Relevant bibliographies by topics / Fault diagnosis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Fault diagnosis'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Fault diagnosis"

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Boubaker, Sahbi, Souad Kamel, Nejib Ghazouani, and Adel Mellit. "Assessment of Machine and Deep Learning Approaches for Fault Diagnosis in Photovoltaic Systems Using Infrared Thermography." Remote Sensing 15, no. 6 (2023): 1686. http://dx.doi.org/10.3390/rs15061686.

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Nowadays, millions of photovoltaic (PV) plants are installed around the world. Given the widespread use of PV supply systems and in order to keep these PV plants safe and to avoid power losses, they should be carefully protected, and eventual faults should be detected, classified and isolated. In this paper, different machine learning (ML) and deep learning (DL) techniques were assessed for fault detection and diagnosis of PV modules. First, a dataset of infrared thermography images of normal and failure PV modules was collected. Second, two sub-datasets were built from the original one: The f
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Elmishali, Amir, Roni Stern, and Meir Kalech. "Data-Augmented Software Diagnosis." Proceedings of the AAAI Conference on Artificial Intelligence 30, no. 2 (2016): 4003–9. http://dx.doi.org/10.1609/aaai.v30i2.19076.

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Software fault prediction algorithms predict which software components is likely to contain faults using machine learning techniques. Software diagnosis algorithm identify the faulty software components that caused a failure using model-based or spectrum based approaches. We show how software fault prediction algorithms can be used to improve software diagnosis. The resulting data-augmented diagnosis algorithm overcomes key problems in software diagnosis algorithms: ranking diagnoses and distinguishing between diagnoses with high probability and low probability. We demonstrate the efficiency o
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Zhu, Liangyu, Shuilong He, Li Ouyang, Chaofan Hu, and Yanxue Wang. "Hierarchical Diagnosis Network Based on Easy Transfer Learning and Its Application in Bearing Fault Diagnosis." Journal of Physics: Conference Series 2184, no. 1 (2022): 012013. http://dx.doi.org/10.1088/1742-6596/2184/1/012013.

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Abstract Aiming at the problem of inconsistent distribution of rolling bearing vibration data under variable operating conditions, insufficient diagnostic data of the target bearing affects the accuracy of fault diagnosis, and the unknown severity of rolling bearing faults, a hierarchical diagnosis network based on easy transfer learning is presented in this paper and its application in the qualitative and quantitative diagnosis of rolling bearing faults. First, the wavelet transform is used to extract the fault features conducive to identifying the rolling bearing vibration data under various
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Tang, Jing, Guangkuo Guo, Ji Wang, and Wei Xu. "Fault injection and diagnosis of the centrifugal fan." Journal of Physics: Conference Series 2366, no. 1 (2022): 012023. http://dx.doi.org/10.1088/1742-6596/2366/1/012023.

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Abstract Centrifugal fan is widely used in industry, vehicle and ship application to provide air cycle power. To detect the fan fault at early stage, this paper explores the fault feature in the vibration signal and fault diagnosis method through the fault injection test, where impeller unbalance, rotor unbalance, and bearing fault are involved. Firstly, the fault mechanism is introduced; then, the fault injection methods of the three faults are introduced to obtain the faulty fans; finally, health and fault tests are performed, where the vibration sensors are employed and distributed on the f
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Sun, Yin Qiu, and Hai Lin Feng. "Intermittent Faults Diagnosis in Wireless Sensor Networks." Applied Mechanics and Materials 160 (March 2012): 318–22. http://dx.doi.org/10.4028/www.scientific.net/amm.160.318.

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Sensor node intermittent faults which sometimes behave as fault-free are common in wireless sensor networks. Intermittent faults also affect network performance and faults detection accuracy, so it is important to diagnose the intermittent faulty nodes accurately. This paper proposes a distributed clustering intermittent faults diagnosis method. First, the network is divided into several clusters with the cluster heads should be diagnosed as good. Then, the cluster members are diagnosed by their cluster head. In order to improve the validity of proposed diagnose method, a strategy which collec
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Chu, Kenny Sau Kang, Kuew Wai Chew, Yoong Choon Chang, and Stella Morris. "An Open-Circuit Fault Diagnosis System Based on Neural Networks in the Inverter of Three-Phase Permanent Magnet Synchronous Motor (PMSM)." World Electric Vehicle Journal 15, no. 2 (2024): 71. http://dx.doi.org/10.3390/wevj15020071.

