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.

A Method of SSVEP Signal Identification Based on Improved eCAA

Brain-computer interfaces(BCI)based on steady-state visual evoked potentials(SSVEP)have attracted great interest because of their higher signal-to-noise ratio,less training,and faster information transfer.However,the existing signal recognition methods for SSVEP do not fully pay attention to the important role of signal phase characteristics in the recognition process.Therefore,an improved method based on extended Canonical Correlation Analysis(eCCA)is proposed.The phase parameters are added from the stimulus paradigm encoded by joint frequency phase modulation to the reference signal constructed from the training data of the subjects to achieve phase constraints on eCCA,thereby improving the recognition performance of the eCCA method for SSVEP signals,and transmit the collected signals to the robotic arm system to achieve control of the robotic arm.In order to verify the effectiveness and advantages of the proposed method,this paper evaluated the method using SSVEP signals from 35 subjects.The research shows that the proposed algorithm improves the average recognition rate of SSVEP signals to 82.76%,and the information transmission rate to 116.18 bits/min,which is superior to TRCA and traditional eCAA-based methods in terms of information transmission speed and accuracy,and has better stability.

EI NIO PHENOMENON AND EXTENDED ASSOCIATE PATTERN ANALYSIS

To study the causes of El Nino Phenomenon the Extended Associate PatternAnalysis (EAPA) is set up with monthly sea surface wind stress and precipitation besides Sea LevelPressure (SLP) and Sea Surface Temperature (SST) in or over the Pacific and related seas since 1979in present paper. The results show that El Nino Phenomenon means a SST redistribution, coveringalmost the whole Pacific that needs a huge amount of energy provided by air-sea interaction in themost Pacific regions; It is the wester burst and wind convergence, coming from meddle latitudesdirectly, instead of Kelvin waves that produce the strong SST warm signal in Nino regions; Twonegative SLP anomalies in middle of the North and South Pacific, most likely produced by the averageair pressure decreasing effect of explosive cyclones through precipitation, and the positive SLPanomaly o-ver the Asia-Australia land bridge, coming mainly from the south hemisphere with a littleinfluence from the Asian continent, are the three major causes for El Nino onset, they work togetherto produce anomalous wind convergence in Nino regions and wester burst in middle of the North andSouth Pacific that result in a warm tongue and cold pincers gearing together; Basically, during itsearly stage the ocean is forced by the atmosphere, while during its late stage the atmosphere isforced by the ocean.

Effects of grazing disturbance of spatial distribution pattern and interspecies relationship of two desert shrubs

Grazing significantly affects the distribution,growth,and productivity of shrubs.In this study,we evalu-ated the effects of grazing disturbance on the spatial distri-bution patterns and interspecific relationships of two desert shrubs,Ammopiptanthus mongolicus and Sarcozygium xan-thoxylon.Three types of grazing conditions were considered,including enclosed area(EA),seasonal rotational grazing area(SRGA),and grazing area(GA)(100 m×100 m),in the West Ordos Nature Reserve of Inner Mongolia,China.The results showed that A.mongolicus and S.xanthoxylon populations were uniformly distributed at a small scale,and the distribution in EA and SRGA became gradually ran-dom.In GA,A.mongolicus population showed aggregated distribution but S.xanthoxylon population showed random distribution at a small scale. Moreover, both A. mongolicus and S. xanthoxylon populations at the 5-7 m scale showed random distribution. At the small and intermediate scales, the two species showed positive interspecific relationships of GA. However, no interspecific relationship was noted between the two species in EA and SRGA. A significant positive relationship (P < 0.01) was noted between the two species at 2-9 m and a negative relationship (P < 0.01) at 13-17 m scales in GA. Positive relationship (P < 0.01) was noted between the two species at 6-13 m scales and a sig-nificant negative relationship (P < 0.01) at 14-24 m scales in SRGA. The two species of desert shrubs showed posi-tive interspecific relationships at the small scale, and they showed negative relationships as the interspecific compe-tition intensified in the presence of grazing disturbance. When the grazing intensity exceeds a certain threshold, the interspecific relationships become weak. Therefore, moder-ate grazing would facilitate interspecific competition and species succession, whereas excessive grazing would disrupt natural competition causing desertification ultimately.

An extended Galerkin analysis for elliptic problems

A general analysis framework is presented in this paper for many different types of finite element methods(including various discontinuous Galerkin methods).For the second-order elliptic equation-div(α▽u)=f,this framework employs four different discretization variables,u_(h),p_(h),u_(h)and p_(h),where u_(h)and p_(h)are for approximation of u and p=-α▽u inside each element,and u_(h)and p_(h)are for approximation of the residual of u and p·n on the boundary of each element.The resulting 4-field discretization is proved to satisfy two types of inf-sup conditions that are uniform with respect to all discretization and penalization parameters.As a result,many existing finite element and discontinuous Galerkin methods can be analyzed using this general framework by making appropriate choices of discretization spaces and penalization parameters.

