EPE Association: NORpie 2000 - Topic 14: MEASUREMENTS AND DIAGNOSIS

NORpie 2000 - Topic 14: MEASUREMENTS AND DIAGNOSIS
You are here: EPE Documents > 05 - EPE Supported Conference Proceedings > NORpie - Proceedings > NORpie 2000 > NORpie 2000 - Topic 14: MEASUREMENTS AND DIAGNOSIS

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   A Resonant System for Determination of Inductor Parameters
By Håkan Skarrie; Mats Alaküla [View]
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Abstract: This paper presents equations for calculating the losses that arises in an inductor at ac-induction. A system for fast measuring of the inductor parameters, inductance L and equivalent series resistance RLS, is also presented. From RLS the total losses of an inductor can be calculated. The system makes use of the oscillation between the capacitor and the inductor in a LC-circuit to determine the parameters. With known C, the resonance frequency of the oscillation determines the inductance L. The damping of the oscillation due to resistances in the circuit determines the series resistance RLS. When the series resistance is known the total average loss of the inductor can be derived as RLS Irms 2.

   DBC Robustness to Thermal Cycling
By Johannes J. Mikkelsen [View]
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Abstract: The Direct Bonded Copper (DBC) substrate technology is widely used as the base material in power electronics. Due to differences in Coefficient of Thermal Expansion (CTE) of the materials used, the robustness to thermal cycling is limited. This paper will deal with the fact, that the supplier’s specification of thermal cycling performance often is specified at a much larger temperature span, than the temperatures actually present in a running application. The aim is to supply the designers of power electronics with some mean of evaluating the actual cycles to failure in a given application.

   Fault Diagnosis of Electric Motors Using Soft Computing - An Overview
By X. Z. Gao; S. J. Ovaska [View]
[Download]

Abstract: During the last decade, soft computing (computational intelligence) has attracted great interest from different regions of research. In this paper, we review the recent developments in the field of soft computing-based electric motor fault diagnosis. Several typical motor fault diagnosis schemes using neural networks, fuzzy logic, neural-fuzzy, and genetic algorithms are presented with descriptive diagrams as well as simplified algorithms. Their advantages and disadvantages are compared and discussed. We demonstrate that soft computing methods are promising in tackling difficult fault detection problems.

NORpie 2000 - Topic 14: MEASUREMENTS AND DIAGNOSIS
You are here: EPE Documents > 05 - EPE Supported Conference Proceedings > NORpie - Proceedings > NORpie 2000 > NORpie 2000 - Topic 14: MEASUREMENTS AND DIAGNOSIS
	[return to parent folder]

	A Resonant System for Determination of Inductor Parameters By Håkan Skarrie; Mats Alaküla	[View] [Download]
Abstract: This paper presents equations for calculating the losses that arises in an inductor at ac-induction. A system for fast measuring of the inductor parameters, inductance L and equivalent series resistance RLS, is also presented. From RLS the total losses of an inductor can be calculated. The system makes use of the oscillation between the capacitor and the inductor in a LC-circuit to determine the parameters. With known C, the resonance frequency of the oscillation determines the inductance L. The damping of the oscillation due to resistances in the circuit determines the series resistance RLS. When the series resistance is known the total average loss of the inductor can be derived as RLS Irms 2.

	DBC Robustness to Thermal Cycling By Johannes J. Mikkelsen	[View] [Download]
Abstract: The Direct Bonded Copper (DBC) substrate technology is widely used as the base material in power electronics. Due to differences in Coefficient of Thermal Expansion (CTE) of the materials used, the robustness to thermal cycling is limited. This paper will deal with the fact, that the supplier’s specification of thermal cycling performance often is specified at a much larger temperature span, than the temperatures actually present in a running application. The aim is to supply the designers of power electronics with some mean of evaluating the actual cycles to failure in a given application.

	Fault Diagnosis of Electric Motors Using Soft Computing - An Overview By X. Z. Gao; S. J. Ovaska	[View] [Download]
Abstract: During the last decade, soft computing (computational intelligence) has attracted great interest from different regions of research. In this paper, we review the recent developments in the field of soft computing-based electric motor fault diagnosis. Several typical motor fault diagnosis schemes using neural networks, fuzzy logic, neural-fuzzy, and genetic algorithms are presented with descriptive diagrams as well as simplified algorithms. Their advantages and disadvantages are compared and discussed. We demonstrate that soft computing methods are promising in tackling difficult fault detection problems.