Electric Field Mill

• Shubham Banwal

• October 2022

Electric Field Mill for Atmospheric Sensing & Lightning Prediction

Problem:

Reliable early detection of lightning requires accurate measurement of atmospheric electric field variations, but raw sensing systems are often noisy, unstable, and difficult to interpret.

Approach:

Designed and implemented an Electric Field Mill–based sensing system to continuously measure atmospheric electric field intensity and detect charge buildup patterns linked to lightning activity.

System Design:

• Electric Field Mill sensor for atmospheric charge detection
• Signal acquisition and conditioning circuitry
• Filtering and calibration layer for noise reduction
• Data processing pipeline for interpreting field variations
• Real-time monitoring output

Key Contributions:

• Developed a precision sensing system for continuous atmospheric electric field measurement
• Built signal processing and filtering mechanisms to improve data accuracy
• Implemented calibration techniques to ensure consistent and reliable output
• Enabled real-time tracking of electric field fluctuations for lightning detection use cases
• Integrated hardware sensing with data processing for actionable outputs
• Tested and validated system performance under varying environmental conditions

Constraints & Tradeoffs:

• High sensitivity to environmental noise requiring robust filtering
• Calibration drift affecting long-term accuracy
• Tradeoff between sensitivity and signal stability
• Hardware limitations impacting precision