Combination of Noninvasive Approaches for General Assessment of Induction Motors

Picazo-Rodenas, M. J.; Antonino-Daviu, José A.; Climente-Alarcón, Vicente; Royo-Pastor, Rafael; Mota-Villar, A.

doi:10.1109/tia.2014.2382880

Cited by 65 publications

(32 citation statements)

References 50 publications

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“…In the case of induction motors, the technique may be very useful, especially for large induction motors, the cost of which can easily amount to $1-2 million and whose unexpected failures can entail losses of several million $ [18]. In these machines, the infrared thermography may play an excellent role to diagnose certain failures or to complement the diagnostic conclusions obtained with other techniques such as vibration or current data analysis [19,20], as will be shown in this paper.…”

Section: Introductionmentioning

confidence: 92%

Application of Infrared Thermography to Failure Detection in Industrial Induction Motors: Case Stories

López-Pérez¹,

Antonino-Daviu

2017

IEEE Trans. on Ind. Applicat.

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148

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Section: Introductionmentioning

confidence: 92%

Application of Infrared Thermography to Failure Detection in Industrial Induction Motors: Case Stories

López-Pérez¹,

Antonino-Daviu

2017

IEEE Trans. on Ind. Applicat.

Self Cite

148

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“…DOP compares the variation in power level due to strain or temperature on the gratings, thus providing additional information to the wavelength shift of FBGs. Multi-signature feature extraction is important especially in OCM of machines because there is a consensus that there exists no single fault signature that is able to detect all possible failures within a machine [14]. The simultaneous use of multi-signature for robust and effective OCM has been investigated in few research works.…”

Section: Wavelength and Power Level Signaturesmentioning

confidence: 99%

Investigation of the Effect of Bonding Points on Metal Surface-Mounted FBG Sensors for Electric Machines

Alalibo¹,

Cao²,

Gbadebo³

et al. 2019

PIER C

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Fibre Bragg Gratings (FBGs) offer several advantages including their immunity to electromagnetic fields making them excellent in situ sensors for feature extraction in electrical machines condition monitoring. However, the pre-requisite of bonding FBGs circumferentially on either the machine cast frame or stator windings can introduce undesired sensing characteristics. This is because the FBG relies on adhesives as the transfer medium for any sensed parameter between the machine and sensor. Whilst FBG sensors rely mainly on wavelength shift, an intolerably low signal-to-noise ratio will result in difficulty in measuring such shifts. As a complementary signature, differential optical power can be combined with wavelength shift to broaden the feature extraction capability of FBG sensors. This makes power level (dBm) an important sensing parameter for FBG sensors. The effect of varying number of bonding points on transmitted optical power is investigated using unstripped and stripped bare fibres as well as an actual FBG sensor. Increasing the number of bonding points beyond an optimum number has been observed to significantly attenuate the optical signal power level and quality for a given dynamic range. Hence, as the number of bonding points is increased, the level of attenuation should be closely monitored to ensure that the optimum number is not exceeded if excellent and accurate FBG sensing characteristics are to be realised.

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“…[6][7][8][9][10][11][12][13][14][15][16][17][18][19].53] Na A Na A Approximation (7) [19.53-0] Na Na Na Na A: Applicable; Na: Not applicable.…”

Section: Log-energy Entropymentioning

confidence: 99%

Broken Rotor Bar Detection in LS-PMSM Based on Startup Current Analysis Using Wavelet Entropy Features

et al. 2017

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High-efficiency motors are being gradually introduced in many industrial applications because of their positive impacts on the environment by reducing energy consumption and CO 2 emission. In this respect, line start permanent magnet synchronous motors (LS-PMSMs) have been introduced recently. Due to their unique configuration, LS-PMSMs allow the obtaining of super premium efficiency levels, accompanied with a high torque and power factor. However, since the use of LS-PMSMs in the industry is in its infancy, no efficient scheme has yet been reported for broken rotor bar (BRB) fault detection in this type of motor. Accordingly, the main aim of this research is to investigate the fault-related feature for BRB faults on LS-PMSMs. In this regard, a simulation model and experimental setup for the investigation of BRB in LS-PMSM are implemented. The detection strategy for BRB in LS-PMSM proposed here is based on the monitoring of the start-up current signal and discrete wavelet transform. The entropy features are used as fault-related features for BRB faults. Finally, the ability of these features is validated for the detection of BRB in LS-PMSM through statistical analysis. In this research, the importance of the starting load is also considered for BRB detection in LS-PMSMs.

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Combination of Noninvasive Approaches for General Assessment of Induction Motors

Cited by 65 publications

References 50 publications

Application of Infrared Thermography to Failure Detection in Industrial Induction Motors: Case Stories

Application of Infrared Thermography to Failure Detection in Industrial Induction Motors: Case Stories

Investigation of the Effect of Bonding Points on Metal Surface-Mounted FBG Sensors for Electric Machines

Broken Rotor Bar Detection in LS-PMSM Based on Startup Current Analysis Using Wavelet Entropy Features

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