对螺杆式冷水机组故障的探讨

本文针对螺杆式冷水机组故障诊断技术进行分析、探讨，得出了螺杆式冷水机组常见故障的表现特征，通过分析研究参数的变化规律总结出故障判断准则。     

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。     

离心式制冷机系统传感器故障诊断的试验研究

传感器的可靠性及准确性对制冷机系统的可靠控制和系统的最优运行起着至关重要的作用。同时,传感器的读数也是进行部件故障诊断的基础。本文提出了基于主元分析法的制冷机传感器故障诊断方法,该方法的主元分析模型由离心式制冷机系统中的相关测量变量在正常条件下的观测样本构成。这一方法利用这些变量在正常条件下的相关性来对传感器的测量观测值进行故障检测与诊断及测量重构,并分别用Q-统计及Q-分布图来对传感器故障进行检测及诊断。本文利用实验室离心式制冷机的试验数据对这一基于主元分析法的传感器故障诊断方法进行了验证。     

故障诊断技术应用于中央空调系统的研究进展

本文对中央空调系统的常见故障,故障诊断方法分类和研究进展进行了较全面的综述,并分别对传感器,执行机构,被控装置三个方面的故障检测与诊断技术在国内外的研究进展进行了介绍。与以往以时间轴为主线的分析方法不同,这种以故障发生器件为目标分类的方式更加清晰、直观地表达了故障诊断应用于中央空调系统中的研究状况。同时,根据研究进展本文总结了故障诊断研究的几个发展方向,为故障诊断研究的发展提供了一定的引导和方向。     

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。     

基于监测数据的冷冻水系统模型建立

通过针对大连市某公共建筑中央空调系统中冷水机组及输配系统水泵的运行参数进行实时检测,了解了冷水机组及水泵的运行状况,并建立运行参数数据库。基于该实测数据库,选取了恰当的冷水机组及水泵参数模型,并通过编程对模型参数分别进行了辨识,最后通过精准度分析,得出所建立的参数模型可以对冷水机组能耗、水泵功率、水泵扬程、水泵效率的预测准确率均可达到90%以上。     

海尔成功研发世界上第一台柔性变容量螺杆式水冷冷水机组

我国中央空调领域研发又有新突破。近日,记者从北京某专业机构了解到,海尔商用空调产品本部近日研发出世界上第一台柔性变容量螺杆式水冷冷水机组,它解决了长期以来中央空调运行成本高的难题,将运行成本降到了最低点,被北京的     

建筑空调系统诊断研究进展

中央空调系统是商业建筑的能耗大户,对中央空调系统的监控有利于掌握系统是否正常运行。当系统不能正常运行时,及时对系统进行诊断,并找出问题所在并提出解决问题的办法;即使系统正常运行,及时对系统的各种指标进行评估以判断系统是否在高能效下运行。因此对建筑空调系统进行各种故障的检测及诊断对保证系统的正常运行,提高系统能效及保证室内环境有重要意义。本文回顾了建筑空调系统故障诊断的研究情况及进展,同时指出这方面的研究应该加强各种诊断策略及方法在实际工程应用方面的研究。     

基于小波包分析的冷水机组故障诊断分析

模拟了单螺杆式冷水机组的9个常见故障,选取压缩机吸气温度和压缩机排气温度作为故障诊断的特征参数,将特征参数进行小波包分解和重构,提取故障特征信号,建立了特征向量-系统状态的对应关系。     

冷水机组故障诊断软件的开发

将模糊理论和人工神经网络运用于专家系统,开发出冷水机组故障诊断软件,以活塞式冷水机组作为实验平台验证了软件的运行效果良好。     

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.     

用参数自整定模型在线检测空气处理机组故障

大型现代建筑大都安装了能源管理与控制系统(EMCS),EMCS系统储存的大量监控数据为空调系统的在线故障检测与诊断提供了方便。提出了一种利用参数自整定空调部件模型在线检测变风量空气处理机组故障的方法。利用遗传算法优化模型参数使模型预测数据与实测值数据的残差最小,因此空调部件模型有较高的预测精度。若模型预测数据与实测数据的残差超出了预先设定的阈值,就意味着变风量空气处理机组可能存在故障。针对在实际应用时确定故障检测阈值的困难,给出了用统计方法确定阈值的方法。故障检测方法在真实建筑中进行了应用和验证,结果表明该故障检测方法可以结合EMCS系统准确有效的检测变风量空气处理机组故障。     

