There has been considerable interest in fault detection and identification recently due to the increasing complexity of automation processes. A more suitable strategy of using knowledge-based techniques instead of traditional linearization techniques is used to produce a model of a non-linear system. A method to generate the training data is presented. A fuzzy relational sliding mode observer (FRSMO) and proportional integral observer (FRPIO) are proposed to estimate the magnitude of incipient faults in information-poor and non-linear systems. In the fuzzy PIO, fault size can be obtained from the error passing the PI feedback compensation. In the fuzzy SMO, the equivalent injection is used to compensate for the fault thus obtaining the fault magnitude. To reduce modelling errors, an on-line learning fault identification scheme is used to update the model and identify the fault in a periodical mode with different time intervals during the whole procedure. The performance of the proposed methods is evaluated using a cooling-coil subsystem of an air-conditioning plant to identify the typical actuator fault and flow reduction fault in a simulation environment.
This book is helpful to those readers who are willing to know about mobile agents. This book elaborates the concepts of fault tolerance in mobile agent systems that how a system continues to perform its task even in case of occurrence of any fault. This book discusses the various existing fault tolerant approaches in mobile agent systems. Along this readers will also find a novel approach for fault tolerance in mobile agent systems. This Novel approach suites well for both read as well as write applications too.
This book presents a new transmission line protection scheme using voltage transient waveforms and fundamental voltage and current signals. The scheme integrates the high frequency transient protection algorithms with the synchronized sampling fault location algorithms to produce high speed fault detection and accurate location to the fault. The algorithms were enhanced by a new fault classification technique based on wavelet singular entropy and neural networks to classify different fault types and detect arcing activity within the faultIn order to reach better reliability and stability to the transmission network, transient adaptive single pole auto reclosing scheme (SPAR) was introduced. In the case of transient faults, the arcing extinction time can be accurately determined and in the case of a permanent fault, breaker re-closure can be avoided.
The Uemachi fault is a 40-kilometer long reverse fault that traverses north south through the middle of the Osaka City, one of the most highly populated regions in Japan. An integrated geophysical survey, using shallow high-resolution seismic reflection and ground penetrating radar (GPR) methods, was carried out across the Uemachi fault system to explore the subsurface geometrical layout of the fault and to investigate the possible activity and evolution of the fault system in order to mitigate future natural hazards. Seismic survey lines that had been acquired using different acquisition parameters and instrumentation were compiled into a single 9.2-kilometer long seismic section that shows the subsurface configuration of the Uemachi fault and the Suminoe flexure. A GPR survey was conducted across the Uemachi fault to investigate the shallow part of the subsurface and to confirm the presence of the shallow faults detected by seismic survey. Integrated information from seismic sections, GPR survey and drilling data in the study area are used to construct a simple structural model, which explains the subsurface geometry, activity, and evolution of the Uemachi fault.
A DC motor is widely used in various electrical appliances and it produces vibrations during its run. Any fault in the motor or the fault in the system on which motor is mounted will result in the failure of the system. So in order to protect the system, there is a need to develop a fault detection system for dc motor working in micro-manufacturing applications. Fast Fourier Transform has been used to examine the presence of faults in the system. Further, speed and acceleration measurements of dc motor are useful for its characterization and control. Also, for this there is a need to develop an embedded system for dc motor speed characterization. The systems has been programmed on ARM Micro-controller.In this research work, the vibration based embedded systems for fault detection and speed characterization of dc motor are presented.
Comprehensive coverage of all aspects of space application oriented fault tolerance techniques • Experienced expert author working on fault tolerance for Chinese space program for almost three decades• Initiatively provides a systematic texts for the cutting-edge fault tolerance techniques in spacecraft control computer, with emphasis on practical engineering knowledge• Presents fundamental and advanced theories and technologies in a logical and easy-to-understand manner• Beneficial to readers inside and outside the area of space applications
The increasing demand for energy generation from renewable sources has led to a growing attention on wind turbines. They represent very complex systems which require reliability, availability, maintainability, safety and, above all, efficiency on the generation of electrical power. Thus, new research challenges arise in the context of modelling and control. Advanced sustainable control systems can provide the optimisation of energy conversion and guarantee the desired performances even in presence of possible anomalous working condition, caused by unexpected faults. This monograph deals with the fault diagnosis and the fault tolerant control of wind turbines, and it proposes novel solutions to the problem of earlier fault detection and accommodation. The developed fault tolerant controller is mainly based on a fault diagnosis module, which provides the on-line information on the faulty or fault-free status of the system, so that the control action can be compensated. The design of the fault estimators involves different approaches, as they offer an effective tool for coping with a poor analytical knowledge of the system dynamics, together with noise and disturbances.
