冷凝器结垢故障对传感器故障诊断方法的影响分析

传感器测量质量是实施系统监控，优化控制及部件故障诊断的重要保证。制冷机系统的部件故障和传感器故障很有可能同时发生。因而在研究传感器故障诊断的方法及应用这一方法进行传感器故障诊断时必须考虑到制冷机的部件故障的影响。根据离心式制冷机的试验数据研究了冷凝器结垢故障对基于主元分析法的制冷机传感器故障诊断方法的影响，研究结果表明基于主元分析的制冷机传感器方法对冷凝器结垢故障不敏感，该方法对有无结垢故障条件下的传感器故障都能成功地进行检测诊断及数据重构。     

基于小波变换的传感器故障诊断研究

主元分析法可以应用于空调系统的传感器故障诊断,但是测量数据中隐含的噪声及系统的动态性影响了这一方法在故障诊断时的效果。本文提出采用小波变换的方法对测量数据进行分解,利用不含噪声及动态性的低频信号进行传感器的故障诊断,即基于小波变换的主元分析故障诊断法。该方法采用一大型离心式制冷机的实测运行数据进行验证,且同时与常规的主元分析法进行比较,结果说明基于小波变换的主元分析法可以提高故障诊断水平。     

建筑能源管理与控制系统中传感器故障及其检测与诊断

描述了传感器故障类型，给出了其故障函数。用主成分分析法对建筑能源管理与控制系统测量数据进行建模并对空调检测系统中的四类传感器故障进行检测与诊断。结果表明主成分分析法具有很好的故障检测和故障诊断能力。     

基于BAS的空调系统过程监测与故障诊断

提出了基于BAS的空调系统过程监测与故障诊断模式，阐述用主成分分析法进行故障诊断的过程，并用其进行空调系统的传感器故障诊断。结果表明，主成分分析法具有很好的故障检测、故障识别和故障重构能力，还表明，故障诊断与BAS相结合是可行的。     

基于主元分析的冷水机组传感器故障识别

测量数据的真实性和准确性是冷水机组安全运行和优化节能的必要条件。长期使用条件下,传感器故障极易发生而且很难识别。在基于主元分析的传感器故障研究中,以Q统计量为检测指标的常规故障检测、诊断与数据重构在故障源的识别上存在一定误判。采用基于数据重构的枚举甄别方法,分析了传感器故障检测、数据重构及故障识别的算法流程,并以实际工程数据进行验证。结果表明,问题传感器的重构数据的故障识别指标变化最明显,可以准确鉴别故障传感器。     

基于数据驱动的变风量空调AHU故障诊断研究

变风量空调系统的空气处理机组(AHU)出现故障时会使系统舒适性降低,能耗和运维成本增加.本文提出了一种基于改进型主元分析(PCA)和BP神经网络算法,用于AHU的模型建立及故障诊断.结果表明使用改进滤波的PCA检测模型主元数为3个,累计贡献率92.7％.当系统传感器出现5％的故障偏差,模型在送风温度、 新风温度、 冷冻...     

基于主成分分析法的空调系统传感器自动故障诊断

由于各种各样的故障,空调系统在整个建筑生命周期内其性能很少能够达到设计目标。为了改善空调系统的性能,在整个建筑生命周期内对其进行定期或连续检测是很必要的。随着空调系统的日益复杂化和对快速可靠检测的需求,人工检测已远远不能满足要求,这使自动检测成为了必须。目前国际上研究建筑空调系统自动检测的技术很热门,但较少考虑空调系统传感器的准确性。传感器读数准确性是空调系统可靠控制和检测的先决条件。本文提出了一种基于主成分分析法的鲁棒故障诊断策略,该策略可以有效地对空气处理单元中的传感器进行自动检测。结合建筑自动化系统,该诊断策略可以实现空调系统传感器故障的在线检测。     

基于主成分法的VAV系统传感器故障检测与诊断

众所周知，VAV系统对控制的要求很高，作为控制系统中非常关键的元件——传感器，一旦出现故障将直接影响控制系统的决策，从而使VAV系统的运行偏离设计要求。因此，VAV系统传感器的故障检测与诊断研究是很有必要的。本文采用主成分分析法(PCA，Principal Component Analysis)对传感器故障的检测、确认与重构进行分析，以期获得一种可行的方案。     

基于STF的车辆ECAS传感器故障诊断研究

电控空气悬架(electronically controlled air suspension,ECAS)系统的有效控制依赖于传感器实时采集的正确车身状态信号。针对电控空气悬架传感器卡死、恒偏差、恒增益3种故障,建立1种ECAS故障检测与隔离方法(fault detection and isolation,FDI)。建立电控空气悬架三自由度1/4车模型以及传感器故障时空气悬架模型,设计故障检测滤波器组,结合传感器实时测量值获得空气悬架输出残差,在此基础上确定故障检测指标,计算指标数值并选取适当阈值进行比较。诊断滤波器采用强跟踪滤波器方法进行设计,选取两级决策变量构造隔离决策函数,实现对故障传感器的检测与隔离。仿真分析表明,所提出的基于STF的方法实现了ECAS传感器故障的检测与隔离,有效提高了车辆控制的可靠性与安全性。     

