scholarly journals Diagnosis of Inter-Turn Short Circuit of Synchronous Generator Rotor Winding Based on Volterra Kernel Identification

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2524 ◽  
Author(s):  
Luo Wang ◽  
Yonggang Li ◽  
Junqing Li
Keyword(s):  
Volterra Series ◽  
Least Squares Method ◽  
Early Stage ◽  
Short Circuit ◽  
Synchronous Generator ◽  
Transfer Model ◽  
Volterra Kernel ◽  
The Time Domain ◽  
Rotor Winding ◽  
Volterra Kernel Identification

The inter-turn short circuit is a common fault in the synchronous generator. This fault is not easily detected at early stage. However, with the development of the fault, it will pose a threat to the safe operation of the generator. To detect the inter-turn short circuit of rotor winding, the feasibility of identifying the stator branch characteristics of synchronous generator during inter-turn short circuit was analyzed. In this paper, an on-line fault identification method based on Volterra kernel identification is presented. This method uses the stator branch voltage and stator unbalance branch current collected from the generator as input and output signals of the series model. Recursive batch least squares method is applied to calculate the three kernels of Volterra series. When the generator is in normal state or fault state, the Volterra kernel will change accordingly. Through the identification of the time-domain kernel of the nonlinear transfer model, the inter-turn short circuit fault of the synchronous generator is diagnosed. The correctness and effectiveness of this method is verified by using the data of fault experimental synchronous generator.

Online Detecting of Inter-Turn Short-Circuit in Generator Rotor Winding Relying on ν-SVR Machine

2021 ◽  
pp. 2150026
Author(s):  
Feng Pan ◽  
Xiansheng Guo ◽  
Shengwang Pan
Keyword(s):  
Prediction Model ◽  
Support Vector Regression ◽  
Dynamic Simulation ◽  
Short Circuit ◽  
Back Propagation ◽  
Synchronous Generator ◽  
Support Vector ◽  
Diagnosis Method ◽  
Rotor Winding ◽  
Online Detecting

To probe an accurate diagnosing approach for synchronous generator (SG) with rotor winding inter-turn short-circuit, a novel online monitoring and detecting method relying on the [Formula: see text]-support vector regression ([Formula: see text]-SVR) machine was proposed, and its effectiveness was further verified by the micro-synchronous generator dynamic simulation. Terminal voltage, active and reactive power of SG were selected as input variables for a novel prediction model based on the [Formula: see text]-SVR, and field current was selected as an output variable of the prediction model. The structures and parameters of the field current prediction model were optimized with the particle swarm optimization (PSO) algorithm and training samples, then the prediction model was established and the field current prediction got under way. By comparing the predicted field current with the corresponding online measured field current, inter-turn short-circuit of rotor winding in SG could be detected sensitively once its absolute value of the prediction relative error exceeded a specific threshold. The micro-synchronous generator dynamic simulation indicated that the proposed online detecting approach based on the [Formula: see text]-SVR machine overcame the shortage of the back-propagation (BP) diagnosis method for misdiagnosis, and its accuracy, sensitivity and threshold setting range of the diagnosis method was the most prominent among these diagnosis methods such as the BP diagnosis method, the Bayesian regularization back-propagation (BRBP) diagnosis method and the [Formula: see text]-support vector regression ([Formula: see text]-SVR) diagnosis method.

scholarly journals Application of unified microprocessor relay protection units in electrical machine diagnostics

2020 ◽  
Vol 21 (6) ◽  
pp. 93-100
Author(s):  
V. I. Polishchuk ◽  
M. V. Kritsky ◽  
D. M. Bannov ◽  
S. V. Malyshev
Keyword(s):  
Short Circuit ◽  
Asynchronous Motor ◽  
Sampling Rate ◽  
Relay Protection ◽  
Synchronous Generator ◽  
Digital Processing ◽  
Electrical Machine ◽  
Selective Determination ◽  
Rotor Winding

The article concentrates on the topical issue connected with the detection of defects in the rotor winding of electric machines. The experimental sampling and digital processing of electrical signals from controlled windings is in the basis. The authors conducted the research using two experimental units for asynchronous motor and synchronous generator, respectively. A distinctive feature of the proposed research stands is in solving the problems of digital processing and data analysis on the basis of the application of microprocessor relay protection unit BMRZ developed in Russia. The authors applied method of wavelet decomposition to select the detailing component. They also presented the results of experiments for the breakage in the short-circuit rotor of an asynchronous motor and proved that the microprocessor-based BMRZ device is capable of digitizing at a sampling rate that meets the requirements, and in conjunction with the data processing algorithms that carry out the selective determination of hard-to-detect defects, is applicable in the diagnosis of electrical machines.

