Gaussian Process Regression Remaining Useful Lifetime Prediction of Thermally Aged Power IGBT

Ismail, Adla; Saïdi, Lotfi; Sayadi, Mounir; Benbouzid, Mohamed

doi:10.1109/iecon.2019.8926710

Cited by 14 publications

(17 citation statements)

References 12 publications

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“…Not only are the mechanical components of WT used to estimate their RUL, the RUL estimation of electrical components is also necessary. A Gaussian process regression technique was proposed to estimate the RUL for degraded high-power IGBTs (insulated-gate bipolar transistor) [165]. This method was proven compatible with accelerated ageing database of real devices as defined under thermal overstress utilizing a direct current at the gate.…”

Section: Remaining Useful Life Estimationmentioning

confidence: 99%

Intelligent Condition Monitoring of Wind Power Systems: State of the Art Review

et al. 2021

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Modern wind turbines operate in continuously transient conditions, with varying speed, torque, and power based on the stochastic nature of the wind resource. This variability affects not only the operational performance of the wind power system, but can also affect its integrity under service conditions. Condition monitoring continues to play an important role in achieving reliable and economic operation of wind turbines. This paper reviews the current advances in wind turbine condition monitoring, ranging from conventional condition monitoring and signal processing tools to machine-learning-based condition monitoring and usage of big data mining for predictive maintenance. A systematic review is presented of signal-based and data-driven modeling methodologies using intelligent and machine learning approaches, with the view to providing a critical evaluation of the recent developments in this area, and their applications in diagnosis, prognosis, health assessment, and predictive maintenance of wind turbines and farms.

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Section: Remaining Useful Life Estimationmentioning

confidence: 99%

Intelligent Condition Monitoring of Wind Power Systems: State of the Art Review

et al. 2021

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“…As shown in Figure 5 [15][16][17], these steps correspond to; first, to "observe" certain phenomena, then to "analyze" them, and, finally, to "act" accordingly. As previously stated, this being the mind is another strategy that implies attempting to predict the appearance of a phenomenon that has just established itself (failure) rather than understanding it once it has occurred (failure).…”

Section: Prognostics and Health Management 21 Phm Cyclementioning

confidence: 99%

Prognostics and Health Management of Renewable Energy Systems: State of the Art Review, Challenges, and Trends

Saïdi

Benbouzid

2021

Electronics

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The purpose of this study is to highlight approaches for predicting a system’s future behavior and estimating its remaining useful life (RUL) to define an effective maintenance schedule. Indeed, prognosis and health management (PHM) strategies for renewable energy systems, with a focus on wind turbine generators, are given, as well as publications published in the recent ten years. As a result, some prognostic applications in renewable energy systems are emphasized, such as power converter devices, battery capacity degradation, and damage in wind turbine high-speed shaft bearings. The paper not only focuses on the methodologies adopted during the early research in the area of PHM but also investigates more current challenges and trends in this domain

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“…These techniques use, for example, Gaussian process (GP) regression. In Reference 22, Ismail et al proposed an IGBT prognostic approach based on the collector‐emitter voltage on the state, and they proposed a model that uses Gaussian regression process for thermally aged power IGBTs RUL estimation.…”

Section: A Brief Review Of Prognostics Approachesmentioning

confidence: 99%

Remaining useful life estimation for thermally aged power insulated gate bipolar transistors based on a modified maximum likelihood estimator

Ismail

Saïdi

Sayadi

et al. 2020

Int Trans Electr Energ Syst

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Power electronics converters (PCVs) such as inverters and rectifiers are crucial parts in industrial applications and energy conversion and are commonly used in several power conversion systems. Previous works have only focused on the fault diagnosis of PCVs; however, recently more consideration has been paid on predicting failures. Thus, reinforcing the reliability of power semiconductor devices is crucial for extending the lifetime of the PCVs‐based electrical power systems. This paper presents a novel prognostic approach for estimating the remaining useful life (RUL) of the power insulated gate bipolar transistors (IGBTs) used in PCVs. An IGBT‐accelerated aging database set under thermal overstress is utilized to evaluate the proposed approach. A data‐driven method based on the feature extraction process and a modified maximum likelihood estimator (MLE) technique to RUL estimation of IGBT have been developed and applied. This method is validated to effectively predict the PVC failures based on an accelerated aging experimental data set.

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Gaussian Process Regression Remaining Useful Lifetime Prediction of Thermally Aged Power IGBT

Cited by 14 publications

References 12 publications

Intelligent Condition Monitoring of Wind Power Systems: State of the Art Review

Intelligent Condition Monitoring of Wind Power Systems: State of the Art Review

Prognostics and Health Management of Renewable Energy Systems: State of the Art Review, Challenges, and Trends

Remaining useful life estimation for thermally aged power insulated gate bipolar transistors based on a modified maximum likelihood estimator

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