Evaluating Overhead Line Asset Integrity Through Drone Enabled Detection of Conductor Damage

Monday, September 28, 2026: 4:40 PM
306A (Québec City Convention Centre)
Dr. Chaoyang Liu, PhD, PE , Exponent, Inc., Menlo Park, CA
Dr. Keli Thurston, PhD, PE , Exponent, Inc., Menlo Park, CA
Dr. Casey Davis, PhD, PE , Exponent, Inc., Menlo Park, CA
Dr. Reeve Dunne, PhD, PE, CFEI , Exponent, Inc., Menlo Park, CA
Dr. Alina Kozinda, PhD, PE , Exponent, Inc., Menlo Park, CA
Dr. Chris Ruhl, PhD , Exponent, Inc., Menlo Park, CA
Ms. Chandini Prasad , Pacific Gas and Electric Company (PG&E), Oakland, CA
Ms. Rosa Serrano , Pacific Gas and Electric Company (PG&E), Oakland, CA
Dr. Natalie Dawley, PhD, PE , Pacific Gas and Electric Company (PG&E), Oakland, CA
Mr. Isaam El Ayadi , Pacific Gas and Electric Company (PG&E), Oakland, CA
Mr. Michael Didyk , Pacific Gas and Electric Company (PG&E), Oakland, CA
Overhead power line reliability is increasingly challenged by aging infrastructure, environmental exposure, and growing demand for uninterrupted service. Many conductor failures originate from localized material defects and damage mechanisms that progress undetected between inspection intervals. Traditional inspection methods for distribution and transmission conductors rely heavily on ground patrols and manned aerial inspections, which are time‑intensive, costly, and limited in their ability to consistently resolve early‑stage material damage. This presentation demonstrates how uncrewed aerial systems (UAS), or drones, can be deployed as an inspection tool to detect defects and damage relevant to asset integrity prior to in‑service failure.

Two field‑based case studies are presented. The first examines distribution‑level conductors, where high‑resolution optical imaging enabled the detection of cracked automatic splices exhibiting advanced mechanical and metallurgical distress. These defects were identified while the conductors remained energized prior to catastrophic failure. Subsequent investigation confirmed the cracking to be consistent with fatigue‑and corrosion‑assisted damage mechanisms that would have been difficult to identify using conventional inspection approaches. Early detection enabled targeted intervention, preventing unplanned outages and limiting secondary damage.

The second case study focuses on transmission‑level inspections, highlighting the capability of UAS platforms to rapidly and systematically survey extended line segments. Consistent, repeatable imagery across entire spans enabled timely condition assessment to support the identification of damage states and deterioration trends with minimal operational disruption. Compared to traditional methods, this approach significantly reduced inspection time and cost while expanding defect detection coverage, allowing the development of new conductor inspection programs.

These studies illustrate how drone‑based inspections can function as a practical non‑destructive evaluation tool for identifying material defects and degradation mechanisms critical to overhead line asset integrity. Integrating UAS into inspection programs enhances failure prevention strategies by enabling earlier detection of damage, improving decision‑quality data, and reducing risk to personnel.