Water characteristics and current structure of the intermediate waters in the arabian sea

At intermediate depths of the Arabian Sea, the circulation and characteristics of water are more influenced by the high saline waters from the north and low saline waters from the south of equator. The interaction of these waters which greatly differ in characteristics is less understood compared to that at the upper layers. An understanding of the nature of the intermediate waters is of vital importance not only because of the unusual characteristics of the waters but also due to the influx of the different water masses from the neighbouring Red Sea and Persian Gulf. Hence, in the present investigation, it is proposed to study the water characteristics and current structure of the intermediate waters in the Arabian Sea through the distribution of the water properties on the isanosteric surfaces of 100, 80, 60 and 4O—cl/t, vertical sections, and scatter diagrams An attempt is also made to present the potential vorticity between different steric levels to understand the circulation and mixing processes. Data collected during and subsequent to International Indian Ocean Expedition (IIOE) are used for this study. The thesis has been divided into six chapters with further sub divisions

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.