eliminate false modes. The eigensystem realization algorithm （ERA） and stochastic subspace identification （SSI） method were then used to identify modal parameters. The results show that the relative errors of frequencies in the first four modes were within 10% for the ERA method, while those of SSI were over 10% in the second and third modes. Therefore, the ERA method is more appropriate for identifying the structural modal parameters for this particular powerhouse layout.

Whole-spacecraft hybrid vibration isolation based on piezoelectric stacks and viscoelastic material

In order to improve the performance of whole-spacecraft vibration isolation systems,choosing piezoelectric stacks and viscoelastic material as the active and passive vibration isolation components,an innovative whole-spacecraft hybrid vibration isolation system (WSHVIS) is designed and studied.The finite element method is used to establish the dynamic model of WSHVIS and analyze its frequency response characteristic.According to the analysis results,eigensystem realization algorithm is applied to obtain the minimum-order state-space model of WSHVIS,which is used to design controller.On this basis,off-line simulation and on-line realization for the WSHVIS is performed.The simulation and experimental results showed that WSHVIS can effectively reduce the vibration loads transmitted from launch vehicle to spacecraft.Compared with passive vibration isolation system,the hybrid vibration isolation system has a significant inhibitory effect on the low-frequency vibration components,and can greatly increase the safety and reliability of spacecraft.

Stability Study of Cable-Suspended Stewart Platform

The control stability of the end manipulator of a cable-suspended Stewart platform in disturbance was studied by combination of the multi-body system dynamics and control theory and the eigensystem realization algorithm （ERA）. The corresponding closodloop vibration control strategies were suggested based on position prediction with PD （proportional plus derivative ） control. Numerical simulation was made on a scale model to study the vibration control effects of the stewart platform with flexible suspension, including system response to step load, system response to cyclic load, and instability. Then, experiments for Stewart platform with cable suspension were designed to study the actual control effects and validate the validity of numerical simulation. The results show that the experimental results agree with the simulation results well, and the the system has a fairly good control effect to the end manipulator. Therefore, a preliminary conclusion can be made that it is feasible using the Stewart platform as the vibration control platform of the flexible support system, by position prediction of the base platform and PD feedback control law.

Vibration analysis and topology optimization of the header of full-feeding rice combine harvester

The header frame of full-feeding rice combine harvester was characterized by severe vibration due to the excitation force generated by the movement of each working part.In order to solve the problem,the parametric model of the header frame was established,and the accuracy of the finite element model was verified by comparison of the results of the free modal analysis and free vibration modal test based on Eigensystem Realization Algorithm(ERA).Then the constrained modal frequencies were calculated and compared with the external excitation source frequencies,the results showed that the first and eighth order modal natural frequencies were coupled with the excitation frequencies of the threshing cylinder and the engine respectively,which were apt to resonate.To avoid resonance and achieve lightweight design,topology optimization,and finite element analysis were carried out.The optimization results showed that the strength and rigidity meet the requirements and the weight was 14.17%lower than before.The first and eighth order modal natural frequencies were far away from the excitation frequencies range of the threshing cylinder and engine,and the frequencies were far away from the range of each excitation frequency,which effectively avoided the occurrence of resonance.Field experiments showed that the peak value of the vibration acceleration in the three directions of the 8 measuring points of the optimized header frame was significantly reduced,which effectively reduced the vibration of the header frame during harvest.This study provides a method for obtaining the vibration characteristics of key components of agricultural machinery and provides a reference for the weight and vibration reduction of header frames of rice,wheat,rape,and other crop combine harvesters.

A System Identification-based Modeling Framework of Bidirectional DC-DC Converters for Power Grids

This paper proposes a system identification framework based on eigensystem realization to accurately model power electronic converters.The proposed framework affords an energy-based optimal reduction method to precisely identify the dynamics of power electronic converters from simulated or actual raw data measured at the converter’s ports.This method does not require any prior knowledge of the topology or internal parameters of the converter to derive the system modal information.The accuracy and feasibility of the proposed method are exhaustively evaluated via simulations and practical tests on a software-simulated and hardware-implemented dual active bridge(DAB)converter under steady-state and transient conditions.After various comparisons with the Fourier series-based generalized average model,switching model,and experimental measurements,the proposed method attains a root mean square error(RMSE)of less than 1%with respect to the actual raw data.Moreover,the computational effort is reduced to 1/8.6 of the Fourier series-based model.

Ambient vibration testing and updating of the finite element model of a simply supported beam bridge

An ambient vibration test on a concrete bridge constructed in 1971 and calibration of its finite element model are presented.The bridge is characterized by a system of post-tensioned and simply supported beams.The dynamic characteristics of the bridge,i.e.natural frequencies,mode shapes and damping ratios were computed from the ambient vibration tests by using the Eigensystem Realization Algorithm(ERA).Then,these characteristics were used to update the finite element model of the bridge by formulating an optimization problem and then using Genetic Algorithms(GA)to solve it.From the results of the ambient vibration test of this type of bridge,it is concluded that two-dimensional mode shapes exist:in the longitudinal and transverse;and these experimentally obtained dynamic characteristics were also achieved in the analytical model through updating.The application of GAs as optimization techniques showed great versatility to optimize any number and type of variables in the model.