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).

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 and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

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.

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.

Rights of the Prisoner: An Evolving Jurisprudence

Imprisonment is the most common method of punishment resorted to by almost all legal systems.The new theories of crime causation propounded in the latter half of the nineteenth century gave rise to the feeling that the prisons could be used as appropriate institutions for reforming the offenders. It called for individualisation of punishment.As a result of international movements for humanisation of prisons the judiciary' in tine common law countries started taking active interest in prisoner's treatment.Various studies reveal that much has been done in America to improve the lot of prisoners and to treat them as human beings.The courts there have gone to the extent of saying that there is no iron curtain between a prisoner and the constitution. Most of the rights available to citizens except those which they cannot enjoy due to the conditions of incarceration have also been granted to prisoner.In India also the judiciary has come forward to protect the rights of the prisoners.Maneka Gandhi is a turning point in prisoner's rights.The repeated intervention of courts in prison administration project the view that prisoners have been denied the basic human rights.The High Courts and the Supreme Court of India have been gradually exercising jurisdiction ixl assuming prison justice, including improving the quality of food and amenities, payment of wages and appropriate standards of medical care. Access to courts must be made easier to the aggrieved prisoners.The government should come forward along with some public spirited citizens and voluntary organisations to form a "discharged prisoner“ aid society. The society should exploit opportunities for rehabilitation of prisoners after their release.Most of the prison buildings in the State of Kerala are ill-equipped, ill furnished and without proper ventilation or sanitation and with insufficient water supply arrangements.In India prisoners and prisons today are governed by the old central legislations like Prisons Act l894 Prisoners Act 1900 and the Transfer of Prisoners Act 1950.

" Studies on Laser induced Phatothermal Phenomena in Selected Organic Compounds and Fullerenes"

In the pre—laser era it was difficult to believe that the optical properties of a medium depend upon the intensity of the radiation incident on it. The basis for this conclusion is that the electric field strength associated with the conventional light sources used before the advent of lasers was much smaller than (103 V/cm) the field sttrengths of atomic or interatomic fields (2 107 —- 10” V/cm). The radiation with such low intensity is not able to affect atomic fields to the extent of changing optical parameters. The invention of laser in 1960 was a turning point. The high degree of coherence of the laser radiation provides high spatial concentration of optical power. With the availability of the femtosecond lasers it has become possible to get extremely high peak powers 2 1013 W/cmz). At such high fields, the relationship between electric ‘polarization P and the electric field strength E ceases to be linear and several nonlinear effects begin to occur. Nonlinear absorption, a branch of nonlinear optics, refers to the interaction between radiation and matter accompanied by absorption of more than one photon. Nonlinear absorption has acquired great importance after the invention of high power lasers. One of the objectives of the present work is to investigate the nonlinear absorption processes occurring in fullerene, selected organic solvents and laser dyes. Fullerenes and laser dyes were chosen because of their highly nonlinear behaviour. Fullerenes, the most beautiful among molecules, offer fascinating field of research owinglto their significant structural properties. As toluene, benzene and carbon disulphide are themost widely used solvents for fullerenes, it seems important to study the nonlinear properties of these liquids as well. Like fullerenes, laser dyes also possess highly delocalized 7r electrons which are responsible for their nonlinear absorption. Dye lasers were the fulfillment of an experimenter’s pipe dream - to have a laser that is easily tunable over a wide range of wavelengths. A better understandingof the photophysical properties of laser dyes can significantly enhance the development and technology of dye lasers. We studied the nonlinear absorption properties of two rhodamine dyes to have some insight into their nonlinear optical properties.

