Download or read book Fault Detection Diagnosis and Prognosis in HVAC Air Handling Systems written by Ying Yan and published by . This book was released on 2018 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: As key sub-systems of HVACs, air handling systems are used to condition air to satisfy human thermal comfort and air quality requirements. Fault diagnosis is critical since it allows system operators to know which faults have occurred, how critical they are, and improve the system availability. Additionally, fault prognosis is critical since it allows system operators to know Remaining Useful lives of systems and their components, and prevents unexpected breakdowns. However, fault diagnosis of known and new fault types and fault prognosis are complex since 1) fault propagation across components is hard to capture; 2) measurement noise cause many false alarms; 3) impacts of changing environments are hard to be captured in Hidden Markov Models (HMMs); 4) normal conditions or known fault types may be identified as new fault types falsely; 5) Hidden Semi-Markov Models (HSMMs) perform well in fault prognosis but are time-consuming; and 6) HSMMs capturing impacts of concurrent failure modes are hard to establish. In this thesis, to capture fault propagation in an efficient manner, a new coupled HMM is developed. To filter out false alarms, coupled statistical process control techniques are developed. To adapt to changing environments, a new online learning algorithm is developed. To identify new fault types with low false identification rates, a robust statistical method is developed. To estimate states of HSMMs with low computational effort, a statistical method is developed to focus on potential state transition points. To reflect accumulation of fault impacts, a statistical method is developed based on Monte-Carlo simulation.
Download or read book Fault Detection and Diagnosis of Air Handling Unit in HVAC System Using Cloud based Data Logging System written by David Lee and published by . This book was released on 2019 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Fault Detection and Diagnostics Modeling for Air handling Units on the Main Campus of The University of Texas at Austin written by Megan Kellie McHugh and published by . This book was released on 2018 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heating, ventilation, and air conditioning accounts for about 44% of energy usage in commercial buildings. In HVAC systems, air handling units are used to condition air based on comfort for occupants or controlled environmental requirements. Faults in AHUs can occur due to failures in equipment, actuators, or sensors and feedback controllers. Leakage typically occurs due to faults in ducts, faults with valves that are stuck, broken, or in the incorrect operating position, faults in measurements of state variables, or faults with the controllers maintaining the setpoint from sensor feedback. The variety faults that can occur in AHUs can lead to increased energy consumption, especially when it remains undetected. AHU faults can also lead to uncomfortable conditions for building occupants or impact research and other special facilities as the campus building types include classroom/academic, hospital/clinic, housing, office/administrative, parking/garage, public assembly/multipurpose, and research laboratories. The building automation systems on the main campus of The University of Texas at Austin manage over 100 buildings each with multiple AHUs in different working conditions. In this paper, a methodology is proposed for the fault detection of AHU steam and chilled water valve leakage and for general fault detection and diagnoses of other common AHU faults on the UT campus. The approach is based on supervised machine learning classification models and compared to the ASHRAE fundamentals expert rule-set models. BAS data trended at 15-minute intervals for periods up to 400 days were used. Faults detected through these methods have been validated by UT Facilities Services upon inspection of the faulty AHUs. A dashboard web application was developed for the interactive use and visualization of the fault detection models by UTFS for continuous maintenance prioritization. A classification analysis allows for the prediction of leakage and provides UTFS a priority ranking of AHUs to address for maintenance in the future. The rule-set models provide a method for continuous tracking of AHU features for faults. Identifying and addressing valve leakage and other faults is expected to reduce energy usage and contribute to reduction in average annual energy use intensity in order to improve demand side energy efficiency while maintaining indoor environmental quality. This will contribute to reach the 2020 energy savings targets set in the 2012 UT Austin Campus Master Plan, which outlines a variety of initiatives for sustainable growth through 2030
Download or read book Fault Detection Diagnosis and Prognosis written by Fausto Pedro García Márquez and published by BoD – Books on Demand. This book was released on 2020-02-05 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the main concepts, state of the art, advances, and case studies of fault detection, diagnosis, and prognosis. This topic is a critical variable in industry to reach and maintain competitiveness. Therefore, proper management of the corrective, predictive, and preventive politics in any industry is required. This book complements other subdisciplines such as economics, finance, marketing, decision and risk analysis, engineering, etc. The book presents real case studies in multiple disciplines. It considers the main topics using prognostic and subdiscipline techniques. It is essential to link these topics with the areas of finance, scheduling, resources, downtime, etc. to increase productivity, profitability, maintainability, reliability, safety, and availability, and reduce costs and downtime. Advances in mathematics, modeling, computational techniques, dynamic analysis, etc. are employed analytically. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support the analysis of prognostic problems with defined constraints and requirements. The book is intended for graduate students and professionals in industrial engineering, business administration, industrial organization, operations management, applied microeconomics, and the decisions sciences, either studying maintenance or needing to solve large, specific, and complex maintenance management problems as part of their jobs. The work will also be of interest to researches from academia.
