คู่มือผู้ใช้ Coral Dev Board

การแนะนำ

The Coral Dev Board is a compact single-board computer designed for quickly prototyping on-device machine learning (ML) products. It features a removable System-on-Module (SoM) and an on-board Edge TPU coprocessor, enabling high-speed ML inferencing with low power consumption. This manual provides essential information for setting up, operating, and maintaining your Coral Dev Board.

สินค้าเกินview และส่วนประกอบ

The Coral Dev Board integrates a System-on-Chip (SoC) with ML capabilities and wireless connectivity, running a derivative of Debian Linux called Mendel.

มีอะไรอยู่ในกล่อง

• Removable system-on-module (SOM)
• 40-pin GPIO expansion header
• แจ็คเสียงขนาด 3.5 มม.
• 2 digital PDM microphones
• 2.54mm 4-pin terminal for stereo speakers
• พอร์ตไฟ Type-C
• Type-C OTG port
• Type-A 3.0 host
• Micro-B serial console port

กระดานรูปแบบ

Familiarize yourself with the key components of the Coral Dev Board.

ภาพ: มุมเอียง view of the Coral Dev Board, showcasing the heatsink and fan assembly, various ports (USB, HDMI), and the GPIO header. This board is designed for on-device machine learning.

ภาพ: จากบนลงล่าง view of the Coral Dev Board, highlighting the central fan and heatsink, along with the various connectors and chips on the board.

ภาพ: ด้านล่าง view of the Coral Dev Board, showing the underside of the circuit board with various solder points and the "Google" branding.

ภาพ: จากบนลงล่าง view of the Coral Dev Board with a standard paperclip placed next to it, illustrating the compact size of the development board.

การตั้งค่า

To begin using your Coral Dev Board, you will need to set up the operating system and development environment.

ขั้นตอนการตั้งค่าเริ่มต้น

1. แหล่งจ่ายไฟ: Connect a compatible Type-C power supply to the board's power port.
2. การเชื่อมต่อจอภาพ: Connect a display via the HDMI port if you require a graphical interface.
3. การเชื่อมต่อเครือข่าย: Connect to a network via Ethernet or configure Wi-Fi.
4. ระบบปฏิบัติการ: The board runs Mendel, a derivative of Debian Linux. Refer to the official Coral documentation for detailed instructions on flashing the OS image to an SD card and booting the device.
5. เครื่องมือพัฒนา: Install the Mendel development tools on your host machine. A 64-bit operating system is required for these tools.
6. การเข้าถึง SSH: Configure SSH access for remote login and file transfer. You may need to use the Mendel development tools to push SSH keys.

สภาพแวดล้อมของซอฟต์แวร์

The Coral Dev Board is optimized for machine learning inference using TensorFlow Lite models.

• TensorFlow Lite: Ensure your machine learning models are converted to TensorFlow Lite format for optimal performance on the Edge TPU.
• Python Support: Currently, Python is the primary language supported for development. Support for C++ is expected in future releases.

Operating the Coral Dev Board

The core functionality of the Coral Dev Board lies in its ability to perform high-speed machine learning inferencing on-device, thanks to its Google Edge TPU coprocessor.

On-Device ML Inferencing

The Edge TPU is capable of performing 4 trillion operations per second (TOPS), using only 0.5 watts per TOP. This allows for efficient execution of state-of-the-art mobile vision models, such as MobileNet V2 at 400 FPS.

แอปพลิเคชั่น

The Coral Dev Board is ideal for applications requiring high-performance computer vision with a small footprint and energy efficiency. This includes:

• Automated quality control in manufacturing.
• Robotics and autonomous systems.
• Smart home devices.
• Predictive maintenance.
• Any edge computing scenario where real-time ML inference is critical.

ข้อมูลจำเพาะ

การซ่อมบำรุง

To ensure the longevity and optimal performance of your Coral Dev Board, follow these maintenance guidelines:

• รักษาความสะอาด: Regularly clean the board with a soft, dry brush or compressed air to remove dust and debris, especially from the fan and heatsink.
• การควบคุมอุณหภูมิ: Ensure adequate ventilation to prevent overheating. The board is designed to run efficiently, but prolonged high-load operations in confined spaces may require additional cooling.
• จัดการด้วยความระมัดระวัง: Avoid static discharge by handling the board on an anti-static mat or by wearing an anti-static wrist strap.
• การอัปเดตซอฟต์แวร์: Periodically check for and install software updates for the Mendel operating system and TensorFlow Lite to benefit from performance improvements and security patches.

การแก้ไขปัญหา

If you encounter issues with your Coral Dev Board, consider the following common troubleshooting steps:

ปัญหาทั่วไปและแนวทางแก้ไข

1. เมนบอร์ดไม่เปิดใช้งาน:
   • Verify the Type-C power supply is correctly connected and provides sufficient power.
   • ตรวจสอบให้แน่ใจว่าเต้ารับไฟฟ้าทำงานได้
2. ไม่มีการแสดงผล:
   • ตรวจสอบการเชื่อมต่อสาย HDMI
   • Ensure your display supports the board's output resolution. Some small LCDs may not be compatible.
3. ปัญหาการเชื่อมต่อเครือข่าย:
   • For Ethernet, check cable connection and router status.
   • For Wi-Fi, verify network credentials and signal strength.
4. ML Inference Issues:
   • Confirm your models are correctly converted to TensorFlow Lite format.
   • Ensure the Edge TPU is properly recognized by the system.
   • Check for any error messages in your application logs.
5. ประสิทธิภาพการทำงานช้า:
   • Verify that your ML models are indeed running on the Edge TPU and not the CPU.
   • Monitor board temperature; excessive heat can lead to throttling.

For more detailed troubleshooting, consult the official Google Coral documentation and community forums.

การรับประกันและการสนับสนุน

For information regarding warranty coverage, technical support, and additional resources, please refer to the official Google Coral website or contact Google's customer support. Keep your purchase receipt for warranty claims.