摘要
智能建筑空调机组故障检测与诊断是保证建筑环境安全、舒适、节能的基本方法.然而,多未知模态辨识仍是其中的关键难点之一.鉴于高斯混合模型(GMM)不受特定概率分布局限,可在区分类别的基础上直接得出数据的统计分布,具有优越的计算性能,且能拟合任意连续分布,本文提出一种基于GMM的空调机组多未知模态辨识方法.仿真试验结果表明,GMM聚类方法在空调机组运行模态辨识中具有较高的准确性与可靠性.
Fault detection and diagnosis for Air-Conditioning（ AC） system in intelligent building is the guarantee of building safety,comfort and energy-saving.How ever,the identification of unknow n modes for AC system is still one of the key difficulties.The Gaussian Mixture Model（ GMM） is not confined to a specified probability distribution and the distribution of given data can be obtained on the basis of classification.With excellent computing performance any continuous distribution can be fitted via GMM.Hence,a new idea of clustering based on GMM to identify the unknown operation modes in AC is developed.The simulation experiment has qualified the accuracy and reliability of this GMM mode identification approach.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2014年第10期2004-2008,共5页
Acta Electronica Sinica
关键词
空调机组
运行模态
高斯混合模型
辨识方法
air-conditioning（AC） system
operation mode
Gaussian mixture model（GM M）
identification approach
