A signal-based technique for fault detection and isolation of inverter faults in multi-phase drives

Meinguet, Fabien; Sandulescu, Paul; Aslan, Bassel; Li, Lü; Nguyen, Ngac Ky; Kestelyn, Xavier; Semail, Eric

doi:10.1109/pedes.2012.6484321

Cited by 12 publications

(8 citation statements)

References 20 publications

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“…As shown in Table 2, SB fault-detection methods have been widely carried out using vector space decomposition (VSD) components [15,18,44,[53][54][55][56][57][58][59][60][61][62][71][72][73][74][75], although monitoring just the phase currents has also been suggested for this purpose [48][49][50][51][52][67][68][69][70], especially in older papers. In a 2012 publication [48], Meinguet et al propose the localization of open-phase faults by quantifying the imbalance of the phase currents, exploiting the fact that these signals are more affected by the occurrence of a fault than the main (α 1 -β 1 ) VSD subspace. The fault is identified after several fundamental cycles.…”

Section: Sb Detection Methodsmentioning

confidence: 99%

“…The main characteristics of the existing detection approaches for phase/switch OC faults in multiphase drives are summarized in Table 2. From this table, it can be observed that some MB [43][44][45][46][63][64][65] and KB [45][46][47]66] solutions for OC identification are available, even though SB ones [15,18,44,[48][49][50][51][52][53][54][55][56][57][58][59][60][61][62]65,[67][68][69][70][71][72][73][74][75] are the most popular by far.…”

Section: Detection Of Phase/switch Oc Faultsmentioning

confidence: 99%

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A Comprehensive Survey on Fault Tolerance in Multiphase AC Drives, Part 2: Phase and Switch Open-Circuit Faults

et al. 2022

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Multiphase machines are very convenient for applications that require high reliability. In this two-part survey, the state of the art about fault tolerance in multiphase drives is reviewed. In Part 1, an overview including numerous fault types was presented, along with fundamental notions about multiphase drives. Here, in Part 2, the focus is placed on phase/switch open-circuit (OC) faults in particular, which have received the most attention in the literature. Phase OC failures involve OCs in stator phases or in converter-machine connections, and switch/diode OCs are frequently dealt with similarly or identically. Thanks to the phase redundancy of multiphase drives, their operation can be satisfactorily continued under a certain number of OCs. Nonetheless, the procedure to follow for this purpose is far from unique. For given OC fault conditions, numerous fault-tolerant possibilities can be found in the literature, each of them with different advantages and disadvantages. Moreover, a great variety of methods have also been devised to detect and diagnose phase/switch OC failures so that, as soon as possible, the most appropriate fault-tolerance measures are applied. Thus, given the broad literature about tolerance to phase/switch OC faults in multiphase drives, the survey presented here is expected to be of great interest for the research community and industry.

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Section: Sb Detection Methodsmentioning

confidence: 99%

Section: Detection Of Phase/switch Oc Faultsmentioning

confidence: 99%

A Comprehensive Survey on Fault Tolerance in Multiphase AC Drives, Part 2: Phase and Switch Open-Circuit Faults

et al. 2022

View full text Add to dashboard Cite

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“…On the one hand, signal-based methods such as current trajectory and instantaneous frequency analysis, considered in refs. [90,91], were applied because of their simplicity and low computational load in detection supervision levels. On the other hand, the model-based techniques were more precise and easier to implement in diagnostic tasks after the mathematical model generation [92].…”

Section: Energy Conversion Stepmentioning

confidence: 99%

Data-Driven Fault Diagnosis for Electric Drives: A Review

Gonzalez-Jimenez

Olmo

Poza

et al. 2021

Sensors

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The need to manufacture more competitive equipment, together with the emergence of the digital technologies from the so-called Industry 4.0, have changed many paradigms of the industrial sector. Presently, the trend has shifted to massively acquire operational data, which can be processed to extract really valuable information with the help of Machine Learning or Deep Learning techniques. As a result, classical Condition Monitoring methodologies, such as model- and signal-based ones are being overcome by data-driven approaches. Therefore, the current paper provides a review of these data-driven active supervision strategies implemented in electric drives for fault detection and diagnosis (FDD). Hence, first, an overview of the main FDD methods is presented. Then, some basic guidelines to implement the Machine Learning workflow on which most data-driven strategies are based, are explained. In addition, finally, the review of scientific articles related to the topic is provided, together with a discussion which tries to identify the main research gaps and opportunities.

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“…In the literature, a wide variety of methods used for fault detection can be classified into signal processing approaches [ 18 , 19 , 20 , 21 , 22 , 23 ], model-based approaches [ 23 , 24 , 25 , 26 ], knowledge-based approaches [ 18 , 27 , 28 , 29 ], and data-driven approaches [ 18 , 23 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ]. With the arrival of technology and the advancement of computing methods, data-driven approaches are gaining attention in the last decades, where it is expected that the data will drive the identification of normal and faulty modes of operation.…”

Section: Introductionmentioning

confidence: 99%

A RUL Estimation System from Clustered Run-to-Failure Degradation Signals

Cho

Carrasco

Ruz

2022

Sensors

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The prognostics and health management disciplines provide an efficient solution to improve a system’s durability, taking advantage of its lifespan in functionality before a failure appears. Prognostics are performed to estimate the system or subsystem’s remaining useful life (RUL). This estimation can be used as a supply in decision-making within maintenance plans and procedures. This work focuses on prognostics by developing a recurrent neural network and a forecasting method called Prophet to measure the performance quality in RUL estimation. We apply this approach to degradation signals, which do not need to be monotonical. Finally, we test our system using data from new generation telescopes in real-world applications.

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A signal-based technique for fault detection and isolation of inverter faults in multi-phase drives

Cited by 12 publications

References 20 publications

A Comprehensive Survey on Fault Tolerance in Multiphase AC Drives, Part 2: Phase and Switch Open-Circuit Faults

A Comprehensive Survey on Fault Tolerance in Multiphase AC Drives, Part 2: Phase and Switch Open-Circuit Faults

Data-Driven Fault Diagnosis for Electric Drives: A Review

A RUL Estimation System from Clustered Run-to-Failure Degradation Signals

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