Air Velocity Transducers

Continuous airflow measurement is often the missing link between spot checks and true understanding of system behavior. TSI air velocity transducers give R&D teams a reliable way to measure velocity over time and integrate those measurements into data acquisition platforms and control schemes. The result is richer datasets for model validation and tighter process control during experiments and pilot operations.

Designed for fixed installation, these compact transducers mount directly in ducts, hoods, tunnels, and chambers. Available analog and digital outputs connect to DAQ systems, PLCs, or building controls, enabling real-time monitoring and feedback. Stable sensing supports long-duration studies, helping researchers quantify diurnal effects, equipment cycling impacts, and the performance of new control strategies.

How transducers advance R&D workflows:

• Continuous datasets support system identification, model validation, and control tuning.
• Real-time signals enable closed-loop control experiments and automated test sequences.
• Trend analysis reveals drift, seasonal shifts, and equipment degradation.
• Correlation with temperature, humidity, and pressure builds a complete environmental profile.

Benefits for research programs:

• Integration-ready outputs and form factors for quick installation.
• Stable performance for extended monitoring campaigns.
• Scalable deployment across multiple points for spatial insight.
• Reduced manual measurement burden and improved data granularity.

Use cases:

• Environmental chamber velocity monitoring for uniformity and repeatability studies.
• Duct velocity tracking during HVAC optimization or novel control research.
• Fume hood and enclosure development requiring steady-state and transient analysis.
• Pilot plant processes that benefit from airflow feedback in safety-critical operations and quality outcomes.

By converting airflow into continuous, actionable signals, TSI air velocity transducers help researchers move beyond snapshots. With better visibility into how systems behave over hours and days, teams can validate models, refine processes, and deliver stronger evidence for design and operational decisions.