Method of Measurement of Capacitance and Dielectric Loss Factor Using Artificial Neural Networks

[1] Cichy, A., Skorkowski, A., Barwinek, S. (2013). Automated quasi-balancing in virtual quasi-balanced circuit designed to capacitance measurements. In 19th Symposium IMEKO TC 4 Symposium and 17th IWADC Workshop, 18-19 July 2013, Barcelona, Spain, 275-280.Search in Google Scholar

[2] Skorkowski, A., Cichy, A. (2009). Virtual capacitance meter based on impedance modulus measurement. In XIX IMEKO World Congress, 6-11 September 2009, Lisbon, Portugal, 648-651.Search in Google Scholar

[3] Amira, H., Hfaiedh, M., Valentin, M. (2009). Quasi-balanced bridge method for the measurements of the impedances. IET Science Measurement & Technology, 3 (6), 403-409.10.1049/iet-smt.2009.0032Search in Google Scholar

[4] Atmanand, M.A., Jagadeesh Kumar, V., Murti, V.G.K. (1996). A microcontroller based quasi-balanced bridge for the measurement of L, C and R. IEEE Transactions on Instrumentation & Measurement, 45 (3), 1-5.10.1109/19.494595Search in Google Scholar

[5] Burbelo, M.I. (2001). Universal quasi-balanced bridges for measuring the parameters of four-element two-terminal networks. Measurement Techniques, 44 (11), 1130-1133.10.1023/A:1014017418854Search in Google Scholar

[6] Atmanand, M.A., Jagadeesh Kumar, V. (1996). A microcontroller based LCR meter. Microprocessors & Micro-Systems, 20, 297-301.10.1016/0141-9331(96)01095-2Search in Google Scholar

[7] Atmanand, M.A., Jagadeesh Kumar, V., Murti, V.G.K. (1995). A novel method of measurement of L and C. IEEE Transactions on Instrumentation & Measurement, 44 (4), 898-903.10.1109/19.392878Search in Google Scholar

[8] Marcuta, C., Fosalau, C., Petrescu, C. (2005). A virtual impedance measuring instruments based on quasi-balanced bridge. In 14th International Symposium on New Technologies in Measurement and 10th Workshop on ADC Modelling and Testing, 12-18 September 2005, Gdynia Maritime University, Poland, Vol. III, 517-523.Search in Google Scholar

[9] Jagadeesh Kumar, V., Sankaran, P., Sudhakar Rao, K. (2003). Measurement of C and tan δ of a capacitor employing PSDs and dual slope DVMs. IEEE Transactions on Instrumentation & Measurement, 52, (5), 1588-1592.10.1109/TIM.2003.817919Search in Google Scholar

[10] Cichy, A. (2013). Non-bridge circuit with double quasi-balancing for measurement of dielectric loss factor. IET Science Measurement & Technology, 7 (5), 274-279.10.1049/iet-smt.2012.0130Search in Google Scholar

[11] Roj, J. (2013). Neural approximation of empirical functions. Acta Physica Polonica A, 124 (3), 554-557.10.12693/APhysPolA.124.554Search in Google Scholar

[12] Hornik, K., Stinchcombe, M., White, H. (1989). Multilayer feedforward networks are universal approximators. Neural Networks, 2, 359-366.10.1016/0893-6080(89)90020-8Search in Google Scholar

[13] Hornik, K. (1991). Approximation capabilities of multilayer feedforward networks. Neural Networks, 4 (2), 251-257.10.1016/0893-6080(91)90009-TSearch in Google Scholar

[14] Haykin, S. (2008). Neural Networks: A Comprehensive Foundation. Third Edition. Prentice Hall.Search in Google Scholar

[15] Gupta, M., Homma, N., Jin, L. (2003) Static and Dynamic Neural Networks: From Fundamentals to Advanced Theory. John Wiley & Sons.10.1002/0471427950Search in Google Scholar

[16] Beale, M.H., Hagan, M.T., Demuth, H.B. (2015). Neural Network Toolbox: User’s Guide. MathWorks Inc.Search in Google Scholar

[17] Hagan, M.T., Menhaj, M. (1994). Training feedforward networks with the Marquardt algorithm. IEEE Transactions on Neural Networks, 5 (6), 989-993.10.1109/72.32969718267874Search in Google Scholar

[18] Glowacz, A., Glowacz, A., Glowacz, Z. (2014). Recognition of monochrome thermal images of synchronous motor with the application of quadtree decomposition and backpropagation neural network. Maintenance and Reliability (Eksploatacja i Niezawodnosc), 16 (1), 92-96.Search in Google Scholar

[19] Roj, J. (2014). Estimation of the artificial neural network uncertainty used for measurand reconstruction in a sampling transducer. IET Science Measurement & Technology, 8 (1), 23-29.10.1049/iet-smt.2013.0035Search in Google Scholar