A simple state-based prognostic model for predicting remaining useful life of IGBT power module

Alghassi, Alireza; Perinpanayagam, Suresh; Jennions, Ian K.

doi:10.1109/epe.2013.6634482

Cited by 11 publications

(8 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, this system is unable to provide the RUL prediction. Algassi et al [7] have proposed a state based prognostics model for predicting remaining useful life of IGBT. K-means clustering, evaluations of clustering and RUL calculations are the main computational elements of their approach.…”

Section: Introductionmentioning

confidence: 99%

Data driven prognostics for predicting remaining useful life of IGBT

Ahsan

Stoyanov

Bailey

2016

2016 39th International Spring Seminar on Electronics Technology (ISSE)

View full text Add to dashboard Cite

Power electronic devices such IGBT (Integrated Gate Bipolar Transistor) are used in wide range of applications such as automotive, aerospace and telecommunications. The ability to predict degradation of power electronic components can minimise the risk of their failure while in operation. Research in this area aims to develop prognostics strategies for predicting degradation behaviour, failure modes and mechanisms, and remaining useful life of these electronic components. In this paper, data driven prognostics approaches based on Neural Network (NN) and Adaptive Neuro Fuzzy Inference System (ANFIS) models are developed and used to predict the degradation of an IGBT device. IGBT life data under thermal overstress load condition with square signal gate voltage bias, available from NASA prognostics data repository, is used to demonstrate the proposed data-driven prognostics strategy. The monitored collector-emitter voltage is used to identify the pattern and duration of different phases in the applied voltage load. The NN and ANFIS models are trained with a subset of the test data to predict remaining useful life (RUL) of the IGBT device under varying load test profiles. The predictive capability and performance of the models is observed and analysed.

show abstract

Section: Introductionmentioning

confidence: 99%

Data driven prognostics for predicting remaining useful life of IGBT

Ahsan

Stoyanov

Bailey

2016

2016 39th International Spring Seminar on Electronics Technology (ISSE)

View full text Add to dashboard Cite

show abstract

“…Alghassi et al has discussed different failures mechanisms related to IGBT and they have also presented prognosis model for the dominant failure at a component level in [21] [22]. From system level prognostics, changes in the energy transfer in Cuk converter can be used to detect earlier sign of degradation and failure.…”

Section: A Dc-dc Convertermentioning

confidence: 99%

Reliability enhanced EV using pattern recognition techniques

Samie

Perinpanayagam

Alghassi

et al. 2014

2014 IEEE International Electric Vehicle Conference (IEVC)

View full text Add to dashboard Cite

This is a copy of the author's accepted version of a paper subsequently published in the proceedings of 2014 IEEE International Electric Vehicle Conference (IEVC). IEEE, pp. 1-8. It is available online at:http://dx.doi.org/10.1109/IEVC.2014.7056199The WestminsterResearch online digital archive at the University of Westminster aims to make the research output of the University available to a wider audience. Copyright and Moral Rights remain with the authors and/or copyright owners.© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Whilst further distribution of specific materials from within this archive is forbidden, you may freely distribute the URL of WestminsterResearch: (http://westminsterresearch.wmin.ac.uk/). Abstract-The following paper will contribute to the development of novel data transmission techniques from an IVHM perspective so that Electrical Vehicles (EV) will be able to communicate semantically by directly pointing out to the worst failure/threat scenarios. This is achieved by constructing an image-based data communication in which the data that is monitored by a vast number of different sensors are collected as images; and then, the meaningful failure/threat objects are transmitted among a number of EVs. The meanings of these objects that are clarified for each EV by a set of training patterns are semantically linked from one to other EVs through the similarities that the EVs share. This is a similar approach to wellknown image compression and retrieval techniques, but the difference is that the training patterns, codebook, and codewords within the different EVs are not the same. Hence, the initial image that is compressed at the transmitter side does not exactly match the image retrieved at the receiver's side; as it concerns both EVs semantically that mainly addresses the worst risky scenarios. As an advantage, connected EVs would require less number of communication channels to talk together while also reducing data bandwidth as it only sends the similarity rates and tags of patterns instead of sending the whole initial image that is constructed from various sensors, including cameras. As a case study, this concept is applied to DC-DC converters which refer to a system that presents one of the major problems for EVs.

show abstract

“…Alghassi et al has discussed different failures mechanisms related to IGBT and they have also presented prognosis model for the dominant failure at a component level in [29] [30]. IGBT experiences a number of failure mechanisms including: bond wire fatigue, bond wire lift up, corrosion of the wires, static and dynamic latch up, loose gate control voltage, etc.…”

Section: Prognostics Of Dc-to-dc Convertermentioning

confidence: 99%

Principle of Duality on Prognostics

Samie¹,

Motlagh²,

Alghassi³

et al. 2014

ijacsa

Self Cite

View full text Add to dashboard Cite

Abstract-The accurate estimation of the remaining useful life (RUL) of various components and devices used in complex systems, e.g., airplanes remain to be addressed by scientists and engineers. Currently, there area wide range of innovative proposals put forward that intend on solving this problem. Integrated System Health Management (ISHM) has thus far seen some growth in this sector, as a result of the extensive progress shown in demonstrating feasible and viable techniques. The problems related to these techniques were that they often consumed time and were too expensive and resourceful to develop. In this paper we present a radically novel approach for building prognostic models that compensates and improves on the current prognostic models inconsistencies and problems. Broadly speaking, the new approach proposes a state of the art technique that utilizes the physics of a system rather than the physics of a component to develop its prognostic model. A positive aspect of this approach is that the prognostic model can be generalized such that a new system could be developed on the basis and principles of the prognostic model of another system. This paper will mainly explore single switch dc-to-dc converters which will be used as an experiment to exemplify the potential success that can be discovered from the development of a novel prognostic model that can efficiently estimate the remaining useful life of one system based on the prognostics of its dual system.

show abstract

A simple state-based prognostic model for predicting remaining useful life of IGBT power module

Cited by 11 publications

References 10 publications

Data driven prognostics for predicting remaining useful life of IGBT

Data driven prognostics for predicting remaining useful life of IGBT

Reliability enhanced EV using pattern recognition techniques

Principle of Duality on Prognostics

Contact Info

Product

Resources

About