Sharif Digital Repository

Detection and isolation of faults in the exhaust gas path of a turbocharged spark ignition (SI) engine is an essential part of the engine control unit (ECU) strategies to minimize exhaust emission and ensure safe operation of a turbocharger. This paper proposes a novel physics-based strategy to detect and isolate an exhaust manifold leakage and a closed-stuck wastegate fault. The strategy is based on a globally optimal parameter estimation algorithm which detects an effective hole area in the exhaust manifold. The estimation algorithm requires prediction of the exhaust manifold's input and output flows. The input flow is predicted by a nonlinear Luenberger observer which is analytically... 

Fault diagnosis following a disturbance in a power system is of great importance for the operators in the control center as a prerequisite for system restoration. In this article, for the first time, an analytic method for fault diagnosis, using the wide area measurement system (WAMS) and employing circuit rules, is developed. Instead of conventional information about status of protective relays and circuit breakers, voltage and current phasors at different points of the power network after fault occurrence are utilized. Because most of the power systems will be equipped with WAMS consisting of high-speed sampling features, the proposed method introduces a new application of WAMS for fault... 

While the importance of wide area measurement system (WAMS) consisting of phasor measurement units (PMUs) is recognized, there are still unidentified applications that can be addressed with the advance of technology. Traditionally, power system operators diagnosed the fault point through the status of protective relays and circuit breakers of the protection system. In large blackouts, however, the malfunction of protection system has itself often been among the suspects of the disaster. This paper proposes an alternative fault diagnosis approach independent of the function of protection system, utilizing PMU data and bus impedance matrix (Zbus). First, the proposed method diagnoses the fault... 

This paper introduces a novel approach for power system fault diagnosis based on synchronized phasor measurements during the fault. The synchronized measurements are obtained in real time from Phasor Measurement Units (PMUs) and compared with offline thresholds determined by decision trees (DTs) to diagnose the fault. The DTs have already been trained offline using detailed power system analysis for different fault cases. While the traditional methods for fault diagnosis use the status of protective relays (PRs) and circuit breakers (CBs) to infer the fault section in the power system, the proposed method uses the available signals following the fault and thus can be trusted even in case of... 

Journal-bearings play a significant role in industrial applications and the necessity of condition monitoring with nondestructive tests is increasing. This paper deals a proper fault detection technique based on power spectral density (PSD) of vibration signals in combination with K-Nearest Neighbor and Support Vector Machine (SVM). The frequency domain vibration signals of an internal combustion engine with three journal-bearing conditions were gained, corresponding to, (i) normal, (ii) corrosion and (iii) excessive wear. The features of the PSD values of vibration signals were extracted using statistical and vibration parameters. The extracted features were used as inputs to the KNN and... 

Design and development of fault diagnosis schemes (FDS) for electric power distribution systems are major steps in realizing the self-healing function of a smart distribution grid. The application of the FDS in the electric power distribution systems is mainly aimed at precise detecting and locating of the deteriorated components, thereby enhancing the quality and reliability of the electric power delivered to the customers. The impacts of two types of the FDS on distribution system reliability are compared and presented in this paper. The first type is a representative of the FDS which diagnoses the deteriorated components after their failing. However, the second type is a representative of... 

Transfer function (TF) is an acknowledged method for power transformer mechanical faults detection. However the past published works mostly discovered how to specify the faults levels and paid less attention to detection of the type of faults using comparison of TFs. whereas, it seems important for most of the applications to specify the type of fault without opening the unit. This paper presents a new method based on vector fitting (VF) to compare the TFs and specify the type, level and location of the fault. For development of the method, and its verification the required measurements are carried out on four model transformers; under intact condition, and under different fault conditions... 

Most multivariate quality control procedures evaluate the in-control or out-of-control condition based upon an overall statistic, like Hotelling's T2. Although T2 is optimal for finding a general shift in mean vectors, it is not optimal for shifts that occur for some subset of variables. This introduces a persistent problem in multivariate control charts, namely the interpretation of a signal that often discourages practitioners in applying them. In this paper, we propose an artificial neural network based model to diagnose faults in out-of-control conditions and to help identify aberrant variables when Shewhart-type multivariate control charts based on Hotelling's T2 are used. The results... 

Changes in the physicochemical conditions of process unit, even under control, may lead to what are generically referred to as faults. The cognition of causes is very important, because the system can be diagnosed and fault tolerated. In this article, we discuss and propose an artificial neural network that can detect the incipient and gradual faults either individually or mutually. The main feature of the proposed network is including the fault patterns in the input space. The scheme is examined through a sample unit with five probable occurring faults. The simulation results indicate that the proposed algorithm can detect both single and two simultaneous faults properly