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.

Antibody Based Diagnostic for Detection Of Vibrios and their Biological Control using Antagonistic Bacteria in Macrobrachium Rosenbergii Larval Rearing Systems

The main objective of the work undertaken here was to develop an appropriate microbial technology to protect the larvae of M.rosenbergii in hatchery from vibriosis. This technology precisely is consisted of a rapid detection system of vibrios and effective antagonistic probiotics for the management of vibrios. The present work was undertaken with the realizations that to stabilize the production process of commercial hatcheries an appropriate, comprehensive and fool proof technology is required primarily for the rapid detection of Vibrio and subsequently for its management. Nine species of Vibrio have been found to be associated with larvae of M. rosenbergii in hatchery. Haemolytic assay of the Vibrio and Aeromonas on prawn blood agar showed that all isolates of V. alginolyticus and Aeromonas sp., from moribund, necrotized larve were haemolytic and the isolates of V.cholerae, V.splendidus II, V.proteolyticus and V.fluvialis from the larvae obtained from apparently healthy larval rearing systems were non-haemolytic. Hydrolytic enzymes such as lipase, chitinase and gelatinase were widespread amongst the Vibrio and Aeromonas isolates. Dominance of V.alginolyticus among the isolates from necrotic larvae and the failure in isolating them from rearing water strongly suggest that they infect larvae and multiply in the larval body and cause mortality in the hatchery. The observation suggested that the isolate V. alginolyticus was a pathogen to the larvae of M.rosenbergii. To sum up, through this work, nine species of Vibrio and genus Aeromonas associated with M.rosenbergii larval rearing systems could be isolated and segregated based on the haemolytic activity and the antibodies (PA bs) for use in diagnosis or epidemiological studies could be produced, based on a virulent culture of V.alginolyticus. This could possibly replace the conventional biochemical tests for identification. As prophylaxis to vibriosis, four isolates of Micrococcus spp. and an isolate of Pseudomonas sp. could be obtained which could possibly be used as antagonistic probiotics in the larval rearing system of M.rosenbergii.

‘Reliability Concepts in Quantile-based Analysis of Lifetime Data

Reliability analysis is a well established branch of statistics that deals with the statistical study of different aspects of lifetimes of a system of components. As we pointed out earlier that major part of the theory and applications in connection with reliability analysis were discussed based on the measures in terms of distribution function. In the beginning chapters of the thesis, we have described some attractive features of quantile functions and the relevance of its use in reliability analysis. Motivated by the works of Parzen (1979), Freimer et al. (1988) and Gilchrist (2000), who indicated the scope of quantile functions in reliability analysis and as a follow up of the systematic study in this connection by Nair and Sankaran (2009), in the present work we tried to extend their ideas to develop necessary theoretical framework for lifetime data analysis. In Chapter 1, we have given the relevance and scope of the study and a brief outline of the work we have carried out. Chapter 2 of this thesis is devoted to the presentation of various concepts and their brief reviews, which were useful for the discussions in the subsequent chapters .In the introduction of Chapter 4, we have pointed out the role of ageing concepts in reliability analysis and in identifying life distributions .In Chapter 6, we have studied the first two L-moments of residual life and their relevance in various applications of reliability analysis. We have shown that the first L-moment of residual function is equivalent to the vitality function, which have been widely discussed in the literature .In Chapter 7, we have defined percentile residual life in reversed time (RPRL) and derived its relationship with reversed hazard rate (RHR). We have discussed the characterization problem of RPRL and demonstrated with an example that the RPRL for given does not determine the distribution uniquely

A Quantile based analysis of income data

Dept. of Statistics, CUSAT

Analysis of System Signals Based on Cross Recurrence Method for System Dynamics Characterization

Natural systems are inherently non linear. Recurrent behaviours are typical of natural systems. Recurrence is a fundamental property of non linear dynamical systems which can be exploited to characterize the system behaviour effectively. Cross recurrence based analysis of sensor signals from non linear dynamical system is presented in this thesis. The mutual dependency among relatively independent components of a system is referred as coupling. The analysis is done for a mechanically coupled system specifically designed for conducting experiment. Further, cross recurrence method is extended to the actual machining process in a lathe to characterize the chatter during turning. The result is verified by permutation entropy method. Conventional linear methods or models are incapable of capturing the critical and strange behaviours associated with the dynamical process. Hence any effective feature extraction methodologies should invariably gather information thorough nonlinear time series analysis. The sensor signals from the dynamical system normally contain noise and non stationarity. In an effort to get over these two issues to the maximum possible extent, this work adopts the cross recurrence quantification analysis (CRQA) methodology since it is found to be robust against noise and stationarity in the signals. The study reveals that the CRQA is capable of characterizing even weak coupling among system signals. It also divulges the dependence of certain CRQA variables like percent determinism, percent recurrence and entropy to chatter unambiguously. The surrogate data test shows that the results obtained by CRQA are the true properties of the temporal evolution of the dynamics and contain a degree of deterministic structure. The results are verified using permutation entropy (PE) to detect the onset of chatter from the time series. The present study ascertains that this CRP based methodology is capable of recognizing the transition from regular cutting to the chatter cutting irrespective of the machining parameters or work piece material. The results establish this methodology to be feasible for detection of chatter in metal cutting operation in a lathe.

Performance Assessment of Sandwich Structures with Debonds and Dents

A sandwich construction is a special form of the laminated composite consisting of light weight core, sandwiched between two stiff thin face sheets. Due to high stiffness to weight ratio, sandwich construction is widely adopted in aerospace industries. As a process dependent bonded structure, the most severe defects associated with sandwich construction are debond (skin core bond failure) and dent (locally deformed skin associated with core crushing). Reasons for debond may be attributed to initial manufacturing flaws or in service loads and dent can be caused by tool drops or impacts by foreign objects. This paper presents an evaluation on the performance of honeycomb sandwich cantilever beam with the presence of debond or dent, using layered finite element models. Dent is idealized by accounting core crushing in the core thickness along with the eccentricity of the skin. Debond is idealized using multilaminate modeling at debond location with contact element between the laminates. Vibration and buckling behavior of metallic honeycomb sandwich beam with and without damage are carried out. Buckling load factor, natural frequency, mode shape and modal strain energy are evaluated using finite element package ANSYS 13.0. Study shows that debond affect the performance of the structure more severely than dent. Reduction in the fundamental frequencies due to the presence of dent or debond is not significant for the case considered. But the debond reduces the buckling load factor significantly. Dent of size 8-20% of core thickness shows 13% reduction in buckling load capacity of the sandwich column. But debond of the same size reduced the buckling load capacity by about 90%. This underscores the importance of detecting these damages in the initiation level itself to avoid catastrophic failures. Influence of the damages on fundamental frequencies, mode shape and modal strain energy are examined. Effectiveness of these parameters as a damage detection tool for sandwich structure is also assessed