<p>The main topic of this licentiate thesis is fast faultdetection. The thesis summaries the work performed in theproject“Fast fault detection for distributionsystems”.</p><p>In the first chapters of the thesis the term“fast”is used in a general manner. The term is laterdefined based upon considerations and conclusions made in thefirst chapters and then related to a specific time.</p><p>To be able to understand and appreciate why fast faultdetection is necessary, power system faults and theirconsequences are briefly discussed. The consequences of a faultare dependent of a number of different factors, one of thefactors being the duration of the fault.</p><p>The importance of the speed of the fault detection dependson the type of equipment used to clear the fault. A circuitbreaker which interrupt currents only when they pass through anatural zero crossing might be less dependent on the speed ofthe fault detection than a fault current limiter which limitsthe fault current before it has reached its first prospectivecurrent peak.</p><p>In order to be able to detect a fault in a power system, thepower system must be observed, i.e., measurements of relevantquantities must be performed so that the fault detectionequipment can obtain information of the state of the system.The fault detection equipment and some general methods of faultdetection are briefly described.</p><p>Some algorithms and their possible adaptation to fast faultdetection are described. A common principle of many algorithmsare that they assume that either a signal or the power systemobject can be described by a model. Sampled data values arethen fitted to the model so that an estimate of relevantparameters needed for fault detection is obtained. An algorithmwhich do not fit samples to a model but use instantaneouscurrent values for fault detection is also described andevaluated.</p><p>Since the exact state of a power system never is known dueto variations in power production and load, a model of thepower system or of the signal can never be perfect, i.e., theestimated parameter can never be truly correct. Furthermore,errors from the data acquisition system contribute to the totalerror of the estimated parameter.</p><p>Two case studies are used to study the performance of the(modified) algorithms. For those studies it has been shown thatthe algorithms can detect a fault within approximately 1msafter fault inception and that one of the algorithms candiscriminate between a fault and two types of common powersystem transients (capacitor and transformer energization).</p><p>The second case study introduced a system with two sourceswhich required a directional algorithm to discriminate betweenfaults inside or outside the protection zone.</p><p>It is concluded that under certain assumptions it ispossible to detect power system faults within approximately 1msand that it is possible to discriminate a power system faultfrom power system transient that regularly occurs within powersystems but which not are faults.</p>

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

In-service performance deterioration of gas turbine engines can be identified, at the engine module level, in terms of reductions in the component mass flow and the efficiency. Continued operation of a deteriorated gas turbine is (i) uneconomical and (ii) unsafe. Timely identification of the faults and ensuing maintenance could prevent both. Gas Path Analysis is a technique to establish the current performance level of the gas turbines and identify the faulty modules. Computer models can predict the off_design performance of gas turbines by aero-thermo-dynamically matching the engine components. This thesis describes the development of DETEM (DEeteriorated Turbine Engine Model), a generalised computer program, developed to model degraded gas turbine engines and analyse faults. The program has an integrated graphics module and creates windows on the VDU terminal,for displaying the program output and accepting the user input. This enables the user to compare the results of two different types of runs at the same time. The program incorporates sensor models that modify the output, with noise and in bias, based on the sensor characteristics, thus simulating a real engine. It is possible to simulate the engine performance at design point, off-design and under transient conditions. The runs could be for a &quot;clean&quot; and a deteriorated engine. Three techniques, iterative, fault coefficient matrix, and a statistical best-estimation technique, have been used to analyse the engine performance and identify the fault. Analysis of two and three shaft turbo-shaft engines and two spool turbo-fan and turbo-jet engines have been worked out in the thesis. Effects of reducing the number of measurements and measuring different engine parameters, on the accuracy of the fault identification, have been studied. The program is considered to have a potential for the generation of fault trees for rule-based expert system applied to gas turbine diagnostics. Because of the controlled output to the screen, a direct comparison of two different runs side by side, on the same screen, makes the program a good teaching aid for gas turbine diagnostics.

From the early days of programming, the dependability of software has been a concern. The development of distributed systems that must respond in real-time and continue to function correctly in spite of hardware failure have increased the concern while making the task of ensuring dependability more complex. This dissertation presents a technique for improving confidence in software designed to execute on a distributed system of fail-stop processors. The methodology presented is based on a temporal logic augmented with time intervals and probability distributions. A temporal logic augmented with time intervals, Bounded Time Temporal Logic (BTTL), supports the specification and verification of real-time properties such as, "The program will poll the sensor every t to T time units." Analogously, a temporal logic augmented with probability distributions, Probabilistic Bounded Time Temporal Logic (PBTTL), supports reasoning about fault-tolerant properties such as, "The program will complete with probability less than or equal to p", and a combination of these properties such as, "The program will complete within t and T time units with probability less than or equal to p." The syntax and semantics of the two logics, BTTL and PBTTL, are carefully developed. This includes development of a program state model, state transition model, message passing system model and failure system model. An axiomatic program model is then presented and used for the development of a set of inference rules. The inference rules are designed to simplify use of the logic for reasoning about typical programming language constructs and commonly occurring programming scenarios. In addition to offering a systematic approach for verifying typical behaviors, the inference rules are intended to support the derivation of formulas expressing timing and probabilistic relationships between the execution times and probabilities of individual statements, groups of statements, message passing and failure recovery. Use of the methodology is demonstrated in examples of varying complexity, including five real-time examples and four combined real-time and fault-tolerant examples.

No description available.