Predictive maintenance devices perform the following tasks, from the moment of measurement all the way to data evaluation:
Predictive maintenance in smart buildings offers advantages ranging from the elimination of unnecessary maintenance tasks to tenant comfort and economic efficiency:
Typical predictive maintenance examples include HVAC units, which can be mission-critical in healthcare and industrial settings. Experience has shown that HVAC fans, motors, and compressors are the components most susceptible to failure. Information about airflow, current consumption, sound, and vibration can help to understand whether the unit is running smoothly or whether a failure is likely to occur soon. Leveraging Infineon’s products, the following critical parameters can be monitored:
• Airflow measurement at the compressor based on the XENSIV™ DPS368 barometric pressure sensor
• Current measurement at the fan and compressor based on the XENSIV™ TLI4971 current sensor
• Position sensing of the motor with XENSIV™ TLI493D-A2B6 3D magnetic sensor
• Sound anomaly detection in the unit with the XENSIV™ IM69D130 MEMS microphone
• Linear vibration measurement with XENSIV™ TLE4997E Linear Hall sensor
• Opened and closed lid detection with XENSIV™ TLE4964-3M Hall sensor
• Speed and direction measurement with XENSIV™ TLI4966G Double Hall sensor
• Data processing with XMC4700 or PSoC™ 6
• Secured connection and authentication with OPTIGA™ Trust M
Get a comprehensive overview of Infineon's sensor and IoT product portfolio for accurate and reliable data collection and processing for condition monitoring and predictive maintenance at: https://www.infineon.com/predictivemaintenance
If you’re interested in more information and insights on our solutions for smart buildings, visit our website www.infineon.io/smartbuilding
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