Power conversion systems for wireless power transfer (WPT) applications have demanding requirements for continuity of service, besides being operated with stressing environmental conditions. Diagnostic and prognostic programs are thus quite useful and this work shows a novel approach based on the analysis of spectra of an autoregressive (AR) model to recognize a wide range of faulty devices, including incipient faults, when deviations from nominal parameters begin to manifest. AR modeling provides cleaner and easier to interpret spectra, where only the salient features remain, and they are more sensitive to variations in the corresponding time domain waveforms. A log spectral distance is calculated that successfully separates healthy and faulty states of the feeding single-phase inverter, even in challenging scenarios of poor signal-to-noise ratio.

Diversi R., Sandrolini L., Simonazzi M., Speciale N., Mariscotti A. (2024). Diagnostics on Power Electronics Converters by Means of Autoregressive Modelling. ELECTRONICS, 13(15), 1-21 [10.3390/electronics13153083].

Diagnostics on Power Electronics Converters by Means of Autoregressive Modelling

Diversi R.;Sandrolini L.
;
Simonazzi M.;Speciale N.;
2024

Abstract

Power conversion systems for wireless power transfer (WPT) applications have demanding requirements for continuity of service, besides being operated with stressing environmental conditions. Diagnostic and prognostic programs are thus quite useful and this work shows a novel approach based on the analysis of spectra of an autoregressive (AR) model to recognize a wide range of faulty devices, including incipient faults, when deviations from nominal parameters begin to manifest. AR modeling provides cleaner and easier to interpret spectra, where only the salient features remain, and they are more sensitive to variations in the corresponding time domain waveforms. A log spectral distance is calculated that successfully separates healthy and faulty states of the feeding single-phase inverter, even in challenging scenarios of poor signal-to-noise ratio.
2024
Diversi R., Sandrolini L., Simonazzi M., Speciale N., Mariscotti A. (2024). Diagnostics on Power Electronics Converters by Means of Autoregressive Modelling. ELECTRONICS, 13(15), 1-21 [10.3390/electronics13153083].
Diversi R.; Sandrolini L.; Simonazzi M.; Speciale N.; Mariscotti A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/985494
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