基于累积残差贡献率的传感器故障定位方法

为准确定位结构健康监测系统中的故障传感器,提出了基于累积残差贡献率的传感器故障定位方法。基于主元分析的基本原理,将车辆荷载和地脉动激励下传感器采集的数据分为主元空间和残差空间,采用SPE统计量对故障进行识别。在此基础上,通过对残差贡献值的推导,提出了累积残差贡献率指标,改进了现有的残差贡献图,提高了故障定位的准确率,并将单传感器故障定位拓展到两个故障传感器的同时定位。数值模拟结果表明:主元分析法能准确识别出预设的4类常见传感器故障,累积残差贡献率不但能更好地定位单传感器故障,两传感器同时发生故障时也能准确定位。     

A fault detection technique for air-source heat pump water chiller/heaters

This paper describes a fault detection method and system to detect the faults in air-source heat pump water chiller/heaters. Principal component analysis (PCA) approach is used to extract the correlation of variables in heat pump unit and reduce the dimension of measured data. A PCA model is built to determine the thresholds of statistics and calculate square prediction errors (SPE) of new observations, which are used to check if a fault occurs in heat pump unit. The fault detection system consists of a PCA-based fault detection code, a backpack computer, a digital logger and eight easy-to-install temperature sensors. A real air-source heat pump water chiller/heater for the air-conditioning system of an office building provides the realistic test platform for the validation of fault detection method. The measured data from the heat pump unit under normal condition shows that the PCA model can capture the major correlation and variance among the test variables. Two levels of artificial condenser fouling fault are successfully detected. The results show that the PCA-based fault detection method is applicable and effective for air-source heat pump water chiller/heater.     

A system-level fault detection and diagnosis strategy for HVAC systems involving sensor faults

This paper presents a strategy for fault detection and diagnosis (FDD) of HVAC systems involving sensor faults at the system level. Two schemes are involved in the system-level FDD strategy, i.e. system FDD scheme and sensor fault detection, diagnosis and estimation (FDD&E) scheme. In the system FDD scheme, one or more performance indices (PIs) are introduced to indicate the performance status (normal or faulty) of each system. Regression models are used as the benchmarks to validate the PIs computed from the actual measurements. The reliability of the system FDD is affected by the health of sensor measurements. A method based on principal component analysis (PCA) is used to detect and diagnose the sensor bias and to correct the sensor bias prior to the use of the system FDD scheme. Two interaction analyses are conducted. One is the impact of system faults on sensor FDD&E. The other is the impact of corrected sensor faults on the system FDD. It is found that the sensor FDD&E method can work well in identifying biased sensors and recovering biases even if system faults coexist, and the system FDD method is effective in diagnosing the system-level faults using processed measurements by the sensor FDD&E.     

冷水机组冷凝器水侧受阻故障模拟实验研究

采用理论分析和实验测试方法,对冷水机组冷凝器水侧受阻故障时空调系统冷水侧、制冷剂侧、冷却水侧的运行参数进行研究,确定对冷水机组冷凝器水侧受阻故障敏感的运行参数。冷却水出水温度、制冷剂冷凝温度、压缩机排气温度是对冷水机组冷凝器水侧受阻故障敏感的运行参数,可以作为检测识别该故障的主要依据。     

A robot fault diagnostic tool for flow rate sensors in air dampers and VAV terminals

A robot fault diagnostic tool for flow rate sensors in air dampers and VAV terminals is presented to ensure well capacity of energy conservation in building air conditioning systems. Principal component analysis (PCA) is used to detect the sensor faults including fixed bias, drifting bias and complete failure. To improve the detection efficiency, several PCA models are built through employing the conservation equations and control relations of the system. With the historical data, PCA models are trained to capture most useful information of normal operation. As a result, the training models can identify whether the present condition is abnormal through comparing the residues with the thresholds. Since the principal component subspace and residue subspace of the operation data space are obtained using PCA decomposition, these two subspaces are used to develop the fault isolation scheme. The new fault detected and the known ones in the library are all projected into the principal component subspace and residue subspace decomposed by PCA. The joint angle plot, illustrating the direction relations of the projections in both subspaces between the new fault and the known ones, is used to diagnose the fault source.     

螺杆式冷水机组的故障模拟及诊断软件的研究

中央空调系统故障排除通常中凭经验判断,这会造成一定的滞后甚至差错。洁净空调类的中央空调系统发生故障时,往往会带来更大的经济损失。因此,HVAC设备与系统故障诊断技术的研究和应用,对控制修复、故障排除和故障预防都有十分重要的意义。本文针对制冷机的工作特性和螺杆冷水机组故障进行了理论分析,得出了螺杆式冷水机组常见故障的表现特征,并在自行设计的实验系统上模拟了8个螺杆式冷水机组的常见故障。通过对实验数据的分析,筛选了5个制冷机运行参数作为故障判断的特征参数,通过分析研究这几个参数的变化规律总结出故障判断准则,在此基础上,编写了一套故障诊断软件,并在该实验系统上进行了 验证,结果表明该故障诊断软件运行可靠、诊断故障准确。