Faults In Synchronous Generators Research Articles

Electromagnetic Signal Analysis for Electrical Fault Diagnosis in Synchronous Generators

This study investigates the enhancement of fault diagnostics in synchronous generators by incorporating electromagnetic signal analysis with conventional diagnostic methodologies. The critical role of synchronous generators in maintaining power system stability and efficiency in industrial and power plant environments is underscored. Finite element modeling (FEM) is employed to simulate various fault conditions, such as stator and rotor winding faults. This study proposes a method that integrates stator current and stray magnetic flux analysis to identify five distinct types of short-circuit faults in stator and rotor windings, thereby enhancing the diagnostic capabilities for electrical faults in synchronous generators. This approach successfully identifies these electrical faults using non-invasive methods, offering a cost-effective solution that enhances fault detection. These findings are based on simulation results and serve as a preliminary stage for further validation through experimental studies. This integration is crucial for the development of efficient diagnostic systems that are capable of adapting to complex fault patterns, reducing human intervention, and streamlining maintenance operations, thus improving the reliability of synchronous generators globally.

Application of an Artificial Neural Network for Detecting, Classifying, and Making Decisions about Asymmetric Short Circuits in a Synchronous Generator

Fast and accurate detection of emerging faults in synchronous generators, which have found wide application in power and transport systems, contributes to ensuring reliable operation of the entire system. This article presents a new approach to making accurate decisions on the continuation of the operation of damaged generators in accordance with the requirements of IEEE standards. The necessity of limiting the duration of operation of the generator in conditions of asymmetric short circuits in the stator windings is substantiated. The authors of the article, based on an artificial neural network in the Matlab software environment, have developed a model for detecting, classifying, and making quick and accurate decisions about the operation of the generator in the event of asymmetric short circuits in the stator windings of the generator. This makes it possible to simulate the operation of the generator at various parameters. Prior to training the neural network, the database formed by phase current and voltage signals was analyzed by various features. The neural network was trained using the back-error-propagation algorithm. The output 10 neurons of the network showed the state of the phase windings of the stator. The recorded information of the output neurons was evaluated, in terms of meeting the requirements of the IEEE standard, and decisions were made about continuing or interrupting the generator operation. Tests of the effectiveness of the model showed that it could achieve the desired result at step 49, and the calculated accuracy was 99.5833%. The results obtained can be successfully used in the development of high-speed and highly reliable diagnostic systems and control and decision-making systems for generators for various purposes.

Equipment for Monitoring Synchronous Generators Condition through External Magnetic Field Waveforms

This paper presents an equipment for monitoring synchronous generators condition through characteristics of the time derivative of the external magnetic field. The developed monitoring methodology allows the identification of established or incipient faults, by detecting changes in the magnetic signature of the synchronous generator. In this methodology, the measurement of signals outside the machine gives this equipment a non-invasive characteristic, allowing its monitoring without interfering or disturbing its operation. The developed system includes the specification of magnetic field sensors, signal measurement and processing equipment, as well as software for analysis and monitoring. The validation of the methodology used in this system was carried out through the analysis of experimental data, presenting efficient results in the detection of electrical and mechanical faults in synchronous generators of an experimental test bench and a hydroelectric power plant. As a result, the commercial specification of this equipment was obtained and two units were implemented in a hydroelectric power plant to monitor 305 MVA synchronous generators.

Online Airgap Flux Based Diagnosis of Rotor Eccentricity and Field Winding Turn Insulation Faults in Synchronous Generators

Rotor faults in a synchronous generator severely deteriorate its performance, reducing the operation efficiency and reliability. Most of the field-wide accepted methods require stoppage of generator operation and disassembly, and online diagnosis of rotor faults is difficult due to the lack of dependable online methods for sensitive rotor fault detection. Therefore, online methods that can reliably and unambiguously detect rotor field winding and eccentricity faults before they lead to machine failure are required. This paper presents a new method for detecting and distinguishing rotor field winding insulation and eccentricity faults online during synchronous generator operation based on measurements from airgap flux probes, which are installed in most synchronous generators used for electric power generation. A non-complex, time domain analysis method is proposed which makes use of the voltage induced in the airgap flux sensor for a reliable prediction of the presence and identification of rotor field winding turn insulation failure and rotor dynamic eccentricity. The method is tested and verified experimentally on a 5 hp synchronous generator and on measurements from a 330 MW pumped storage generator.

