Optics11 webinar: From FAT to Fleet: Making PD Detection Actionable
Upcoming
| FreeHosted by: Transformers Academy
Partial discharge monitoring only creates value when it leads to reliable localization and effective decisions, not just detection.
In this E-lesson, Optics11 presents practical case studies of fiber-optic PD monitoring of transformers, using OptiFender.
The session connects two critical use cases:
• OEMs perspective: improving PD and defect localization during FAT • Asset owner perspective: enabling condition based monitoring and avoid unplanned maintenance or outages
You will see how fiber-optic sensing technology enables high-precision PD localization, pinpointing the exact PD source and reducing ambiguity in test results.
For in-service transformers, we demonstrate how continuous PD measurements are translated into a real-time health status, supporting condition-based maintenance strategies.
This session also covers: • Implementation and commissioning considerations in both factory and field environments • Integration into existing asset management workflows • How decision-grade PD data supports faster fault assessment and reduces operational risk
About the author
Jamie Bryson
Head of Product ManagementJamie is Head of Product Management for Energy at Optics11, helping utilities predict failures, reduce downtime, and protect high-voltage assets. With more than 25 years of experience across engineering, sales, and product management, and a background in Electrical and Electronic Engineering, he bridges deep-tech innovation and commercial strategy to deliver robust hardware solutions that perform in harsh environments and generate actionable insights for the modern grid.
Dr. Hamed Hashemi Dezaki
Partial Discharge LeadDr. Hamed Hashemi is Partial Discharge Lead at Optics11, with more than 15 years of experience in partial discharge diagnostics, high-voltage testing, and condition monitoring across transformers, cables, and GIS assets. An expert in HV engineering and power systems, he combines technical depth with hands-on experience in commissioning, customer training, and global field operations, with a strong focus on digitalizing power asset diagnostics and advancing predictive maintenance.