Article
Construction & Building Technology
Dong Wei, Haodong Feng, Qi Han, Kun Jia
Summary: This study developed a system level to component scale FDD strategy for VAV systems using a hierarchical modeling framework and combined techniques to enhance accuracy and reliability. Additionally, a control quantity based residual statistics method was proposed in the unit layer to detect progressive failures in VAV systems, considering the non-obvious symptoms of these faults.
ENERGY AND BUILDINGS
(2022)
Article
Green & Sustainable Science & Technology
Tingting Li, Mengqiu Deng, Yang Zhao, Xuejun Zhang, Chaobo Zhang
Summary: A proactive AHU fault isolation method is proposed in this study to introduce dynamic disturbances and generate additional diagnostic information for isolating serious faults. Proactive fault isolation rules are developed based on the additional diagnostic information, which have been evaluated on a simulated air-conditioning system to effectively isolate the serious faults of AHUs.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Construction & Building Technology
Fanyong Cheng, Wenjian Cai, Xin Zhang, Huanyue Liao, Can Cui
Summary: This paper introduces a novel fault detection and diagnosis method using multiscale convolutional neural networks for Air Handling Unit in HVAC system. By utilizing three different scale kernels and an end-to-end learning strategy, the proposed method can effectively extract discriminative features to improve diagnostic performance. The comparison results show that the proposed MCNNs-based FDD method outperforms other commonly used methods.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Yulong Yu, Hanyuan Zhang, Wei Peng, Ruiqi Wang, Chengdong Li
Summary: This paper proposes an images based deep learning model for fault diagnosis of AHU. The method extracts and ranks features using kernel slow feature analysis, transforms them into two-dimensional grayscale images, and uses convolutional neural networks (CNNs) for fault diagnosis.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Chengdong Li, Yulong Yu, Linyuan Shang, Hanyuan Zhang, Yongqing Jiang
Summary: This paper proposes an AHU fault diagnosis model based on probabilistic slow feature analysis (PSFA) and attention residual network (AResNet) to improve the accuracy of fault diagnosis. The proposed model is built using the PSFA method and AResNet, and experiments are conducted on the experimental data with different noise levels. The results show that the proposed PSFA-AResNet model outperforms other popular methods in fault diagnosis performance under three different noise levels.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Construction & Building Technology
Bingjie Wu, Wenjian Cai, Haoran Chen, Xin Zhang
Summary: A novel simultaneous fault diagnosis model, CC-RF, is proposed and validated with on-site experiments, achieving high accuracy and performance in diagnosing both single and simultaneous faults. The model is proven to be scalable with reasonable training time and shows good competence in online analysis.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Hanyuan Zhang, Chengdong Li, Qinglai Wei, Yunchu Zhang
Summary: This paper introduces a novel SFA algorithm STBDSFA based on sparse feature representation to enhance the effectiveness of dynamic AHU system FDD. The algorithm shows high fault detection and diagnosis rates on experimental datasets.
ENERGY AND BUILDINGS
(2022)
Article
Construction & Building Technology
Hanyuan Zhang, Chengdong Li, Ding Li, Yunchu Zhang, Wei Peng
Summary: This paper presents an enhanced kernel slow feature analysis (SFA) based fault detection and diagnosis (FDD) scheme for nonlinear AHU systems, utilizing novel algorithms such as threeway data based kernel SFA (TBKSFA) and kernel discriminant SFA (KDSFA) to improve performance in capturing dynamic characteristics and identifying fault patterns. Experimental results show significant improvements compared to other popular methods.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Guofeng Ma, Haoran Ding
Summary: This study proposes a semi-supervised FDD method based on random forest, which has been verified in two practical applications. The results show that the proposed method can effectively utilize a large amount of unlabeled data, improve the generalization performance of the model, and improve the diagnostic accuracy of different column categories by about 10%. These results are helpful for the development of advanced data-driven fault detection and diagnosis tools for intelligent building systems.
Review
Energy & Fuels
Hyo-Jun Kim, Young-Hum Cho
Summary: The study reviewed types, control methods, prediction models, and sensor calibration methods of variable air volume (VAV) terminal units. Analysis of the existing research revealed the importance of control methods, mathematical models, and sensor calibration techniques in improving the efficiency of VAV systems.
Article
Construction & Building Technology
Zhiqiang Liu, Zhenlin Huang, Jiaqiang Wang, Chang Yue, Sungmin Yoon
Summary: This study introduced a novel fault detection, diagnosis, and self-calibration method based on Bayesian inference and virtual sensing to estimate various faults, including sensor and component faults. The method effectively recognized system operating state and identified fault positions, reducing deviation rate by up to 98.0% in most fault scenarios.
