Multi-Feature Fusion-Based Mechanical Fault Diagnosis for On-Load Tap Changers in Smart Grid With Electric Vehicles

Yan, Yan; Ma, Hongzhong; Wen, Miaowen; Dang, Shuping; Xu, Huiling

doi:10.1109/jsen.2020.3021920

“…A recent special issue [24] reports the cutting-edge advances and ICT technologies pertaining to the seamless integration of sensors with the transportation infrastructure. The main focus of the contributions in [24] is on sensing technologies for private transportation systems, oriented to autonomous driving [25,26], intelligent fault detection [27,28], electric charging optimization [29], road condition monitoring [30,31], precise fleet management [32], speed detection and accident avoidance [33,34]: in the same issue, less attention is dedicated to the integration of sensing technologies within PT systems. Moreover, sensing techniques for crowd monitoring are not specifically discussed.…”

Section: Introductionmentioning

confidence: 99%

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Darsena¹,

Gelli²,

Iudice³

et al. 2022

Preprint

0

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<p>Management of crowd information in public transportation (PT) systems is crucial, both to foster sustainable mobility, by increasing the user's comfort and satisfaction during normal operation, as well as to cope with emergency situations, such as pandemic crises, as recently experienced with COVID-19 limitations. This paper presents a taxonomy and review of sensing technologies based on Internet of Things (IoT) for real-time crowd analysis, which can be adopted in the different segments of the PT system (buses/trams/trains, railway/metro stations, and bus stops). To discuss such technologies in a clear systematic perspective, we introduce a reference architecture for crowd management, which employs modern information and communication technologies (ICT) in order to: (i) monitor and predict crowding events; (ii) implement crowd-aware policies for real-time and adaptive operation control in intelligent transportation systems (ITSs); (iii) inform in real-time the users of the crowding status of the PT system, by means of electronic displays installed inside vehicles or at bus stops/stations, and/or by mobile transport applications. It is envisioned that the innovative crowd management functionalities enabled by ICT/IoT sensing technologies can be incrementally implemented as an add-on to state-of-the-art ITS platforms, which are already in use by major PT companies operating in urban areas. Moreover, it is argued that, in this new framework, additional services can be delivered to the passengers, such as, e.g., on-line ticketing, vehicle access control and reservation in severely crowded situations, and evolved crowd-aware route planning.</p>

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“…A recent special issue [26] reports the cutting-edge advances and ICT technologies pertaining to the seamless integration of sensors with the transportation infrastructure. The main focus of the contributions in [26] is on sensing technologies for private transportation systems, oriented to autonomous driving [27,28], intelligent fault detection [29,30], electric charging optimization [31], road condition monitoring [32,33], precise fleet management [34], speed detection and accident avoidance [35,36]: in the same issue, less attention is dedicated to the integration of sensing technologies within PT systems. Moreover, sensing techniques for crowd monitoring are not specifically discussed.…”

Section: Introductionmentioning

confidence: 99%

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Darsena¹,

Gelli²,

Iudice³

et al. 2022

Preprint

0

View full text Add to dashboard Cite

<p>Management of crowd information in public transportation (PT) systems is crucial, both to foster sustainable mobility, by increasing the user's comfort and satisfaction during normal operation, as well as to cope with emergency situations, such as pandemic crises, as recently experienced with COVID-19 limitations. This paper presents a taxonomy and review of sensing technologies based on Internet of Things (IoT) for real-time crowd analysis, which can be adopted in the different segments of the PT system (buses/trams/trains, railway/metro stations, and bus stops). To discuss such technologies in a clear systematic perspective, we introduce a reference architecture for crowd management, which employs modern information and communication technologies (ICT) in order to: (i) monitor and predict crowding events; (ii) implement crowd-aware policies for real-time and adaptive operation control in intelligent transportation systems (ITSs); (iii) inform in real-time the users of the crowding status of the PT system, by means of electronic displays installed inside vehicles or at bus stops/stations, and/or by mobile transport applications. It is envisioned that the innovative crowd management functionalities enabled by ICT/IoT sensing technologies can be incrementally implemented as an add-on to state-of-the-art ITS platforms, which are already in use by major PT companies operating in urban areas. Moreover, it is argued that, in this new framework, additional services can be delivered to the passengers, such as, e.g., on-line ticketing, vehicle access control and reservation in severely crowded situations, and evolved crowd-aware route planning.</p>

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“…As the only moving component in a converter transformer, the OLTC switches between different taps to change the transformation ratio to regulate the valve-side voltage. Due to the considerable mechanical and electrical stress suffered by the OLTC, its failure rate is significantly higher than that of other fixed components, and according to statistical reports, OLTC-induced transformer faults make up over 20% of total faults [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Bidirectional field–circuit coupling analysis of converter transformer inter‐tap short‐circuit faults in on‐load tap changers

Yan

¹

,

Zhang

²

,

Xu

³

et al. 2022

IET Generation Trans & Dist

7

0

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Converter transformer inter‐tap short‐circuit faults in on‐load tap changers have occurred successively in recent years, resulting in severe accidents and enormous losses. Due to the lack of an effective model and credible arc‐in‐oil conductance parameters, related fault analysis has remained a challenge. This paper develops a bidirectional field–circuit coupling method for modelling inter‐tap faults, in which the electromagnetic field and electric circuit are directly coupled and simultaneously solved. After verification based on on‐site arcing tests, the Schavemaker model is applied to calculate the non‐linear arc conductance. Taking a ±800 kV UHVDC system as a study case, inter‐tap faults in a 415 MVA/500 kV converter transformer are simulated and analysed. Under an inter‐tap fault, the flux distribution is significantly distorted, with large radial leakage fluxes near the shorted turns, and the circulating current can reach tens or even hundreds of kiloamperes. Further calculation results for faults between various taps indicate that leakage flux distortion and the change in the transformation ratio are the main factors influencing the short‐circuit current. These representative findings effectively reveal the variation characteristics of the leakage flux and the short‐circuit current as well as the non‐linear relationship between fault severity and tap position under inter‐tap faults.

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Multi-Feature Fusion-Based Mechanical Fault Diagnosis for On-Load Tap Changers in Smart Grid With Electric Vehicles

Cited by 21 publications

References 39 publications

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Bidirectional field–circuit coupling analysis of converter transformer inter‐tap short‐circuit faults in on‐load tap changers

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