A Hybrid Method to Diagnose 3D Rotor Eccentricity Faults in Synchronous Generators Based on ALIF_PE and KFCM

This paper proposed a new hybrid diagnosis method for the generator’s 3D static eccentricity faults which include the axial eccentricity, the radial eccentricity, and the mixed eccentricity composed of the former two. Firstly, adaptive local iterative filtering (ALIF) method was used to decompose the vibration signals of the generator under eccentricity faults. Then, in order to figure out the intrinsic mode function (IMF) components with the upmost feature information, the correlation coefficient was calculated. Finally, the components’ permutation entropy (PE) is extracted to construct the eigenvector matrix which can be used to input the kernel fuzzy C-means (KFCM) algorithm to obtain the result of clustering. The result indicates that the classification coefficient based on ALIF and KFCM behaves closer to 1, while the average fuzzy entropy (FE) is closer to 0, showing that this method is able to detect different eccentricity faults more accurately.

Turn to Turn Fault Detection, Discrimination, and Faulty Region Identification in the Stator and Rotor Windings of Synchronous Machines Based on the Rotational Magnetic Field Distortion

A flux-based technique is proposed for the on-line detection, localization and discrimination of stator and rotor turn-to-turn faults in synchronous generators, using the measured air-gap rotational magnetic field. Simple magnetic field sensors (MFSs) are installed in the stator slots at different regions, and the corresponding induced voltages are measured. Several differential voltages are then obtained to give a picture of the rotational magnetic field symmetricity, whose distortions indicate the presence of the stator or rotor faults. The proposed diagnostic technique is presented in detail and validated initially by simulation results obtained with a finite element simulation package and afterwards through the experimental tests. The obtained results demonstrate that the proposed technique can be used to detect and discriminate stator and rotor turn-to-turn faults with appropriate sensitivity. In addition, the region of the stator turn-to-turn faults can be identified as well.

Enhanced ANN with Ant Lion Optimization for Diagnose the Incipient Faults of Synchronous Generator

Enhanced ANN with Ant Lion Optimization for Diagnose the Incipient Faults of Synchronous Generator

DWT with Enhanced ANN Technique for Detecting and Classifying the Faults of Synchronous Generator

In the paper, a hybrid technique based fault detector algorithm for synchronous generator is proposed. The hybrid technique is the combination of Artificial Neural Network (ANN) and Gravitational Search Algorithm (GSA). The GSA is used to train the ANN and improve the performance of ANN. Initially, the synchronous generator is analyzed in the normal condition. After that, the fault is created in the synchronous generator and the system behaviors are monitored and signals are measured which can be seen as distorted waveforms. These distorted waveforms are composed of different frequency components and which are needed to be represented in time- frequency domain for fault analysis. For this representation of signal, discrete wavelet transform (DWT) is presented. It extracts the features and forms the datasets which are forwarded to ANN classifier for classifying the type of fault occurred in the stator winding of the synchronous generator. In order to evaluate the effectiveness of the proposed method, the internal faults are analyzed. The proposed technique is implemented in MATLAB/simulink platform and this is validated using statistical measures such as accuracy, sensitivity & specificity. The proposed method is compared with the existing techniques DWT-ANN with GA and DWT-ANN methods.

A Novel Method Based on Fuzzy Logic and Data Mining for Synchronous Generator Digital Protection

A new internal fault protection scheme for synchronous generators, based on the fuzzy inference system, is proposed. The proposed method is developed and tested by using an oscillogram dataset gathered from fault simulations and experiments conducted on real-life synchronous generators. Data mining is used to support the choice of the most relevant variables to identify synchronous generator internal faults. The selected variables are used as inputs to a fuzzy–logic system designed to identify and detect faults. A part of the oscillogram dataset is used to demonstrate the effectiveness of the proposed protection. The results show that the proposed protection scheme is more sensitive in detecting ground faults in synchronous generators with high-impedance grounding compared to conventional devices. It is also shown that the proposed scheme is able to identify interturns and interpath faults. The proposed method was embedded in a PC104 processor and tested in a real-time environment to show its practical feasibility.

