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Fuzzy-genetic algorithm for automatic fault detection in HVAC systems

机译:暖通空调系统故障自动检测的模糊遗传算法

摘要

Detecting fault before it deteriorates the system performance is crucial for the reliability and safety of many engineering systems. This paper develops an intelligent technique based on fuzzy-genetic algorithm (FGA) for automatically detecting faults on HVAC system. Many researchers have proposed only using fuzzy systems to effect fault detection and diagnosis. Other applications of the FGA are mainly focused on the synthesis of fuzzy control rules. The proposed automatic fault detection system (AFD) monitors the HVAC system states continuously by fuzzy system. The optimization capability of genetic algorithms allows the generation of optimal fuzzy rules. Faults are represented as different fault levels in the AFD system and are distinguished by fuzzy system after tuning its rule table. Simulation studies are conducted to verify the proposed AFD system for the single zone air handler system.
机译:在故障恶化系统性能之前对其进行检测对于许多工程系统的可靠性和安全性至关重要。本文开发了一种基于模糊遗传算法(FGA)的智能技术,用于自动检测HVAC系统的故障。许多研究人员提出仅使用模糊系统来实现故障检测和诊断。 FGA的其他应用主要集中在模糊控制规则的综合上。所提出的自动故障检测系统(AFD)通过模糊系统连续监视HVAC系统状态。遗传算法的优化能力允许生成最佳模糊规则。故障在AFD系统中表示为不同的故障级别,并在调整规则表后通过模糊系统对其进行区分。进行了仿真研究,以验证用于单区域空气处理器系统的拟议AFD系统。

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