Field correlation between electromagnetic and high flux stator core tests

Bertenshaw, D. R.; Smith, Alexander C.

doi:10.1049/cp.2012.0144

Cited by 5 publications

(6 citation statements)

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“…The electromagnetic Quad signal of 100 mA has been shown to correlate to ∼9 °C for a typical 15 mm long surface fault (e.g. Fault_1) [31]. From Fig.…”

Section: Discussionmentioning

confidence: 99%

Three‐dimensional finite element analysis of large electrical machine stator core faults

Ho¹,

Bertenshaw²,

Smith

et al. 2014

IET Electric Power Applications

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Faults in the stator cores of large electrical machines can both damage local winding insulation and propagate to catastrophic failure. This study develops three-dimensional finite element models of inter-laminar insulation faults in order to obtain a deeper understanding of the electromagnetic behaviour of core faults and the sensitivity of sensing systems. The problem of developing a model that adequately reflects the laminar constraints of the structure, while remaining computable is addressed, together with eliminating images from boundaries. The model was validated by experimental measurement and results shown to be closely matched, with the fault current distribution also predicted. The sensitivity profiles for various fault positions and lengths were determined, which enables condition-monitoring sensors to be more specific about the location and true threat that a fault signal may pose to the machine.

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“…The electromagnetic Quad signal of 100 mA has been shown to correlate to ∼9 °C for a typical 15 mm long surface fault (e.g. Fault_1) [31]. From Fig.…”

Section: Discussionmentioning

confidence: 99%

Three‐dimensional finite element analysis of large electrical machine stator core faults

Ho¹,

Bertenshaw²,

Smith

et al. 2014

IET Electric Power Applications

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“…Any fault current is detected as that mpd in quadrature to the excitation field, indicated as a ‘ Quad ’ current [8], with the recommendation that signals above 100 mA ‘be investigated further’ [9]. The two tests have been shown to correlate in practice at ∼10°C/100 mA [10], and to similarly correlate to common alternate electromagnetic systems e.g. DIRIS [11].…”

Section: Introductionmentioning

confidence: 99%

Electromagnetic modelling and detection of buried stator core faults

Bertenshaw¹,

Smith

et al. 2017

IET Electric Power Applications

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Interlamination insulation faults in the stator cores of large electrical machines can damage both winding insulation and stator core, thus confidence in electromagnetic test results is important. They may be validated by FE methods, however the 3D models required for short faults are computationally challenged by laminated structures, requiring approximations. A homogenised 3D FE model was used to model faults buried in the teeth and yoke of the core, with a new experimental methodology developed to calibrate fault currents. Limitations were identified in modelling just a core section due to images and the constraint of axial packet air gaps on fault flux dispersion. A system of transverse 2D FE models of the principal fault flux paths in the core were constructed to estimate the differential impact on fault signals by the air gap presence and applied to the 3D FE model. Together with corrections for images this gave close predictions of experimental results, supporting the validity of the model. The verified electromagnetic test results now permit assessment of the threat that a detected buried fault presents.

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“…Figure 1 shows some examples of faults that can occur due to insulation wear of the stator. Figure 1 a presents a failure caused by defects in insulation between the core and the bars, which can cause partial discharges by corona effect due to potential difference between core and bars [ 3 ]. Figure 1 b shows a failure caused by defects in insulation between bottom and top bars, which can also cause partial discharges due to the phase difference between the bars, increasing risk of short circuit in the stator [ 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, these faults can be identified as hotspots in certain parts of the structure. However, if the defect is not identified and repaired in the early stages, the hotspots can propagate over the structure, affecting the life expectancy of the insulation layer, leading in extreme cases to a catastrophic failure of the generator [ 3 , 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

Sparse Reconstruction for Temperature Distribution Using DTS Fiber Optic Sensors with Applications in Electrical Generator Stator Monitoring

Bazzo

Pipa

Silva³

et al. 2016

Sensors

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This paper presents an image reconstruction method to monitor the temperature distribution of electric generator stators. The main objective is to identify insulation failures that may arise as hotspots in the structure. The method is based on temperature readings of fiber optic distributed sensors (DTS) and a sparse reconstruction algorithm. Thermal images of the structure are formed by appropriately combining atoms of a dictionary of hotspots, which was constructed by finite element simulation with a multi-physical model. Due to difficulties for reproducing insulation faults in real stator structure, experimental tests were performed using a prototype similar to the real structure. The results demonstrate the ability of the proposed method to reconstruct images of hotspots with dimensions down to 15 cm, representing a resolution gain of up to six times when compared to the DTS spatial resolution. In addition, satisfactory results were also obtained to detect hotspots with only 5 cm. The application of the proposed algorithm for thermal imaging of generator stators can contribute to the identification of insulation faults in early stages, thereby avoiding catastrophic damage to the structure.

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Field correlation between electromagnetic and high flux stator core tests

Cited by 5 publications

References 0 publications

Three‐dimensional finite element analysis of large electrical machine stator core faults

Three‐dimensional finite element analysis of large electrical machine stator core faults

Electromagnetic modelling and detection of buried stator core faults

Sparse Reconstruction for Temperature Distribution Using DTS Fiber Optic Sensors with Applications in Electrical Generator Stator Monitoring

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