Characteristics of nonideal operational amplifiers

The departures of the operational amplifiers (OA's) from the ideal performance and their effect on VCV's in the inverting and noninverting mode are discussed. It is found that for the same ideal gain, the bandwidths for the inverting and noninverting modes are different, the former being less. Complete equivalent circuits describing the frequency dependance of the input and output impedances for both modes are given. In particular, the output impedance is shown to be inductive for the frequencies of interest, and this is also confirmed by experimental results.

Effect of amplifier imperfections on active networks

The deviation in the performance of active networks due to practical operational amplifiers (OA) is mainly because of the finite gain bandwidth productBand nonzero output resistanceR_0. The effect ofBandR_0on two OA impedances and single and multi-OA filters are discussed. In filters, the effect ofR_0is to add zeros to the transfer function often making it nonminimum phase. A simple method of analysis has been suggested for 3-OA biquad and coupled biquad circuits. A general method of noise minimization of the generalized impedance converter (GIC), while operating OA's within the prescribed voltage and current limits, is also discussed. The 3-OA biquadratic sections analyzed also exhibit noise behavior and signal handling capacity similar to the GIC. The GIC based structures are found to be better than other configurations both in biquadratic sections and direct realizations of higher order transfer functions.

Noise minimization in RC-active filters using generalized impedance converters

A procedure has been given for minimizing the total output noise of a Generalized Impedance Converter (GIC), subject to constraints dictated by signal handling capability of the Operational Amplifiers and ease of microcircuit fabrication. The noise reduction is achieved only by the adjustment of RC elements of the GIC, and the total output noise after optimization in the example cited is close to the theoretical lower limit. The output noise of a higher-order filter can be reduced by RC-optimizing the individual GIC's of the active realization. Experimental results on a 20–24 kHz channel bank band-pass filter demonstrate the effectiveness of the above procedure.

Topological analysis of general linear networks

A new method of network analysis, a generalization in several different senses of existing methods and applicable to all networks for which a branch-admittance (or impedance) matrix can be formed, is presented. The treatment of network determinants is very general and essentially four terminal rather than three terminal, and leads to simple expressions based on trees of a simple graph associated with the network and matrix, and involving products of low-order, usually(2 times 2)determinants of tree-branch admittances, in addition to tree-branch products as in existing methods. By comparison with existing methods, the total number of trees and of tree pairs is usually considerably reduced, and this fact, together with an easy method of tree-pair sign determination which is also presented, makes the new method simpler in general. The method can be very easily adapted, by the use of infinite parameters, to accommodate ideal transformers, operational amplifiers, and other forms of network constraint; in fact, is thought to be applicable to all linear networks.

Compensator Design for Closed Loop Hall-Effect Current Sensors

Closed loop current sensors used in power electronics applications are expected to have high bandwidth and minimal measurement transients. In this paper, a closed loop compensated Hall-effect current sensor is modeled. The model is used to tune the sensor's compensator. Analytical expression of step response is used to evaluate the performance of the PI compensator in the current sensor. This analysis is used to devise a procedure to design parameters of the PI compensator for fast dynamic response and for small dynamic error. A prototype current sensor is built in the laboratory. Simulations using the model are compared with experimental results to validate the model and to study the variation in performance with compensator parameters. The performance of the designed PI compensator for the sensor is compared with a commercial current sensor. The measured bandwidth of the designed current sensor is above 200 kHz, which is comparable to commercial standards. Implementation issues of PI compensator using operational amplifiers are also addressed.

Effects of mass of charge on loop heat pipe operational characteristics

Experimental results on a loop heat pipe, using R134a as the working fluid, indicates that the liquid inventory in the compensation chamber can significantly influence the operating characteristics. The large liquid inventory in the compensation chamber, under terrestrial conditions, can result in loss of thermal coupling between the compensation chamber and the evaporator core. This causes the operating temperature to increase monotonically. This phenomenon, which has been experimentally observed, is reported in this paper. A theoretical model to predict the steady-state performance of a loop heat pipe with a weak thermal link between the compensation chamber and the core, as observed in the experiment, is also presented. The predicted and the experimentally determined temperatures correlate well.

Nonideal negative resistors and capacitors using an operational amplifier

Negative impedance converters (NIC's) may be used to realize negative driving-point impedances. The effect of the nonideal characteristics of the operational amplifier such as finite frequencydependent gain and output impedance on the performance of the negative impedances is analyzed. Detailed equivalent circuits showing the additional positive or negative inductive impedances due to the nonideal characteristics are given for negative resistance and negative capacitance realizations, and their relative performances are compared. The experimental results confirm the validity of the equivalent circuits. The effect of the slew rate of the operational amplifier on the maximum signal-handling capability (SHC) of the negative impedances at high frequencies is studied. Practical design considerations for achieving wider bandwidth as well as improved SHC are discussed.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

WOMM: A Weak Operational Memory Model

Memory models of shared memory concurrent programs define the values a read of a shared memory location is allowed to see. Such memory models are typically weaker than the intuitive sequential consistency semantics to allow efficient execution. In this paper, we present WOMM (abbreviation for Weak Operational Memory Model) that formally unifies two sources of weak behavior in hardware memory models: reordering of instructions and weakly consistent memory. We show that a large number of optimizations are allowed by WOMM. We also show that WOMM is weaker than a number of hardware memory models. Consequently, if a program behaves correctly under WOMM, it will be correct with respect to those hardware memory models. Hence, WOMM can be used as a formally specified abstraction of the hardware memory models. Moreover; unlike most weak memory models, WOMM is described using operational semantics, making it easy to integrate into a model checker for concurrent programs. We further show that WOMM has an important property - it has sequential consistency semantics for datarace-free programs.