Third-Order Volterra Kernel Identification Technique in Aerodynamics

2011 ◽  
Vol 52-54 ◽  
pp. 618-623
Author(s):  
Yun Hai Wang ◽  
Jing Long Han ◽  
Wei Zhou
Keyword(s):  
Nonlinear System ◽  
Volterra Series ◽  
Volterra Kernel ◽  
Third Order ◽  
Volterra Kernels ◽  
Weakly Nonlinear ◽  
The Third ◽  
Identification Technique ◽  
Volterra Kernel Identification ◽  
Identification Techniques

In this paper, we will extend a Volterra identification technique of nonlinear systems. In reality there exists a large class of weakly Nonlinear System which can be well defined by the first few kernels of the Volterra series. In general, Engineers believe that identifying high-order Volterra kernels is a big problem and hope for the advent of better identification techniques. However, with the extensive development of the Volterra kernels’ identification technique, the situation may improve. The formulas used to calculate kernels up to the third-order are given.

scholarly journals Comparative Study of Integer and Non-Integer Order Models of Synchronous Generator

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4416
Author(s):  
Szymon Racewicz ◽  
Filip Kutt ◽  
Michał Michna ◽  
Łukasz Sienkiewicz
Keyword(s):  
Time Domain ◽  
Direct Method ◽  
Short Circuit ◽  
Synchronous Generator ◽  
Equation System ◽  
Integer Order ◽  
Salient Pole ◽  
Three Phase ◽  
The Time Domain ◽  
Voltage Recovery

This article presents a comparison between integer and non-integer order modelling of a synchronous generator, in the frequency domain as well as in the time domain. The classical integer order model was compared to one containing half-order systems. The half-order systems are represented in a Park d-q axis equivalent circuit as impedances modelled by half-order transmittances. Using a direct method based on the approximation of the half-order derivatives by the Grünwald–Letnikov definition, a state-space equation system was solved. For both models, a computational program written in Matlab® software was used. For the purpose of time domain simulation, the machine models were connected to an electric load composed of an RL circuit. To validate and compare both models, simulation results of a three-phase short-circuit and a no-load voltage recovery were compared with corresponding measurements performed on a solid salient-pole synchronous generator of 125 kVA.

scholarly journals Increasing Electric Vehicles Reliability by Non-Invasive Diagnosis of Motor Winding Faults

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2510
Author(s):  
Konrad Górny ◽  
Piotr Kuwałek ◽  
Wojciech Pietrowski
Keyword(s):  
Electric Vehicles ◽  
Diagnostic Method ◽  
Induction Motors ◽  
Early Stage ◽  
Short Circuit ◽  
Damage Classification ◽  
Non Invasive ◽  
Signal Features ◽  
Empirical Wavelet Transform ◽  
Simulation Results

The article proposes a proprietary approach to the diagnosis of induction motors allowing increasing the reliability of electric vehicles. This approach makes it possible to detect damage in the form of an inter-turn short-circuit at an early stage of its occurrence. The authors of the article describe an effective diagnostic method using the extraction of diagnostic signal features using an Enhanced Empirical Wavelet Transform and an algorithm based on the method of Ensemble Bagged Trees. The article describes in detail the methodology of the carried out research, presents the method of extracting features from the diagnostic signal and describes the conclusions resulting from the research. Phase current waveforms obtained from a real object as well as simulation results based on the field-circuit model of an induction motor were used as a diagnostic signal in the research. In order to determine the accuracy of the damage classification, simple metrics such as accuracy, sensitivity, selectivity, precision as well as complex metrics weight F1 and macro F1 were used.

scholarly journals Determination of synchronous generator nonlinear model parameters based on power rejection tests using a gradient optimization algorithm

2017 ◽  
Vol 65 (4) ◽  
pp. 479-488 ◽  
Author(s):  
A. Boboń ◽  
A. Nocoń ◽  
S. Paszek ◽  
P. Pruski
Keyword(s):  
Parameter Estimation ◽  
Objective Function ◽  
Optimization Algorithm ◽  
Least Squares Method ◽  
Synchronous Generator ◽  
Operating Conditions ◽  
Model Parameters ◽  
State Variables ◽  
Starting Point ◽  
Gradient Optimization

