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.

Applications of cardanol in rubber processing

This research project explores the utilization of cardanol in various capacities for rubber processing. Cardanol is a phenol with a long side chain in the meta position of the benzene ring. It is obtained by the vacuum distillation of cashew Hut shell liquid (CNSL) which is a cheap agro-byproduct. In this study, the plasticizer property of cardanol was investigated in silica filled and HAF black filled NR, NBR, EPDM and CR by comparing cure characteristics and mechanical properties of vulcanizates containing conventional plasticizer with those containing cardanol as plasticizer. The co-activator, antioxidant and accelerator properties were investigated in gum samples of NR, NBR, EPDM and CR by comparing the properties of vulcanizates which contain conventional co-activator, antioxidant and accelerator with those in which each of them was replaced by cardanol. The general effectiveness of cardanol was investigated by determination of cure time , measurement of physical and mechanical properties, ageing studies, crosslink density, extractability, FTIR spectra, TGA etc.The results show that cardanol can be a substitute for aromatic oil in both silica filled and HAF black filled NR. Again, it can replace dioctyl phthalate in both silica filled and HAF black filled NBR. Similarly, cardanol Can replace naphthenic oil in silica filled as well as HAF black filled EPDM and CR. The cure characteristics and mechanical properties are comparable in all the eight cases. The co-activator property of cardanol is comparable to stearic acid in all the four rubbers. The cure characteristics and mechanical properties in this case are also comparable. The antioxidant ,property of cardanol is comparable to TQ in all the four rubbers. The antioxidant property of cardanol is comparable to TQ in all the four case of NBR and EPDM.The accelerator property of cardarlol is comparable with CBS in the case of NBR and EPDM. No accelerator property is observed in the case of NR. The accelerator property of cardanol in CR is not negligible when compared with TMTD.

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).