A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> In this paper we survey a number of methods for the detection of abrupt changes (such as failures) in stochastic dynamical systems. We concentrate on the class of linear systems, but the basic concepts, if not the detailed analyses, carry over to other classes of systems. The methods surveyed range from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, to the development of jump process formulations. Tradeoffs in complexity vs performance are discussed. <s> BIB001 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> The supervision of technical processes is the subject of increased development because of the increasing demands on reliability and safety. The use of process computers and microcomputers permits the application of methods which result in an earlier detection of process faults than is possible by conventional limit and trend checks. With the aid of process models, estimation and decision methods it is possible to also monitor nonmeasurable variables like process states, process parameters and characteristic quantities. This contribution presents a brief summary of some basic fault detection methods. This is followed by a description of suitable parameter estimation methods for continuous-time models. Then two examples are considered, the fault detection of an electrical driven centrifugal pump by parameter monitoring and the leak detection for pipelines by a special correlation method. <s> BIB002 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Techniques to detect and isolate failures in complex technological systems, such as sensor biases, actuator malfunctions, leaks, and equipment deterioration are surveyed. The methods are based on analytical redundancy afforded by a mathematical model of the system. The main components of such techniques are residual generation using the model, signature generation by statistical testing, and signature analysis. Model-structural conditions for failure isolation are introduced together with transformation methods to implement them. Sensitivity and robustness considerations are presented, and a design framework based on model redundancy is proposed. > <s> BIB003 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Abstract The paper reviews the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and presents some new results. It outlines the principles and most important techniques of model-based residual generation using parameter identification and state estimation methods with emphasis upon the latest attempts to achieve robustness with respect to modelling errors. A solution to the fundamental problem of robust fault detection, providing the maximum achievable robustness by decoupling the effects of faults from each other and from the effects of modelling errors, is given. This approach not only completes the theory but is also of great importance for practical applications. For the case where the prerequisites for complete decoupling are not given, two approximate solutions—one in the time domain and one in the frequency domain—are presented, and the crossconnections to earlier approaches are evidenced. The resulting observer schemes for robust instrument fault detection, component fault detection, and actuator fault detection are briefly discussed. Finally, the basic scheme of fault diagnosis using a combination of analytical and knowledge-based redundancy is outlined. <s> BIB004 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> An overview of failure-tolerant control is presented, focusing on the control of continuous-time dynamic systems (or plants) whose motions can be represented by integrals of nonlinear ordinary differential equations. Failure tolerance may be called upon to improve system reliability, maintainability, and survivability, and the issues attached to achieving these goals are examined. Robustness, which is required in some degree by all failure-tolerant systems, is discussed. The use of parallel redundancy is examined. Analytical redundancy, the principal functions of which are failure detection, failure identification, and control-system reconfiguration, is also considered. The use of expert systems and neural networks is discussed. > <s> BIB005 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Proper detection and diagnosis of failing system components is crucial to efficient mining operations. However, the harsh mining environment offers special challenges to these types of actions. The atmosphere is damp, dirty, and potentially explosive, and equipment is located in confined areas far from shop facilities. These conditions, coupled with the increasing cost of downtime and complexity of mining equipment, have forced researchers and operators to investigate alternatives for improving equipment maintainability. This paper surveys monitoring and diagnosis technologies that offer opportunities for improving equipment availability in mining. Expert systems, model-based approaches, and neural nets are each discussed in the context of fault detection and diagnosis. The paper concludes with a comparative discussion summarizing the advantages and disadvantages of each. > <s> BIB006 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Abstract The paper provides a description of a new and comprehensive model of concepts termed Technical Failure and Fault Management Model and focusses, after outlining basic concepts, the Management System Model and the Diagnostic System Model . For both, the aspects functions, purposes and means play an important role to structurize the comprehensive set of concepts and to describe both the concepts and the resulting mutual relations. <s> BIB007 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Abstract This paper gives a review of the principal observer-based fault diagnosis approaches for nonlinear systems. Some schemes extending the well-known diagnosis methods for linear systems to the nonlinear case are considered. The robustness of these schemes in presence of unknown inputs is discussed. Similarities between the approaches considered are pointed out also. The survey is concluded with a description of some open problems. <s> BIB008 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Abstract