• ARUN KUMAR

      Articles written in Sadhana

    • Modified Berlekamp-Massey algorithm and modelling of discrete-time signals

      S K Mullick Arun Kumar Parag Jain

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      The objective of the present paper is the study of models which view the given 1-D data as the impulse response of a minimal order discrete linear filter with data and coefficients confined to a finite field. This representation is known as “minimal partial realization” problem in linear system theory and has been tackled successfully by Ho and Kalman. Interestingly, the same problem is addressed and solved in a coding theory context by the well-known Berlekamp-Massey (bm) algorithm. We present a modified recursive version of thebm algorithm specially suited to our task of signal modelling. By introducing an absolute error bound, one can further solve the approximation problem computationally. The paper includes a number of examples and a mention of the software for this purpose.

    • Fault diagnosis of machines

      H N Mahabala A T Arun Kumar R R Kurup G Ravi Prakash

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      This paper presents four major approaches for diagnosing machine faults. Given the description of a system to be diagnosed and the observations on the system when it works, the need for diagnosis arises when the observations are different from those expected. The objective of diagnosis is to identify the malfunctioning components in a systematic and efficient way. The four approaches discussed are based on fault-tree, rule, model, and qualitative model. Early diagnosis systems used fault-tree and rule-based approaches. These are efficient in situations where an expert is able to provide the knowledge in the form of associations between symptoms and faults. Model-based and qualitative model-based approaches overcome many of the deficiencies of the earlier approaches. Model-based approaches can take care of situations (faults) not envisageda priori. Also, one can cater to minor variations in design using the same set of components and their interconnections. This paper discusses in each case, how the knowledge is represented and what diagnosis technique is to be adopted, and their relative advantages and disadvantages. Implementation of each method is also discussed.

    • A fuzzy expert system approach using multiple experts for dynamic follow-up of endemic diseases

      Apurba Banerjee Arun Kumar Majumder Anupam Basu

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      In this paper, an architecture oflepdiag — a knowledge-based system for on-line diagnosis and for monitoring prognosis of leprosy is presented. The important features oflepdiag that have been detailed are a multiple expert environment, a homeostatic expert containing the model of immune reaction, a performance evaluator that can compare the observed signs and symptoms with those predicted by the homeostatic expert and a prognostic expert which optimizes the management schedule for the patients. The entire systems is built around a fuzzy expert-system building toolfext to deal with the imprecise knowledge.

    • Analysis of generalized continual-clamp and split-clamp PWM schemes for induction motor drive

      SOUMITRA DAS V S S PAVAN KUMAR HARI ARUN KUMAR G NARAYANAN

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      Continual-clamp pulse width modulation (CCPWM) clamps each phase of a three-phase inverter to one of the two dc buses continually for 60°duration in each half of the fundamental cycle. Split-clamp pulse width modulation (SCPWM) divides the 60° clamping interval into two sub-intervals, which are not necessarily equal, and falling in two different quarter cycles. Whether continual clamp or split clamp, the positioning of the clamping interval in case of CCPWM, and the ratio of splitting the clamping interval in SCPWM – all influencethe waveform quality of the inverter output. This paper derives analytically closed-form expressions for the total RMS harmonic distortion factor and torque ripple factor pertaining to CCPWM with any arbitrary position of the clamping interval (i.e., generalized CCPWM) and also corresponding to SCPWM with any arbitrary ratio of splitting of the clamping interval (i.e., generalized SCPWM). The analytical results are well supported by experimental results on 3-hp and 5-hp induction motor drives.

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