SENSOR FAULT DETECTION AND DIAGNOSIS FOR VAV SYSTEM BASED ON PRINCIPAL COMPONENT ANALYSIS

摘要：

VAV system is a very complicated one in air-conditionging systems, thus automatic control become the key of such a system. As necessary components in automatic control system, sensor has failure risk. It is so expensive that detect sensor fault by hardware redundancy in comfortable air-condi-tioning system. This paper presents an approach, Principal Component Analysis (PCA), to detect and identify sensor fault in VAV system. The PCA model partitions the measurement space into a principal component subspace (PCS) where normal variation occurs, and a residual rubspace (RS) that faults may occupy. When the actual fault is assumed, the maximum reduction in the squared prediction error (SPE) is achieved. A fault-identification index was defined in terms of SPE. Some examples were provided to prove this method is feasible. This paper also presents a fault reconstruction algorithm to reconstruct the identified faulty data.

关键词： Sensor fault Principal component analysis Residual subspace Squared prediction error Fault reconstruction VAV system

作者: Xiaowen Yi Youming Chen

作者单位: College of Civil Engineering, Hunan University, Changsha, Hunan 410082, China

会议类型: 国际会议

会议名称: 第10届建筑模拟国际会议

会议地点: 北京

会议语种:英文

在线出版日期: 2007-09-03（万方平台首次上网日期，不代表论文的发表时间）