Weld Monitoring Dashboard

Built a real-time weld monitoring dashboard streaming arc current (0–300A), arc voltage (0–50V), and TCP position at 90Hz with synchronized CSV data capture — used for weld quality diagnostics, process optimization, and compliance with welding standards (AWS D1.1, ISO 3834). Optimized EtherNet/IP polling from 10Hz to 125Hz to achieve the data rate.

Developed a Chart.js-based real-time streaming dashboard with dual-axis weld plotting: left Y-axis shows arc current (0–300A range), right Y-axis shows arc voltage (0–50V range), sharing a synchronized time axis with continuous scrolling. A separate TCP position chart plots X/Y/Z coordinates of the welding torch tip (Tool Center Point) computed from forward kinematics — enabling direct correlation between weld parameter excursions and physical position on the workpiece. Rolling statistics compute and display average current and voltage, peak values, torch duty cycle percentage, and actual message rate in Hz to verify data throughput. Interactive point selection lets operators click on chart points for post-weld quality analysis.

Achieved 90Hz data throughput by optimizing the EtherNet/IP Requested Packet Interval (RPI) from the default 100ms (10Hz) to 8ms (125Hz output from the Miller welder, yielding ~90Hz after network jitter and processing). Applied voltage calculation fixes using Math.abs() with lowered detection threshold from 0.01 to 0.001 for accurate voltage reporting near zero-crossings. Implemented a 250ms throttle (4Hz) for diagnostic display updates while the underlying data streams at 90Hz — the UI refreshes smoothly while the data pipeline captures every sample.

Built a complete CSV recording system with start/stop control capturing every sample: timestamp, arc current, arc voltage, X/Y/Z TCP position, torch state (on/off), and gas state (flowing/stopped). This enables post-weld quality analysis against welding code requirements — many standards including AWS D1.1 (structural steel) and ISO 3834 (quality requirements for fusion welding) require documented weld parameters as proof of process compliance. Built three supporting test tools: a welding status simulator, a standalone simulator (complete test environment requiring no ROS infrastructure), and a headless Python weld recorder (weld_recorder.py) that subscribes directly to the ROS topic for background CSV capture.