TIDUF85A August   2024  – December 2024

 

  1.   1
  2.   Description
  3.   Resources
  4.   Features
  5.   Applications
  6.   6
  7. 1System Description
    1. 1.1 Key System Specifications
  8. 2System Overview
    1. 2.1 Block Diagram
      1. 2.1.1 Subsystems
        1. 2.1.1.1 Arc Detection Channels
          1. 2.1.1.1.1 Isolated Current Measurement
          2. 2.1.1.1.2 Band-Pass Filter
          3. 2.1.1.1.3 Analog-to-Digital Conversion
          4. 2.1.1.1.4 Arc Detection Using Embedded AI Models
        2. 2.1.1.2 Arc Labeling Circuit
          1. 2.1.1.2.1 Isolated String Voltage Measurement
          2. 2.1.1.2.2 Isolated Arc Voltage Measurement With Isolated Comparator
          3. 2.1.1.2.3 Window Comparator for Advanced Labeling
    2. 2.2 Design Considerations
      1. 2.2.1 Current Sensor and Input Stage
      2. 2.2.2 Analog Band-Pass Filter
      3. 2.2.3 Arc-Labeling Circuit
        1. 2.2.3.1 String Voltage Sensing
        2. 2.2.3.2 Arc Gap Voltage Sensing
        3. 2.2.3.3 Differential to Single-Ended Conversion
        4. 2.2.3.4 Window Comparator for Arc Labeling
      4. 2.2.4 Auxiliary Power Supply
      5. 2.2.5 controlCard and Debug Interface
    3. 2.3 Highlighted Products
      1. 2.3.1 TIEVM-ARC-AFE
      2. 2.3.2 TMDSCNCD28P55X – TMDSCNCD28P55X controlCARD Evaluation Module
        1. 2.3.2.1 Hardware Features
      3. 2.3.3 OPA4323 – Quad, 5.5V, 20MHz, Zero-Cross Low-Noise (6nV/√Hz) RRIO Operational Amplifier
      4. 2.3.4 OPA323 – Single, 5.5V, 20MHz, Zero-Cross Low-Noise (6nV/√Hz) RRIO Operational Amplifier
      5. 2.3.5 AMC3330 – ±1V Input, Precision Voltage Sensing Reinforced Isolated Amplifier With Integrated DC/DC
      6. 2.3.6 AMC23C11 – Fast-Response, Reinforced, Isolated Comparator With Adjustable Threshold and Latch Function
  9. 3Hardware, Testing Requirements, and Test Results
    1. 3.1 Signal Chain Verification
      1. 3.1.1 Hardware Requirements
      2. 3.1.2 Test Setup
      3. 3.1.3 Test Results
    2. 3.2 Arc Testing
  10. 4Design and Documentation Support
    1. 4.1 Design Files
      1. 4.1.1 Schematics
      2. 4.1.2 BOM
    2. 4.2 Tools and Software
    3. 4.3 Documentation Support
    4. 4.4 Support Resources
    5. 4.5 Trademarks
  11. 5About the Author
  12. 6Revision History
2.1.1.1.4 Arc Detection Using Embedded AI Models

The acquired data is fed into a preprocessing block followed by an embedded AI model. More details regarding the process of detecting arcs using AI models are found in the software users guide, which is included in the software download folder.