Injury Failure Research Articles

Investigation of influence of winding structure on reliability of permanent magnet machines

Winding is an important part of the electrical machine and plays a key role in reliability. In this paper, the reliability of multiphase winding structure in permanent magnet machines is evaluated based on the Markov model. The mean time to failure is used to compare the reliability of different windings structure. The mean time to failure of multiphase winding is derived in terms of the underlying parameters. The mean time to failure of winding is affected by the number of phases, the winding failure rate, the fault-tolerant mechanism success probability, and the state transition success probability. The influence of the phase number, winding distribution types, multi three-phase structure, and fault-tolerant mechanism success probability on the winding reliability is investigated. The results of reliability analysis lay the foundation for the reliability design of permanent magnet machines.

The Role of Neural Networks in Predicting the Thermal Life of Electrical Machines

For a continuous mode of operation, insulating material in an electrical machine is subject to constant thermal, electrical, mechanical and environmental stresses where thermal stress is a major cause of gradual insulation deterioration, which leads to ultimate winding failure. To guarantee a satisfactory lifetime, electrical machines are designed to operate winding temperatures well below their thermal class, which results in an oversized design. Standard methods for thermal lifetime evaluation of electrical machines are based on accelerated aging tests that require several months of testing. This paper proposes an alternative approach relying on a supervised neural network that significantly shortens the time demanded by accelerated aging tests for thermal lifetime evaluation of electrical machines. The supervised neural network is based on a feedforward neural network trained with Bayesian Regularisation Backpropagation (BRP) algorithm. The network predicts the wire insulation resistance with respect to its aging time at aging temperatures of 250°C, 270°C and 290°C, which reveals a good match of prediction outcomes against the experimental findings. The mean time-to-failure at each aging temperature is extracted using the Weibull probability plot in order to compare the Arrhenius curves for both conventional and proposed method and a relative error of 0.125% is achieved in terms of their temperature indexes. In addition, the analysis shows a time saving of 1680 hours (57% time saved of experimental test procedure) when the thermal life of the insulating material is predicted using BRP neural network.

Исследование вибрационных характеристик обмоток тягового двигателя пульсирующего тока НБ-514

The purpose of the article is to study the vibration characteristics of the windings of NB-514 pulsed current traction motor to identify the causes of early failure of the pole windings in order to improve their reliability in operation. The amplitude-frequency characteristics of NB-514 pulsed current traction motor winding vibration are studied; the analog vibration signal is converted into a digital code, which follows by the signal processing by digital methods. To study vibration characteristics a test bench is created, which enables the measurement of amplitude and frequency characteristics of traction motor vibrations. The analysis of the obtained measurements has shown that there are electromechanical resonances with a high degree of q-factor of the compensating winding of NB-514 traction motor and connection points of its windings and the brush holder bus at the frequencies close to 100, 200, 400, 500 and 600 Hz.

Contribution of inrush current to mechanical failure of power transformers windings

This work presents a study regarding the contribution of inrush current to the occurrence of mechanical fatigue in windings of a power transformer and, consequently, the impact of that phenomenon on the equipment's lifetime. In order to perform the study, electromagnetic transient simulations were used to determine the inrush current in a three-phase transformer model. Then, three-dimensional simulations, based on the finite element method, were performed to determine the electromechanical stresses in the equipment windings, under the effect of the inrush current. Next, the methods of critical plans and Palmgren–Miner were applied to perform the fatigue study. From the results, the impact of inrush current on the integrity of the transformer's windings was determined, as well as, to estimate the reduction of lifespan of the equipment due to inrush occurrence. The number of inrushes needed for the total reduction of lifespan of the equipment due to mechanical fatigue was also determined. The results can be used in the transformers design stage, with the purpose of assisting the evaluation of mechanical withstand of equipment, which can minimise the possibility of failure and increase its lifespan.

