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.

Fracture mode identification of low alloy steels and cast irons by electron back-scattered diffraction misorientation analysis

The fracture modes of low alloy steels and cast irons under tensile and fatigue conditions were identified by electron back-scattered diffraction（EBSD） misorientation analysis in this research. The curves of grain reference orientation deviation（GROD） distribution perpendicular to the fracture surface were obtained by EBSD observation, and the characteristics of each fracture mode were identified. The GROD value of the specimen fractured in tension decreases to a constant related to the elongation of corresponding specimen in the far field（farther than 5 mm away from the fracture surface）. The peak exhibits in GROD curves of two smooth specimens and a notched specimen near the fracture surface（within 5 mm away from the fracture surface）, and the formation mechanisms were discussed in detail based on the influences of specimen geometries（smooth or notched） and material toughness. The GROD value of fatigue fractured specimen is close to that at undeformed condition in the whole field, except the small area near the crack path. The loading conditions（constant stress amplitude loading or constant stress intensity factor range K loading） and the EBSD striation formation during fatigue crack propagation were also studied by EBSD observation parallel to the crack path.

Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

The problem of linear time-varying（LTV） system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the ＂frozen-time＂ assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stabilitypreserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system＇s stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam exper- imental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides anew way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.

IMPROVED COVARIANCE DRIVEN BLIND SUBSPACE IDENTIFICATION METHOD

An improved covariance driven subspace identification method is presented to identify the weakly excited modes. In this method, the traditional Hankel matrix is replaced by a reformed one to enhance the identifiability of weak characteristics. The robustness of eigenparameter estimation to noise contamination is reinforced by the improved Hankel matrix, in combination with component energy index （CEI） which indicates the vibration intensity of signal components, an alternative stabilization diagram is adopted to effectively separate spurious and physical modes. Simulation of a vibration system of multiple-degree-of-freedom and experiment of a frame structure subject to wind excitation are presented to demonstrate the improvement of the proposed blind method. The performance of this blind method is assessed in terms of its capability in extracting the weak modes as well as the accuracy of estimated parameters. The results have shown that the proposed blind method gives a better estimation of the weak modes from response signals of small signal to noise ratio （SNR）and gives a reliable separation of spurious and physical estimates.

High-accuracy mode recognition method in orbital angular momentum optical communication system

Vortex optical communication has been a hot research field in recent years. A key step is mode recognition in the orbital angular momentum(OAM) free-space optical(FSO) communication system. In this article, we propose an OAM mode recognition method based on image recognition technology, which uses the interferogram between the vortex beam and the Gaussian beam to identify the OAM mode. In order to resist the influence of atmospheric turbulence on the recognition accuracy, we added a Gaussian smoothing filter into the recognition process. Moreover, we used random phase screens to generate interferogram sets at distances of 1 km and 2 km. The verification result shows that the proposed scheme produces high identification accuracy for the distorted optical field. The average accuracy can reach 100% and 87.78% under the conditions of medium-and strong-turbulence levels, respectively. It is anticipated that these results might be helpful for improving the reliability of the OAM-FSO communication system in the future.