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Three-phase motors find extensive applications in various industries. Open-circuit faults are a common occurrence in inverters, and the open-circuit fault diagnosis system plays a crucial role in identifying and addressing these faults to enhance the safety of motor operations. Nevertheless, the current open-circuit fault diagnosis system faces challenges in precisely detecting specific faulty switches. The proposed work presents a neural network-based open-circuit fault diagnosis system for identifying faulty power switches in inverter-driven motor systems. The system leverages trained phase-
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Sabna M. "A Single Detection And Diagnosis Algorithm For Electrical Faults in a Five-Phase.Permanent.Magnet Synchronous Motor Drive." Journal of Electrical Systems 20, no. 11s (2024): 3369–87. https://doi.org/10.52783/jes.8091.

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In all processing and manufacturing industries, approximately half of the operating cost is contributed to the maintenance process. Due to high reliability, and fault-tolerant capability, five-phase Permanent Magnet Synchronous Motors (5ϕ-PMSM) are commonly used in high-power and fault-tolerant applications. Early-stage detection and diagnosis of faults can reduce maintenance costs. This paper proposes a single algorithm for detecting and diagnosing electrical faults such as inter-turn short circuit faults, phase-to-phase faults, phase-to-ground to ground faults, and open circuit faults in a 5
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Benyettou, L., T. Benslimane, O. Abdelkhalek, T. Abdelkrim, and K. Bentata. "Faults Diagnosis in Five-Level Three-Phase Shunt Active Power Filter." International Journal of Power Electronics and Drive Systems (IJPEDS) 6, no. 3 (2015): 576. http://dx.doi.org/10.11591/ijpeds.v6.i3.pp576-585.

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In this paper, characteristics of open transistor faults in cascaded H-bridge five-level three-phase PWM controlled shunt active power filter are determined. Phase currents can’t be trusted as fault indicator since their waveforms are slightly changed in the presence of open transistor fault. The proposed method uses H bridges output voltages to determine the faulty phase, the faulty bridge and more precisely, the open fault transistor.
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Asokan, A., and D. Sivakumar. "Model based fault detection and diagnosis using structured residual approach in a multi-input multi-output system." Serbian Journal of Electrical Engineering 4, no. 2 (2007): 133–45. http://dx.doi.org/10.2298/sjee0702133a.

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Fault detection and isolation (FDI) is a task to deduce from observed variable of the system if any component is faulty, to locate the faulty components and also to estimate the fault magnitude present in the system. This paper provides a systematic method of fault diagnosis to detect leak in the three-tank process. The proposed scheme makes use of structured residual approach for detection, isolation and estimation of faults acting on the process [1]. This technique includes residual generation and residual evaluation. A literature review showed that the conventional fault diagnosis methods l
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Sun, Yong Kui, and Zhi Bin Yu. "Analog Circuits Fault Diagnosis Using Multifractal Analysis." Advanced Materials Research 721 (July 2013): 367–71. http://dx.doi.org/10.4028/www.scientific.net/amr.721.367.

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Analog circuits fault diagnosis using multifractal analysis is presented in this paper. The faulty response of circuit under test is analyzed by multifratal formalism, and the fault feature consists of multifractal spectrum parameters. Support vector machine is used to identify the faults. Experimental results prove the proposed method is effective and the diagnosis accuracy reaches 98%.
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Dissertations / Theses on the topic "Fault diagnosis"

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Fan, Xiaoxin. "Fault diagnosis of VLSI designs: cell internal faults and volume diagnosis throughput." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/3450.