Fault-tolerant control is used in systems that need to be able to detect faults and prevent simple faults related to control loops from developing into production stoppages or failures at a plant level. This is obtained by combining fault detection with supervisory control and re-configuration to accommodate faults. Much attention has been focused on fault detection in its own right. This paper deals with fault tolerant control from a much wider point of view, covering the entire design process from the engineering of the interface to structural implementation. Experience ranging from a simple temperature control to a complex satellite control system demonstrates significant improvements in plant availability using simple means. <s> BIB009 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> This paper is intended as a tutorial overview of induction motors signature analysis as a medium for fault detection. The purpose is to introduce in a concise manner the fundamental theory, main results, and practical applications of motor signature analysis for the detection and the localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of induction motors. The paper is focused on the so-called motor current signature analysis which utilizes the results of spectral analysis of the stator current. The paper is purposefully written without "state-of-the-art" terminology for the benefit of practising engineers in facilities today who may not be familiar with signal processing. <s> BIB010 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> In this part of the paper, we review qualitative model representations and search strategies used in fault diagnostic systems. Qualitative models are usually developed based on some fundamental understanding of the physics and chemistry of the process. Various forms of qualitative models such as causal models and abstraction hierarchies are discussed. The relative advantages and disadvantages of these representations are highlighted. In terms of search strategies, we broadly classify them as topographic and symptomatic search techniques. Topographic searches perform malfunction analysis using a template of normal operation, whereas, symptomatic searches look for symptoms to direct the search to the fault location. Various forms of topographic and symptomatic search strategies are discussed. <s> BIB011 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Abstract For the improvement of reliability, safety and efficiency advanced methods of supervision, fault-detection and fault diagnosis become increasingly important for many technical processes. This holds especially for safety related processes like aircraft, trains, automobiles, power plants and chemical plants. The classical approaches are limit or trend checking of some measurable output variables. Because they do not give a deeper insight and usually do not allow a fault diagnosis, model-based methods of fault-detection were developed by using input and output signals and applying dynamic process models. These methods are based, e.g., on parameter estimation, parity equations or state observers. Also signal model approaches were developed. The goal is to generate several symptoms indicating the difference between nominal and faulty status. Based on different symptoms fault diagnosis procedures follow, determining the fault by applying classification or inference methods. This contribution gives a short introduction into the field and shows some applications for an actuator, a passenger car and a combustion engine. <s> BIB012 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> On-line fault detection and isolation techniques have been developed for automated processes during the last few years. These methods include numerical methods, artificial intelligence methods or combinations of the two methodologies. This paper includes a reference to recent research work on numerical methods, an extensive presentation of artificial intelligence methods used for the fault detection process in technical systems and relevant survey material. Special reference is made to the on-line expert systems development where specific resent research work is illustrated. <s> BIB013 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> This paper is the second of a two-part review of methods for automated fault detection and diagnostics (FDD) and prognostics whose intent is to increase awareness of the HVAC&R research and development community to the body of FDD and prognostics developments in other fields as well as advancements in the field of HVAC&R. The first part of the review focused on generic FDD and prognostics, provided a framework for categorizing methods, described them, and identified their primary strengths and weaknesses (Katipamula and Brambley 2005). In this paper we address research and applications specific to the fields of HVAC&R, provide a brief discussion on the current state of diagnostics in buildings, and discuss the future of automated diagnostics in buildings. <s> BIB014 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. This paper presents a survey of machine condition monitoring and fault diagnosis using support vector machine (SVM). It attempts to summarize and review the recent research and developments of SVM in machine condition monitoring and diagnosis. Numerous methods have been developed based on intelligent systems such as artificial neural network, fuzzy expert system, condition-based reasoning, random forest, etc. However, the use of SVM for machine condition monitoring and fault diagnosis is still rare. SVM has excellent performance in generalization so it can produce high accuracy in classification for machine condition monitoring and diagnosis. Until 2006, the use of SVM in machine condition monitoring and fault diagnosis is tending to develop towards expertise orientation and problem-oriented domain. Finally, the ability to continually change and obtain a novel idea for machine condition monitoring and fault diagnosis using SVM will be future works. <s> BIB015 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> This paper provides a tutorial introduction to reconfigurable control and surveys recent advances on this topic. Control