Synchronous generator stator protection using a fuzzy logic-based voltage-controlled overcurrent protection scheme

Summary The most common protection scheme for synchronous generators against stator windings fault is the differential protection scheme. In this paper, a new voltage-controlled overcurrent protection scheme is proposed as a backup protection method for the differential protection method. This scheme is designed to operate in conditions in which differential protection fails to do so and is implemented by fuzzy controllers. The fuzzy controllers set the plug setting of the overcurrent relay. In the proposed method, the fault conditions can be determined regardless of variations of voltage and the current of terminal in different operating states of the synchronous generator. This is realized by measuring not only the terminal voltages and currents of the generator, which are usually used in conventional voltage-controlled overcurrent protection schemes but also other variables that promote the accuracy of the proposed scheme. For presenting this protection method, a synchronous generator with internal fault model is used. The fault model is based on the direct-phase representation that uses the conventional and readily available machine data. Simulations for various types of stator faults of synchronous generator validate the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.

A Synchronous Generator Internal Fault Model Based on the Voltage-Behind-Reactance Representation

An internal fault in a synchronous generator produces an effect similar to increasing the number of grouped coils in the stator winding, making it necessary to use additional time-variant inductances to represent the condition, with the ensuing increase in modeling complexity and computation time required for its solution. In this paper, a new model for the simulation of internal faults in synchronous generators is presented. The model is based on the so-called voltage-behind-reactance (VBR) representation, a contemporary reference frame, which has proved to be numerically more efficient than the classical phase-domain model used to study internal faults in synchronous generators; making it a better fit for large-scale, multimachine power systems applications, the long-term objective of this research work. An implementation for electromagnetic transients program (EMTP) type solutions is presented together with a test case where internal faults are applied, producing results that are in close agreement with results available in the open literature. Furthermore, an external perturbation is also carried out and results match exactly those produced by an equivalent VBR implementation.

Modeling and Real-Time Simulation of Internal Faults in Synchronous Generators With Parallel-Connected Windings

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In large synchronous generators, the stator windings are usually parallel-connected in order to increase the machine current capacity. In analysis and modeling, the parallel windings are usually lumped into one equivalent stator winding since equal currents flow in these windings. However, when an internal fault occurs in the windings, the symmetry between the parallel windings is broken and different currents will flow in the parallel windings since unsymmetrical magnetic linkage may exist between the stator windings. The aim of this paper is to present a simulation model to investigate the internal fault currents of large synchronous generators with parallel-connected windings. This model is based on a modified winding function theory that takes into account all space harmonics. Moreover, the calculation of the machine inductances is made easier by the use of the machine electrical parameters instead of the geometrical ones. The simulation results illustrate the existence of different currents in parallel windings in the case of internal faults. Results are given for an implementation of the internal fault model in a real-time simulator of large power networks. </para>

Wavelet Transform Based Protection of Stator Faults in Synchronous Generators

This article presents a novel wavelet power based algorithm for protection of stator windings of a three-phase synchronous generator. The proposed algorithm is based on the comparison of the instantaneous power of the wavelet packet transform coefficients of voltage and current samples of different faulted and normal conditions acquired from the terminals of the generator. The wavelet powers of the second level high frequency details of fault currents and voltages using a selected mother wavelet show distinctive features between different faulted and normal conditions. The proposed wavelet power based detection algorithm is developed and implemented in real-time using the ds1102 digital signal processor board. The protection technique is tested on-line on a laboratory 1.6 kW three-phase synchronous generator. Different types of stator faults at generator terminals for testing the technique in real-time, faults were identified promptly and properly, and the trip signal was initiated almost at the instant or within one cycle of fault occurrence.

Simulation of internal faults in synchronous generators

An internal fault in the armature winding of a synchronous generator occurs due to the breakdown of the winding insulation. In this paper, a method for simulating internal faults in synchronous generators, using direct phase quantities, is described. Simulation results showing the fault currents, during a single phase to ground fault and a two phase to ground fault, are presented.

Synchronous generator internal fault computation and experimental verification

Along with the development of electric power industry, accurate analysis of faulted generators becomes more and more important. The paper presents a method for simulating internal faults in synchronous generators, consisting of a single path per phase, using direct phase quantities. Simulation results showing the fault currents, during single phase to ground faults and two phase to ground faults, are compared with actual fault currents to verify the proposed method.

Analysis of asymmetrical faults in synchronous generators by d-q-0 frame of reference

The paper describes the development of a mathematical model in the d-q-0 frame of reference for the analysis of unbalanced operation of synchronous machines. The equations for faults between two phases and between one line and the generator neutral are described. The solution of the equations of the model by digital computer is presented. Initially, the model neglects nonlinearities and subtransients in the synchronous generator. The validity of the method of analysis developed is examined by comparing the computed results with the test results for a 7 MW generator and a 50 MW generator.