基于分类器链的多联机软故障水平辨识研究  

Research on Identification of Soft-fault Level in VRF System Based on Classifier Chain

作　　者：何宇轩 石靖峰 周镇新 陈焕新[1] 任兆亭 夏兴祥 程亨达 He Yuxuan;Shi Jingfeng;Zhou Zhenxin;Chen Huanxin;Ren Zhaoting;Xia Xingxiang;Cheng Hengda(School of Energy and Power Engineering,Huazhong University of Science and Technology,Wuhan,430074,China;Qingdao Hisense Hitachi Air-conditioning Systems Co.,Ltd.,Qingdao,266510,China)

机构地区：[1]华中科技大学能源与动力工程学院,武汉430074 [2]青岛海信日立空调系统有限公司,青岛266510

出　　处：《制冷学报》2023年第5期50-58,共9页Journal of Refrigeration

基　　金：国家自然科学基金(51876070)资助项目。

摘　　要：多联机空调系统在建筑中已得到广泛应用,在多联机的运行中,软故障较为常见,且难以识别,使系统效率下降。本文以一维卷积神经网络作为基分类器,提出一种基于分类器链的多联机软故障水平辨识模型,使用室外机脏污故障的实验数据,以故障诊断模型为基础设置了基分类器的结构及参数,提出两种新的对数据标签的编码方式。在初步建立软故障水平辨识模型之后,对基分类器中的卷积核数量进行了进一步调整,并提出放大系数以改进标签的编码方式。结果表明:改进后的分类器链模型对室外机脏污故障的诊断准确率可达96%以上,提高2%~3%,且本文提出的编码方式不会将故障工况诊断为正常工况,适合在分类器链模型中使用。Variable refrigerant flow(VRF) systems are widely used in buildings.Soft faults are common and difficult to identify during VRF operation,making the system less efficient.In this study,a soft-fault level identification model for VRF was proposed based on a classifier chain using one-dimensional convolutional neural networks as the base classifiers.The structure and parameters of the base classifiers were set according to a fault diagnosis model using the experimental data of fouling faults in the outdoor unit;two new methods for encoding data labels were proposed.After establishing the initial soft-fault level identification model,the number of convolution kernels in the base classifiers was further adjusted and a magnification factor was proposed to improve the label encoding.The results showed that the improved classifier chain model can diagnose fouling faults in the outdoor unit with an accuracy greater than 96%,corresponding to an increase of 2%-3% from the baseline.The encoding methods proposed in this study did not diagnose faulty conditions as normal and are suitable for use in the classifier chain model.

关 键 词：多联机 故障检测与诊断 故障程度辨识 分类器链 卷积神经网络 

分 类 号：TB657.2[一般工业技术—制冷工程] TU831.3[建筑科学—供热、供燃气、通风及空调工程]