ENERGY AND BUILDINGS
(2021)
Article
Automation & Control Systems
Shunjian Ma, Yuanyuan Zou, Shaoyuan Li
Summary: This paper proposes a coordinated strategy of distributed model predictive control (DMPC) to regulate Variable Air Volume (VAV) boxes and Air Handling Unit (AHU) in a multi-zone HVAC system. By implementing equivalent local cooling cost and total-air-mass-rate penalty term, the operational cost of the HVAC system can be reduced with coordination from both DMPC and the upper layer.
JOURNAL OF PROCESS CONTROL
(2021)
Article
Construction & Building Technology
Bingjie Wu, Wenjian Cai, Fanyong Cheng, Haoran Chen
Summary: An advanced deep learning-based method using transformer architecture is proposed to diagnose simultaneous faults with time-series data. The method achieves accurate diagnosis in the early stage without a steady-state detector and has been validated with satisfactory performances on real-world data.
ENERGY AND BUILDINGS
(2022)
Article
Computer Science, Artificial Intelligence
Yanfeng Chai, Jiake Ge, Qiang Zhang, Yunpeng Chai, Xin Wang, Qingpeng Zhang
Summary: One configuration cannot meet all workloads and resource limitations in modern databases. We propose a correlation expert tuning system (CXTuning) that utilizes a correlation knowledge model and a multi-instance mechanism to achieve fine-grained tuning, reducing training time and achieving additional performance improvement.
Article
Construction & Building Technology
Panayiotis M. Papadopoulos, Georgios Lymperopoulos, Marios M. Polycarpou, Petros Ioannou
Summary: This paper proposes a distributed model based fault diagnosis algorithm for detecting and identifying faults in HVAC systems. The algorithm models the temperature dynamics of each local device and its neighboring zones and uses residual signals and adaptive thresholds to determine the presence of faults.
ENERGY AND BUILDINGS
(2022)
Article
Thermodynamics
Youming Chen, Yaling Xiao, Siqian Zheng, Yang Liu, Yupeng Li
Article
Green & Sustainable Science & Technology
Youming Chen, Bingbing Pan, Xunshui Zhang, Ciyuan Du
Article
Energy & Fuels
Yang Liu, Youming Chen
Article
Energy & Fuels
Zhixiong Ding, Wei Wu, Youming Chen, Michael Leung
Article
Energy & Fuels
Zhixiong Ding, Wei Wu, Youming Chen, Yantong Li
Article
Construction & Building Technology
Haitao Wang, Daoguang Feng, Kai Liu
Summary: This paper proposes a FDD method for detecting and diagnosing multiple faults of VAV terminals using a hybrid method, an adaptive zone air-temperature model, and a two-layered random forest method. The validation results show that the method can accurately detect and diagnose simultaneous multiple faults.
BUILDING AND ENVIRONMENT
(2021)
Article
Construction & Building Technology
Baisong Ning, Youming Chen, Hongyuan Jia
Summary: This study explored the dynamic thermal performance of pipe-embedded radiant systems and developed a response factor method to calculate their performance, which showed good accuracy and simplicity. It can be used for dynamic simulation and cooling load calculation of pipe-embedded radiant systems.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Zhengcheng Fang, Youming Chen
Summary: There is a correlation between the generation of coincident design weather data (CDWD) and building parameters as well as indoor cooling load. The periodic response factor method proves to be more applicable for generating CDWD and practical engineering applications compared to the transfer function method.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Zhengcheng Fang, Youming Chen, Zhengtao Ai, Hongqiang Li
Summary: Accurate design cooling load can improve the investment economics, operating energy efficiency and reliability of building air-conditioning systems. The comprehensive clustering method proposed in this study provides a more rational approach to determine the coincident design day (CDD) and shows that the CDDs are not extreme as the conventional design weather data.
BUILDING AND ENVIRONMENT
(2022)
Article
Energy & Fuels
Haitao Wang, Huanhuan Gao
Summary: This paper investigates the impacts of metro train blockages on critical velocity in sloping subway tunnel fires. A global model is presented to predict the critical velocity in the blocked zone, taking into account the blockage ratio and tunnel slope. The results show that the reduction in critical velocity is less than the blockage ratio and the aerodynamic shadow zone downstream of the blockage significantly affects the critical velocity.