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The modern VLSI circuit designs manufactured with advanced technology nodes of 65nm or below exhibit an increasing sensitivity to the variations of manufacturing process. New design-specific and feature-sensitive failure mechanisms are on the rise. Systematic yield issues can be severe due to the complex variability involved in process and layout features. Without improved yield analysis methods, time-to-market is delayed, mature yield is suboptimal, and product quality may suffer, thereby undermining the profitability of the semiconductor company. Diagnosis-driven yield improvement is a metho
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Hurdle, Emma Eileen. "System fault diagnosis using fault tree analysis." Thesis, Loughborough University, 2008. https://dspace.lboro.ac.uk/2134/34678.

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Fault tree analysis is a method that describes all possible causes of a specified system state in terms of the state of the components within the system. Fault trees are commonly developed to analyse the adequacy of systems, from a reliability or safety point of view during the stages of design. The aim of the research presented in this thesis was to develop a method for diagnosing faults in systems using a model-based fault tree analysis approach, taking into consideration the potential for use on aircraft systems. Initial investigations have been conducted by developing four schemes that use
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Pavlidis, Antonios. "Analog Hardware Fault Diagnosis." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS452.

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Le nombre de circuits intégrés (CIs) utilisés dans les applications liées à des missions critiques et à la sûreté augmente sans cesse. Ces applications imposent aux CIs de présenter des propriétés de sûreté fonctionnelle. Cette thèse introduit un auto-test intégré (BIST) pour les CIs analogiques et à signaux mixtes, appelé autotest à symétrie (SymBIST) pour répondre à l’objectif de sûreté fonctionnelle. SymBIST repose sur le principe du BIST et sur l'existence de signaux invariants en fonctionnement nominal et variant en cas de fonctionnement erroné. Les invariants sont mesurés à l'aide de dis
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Frisk, Erik. "Residual generation for fault diagnosis." Doctoral thesis, Linköping : Univ, 2001. http://www.bibl.liu.se/liupubl/disp/disp2001/tek716s.pdf.

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Edwards, S. "Fault diagnosis of rotating machinery." Thesis, Swansea University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.636771.

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In this thesis, topics of importance to the fault diagnosis of rotating machinery in the power generation industry have been addressed, including a review of the relevant literature and an overview of the associated rotordynamics modelling and analysis techniques. For faults involving rotor-stator interaction it has been shown that the inclusion of torsion in mathematical models used for rotor-stator contract analyses can have a significant influence on the dynamic behaviour of the system. A 3 degrees-of-freedom model based on the Jeffcott rotor was developed and, for physically realistic syst
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Adam, Johan D. "Failure diagnostic expert systems : a case study in fault diagnosis /." Master's thesis, This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-01202010-020148/.

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ZHANG, XIAODONG. "FAULT DIAGNOSIS AND FAULT-TOLERANT CONTROL IN NONLINEAR SYSTEMS." University of Cincinnati / OhioLINK, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1021937028.

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Avram, Remus C. "Fault Diagnosis and Fault-Tolerant Control of Quadrotor UAVs." Wright State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=wright1464343320.

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Pernestål, Anna. "Probabilistic Fault Diagnosis with Automotive Applications." Doctoral thesis, Linköpings universitet, Fordonssystem, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-51931.

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The aim of this thesis is to contribute to improved diagnosis of automotive vehicles. The work is driven by case studies, where problems and challenges are identified. To solve these problems, theoretically sound and general methods are developed. The methods are then applied to the real world systems. To fulfill performance requirements automotive vehicles are becoming increasingly complex products. This makes them more difficult to diagnose. At the same time, the requirements on the diagnosis itself are steadily increasing. Environmental legislation requires that smaller deviations from spec
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Brunson, Christopher M. "Matrix converter fault detection and diagnosis." Thesis, University of Nottingham, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.718994.

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With the increased use of power electronics in aerospace, automotive, industrial, and energy generation sectors, the demand for highly reliable and power dense solutions has increased. Taking into account the demands for high reliability and high power density, matrix converters become attractive. With their lack of large bulky DC- Link capacitors, high power densities are possible with capability to operate with high ambient temperatures [7]. Demand for high reliability under tight weight and volume constrains, often it is not possible to have an entirely redundant system. Under these conditi
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Books on the topic "Fault diagnosis"

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Korbicz, Józef, Zdzisław Kowalczuk, Jan M. Kościelny, and Wojciech Cholewa, eds. Fault Diagnosis. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18615-8.

