Reliability model for switchgear failure analysis applied to ageing

Velásquez, Ricardo Manuel Arias; Lara, Jennifer Vanessa Mejía; Melgar, Andrés

doi:10.1016/j.engfailanal.2019.03.004

Cited by 24 publications

(11 citation statements)

References 20 publications

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“…It illustrates the ageing process and the necessary data for the creation of the model. This model can be demonstrated and analysed with an important factor; it represents the flexibility to build the reliability expected during the maintenance strategy-making and the knowledge of the equipment" [16]. Calixto (2016) stated that "RAM analysis is the basis for complex system performance analysis.…”

Section: Maintenance Reliability and Availabilitymentioning

confidence: 99%

Increasing the Reliability of an Electrical Power System in a Big European Hospital through the Petri Nets and Fuzzy Inference System Mamdani Modelling

et al. 2021

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The big hospitals’ electricity supply system’s reliability is discussed in this article through Petri nets and Fuzzy Inference System (FIS). To simulate and analyse an electric power system, the FIS Mamdani in MATLAB is implemented. The advantage of FIS is that it uses human experience to provide a faster solution than conventional techniques. The elements involved are the Main Electrical Power, the Generator sets, the Automatic Transfer Switches (ATS), and the Uninterrupted Power Supply (UPS), which are analysed to characterize the system behaviour. To evaluate the system and identified the lower reliability modules being proposed, a new reliable design model through the Petri Nets and Fuzzy Inference System approach. The resulting approach contributes to increasing the reliability of complex electrical systems, aiming to reduce their faults and increase their availability.

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Section: Maintenance Reliability and Availabilitymentioning

confidence: 99%

Increasing the Reliability of an Electrical Power System in a Big European Hospital through the Petri Nets and Fuzzy Inference System Mamdani Modelling

et al. 2021

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“…Data is collected by using Partial Discharge (PD) Detector. In the concept of ELM, all input data will be restored as shown in (1).…”

Section: Training Phasementioning

confidence: 99%

“…Switchgear is one of the vital equipment in a power distribution network [1]. In power generating system, switchgears act as a mean to isolate and de-energize specific electrical components and buses to ensure safety of downstream maintenance work, such as faults clearing, routine maintenance, and equipment replacements.…”

Section: Introductionmentioning

confidence: 99%

Corona fault detection in switchgear with extreme learning machine

Ishak¹,

Koh²,

Tan³

et al. 2020

Bulletin EEI

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Switchgear is a very important component in a power distribution line. Failure in a switchgear can lead to catastrophic danger and losses. In this research, a fault detection system is proposed with the implementation of Extreme Learning Machine (ELM). This algorithm is capable to identify faults in a switchgear by analyzing the sound wave generated. Experiments are carried out to investigate the performance of the developed algorithm in identifying Corona faults in switchgears. The performances are analyzed in time and frequency domains, respectively. In time domain analysis, the results show 90.63%, 87.5%, and 87.5% of success rates in differentiating the Corona and non-Corona cases in training, validation and testing phases respectively. In frequency domain analysis, the results show 89.84%, 83.33%, and 87.5% success rates in training, validation and testing phases respectively. It can thus be concluded that the developed algorithm performed well in identifying Corona faults in switchgears.

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“…A reliable and robust power distribution network has become highly essential in order to ensure steady power supplies to end users. Switchgear plays a crucial part in a power distribution network to separate and power down specific buses to secure the safety of downstream maintenance work, including maintenance work, faults attending, and components changing [1]. They can basically be classified into several groups based on the insulating materials, for example oil or air.…”

Section: Introductionmentioning

confidence: 99%

Arcing Faults Detection in Switchgear with Extreme Learning Machine

Ishak

Koh

Tan

et al. 2022

J. Phys.: Conf. Ser.

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The robustness of switchgears has critical impacts on the general efficiency of power distribution systems. Faulty switchgears lead to many unwanted complications for utility bodies, which in turn lead to even bigger issues. In this paper, a remote arcing fault sensing technique is proposed using ELM. By analysing the sonic waves emitted, the proposed method is capable to detect possible arcing faults in switchgears. Tests and experiments have been conducted to investigate the performance of the proposed algorithm in detecting these arcing faults. The obtained results are analysed in time and frequency domains. In the time domain analysis, the results show 93.75% success rate in training stage, 95.83% in validation stage, and 87.5% in testing stage. In the frequency domain analysis, the results show 93.75% success rate in training stage, 91.67% in validation stage, and 100% success rate in testing stage. It is thus concluded that the proposed algorithm is capable to identify arcing faults in switchgears.

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Reliability model for switchgear failure analysis applied to ageing

Cited by 24 publications

References 20 publications

Increasing the Reliability of an Electrical Power System in a Big European Hospital through the Petri Nets and Fuzzy Inference System Mamdani Modelling

Increasing the Reliability of an Electrical Power System in a Big European Hospital through the Petri Nets and Fuzzy Inference System Mamdani Modelling

Corona fault detection in switchgear with extreme learning machine

Arcing Faults Detection in Switchgear with Extreme Learning Machine

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