Wiznet makers

WIZnet

Published February 17, 2023 ©

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Original Link

AI-driven IoT 3D Printer Motion & Status Tracker w/ Telegram

Ethernet HAT Contest winner project

COMPONENTS Hardware components

Raspberry Pi - Raspberry Pi Pico

x 1


WIZnet - WIZnet Ethernet HAT

x 1


DFRobot - HuskyLens AI Camera

x 1


Raspberry Pi - Raspberry Pi 4

x 1


Creality - CR-6 SE 3D Printer

x 1

Software Apps and online services

thonny.org - Thonny

x 1


Raspberry Pi - Raspbian

x 1


Adafruit - Circuitpython

x 1


Autodesk - Fusion 360

x 1


UltiMaker - Cura

x 1


microsoft - Visual Studio 2017

x 1


PROJECT DESCRIPTION

This project is Ethernet HAT contest winner and was moved from old maker site.

Story

Step 1: Designing and printing a T-800 Terminator-inspired case

Since I wanted to place the device towards my FDM 3D printer while printing 3D models in my workshop, I decided to design a complementing metallic case to create a robust and sturdy mechanism operating flawlessly. To make device connections more accessible, I added a removable top cover to the case. Then, I got inspired by The Terminator to add a T-800 replica to the device since it aims to track the movements of the printer and detect potential malfunctions to eliminate them :)

I designed the main case and its removable top cover in Autodesk Fusion 360. You can download their STL files below.

For the T-800 replica affixed to the removable top cover, I utilized this model from Thingiverse:

Then, I sliced all 3D models (STL files) in Ultimaker Cura.

Since I wanted to create a solid structure for the metallic case with the removable top cover and emphasize the T-800 theme, I utilized this PLA filament:

  • eSilk Silver

Finally, I printed all parts (models) with my Creality CR-6 SE 3D Printer. Although I am a novice in 3D printing, and it is my first FDM 3D printer, I got incredible results effortlessly with the CR-6 SE :)

Step 1.1: Assembling the case and making connections & adjustments

First of all, I soldered female pin headers (11mm long legs) to the WIZnet Ethernet HAT and male pin headers to the Raspberry Pi Pico in order to connect them to the mini breadboard as shown below.

To recognize the learned tags (AprilTags) so as to track the printer motions (X-axis, Y-axis, and Z-axis), I connected the HuskyLens AI camera to the Raspberry Pi Pico by utilizing the I2C protocol. Also, I added a 10mm common anode RGB LED module (Keyes) and a buzzer to indicate the outcomes of operating functions.

Since the Raspberry Pi Pico operates at 3.3V, it is not able to power the HuskyLens AI camera and the RGB LED at the same time sufficiently. Therefore, I employed an external power source to supply the mentioned components: To elicit stable supply voltage, I connected a USB buck-boost converter board to a Xiaomi power bank.

After completing sensor connections and adjustments on mini breadboards successfully, I made the breadboard connection points rigid by utilizing a hot glue gun.

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