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Autodata, ed. Fault diagnosis. Autodata, 1993.

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Chen, Tinghuai. Fault Diagnosis and Fault Tolerance. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77179-8.

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Isermann, Rolf. Fault-Diagnosis Applications. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-12767-0.

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Isermann, Rolf. Fault-Diagnosis Systems. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-30368-5.

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Fong, Rebecca Pui Shan. Probabilistic fault diagnosis. National Library of Canada, 2003.

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Loveday, George. Electronic fault diagnosis. 2nd ed. Longman Scientific & Technical, 1986.

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Denton, Tom. Advanced Automotive Fault Diagnosis. Routledge, 2020. http://dx.doi.org/10.1201/9780429317781.

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Varga, Andreas. Solving Fault Diagnosis Problems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51559-5.

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Karmakar, Subrata, Surajit Chattopadhyay, Madhuchhanda Mitra, and Samarjit Sengupta. Induction Motor Fault Diagnosis. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0624-1.

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Book chapters on the topic "Fault diagnosis"

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Chen, Tinghuai. "Computer System Diagnosis and Society Diagnosis." In Fault Diagnosis and Fault Tolerance. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77179-8_2.

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Cholewa, Wojciech, and Jan Maciej Kościelny. "Introduction." In Fault Diagnosis. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18615-8_1.

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Janczak, Andrzej. "Parametric and Neural Network Wiener and Hammerstein Models in Fault Detection and Isolation." In Fault Diagnosis. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18615-8_10.

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Kościelny, Jan Maciej, and Michał Syfert. "Application of Fuzzy Logic to Diagnostics." In Fault Diagnosis. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18615-8_11.

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Witczak, Marcin, and Józef Korbicz. "Observers and Genetic Programming in the Identification and Fault Diagnosis of Non-Linear Dynamic Systems." In Fault Diagnosis. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18615-8_12.

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Kowalczuk, Zdzisław, and Tomasz Białaszewski. "Genetic Algorithms in the Multi-Objective Optimisation of Fault Detection Observers." In Fault Diagnosis. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18615-8_13.

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Marciniak, Andrzej, and Józef Korbicz. "Pattern Recognition Approach to Fault Diagnostics." In Fault Diagnosis. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18615-8_14.

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Cholewa, Wojciech. "Expert Systems in Technical Diagnostics." In Fault Diagnosis. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18615-8_15.

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Ligęza, Antoni. "Selected Methods of Knowledge Engineering in Systems Diagnosis." In Fault Diagnosis. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18615-8_16.

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Moczulski, Wojciech. "Methods of Acquisition of Diagnostic Knowledge." In Fault Diagnosis. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18615-8_17.

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Conference papers on the topic "Fault diagnosis"

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He, David, Eric Bechhoefer, Yongzhi Qu, and Brandon Hecke. "Bearing Fault Diagnosis Using A Spectral Average Based Approach." In Vertical Flight Society 70th Annual Forum & Technology Display. The Vertical Flight Society, 2014. http://dx.doi.org/10.4050/f-0070-2014-9527.

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The diagnosis of bearing health through the quantification of accelerometer data has been an area of interest for many years and has resulted in numerous signal processing methods and algorithms. In this paper, a new bearing fault diagnostic approach that combines envelope analysis, time synchronous resampling, and spectral averaging of vibration signals is presented. In this method, the accelerometer signal is first digitized simultaneously with tachometer signal acquisition. Then, the digitized vibration signal is band pass filtered to retain the information associated with the bearing defec
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Loboda, Igor, Sergey Yepifanov, and Yakov Feldshteyn. "An Integrated Approach to Gas Turbine Monitoring and Diagnostics." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-51449.

