The cross-flow fan features a compact structure and uniform airflow distribution, making it widely used in scenarios such as rail transit air conditioning, HVAC purification, cabinet cooling, commercial air conditioning, and tunnel ventilation. It serves as the core execution unit for various temperature control and ventilation systems. Traditional operation and maintenance models rely on manual periodic inspections, making it difficult to promptly detect hidden faults like bearing wear, rotor imbalance, airflow reduction, and motor overheating, often leading to passive repairs only after fan failure. With the maturity of industrial sensing technology and IoT monitoring solutions, the integration of various sensors for cross-flow fan condition monitoring has driven the transition of equipment maintenance from reactive emergency repairs and scheduled inspections to predictive maintenance, enhancing the reliability, safety, and energy efficiency of ventilation systems.
Most faults in cross-flow fans are not sudden but result from a gradual degradation process. Signals such as vibration, temperature, rotational speed, air pressure, and airflow will exhibit characteristic changes in advance, which serves as the core focus for sensor monitoring. At the mechanical condition monitoring level, triaxial vibration sensors are critical components, typically mounted at the fan bearing housing or motor casing to continuously collect vibration acceleration and velocity signals across different frequency bands. Imbalances caused by dust accumulation on the impeller, wear of bearing balls, looseness in the shaft system, or abnormal assembly clearances will manifest as characteristic peaks in the vibration spectrum. After sensors transmit data in real time, the system can set threshold alerts to issue warnings before severe faults like abnormal noise, jamming, or bearing scraping occur, thereby preventing major damage such as impeller deformation or motor burnout.
Temperature sensors are deployed in conjunction with vibration monitoring systems, focusing on tracking the temperature of motor windings and bearing housings. The continuous operation of axial flow fans under limited cooling conditions can lead to excessive temperature rise due to voltage abnormalities, excessive load, or bearing jamming. PT100 and other temperature sensors can accurately capture temperature fluctuations, enabling controller-based overtemperature interlock protection. Once the temperature exceeds the safety threshold, immediate shutdown or load reduction is triggered to prevent insulation aging and motor burnout.
The air volume, air pressure, and rotational speed sensors are responsible for monitoring the output performance of the fan. Differential pressure sensors and air velocity sensors are installed at the inlet and outlet of the air duct to collect static pressure and air velocity data, convert real-time air volume, and detect ventilation capacity degradation caused by filter blockage, air duct leakage, or impeller slippage. The Hall speed sensor provides real-time feedback on the rotational speed of the shaft, compares it with the theoretical speed, identifies missing or blocked rotation faults, and supports closed-loop speed regulation with variable frequency drives. In scenarios such as rail transit and machine room cooling, where strict requirements are imposed on air volume stability, this type of sensor monitoring ensures stable heat exchange and dissipation capabilities, preventing main equipment from overheating and shutting down due to insufficient ventilation.
The entire monitoring chain consists of front-end sensors, acquisition modules, communication units, and an upper-level platform, supporting wired or IO-Link, wireless transmission. The raw signals collected by sensors undergo preprocessing at edge nodes, filtering out noise caused by on-site dust and variable-frequency electromagnetic interference, before being uploaded to the monitoring platform for automatic storage, trend curve generation, and fault logging. Maintenance personnel can remotely monitor the real-time operating conditions of each cross-flow fan without visiting the site. The platform establishes degradation models based on historical data to assess remaining service life, schedule maintenance orders rationally, and eliminate the need for blind disassembly and repair, significantly reducing spare parts and labor costs.
Tunnel ventilation fans are often installed in batches and scattered locations, with many devices hidden inside ducts or equipment units, making routine inspections difficult. The online monitoring solution with sensors effectively addresses the pain points of "invisibility, imprecise measurement, and delayed early warnings." However, during selection and installation, it is also necessary to adapt to on-site conditions: in high-dust or humid environments, prioritize sensors with higher protection ratings; at points with significant fan start-stop impacts, implement shock absorption and secure fastening to minimize data drift caused by vibration interference on the sensors themselves.
In the wave of intelligent upgrading across industries such as smart manufacturing, rail transit, and data centers, sensors have become the "digital senses" of ducted fans. By integrating multi-dimensional sensing signals for monitoring, it not only safeguards the safety baseline of ventilation systems and reduces unplanned downtime risks but also optimizes fan speed control strategies based on real operational data, minimizing unnecessary energy consumption. In the future, with the continuous iteration of smart sensing and edge diagnostic algorithms, the monitoring of ducted fans will further advance toward lightweight, low-power, and self-diagnostic capabilities, laying a solid foundation for intelligent, end-to-end management of ventilation and HVAC systems.