AbstractThe paper presents a method for determining electromagnetic parameters of different synchronous generator models based on dynamic waveforms measured at power rejection. Such a test can be performed safely under normal operating conditions of a generator working in a power plant. A generator model was investigated, expressed by reactances and time constants of steady, transient, and subtransient state in the d and q axes, as well as the circuit models (type (3,3) and (2,2)) expressed by resistances and inductances of stator, excitation, and equivalent rotor damping circuits windings. All these models approximately take into account the influence of magnetic core saturation. The least squares method was used for parameter estimation. There was minimized the objective function defined as the mean square error between the measured waveforms and the waveforms calculated based on the mathematical models. A method of determining the initial values of those state variables which also depend on the searched parameters is presented. To minimize the objective function, a gradient optimization algorithm finding local minima for a selected starting point was used. To get closer to the global minimum, calculations were repeated many times, taking into account the inequality constraints for the searched parameters. The paper presents the parameter estimation results and a comparison of the waveforms measured and calculated based on the final parameters for 200 MW and 50 MW turbogenerators.

scholarly journals Research on the Time-Domain Dielectric Response of Multiple Impulse Voltage Aging Oil-Film Dielectrics

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1948
Author(s):  
Chenmeng Zhang ◽  
Kailin Zhao ◽  
Shijun Xie ◽  
Can Hu ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Time Domain ◽  
Dielectric Response ◽  
Early Stage ◽  
Debye Model ◽  
Polarization Current ◽  
Depolarization Current ◽  
Oil Film ◽  
Impulse Voltage ◽  
The Time Domain ◽  
Film Dielectric

Power capacitors suffer multiple impulse voltages during their lifetime. With the multiple impulse voltage aging, the internal insulation, oil-film dielectric may deteriorate and even fail in the early stage, which is called accumulative effect. Hence, the time-domain dielectric response of oil-film dielectric with multiple impulse voltage aging is studied in this paper. At first, the procedure of the preparation of the tested samples were introduced. Secondly, an aging platform, impulse voltage generator was built to test the accumulative effect of capacitor under multiple impulse voltage. Then, a device was used to test the time-domain dielectric response (polarization depolarization current, PDC) of oil-film dielectric in different aging states. And finally, according to the PDC data, extended Debye model and characteristic parameters were obtained by matrix pencil algorithm identification. The results indicated that with the increase of impulse voltage times, the time-domain dielectric response of oil-film dielectric changed accordingly. The polarization current curve moved up gradually, the insulation resistance decreased when subjected to the repeated impulses. In frequency domain, the frequency spectrum of tan δ changed along with the impulse accumulation aging, especially at low frequency. At last, combined with the aging mechanism of oil-film dielectric under multiple impulse voltage, the test results were discussed.

scholarly journals Analysis of Torque Ripples of an Induction Motor Taking into Account a Inter-Turn Short-Circuit in a Stator Winding

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3626 ◽  
Author(s):  
Wojciech Pietrowski ◽  
Konrad Górny
Keyword(s):  
Early Stage ◽  
Short Circuit ◽  
Torque Ripple ◽  
Drive System ◽  
Electrical Machines ◽  
Stator Winding ◽  
Permanent Magnet Synchronous Machines ◽  
Noninvasive Diagnostics ◽  
Drive Systems ◽  
Commercial Applications

Despite the increasing popularity of permanent magnet synchronous machines, induction motors (IM) are still the most frequently used electrical machines in commercial applications. Ensuring a failure-free operation of IM motivates research aimed at the development of effective methods of monitoring and diagnostic of electrical machines. The presented paper deals with diagnostics of an IM with failure of an inter-turn short-circuit in a stator winding. As this type of failure commonly does not lead immediately to exclusion of a drive system, an early stage diagnosis of inter-turn short-circuit enables preventive maintenance and reduce the costs of a whole drive system failure. In the proposed approach, the early diagnostics of IM with the inter-turn short-circuit is based on the analysis of an electromagnetic torque waveform. The research is based on an elaborated numerical field–circuit model of IM. In the presented model, the inter-turn short-circuit in the selected winding has been accounted for. As the short-circuit between the turns can occur in different locations in coils of winding, computations were carried out for various quantity of shorted turns in the winding. The performed analysis of impact of inter-turn short-circuit on torque waveforms allowed to find the correlation between the quantity of shorted turns and torque ripple level. This correlation can be used as input into the first layer of an artificial neural network in early and noninvasive diagnostics of drive systems.

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