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2009 | Buch

Introduction Kapitel lesen Erstes Kapitel lesen

Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach

verfasst von: Ehsan Sobhani-Tehrani, Khashayar Khorasani

Verlag: Springer US

Buchreihe : Lecture Notes in Control and Information Sciences

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

Theincreasingcomplexityofspacevehiclessuchassatellites,andthecostreduction measures that have affected satellite operators are increasingly driving the need for more autonomy in satellite diagnostics and control systems. Current methods for detecting and correcting anomalies onboard the spacecraft as well as on the ground are primarily manual and labor intensive, and therefore, tend to be slow. Operators inspect telemetry data to determine the current satellite health. They use various statisticaltechniques andmodels,buttheanalysisandevaluation ofthelargevolume of data still require extensive human intervention and expertise that is prone to error. Furthermore, for spacecraft and most of these satellites, there can be potentially unduly long delays in round-trip communications between the ground station and the satellite. In this context, it is desirable to have onboard fault-diagnosis system that is capable of detecting, isolating, identifying or classifying faults in the system withouttheinvolvementandinterventionofoperators.Towardthisend,theprinciple goal here is to improve the ef?ciency, accuracy, and reliability of the trend analysis and diagnostics techniques through utilization of intelligent-based and hybrid-based methodologies.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction
There is an increasing demand for man-made dynamic systems to operate autonomously in the presence of faults and failures in sensors, actuators, or components. Fault detection and identification are essential components of an autonomous system. Hence, a high demand exists for the development of intelligent systems that are able to autonomously detect the presence and isolate the location of faults occurring in different components of complex dynamic systems. Especially faults in a control loop are of particular importance as they may instantly result in instability of the controlled system. Thus, it is crucial that faults are efficiently and timely detected and isolated while the system is in operation. This is essentially the concept of online health monitoring though, in general, health monitoring may also be performed offline using stored data in a post-processing capacity to determine if the system overhaul is necessary. In general, autonomous online health monitoring and fault diagnosis is essential for mission- and safety-critical systems as opposed to fail-operational systems, where offline health monitoring and fault diagnosis is usually sufficient – in order to perform maintenance. In this monograph, the main focus is on developing a fault diagnosis (FD) methodology that enables online health monitoring of nonlinear systems; however, the proposed approach can as well be applied for offline monitoring purposes.
Ehsan Sobhani-Tehrani, Khashayar Khorasani
Chapter 2. Fault Detection and Diagnosis
In this chapter, we start with the formal definition and formulation of the fault detection and diagnosis problem in nonlinear systems. Then, desired attributes of a fault diagnosis system and the rationale behind each attribute are discussed. A comprehensive survey and analysis of the literature on model-based and computational intelligence (CI)-based approaches to fault diagnosis is then presented with individual emphasis on the tasks of detection, isolation and identification. A number of well-known methodologies within each approach are further demonstrated, and their respective advantages and disadvantages are highlighted. Finally, the issue of robustness in fault diagnosis is introduced and briefly discussed.
Ehsan Sobhani-Tehrani, Khashayar Khorasani
Chapter 3. Proposed FDII for Nonlinear Systems with Full-State Measurement
In this monograph, a new integrated solution to the problem of fault detection, isolation and identification (FDII) for nonlinear systems is proposed. The proposed fault diagnosis methodology benefits from both a priori mathematical model information of the system and the nonlinear function approximation and adaptation capability of neural networks in a hybrid framework. More specifically, mathematical model of the system is used to construct a bank of parameterized fault models, which enables fault isolation.
Ehsan Sobhani-Tehrani, Khashayar Khorasani
Chapter 4. Proposed FDII for Nonlinear Systems with Partial State Measurement
Similar to many of the existing fault diagnosis methods, the two FDII schemes developed in the previous chapter relied on the availability of full-state measurements. However, even with recent advances in sensor and instrumentation technology, all the states of a dynamical system may not be directly measurable. This might be due to unavailability of operational, accurate, or reliable (on-board) sensors for measurement of some specific physical variables. For example, the state of charge (SOC) in batteries – employed almost everywhere from portable electronics to hybrid electric vehicles (HEV) – cannot be directly measured while the battery is in operation. Some experimental methods certainly exist for measuring the SOC, but such measurements have to be taken under a controlled experimental setup and cannot be achieved while the battery provides power to the system (i.e., laptop, HEV, etc.).
Ehsan Sobhani-Tehrani, Khashayar Khorasani
Chapter 5. Application to a Satellite’s Attitude Control Subsystem
Like many other man-made dynamical systems, spacecraft are potentially subjected to unexpected anomalies and failures in subsystems and components during their mission lifetime. Future generations of spacecraft need to show proper reaction to unexpected events such as component/subsystem failures or environmental interactions. Most currently used spacecraft controllers react to different situations according to some, often, hard-coded routines. This is impractical when the spacecraft is facing an unexpected event. On the other hand, the probability of fault occurrence increases with the time needed to accomplish the mission. Hence, the development of technologies that enable the spacecraft to automatically detect, isolate, identify, and eventually respond and recover from (unexpected) faults/failures in its components, subsystems, or mission goals is highly desirable. The main goal of an autonomous operation should be to maintain the spacecraft’s safety and to perform the critical functions in priority.
Ehsan Sobhani-Tehrani, Khashayar Khorasani
Chapter 6. Conclusions
In this monograph, the problem of fault diagnosis in components and actuators of nonlinear systems was considered. A fault diagnosis system at its best must be able to not only detect the presence and isolate the location of faults in a system but also identify them (i.e., estimate their severities) once they are detected and isolated. Hence, a diagnostic system is also equivalently called a fault detection, isolation, and identification (FDII) system. While the importance of fault detection and isolation (FDI) is evident for health monitoring of engineering systems, the importance of fault identification has not been equally recognized in the literature. Consequently, fewer theoretical and practical contributions in the domain of fault identification or severity estimation exist in the literature, especially for nonlinear systems. However, it was shown in Chapter 1 that identification of fault severities is a cornerstone to fault prognosis and subsequently to develop a condition-based maintenance (CBM) system. Furthermore, it was shown that the accurate fault identification is an invaluable asset for fault tolerant control systems, in general, and is a necessity for implementing active fault accommodation and recovery procedures, in particular.
Ehsan Sobhani-Tehrani, Khashayar Khorasani
Backmatter
Metadaten
Titel
Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach
verfasst von
Ehsan Sobhani-Tehrani
Khashayar Khorasani
Copyright-Jahr
2009
Verlag
Springer US
Electronic ISBN
978-0-387-92907-1
Print ISBN
978-0-387-92906-4
DOI
https://doi.org/10.1007/978-0-387-92907-1

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