Parametric Models for Wind Load Resistances of Wood-Frame Walls

The progressive failure analysis of wood-frame structures under wind loads requires the resistances of each of the components (such as roof, walls, and connections) as input. The resistance functions should be able to account for the variability in the design parameters, support, and loading conditions. This study provides parametric models to calculate the in-plane (IP) and out-of-plane (OP) wind load resistances of wood-frame walls based on finite element analysis (FEA). The finite element model (FEM) of the walls are validated against experiments from published literature, and the IP and OP failure loads of the walls are determined for different length, height, stud spacing, sheathing nail spacing, sheathing thickness, presence of drywall and opening, and different support conditions. Based on a broad set of data generated by finite element calculations, two parametric models are developed to estimate the IP and OP wind load resistances of the walls by considering all of the variable parameters in this study. The parametric models demonstrate very good agreement with the FEM generated data and the available experimental results and will be useful to facilitate progressive wind failure analysis of wood-frame structures.

Modified Rotor Flux Estimators for Stator-Fault-Tolerant Vector Controlled Induction Motor Drives

This paper deals with fault-tolerant control (FTC) of an induction motor (IM) drive. An inter-turn short circuit (ITSC) of the stator windings was taken into consideration, which is one of the most common internal faults of induction machines. The sensitivity of the classic, well-known voltage and current models to the stator winding faults was analyzed. It has been shown that these classical state variable estimators are sensitive to induction motor parameter changes during stator winding failure, which results in unstable operation of the direct field-oriented control (DFOC) drive. From a safety-critical applications point of view, it is vital to guarantee stable operation of the drive even during faults of the machine. Therefore, a new FTC system has been proposed, which consists of new modified rotor flux estimators, robust to stator winding faults. A detailed description of the proposed system is presented herein, as well as the results of simulation and experimental tests. Simulation analyses were performed using MATLAB/Simulink software. Experimental tests were carried out on the experimental test bench with a dSpace DS1103 card. The proposed solution could be applied as an alternative rotor flux estimation technique for the modern FTC drive.

A Synchronous Machine with Abnormal Damper Winding Parameters

Abstract—During the operation of synchronous explicit-pole machines, the damper winding failures can occur due to electromechanical and thermal effects on the elements upon a sudden short circuit of a stator winding, at frequent launches in the motoring mode, and at three-phase voltage unbalance. These effects can lead to damage to the contacts of rods of the damper winding with its short-circuiting rings and to the destruction of elements of the rings themselves. The defects can appear in a noticeable form only in the transient, asynchronous, and asymmetric modes. Based on a 2D analytical model of a synchronous explicit-pole machine in d, q coordinates, the rod currents and electromagnetic torque are analyzed in the asynchronous machine mode upon breakage of rods and interpole bridges near one or two poles of a damper winding. It has been concluded that the most dangerous anomaly of a damper winding is the breakage of interpole bridges near one or two poles, upon which high currents occur in rods and the electromagnetic torque is ten times higher than the nominal value.

On the Computation of Frequency-Dependent Core and Proximity Effects for Transient Analysis of Transformer Windings

Overvoltages and dielectric stresses caused by transient conditions can result in the failure of transformer windings. Adequate prediction of these conditions is generally based on the implementation of accurate computer models, which, in turn, require an accurate computation of electrical parameters. This paper analyzes the computation of frequency-dependent core and proximity losses included in the transient model of transformer windings, using the finite element method and analytical expressions. A modified formula to calculate the proximity losses is presented. The results from a frequency-domain winding model are compared with experimental measurements on a disk-type prototype winding. These results show that including the frequency-dependent proximity losses is essential to accurately reproducing the experimental results. They also show that the core losses have a modest effect on the transient response of the winding when compared with measurements.

