Common Mistakes to Avoid When Procuring Data Acquisition Systems for Triaxial Labs

Buying a DAQ for triaxial testing isn’t just about “how many channels” and “what sampling rate”. The right platform must speak your sensors’ language, capture clean, synchronous data, slot into your software workflow, and scale with your lab. Here are the big pitfalls—and what to do instead.

Why Overlooking Sensor Compatibility Causes Problems

Typical mistakes

• Choosing DAQs that can’t excite mV/V bridge sensors¹ (load cells, pressure transducers) with stable, low-noise excitation.
• No native support for LVDTs² (displacement), forcing makeshift analogue inputs and noisy demodulation.
• Ignoring ±10 V / 0–5 V / 4–20 mA channels for smart transmitters, or missing digital buses (RS-485/Modbus, encoder inputs).
• Mismatched connectors, poor shielding, and no strain relief—leading to intermittent faults.

Symptoms

• Drifting zero, poor repeatability, B-values that won’t stabilise, or “steppy” strain.
• Excessive noise on displacement and pore pressure.

Do this instead

• Map sensors → interfaces before you shop:

  Sensor	DAQ must support	Notes
  Load cell (mV/V)	Stable bridge excitation (2.5–10 V), low-noise amp, 18–24-bit ADC	Shunt cal & thermal stability help
  Pore/cell/back pressure	mV/V or 0–5 V; clean analogue inputs	Temperature-compensated transducers preferred
  LVDT	Native LVDT module or AC excitation + demod	Rigid mounting cuts mechanical noise
  Volume change (pump/encoder)	Encoder/digital counts or analogue input	Derive flow/volume in software
  Temperature	RTD/thermistor input with linearisation	Useful for drift diagnostics

• Require multi-point, up/down calibration routines with certificate storage and expiry reminders.

• Specify shielded cabling, proper connectors (BNC/DIN/5-pin), and documented earthing.

Why Underestimating Sampling Speed Hampers Accuracy

Typical mistakes

• One “global” sample rate for every channel.
• No anti-alias filtering; or sampling too low for displacement control.
• Channels sampled on different clocks → phase errors in ( q!-!p’ ) paths.

What goes wrong

• Aliasing and jagged stress–strain curves.
• Incorrect B-checks and rate-dependent artefacts.
• Missed peaks in cyclic or post-peak behaviour.

Do this instead

• Match rate to signal bandwidth and add proper filtering:

  Channel	Monotonic CU/CD	Low-pass (start point)
  Axial load / pressures	10–20 Hz	2–5 Hz
  Displacement (LVDT)	20–50 Hz	5–10 Hz
  Volume change	5–10 Hz	1–2 Hz

• For cyclic/dynamic, require simultaneous sampling at 100–1,000+ Hz.

• Insist on a single hardware clock across channels (don’t trust PC-clock sync).

• Publish noise specs (rms/ENOB) and give access to filter settings.

How Ignoring Software Integration Creates Workflow Gaps

Typical mistakes

• Closed data formats that won’t export to LIMS or spreadsheets.
• No calculated channels³ ( ( q ), ( p’ ), ( \varepsilon_a ), ( \varepsilon_v ), B-value )—forcing error-prone manual sheets.
• Lack of scripts⁴ for stages (saturation → consolidation → shearing) and no stop conditions (u-excess, strain limit, post-peak %).
• Missing auto-save, checkpoints, audit logs, or role-based access → traceability risks.

Consequences

• Time lost re-keying data; inconsistent methods between operators.
• Painful audits; hard-to-defend results.

Do this instead

• Require:
  • Versioned method & channel templates with units, scale factors, zeroing rules.
  • Calculated channels for effective stress and stiffness windows (E50).
  • Scripted control + interlocks (over-pressure, over-stroke) and stop rules.
  • Open exports (CSV/TDMS/Parquet) with rich metadata (operator, calibration IDs, firmware).
  • Auto-save + checkpoint files + checksums; audit trails aligned with ISO/IEC 17025 practice.

Why Neglecting Scalability Increases Future Costs

Typical mistakes

• Buying to today’s channel count with no room for a second cell, cyclic module, or smart pumps.
• Non-modular hardware; short product life; no firmware pathway.
• Under-spec’d network/storage for parallel tests.

Downside

• A second DAQ just to add two sensors; mismatched systems; duplicated training and spares.
• Costly re-validation and downtime when you “rip and replace”.

Do this instead

• Choose modular or networkable⁵ DAQs with spare analogue/digital slots and clean Ethernet comms.
• Keep performance headroom⁶: 24-bit for mV/V, channel isolation, stable excitation, CPU/network capacity for multiple rigs.
• Check lifecycle: 5–10 years of parts/firmware, field-replaceable modules, clear calibration/service pricing.
• Plan storage: local + mirrored disk, and automatic archiving to NAS/LIMS.

Quick Procurement Scorecard (print this)

Bottom Line

Most DAQ regrets come from four blind spots: sensor fit, sampling & sync, software workflow, and scalability. Tackle those upfront and you’ll buy once, test faster, pass audits, and get cleaner ( q!-!p’ ) paths with fewer re-tests—and a lab that grows without ripping out what you just installed.