In order to ensure the long-term stable operation of substation Unmanned Aerial Vehicle (UAV), a UAV health status assessment method based on the entropy weight-variable weight Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) fuzzy evaluation is proposed in this paper. By selecting operational evaluation parameters, the ideal positive and negative solution vectors of UAV flight parameters are analyzed and calculated, and the real-time health indicators of UAVs are obtained by calculating the distance of UAV real-time operational parameters to the ideal and anti-ideal solution vectors. Considering that the impact of abnormal individual operational parameters on UAV health status may be obscured by health indicators, variable weight theory is introduced to modify the abnormal indicators, making the assessment results more accurate. Health status levels are established, and the obtained health indicators are mapped to different health status levels, achieving the health status assessment of UAVs at substations. Case study results show that the proposed method intuitively provides the overall health status level of UAVs and is easy to implement in engineering.
Health Status Assessment Method Based on Entropy-Variable Weight TOPSIS Fuzzy Comprehensive Assessment for Substation UAV
17.01.2025
1126866 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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