Inter-turn Fault Research Articles

Matlab sensitivity analysis toolbox: an application on faults identification in induction motors

PurposeThis paper aims to introduce the usage of sensitivity analysis (SA) for the problem of faults identification in three-phase induction motors (IMs). These motors are susceptible to different kinds of faults that should be detected in a proper time to keep the systems working in a safety environment.Design/methodology/approachOne of the effective approaches for faults identifications, which is presented in the literature, is a model-based strategy. This strategy mainly depends on using a software model to make an identification decision. Therefore, this work intends to examine the model sensitivity towards variables’ variation. The SA toolbox of Matlab R2017b package is used for this purpose since the Matlab software is a well-known environment, and it is easy for a nonstatistical person to deal with it. As a study case, open-circuit and stator inter-turn faults in the stator windings of a three-phase IM have been chosen.FindingsThe results show that the model-based strategy is considerably speed up by up to 30% when neglecting the trivial model’s parameters with the same accurate identification decision as compared with the results of this strategy without using the SA.Originality/valueThe novelty of this work is summarized in devoting the usage of SA in the field of faults identification to enhance the speed of final decision.

Incipient Interturn Short-Circuit Fault Diagnosis of Permanent Magnet Synchronous Motors Based on the Data-Driven Digital Twin Model

As the most common fault of permanent magnet synchronous motor, inter-turn short circuit fault has great harm and develops rapidly. Once it is not diagnosed in time, it will bring secondary damage to the motor system. In the process of early fault diagnosis, the harmonic of the motor often increases the difficulty of fault feature extraction. In order to improve the reliability of the system, a method for early inter-turn short circuit diagnosis of permanent magnet synchronous motors based on data-driven digital twin models is proposed in this paper. Firstly, the three-phase current residuals of the permanent magnet synchronous motor under inter-turn short circuit fault are analyzed theoretically. Secondly, the digital twin model of the target motor in healthy states is established through NARX(Nonlinear Auto-Regressive model with Exogenous Inputs) network. Finally, the early short circuit diagnosis is completed through the analysis of the three-phase current residual. The method proposed in this paper does not need fault data and can complete the diagnosis of minor faults under the condition of large harmonic and certain inherent asymmetry. It has high sensitivity and obvious fault characteristics. Theoretical derivation and experiments verify the effectiveness of the proposed method.

Advanced Fault Tolerant 3×3-Phase PM Drive With Concentric Winding for EV Application

Fault tolerant machine drive is essential for EV application to ensure uninterrupted operation during fault event. Among various fault modes, inter-turn fault is the most challenging failure for the PM drive which requires special measures to suppress the excessive fault current. In this paper, a novel concentric winding (CW) is analyzed for a 3×3-phase PM drive to restrict the turn fault current. Compared with the conventional distributed winding (DW), the two sub-coils of each phase occupy the same space angle and both align with the phase axis, and the winding factor of each coil is 0.96 which is 4% lower than the DW. Owing to the two aspects, the coil flux linkages are more effectively nullified after applying winding terminal short circuit (TSC) which indicates lower fault current. The two machines’ healthy performance as well as various fault modes’ behaviors are investigated by detailed simulation and test investigation. The results prove the CW machine has the same healthy characteristics as the DW machine, and the maximum inter-turn fault current is up to 17% lower than the counterpart. In addition, the improved turn fault current suppression capability is achieved simply by re-arranging the coil layout without introducing any extra cost.

A Novel Indicator-Based Online Diagnostics Technique of Interturn Short-Circuit Faults in Synchronous Reluctance Machines

In recent years, the adoption of Synchronous Reluctance Machine (SynRM) drives for safety-critical equipment has witnessed notorious growth. The difficulties inherent to monitoring and fault diagnostics of SynRM drives are highly prominent. Inter-turn short-circuit faults (ITSCFs) are among the failure modes which are most critical and, simultaneously, more challenging to identify, in all types of motor drives. Still, the effective diagnostic task becomes even more challenging in SynRM drives, because of the harmonic pollution and intricated control configuration. To overcome the aforementioned challenges, the current research proposes a universal and effective online diagnostics technique, based on the computation and monitoring of a relevant severity factor, defined as the ratio of the zero, negative and positive voltage symmetrical components. The Short Time Least Square Prony’s (STLSP) approach is used to implement this method online in LabVIEW environment. In addition to the wide applicability of the method, the obviation of any motor parameter’s estimation and reduced requirements regarding variables’ measurements make the proposed approach extremely advantageous for motor drives with complex control architecture and operating conditions. The experimental results demonstrate the excellent generalization capability of the proposed method, as well as high accuracy and robustness. To confirm the claims, the proposed technique is implemented on a 2.2 kW SynRM drive, tested in both healthy and faulty conditions.

