This paper deals with various multipulse AC-DC converters for improving the power quality in vector-controlled induction motor drives (VCIMDs) at the point of common coupling. These multipulse AC-DC converters are realized using a reduced rating autotransformer. Moreover, DC ripple reinjection is used to double the rectification pulses resulting in an effective harmonic mitigation. The proposed AC-DC converter is able to eliminate up to 21st harmonics in the supply current. The effect of load variation on VCIMD is also studied to demonstrate the effectiveness of the proposed AC-DC converter. A set of power quality indices on input AC mains and on the DC bus for a VCIMD fed from different AC-DC converters is also given to compare their performance.

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Use of conventional two-level pulse width modulation (PWM) inverters provide less distorted current and voltage but at the cost of higher switching losses due to high switching frequencies. Multilevel inverters are emerging as a viable alternative for high power, medium voltage applications. This paper compares total harmonic distortion and switching losses in conventional two-level inverters with multilevel inverters (three-level and five-level) at different switching frequencies. An optimized switching frequency has been obtained for a lower level of total harmonic distortion and switching losses. Diode-clamped, three-phase topology is considered for study. A sinusoidal PWM technique is used to control the switches of the inverter. Simulation study confirms the reduction in harmonic distortion and switching losses as the number of the levels increases.

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This paper deals with a voltage and frequency control of an isolated asynchronous generator feeding 3-phase 4-wire loads in constant power applications where terminal voltage, excitation capacitor, speed and generated power of the generator remain constant under all operating conditions. The proposed controller is functioning as an improved electronic load controller (IELC) to regulate the frequency and as a source of reactive power to regulate the terminal voltage. Three single-phase voltage source converters (VSCs) are connected to each phase of the generator through three single-phase transformers and there is an auxiliary load with a chopper at the self-regulated DC bus of the IELC. These VSCs along with transformers provide their function as a voltage regulator, a harmonic eliminator, a load balancer and a neutral current compensator whereas the chopper and the auxiliary load at the DC bus are used to regulate the frequency. The complete system is modelled and simulated in MATLAB along with Simulink and Power system Block set toolboxes. The simulated results are presented to demonstrate the capability of an isolated generating system driven by uncontrolled pico hydro turbine and feeding 3-phase 4-wire linear/non-linear balanced/unbalanced loads.

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This paper proposes a non-isolated 36-pulse controlled AC-DC converter for medium power rating drives. It involves pulse multiplication in a 12-pulse AC-DC converter. The approach employs a polygon autotransformer arrangement, which results in a near equal leakage reactance in series with each thyristor bridge. The volt-ampere rating of the autotransformer is observed to be small and the converter meets IEEE-519 standard power-quality requirements over a wide range of firing angle.

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Machines never break down by chance. Their operating condition gradually deteriorates and this gradual quantitative deterioration transforms into a failure, manifesting a qualitative change. When a fault takes place, some of the machine parameters are subjected to change. The change in the machine parameter depends on the degree of faults and the interaction with other parameters. In most cases, more than one parameter is subjected to change under abnormal conditions. If these machine parameters can be measured, they give information relating to a developing fault and then maintenance can be planned for the next available shutdown. Therefore, condition monitoring requires measurement to be taken from the machine on a continuous basis and is used to indicate the current working condition of that machine. There are a number of parameters that can be considered for monitoring the machine. For induction machines, monitoring parameters are terminal voltages, line currents, stack temperature of stator, rotor speed, torque, stator frame vibration, bearing vibrations, etc. ^{[1],[2],[3],[4]} This paper discusses the results of the laboratory investigations carried out on 10-hp cage induction motors to identify the machine health by monitoring. A data acquisition system, capable of recording vibration, line currents and line voltages, is designed and fabricated. The signals are sampled at a suitable sampling frequency using an add-on card and are saved in a computer for future use. The vibration signals are measured at a load end bearing of the test motor. The recorded vibration signals are then pre-processed both in time and frequency domain to extract the important features that contain the maximum fault information. The selected features are analysed for their class separation capability using the Fisher criterion. These features are then used as an input to the fault classifier. The fault classifier used in this study is the multi-layered perception trained with a back propagation algorithm. Two networks are trained independently, one with time domain parameters, module-TD, and the other with frequency domain parameters, module-FD. It is found that module-TD gives its best performance for incipient fault detection (100%); however, for medium degree fault, it gives an 85% efficiency. The frequency parameter-based module gives a better performance for both the cases (98 and 95% respectively). However, a combination of the two can be used to enhance the decision ability of the system.

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This paper proposes an optimum speaker-independent, isolated word Hidden Markov Model (HMM) recognizer for the Hindi language. The recognition system is based on the combination of the vector quantization (VQ) technique at the acoustical level and the Markovian modeling at the recognition level. The recognizer consists of three modules - feature extraction, vector quantizer and HMM training and testing modules. The scheme proposed here firstly computes the acoustic features in terms of the Linear Predictive Cepstral LPC coefficients, Mel-Frequency Cepstral coefficients and delta MFCC along with noise and silence detection. Then, codebooks are created using VQ, and finally in the recognition phase, an optimum set of parameters are derived from different phases for getting the highest recognition score. The training and testing database consists of a set of 35 utterances of nine Indian cities/states and 35 utterances of nine digits spoken in Hindi by male and female speakers. The recognition rate was observed to be 98.61%.

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The performance of a modified self-commutating CSI-fed induction motor drive is investigated in this paper. The mathematical model of the complete drive system is developed in the synchronously rotating d-q reference frame. Closed form mathematical expressions are developed for torque, phase voltage, efficiency, power factor, total loss, etc. The steady state performance curves of the drive are obtained for the different operating conditions and are discussed in detail. Experiments are also carried out to investigate the performance and compared with the analytical results.

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This paper presents the experimental evaluation of the 'Specific Absorption Rate' (SAR) reduction in a human head due to radio frequency (RF) shields attached to a mobile handset. Shields of various shapes and sizes were made from a nickel-zinc spinel ferrite. The human head was simulated by a fibre glass container filled with NaCl solution to represent the muscle tissues. An E-field probe was used to measure the electric field strength at various points in the head model with and without the RF shields. The E-field variations in the head model show that the developed ferrite RF shields reduce the 'SAR' effectively.

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In this article, the stability of the closed-loop, controlled matrix converter (MC)-fed induction motor drive system is evaluated by analyzing the migration of eigenvalues of the system state matrix, linearized around the operating point for closed-loop controlled MC-fed induction motor drive. A digital low-pass filter has been applied to the input voltages, and using these filtered voltages for calculating the duty-cycles of the MC, the system stability can be improved.

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In this paper, novel very-large-scale integration (VLSI) algorithms for computing the Discrete Sine Transform (DST) and its inverse (IDST) are proposed. By respectively folding the inputs, the DST kernels are derived to realize it through Infinite-impulse response (IIR) structure. Single folding algorithm provides data throughput two times of that achieved by the conventional methods. The double folding recursive algorithms for DST and IDST have been suggested, which reduce the computation cycles to one forth of that in the single folding method. Moreover, the regular and modular properties of the proposed recursive structures are easily amenable to VLSI implementation.

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