2022
DOI: 10.1016/j.epsr.2022.108111
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A monitoring and diagnostics method based on FPGA-digital twin for power electronic transformer

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Cited by 21 publications
(4 citation statements)
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“…It utilizes an FPGA board to integrate different sensors, enabling cost-effective integration of multiple analog sensor inputs and efficient processing. In another study, Xiong et al [34] develop a real-time fieldprogrammable gate array-digital twin technique for monitoring and diagnostics of power electronic transformers. They propose a novel method based on FPGA-DT to analyze and detect open-circuit faults in PETs by comparing fault characteristics between actual and DT systems.…”
Section: State Of the Artmentioning
confidence: 99%
“…It utilizes an FPGA board to integrate different sensors, enabling cost-effective integration of multiple analog sensor inputs and efficient processing. In another study, Xiong et al [34] develop a real-time fieldprogrammable gate array-digital twin technique for monitoring and diagnostics of power electronic transformers. They propose a novel method based on FPGA-DT to analyze and detect open-circuit faults in PETs by comparing fault characteristics between actual and DT systems.…”
Section: State Of the Artmentioning
confidence: 99%
“…5. Approaches for using the digital twin as a reference model and use the deviations to detect unwanted behavior are one natural application of such deviations (Milton et al, 2020;Xiong et al, 2022). However, the objective of the digital twin for safety demonstrations rely on an accurate digital twin.…”
Section: Update To Manage Deviationsmentioning
confidence: 99%
“…It can also accurately determine the timeline and scope of equipment to be repaired and replaced, avoiding manual inspection and maintenance time and thus reducing O&M costs. Through the analysis and prediction of equipment operation data to develop a more accurate maintenance plan, timely monitoring and adjustment of equipment operation status can take place, reducing unnecessary maintenance work and improving maintenance efficiency and quality [117].…”
mentioning
confidence: 99%