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This paper presents an investigation of a conventional gas turbine diagnostic process and its generalization. A usual sequence of diagnostic actions consists of two stages: monitoring (fault detection) and subsequent proper diagnosis (fault identification). Such an approach neither implies fault identification nor uses the information about incipient faults unless the engine is recognized as faulty. In previous investigations for engine steady state operation conditions we addressed diagnostics problems without their relation with the monitoring process. Fault classes were given by samples of
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Davison, Craig R., and A. M. Birk. "Automated Fault Diagnosis for Small Gas Turbine Engines." In ASME Turbo Expo 2002: Power for Land, Sea, and Air. ASMEDC, 2002. http://dx.doi.org/10.1115/gt2002-30029.

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In one possible model of distributed power generation a large number of users will operate individual, gas turbine powered, cogeneration systems. These systems will be small, relatively inexpensive, and installed in locations without ready access to gas turbine maintenance experts. Consequently an automated method to monitor the engine and diagnose its health is required. To remain compatible with the low cost of the power system the diagnostics must also be relatively inexpensive to install and operate. Accordingly a minimum number of extra sensors should be used and the analysis performed by
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Jiang, Hao, Xinyu Ren, and Xiaojian Fang. "Aeroengine Multi-Fault Diagnosis Based on Hierarchical Multi-mode Filtering." In GPPS Xi'an21. GPPS, 2022. http://dx.doi.org/10.33737/gpps21-tc-136.

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Carry out model-based online fault diagnosis for aero-engine sensors, actuators and components. Traditional methods use a set of filters to estimate the current state of the engine, and then process the estimated residuals of each filter to obtain the diagnosis result. For single engine faults, this method has a good diagnostic effect, but when double engine faults are considered, the amount of calculation will greatly increase, and the accuracy and real-time performance of fault diagnosis cannot meet the requirements. In this regard, this paper proposes a fault diagnosis algorithm based on hi
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Yu, Rui, Xianling Li, Mo Tao, and Zhiwu Ke. "Fault Diagnosis of Feedwater Pump in Nuclear Power Plants Using Parameter-Optimized Support Vector Machine." In 2016 24th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/icone24-60334.

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The condition monitoring of the feedwater pump in secondary circuit is critical to the safe operation of the nuclear power plant. This article presents a fault diagnosis method of feedwater pump by using parameter-optimized support vector machine (SVM). While the fault features of feedwater pump are reflected from the power spectrum of the vibration signals, we trained and diagnosed the fault feature table with support vector machine. The optimal penalty factor C and kernel parameter γ of support vector machine are selected by grid search and k-fold cross validation. Then the faults are diagno
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Aretakis, N., I. Roumeliotis, and K. Mathioudakis. "Performance Model “Zooming” for In-Depth Component Fault Diagnosis." In ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-23262.

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A method giving the possibility for a more detailed gas path component fault diagnosis, by exploiting the “zooming” feature of current performance modelling techniques, is presented. A diagnostic engine performance model is the main tool that points to the faulty engine component. A diagnostic component model is then used to identify the fault. The method is demonstrated on the case of compressor faults. A 1-D model based on the “stage stacking” approach is used to “zoom” into the compressors, supporting a 0-D engine model. A first level diagnosis determines the deviation of overall compressor
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Shao, Jiye, Rixin Wang, Jingbo Gao, and Minqiang Xu. "Probabilistic Model-Based Fault Diagnosis of the Rotor System." In ASME 2007 Power Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/power2007-22072.

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The rotor is one of the most core components of the rotating machinery and its working states directly influence the working states of the whole rotating machinery. There exists much uncertainty in the field of fault diagnosis in the rotor system. This paper analyses the familiar faults of the rotor system and the corresponding faulty symptoms, then establishes the rotor’s Bayesian network model based on above information. A fault diagnosis system based on the Bayesian network model is developed. Using this model, the conditional probability of the fault happening is computed when the observat
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Wang, Zhao-Hui, Lai-Bin Zhang, Wei Liang, and Lixiang Duan. "Research of Method to Diagnosing Complex Fault of Compressor in Pipeline Station." In 2006 International Pipeline Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/ipc2006-10050.

