Thermal Model of Electrical Contacts Based on Experimental Data

Chudnovsky, Bella H.; Livshitz, A.; Chudnovsky, B.A.

doi:10.1109/holm.2008.ecp.45

Cited by 5 publications

(6 citation statements)

References 6 publications

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“…Our R 2 -values for the different models, which shows how well the model explains the data, are lower than those presented in Chudnovsky et al (2008, -values between 0.91 and 0.98. A plausible reason for this is that their sensors are placed in closed compartments in equipment placed indoors.…”

Section: Discussioncontrasting

confidence: 85%

“…The histogram is also normalised for each interval of values of the current and plotted in colour, so the most common temperature residual is the reddest (the brightest in black-and-white). The curve following the brightest spots looks quadratic, which corresponds to the results in Chudnovsky et al (2008). According to Joule's law, P = R · I 2 where P is the power, R the resistance and I the current, the power losses increase with current and so does the temperature.…”

Section: A Quadratic Modelsupporting

confidence: 52%

“…We have applied both the linear and the quadratic model presented in Chudnovsky et al (2008) to disconnectors when they studied circuit breakers. The result is the same: the quadratic model is better.…”

Section: Discussionmentioning

confidence: 99%

“…A system with IR sensor is more suitable due to the reasons presented earlier. The papers by Zhang et al (2012), Huang et al (2011) and Shi et al (2002) describe systems with conventional sensors, but they do not explain how the monitored data should be interpreted, whereas Chudnovsky (2007), Chudnovsky et al (2008) and Livshitz et al (2005) have illustrative examples of temperature data and both a linear and a quadratic model to explain the data. However, they study medium-voltage circuit breakers, with sensors in closed compartments, while this article studies sensors on disconnectors, which are outdoors, so the thermal flow is different.…”

Section: Outline Of the Papermentioning

confidence: 99%

“…They find that a quadratic dependency on current is better than a linear one. Chudnovsky et al (2008) present a regression model with an additional factor in the coefficient of the squared current that expresses the aging of contacts. This factor causes an increase of the temperature.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Condition monitoring of disconnectors in the electric power transmission grid with temperature sensors

Westerlund

Hilber

Lindquist³

2016

IJISE

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This paper presents a method that can be used to rank disconnectors in the electric power system, according to the condition of one of the most critical parts, the contacts. The temperature of the contacts can be continuously measured by a new type of infrared sensor. For the case study, 54 sensors were placed on six disconnectors together with reference sensors measuring the ambient temperature. The measured temperature at each contact is then regressed against the ambient temperature and the current through the disconnector. Both a linear and a quadratic dependency of the current are tested and the quadratic one explains the data best. The coefficient of the current serves as a measure of the condition of the contact. Then, it becomes possible to identify in which contacts the resistance has increased the most. As a consequence, it is possible to make better maintenance decisions for the disconnectors.

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Section: Discussioncontrasting

confidence: 85%

Section: A Quadratic Modelsupporting

confidence: 52%

Section: Discussionmentioning

confidence: 99%