Online Fault Detection Configuration on Equipment Side of a Variable-Air-Volume Air Handling Unit

With the development of the technology of the Internet of Things,more and more operational data can be collected from air conditioning systems.Unfortunately,the most of existing air conditioning controllers mainly provide controlling functions more than storing,processing or computing the measured data.This study develops an online fault detection configuration on the equipment side of air conditioning systems to realize these functions.Modbus communication is served to collect real-time operational data.The calculating programs are embedded to identify whether the measured signals exceed their limits or not,and to detect if sensor reading is frozen and other faults in relation to the operational performance are generated or not.The online fault detection configuration is tested on an actual variable-air-volume(VAV)air handling unit(AHU).The results show that the time ratio of fault detection exceeds 95.00%,which means that the configuration exhibits an acceptable fault detection effect.

Novel Approach for Fault Detection and Diagnosis of Sensors in Air Handling Units Using Wavelet Energy Entropy

A novel fault diagnosis method for sensors in air handling unit（AHU） using wavelet energy entropy was presented. Instead of directly comparing the numerous data under noise conditiom, the wavelet energy entropy residual was compared in the proposed method. Three.level wavelet analysis was used to decompose the measurement data under both fault-free and faulty operation conditions. The concept of Shannon entropy was referred to define wavelet energy entropy of the wavelet coefficients. The sensor faults were diagnosed by comparing the deviation of the wavelet energy entropy of the measured signal and the estimated one with the preset threshold. Testing results showed that the wavelet energy entropy was sensitive to diagnose the biased faults. The wavelet energy entropy residuals exceed the threshold significantly when faults occur. In addition, the severer the faults were, the larger the residuals would be. The results prove that the proposed method is feasible and effective for the fault detection and diagnosis of the sensors.

Fault isolation of air handling unit based on neural network

Aiming at various faults in an air conditioning system,the fault characteristics are analyzed.The influence of the faults on the energy consumption and thermal comfort of the system are also discussed.The simulation results show that the measurement faults of the supply air temperature can lead to the increase in energy consumption.According to the fault characteristics,a data-driven method based on a neural network is presented to detect and diagnose the faults of air handling units.First,the historical data are selected to train the neural network so that it can recognize and predict the operation of the system.Then,the faults can be diagnosed by calculating the relative errors denoting the difference between the measuring values and the prediction outputs.Finally,the fault diagnosis strategy using the neural network is validated by using a simulator based on the TRNSYS platform.The results show that the neural network can diagnose different faults of the temperature,the flow rate and the pressure sensors in the air conditioning system.

Analysis of Fresh Air Volume of Air-conditioning System for Railway Vehicles

The relevant standard requirements both in domestic and abroad provide the basis for designing air-conditioning system of railway vehicles present. However, there are great differences in the fresh air volume indicators among different standards requirements, and the requirements of each vehicle procurement contracts are also different. The design of air-conditioning become difficult above these. In this paper, the fresh air volume of different type railway vehicles is analyzed from health and equipment electricity consumption according to the railway vehicles air-conditioning system standard requirements in domestic and abroad. Some advises for designing air-conditioning system of railway vehicles through the fresh air volume calculation and comparison for domestic air-conditioning system of railway vehicles was provided.

Experimental Study of Air Conditioning Unit of Evaporative Cooling Assisted Mechanical Refrigeration

The evaporative cooling,which assists the refrigeration machinery air-conditioning systems test-rig,has been designed.Its structure and working principle were described,and the performance test was conducted and analyzed.The test shows that making full use of the evaporative cooling "free cooling" in Spring and Autumn seasons can fully meet the requirements of air-conditioned comfort through the switch of the function in different seasons.Taking into account the evaporative cooling fan and pump energy consumption,compared with the traditional mechanical refrigeration system,more than 80 percent of energy can be saved,and the energy efficiency ratio of the Unit(EER)is as high as 7.63.Using the two stages of indirect evaporative cooling to pre-cool the new wind in summer,under the conditions of the same air supply temperature requirements,0.83 kg/s chilled water saved can be equivalent to the traditional mechanical refrigeration system,and when the new wind ratio up to 50 percent,more than 10 percent load was reduced in mechanical refrigeration system.The overall EER increased about 35 percent.

