01Overview
Thermal Transformer Diagnostics is an enterprise-grade industrial monitoring and inspection platform designed for high-voltage transformer asset tracking across regional electrical utility grids.
The system combines HTML5 Canvas-based thermal image annotation with automated oil Dissolved Gas Analysis (DGA) digital workflows, allowing engineers and technicians to detect critical insulation anomalies and track degradation over time.
02My contributions
- 01
Built the frontend and its API integration layer with React 19, TypeScript, and RTK Query for real-time asset tracking, inspection workflows, and health monitoring of high-voltage transformers across regional networks.
- 02
Engineered an interactive canvas annotation tool using Konva / React-Konva for side-by-side thermal image analysis, allowing engineers to annotate fault bounding boxes, adjust aspect ratios, and record AI human-review verdicts.
- 03
Developed complex multi-step digital inspection and oil analysis forms using React Hook Form and Zod schema validation, ensuring strict data integrity for electrical, physical, and Dissolved Gas Analysis (DGA) parameters.
- 04
Designed a centralized RTK Query API layer featuring automated JWT bearer token injection, global error transformations, tag-based cache invalidation, and optimistic UI updates.
- 05
Implemented multi-tier Role-Based Access Control (RBAC) across Admin, Engineer, and Technician roles with dynamic route guards, regional filter panels (CSC/Feeder/Branch), and PDF inspection report generation.
03Architecture highlights
04Key features
- Industrial asset tracking
- Transformer health monitoring
- Side-by-side thermal image analysis
- Canvas annotations with fault bounding boxes
- AI-assisted human review
- Multi-step inspection workflows
- Oil and DGA analysis with validation
- Regional filtering (CSC / Feeder / Branch)
- PDF inspection reports