reconfiguration is an important method of fault-tolerant control that uses the results of a fault diagnosis component to restructure the control loop and to adapt the controller to the faulty plant. This paper describes recent approaches that are suitable for on-line application. These approaches lead to a redesign of the controller or augment the control loop with a reconfiguration block that adapts the nominal controller to the dynamical properties of the faulty plant. The approaches are illustrated by means of a running example and experimental applications of selected methods. Challenges for future research in the field are stated. <s> BIB016 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> A survey on fault-tolerant control is presented for variable speed drives (VSD), mainly addressing DC and induction motors. Thus, fault diagnosis, accommodation and hardware reconfiguration are reviewed with application to VSD. First, the most common fault scenarios in these electrical machines are described. These conditions are analysed, and their implications and mathematical modelling are discussed. Next, the fault diagnosis strategies based on signal processing, model-based techniques and artificial intelligence are reviewed. Moreover, the diverse hardware reconfiguration schemes of power actuators with semiconductor failures are detailed. A key piece in any VSD is the control algorithm, which can be severely affected in a fault condition. Finally, the fault accommodation schemes suggested so far in the literature are illustrated. <s> BIB017 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many anomaly detection techniques have been specifically developed for certain application domains, while others are more generic. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. We have grouped existing techniques into different categories based on the underlying approach adopted by each technique. For each category we have identified key assumptions, which are used by the techniques to differentiate between normal and anomalous behavior. When applying a given technique to a particular domain, these assumptions can be used as guidelines to assess the effectiveness of the technique in that domain. For each category, we provide a basic anomaly detection technique, and then show how the different existing techniques in that category are variants of the basic technique. This template provides an easier and more succinct understanding of the techniques belonging to each category. Further, for each category, we identify the advantages and disadvantages of the techniques in that category. We also provide a discussion on the computational complexity of the techniques since it is an important issue in real application domains. We hope that this survey will provide a better understanding of the different directions in which research has been done on this topic, and how techniques developed in one area can be applied in domains for which they were not intended to begin with. <s> BIB018 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Fault tolerant control (FTC) is the branch of control theory, ::: dealing with the control of systems that become faulty during ::: their operating life. Following the systems classification, as ::: linear and nonlinear models, FTC can be classified in two ::: different groups, linear FTC (LFTC) dealing with linear models, ::: and the one of interest to us in this paper, nonlinear FTC (NFTC), ::: which deals with nonlinear models. We present in this paper a ::: survey of some of the results obtained in these last years on NFTC. <s> BIB019 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Fault detection, isolation, and reconfiguration (FDIR) is an important and challenging problem in many engineering applications and continues to be an active area of research in the control community. This paper presents a survey of the various model-based FDIR methods developed in the last decade. In the paper, the FDIR problem is divided into the fault detection and isolation (FDI) step, and the controller reconfiguration step. For FDI, we discuss various model-based techniques to generate residuals that are robust to noise, unknown disturbance, and model uncertainties, as well as various statistical techniques of testing the residuals for abrupt changes (or faults). We then discuss various techniques of implementing reconfigurable control strategy in response to faults. <s> BIB020 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> This review paper is to give a full picture of fault detection and diagnosis (FDD) in complex systems from the perspective of data processing. As a matter of fact, an FDD system is a data-processing system on the basis of information redundancy, in which the data and human's understanding of the data are two fundamental elements. Human's understanding may be an explicit input-output model representing the relationship among the system's variables. It may also be represented as knowledge implicitly (e.g., the connection weights of a neural network). Therefore, FDD is done through some kind of modeling, signal processing, and intelligence computation. In this paper, a variety of FDD techniques are reviewed within the unified data-processing framework to give a full picture of FDD and achieve a new level of understanding. According to the types of data and how the data are processed, the FDD methods are classified into three categories: model-based online data-driven methods, signal-based methods, and knowledge-based history data-driven methods. An outlook to the possible evolution of FDD in industrial automation, including the hybrid FDD and the emerging networked FDD, are also presented to reveal the future development direction in this field. <s> BIB021 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Abstract Nonstationary signal analysis is one of the main topics in the field of machinery fault diagnosis. Time–frequency analysis can identify the signal frequency components, reveals their time variant features, and is an effective tool to extract machinery health information contained in nonstationary signals. Various time–frequency analysis methods have been proposed and applied to machinery fault