S. Edward Ra jan, P.S. Kannan, K. Muneeswaran, and T. Revathi
Adaptive AC bridge, digital AC bridge, universal AC bridge,impedance measurement, Artificial Neural Network (ANN)
Bridges are the measuring devices used for accurate measurement of impedance. As such, there is no universal bridge circuit that measures impedance of all types of passive components. Moreover, the bridges available cannot be used for high-frequency impedance measurements. This paper proposes an automatic digital AC bridge model, which is considered to be universal and suitable for high- frequency impedance measurement up to 1 MHz. In this adaptive digital AC Bridge, balancing is achieved by means of Artificial Neural Network based on stochastic gradient search algorithm. Among the various gradient search techniques, the Widrow-Hoff’s Least Mean Square (LMS) technique has been chosen as it involves less computational burden. The digital AC bridge operations have been verified by simulation. The simulated system was tested for measuring impedances of pure and impure inductors, capacitors, resistors, and a series combination of an inductance and a capacitance. The effects of various parameters like supply voltage, reference resistance, learning rate, and sampling rate were considered to investigate the performance of universal high-precision AC Bridge, and the results are reported. This model is advantageous over the traditional heuristic methods in terms of higher accuracy, faster convergence, and greater reproducibility and reliability.
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