Effects of various information scenarios on layer-wise relevance propagation-based interpretable convolutional neural networks for air handling unit fault diagnosis

Deep learning(DL),especially convolutional neural networks(CNNs),has been widely applied in air handling unit(AHU)fault diagnosis(FD).However,its application faces two major challenges.Firstly,the accessibility of operational state variables for AHU systems is limited in practical,and the effectiveness and applicability of existing DL methods for diagnosis require further validation.Secondly,the interpretability performance of DL models under various information scenarios needs further exploration.To address these challenges,this study utilized publicly available ASHRAE RP-1312 AHU fault data and employed CNNs to construct three FD models under three various information scenarios.Furthermore,the layer-wise relevance propagation(LRP)method was used to interpret and explain the effects of these three various information scenarios on the CNN models.An R-threshold was proposed to systematically differentiate diagnostic criteria,which further elucidates the intrinsic reasons behind correct and incorrect decisions made by the models.The results showed that the CNN-based diagnostic models demonstrated good applicability under the three various information scenarios,with an average diagnostic accuracy of 98.55%.The LRP method provided good interpretation and explanation for understanding the decision mechanism of CNN models for the unlimited information scenarios.For the very limited information scenario,since the variables are restricted,although LRP can reveal key variables in the model’s decision-making process,these key variables have certain limitations in terms of data and physical explanations for further improving the model’s interpretation.Finally,an in-depth analysis of model parameters—such as the number of convolutional layers,learning rate,βparameters,and training set size—was conducted to examine their impact on the interpretative results.This study contributes to clarifying the effects of various information scenarios on the diagnostic performance and interpretability of LRP-based CNN models for AHU FD,which helps provide improved reliability of DL models in practical applications.

Impact of Varying Blower Opening Degrees on Indoor Environment and Thermal Comfort

At present,air handling units are usually used indoors to improve the indoor environment quality.However,while introducing fresh air to improve air quality,air velocity has a certain impact on the occupants’thermal comfort.Therefore,it is necessary to explore the optimization of air-fluid-body interaction dynamics.In this study,the indoor air flow was changed by changing the opening and closing degree of the blower,and the thermal manikin is introduced to objectively evaluate the human thermal comfort under different air velocities.The main experimental results show that the air change rate increases with the increase of the opening and closing degree of the blower considering an ACH(air changes per hour)range between 3.8 and 10.For a better prediction,a linear correlation with a coefficient of 0.995 is proposed.As the blower’s opening is adjusted to 20%,25%,30%,35%,and 40%,the air velocity sensor positioned directly beneath the air inlet records average velocities of 0.19,0.20,0.21,0.28,and 0.34 m/s over four hours,respectively.Observations on thermal comfort and the average sensation experienced by individuals indicate an initial increase followed by a decline when the blower’s operation begins,with optimal conditions achieved at a 35%opening.These findings offer valuable insights for future indoor air ventilation and heat transfer design strategies.

Feasibility of condensate water recycle of split air handling unit in Chinese University buildings

Recycling the condensate water of the air conditioner could be explored as an alternative water source to con-tribute to building the green campus.This paper explored the condensate water production through actual mea-surement based on a split air handling unit(SAHU)in a university building.Then,the statistical analysis was used to analyze the recycling feasibility and the impact factors of the condensate water production in 31 Chinese provincial capital cities to obtain the recycling potential map of the condensate water generated from a SAHU.Results showed that:(1)In the measurement,the amount of condensate water produced by a single split air conditioner was 1.6 kg from 12:40 to 13:40.Therefore,the daily output of condensate water of the air condi-tioner with the university operation schedule could reach 52.99 kg during the main air-conditioning season.(2)Among the 31 provincial capital cities in China,the largest condensate water outputs could be found in the Hot Summer and Warm Winter zone and the Hot Summer and Cold Winter zone,with an average monthly output of 1600 kg and 1100 kg,respectively.(3)Regression analysis showed that the dry-bulb temperature and dew point temperature of outdoor air had the highest positive and significant influence on condensate water production.The objective of this study is to provide theoretical guidance for the design and energy conservation evaluation of the feasibility of SAHU condensate water recycling in universities.

Indoor Surveillance of Airborne Fungi Contaminating Intensive Care Units and Operation Rooms in Assiut University Hospitals, Egypt

