The amount of energy used in buildings accounts for 40% of our energy consumption worldwide. With a suitable building control system this consumption can be significantly reduced. For this purpose pertinent data on the building’s indoor and outdoor environment must be recorded. Pressure sensors are primarily used in the following devices:
- VAV ventilation
- Filter control
Ventilation in buildings is important for the control and monitoring of building facilities. Reducing the airstreams in buildings considerably lowers operating costs. Costs are cut by reduced fan outputs and less consumption of energy for air preparation (heating, cooling, humidification and dehumidification) and the system lifetime is lengthened. A variable air/volume flow is essential in buildings today. It must be regulated depending on the air quality, room temperature and room humidity and on consideration of the building’s users.
Fans are part of the ventilation system. They ensure the required flow of air in the ventilation shafts. Here, demand-based control is a basic requirement if energy is to be used efficiently. This in turn requires information on the amount of gas required and on the gas flow.
Soiled air filters increase the loss of pressure in air ducts and systems, resulting in higher fan outputs and a rise in energy costs. An electronic filter monitoring system with an integrated differential pressure sensor measures the drop in pressure across the filter and triggers a filter change warning in good time. Sensitive pressure sensors thus considerably help to ensure that ventilation and air conditioning systems operate cost effectively. Monitoring differential pressure also allows defects such as torn filters to be detected.
Compressors are used in HVAC systems to remove heat by compressing a gas or coolant and returning it to condensation temperature. Compression is usually performed at a high pressure, calling for robust sensors which are resistant to vibration. Heat pumps operate in a similar fashion and require high pressures in an inverse process.