非稳态条件下暖通空调系统传感器金属材料故障诊断  

Fault diagnosis of metal materials in sensors of HVAC systems under non-steady state conditions

作　　者：苏向阳[1] SU Xiangyang(General Department Nanning First People's Hospital,Nanning 530022,Guangxi,China)

机构地区：[1]南宁市第一人民医院总务科,广西南宁530022

出　　处：《金属功能材料》2024年第3期99-106,共8页Metallic Functional Materials

摘　　要：暖通空调系统的运行状态会随时间发生变化,在这种非稳态条件下进行传感器金属材料故障诊断,会导致诊断性能下降,对此,研究非稳态条件下暖通空调系统传感器金属材料故障诊断方法。首先,利用CEEMD法与小波变换法对采集到的数据进行预处理,降低非稳态条件下的噪声干扰。然后,根据已知的传感器金属材料故障类型进行故障特征提取;最后,采用LSTM网络实现暖通空调系统传感器金属材料故障诊断。实验结果表明,所提方法去噪效果好、检测精度高、检测效率高,适用于暖通空调系统传感器金属材料的故障诊断。The operating status of HVAC systems can change over time.Diagnosing sensor metal material faults under such non-steady state conditions can lead to a decrease in diagnostic performance.Therefore,a method for diagnosing sensor metal material faults in HVAC systems under non-steady state conditions is studied.Firstly,the collected data is preprocessed using CEEMD and wavelet transform methods to reduce noise interference under non-stationary conditions.Then,fault features are extracted based on known types of sensor metal material faults.Finally,an LSTM network is used to achieve the diagnosis of metal material faults in HVAC system sensors.The experimental results show that the proposed method has good denoising effect,high detection accuracy,and high detection efficiency,and is suitable for fault diagnosis of metal materials in sensors in HVAC systems.

关 键 词：非稳态条件 暖通空调系统传感器 长短期记忆神经网络 金属材料故障诊断 小波变换法 

分 类 号：TU831.3[建筑科学—供热、供燃气、通风及空调工程]