Mycoflora of atmospheric air and dust samples collected from air conditioning systems in 12 of each I.C.U. （intensive care units） and O.R. （operation rooms） were tested using settle and dilution plate methods on four types of agar media and incubated at 25℃. Forty-five fungal species representing 23 genera were isolated and identified. The most prevalent genera recorded were Cladosporium, Aspergillus, Penicillium and Fusarium. The total colony forming units of airborne fungi recovered in I.C.U. and O.R. ranged between 31.13-49.61 colonies/m3 on the four types of media usedl The fungal total catch of the dust samples collected from the air conditioning system filters in I.C.U. and O.R. were ranged from 65.5-170 colonies/mg dust. Since, the interest to replace synthetic xenobiotics by natural compounds with low environmental persistence and biodegradable to control such airborne fungal contaminants is needed. In this respect, essential oils showed to possess a broad spectrum of antifungal activity. Fungal static ability of six oils was tested on 30 different fungal isolates. Vapors of common thyme oil exhibited the strongest inhibitory effects on the tested isolates, whereas the headspace vapors of blue gum and ginger had no inhibitory effects on the tested fungal isolates. These data revealed that the air conditioning systems may be an important source of contamination in I.C.U. and O.R. of Assiut university hospitals. Thus, patients may be in risk of being exposed to contaminated atmospheric air by opportunistic fungi and the use of essential oils as an alternative option to control hospital wards from fungal contaminants needs further studies.

Tracking controller design for air handling units with uncertainties

As an important component of the heating,ventilating and air conditioning(HVAC)systems,air handling units(AHUs)are responsible for regulating indoor temperature and humidity.In this paper,a multivariable nonlinear dynamic model of the AHUs with unknown strength of the humidity source is considered,and an improved backstepping controller is proposed to realize the tracking objective of the indoor temperature,relative humidity and carbon dioxide concentration.Firstly,the original system is represented in simplified state space form,and then the state transformation is introduced with a gain to overcome the difficulty caused by the unknown strength of the humidity source.Then,the improved backstepping controller is designed in a step-by-step way.Moreover,the stability of the closed-loop system is analyzed in detail.Finally,we consider the case that the AHUs work in summer of Jinan,China,as an example.The simulation results show the effectiveness of the controller.Meanwhile,the performance of the improved backstepping controller are compared with that of the decoupled sliding mode and PID controllers.

贫数据中基于模型自训练的空气处理设备故障诊断

针对空气处理设备(AHU)故障贫数据,基于深度置信网络(DBN)模型对4种特征选择算法进行对比研究,结果表明最大相关最小冗余算法的特征子集在诊断准确率及子集元素稳定性上表现最优。提出将DBN嵌入自训练框架的故障诊断模型,发现DBN自训练的诊断准确率较单纯DBN最高可提升19.5%。提出均匀抽样及按比例抽样2种自训练伪标签抽样策略,二者的诊断准确率均随抽样数减小而增大,在不同抽样数中的最大差异为3.42%;在所有贫数据样本中,均匀抽样策略始终优于按比例抽样,诊断准确率最大相差1.39%,表明在故障标签匮乏时,采用均匀抽样策略及较小的抽样数有利于提升DBN自训练的诊断性能。

基于反步法的空气处理机组温湿度跟踪控制

针对空气处理机组室内湿负荷和进回水温差不确定的情况,提出一种带有多参数的反步控制器,可以实现温度和湿度的跟踪控制。为了设计方便,先将空气处理机组的动态模型转换为状态空间表达形式,通过引入带增益的状态变换,将原系统的跟踪控制问题转换为变换后所得新系统的稳定控制问题;利用反步法逐步设计了控制器,并通过选择合适的设计参数,实现了温度和湿度的跟踪控制目标;分析了闭环系统的稳定性并给出了证明过程。结果表明:仿真实验验证了所研控制器的有效性,通过与PID控制器对比可知,所设计控制器的跟踪效果更好。

Strategy of constructing virtual peaking unit by public buildings’central air conditioning loads for day-ahead power dispatching

With the gradually widely usage of the air conditioning(AC) loads in developing countries, the urban power grid load has swiftly increased over the past decade.Especially in China, the AC load has accounted for over30% of the maximum load in many cities during summer.This paper proposes a scheme of constructing a virtual peaking unit(VPU) by public buildings’ cool storage central AC(CSCAC) systems and non-CSCAC(NCSCAC)systems for the day-ahead power network dispatching(DAPND). Considering the accumulation effect of different meteorological parameters, a short term load forecasting method of public building’s central AC(CAC) baseline load is firstly discussed. Then, a second-order equivalent thermal parameters model is established for the public building’s CAC load. Moreover, the novel load reduction control strategies for the public building’s CSCAC system and the public building’s NCSCAC system are respectively presented. Furthermore, based on the multiple-rank control strategy, the model of the DAPND with the participation of a VPU is set up. The VPU is composed of large-scale regulated public building’s CAC loads. To demonstrate the effectiveness of the proposed strategy, results of a sample study on a region in Nanjing which involves 22 public buildings’ CAC loads are described in this paper. Simulated results show that, by adopting the proposed DAPND scheme, the power network peak load in the region obviously decreases with a small enough deviation between the regulated load value and the dispatching instruction of the VPU. The total electricity-saving amount accounts for7.78% of total electricity consumption of the VPU before regulation.