Operational experience on a grid connected 100 kWe biomass gasification power plant in Karnataka, India

The paper reports the operational experience from a 100 kWe gasification power plant connected to the grid in Karnataka. Biomass Energy for Rural India (BERI) is a program that implemented gasification based power generation with an installed capacity of 0.88 MWe distributed over three locations to meet the electrical energy needs in the district of Tumkur. The operation of one 100 kWe power plant was found unsatisfactory and not meeting the designed performance. The Indian Institute of Science, Bangalore, the technology developer, took the initiative to ensure the system operation, capacity building and prove the designed performance. The power plant connected to the grid consists of the IISc gasification system which includes reactor, cooling, cleaning system, fuel drier and water treatment system to meet the producer gas quality for an engine. The producer gas is used as a fuel in Cummins India Limited, GTA 855 G model, turbo charged engine and the power output is connected to the grid. The system has operated for over 1000 continuous hours, with only about 70 h of grid outages. The total biomass consumption for 1035 h of operation was 111 t at an average of 107 kg/h. Total energy generated was 80.6 MWh reducing over loot of CO(2) emissions. The overall specific fuel consumption was about 1.36 kg/kWh, amounting to an overall efficiency from biomass to electricity of about 18%. The present operations indicate that a maintenance schedule for the plant can be at the end of 1000 h. The results for another 1000 h of operation by the local team are also presented. (C) 2011 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

Arithmetic coding based lossless compression schemes for power system steady state operational data

Introduction of processor based instruments in power systems is resulting in the rapid growth of the measured data volume. The present practice in most of the utilities is to store only some of the important data in a retrievable fashion for a limited period. Subsequently even this data is either deleted or stored in some back up devices. The investigations presented here explore the application of lossless data compression techniques for the purpose of archiving all the operational data - so that they can be put to more effective use. Four arithmetic coding methods suitably modified for handling power system steady state operational data are proposed here. The performance of the proposed methods are evaluated using actual data pertaining to the Southern Regional Grid of India. (C) 2012 Elsevier Ltd. All rights reserved.

Operational inferences on VANETs in 802.16e and 802.11p with improved performance by Congestion alert

Mobile WiMAX is a burgeoning network technology with diverse applications, one of them being used for VANETs. The performance metrics such as Mean Throughput and Packet Loss Ratio for the operations of VANETs adopting 802.16e are computed through simulation techniques. Next we evaluated the similar performance of VANETs employing 802.11p, also known as WAVE (Wireless Access in Vehicular Environment). The simulation model proposed is close to reality as we have generated mobility traces for both the cases using a traffic simulator (SUMO), and fed it into network simulator (NS2) based on their operations in a typical urban scenario for VANETs. In sequel, a VANET application called `Street Congestion Alert' is developed to assess the performances of these two technologies. For this application, TraCI is used for coupling SUMO and NS2 in a feedback loop to set up a realistic simulation scenario. Our inferences show that the Mobile WiMAX performs better than WAVE for larger network sizes.

Influence of operational and geometrical parameters on the performance of twin thermoacoustic prime mover

Thermoacoustics is the interaction between heat and sound, which are useful in designing heat engines and heat pumps. Research in the field of thermoacoustics focuses on the demand to improve the performance which is achieved by altering operational, geometrical and fluid parameters. The present study deals with improving the performance of twin thermoacoustic prime mover, which has gained the significant importance in the recent years for the production of high amplitude sound waves. The performance of twin thermoacoustic prime mover is evaluated in terms of onset temperature difference, resonance frequency and pressure amplitude of the acoustic waves by varying the resonator length and charge pressures of fluid medium nitrogen. DeltaEC, the free simulation software developed by LANL, USA is employed in the present study to simulate the performance of twin thermoacoustic prime mover. Experimental and simulated results are compared and the deviation is found to be within 10%.

Improving the Sensitivity and Bandwidth of In-Plane Capacitive Microaccelerometers Using Compliant Mechanical Amplifiers

This paper presents a method to enhance both the sensitivity and bandwidth of in-plane capacitive micromachined accelerometers by using compliant mechanical amplifiers, and thus obviating the compromise between the sensitivity and bandwidth. Here, we compare one of the most sensitive single-axis capacitive accelerometers and another with large resonant frequency reported in the literature with the modified designs that include displacement-amplifying compliant mechanisms (DaCMs) occupying the same footprint and under identical conditions. We show that 62% improvement in sensitivity and 34% improvement in bandwidth in the former, and 27% and 25% in the latter can be achieved. Also presented here is a dual-axis accelerometer that uses a suspension that decouples and amplifies the displacements along the two in-plane orthogonal axes. The new design was microfabricated, packaged, and tested. The device is 25-mu m thick with the interfinger gap as large as 4 m. Despite the simplicity of the microfabrication process, the measured axial sensitivity (static) of about 0.58 V/g for both the axes was achieved with a cross-axis sensitivity of less than +/- 2%. The measured natural frequency along the two in-plane axes was 920 Hz. Displacement amplification of 6.2 was obtained using the DaCMs in the dual-axis accelerometer. 2013-0083]