E1 Nio phenomenon in simple ocean data assimilation data

To study how the air and sea interact with each other during El Nifio/La Nifia onsets, extended associate pattern analysis （EAPA） is adopted with the simple ocean data assimilation （SODA） data. The results show that as El Niйo/La Niйa＇s parents their behaviors are quite different, there does not exist a relatively independent tropical atmosphere but does exist a relatively independent tropical Pacific Ocean because the air is heated from the bottom surface instead of the top surface and of much stronger baroclinic instability than the sea and has a very large inter-tropical convergence zone covering the most tropical Pacific Ocean. The idea that it is the wester burst and wind convergence, coming from middle latitudes directly that produce the seawater eastward movement and meridional convergence in the upper levels and result in the typical E1 Nifio sea surface temperature warm signal is confirmed again.

An extended binary subband canonical correlation analysis detection algorithm oriented to the radial contraction-expansion motion steady- state visual evoked paradigm

The radial contraction-expansion motion paradigm is a novel steady-state visual evoked experimental paradigm,and the electroencephalography(EEG)evoked potential is different from the traditional luminance modulation paradigm.The signal energy is concentrated chiefly in the fundamental frequency,while the higher harmonic power is lower.Therefore,the conventional steady-state visual evoked potential recognition algorithms optimizing multiple harmonic response components,such as the extended canonical correlation analysis(eCCA)and task-related component analysis(TRCA)algorithm,have poor recognition performance under the radial contraction-expansion motion paradigm.This paper proposes an extended binary subband canonical correlation analysis(eBSCCA)algorithm for the radial contraction-expansion motion paradigm.For the radial contraction-expansion motion paradigm,binary subband filtering was used to optimize the weighting coefficients of different frequency response signals,thereby improving the recognition performance of EEG signals.The results of offline experiments involving 13 subjects showed that the eBSCCA algorithm exhibits a better performance than the eCCA and TRCA algorithms under the stimulation of the radial contraction-expansion motion paradigm.In the online experiment,the average recognition accuracy of 13 subjects was 88.68%±6.33%,and the average information transmission rate(ITR)was 158.77±43.67 bits/min,which proved that the algorithm had good recognition effect signals evoked by the radial contraction-expansion motion paradigm.

End-of-life batteries management and material flow analysis in South Korea

Consumers increasingly have worn-out batteries as electrical and electronic equipment with new technical developments are introduced into the market and quickly replace older models. As a result, large amounts of end-of-life （EOL） or waste batteries are generated. Such batteries may contain a variety of materials that includes valuable resources as well as toxic elements. Thus, the proper recycling and management of batteries is very important from the perspective of resource conservation and environmental effect. The collection and recycling of EOL batteries is relatively low in South Korea compared to other countries, although an extended producer responsibility （EPR） policy was adopted for battery recycling in 2003. In this study, the management and material flow of EOL batteries is presented to determine potential problems and quantitative flow, based on literature review, site visits to battery recycling facilities, and interviews with experts in the Korea Battery Recycling Association （KBRA）, manufacturers, and regulators in government. The results show that approximately 558 tons of manganese-alkaline batteries, the largest fraction among recycling target items, was disposed in landfills or incinerators in 2015, while approximately 2,000 tons of batteries were recovered at a recycling facility by simple sorting and crushing processes. By raising environmental awareness, more diverse and effective collection systems could be established for consumers to easily dispose of EOL batteries in many places. Producers, retailers and distributors in South Korea should also play an important role in the collection of EOL batteries from consumers. Lithium-ion batteries from many electronic devices must be included in the EPR system for resource recovery.

Spatial transformation of general sampling-aliasing frequency region for rotating-blade parameter identification with emphasis on single-probe blade tip-timing measurement

Blade-health monitoring is intensely required for turbomachinery because of the high failure risk of rotating blades.Blade-Tip Timing(BTT)is considered as the most promising technique for operational blade-vibration monitoring,which obtains the parameters that characterize the blade condition from recorded signals.However,its application is hindered by severe undersampling and stringent probe layouts.An inappropriate probe layout can make most of the existing methods invalid or inaccurate.Additionally,a general conflict arises between the allowed and required layouts because of arrangement restrictions.For the sake of economy and safety,parameter identification based on fewer probes has been preferred by users.In this work,a spatial-transformation-based method for parameter identification is proposed based on a single-probe BTT measurement.To present the general Sampling-Aliasing Frequency(SAFE)map definition,the traditional time-frequency analysis methods are extended to a time-sampling frequency.Then,a SAFE map is projected onto a parameter space using spatial transformation to extract the slope and intercept parameters,which can be physically interpreted as an engine order and a natural frequency using coordinate transformation.Finally,the effectiveness and robustness of the proposed method are verified by simulations and experiments under uniformly and nonuniformly variable speed conditions.