LOCAL CHAOS CHARACTERISTICS IN A SELF ASPIRATED REVERSED FLOW JET LOOP REACTOR

The local chaos characteristics of the time series pressure fluctuations of gas liquid two phase flow in a self aspirated reversed flow jet loop reactor are studied by the deterministic chaos analysis technique. It is found that the estimated local largest Lyapunov exponent is positive in all cases and the profile is similar to that of the local fractal dimension in this reactor. The positive largest Lyapunov exponent shows that the reactor is a nonlinear chaotic system. The obvious distribution indicates that the local nonlinear characteristic parameters such as the Lyapunov exponent and the fractal dimension could be applied to further study the flow characteristics such as the flow regine transitions and flow structures of the multi phase reactors.

Chaotic Characteristic Analysis of Air Traffic System

Chaotic characteristics of traffic flow time series is analyzed to further investigate nonlinear characteristics of air traffic system.Phase space is reconstructed both by time delay which is built through mutual information,and by embedding dimension which is based on false nearest neighbors method.In order to analyze chaotic characteristics of time series,correlation dimensions and the largest Lyapunov exponents are calculated through Grassberger-Procaccia(G-P)algorithm and small-data method.Five-day radar data from the control center in Guangzhou area are analyzed and the results show that saturated correlation dimensions with self-similar structures exist in time series,and the largest Lyapunov exponents are all equal to zero and not sensitive to initial conditions.Air traffic system is affected by multiple factors,containing inherent randomness,which lead to chaos.Only grasping chaotic characteristics can air traffic be predicted and controlled accurately.

Eigenvalue extraction of current signal during spot welding based on space-phase reconstruction

Nonlinear methods are used to analyze current signal of spot welding and the minimum embedding dimension, correlation dimension, the optimal time delay and the largest Lyapunav exponent of current signal time series are calculated in this paper. The chaotic character of current signal time series is discovered. Then a chaotic neural network is built and used to predict the future current signal. Means of residual error out of the network are used as eigenvalue of current signal during spot welding. It is shown that spatter can greatly affect the means of residual error of spot welding after analysis, the mean values of output errors of signal contaminated by spatter noise are more than 0. 08, but the mean values of output errors of the signal with no spatter noise are less than 0. 04, so mean of residual errors can be employed as the character of spatter.

Nonlinear Dynamics of Permanent-magnet Synchronous Motor with v/f Control

The nonlinear dynamics of permanent-magnet synchronous motor(PMSM) with v/f control signals is investigated intensively.First,the equilibria and steady-state characteristics of the system are formulated by analytical analysis.Then,some of its basic dynamical properties,such as characteristic eigenvalues,Lyapunov exponents and phase trajectories are studied by varying the values of system parameters.It is found that when the values of the system parameters are smaller,the PMSM operates in stable domains,no matter what the values of control gains are.With the values of parameters increasing,the unstability appears and PMSM falls into chaotic operation.Furthermore,the complex dynamic behaviors are verified by means of simulation.