Hierarchical Extreme Learning Machine-Polynomial Based Low Valued Capacitance Measurement Using Frequency Synthesizer-Vector Voltmeter

作者：Sarkar Gautam^*; Chatterjee Amitava; Rakshit Anjan; Bhattacharya Kesab

来源：IEEE Transactions on Instrumentation and Measurement, 2014, 63(9): 2180-2187.

DOI：10.1109/TIM.2014.2307991

• Capacitance measurement
• extreme learning machine (ELM)
• frequency synthesizer-vector voltmeter (FSVV)
• polynomial

This present paper describes the development of a capacitance measurement system in the picofarad region. The system uses an universal serial bus port-based arrangement in conjunction with an indigenously developed Programmable Intelligent Computer microcontroller-based frequency synthesizer-vector voltmeter that can be used to measure the voltage in vector form and the capacitance can be determined using circuit solution technique. An intelligent two-layered, hierarchical reinforcement-based instrumentation scheme is proposed that can be integrated along with the original measurements to significantly improve the system performance. In layer 1, an extreme learning machine-based supervised phase reinforcement scheme is employed to improve the accuracy of the voltage measurement. Subsequently, in layer 2, local polynomial-based reinforcements are employed to improve both the resistive and reactive part measurements in the unknown capacitance. Three variants of ELM-based reinforcements are implemented for capacitance measurements in the range 100-10 000 pF and the utility of the hybrid ELM-polynomial-based reinforcements for such measurements is aptly demonstrated.

• 出版日期2014-9