An Insulation Monitoring Method for Transformer Windings Based on Electroluminescence Effect

Currently, the insulation monitoring method for transformer windings mainly monitors voltage, current, leakage inductance, leakage magnetic field, temperature, and dissolved gas in oil. However, these methods often have the disadvantages of low sensitivity, inability to locate, and slow response time. This paper presents a novel insulation monitoring method for transformer windings based on electroluminescence. In this method, electroluminescent coatings are sprayed on the sides of the blocks between pancake windings. The electric field intensity between the windings is measured according to the coating’ luminance, then the winding insulation state is monitored, and faults can be located. To verify this method, we make a transformer winding model based on the principle of capacitive voltage division. Interturn and interlayer insulation faults are simulated by changing capacitors. The results show that the method has an error of less than 3% in measuring the electric field between transformer pancake windings and is feasible for transformer winding insulation monitoring. In addition, this method also can be used for the detection of transformer winding deformation.

An Improved High-Frequency Voltage Injection Method for Interturn Short-Circuit Fault Detection in PMSMs

The inter-turn short-circuit fault (ITSCF) is a common incipient fault for the permanent magnet synchronous machine (PMSM) drive system. In recent years, the high-resolution ITSCF detection method that combines the high frequency (HF) signal injection and zero-sequence voltage measurement has been put forward. However, for the traditional HF signal injection technique, nonnegligible voltage distortion may occur when the injection frequency is close to the PWM carrier-frequency. In addition, the injected voltage varies with the operating conditions of the PMSM. These drawbacks of the traditional HF signal injection technique greatly limit the ITSCF detection performance using HF signal injection. To further improve the ITSCF detection performance, an improved HF injection scheme is proposed in this paper. In the proposed method, the six active voltage vectors are injected into the PMSM in certain orders to realize a rotating voltage injection, and the injection frequency is up to five-sixth of the PWM carrier-frequency. By employing the proposed injection method, the ITSCF detection sensitivity can be much improved. And the ITSCF detection performance is not affected by the operation conditions of the PMSMs. Finally, the simulations and experiments are carried out to verify the proposed method.

Fault Diagnosis/Separation of Surface Mounted Permanent Magnet Synchronous Machine by Current and its Homopolar Orders Analysis

Performance analysis of Surface Mounted Permanent Magnet Synchronous Machine (SM-PMSM) is investigated in this paper. The machine dynamic in both healthy and faulty cases is analyzed, where dynamic, static, and mixed eccentricities as well as inter-turn and demagnetization faults are considered by a unique model. Stator Current Signature Analysis (SCSA) is used for the fault detection, and a method is proposed for the faults diagnosis and identification. Also, a flexible Magnetic Equivalent Circuit (MEC) with adjustable accuracy is used to model saturation effect thanks to its more flexibility and shorter processing time compared to the Finite-Element Method (FEM). The Power Spectral Density (PSD) is used for the faults detection, where analysis of the homopolar orders is proposed to be able to differentiate various faults from each other. Performed validation by experimental and FEM-based results shows the effectiveness of the presented model and proposed fault detection method.

Modelling and Analysis of Inter-Turn Short-Circuit Fault of PM Machines With Parallel-Connected Coils

This paper presents a general analytical fault model in a compact matrix form for surface-mounted permanent magnet (SPM) machines with parallel-connected coils, which is useful to study the machine performance under the inter-turn short circuit (ITSC) fault. To simplify the fault model, the multiphase Clarke transformation has been proposed. In the model, the branch currents rather than the phase currents are employed as state variables to describe machine behaviours under fault. Additionally, self- and mutual-inductances are obtained by winding function approach (WFA) plus slot permeance method. The proposed analytical fault model is applied to a 3 kW 96-slot 32-pole SPM machine and validated by time-stepping FE simulations. A small scale 12-slot 4-pole SPM machine prototype has also been built to further validate the accuracy of the proposed fault model.

