Environmental infringement and sag estimation for power transmission lines with unmanned aerial vehicles and multi-modal sensors

Abstract

This paper proposes an advanced unmanned aerial vehicle-based framework that integrates three-dimensional LiDAR and infrared camera measurements for environmental infringement assessment. The proposed framework features three characteristics. First, multi-sensor measurements are fused for environmental infringement. This approach provides useful information to detect vegetation encroachment and other hazards. Second, an extreme operational temperature is estimated by addressing the sag and estimated temperature theoretical formulation for transmission lines (TLs). This information quantifies the effect of abnormal thermal conditions on TL tension behavior. Third, uncertainty quantification is incorporated by analyzing sensor inaccuracies and repeatability errors of embedded algorithms. This characteristic enhances the reliability of the environmental infringement assessment. Each characteristic is underpinned by specific achievements, for example, real-time sensor fusion and on-board processing, dual-stage temperature modeling and critical-temperature detection, and combined uncertainty analysis with multi-site validation. Extensive field experiments conducted on multiple TLs demonstrate the effectiveness of the proposed framework and confirm that it would be effective for TL health inspection via environmental infringement and extreme operational temperature estimation under various conditions.