We propose a new class of mathematical structures called (m, n)-semirings (which generalize the usual semirings), and describe their basic properties. We also de?ne partial ordering, and generalize the concepts of congruence, homomorphism, etc., for (m, n)-semirings. Following earlier work by Rao , we consider a system as made up of several components whose failures may cause it to fail, and represent the set of systems algebraically as an (m, n)-semiring. Based on the characteristics of these components we present a formalism to compare the fault tolerance behavior of two systems using our framework of a partially ordered (m, n)-semiring. Assuming 0 as a system which is “always up” and 1 as a system which is “always down”, based on these assumptions we prove which system is more fault tolerant. We also compare the fault tolerance behavior of two congruent system using the congruence relation. We check whether two systems are congruent or not based on their fault tolerance behavior. We have also mentioned an example of wireless sensor network and comparison of fault tolerance in two such networks.
Our work is aimed at developing a fault tolerance policy for embedded mobile devices where we can determine suitability of a fault tolerance mechanism for the application with respect to the needs of user and available resources. More precisely, we are developing methods to define requirements of applications and services offered by a particular fault tolerance mechanism. This helps us in finding compatibility between applications and mechanisms at any given time, and allows us to choose the most suitable mechanism. Another part of out thesis has been to develop two distributed coordinated checkpointing algorithms. The practical implementation of our work has been done on WTK 2.0 with J2ME-MIDP. We have done an implementation of our work with our checkpointing mechanisms and game application. We have also shown how to profile applications and mechanisms to integrate in our work.
Recently, robotics research has been gained a lot of attentions, due to its wide applications, especially in some places that human beings cannot survive, like in a planet or fire. Flocking, as one of important applications of coordination of multiple robots, has a lot of applications. Our research goal is to achieve the effective coordinated flocking even with the crash of mobile robots. First, we proposed a fault tolerant flocking in an asynchronous model. Our algorithm ensures that the crash of faulty robots does not bring the formation to a permanent stop, and that the correct robots are thus eventually allowed to reorganize and continue moving together. We further design a new method by allowing the formation to move to any direction, including rotation, yet in a semi-synchronous model. We analyze the self-stabilization of our fault tolerant flocking algorithms when the memory of robots may corrupt. Finally, we propose a non-fault tolerant flocking algorithm in order to compare the performance with the above fault-tolerant ones. The described algorithm can effectively adapt to the environment to avoid the collision among robots and obstacles.
Process history based approaches for fault diagnosis has been widely used recently. Principal Component Analysis (PCA) is one of these approaches, which is a linear approach; however most of the processes are nonlinear. Hence nonlinear extensions of the PCA have been developed. Nonlinear Principal Component Analysis (NLPCA) based on the neural networks is a common method which is used for process monitoring and fault diagnosis. NLPCA based neural networks are implemented using different methods, in this book we apply Auto-Associative Neural Networks (AANN) for implementing NLPCA. This work is aimed towards the development of an algorithm used in conjunction with an Auto Associative Neural Network (AANN) to help locate and reconstruct faulty sensor inputs in control systems. Also an algorithm is developed for locating the source of the process fault.
This work proposes an approach to software faults diagnosis in complex fault tolerant systems, encompassing the phases of error detection, fault location, and system recovery. Errors are detected in the first phase, exploiting the operating system support. Faults are identified during the location phase, through a machine learning based approach. Then, the best recovery action is triggered once the fault is located. Feedback actions are also used during the location phase to improve detection quality over time. A real world application from the Air Traffic Control field has been used as case study for evaluating the proposed approach. Experimental results, achieved by means of fault injection, show that the diagnosis engine is able to diagnose faults with high accuracy and at a low overhead.
Reversible or information-lossless circuits have applications in digital signal processing, communication, computer graphics and cryptography. They are also a fundamental requirement in the emerging field of quantum computation. We investigate the synthesis of reversible circuits that employ a minimum number of gates and contain no redundant input-output line pairs. In this thesis, we have proposed a structure which constructs Reversible Programmable Array Logic (RPAL).An algorithm has been proposed to reduce total number of gates, garbage outputs in the AND plane of a RPAL. We compare the existing AND plane with the proposed one using benchmark functions. We make the RPLA as fault tolerant. Our proposed design can realize ESOP (Exclusive Sum-of-Products) operations in terms of multi-output functions by using minimum number of gates, garbage outputs and quantum cost. In our design, we have used fault tolerant FRG (Fredkin Gate) and F2G (Feynman Double Gate) for making our RPAL Fault Tolerant. We have also proposed a non fault tolerant design for RPAL with the minimum number of gates, garbage outputs and quantum cost.