Bearing Fault Detection in Induction Motors Employing Difference Visibility Graph

Roy, Sayanjit Singha; Chatterjee, Soumya; Barman, Ritwick; Roy, Saptarshi; Dey, Sayantan

doi:10.1109/pedes49360.2020.9379635

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…There are many studies using Visibility Graphs in the literature [15][16][17][18][19][20][21][22]. In one of these, the EEG activities of people with Alzheimer's disease were performed using a visibility graph-based method [15].…”

Section: Figure 2 a Sample Visibility Graphmentioning

confidence: 99%

“…In one of the literature studies we discussed, it focused on the classification of motor images obtained from EEG signals with a versatile, weighted visibility graph and a deep learning-based method [16]. In another study, a method using visibility graphs was used to detect bearing failures in asynchronous motors [17]. In another study, pulse variability-related visibility graphs were used to detect late-onset sepsis in premature infants [18].…”

Section: Figure 2 a Sample Visibility Graphmentioning

confidence: 99%

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Weighted Visibility Graph Based WiFi Indoor Positioning Method Using Heuristic Optimization

Altundoğan,

Karaköse

2024

Turkish Journal of Science and Technology

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With the widespread use of wireless communication technologies and IoT applications, researchers are developing approaches that utilize WiFi signals for indoor location determination. In this study, indoor positioning process based on heuristic optimization-based methods was performed by creating weighted visibility matrices of access points based on WiFi signal strength (RSSI) values. In the proposed method, the PSO and GA approaches determine the position of the mobile user using a common fitness function based on the visibility weight matrices. The proposed method has been tested on a virtual scenario where position ranges based on RSSI ranges are determined. Both heuristic optimization methods are compared according to different criteria and the positioning process is performed with a maximum error of 3m for the GA based method and a maximum of 1.5m for the PSO based method.

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