Article
Green & Sustainable Science & Technology
Haitao Wang, Yuge Huang, Chengzhou Guo, Liu Yang, Lu Huang
Summary: The building industry is important for economic and social development but contributes significantly to carbon emissions. However, there is currently no mature design theory for low-carbon buildings. This paper presents a low-carbon optimization design method for roof insulation using a carbon emissions assessment method, comprehensive economic analysis model, and evaluation index. The method includes an extended economic analysis model to consider insulation carbon emissions, a new comprehensive economic analysis model to evaluate economic performances, and a balanced index to assess carbon reduction. The results validate that carbon emission cost improves economic performances and that insulation's economic benefits increase with the service life. The proposed method can be a convenient tool for low-carbon roof insulation design in real buildings.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2023)
Article
Construction & Building Technology
Cong Li, Youming Chen
Summary: Natural ventilation is proposed as a potential measure to improve building energy performance. A multi-factor optimization method is introduced to maximize the utilization of natural ventilation. The method uses natural ventilation strategy as the air conditioning system operation strategy and applies support vector regression and particle swarm optimization to predict the energy consumption and find the optimal solution. A case study demonstrates the feasibility and effectiveness of the method.
ENERGY AND BUILDINGS
(2023)
Article
Construction & Building Technology
Haitao Wang, Yuge Huang, Liu Yang
Summary: This paper presents an integrated economic and environmental assessment-based optimization design method to find the best candidate insulation design scheme for building roofs. The method includes the determination of roof thermal insulation type and the optimum insulation thickness. The validation results show good agreement between the predicted and measured data.
Proceedings Paper
Construction & Building Technology
Baisong Ning, Youming Chen
10TH INTERNATIONAL SYMPOSIUM ON HEATING, VENTILATION AND AIR CONDITIONING, ISHVAC2017
(2017)
Proceedings Paper
Construction & Building Technology
Yang Liu, Youming Chen, Yupeng Li, Siqian Zheng
10TH INTERNATIONAL SYMPOSIUM ON HEATING, VENTILATION AND AIR CONDITIONING, ISHVAC2017
(2017)
Article
Construction & Building Technology
Samiran Khorat, Debashish Das, Rupali Khatun, Sk Mohammad Aziz, Prashant Anand, Ansar Khan, Mattheos Santamouris, Dev Niyogi
Summary: Cool roofs can effectively mitigate heatwave-induced excess heat and enhance thermal comfort in urban areas. Implementing cool roofs can significantly improve urban meteorology and thermal comfort, reducing energy flux and heat stress.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Qi Li, Jiayu Chen, Xiaowei Luo
Summary: This study focuses on the vertical wind conditions as a main external factor that limits the energy assessment of high-rise buildings in urban areas. Traditional tools for energy assessment of buildings use a universal vertical wind profile estimation, without taking into account the unique wind speed in each direction induced by the various shapes and configurations of buildings in cities. To address this limitation, the study developed an omnidirectional urban vertical wind speed estimation method using direction-dependent building morphologies and machine learning algorithms.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Xiaojun Luo, Lamine Mahdjoubi
Summary: This paper presents an integrated blockchain and machine learning-based energy management framework for multiple forms of energy allocation and transmission among multiple domestic buildings. Machine learning is used to predict energy generation and consumption patterns, and the proposed framework establishes optimal and automated energy allocation through peer-to-peer energy transactions. The approach contributes to the reduction of greenhouse gas emissions and enhances environmental sustainability.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Ying Yu, Yuanwei Xiao, Jinshuai Chou, Xingyu Wang, Liu Yang
Summary: This study proposes a dual-layer optimization design method to maximize the energy sharing potential, enhance collaborative benefits, and reduce the storage capacity of building clusters. Case studies show that the proposed design significantly improves the performance of building clusters, reduces energy storage capacity, and shortens the payback period.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Felix Langner, Weimin Wang, Moritz Frahm, Veit Hagenmeyer
Summary: This paper compares two main approaches to consider uncertainties in model predictive control (MPC) for buildings: robust and stochastic MPC. The results show that compared to a deterministic MPC, the robust MPC increases the electricity cost while providing complete temperature constraint satisfaction, while the stochastic MPC slightly increases the electricity cost but fulfills the thermal comfort requirements.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Somil Yadav, Caroline Hachem-Vermette
Summary: This study proposes a mathematical model to evaluate the performance of a Double Skin Facade (DSF) system and its impact on indoor conditions. The model considers various design parameters and analyzes their effects on the system's electrical output and room temperature.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Ruijun Chen, Holly Samuelson, Yukai Zou, Xianghan Zheng, Yifan Cao
Summary: This research introduces an innovative resilient design framework that optimizes building performance by considering a holistic life cycle perspective and accounting for climate projection uncertainties. The study finds that future climate scenarios significantly impact building life cycle performance, with wall U-value, windows U-value, and wall density being major factors. By using ensemble learning and optimization algorithms, predictions for carbon emissions, cost, and indoor discomfort hours can be made, and the best resilient design scheme can be selected. Applying this framework leads to significant improvements in building life cycle performance.
ENERGY AND BUILDINGS
(2024)