Download or read book Online learning based Fault Detection and Diagnosis for HVAC Systems in Commercial Buildings written by Majid Karami and published by . This book was released on 2019 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heating, ventilation, and air conditioning (HVAC) systems account for a significant portion of the energy consumption in buildings. Faults in HVAC systems, such as equipment degradation, failure in sensors and controllers, if not detected at early stages, can raise the maintenance costs, occupant discomfort, and a significant amount of wasted energy, around 15% to 30% of the total energy consumed in the building. Such a significant energy impact introduced by various faults demonstrates substantial potential for energy saving in buildings by implementing automatic fault detection and diagnosis (AFDD) systems. Despite the extensive research on AFDD of HVAC systems, there is a lack of an AFDD method which is capable of handling the unexplored states in systems. The unexplored states may arise in HVAC systems as the data for training the AFDD algorithm of such complicated nonlinear systems is usually limited. Most of the conventional AFDD methods are only capable of diagnosing the faults for which the prior information is available during the training process, but cannot diagnose an unseen fault in systems. Other possibilities of unexplored states are a new operational mode in the system, change in the control setpoints, and change in the system components due to retrofit and maintenance. The challenge is how to evolve the AFDD algorithm to learn the information about the new faults or new dynamics in the HVAC systems. In this study, to address the problems above, the online-learning-based AFDD algorithm is developed which allows the adaptation of both the structure and the parameters of the AFDD algorithm when a new state in the system is recognized. The proposed AFDD algorithm relies upon an evolving Gaussian mixture modeling approach and has the ability to diagnose any of the already-known faults in the system, reveal an unknown state in the system, and learn the information of the new states. The performance evaluation of the proposed evolving AFDD algorithm is illustrated in detection and diagnosis of various faults in a chiller plant and a variable air volume (VAV) system as they are two common HVAC systems in commercial buildings. The AFDD algorithm is evaluated using both simulation studies and an experiment using an actual VAV system. The results demonstrate the effectiveness of the proposed AFDD algorithm in detecting and diagnosing common faults as well as unseen states in the HVAC systems.
Download or read book Fault Detection and Diagnosis on HVAC System Using Knowledge Based Expert System written by Yunfeng Xiao and published by . This book was released on 1997 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Automated Diagnostics and Analytics for Buildings written by Barney L. Capehart and published by CRC Press. This book was released on 2021-01-07 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the widespread availability of high-speed, high-capacity microprocessors and microcomputers with high-speed communication ability, and sophisticated energy analytics software, the technology to support deployment of automated diagnostics is now available, and the opportunity to apply automated fault detection and diagnostics to every system and piece of equipment in a facility, as well as for whole buildings, is imminent. The purpose of this book is to share information with a broad audience on the state of automated fault detection and diagnostics for buildings applications, the benefits of those applications, emerging diagnostic technology, examples of field deployments, the relationship to codes and standards, automated diagnostic tools presently available, guidance on how to use automated diagnostics, and related issues.
