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Evaluation of a Decoupling-Based Fault Detection and Diagnostic Technique-Part I: Field Emulation Evaluation

机译:基于解耦的故障检测和诊断技术的评估-第一部分:现场仿真评估

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Existing methods addressing automated fault detection and diagnosis (FDD) for vapor compression air conditioning system have good performance for faults that occur individually, but they have difficulty in handling multiple-simultaneous faults. The decoupling-based (DB) FDD method explicitly addresses diagnostics for multiple-simultaneous faults for the first time. This paper is the first part of a two-part evaluation of the DB FDD technique whose intent is to validate the DB FDD performance and demonstrate its applications. The first part focuses on sensitivity and robustness evaluation through controlled field emulation testing. Sensitivity tests with artificially introduced faults show that individual faults can be identified before they cause a 5% of degradation in cooling capacity, EER and sensible heat ratio. Robustness tests for forty-one multiple-simultaneous-fault combinations demonstrate that no wrong diagnosis occurs with only two false alarms and two sensitivity losses for a liquid-line restriction. The second part, accompanying the first one, focuses on field applications in California.
机译:解决蒸气压缩式空调系统的自动故障检测和诊断(FDD)的现有方法对于单独发生的故障具有良好的性能,但是它们在处理多个同时发生的故障方面存在困难。基于解耦(DB)的FDD方法首次明确解决了多个同时故障的诊断问题。本文是对DB FDD技术的两部分评估的第一部分,其目的是验证DB FDD性能并演示其应用。第一部分着重于通过受控现场仿真测试进行灵敏度和鲁棒性评估。对人为引入的故障进行的敏感性测试表明,在单个故障导致冷却能力,EER和显热比降低5%之前,可以对其进行识别。对41个多重同时故障组合的鲁棒性测试表明,对于液位限制,只有两个错误警报和两个灵敏度损失,才不会发生错误诊断。第二部分,与第一部分相伴,着重于加利福尼亚的现场应用。

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