Progress of insulation ageing and diagnostics of high voltage rotating machine windings in Japan

Kimura, Ken

doi:10.1109/57.216783

Cited by 39 publications

(8 citation statements)

References 13 publications

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“…With vertical shaft alignment hydro generators, bars with deteriorated or detached corona protections caused by the lubricant from leaking bearing sealing penetrating into the stator slots have been detected [13]. Dimensional changes caused by ageing of solid insulations and loosening of the slot wedges allow bar vibration in slots [14]. These vibrations can lead to the abrasion of the slot-corona protection of the winding and at the sharp edges of stator core damaging the insulation and reducing its lifetime.…”

Section: Experimental Studymentioning

confidence: 99%

Electrical ageing in lifetime estimation of hydroelectric generator stator windings

Kokko

2010

The XIX International Conference on Electrical Machines - ICEM 2010

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Φ Abstract --Objective of this study is to presents an approach for predicting electrical ageing in the lifetime estimation of hydroelectric generator stator windings. Accelerated voltage endurance tests can be used for new or in-service aged stator bars to estimate electrical ageing. However, sample windings removal from each operating unit are needed for testing, taking several days. Therefore, it is not a practical alternative for analysing large numbers of units. Instead, it was decided to use the electrical ageing model and to match the factors of the model with winding lifetimes in the generator database. Based on the experimental study, it was concluded that in some cases the electrical field stress restricts the targeted winding lifetime. Therefore, it is necessary to include electrical ageing model to estimate the lifetime of stator windings. Additionally, electrical ageing curves for various winding insulation systems were conducted including asphaltic-mica, shellac-mica, epoxy re-impregnated shellac-mica and epoxy-mica.

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Section: Experimental Studymentioning

confidence: 99%

Electrical ageing in lifetime estimation of hydroelectric generator stator windings

Kokko

2010

The XIX International Conference on Electrical Machines - ICEM 2010

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“…So, to evaluate the aging condition and residual life of generator stator bars, it is of great importance to do the study on aging characteristics of stator bars in generator. Now, lots of work has been done on this subject, and much has been accomplished too [1][2][3][4]. In this paper, the author investigated the developing rule of the dielectric loss, partial discharge parameters and breakdown voltage of stator bar sample with aging time, present the characteristic parameters used to assess the aging condition of stator insulation, which provides a basis to diagnosis based on nondestructive electric parameters and residual life evaluation of large generator stator bars.…”

Section: Introductionmentioning

confidence: 99%

Study on Multi-Factor Aging Characteristics of Generator Stator Bars

Yuao

Gao

et al. 2006

2006 IEEE 8th International Conference on Properties and Applications of Dielectric Materials

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A long-term accelerated aging test is conducted on the stator bar of 300MW/18KV generator by using a multi-factor aging test system which combines electrical, thermal and vibrational stresses. Under the multi-factor aging, the developing rule of the dielectric loss, partial discharge parameters and breakdown voltage of stator bar sample with aging time is investigated. Moreover the characteristic parameters used to assess the aging condition of stator insulation are stated, which provides a basis to predict the breakdown voltage of stator bar in generator.

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“…A method to quantitatively calculate the reliability of multi-parameter diagnosis is put forward. Moreover, as an example, referring to the different non-destructive diagnosis methods for generators [5][6][7][8][9], the reliability of multi-parameter diagnosis for the stator bar of generator (300 MW, 18 kV) is studied, and the optimized diagnosis algorithm is calculated.…”

Section: Introductionmentioning

confidence: 99%

The optimization of multi-parameter insulation diagnosis

Shen

et al. 2009

2009 IEEE Conference on Electrical Insulation and Dielectric Phenomena

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On the basis of statistical theory, a method to quantitatively determine the reliability of multi-parameter diagnosis and to optimize the algorithm of multi-parameter diagnosis is put forward. This method is based on the statistical law, and concerns correlation between the different parameters. Moreover, as an example, the stator bar of generator (300 MW, 18 kV) is studied. 30 samples were selected from different parts of the practical stator bar of generators, and the parameters of dielectric loss, partial discharge and remaining breakdown voltage (BDV, 50 Hz) of each sample were measured. This method is applied to the estimation BDV of generator bars and the optimized multi-parameter diagnosis algorithm is determined on the basis of actual data. Sk+, tan and C are selected as the optimal parameter group by this method. Comparing with experimental data, it shows that the quantity of parameters is not the more the better. To choose appropriate parameters for assessing insulation condition is important. In order to choose appropriate parameters, two following principles are suggested. 1) It is efficient to select the parameters which have significant correlation with estimation object, as well as to obviate those of limited correlation. 2) Correlation between parameters should be taken into account. Generally speaking, the degree of correlation between parameters is the lower the better.

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Progress of insulation ageing and diagnostics of high voltage rotating machine windings in Japan

Cited by 39 publications

References 13 publications

Electrical ageing in lifetime estimation of hydroelectric generator stator windings

Electrical ageing in lifetime estimation of hydroelectric generator stator windings

Study on Multi-Factor Aging Characteristics of Generator Stator Bars

The optimization of multi-parameter insulation diagnosis

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