Article
Engineering, Industrial
Shiwang Hou, Keming Yu
Summary: This study introduces a new non-parametric cumulative sum (CUSUM) control chart method to monitor arbitrary distribution changes and diagnose detailed change types simultaneously, which outperforms other methods in detecting small changes.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Leo C. E. Huberts, Rob Goedhart, Ronald J. M. M. Does
Summary: This article explores the importance of parameter estimation in Statistical Process Monitoring and proposes a cautious updating scheme to improve the performance of control charts. A case study using data from a truck manufacturer demonstrates the effectiveness of these updating rules.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Thermodynamics
Shuanghua Cao, Weichao Zhao, Anxiong Zhu
Summary: In recent years, the research on the control method of variable air volume (VAV) has focused on addressing the overshoot issue of single terminal PID control in air-conditioning systems. This study proposes a control method that combines intervention control and PID control. LabVIEW simulation and experiments were conducted to analyze the performance of terminal intervention PID control. The results show that the control strategy using the intervention recognition algorithm nested with the PID algorithm performs well in terms of dynamic performance, robustness, and adaptability.
CASE STUDIES IN THERMAL ENGINEERING
(2023)
Article
Multidisciplinary Sciences
Muhammad Arslan, Syed Masroor Anwar, Showkat Ahmad Lone, Zahid Rasheed, Majid Khan, Saddam Akbar Abbasi
Summary: The AEWMA control charts are an advanced form of classical memory control charts used for efficiently monitoring shifts in process parameters. This study presents a new AEWMA control chart that estimates location shifts using HEWMA statistic and adaptively updates the smoothing constant, improving the performance of the control chart.
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
Multidisciplinary Sciences
Olatunde Adebayo Adeoti, Kayode Samuel Adekeye
Summary: This study aims to model COVID-19 mortality in Nigeria using four non-normal distributions, and proposes a control chart to monitor the deaths based on the best-fit distribution. The results show that the proposed Gamma-CUSUM chart outperforms the standard normal-CUSUM chart by detecting a change in the number of deaths on day 68 and identifying the exact point of change.
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
Engineering, Aerospace
Yujiang Zhong, Youmin Zhang, Shuzhi Sam Ge, Xiao He
Summary: This article investigates the fault detection and diagnosis problem in multiagent systems with sensor faults and disturbances. A distributed proportional integral derivative formation control protocol is constructed for practical formation. A distributed FDD scheme, consisting of a fault detection module, a fault isolation module, and a fault estimation module, is designed within the formation control. The effectiveness of the proposed FDD scheme is demonstrated through simulation results.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2023)
Article
Automation & Control Systems
Liang Liu, Jianchang Liu, Honghai Wang, Shubin Tan, Yuanchao Liu, Miao Yu, Peng Xu
Summary: The detection of incipient faults in complex industrial processes is a challenging problem for traditional dynamic detection methods. This paper proposes a fault detection method based on the dynamic k-nearest neighbor model and Dual Control Chart (DKNN-DCC), which improves the detection performance of incipient faults by using long-sequence dynamic detection. The effectiveness of the proposed method is demonstrated through experiments on the Tennessee Eastman (TE) process and the continuously stirred tank reactor (CSTR) process.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Kaixuan Shao, Yigang He, Xiaoyan Liu, Zhikai Xing, Bolun Du
Summary: The article proposes a novel indicator called FrEDE to cope with the challenges of fault detection in wind turbine systems. By utilizing the concepts of fractional calculus and dispersion entropy, and integrating information factor and entropy calculation, FrEDE is able to accurately detect the dynamic changes of complex systems and effectively differentiate between normal and faulty states.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Automation & Control Systems
Yinghong Zhao, Xiao He, Junfeng Zhang, Hongquan Ji, Donghua Zhou, Michael G. Pecht
Summary: The MA-type scheme, also known as the smoothing method, has been established within the MSPM framework since the 1990s. This paper introduces an optimally weighted moving average theory for detecting intermittent faults, improving on the existing MA method.
Article
Mathematics
Muhammad Riaz, Babar Zaman, Ishaq Adeyanju Raji, M. Hafidz Omar, Rashid Mehmood, Nasir Abbas
Summary: This study proposes two adaptive control charts to monitor shifts of different sizes in the process mean vector. By applying dimension reduction techniques and adaptive methods, the monitoring effectiveness of the shifts is improved. The performance of the proposed control charts is evaluated through Monte Carlo simulation and performance comparison measures, and is found to be superior to other control charts.
Article
Thermodynamics
Yuanpeng Mu, Jili Zhang, Zhixian Ma, Mingsheng Liu
Summary: This paper proposes a novel damper opening prediction algorithm and a flow rate control method based on demand air flow rate, which are both verified through case simulation. The prediction algorithm is based on a duct network impedance model, with a maximum prediction error of less than 1 degree. The flow rate control method does not require static pressure measurement and can reduce airflow fluctuation time by 55% and fan power consumption by 21.6% compared to the constant static pressure setting method.
Article
Engineering, Industrial
Steven E. Rigdon, Nathaniel T. Stevens, James D. Wilson, William H. Woodall
Summary: Control chart performance is often measured using average run length or median run length. However, these measures do not indicate which method is more likely to signal first. We introduce the idea of "first to signal" to compare different charts based on this criterion.
QUALITY ENGINEERING
(2023)
Article
Construction & Building Technology
Burak Gunay, Jayson Bursill, Brent Huchuk, Scott Shillinglaw
Summary: The implementation of sequences of operation for HVAC systems into a building automation system (BAS) is crucial for building performance. This paper introduces a new method of fault detection and diagnostics (FDD) using inverse models to detect programming logic faults in VAV AHU systems.
BUILDING AND ENVIRONMENT
(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)