Raspberry Pi DAQ: Turning a $60 SBC into a Precision Test Rig

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Raspberry Pi 5 ships with PCIe connectivity and a quad-core Cortex-A76 at 2.4 GHz, giving mechanical test benches enough horsepower to sample analog signals at kilohertz rates while running edge analytics locally. Engineers bolt a 24-bit simultaneous-sampling HAT onto the 16-lane FFC connector, map GPIO interrupts in Python, and stream synchronized acceleration, strain, and thermocouple data to an InfluxDB instance. The bill of materials—including a heat-sink case and industrial device-tree overlay—comes in under 250 dollars, a fraction of proprietary data-acquisition modules yet offering comparable 104 dB SNR for mid-band applications.

Prototyping loops tighten when acquisition hardware fits in a jacket pocket. A machinist rough-cuts an aluminum bracket, mounts it on a shaker table, and wires piezoelectric accelerometers to the Pi HAT. Within minutes, a Grafana dashboard visualizes peak-to-peak acceleration, letting the designer tweak rib geometry and rerun the test before shop cleanup. By pairing the DAQ with a 3-D-printed sensor pod, teams validate modal frequencies of drone frames, bike components, or injection-molded housings without booking time on a corporate dynamics lab—empowering rapid iteration and local decision-making.

Design-for-manufacture meets edge computing when Pi-powered DAQs station themselves on the production line. Engineers model enclosure ribs and cable glands in CAD so the single-board computer nests within a standard DIN-rail case, protecting it from coolant spray and electromagnetic noise. Draft angles are added for easy ejection in a two-slide mold, and heat-sink fins align with core pins that keep wall thickness uniform, preventing sink marks that would impede airflow. These DfM touches enable volume production of rugged enclosures at domestic plastics shops, supporting reshored final assembly.

New sensor-fusion frameworks leverage the Pi 5’s GPU for on-device AI. A tensor-accelerated VibrationNet model flags bearing defects in real time, pushing alerts to the MES long before scrap occurs. Because the codebase is open source, manufacturers avoid vendor lock-in and can harden cybersecurity in line with ISO/SAE 21434. Regional contract manufacturers in Mexico now preload Pi images with calibrated ADC drivers, so U.S. plants receive plug-and-play modules—shortening supply chains and insulating programs from global silicon shocks.

Raspberry Pi DAQ rigs are not cure-alls; engineers must still shield cables, compensate for 3.3 V logic levels, and respect Nyquist limits. Yet the platform’s expanding ecosystem of isolating HATs, PoE+ hats, and real-time kernels makes it a credible alternative to legacy systems. Teams that embrace the Pi’s blend of openness and compute density will find data-driven design decisions arriving faster and at far lower cost than ever imagined.

Creator: Rui Vale de sousa | Credit: Getty Images/Hemera
 

 

References
Raspberry Pi Foundation Blog, “PCIe Unlocks New Industrial I/O on Pi 5,” April 2025
IEEE Spectrum, “Open DAQ Platforms Challenge Proprietary Test Gear,” February 2024
Make: Magazine, “Building a Pi-Based Vibration Logger,” March 2025
Automation World, “Edge AI on Single-Board Computers,” January 2025

Target Keywords: raspberry pi daq, low-cost data acquisition, pi 5 i/o hat, test bench instrumentation, edge analytics, manufacturing monitoring

About This Blog

Mantix Engineering curates these articles to spark fresh thinking around mechanical design, prototyping, and advanced manufacturing. Topics rotate intentionally, so whether you model injection‑molded parts, tune CNC tool paths, or explore next‑generation additive processes, you’ll always find something new to learn.

Need hands‑on support for your next project? Visit Mantix Engineering to see how our engineers can accelerate your product from concept to production.

 

Location: Seattle, WA, USA

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