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The compressor is dynamical equipment in pipeline station to deliver oil gas, it’s fault can result big accident such as stopping delivery and producing economic losing, and some fault of compressor are very complex due to the compressor’s complicated structure. Many compressor have carried simple diagnostic system, which can only diagnose normal fault, are not effective for diagnosing complex fault because these fault attributes are not obvious. This paper has researched the method to diagnose complex fault, by collecting the compressor’s vibration signals, using wavelet noise reduction techn
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Mendonça, Luis, S. M. Vieira, and J. M. C. Sousa. "INTELLIGENT FAULT DIAGNOSIS OF MARINE EQUIPMENTS." In Maritime Transport Conference. Universitat Politècnica de Catalunya. Iniciativa Digital Politècnica, 2024. http://dx.doi.org/10.5821/mt.12834.

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The automatic and intelligent diagnosis of faults in marine equipment is a task that is considered to be of great importance considering the numerous tasks that are associated with professionals working on ships. The possibility of including automatic and intelligent processes on a ship makes it possible to monitor equipment more effectively and make more informed decisions. This approach has received a lot of attention in the academic and industrial fields as it can offer considerable economic and safety advantages. Some fault diagnosis approaches can be found in the literature, where mathema
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Cheng, Cheng, Yiwei Cheng, Wenwei Liu, and Yuanhang Wang. "Federated Learning for Rolling Bearing Fault Diagnosis: A RepViT-Enabled Approach." In 6th International Conference on Structural Health Monitoring and Integrity Management, 8 - 10 November 2024, Zhengzhou. NDT.net, 2025. https://doi.org/10.58286/31020.

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Federated learning (FL) has emerged as a promising approach for fault diagnosis in rotating machinery, addressing data privacy and availability challenges. This paper presents a federated learning-based fault diagnosis framework, leveraging lightweight Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) to diagnose faults under varying operating conditions accurately. The proposed methodology utilizes the RepViT model, a hybrid architecture combining MobileNetV3_L and lightweight ViTs, to achieve efficient fault diagnosis on mobile devices. Experiments conducted on the HUST-bea
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Reports on the topic "Fault diagnosis"

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Graham, Bryan P. Multiple Fault Diagnosis System. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada200406.

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Seginer, Ido, Louis D. Albright, and Robert W. Langhans. On-line Fault Detection and Diagnosis for Greenhouse Environmental Control. United States Department of Agriculture, 2001. http://dx.doi.org/10.32747/2001.7575271.bard.

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Background Early detection and identification of faulty greenhouse operation is essential, if losses are to be minimized by taking immediate corrective actions. Automatic detection and identification would also free the greenhouse manager to tend to his other business. Original objectives The general objective was to develop a method, or methods, for the detection, identification and accommodation of faults in the greenhouse. More specific objectives were as follows: 1. Develop accurate systems models, which will enable the detection of small deviations from normal behavior (of sensors, contro
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Allison, Kenneth R. Use of a Working Model in Fault Diagnosis. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada195621.

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Church, K. G., R. R. Kolesar, M. E. Phillips, and R. C. Garrido. Air Vehicle Diagnostic System: CH-46 Aft Main Transmission Fault Diagnosis-Final Report. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada329362.

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Springer, David. Expert Meeting Report: HVAC Fault Detection, DIagnosis, and Repair/Replacement. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1254918.

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Springer, David. Expert Meeting Report: HVAC Fault Detection, Diagnosis, and Repair/Replacement. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1255641.

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Frank, Stephen M., Guanjing Lin, Xin Jin, et al. Metrics and Methods to Assess Building Fault Detection and Diagnosis Tools. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1503166.

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Kim, Minsung, Seok Ho Yoon, W. Vance Payne, and Piotr A. Domanski. Cooling mode fault detection and diagnosis method for a residential heat pump. National Institute of Standards and Technology, 2008. http://dx.doi.org/10.6028/nist.sp.1087.

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Reifman, J., T. Y. C. Wei, and J. E. Vitela. PRODIAG: Combined expert system/neural network for process fault diagnosis. Volume 1, Theory. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/219266.

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Bae, Yeonjin, Borui Cui, Jaewan Joe, et al. Review: Sensor Impact on Building Controls and Automatic Fault Detection and Diagnosis (AFDD). Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1671427.

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