Development of Time - Frequency Techniques for Sonar Applications

Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.

Recurrence Quantification Analysis of System Signals for Detecting Tool and Chatter in Turning

In this thesis, the applications of the recurrence quantification analysis in metal cutting operation in a lathe, with specific objective to detect tool wear and chatter, are presented.This study is based on the discovery that process dynamics in a lathe is low dimensional chaotic. It implies that the machine dynamics is controllable using principles of chaos theory. This understanding is to revolutionize the feature extraction methodologies used in condition monitoring systems as conventional linear methods or models are incapable of capturing the critical and strange behaviors associated with the metal cutting process.As sensor based approaches provide an automated and cost effective way to monitor and control, an efficient feature extraction methodology based on nonlinear time series analysis is much more demanding. The task here is more complex when the information has to be deduced solely from sensor signals since traditional methods do not address the issue of how to treat noise present in real-world processes and its non-stationarity. In an effort to get over these two issues to the maximum possible, this thesis adopts the recurrence quantification analysis methodology in the study since this feature extraction technique is found to be robust against noise and stationarity in the signals.The work consists of two different sets of experiments in a lathe; set-I and set-2. The experiment, set-I, study the influence of tool wear on the RQA variables whereas the set-2 is carried out to identify the sensitive RQA variables to machine tool chatter followed by its validation in actual cutting. To obtain the bounds of the spectrum of the significant RQA variable values, in set-i, a fresh tool and a worn tool are used for cutting. The first part of the set-2 experiments uses a stepped shaft in order to create chatter at a known location. And the second part uses a conical section having a uniform taper along the axis for creating chatter to onset at some distance from the smaller end by gradually increasing the depth of cut while keeping the spindle speed and feed rate constant.The study concludes by revealing the dependence of certain RQA variables; percent determinism, percent recurrence and entropy, to tool wear and chatter unambiguously. The performances of the results establish this methodology to be viable for detection of tool wear and chatter in metal cutting operation in a lathe. The key reason is that the dynamics of the system under study have been nonlinear and the recurrence quantification analysis can characterize them adequately.This work establishes that principles and practice of machining can be considerably benefited and advanced from using nonlinear dynamics and chaos theory.

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.

Studies on electroluminescence using Powder and thin film devices

The subject of electroluminescence has currently acquired great importance because of its potential applications in display systems of a wide variety. A large number of scientists working in commercial, governmental as well as academic institutions all over the world are at present engaged in the intense effort to develop new and efficient phosphor materials and electroluminescent devices. This thesis presents the work carried out by the author in this field during the past few years. The studies discussed in this thesis are mostly confined to the development of some new phosphor materials, their uses in powder and thin film electroluminescent devices and to their electrical and spectral characteristics. Care has been taken to bring' out the physics involved in all the above aspects of the phenomenon

A Writer Identification System For Handwritten Malayalam Documents

Handwriting is an acquired tool used for communication of one's observations or feelings. Factors that inuence a person's handwriting not only dependent on the individual's bio-mechanical constraints, handwriting education received, writing instrument, type of paper, background, but also factors like stress, motivation and the purpose of the handwriting. Despite the high variation in a person's handwriting, recent results from different writer identification studies have shown that it possesses sufficient individual traits to be used as an identification method. Handwriting as a behavioral biometric has had the interest of researchers for a long time. But recently it has been enjoying new interest due to an increased need and effort to deal with problems ranging from white-collar crime to terrorist threats. The identification of the writer based on a piece of handwriting is a challenging task for pattern recognition. The main objective of this thesis is to develop a text independent writer identification system for Malayalam Handwriting. The study also extends to developing a framework for online character recognition of Grantha script and Malayalam characters

" Nonlinear Signal Processing of Electroencephalogram .' Application in the Study of Neurodynamics. "

Interfacings of various subjects generate new field ofstudy and research that help in advancing human knowledge. One of the latest of such fields is Neurotechnology, which is an effective amalgamation of neuroscience, physics, biomedical engineering and computational methods. Neurotechnology provides a platform to interact physicist; neurologist and engineers to break methodology and terminology related barriers. Advancements in Computational capability, wider scope of applications in nonlinear dynamics and chaos in complex systems enhanced study of neurodynamics. However there is a need for an effective dialogue among physicists, neurologists and engineers. Application of computer based technology in the field of medicine through signal and image processing, creation of clinical databases for helping clinicians etc are widely acknowledged. Such synergic effects between widely separated disciplines may help in enhancing the effectiveness of existing diagnostic methods. One of the recent methods in this direction is analysis of electroencephalogram with the help of methods in nonlinear dynamics. This thesis is an effort to understand the functional aspects of human brain by studying electroencephalogram. The algorithms and other related methods developed in the present work can be interfaced with a digital EEG machine to unfold the information hidden in the signal. Ultimately this can be used as a diagnostic tool.

