A Method for Online Stator Insulation Prognosis for Inverter-Driven Machines

Jensen, William R.; Strangas, Elias G.; Foster, Shanelle N.

doi:10.1109/tia.2018.2854408

Cited by 41 publications

(22 citation statements)

References 24 publications

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“…Prognosis of machine faliure can increase the reliability of the system and decrease cost of operation and chances of unexpected failure. The concepts and decisions associated with failure prognosis extracted from discussions in [39]- [40], [49]- [51] are aggregated in Fig. 6.…”

Section: Fault Prognosticsmentioning

confidence: 99%

“…Kalman filter is the optimal linear estimator for linear system models. The Extended Kalman Filter [39]- [40] and the Unscented Kalman Filter linearize the model, but are not optimal. Particle Filters [41], a Monte Carlo method, is a Baysian model based estimation of internal states in dynamical systems when partial observations are made.…”

Section: Fault Prognosticsmentioning

confidence: 99%

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Condition Monitoring of Industrial Electric Machines: State of the Art and Future Challenges

Lee

Stone

Antonino-Daviu

et al. 2020

EEE Ind. Electron. Mag.

Self Cite

121

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The limitations of thermal, vibration, or electrical monitoring of electric machines such as false indications, low sensitivity, and difficulty of fault interpretation have recently been exposed. This has led to a shift in the direction in research towards applying new techniques for improving the reliability of condition monitoring. With the changing environment, the purpose of this article is to provide an overview of the recent trend in the industrial demand and research activity in condition monitoring technology. The new developments in insulation testing, electrical testing, flux analysis, transient analysis, and fault prognostics are summarized. The future challenges and recommendations for future work for the new technologies are also stated to support researchers target research/development efforts according to industrial needs.

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Section: Fault Prognosticsmentioning

confidence: 99%

Section: Fault Prognosticsmentioning

confidence: 99%

Condition Monitoring of Industrial Electric Machines: State of the Art and Future Challenges

Lee

Stone

Antonino-Daviu

et al. 2020

EEE Ind. Electron. Mag.

Self Cite

121

View full text Add to dashboard Cite

show abstract

“…In [16], [17] a single current sensor sums the three phase currents together to measure the common mode current at multiples of line frequency. A cheaper method was investigated in [13], [14] using a shunt resistor based current sensor. An alternate method was used in [15] to use the high frequency components of the common mode current to characterize a resonance model to track the change of capacitance over time.…”

Section: Ground-wall Impedancementioning

confidence: 99%

Online Condition Monitoring for Diagnosis and Prognosis of Insulation Degradation of Inverter-Fed Machines

Tsyokhla

Griffo

Wang

2019

IEEE Trans. Ind. Electron.

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Real-time winding insulation condition monitoring is becoming an important research topic in response to increase in high availability and reliability demands in modern drives. In this paper, a novel method is proposed to monitor ground-wall insulation of low voltage inverter-fed machines based on a multi-frequency measurement of equivalent insulation ground-wall capacitance and dissipation factor. The monitoring is applied to four machine stator samples subjected to accelerated aging until failure. Insulation degradation is continuously tracked via the capacitance and dissipation parameters. A link between ground-wall insulation capacitance and final lifetime is established. The relationship between capacitance progression and its value at final machine failure is used to develop a method for prognosis of the final failure time.

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“…In other words, prognostics aim to forecast the evolution of a fault and to predict when the machine will no longer operate as designed or desired [3]. Prognostics may be used to evaluate the rate of degradation and may permit the machine to continue to operate regularly until the moment of failure; it may diminish unnecessary expensive maintenance and unexpected failures [4].…”

Section: Introductionmentioning

confidence: 99%

Novel Diagnostic Techniques for Rotating Electrical Machines—A Review

Frosini

2020

Energies

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This paper aims to update the review of diagnostic techniques for rotating electrical machines of different type and size. Each of the main sections of the paper is focused on a specific component of the machine (stator and rotor windings, magnets, bearings, airgap, load and auxiliaries, stator and rotor laminated core) and divided into subsections when the characteristics of the component are different according to the type or size of the machine. The review considers both the techniques currently applied on field for the diagnostics of the electrical machines and the novel methodologies recently proposed by the researchers in the literature.

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A Method for Online Stator Insulation Prognosis for Inverter-Driven Machines

Cited by 41 publications

References 24 publications

Condition Monitoring of Industrial Electric Machines: State of the Art and Future Challenges

Condition Monitoring of Industrial Electric Machines: State of the Art and Future Challenges

Online Condition Monitoring for Diagnosis and Prognosis of Insulation Degradation of Inverter-Fed Machines

Novel Diagnostic Techniques for Rotating Electrical Machines—A Review

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