Comparing MCSA with vibration analysis in order to detect bearing faults — A case study

Corne, Bram; Vervisch, Bram; Debruyne, Colin; Knockaert, Jos; Desmet, Jan

doi:10.1109/iemdc.2015.7409240

Cited by 21 publications

(13 citation statements)

References 25 publications

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“…Furthermore, in some emulation experiments, the stator current was analysed with focus on detecting the bearing faults. Fortunately, the bearing-fault signatures were found in the exact way as they propagate with a real faulty bearing [11]. For completion, Table 4 is included presenting a very condensed result of the dominant fault-related component in the stator current during both emulation and real industrial cases (IMs severing bearing problems).…”

Section: Single Point Bearing Fault Emulationsmentioning

confidence: 99%

“…The core research of the authors concerns the development of mechanical fault detection in electric machines by analysing the stator current. Research already proved the feasibility of using the stator current to examine the mechanical condition of the machine, but the determination of severity stages when specific faults are detected is still lacking [11]. Due to the absence of the urgency statement when a mechanical problem is detected, the technology remains unserviceable.…”

Section: Introductionmentioning

confidence: 99%

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Emulating single point bearing faults with the use of an active magnetic bearing

Corne

Vervisch

Derammelaere³

et al. 2018

IET Science, Measurement & Technology

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Section: Single Point Bearing Fault Emulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Emulating single point bearing faults with the use of an active magnetic bearing

Corne

Vervisch

Derammelaere³

et al. 2018

IET Science, Measurement & Technology

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“…). These specific faultindicators and their unique signatures in terms of frequency are extensively discussed in [10] and can be summarized for outer race, inner race, ball and bearing cage faults, respectively as [4], [8]- [10], [12], [21]- [26]:…”

Section: Methodsmentioning

confidence: 99%

“…A few decades ago, research sufficiently proved the feasibility of using the stator current to examine both the electrical and mechanical conditions of the electric machine, [1]- [3], [11]. Unfortunately, until today, the determination of severity-stages when specific mechanical faults are evolving is still lacking, [12]. Due to the absence of the urgency-statement when a mechanical problem is detected, the technology is unfortunately categorized as unserviceable.…”

Section: Introductionmentioning

confidence: 99%

Single point outer race bearing fault severity estimation using stator current measurements

Corne

Vervisch

Derammelaere

et al. 2017

2017 IEEE International Electric Machines and Drives Conference (IEMDC)

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Abstract-Although numerous valuable research has been conducted by many authors, the relation between evolving mechanical faults and their fault-indicating reflections in the electrical signals of rotating electric machinery still requires extensive attention. This lack of information implies serious obstructions in the evolution of applying motor current signature analysis as a complete and reliable condition monitoring technology. However, as previous research of the authors resulted in the construction of a unique test-bench where specific mechanical faults can be introduced into an 11kW induction machine with high reproducibility and accuracy, the relations between evolving mechanical faults and their reflections in the stator current can be investigated and quantified experimentally. Using this mechanical fault-emulator, experiments where conducted where the severity of a single point outer race bearing fault and its corresponding signature in the stator current's spectral fault-components are accurately analyzed. These evolving faulty components are trended and characterized, resulting in the desired quantification of the mechanical fault-severity. Based on these results, it is possible to inversely estimate the severity of single point outer race bearing problems by acquiring nothing more then the stator current timefunctions.

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“…One condition to apply this technique is a sufficient accurate current spectrum. This can be obtained by measuring long enough, applying a good frequency transformation (such as [23]) and solving the Picket Fence Effect, [24].…”

Section: B Mechanical Unbalancementioning

confidence: 99%

Misalignment and unbalance fault severity estimation using stator current measurements

Corne

Knockaert

Desmet

2017

2017 IEEE 11th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED)

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Abstract-The feasibility of using stator current measurements in order to detect mechanical problems in electric rotating machinery has been proven by many authors several decades ago. However, this way of detecting problems has never been exploited as a full-covering and reliable prognostic monitoring technology. Although the imposed current-signatures of different evolving mechanical faults in electric machines are well characterized, the relation between the severity of those faults and the corresponding faulty signatures is still not elucidated thoroughly. As the authors built an innovative test-rig on which all kinds of mechanical faults can be emulated with a wide variety of controllable environmental conditions, those specific relations can finally be investigated. The test-rig contains an 11kW induction machine with an integrated active magnetic bearing at drive-end side. The magnetic bearing can easily manipulate the rotor's position corresponding to a real manifesting and evolving mechanical fault with a high accuracy and reproducibility. In this paper, the relation of the current fault-signatures and the severity of misalignment and mechanical unbalance is investigated. After theoretically describing the different eccentricity-related rotorfaults, the faults are induced and emulated on the induction machine under test. The fault-components in the stator currents' spectra are monitored while the severity of the faults is being increased. By fitting corresponding trending-functions on the obtained results, the severity of misalignment and unbalance can be estimated out of stator current measurements.

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Comparing MCSA with vibration analysis in order to detect bearing faults — A case study

Cited by 21 publications

References 25 publications

Emulating single point bearing faults with the use of an active magnetic bearing

Emulating single point bearing faults with the use of an active magnetic bearing

Single point outer race bearing fault severity estimation using stator current measurements

Misalignment and unbalance fault severity estimation using stator current measurements

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