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A fault detection and diagnosis strategy of VAV air-conditioning systems for improved energy and control performances

机译:VAV空调系统的故障检测和诊断策略,可改善能源和控制性能

摘要

This paper presents the results of a site survey study on the faults in variable air volume (VAV) terminals and an automatic fault detection and diagnosis (FDD) strategy for VAV air-conditioning systems using a hybrid approach. The site survey study was conducted in a commercial building. 20.9% VAV terminals were ineffective and 10 main faults were identified in the VAV air-conditioning systems. The FDD strategy adopts a hybrid approach utilizing expert rules, performance indexes and statistical process control models to address these faults. Supported by a pattern recognition method, expert rules and performance indexes based on system physical characteristics are adopted to detect 9 of the 10 faults. Two pattern recognition indexes are introduced for fault isolation to overcome the difficulty in differentiating damper sticking and hysteresis from improper controller tuning. A principal component analysis (PCA)-based method is developed to detect VAV terminal flow sensor biases and to reconstruct the faulty sensors. The FDD strategy is tested and validated on typical VAV air-conditioning systems involving multiple faults both in simulation and in situ tests.
机译:本文介绍了对变风量(VAV)终端中的故障进行现场调查研究的结果,以及使用混合方法对VAV空调系统进行自动故障检测和诊断(FDD)策略的结果。现场调查研究是在一栋商业建筑中进行的。 VAV空调系统中有20.9%的VAV端子无效,并且发现了10个主要故障。 FDD策略采用混合方法,利用专家规则,性能指标和统计过程控制模型来解决这些故障。在模式识别方法的支持下,采用专家规则和基于系统物理特性的性能指标来检测10个故障中的9个。引入了两种模式识别指标来进行故障隔离,以克服区分阻尼器粘滞和滞后与控制器调整不当的困难。开发了一种基于主成分分析(PCA)的方法来检测VAV终端流量传感器的偏差并重建故障传感器。 FDD策略在典型的VAV空调系统上进行了测试和验证,该系统在仿真和现场测试中都涉及多个故障。

著录项

  • 作者

    Qin J; Wang S;

  • 作者单位
  • 年度 2005
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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