Fault diagnosis of air conditioning systems based on qualitative bond graph

The bond graph method represents a unified approach for modeling engineering systems. The main idea is that power transfer bonds the components of a system. The bond graph model is the same for both quantitative representation, in which parameters have numerical values, and qualitative approach, in which they are classified qualitatively. To infer the cause of faults using a qualitative method, a system of qualitative equations must be solved. However, the characteristics of qualitative operators require specific methods for solving systems of equations having qualitative variables. This paper proposes both a method for recursively solving the qualitative system of equations derived from bond graph, and a bond graph model of a direct-expansion, mechanical vapor–compression air conditioning system. Results from diagnosing two faults in a real air conditioning system are presented and discussed. Occasionally, more than one fault candidate is inferred for the same set of qualitative values derived from measurements. In these cases, additional information is required to localize the fault. Fault diagnosis is initiated by a fault detection mechanism which also classifies the quantitative measurements into qualitative values; the fault detection is not presented here.     

大型制冷机组故障调查与分析

介绍了制冷机组故障调查的方法、手段、时间、范围等,使用多种方法调查了制冷机组各部件的故障发生情况.同时,应用可靠性理论和故障率理论分析和总结了制冷机组的故障分布规律.所进行的调查和分析可为我国大型制冷机组行业提供有益的经验和基础数据.     

Application of the cumulative exergy approach to different air conditioning systems

The cumulative exergy approach is applied to evaluate two cases with different air conditioning systems. The first case includes three air conditioning systems, one is the gas direct fired air conditioning system, and the other two have air cooled heat-pump chiller and water chiller, respectively; the second case consists of four air conditioning systems, one is the gas direct fired air conditioning system, and the others have centrifugal water chiller, screw water chiller, air cooled water chiller, respectively. The results of the first case show that the air conditioning system with the air cooled heat-pump chiller maybe inferior to that with the water chiller, as the cumulative exergy efficiency of the former is 11.28%, which is less than that of the latter (11.92%). The second case shows that the gas direct fired air conditioning system, whose cumulative exergy efficiency is 14.86%, is better than the system with the air cooled water chiller, whose cumulative exergy efficiency is only 11.56%. The results are different from those of the exergy analysis, indicating that cumulative exergy analysis is an effective method to quantitatively evaluate different air conditioning systems according to resource utilization.     

Bayesian network based FDD strategy for variable air volume terminals

This paper presents a diagnostic Bayesian network (DBN) for fault detection and diagnosis (FDD) of variable air volume (VAV) terminals. The structure of the DBN illustrates qualitatively the casual relationships between faults and symptoms. The parameters of the DBN describe quantitatively the probabilistic dependences between faults and evidence. The inputs of the DBN are the evidences which can be obtained from measurements in building management systems (BMSs) and manual tests. The outputs are the probabilities of faults concerned. Two rules are adopted to isolate the fault on the basis of the fault probabilities to improve the robustness of the method. Compared with conventional rule-based FDD methods, the proposed method can work well with uncertain and incomplete information, because the faults are reported with probabilities rather than in the Boolean format. Evaluations are made on a dynamic simulator of a VAV air-conditioning system serving an office space using TRNSYS. The results show that it can correctly diagnose ten typical VAV terminal faults.     

A sensor fault detection strategy for air handling units using cluster analysis

Sensors are an essential component in the control systems of air handling units (AHUs). A biased sensor reading could result in inappropriate control and thereby increased energy consumption or unsatisfied indoor thermal comfort. This paper presents an unsupervised learning based strategy using cluster analysis for AHU sensor fault detection. The historical data recorded from sensors is first pre-processed to reduce the dimensions using principal component analysis (PCA). The clustering algorithm Ordering Points to Identify the Clustering Structure (OPTICS) is then employed to identify the spatial separated data groups (i.e. clusters), which possibly indicate the occurrence of sensor faults. The data points in different clusters are then checked for temporal separation in order to confirm the occurrence of sensor faults. The proposed sensor fault detection strategy is tested and evaluated with the data collected from a simulation system. The results showed that this strategy can detect single and non-simultaneously occurred multiple sensor faults in AHUs. The fault detection results were not strongly affected by the selection of the user defined input parameters required in OPTICS.