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A Fuzzy Logic-Based Automation toward Intelligent Air Conditioning Systems

机译:基于模糊的逻辑自动化智能空调系统

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Most of the energy used in residential buildings originates from air conditioners. Meanwhile, air conditioner manufacturers are addressing this issue by the production of efficient air conditioners. However, the convertible frequency air conditioners are expensive, up to 60% higher than the fixed frequency control air conditioners. Besides the human behavior in determining the temperature, setpoint plays an important role regardless of the air conditioners technology used. This study incorporated intelligence in setting up the temperature by means of specially designed remote control. The Tsukamoto fuzzy reasoning was utilized as a decision making system with two inputs, namely the outdoor temperature and the number of occupants. The device used DHT22 as the temperature sensor and HC-SR04 to detect incoming and outgoing occupants. Furthermore, the fuzzy inference system generated infrared signal associated with the temperature setpoint. This signal was received by the air conditioner receiver to adjust the temperature setpoint accordingly. The result of this study showed that the fuzzy inference system determines the temperature setpoint appropriately under variations of surrounding temperature and the number of occupants. The proposed approach yielded a satisfactory perception of thermal comfort and also a promising approach to energy conservation.
机译:住宅建筑中使用的大部分能量来自空调。与此同时,空调制造商正在通过生产高效的空调来解决这个问题。然而,可转换频率空调昂贵,高达60%高于固定频率控制空调。除了确定温度时的人类行为,设定值不论使用所使用的空调技术如何起着重要作用。本研究通过专门设计的遥控器在建立温度时融入了智能。 Tsukamoto模糊推理用作具有两个输入的决策系统,即室外温度和乘员的数量。该器件使用DHT22作为温度传感器和HC-SR04来检测进出的乘员。此外,模糊推理系统产生了与温度设定值相关的红外信号。该信号由空调接收器接收,以便相应地调节温度设定点。该研究的结果表明,模糊推理系统在周围温度和乘员人数的变化下适当地确定温度设定点。该拟议方法对热舒适感产生了令人满意的感知,也有希望的节能方法。

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