Modeling of Symmetrical Six-Phase Induction Machines Under Stator Faults

This paper addresses the occurrence of stator faults in six-phase induction machines, with a symmetrical winding, operating under both balanced and unbalanced supply voltage conditions. A dynamic model of the motor was developed in Matlab/Simulink environment, taking into consideration the occurrence of inter-turn short circuit faults. To validate the proposed approach, simulation results, covering the full range of operation and different fault severity levels, are compared with the motor experimental performance. The voltages and currents obtained from the simulation present a good agreement with the corresponding experimental results, demonstrating the accuracy of the proposed model

Robust Novel Indicator To Distinguish between an Inter-Turn Short Circuit Fault and Load Unbalance in PMSG

In the aim to increase the reliability of the permanent magnet synchronous generator (PMSG), this paper proposes an efficient symmetrical component-based method to detect and accurately diagnose an incipient inter-turn short circuit (ITSC) fault in the PMSG without any confusion with a load unbalance. In fact, the existence of a negative sequence voltage component in the PMSG may be due to ITSC faults or to load unbalance, which creates confusion and affects the accuracy of the fault detection. To address this issue, this paper proposes a novel robust indicator capable of distinguishing without any ambiguity, an ITSC fault from a load unbalance in the machine. Hence, the objective of this paper is to demonstrate the behavior and the effectiveness of the novel indicator able to discriminate between the two operating modes, through original thorough analytical and simulation studies, validated experimentally on a real PMSG.

Waveform dissimilarity factor-based protection for main transformers in wind farms

Current differential protection (CDP) is widely used as main protection for transformers due to its high reliability and selectivity. Owing to non-fundamental frequency current, magnetizing inrush and current transformer (CT) saturation, CDP may undergo slow operating speed when the internal fault occurs. When the external fault occurs, CDP may false operate. Furthermore, given the disadvantage of Hausdorff distance being extremely sensitive to abnormal data, a new metric that reveals the dissimilarity degree of two waveforms is presented, namely waveform dissimilarity factor (WDF). WDF has inherent immunity to abnormal data. Subsequently, WDF-based protection for main transformer is proposed herein. In order to reduce the adverse effects of magnetizing inrush and CT saturation and accurately identify internal faults, the reward and punishment mechanism is designed. The protection principle is elaborated and its operating characteristics are analyzed under various conditions. Finally, by constructing the DFIG-based wind farm, PSCAD is used to verify the advantages of the novel protection algorithm based on WDF. Its performance is widely assessed in various scenarios in detail, including magnetizing inrushes, minor and server internal faults, inter-turn fault, turn-to-ground fault, internal fault with CT saturation and external fault with CT saturation, data loss, abnormal data, and CT error. The results show that the novel protection scheme has the characteristics of fast, secure, and robust.

Electromagnetic Vibration Characteristics of Inter-Turn Short Circuits in High Frequency Transformer

As a common fault of transformer winding, inter-turn short circuits cause severe consequences, such as excessive current and serious deformation of winding. Aiming to solve the problem of inter-turn short circuit at the end-winding and middle-winding of high frequency transformers (HFT), this paper considers the electromagnetic vibration characteristics of inter-turn short circuits (interleaved winding and continuous winding) at different positions, and the HFT is established by the multi-physical field coupling principle. Coupling equations for the inter-turn short circuit, as well as electromagnetic force and sound pressure level, are established to characterize the vibration noise mechanism of inter-turn short circuits. Furthermore, the HFT equivalent model is simulated in 3D finite element method (FEM) to emulate the real transformer operation and investigate the impact of interleaved winding and continuous winding under inter-turn short circuit faults. The short-circuit current and axial flux leakage, as well as the harmonic response of vibration acceleration and sound pressure level distribution, are obtained when inter-turn short circuits occur at different positions. Finally, the results show that the electromagnetic effect of the inter-turn short circuit in end-winding is worse than it is in middle-winding. Advantages in resisting impulse current make interleaved winding superior to continuous winding in terms of vibration and noise.