diagnosis. These include linear and bilinear time–frequency representations (e.g., wavelet transform, Cohen and affine class distributions), adaptive parametric time–frequency analysis (based on atomic decomposition and time–frequency auto-regressive moving average models), adaptive non-parametric time–frequency analysis (e.g., Hilbert–Huang transform, local mean decomposition, and energy separation), and time varying higher order spectra. This paper presents a systematic review of over 20 major such methods reported in more than 100 representative articles published since 1990. Their fundamental principles, advantages and disadvantages, and applications to fault diagnosis of machinery have been examined. Some examples have also been provided to illustrate their performance. <s> BIB022 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> With wide-spread application of power electronic systems across many different industries, their reliability is being studied extensively. This paper presents a comprehensive review of reliability assessment and improvement of power electronic systems from three levels: 1) metrics and methodologies of reliability assessment of existing system; 2) reliability improvement of existing system by means of algorithmic solutions without change of the hardware; and 3) reliability-oriented design solutions that are based on fault-tolerant operation of the overall systems. The intent of this review is to provide a clear picture of the landscape of reliability research in power electronics. The limitations of the current research have been identified and the direction for future research is suggested. <s> BIB023 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Inverters play key roles in motor drives, flexible power transmissions, and recently grid-tied renewable energy generation units. Therefore, availability and reliability of inverters have become increasingly important. Following early stage fault detections in inverters, remedial actions can extend normal operation of inverters and, in some cases, derate the system to prevent unexpected shutdowns. A remedial action typically contains a combination of hardware and software reconfigurations. The main purpose of this paper is to provide an instructive survey of existing fault-tolerance (remedial) techniques for three-phase, two-level, and multilevel inverters. <s> BIB024 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Recently, to ensure the reliability and safety of modern large-scale industrial processes, data-driven methods have been receiving considerably increasing attention, particularly for the purpose of process monitoring. However, great challenges are also met under different real operating conditions by using the basic data-driven methods. In this paper, widely applied data-driven methodologies suggested in the literature for process monitoring and fault diagnosis are surveyed from the application point of view. The major task of this paper is to sketch a basic data-driven design framework with necessary modifications under various industrial operating conditions, aiming to offer a reference for industrial process monitoring on large-scale industrial processes. <s> BIB025 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Copyright © 2014 Hongli Dong et al.This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. <s> BIB026 </s> A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches <s>  <s> Swarm systems have received increasing research attention in recent years and they can be found in many application areas as diverse as unmanned vehicle formation systems, multi-robot systems, sensor networks, etc. Reliability and safety are important issues in swarm systems, which can be improved by the fault diagnosis technology. In this paper, recent development of fault diagnosis algorithms for swarm systems is reviewed. The description of swarm systems is given, followed by characteristics of faults in swarm systems. Specially, faults in swarm systems are classified into topology faults and component faults. Then fault diagnosis algorithms for swarm systems are classified according to their architectures, fault types and approaches, respectively. Finally, several unsolved problems of fault diagnosis algorithms for swarm systems are highlighted. <s> BIB027
A fault is defined as an unpermitted deviation of at least one characteristic property or parameter of the system from the acceptable/usual/standard condition BIB007 . Examples of such malfunctions are the blocking of an actuator, the loss of a sensor (e.g., a sensor gets stuck at a particular value or has a variation in the sensor scalar factor), or the disconnection of a system component. Therefore, the faults are often classified as actuator faults, sensor faults, and plant faults (or called component faults or parameter faults), which either interrupt the control action from the controller on the plant or produce substantial measurement errors or directly change the dynamic input/output properties of the system, leading to system performance degradation and even the damage and collapse of the whole system. In order to improve the reliability of a system concerned, fault diagnosis is usually employed to monitor, locate, and identify the faults by using the concept of redundancy, either hardware redundancy or software redundancy (or called analytical redundancy). The basic idea of the hardware redundancy is to use identical components with the same input signal so that the duplicated output signals can be compared, leading to diagnostic decision by a variety of methods such as limit checking and majority voting. Hardware redundancy is reliable, but expensive and increasing weights and occupying more space. It is necessary for key components to equip with the redundant duplicate, but would not be applicable if the hardware redundancy is applied to the whole system due to the cost or the difficulty for physical installing when the space and/or weight are strictly constrained. With the mature of modern control theory, the analytical redundancy technique has become the main stream of the fault diagnosis research since the 1980s, whose schematic can be depicted as in Fig. 1 . For a controlled system subjected to actuator