一种核电厂重要厂用水泵房环境温湿度高处理方法

高温高湿气候时,东南沿海核电厂重要厂用水泵房频发温度高报警或设备凝露问题,影响泵电机运行安全,降低核电厂冷源安全可靠性。因此,在不改变当前通风方式情况下,提出在泵房进风风室增加一种新风混风制冷机组进行空气温湿度处理的方法。机组采用两路新风,将经制冷除湿后的新风与外界新风混合。通过计算确定进风参数。该方法无需冷却所有新风,无需再热段,通过混风升温降低相对湿度,可以彻底解决所有工况下泵房环境温度、湿度超标问题,且兼顾经济性。

前置暖风器电站锅炉烟气余热回收系统多参数设计与变工况运行策略

针对前置暖风器烟气余热回收系统,建立了多参数设计优化与变工况特性计算模型,开展了系统的多参数优化,并提出了运行参数控制策略。结果表明:多参数优化后系统在设计工况下的节煤率为3.67 g/(kW·h);多参数优化后的系统在变工况下虽能保持较高的节煤率,但系统的安全性受到环境温度和负荷的严重制约;采用所提出的控制策略可使系统在100%额定负荷下,安全运行的环境温度下限从24℃扩展至-3℃,显著提高了系统优化的综合效果。

融霜工况影响下空气源热泵机组频率控制系统

空气源热泵机组在融霜工况下,由于外部环境温度低,机组内部的水箱和管路可能会结霜,导致传热效率下降、能耗增加,使得频率控制不精准。为此,设计融霜工况影响下空气源热泵机组频率控制系统。设计PLC频率控制结构、频率控制中央处理器与PID控制阀门,联合控制热源侧水泵变频。计算机组结霜量,获取换热器的有效集热量。基于分段调节思想,利用计算机调整侧水泵出水量和调节参数,计算融霜启动调频速度。由实验结果可知,所设计系统在不同融霜工况下控制效果与实际最为接近,控制结果误差最大仅为0.1 Hz,能够实现精准控制频率。

模块化光伏空调机组研发及性能实测分析

针对岛礁等孤立区域远离内陆、设备系统维修不便、安全可靠性要求高的问题,本文设计出直流型、交流型蓄电模块化新型光伏空调机组,对蓄电、逆变、制冷等机组部件进行了集成设计,对集成热堆积造成的机组性能衰减进行了理论分析。搭建了性能实验平台,实测了晴天、多云和雨天等不同天气工况下模块化空调机组的运行性能,得到2类机组的COP范围为2.80~3.35。模块化光伏空调机组可满足太阳能丰富的孤立区域的空调需求,具有更换灵活方便的特点。

空调新风系统需求响应潜力评估及影响因素研究

需求响应是保障电力供需平衡的重要措施,空调是重要的需求响应资源。空调新风负荷能耗占比高,但是基于室内二氧化碳浓度的新风负荷参与电力系统需求响应的潜力尚不清晰。该文以办公建筑新风系统为例,分别以单位小时能耗最低和全天电费最低为目标,提出了新风系统短期响应和全天响应策略,并建立了相应的响应潜力评估方法。研究结果表明:室内二氧化碳浓度惯性小,新风系统调节速度快,是优良的短期响应资源,单位小时能耗可削减20%~100%,人员密度越低,响应潜力越大,夏季尖峰电价时段平均可削减34%的新风负荷。以峰谷分时电价为响应信号,全天总运行费用可节省14%。在此基础上,进一步探究了室内二氧化碳浓度上限、人员密度、换气次数和气候区对新风负荷响应潜力的影响规律。新风柔性为建筑参与电网响应提出了新的解决方案,对于改善电力供需矛盾有较高的应用价值。

大型机场航站楼中旅客登机桥及桥载设备的电气设计探讨

大型机场由于登机桥数量众多、类型各异、搭载的用电设备种类繁多,对登机桥及桥载设备的电气设计提出了更高要求。本文以西部某大型航站楼为例,介绍登机桥的不同分类和桥载设备的基本用电要求等,深入探讨了大型机场航站楼旅客登机桥的电气设计规范与要求,以期为相关领域的设计与实践提供有益参考。

多联机空调系统夏季工况设计流程探讨

根据《实用供热空调设计手册》的设计流程,结合《多联机空调系统设计应用技术规程》的设计要求,研究分析了多联机空调系统在夏季工况时负荷处理、新风形式的特点,指出室内机选型时须进行显热量校核、潜热量校核、气流组织校核的必要性,并对文献中的设计流程提出修改建议。