4.5 Article

Smart Filter Performance Monitoring System

期刊

AEROSOL AND AIR QUALITY RESEARCH
卷 23, 期 4, 页码 -

出版社

TAIWAN ASSOC AEROSOL RES-TAAR
DOI: 10.4209/aaqr.220416

关键词

Filter performance; Filtration efficiency; Low-cost sensors; Air quality monitoring; Air filter

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Air filters are essential for removing particulate pollutants from the air to provide cleaner air. However, there is limited performance monitoring for air filters, leading to uncertainty in their efficacy after replacement. This study presents a prototype of a smart filter performance monitoring system that provides real-time data on filtration efficiency, differential pressure, temperature, and humidity. Three case studies demonstrate the feasibility and advantages of the system in various applications. It not only ensures the effectiveness of air purifiers and HVAC systems for residential customers but also allows industrial customers to monitor the cleanliness of filtered air for their internal combustion engines or gas turbines. Additionally, the filter monitoring data can be used for research purposes and product improvement.
Air filters are widely used in residential and industrial applications. It is designed to remove particulate pollutants in the air to supply cleaner air to either occupants or industrial equipment. Without air filters, the occupants might suffer from polluted air, and expensive industrial equipment could be damaged by contaminants. However, air filters are installed and operated with a limited performance monitoring system, and the efficacy of air filters is unknown after replacement. Here, we propose and prototype a smart filter performance monitoring system that costs less than 200 U.S. dollars and can report filtration efficiency, differential pressure, temperature, and RH (relative humidity) in real time. Three case studies are presented: an air purifier, a teaching building HVAC (heating, ventilation, and air conditioning) system, and a large-scale air cleaning system. Applications of the proposed system cover from household to industrial, which not only verified the concept of the system but also proved its feasibility and advantages of the system. With the proposed system, residential customers can rest assured with their air purifiers or HVAC furnace filter; industrial customers can monitor the filtered air cleanness that will enter their internal combustion engines or gas turbines. Moreover, filter monitoring data can establish a database for researchers to validate the filter models or train a machine learning model for filter performance prediction. Filter or air-cleaning device manufacturers can improve their products or recommend suitable products to their customers based on big data contributed by this filter monitoring system.

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