IPC Protocol Wiretapping & Packet Analysis

Role

Engineer Intern

Organisation

A*STAR Advanced Remanufacturing and Technology Centre (ARTC)

Period

Sep 2022 – Apr 2023

Tech Stack

Python, Wireshark, Matplotlib, Ethernet Powerlink (EPL)

Network Packet Analysis

The Challenge

To evaluate the elemental composition of metal powder during a print, we needed to integrate an optical spectrometer to capture plasma emissions excited by the printer's laser. However, the spectrometer must only collect data when the building platform and recoater blade are stationary. Because commercial 3D printers are closed systems, we had to reverse-engineer the machine's internal states to synchronize our external sensors.

Network Wiretapping & Data Capture

Working alongside senior engineers, we achieved this by hardware tapping the machine's Industrial PC (IPC) to eavesdrop on the internal Ethernet Powerlink (EPL) V2 network communications.

Python Data Pipeline & Optimization

With the raw network traffic captured, the next step was parsing the hex strings into usable integer formats and plotting them over time to find visual patterns corresponding to physical machine movements.

Reverse-Engineering Results

To verify what these mysterious packet graphs represented, I cross-referenced their visual peaks and troughs against our known InfluxDB telemetry data (which tracked actual recoater speed, dispenser position, and filter pressure).

Through this analysis, I successfully proved that "Node ID 2" perfectly correlated with the position and speed of the recoater blade. Deciphering these packets established the crucial baseline needed to automatically trigger the spectrometer and other quality-assurance sensors exactly when the machine was in the correct state.

Project Resources

Download Project Report (PDF) Download Project Poster (PDF)