A rule-based fault detection method for air handling units

Air handling unit performance assessment rules (APAR) is a fault detection tool that uses a set of expert rules derived from mass and energy balances to detect faults in air handling units (AHUs). Control signals are used to determine the mode of operation of the AHU. A subset of the expert rules which correspond to that mode of operation are then evaluated to determine whether a fault exists. APAR is computationally simple enough that it can be embedded in commercial building automation and control systems and relies only upon the sensor data and control signals that are commonly available in these systems. APAR was tested using data sets collected from a “hardware-in-the-loop” emulator and from several field sites. APAR was also embedded in commercial AHU controllers and tested in the emulator.     

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.     

A robust fault detection and diagnosis strategy for pressure-independent VAV terminals of real office buildings

A robust fault detection and diagnosis (FDD) strategy using a hybrid approach is presented for pressure-independent variable air volume (VAV) terminals in this paper. The residual-based cumulative sum (CUSUM) control charts are utilized to detect faults in VAV terminals. The residuals between the temperature error and its predication are generated using autoregressive time-series models. The standard CUSUM control charts are used to monitor the residuals which are statistically independent. If the CUSUM value exceeds the chart limits, it means the occurrence of fault or abnormity in the corresponding VAV terminal. The residual-based CUSUM control chart can improve the accuracy of fault detection through eliminating the effects of serial correlation on the performance of control charts. Also, the residual-based CUSUM control chart can enhance the robustness and reliability of fault detection through reducing the impacts of normal transient changes. A rule-based fault classifier consisting of expert rules and fault isolation algorithms is developed to isolate 15 fault sources. The FDD strategy was online tested and validated using in real time data collected from real VAV air-conditioning systems.     

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

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.     

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.     

变风量空调系统的新风

介绍了ASHARE标准关于变风量空调系统中新风量确定的方法，常用的新风量测量方法和控制方法以及新风的利用，探讨了测试中发现的新风量确定和新风品质等问题。     

Validated air handling unit model using indirect evaporative cooling

This paper presents the validated Modelica model of a Menerga? Adsolair? type 58 Air Handling Unit. The unit consists of two fans, four dampers, three air filters and further allows heat recovery (including free cooling), indirect evaporative cooling and active cooling. The first principles model uses manufacturer data sheet information and optionally also measurement data to calibrate some parameters for increased accuracy. Model validation is based on measurement data and results in an average normalized absolute error for the electrical power consumption of approximately 1%. A custom developed control strategy is compared with the measured performance of a proprietary controller. The model is available open source as part of the IDEAS Modelica library.     

改良双风道系统空气处理机的应用

以北京丽都饭店一期工程空调系统为例,介绍改良双风道空调系统的优缺点,这种系统初投资少,由1台机组可以获得两种状态参数的空气,可满足不同区域对不同空气参数的要求。2002年测试了空调系统运行参数,结果表明空调机组基本可以满足设计要求。     

带有溶液热回收器的新风空调机

为了解决新风量的增加受新风处理能耗制约的问题 ,提出了一种带有溶液热回收器的新风空调机 ,分析了其工作原理和特点。由于热回收效率高 ,新风处理能耗大大降低 ,新风机的性能系数可以达到 6～ 1 0。新风机中盐溶液的喷淋能够起到杀菌除尘的作用。     

圆形断面净化空调机组相关问题的探讨

建立了数学模型,对比分析了圆形断面和正方形断面空调机组的沿程阻力,表冷器、过滤器的断面风速和阻力,机组的隔声性能.结果表明,在相同条件下,圆形断面空调机组的沿程阻力可以降低11％,但是以多占用机房面积为代价的;表冷器、过滤器阻力明显增加;机组壁板的隔声效果较差.     

Excel在制冷机组故障检测与诊断工具开发中的应用

用Excel表格作为后台数据库,在VC平台上结合.NET数据库技术,开发了大型制冷机组的故障检测与诊断工具。用现场实验数据进行检验表明,该故障检测与诊断工具具有运行稳健,故障检测准确、快速等优点,能够用于生产现场的实时故障检测与诊断。     

空调系统的VAV末端

概要介绍了空调系统ＶＡＶ末端的工作原理、产品特点、基本组合、部件结构、选型及设备使用方法，预测了ＶＡＶ末端在国内的发展前景。     

内区新风机组盘管的选型设计

分析了冬季空调内区房间过热及内区新风机组盘管冻裂的原因,通过对冬、夏不同工况加热冷却盘管的选型计算,提出为避免上述问题,当加热冷却盘管排数差别较大时,应分别设置.     

变风量空调系统风机总风量控制方法

通过对压力无关型变风量末端的分析得出了设定风量作为控制变量,进而提出了变风量系统总风量控制方法,使用空调系统模拟软件ＨＶＡＣＳＩＭ＋对其与定静压、变静压控制方法作了对比模拟研究,并在实际系统中进行了实验验证     

VAV系统中新风量的控制

介绍了变风量系统新风量控制中的风阀控制、送回风机控制、独立设置风机、混合段静压控制、ＣＯ２浓度控制和人数估计控制等方法,分析了各种方法的特点和应用范围。     

Fault detection and diagnosis based on improved PCA with JAA method in VAV systems

In this paper, improved principal component analysis (PCA) with joint angle analysis (JAA) is presented to detect and diagnose both fixed and drifting biases of sensors in variable air volume (VAV) systems. Fault characteristic concerned in PID controller in the VAV systems is analyzed and discussed. The squared prediction error (SPE) plot based on PCA is used to detect the sensor fixed and drifting biases. Then the JAA plot instead of conventional contribution plot is used to diagnose the faults. And they are tested and evaluated online in a simulated centralized VAV air-conditioning systems.     

Evaluation of faults impacts on energy consumption and indoor air quality on an air handling unit

The effects of faults on an air handling unit (AHU) are often poorly evaluated (assuming indoor air quality (IAQ) problems), and under-estimated in consumption balances. Based on an experimental site, this paper presents a quantitative study of some different faults that can appear on AHUs.     

一种余热驱动溶液调湿新风机组冬季运行研究

测试分析了一种余热驱动溶液调湿新风机组的冬季运行情况,得出了这种机组在冬季工况下的运行性能。在测试数据的基础上,分析了机组的送风参数随热水温度、热水流量和溶液浓度的变化情况。基于这些变化关系,得出了冬季工况下机组送风参数控制的基本原理和方法。     

VAV空调系统在中小建筑中的应用

1　工程概况上海市科技大楼的第 6层采用VAV空调系统 ,该层单独出租 ,包括接待前台、大小会议室、档案资料室、各类办公室及敞开式办公大空间。建筑面积 5 10m2 ,空调面积 4 10m2 ,建筑层高 3.3m ,空调冷负荷 6 0kW ,冷负荷指标 110W /m2 。该工程于 2 0 0 1年 1月进行方案论证、设计 ,3月开始安装施工 ,4月下旬竣工、调试 ,运行至今 ,效果良好。2　设计说明2 .1　冷热源选用空调主机为 1台高静压、风冷管道式热泵机组 ,制冷量6 0kW ,室外机有 2台压缩机 ,输入功率为 2 1.9kW ,可以分级启动 ,设置在屋顶 ;室内机为吊顶卧式暗装 ,输入功率…     

青岛广电大厦演播室空调机房的改造

为保证广播电台演播室的正常工作,对原有的空调机房进行了改造.在空调机房内设置风冷机组,并将风冷机组的蒸发器安装在原组合式空调机组内部,满足了电台演播室全年需要制冷的需求,并具备一定的节能效果.