Distributed Measuring System for Predictive Diagnosis of Uninterruptible Power Supplies in Safety-Critical Applications

Sergio Saponara
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Sergio Saponara: Dipartimento Ingegneria della Informazione-Università di Pisa, via G. Caruso 16, Pisa 56122, Italy

Energies, 2016, vol. 9, issue 5, 1-18

Abstract: This work proposes a scalable architecture of an Uninterruptible Power Supply (UPS) system, with predictive diagnosis capabilities, for safety critical applications. A Failure Mode and Effect Analysis (FMEA) has identified the faults occurring in the energy storage unit, based on Valve Regulated Lead-Acid batteries, and in the 3-phase high power transformers, used in switching converters and for power isolation, as the main bottlenecks for power system reliability. To address these issues, a distributed network of measuring nodes is proposed, where vibration-based mechanical stress diagnosis is implemented together with electrical (voltage, current, impedance) and thermal degradation analysis. Power system degradation is tracked through multi-channel measuring nodes with integrated digital signal processing in the transformed frequency domain, from 0.1 Hz to 1 kHz. Experimental measurements on real power systems for safety-critical applications validate the diagnostic unit.

Keywords: uninterruptible power supply (UPS); predictive maintenance; measurements on power transformers; battery monitoring; power electronics and components (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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