Fibrous filters play a crucial role in determining indoor air quality and protect people from bacteria, particulates, and viruses such as COVID-19. However, there is a lack of comprehensive research on methods for effectively evaluating and predicting the operating performance of these filters. In this study, we conducted laboratory and field tests on coarse (G4) and medium (F9 or F7) filters from four different brands to assess both their initial and operating performance. We discovered that a fluffy fiber structure in coarse filters could achieve an impressive threefold increase in dust holding capacity (DHC) compared to normal filters. Utilizing initial pressure drop, initial particle capture efficiency, and DHC, we introduced a new quality factor (Q) that integrates these parameters to evaluate the filter's long-term performance. This approach addresses the limitations of traditional quality factor, which neglects DHC and tends to underestimate the performance of filters with high DHC. Additionally, we proposed a simple method to predict the filter's operating pressure drop, using particle concentration data from weather report. This allows for convenient assessment of the fresh air system's operating status, offering potential integration into a user-friendly mobile application or computer software. These findings contribute innovative ideas for enhancing the intelligent and energy-efficient operation of fresh air systems.

中文翻译：

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住宅新风系统纤维过滤器运行性能评价与预测

纤维过滤器在确定室内空气质量并保护人们免受细菌、颗粒物和病毒（如 COVID-19）侵害方面发挥着至关重要的作用。然而，缺乏对有效评估和预测这些过滤器运行性能的方法的全面研究。在这项研究中，我们对四个不同品牌的粗滤器（G4）和中滤器（F9 或 F7）进行了实验室和现场测试，以评估其初始性能和运行性能。我们发现，与普通过滤器相比，粗过滤器中的蓬松纤维结构可以将容尘量 (DHC) 提高三倍，令人印象深刻。利用初始压降、初始颗粒捕获效率和 DHC，我们引入了一个新的品质因数 (Q)，它集成了这些参数来评估过滤器的长期性能。这种方法解决了传统品质因数的局限性，传统品质因数忽略了 DHC，并且往往会低估具有高 DHC 的滤波器的性能。此外，我们提出了一种简单的方法来使用天气预报中的颗粒浓度数据来预测过滤器的运行压降。这样可以方便地评估新风系统的运行状态，从而可以集成到用户友好的移动应用程序或计算机软件中。这些发现为增强新风系统的智能和节能运行提供了创新思路。