In vivo screening of mangrove plants for anti WSSV activity in Penaeus monodon, and evaluation of Ceriops tagal as a potential source of antiviral molecules

The objective of the study was to find out a natural way to fight white spot syndrome virus (WSSV) in cultured shrimps, as the present scenario necessitated an organic remedy for the devastating pathogen in crustaceans. Under this research programme seven mangrove plants were collected, identified and aqueous extracts screened for their protective effect on the giant tiger shrimp Penaeus monodon against WSSV. The experimental design consisted two modes of application, such as exposure of the virus to the extract and injection challenge, and oral administration of the extract coated feed followed by oral challenge. All experimental animals were monitored through a nested diagnostic PCR analysis. Of the seven mangrove extracts screened aqueous extract from Ceriops tagal imparted total protection to shrimp from WSSV when challenged by both methods. Shrimps administered with the aqueous extract from C. tagal were devoid of virions. The HPLC fingerprint of the aqueous extracts from C. tagal showed more than 25 peaks and 7 of them were larger and well separated. Preliminary phytochemical analysis revealed the presence of alkaloids, flavonoids, polyphenolics, cardiac glycosides, saponins and sterols. The study indicated suitability of the aqueous extract of C. tagal as a possible prophylaxis for WSSV infection in shrimp. This is the first report on the anti WSSV property of the mangrove plant C. tagal

In vivo screening of mangrove plants for anti WSSV activity in Penaeus monodon, and evaluation of Ceriops tagal as a potential source of antiviral molecules

The objective of the study was to find out a natural way to fight white spot syndrome virus (WSSV) in cultured shrimps, as the present scenario necessitated an organic remedy for the devastating pathogen in crustaceans. Under this research programme seven mangrove plants were collected, identified and aqueous extracts screened for their protective effect on the giant tiger shrimp Penaeus monodon against WSSV. The experimental design consisted two modes of application, such as exposure of the virus to the extract and injection challenge, and oral administration of the extract coated feed followed by oral challenge. All experimental animals were monitored through a nested diagnostic PCR analysis. Of the seven mangrove extracts screened aqueous extract from Ceriops tagal imparted total protection to shrimp from WSSV when challenged by both methods. Shrimps administered with the aqueous extract from C. tagal were devoid of virions. The HPLC fingerprint of the aqueous extracts from C. tagal showed more than 25 peaks and 7 of them were larger and well separated. Preliminary phytochemical analysis revealed the presence of alkaloids, flavonoids, polyphenolics, cardiac glycosides, saponins and sterols. The study indicated suitability of the aqueous extract of C. tagal as a possible prophylaxis for WSSV infection in shrimp. This is the first report on the anti WSSV property of the mangrove plant C. tagal

Development and microwave characterization of selected biocompatible materials and conducting polymers

The 20th century witnessed the extensive use of microwaves in industrial, scientific and medical fields. The major hindrance to many developments in the ISM field is the lack of knowledge about the effect of microwaves on materials used in various applications. The study of the interaction of microwaves with materials demanded the knowledge of the dielectric properties of these materials. However, the dielectric properties of many of these materials are still unknown or less studied. This thesis is an effort to shed light into the dielectric properties of some materials which are used in medical, scientific and industrial fields. Microwave phantoms are those materials used in microwave simulation applications. Effort has been taken to develop and characterize low cost, eco-friendly phantoms from Biomaterials and Bioceramics. The interaction of microwaves with living tissues paved way to the development of materials for electromagnetic shielding. Materials with good conductivity/absorption properties could be used for EMI shielding applications. Conducting polymer materials are developed and characterized in this context. The materials which are developed and analyzed in this thesis are Biomaterials, Bioceramics and Conducting polymers. The use of materials of biological origin in scientific and medical applications provides an eco-friendly pathway. The microwave characterization of the materials were done using cavity material perturbation method. Low cost and ecofriendly biomaterial films were developed from Arrowroot and Chitosan. The developed films could be used in applications such as microwave phantom material, capsule material in pharmaceutical applications, trans-dermal patch material and eco-friendly Band-Aids. Bioceramics with better bioresorption and biocompatibility were synthesized. Bioceramics such as Hydroxyapatite, Beta tricalcium phosphate and Biphasic Calcium Phosphate were studied. The prepared bioceramics could be used as phantom material representing Collagen, Bone marrow, Human abdominal wall fat and Human chest fat. Conducting polymers- based on Polyaniline, are developed and characterized. The developed materials can be used in electromagnetic shielding applications such as in anechoic chambers, transmission cables etc