PWM Harmonic-Current-Based Interturn Short-Circuit Fault Diagnosis for the Aerospace FTPMSM System Even in the Fault-Tolerant Operation Condition

This paper proposes a new PWM harmonic current based diagnostic method for the interturn short-circuit fault (ITSCF) of fault tolerant permanent magnet synchronous motor (FTPMSM) drives, which is able to detect and locate the fault phase for the system even in fault tolerant operation (FTO) condition. The ITSCF model for the H-bridge drive based FTPMSM system is firstly proposed, while the high-frequency (HF) harmonic current component and impedance are analyzed both in normal and ITSCF conditions. The PWM harmonic current based fault diagnostic approach is then proposed to confirm the fault phase, which consists of the band-pass filter, the periodic root mean square (RMS) calculator and the fault identification. The resulting fault diagnostic method has simple structure, fast fault detection, good robustness and low computational burden, which can achieve the ITSCF for the FTPMSM system both under normal and FTO conditions. The effectiveness of the ITSCF diagnostic method is verified via the six-phase FTPMSM experimental platform, which can provide a guideline for the ITSCF mitigation and FTO of the FTPMSM system.

Detection of the stator inter-turn fault using the energy feature of the wavelet coeffcients obtained through continuous wavelet transform

This research aims to investigate a fault detection method applicable to the stator part of the Brush-Less DC motor (BLDC). Indeed, it is a concern to make sure the motor is operating in a healthy mode, and in any other case, it is of great importance to detect the fault as soon as possible to prevent the further ruin of the major system. Regarding this, a sub-branch method of the Wavelet Transform (WT) analysis, named Continuous Wavelet Transform (CWT), is utilized to observe the short-circuit fault in the stator coils. Thus, a novel simulator of the BLDC motor is developed by making an interconnection between ADAMS and MATLAB in which different electrical and mechanical components are included. Therefore, a close-to-reality model of the BLDC motor is achieved, leading to a more accurate evaluation of the proposed method. An energy-type feature will be suggested to characterize the fault happening. Through acquiring the normalized energy amount for one of the Wavelet Coefficient (WC) signals, obtained by the CWT, and comparing the energy with a predefined threshold amount of energy for that signal, it is feasible to detect the stator's flawed performance. By conducting different simulations, the proposed method will be validated.

Research on Fault Diagnosis Algorithm of Ship Electric Propulsion Motor

The permanent magnet synchronous motor (PMSM) has been used in electric propulsion and other fields. However, it is prone to the stator winding inter-turn short-circuit, and if no effective measures are taken, the ship’s power system will be paralyzed. To realize intelligent diagnosis of inter-turn short circuits, this paper proposes an intelligent fault diagnosis method based on improved variational mode decomposition (VMD), multi-scale principal component analysis (PCA) feature extraction, and improved Bi-LSTM. Firstly, the stator current simulation dataset is obtained by using the mathematic model of the inter-turn short-circuit of PMSM, and the parameters of VMD are optimized by the grey wolf algorithm. Then, the data is coarse-grained to obtain multi-scale features, and the main features are selected as the sample data for fault classification by PCA. Subsequently, the Bi-LSTM neural network is used for training and analyzing the data of the sample set and the test set. Finally, the learning rate and the number of hidden-layer nodes of the Bi-LSTM are optimized by the whale algorithm to increase the diagnosis accuracy. Experimental results show that the accuracy of the proposed method for inter-turn short-circuited fault diagnosis is as high as 100%, which confirms the effectiveness of the method.

Sensitive Inter-turn Fault Detection Approach for Induction Motor Under Various Operating Conditions

Sensitive Inter-turn Fault Detection Approach for Induction Motor Under Various Operating Conditions

Fault diagnosis of inter-turn short circuit in turbogenerator rotor windings based on vibration-current signal fusion

The inter-turn short circuit of rotor winding is a common fault of turbogenerator, and fault diagnosis in the early stage is of great significance to ensure the safe and reliable operation of turbogenerator. In this paper, an inter-turn short circuit fault diagnosis model based on vibration-current fusion is proposed by using the real-time state data collected by the distributed control system (DCS) of turbogenerators. Firstly, Pearson correlation coefficient (PCC) analysis method is used to analyze the correlation characteristics between the square of generator excitation current and the shaft radial vibration when the inter-turn short circuit occurs in the rotor winding of the turbogenerator. Then, the method of cooperative gain transformation is adopted to fuse current-vibration correlation coefficient which can amplify the weak correlation between the square of the excitation current and the vibration signal during the early defect, and the residual between the measured and predicted excitation current is combined to further calculate the cooperative gain residual, and an early warning signal can be issued when cooperative gain residual exceeds threshold. Finally, the model is verified by the historical DCS data of a 600 MW large turbogenerator. The results show that the proposed model can sensitively and accurately diagnose the early defects of inter-turn short circuit in turbogenerator rotor windings and ensure the safe operation of the generator.