Download or read book Detection and Diagnosis of Faults and Energy Monitoring of Heating Ventilating and Air Conditioning Systems with Least intrusive Power Analysis written by Dong Luo and published by . This book was released on 2001 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Faults indicate degradation or sudden failure of equipment in a system. Widely existing in heating, ventilating, and air conditioning (HVAC) systems, faults always lead to inefficient energy consumption, undesirable indoor air conditions, and even damage to the mechanical components. Continuous monitoring of the system and analysis of faults and their major effects are therefore crucial to identifying the faults at the early stage and making decisions for repair. This requires the method of fault detection and diagnosis (FDD) not only to be sensitive and reliable but also to cause minimal interruption to the system's operation at low cost. However, based on additional sensors for the specific information of each component or black-box modeling, current work of fault detection and diagnosis introduces too much interruption to the system's normal operation associated with sensor installation at unacceptable cost or requires a long time of parameter training. To solve these problems, this thesis first defines and makes major innovations to a change detection algorithm, the generalized likelihood ratio (GLR), to extract useful information from the system's total power data. Then in order to improve the quality of detection and simplify the training of the power models, appropriate multi-rate sampling and filtering techniques are designed for the change detector. From the detected variations in the total power, the performance at the system's level is examined and general problems associated with unstable control and on/off cycling can be identified. With the information that are basic to common HVAC systems, power functions are established for the major components, which help to obtain more reliable detection and more accurate estimation of the systems' energy consumption. In addition, a method for the development of expert rules based on semantic analysis is set up for fault diagnosis . Power models at both system and component levels developed in this thesis have been successfully applied to tests in real buildings and provide a systematic way for FDD in HVAC systems at low cost and with minimal interruption to systems' operation.
Download or read book Classification Techniques for Fault Detection and Diagnosis of an Air Handling Unit written by J. M. House and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Backpropagation written by Yves Chauvin and published by Psychology Press. This book was released on 2013-02-01 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Composed of three sections, this book presents the most popular training algorithm for neural networks: backpropagation. The first section presents the theory and principles behind backpropagation as seen from different perspectives such as statistics, machine learning, and dynamical systems. The second presents a number of network architectures that may be designed to match the general concepts of Parallel Distributed Processing with backpropagation learning. Finally, the third section shows how these principles can be applied to a number of different fields related to the cognitive sciences, including control, speech recognition, robotics, image processing, and cognitive psychology. The volume is designed to provide both a solid theoretical foundation and a set of examples that show the versatility of the concepts. Useful to experts in the field, it should also be most helpful to students seeking to understand the basic principles of connectionist learning and to engineers wanting to add neural networks in general -- and backpropagation in particular -- to their set of problem-solving methods.
Download or read book Fault Detection and Diagnosis in Building HVAC Systems written by Massieh Najafi and published by . This book was released on 2010 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building HVAC systems account for more than 30% of annual energy consumption in United States. However, it has become apparent that only in a small percentage of buildings do HVAC systems work efficiently or in accordance with design intent. Studies have shown that operational faults are one of the main reasons for the inefficient performance of these systems. It is estimated that an energy saving of 5 to 15 percent is achievable simply by fixing faults and optimizing building control systems. In spite of good progress in recent years, methods to manage faults in building HVAC systems are still generally undeveloped; in particular, there is still a lack of reliable, affordable, and scalable solutions to manage faults in HVAC systems. Modeling limitations, measurement constraints, and the complexity of concurrent faults have made the diagnosis of these problems as much an art as a science. The challenge is how to evaluate system performance within the boundaries defined by such limitations. This thesis focuses on a number of issues that, in our opinion, are crucial to the development of reliable and scalable diagnostic solutions for building HVAC systems. Diagnostic complexity due to modeling and measurement constraints, the pro-activeness of diagnostic mechanisms, bottom-up versus top-down diagnostic perspectives, diagnosis-ability, and the correlation between measurement constraints and diagnostic capability will be discussed in detail. We will develop model-based and non-model-based diagnostic algorithms that have the capability of dealing with modeling and measurement constraints more effectively. We will show how the effect of measurement constraints can be traced to the information entropy of diagnostics assessments and how this can lead to a framework optimizing the architecture of sensor networks from the diagnostic perspective. In another part of this study, we focus on proactive diagnostics. In the past, the topic of proactive fault diagnostics has not been given enough attention, even though the capability of conducting and supervising automated proactive testing is essential in terms of being able to replace manual troubleshooting with automated solutions. We will show how a proactive testing problem can be formulated as a decision making problem coupled with a Bayesian network diagnostic model. The algorithms presented in this thesis have been implemented and tested in the Lawrence Berkeley National Laboratory (LBNL) using real and synthetic data.