fault f a , process/component fault f c , and sensor fault f s , the input u and the output y are used to construct a fault diagnosis algorithm, which is employed to check the consistency of the feature information of the real-time process carried by the input and output data against the preknowledge on a healthy system, and a diagnostic decision is then made by using diagnostic logics. Compared with hardware redundancy methods, analytical redundancy diagnostic methods are more cost effective, but more challenging due to environmental noises, inevitable modeling error, and the complexity of the system dynamics and control structure. Fault diagnosis includes three tasks, that is, fault detection, fault isolation, and fault identification. Fault detection is the most basic task of the fault diagnosis, which is used to check whether there is malfunction or fault in the system and determine the time when the fault occurs. Furthermore, fault isolation is to determine the location of the faulty component, and fault identification is to determine the type, shape, and size of the fault. Clearly, the locations of the faulty components and their severe degrees of the malfunctions described by the types, shapes, and sizes of the faults are vital for the system to take fault-tolerant responses timely and appropriately to remove the adverse effects from the faulty parts to the system normal operation. The schematic of fault-tolerant control is depicted in Fig. 2 , which shows that fault-tolerant control is integrated with fault diagnosis in essence. Real-time fault diagnosis can detect whether the system is faulty and tell where the fault occurs and how severe the malfunction is. Based on the valuable information, the supervision system can thus take appropriate faulttolerant actions such as offsetting the faulty signals by actuator/ sensor signal compensation, tuning or reconfiguring the controller, and even replacing faulty components by redundant duplicates, so that the adverse effects from faults are accommodated or removed. During the last four decades, fruitful results have been reported on fault diagnosis methods, fault-tolerant control techniques, and their applications in various industrial processes and systems. A number of survey papers were written, for instance, BIB001 - BIB024 , which are presented in Table I, categorized  in terms of years and methods/applications.   TABLE I  SURVEY PAPERS FOR FAULT DIAGNOSIS AND FAULT TOLERANCE Specifically, in 1976, Willsky presented the key concepts of analytical redundancy for model-based fault detection and diagnosis in the early survey paper BIB001 . More comprehensive model-based fault diagnosis methods such as parity space approaches, observer-based methods, and parameter estimation techniques are reviewed by BIB002 BIB003 BIB004 BIB008   BIB012 . A three-part survey paper  BIB011  on fault diagnosis was presented in 2003 from the viewpoint of quantitative mode-based, qualitative modelbased, and process history-based methods, respectively. In BIB018 , a structured and comprehensive overview of the research on anomaly detection is provided, which is referred to the problem of finding patterns in data that do not conform to expected behavior and has an extensive use in a wide variety of applications such as intrusion detection for cyber security, military surveillance for enemy activities, and fault detection in safety-critical systems. In BIB013 BIB021 BIB025 , comprehensive fault diagnostic methods were reviewed respectively from the datadriven perspective. In BIB026 , a short review on fault detection in sensor networks was provided. With respect to fault diagnosis methods for various processes/systems applications, a couple of survey papers were addressed for mining equipment BIB006 , electric motors BIB010   , building systems (such as heating, ventilating, airconditioning, and refrigeration) BIB014 ,  , machinery system BIB015 , BIB022 , and swarm systems (consisting of multiple intelligent interconnected nodes and possessing swarm capability) BIB027 , respectively. For fault-tolerant control, an early review paper was presented by BIB005 in 1991, which introduced the basic concepts of fault-tolerant control and analyzed the applicability of artificial intelligence (e.g., neural network and expert systems) to faulttolerant control systems. In 1997, an overview of fault-tolerant control was given from the system development view BIB009 . In the same year, a comprehensive review was contributed by  , which presented the key issues of the fault-tolerant control systems and outlined the state of the art in this field. Reconfigurable fault-tolerant control systems are reviewed extensively by  BIB016  , respectively. Some results on faulttolerant control for nonlinear systems were reviewed by BIB019 . Along with fault diagnosis, brief reviews on data-driven faulttolerant control and model-based fault-tolerant reconfiguration were presented by  and BIB020 , respectively. From the viewpoint of industrial applications, fault tolerance techniques were reviewed for electric drive systems BIB017 and power electronics systems BIB023 , BIB024 , respectively. The three-part survey paper aims to give a comprehensive overview for real-time fault diagnosis and fault-tolerant control, with particular attention on the results reported in the last decade. Generally, fault diagnosis methods can be categorized into model-based methods, signal-based methods, knowledgebased methods, hybrid methods (the combination methods of at least two methods), and active fault diagnosis methods. In this paper, fault diagnosis techniques will be reviewed from the model-and signal-based perspectives; and the knowledgebased, hybrid, and active fault diagnosis techniques will be reviewed in the second part of the three-part survey paper. This paper and the second part aim to review the existing fault diagnosis methods and applications within a framework by using the up-to-date references. The rest of this paper is organized as follows. Following the introduction session, model-based fault diagnosis techniques are reviewed in Section II. Signal-based fault diagnosis is reviewed in Section III. This paper is ended with the conclusions in Section IV.