Online Interturn Short-Circuit Fault Diagnosis in Induction Motors Operating Under Unbalanced Supply Voltage and Load Variations, Using the STLSP Technique

It is well known that the most common reason for electrical machines breakdown is the stator windings’ fault occurrence. Indeed, this type of fault represents almost 40% of faults occurring in induction machines. One of the major causes of stator defects is the occurrence of interturn short-circuit (ITSC) faults that have critical and dangerous effects on the motor itself, as well as on the related electrical equipment. Therefore, early detection and a precise severity estimation of the occurrence of ITSC faults for all working conditions can prevent failure breakdowns and increase reliability and safety of industrial facilities. In this context, this article proposes an efficient online diagnostics method based on calculating and monitoring a pertinent severity factor defined as the ratio between the zero and positive voltage symmetrical components. The online implementation of this method is performed on a LabVIEW environment, using the short-time least square Prony's (STLSP) method. It does not need any estimation of motor parameters and it requires only voltage sensors. Several tests under healthy and faulty conditions are carried out on a three-phase 3-kW induction motor. The obtained results demonstrate the effectiveness of the proposed method for diagnosing the occurrence of ITSC faults with high reliability, fastness, and high precision, even under load variations or unbalanced supply voltage.

A Case for Micromachines in Laboratory-Based DFIG Wind Turbine Systems for Fault Studies

For laboratory-based systems, the selection of components is critical to ensure proper representation of the actual system. In past investigations, researchers made use of small-scale off-the-shelf wound rotor induction machines (WRIMs) to perform laboratory-based studies. However, there are no reports validating their applicability in comparison to using the actual machines. In this regard, this paper investigates the correlation between the dimensional parameters and the electrical asymmetry indicators for a large-scale wind generator and laboratory-based generators. For the latter, a comparison is made between using a standard small-scale off-the-shelf WRIM and a micromachine. It is shown that the harmonic frequencies in a healthy machine and those due to inherent asymmetries appear at the same positions on the stator current spectrum for the three machines. However, there is a difference in the amplitudes of these components, given their dependence on the winding factors for a specific machine. The dimensional analysis techniques used to scale down the large-scale generator into a micromachine ensure that these parameters are related. However, this is not the case for the standard small-scale WRIM. Further work demonstrates the correlation of the fault-related harmonics between the micromachine and the large-scale machine for a rotor inter-turn fault condition. Micromachines are designed to ensure that the time constants are proportional representations of the larger machine, thus providing an accurate reflection of what is expected under transient operating conditions of wind turbines. This would assist in the development of condition monitoring strategies that are suited for the actual systems in the industry.

Inter-Turn Breakdown Fault Analysis and Winding Structure Optimisation of Winding of Dry-Type Transformers in Wind Farms

To address the problem of winding turn-to-turn breakdown faults in 35 kV dry-type transformers in wind farms under overvoltage conditions, this paper establishes a simulation model based on the structural dimensions and material parameters of the transformer windings. The winding distribution parameters were calculated using the finite element method. The transient processes inside the high-voltage coil were calculated by constructing a multi-conductor transmission line model (MTL) that took into account the influence of the secondary winding. The voltage distribution of the winding was analysed for both lightning shock and extra-fast transient overvoltage conditions. The simulation results show that the maximum overvoltage between turns of the transformer winding under lightning shock is 5.282 kV; the maximum overvoltage between turns of the winding under very fast transient overvoltage is 11.6 kV, which occurs between the first 2–3 layers of the section, close to the insulation breakdown margin. On this basis, the transformer winding structure was optimised and the maximum inter-turn overvoltage after optimisation was 9.104 kV, reducing the likelihood of insulation breakdown by 24.1%. Finally, the accuracy of the winding structure optimisation simulation study was verified by testing the transformer’s impulse voltage before and after optimisation, providing a reference for the stable operation of 35 kV dry-type transformers in wind farm practical applications.