Download or read book Applied Change of Mean Detection Techniques for HVAC Fault Detection and Diagnosis and Power Monitoring written by Roger Owen Hill and published by . This book was released on 1995 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: A signal processing technique, the detection of abrupt changes in a time-series signal, is implemented with two different applications related to energy use in buildings. The first application is a signal pre-processor for an advanced electric power monitor, the Nonintrusive Load Monitor (NILM), which is being developed by researchers at the Massachusetts Institute of Technology. A variant form of the generalized likelihood ratio (GLR) change-detection algorithm is determined to be appropriate for detecting power transients which are used by the NILM to uniquely identify the start-up of electric end-uses. An extension of the GLR change-detection technique is used with a second application, fault detection and diagnosis in building heating ventilation and air-conditioning (HVAC) systems. The method developed here analyzes the transient behavior of HVAC sensors to define conditions of correct operation of a computer simulated constant air volume HVAC sub-system. Simulated faults in a water-to-air heat exchanger (coil fouling and a leaky valve) are introduced into the computer model. GLR-based analysis of the transients of the faulted HVAC system is used to uniquely define the faulty state. The fault detection method's sensitivity to input parameters is explored and further avenues for research with this method are suggested.
Download or read book Fault Detection and Diagnosis in Industrial Systems written by L.H. Chiang and published by Springer Science & Business Media. This book was released on 2000-12-11 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Early and accurate fault detection and diagnosis for modern chemical plants can minimize downtime, increase the safety of plant operations, and reduce manufacturing costs. This book presents the theoretical background and practical techniques for data-driven process monitoring. It demonstrates the application of all the data-driven process monitoring techniques to the Tennessee Eastman plant simulator, and looks at the strengths and weaknesses of each approach in detail. A plant simulator and problems allow readers to apply process monitoring techniques.
Download or read book Sensor Fault Detection and Diagnosis of Air Handling Units written by Fu Xiao and published by . This book was released on 2004 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Model based Fault Detection and Diagnosis of an Air Handling Unit Using a Fuzzy Rule Classifier written by Moosung Kim and published by . This book was released on 2005 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems written by Hamid Reza Karimi and published by Academic Press. This book was released on 2021-06-05 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fault Diagnosis and Prognosis Techniques for Complex Engineering Systems gives a systematic description of the many facets of envisaging, designing, implementing, and experimentally exploring emerging trends in fault diagnosis and failure prognosis in mechanical, electrical, hydraulic and biomedical systems. The book is devoted to the development of mathematical methodologies for fault diagnosis and isolation, fault tolerant control, and failure prognosis problems of engineering systems. Sections present new techniques in reliability modeling, reliability analysis, reliability design, fault and failure detection, signal processing, and fault tolerant control of engineering systems. Sections focus on the development of mathematical methodologies for diagnosis and prognosis of faults or failures, providing a unified platform for understanding and applicability of advanced diagnosis and prognosis methodologies for improving reliability purposes in both theory and practice, such as vehicles, manufacturing systems, circuits, flights, biomedical systems. This book will be a valuable resource for different groups of readers – mechanical engineers working on vehicle systems, electrical engineers working on rotary machinery systems, control engineers working on fault detection systems, mathematicians and physician working on complex dynamics, and many more. - Presents recent advances of theory, technological aspects, and applications of advanced diagnosis and prognosis methodologies in engineering applications - Provides a series of the latest results, including fault detection, isolation, fault tolerant control, failure prognosis of components, and more - Gives numerical and simulation results in each chapter to reflect engineering practices
Download or read book Fault Detection and Diagnosis in Engineering Systems written by Janos Gertler and published by Routledge. This book was released on 2017-11-22 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring a model-based approach to fault detection and diagnosis in engineering systems, this book contains up-to-date, practical information on preventing product deterioration, performance degradation and major machinery damage.;College or university bookstores may order five or more copies at a special student price. Price is available upon request.
