Projects per year
condition monitoring methodologies that are based on advanced software and requires no extra hardware could be more attractive to industry. In this digest, a condition monitoring methodology that estimates the capacitance value of the dc-link capacitor in a three phase Front-End diode bridge motor drive is proposed. The proposed software methodology is based on Artificial Neural Network (ANN) algorithm. The harmonics of the dc-link voltage are used
as training data to the Artificial Neural Network. Fast Fourier Transform (FFT) of the dc-link voltage is analysed in order to study the impact of capacitance variation on the harmonics order. Laboratory experiments are conducted to
validate the proposed methodology and the error analysis of the estimated results is also studied.
|Title of host publication||Proceedings of 2017 IEEE Energy Conversion Congress and Exposition (ECCE)|
|Number of pages||8|
|Publication date||Oct 2017|
|Publication status||Published - Oct 2017|
|Event||2017 IEEE Energy Conversion Congress and Exposition (ECCE) - Cincinnati, Ohio, United States|
Duration: 1 Oct 2017 → 5 Oct 2017
|Conference||2017 IEEE Energy Conversion Congress and Exposition (ECCE)|
|Period||01/10/2017 → 05/10/2017|
Blaabjerg, F., Munk-Nielsen, S., Iannuzzo, F., Wang, H., Uhrenfeldt, C., Beczkowski, S. M., Zhou, D., Choi, U., Jørgensen, A. B., Vernica, I., Sangwongwanich, A., Christensen, N., Ceccarelli, L., Nielsen, C. K., Bahman, A. S., Pedersen, K., Pedersen, K. B. & Kristensen, P. K.
01/01/2017 → 30/06/2021
01/03/2016 → 31/05/2018