Time evolution of Nd:YAG laser-induced plasma from GdBa2Cu3O7 high-Tc superconductor

In order to characterise the laser ablation process from high-Tc superconductors, the time evolution of plasma produced by a Q-switching Nd:YAG laser from a GdBa2Cu3O7 superconducting sample has been studied using spectroscopic and ion-probe techniques. It has been observed that there is a fairly large delay for the onset of the emission from oxide species in comparison with those from atoms and ions of the constituent elements present in the plasma. Faster decay occurs for emission from oxides and ions compared with that from neutral atoms. These observations support the view that oxides are not directly produced from the target, but are formed by the recombination process while the plasma cools down. Plasma parameters such as temperature and velocity are also evaluated.

Effect of a fluctuating parameter mismatch and the associated time-scales on coupled Rossler oscillators

We study the effect of parameter fluctuations and the resultant multiplicative noise on the synchronization of coupled chaotic systems. We introduce a new quantity, the fluctuation rate Ф as the number of perturbations occurring to the parameter in unit time. It is shown that ϕ is the most significant quantity that determines the quality of synchronization. It is found that parameter fluctuations with high fluctuation rates do not destroy synchronization, irrespective of the statistical features of the fluctuations. We also present a quasi-analytic explanation to the relation between ϕ and the error in synchrony.

Permutation entropy based real-time chatter detection using audio signal in turning process

Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).