Channel Adaptive MAC Protocol with Traffic-Aware Distributed Power Management in Wireless Sensor Networks-Some Performance Issues

In Wireless Sensor Networks (WSN), neglecting the effects of varying channel quality can lead to an unnecessary wastage of precious battery resources and in turn can result in the rapid depletion of sensor energy and the partitioning of the network. Fairness is a critical issue when accessing a shared wireless channel and fair scheduling must be employed to provide the proper flow of information in a WSN. In this paper, we develop a channel adaptive MAC protocol with a traffic-aware dynamic power management algorithm for efficient packet scheduling and queuing in a sensor network, with time varying characteristics of the wireless channel also taken into consideration. The proposed protocol calculates a combined weight value based on the channel state and link quality. Then transmission is allowed only for those nodes with weights greater than a minimum quality threshold and nodes attempting to access the wireless medium with a low weight will be allowed to transmit only when their weight becomes high. This results in many poor quality nodes being deprived of transmission for a considerable amount of time. To avoid the buffer overflow and to achieve fairness for the poor quality nodes, we design a Load prediction algorithm. We also design a traffic aware dynamic power management scheme to minimize the energy consumption by continuously turning off the radio interface of all the unnecessary nodes that are not included in the routing path. By Simulation results, we show that our proposed protocol achieves a higher throughput and fairness besides reducing the delay

Molecular Epidemiology of Escherichia coli isolates from Environmental, Food and Clinical Sources

In the present study diversity of E. coli in the water samples of Cochin estuary were studied for a period of 3 years ranging from January 2010- December 2012. The stations were selected based on the closeness to satellite townships and waste input. Two of the stations (Chitoor and Thevara) were fixed upstream, two in the central part of the estuary namely Bolgatty and Off Marine Science Jetty, and one at the Barmouth. Diversity was assessed in terms of serotypes, phylogenetic groups and genotypes. Two groups of seafood samples such as fish and shellfish collected from the Cochin estuary were used for isolation of E. coli. One hundred clinical E. coli isolates were collected from one public health centre, one hospital and five medical labs in and around Cochin City, Kerala. From our results it was clear that pathogen cycling is occurring through food, water and clinical sources. Pathogen cycling through food is very common and fish and shellfish that harbour these strains might pose potential health risk to consumer. Estuarine environment is a melting pot for various kinds of wastes, both organic and inorganic. Mixing up of waste water from various sources such as domestic, industries, hospitals and sewage released into these water bodies resulting in the co-existence of E. coli from various sources thus offering a conducive environment for horizontal gene transfer. Opportunistic pathogens might acquire genes for drug resistance and virulence turning them to potential pathogens. Prevalence of ExPEC in the Cochin estuary, pose threat to people who use this water for fishing and recreation. Food chain also plays an important role in the transit of virulence genes from the environments to the human. Antibiotic resistant E. coli are widespread in estuarine water, seafood and clinical samples, for reasons well known such as indiscriminate use of antibiotics in animal production systems, aquaculture and human medicine. Since the waste water from these sources entering the estuary provides selection pressure to drug resistant mutants in the environment. It is high time that the authorities concerned should put systems in place for monitoring and enforcement to curb such activities. Microbial contamination can limit people’s enjoyment of coastal waters for contact recreation or shellfish-gathering. E. coli can make people sick if they are present in high levels in water used for contact recreation or shellfish gathering. When feeding, shellfish can filter large volumes of seawater, so any microorganisms present in the water become accumulated and concentrated in the shellfish flesh. If E. coli contaminated shellfish are consumed the impact to human health includes gastroenteritis, urinary tract infections (UTIs), and bacteraemia. In conclusion, the high prevalence of various pathogenic serotypes and phylogenetic groups, multidrug-resistance, and virulence factor genes detected among E. coli isolates from stations close to Cochin city is a matter of concern, since there is a large reservoir of antibiotic resistance genes and virulence traits within the community, and that the resistance genes and plasmid-encoded genes for virulence were easily transferable to other strains. Given the severity of the clinical manifestations of the disease in humans and the inability and/or the potential risks of antibiotic administration for treatment, it appears that the most direct and effective measure towards prevention of STEC and ExPEC infections in humans and ensuring public health may be considered as a priority.