Modeling frequency response of transformer winding to investigate the influence of RLC

<span>Frequency response measurements are used for power transformer winding failures detection. The variation between frequency responses indicate mechanical changes in the transformer winding. One method to investigate winding failures in transformer is to develop a reliable circuit model which can simulate the frequency response of an actual winding. The main reason to use the model is because it is expensive to create damages on an actual winding. This paper proposes n-stages circuit ladder network to simulate the response of a winding which has unique design. It presents a new technique to calculate the resistance, inductance and capacitance of the winding. Then, the relationship between the RLC parameters and the frequency response is studied. The winding chosen in this investigation is a single phase 33kV transformer winding. The simulated frequency response was compared with the measured response to verify the proposed model. The model can give a comprehensive understanding about the effect of RLC parameters on the frequency response.</span>

Application of Self-Organizing Neural Networks to Electrical Fault Classification in Induction Motors

Electrical winding faults, namely stator short-circuits and rotor bar damage, in total constitute around 50% of all faults of induction motors (IMs) applied in variable speed drives (VSD). In particular, the short circuits of stator windings are recognized as one of the most difficult failures to detect because their detection makes sense only at the initial stage of the damage. Well-known symptoms of stator and rotor winding failures can be visible in the stator current spectra; however, the detection and classification of motor windings faults usually require the knowledge of human experts. Nowadays, artificial intelligence methods are also used in fault recognition. This paper presents the results of experimental research on the application of the stator current symptoms of the converter-fed induction motor drive to electrical fault detection and classification using Kohonen neural networks. The experimental tests of a diagnostic setup based on a virtual measurement and data pre-processing system, designed in LabView, are described. It has been shown that the developed neural detectors and classifiers based on self-organizing Kohonen maps, trained with the instantaneous symmetrical components of the stator current spectra (ISCA), enable automatic distinguishing between the stator and rotor winding faults for supplying various voltage frequencies and load torque values.

Research of thermal performance by metallographic investigation of stator winding solder region in hydroelectric power plants

Hydroelectric power plants are the most widely used renewable energy sources all over the world. In these plants, many studies have been conducted in order to produce energy continuously and efficiently. Among these studies, predictive maintenance methods, efforts to increase power by improving cooling conditions, and improving efficiency by improving the turbine wheel. In this paper, soldering at the junctions of the stator windings in the central generators has been investigated. Traditional solder (CuZn) materials and silver alloy solders (Ag-Cu-Zn) have been investigated in terms of thermal and metallographic. Silver alloy soldering has been found to have lower electrical conductivity than conventional soldering. The winding temperatures measured on the generating generator show that silver alloy soldering is more efficient. Reducing the stator winding temperature in hydroelectric power plants allows more energy production and also reduces costs by preventing winding failures.

Assessment of failure to the stator winding of the induction motor by means of deep neural network

Due to the fact that inter-turn short-circuits are the ones of the most common causes of damage to stator of induction motors, research on their early detection is still gaining in importance. The scientific novelty in the presented article is an approach in which a decision element informing about the failure of stator of induction machine is a deep artificial neural network. In the learning process, torque waveforms subjected to a continuous wavelet transform were used. In order to classify of the stator winding failures the accelerator of artificial neural networks was used.

Short-Circuit Fault Detection Observer Design in a PMSM

This paper explores detecting interturn short-circuit (ITSC) faults in surface permanent magnet synchronous machines (SPMSM) while simultaneously estimating the (typically large) fault current to determine if operation is within thermal limits. ITSC faults are caused by electrical insulation failures in the stator windings and can lead to shorts to ground resulting in oscillations in torque, localized heating, and even fires. This paper proposes a moving horizon observer methodology for detecting such faults, the level of fault, the motor state, and a thermally sensitive parameter in SPMSM. Theoretical verification of the observability and detection of fault levels and currents is also set forth. Fault detection, fault current estimation, and parameter estimation are verified via simulation for a set of ITSC faults using noisy measurements.

Preclosure spectroscopic differences between healed and dehisced traumatic wounds.

BackgroundThe complexity and severity of traumatic wounds in military and civilian trauma demands improved wound assessment, before, during, and after treatment. Here, we explore the potential of 3 charge-coupled device (3CCD) imaging values to distinguish between traumatic wounds that heal following closure and those that fail. Previous studies demonstrate that normalized 3CCD imaging values exhibit a high correlation with oxygen saturation and allow for comparison of values between diverse clinical settings, including utilizing different equipment and lighting.MethodsWe screened 119 patients at Walter Reed National Military Medical Center and at Grady Memorial Hospital with at least one traumatic extremity wound of ≥ 75 cm2. We collected images of each wound during each débridement surgery for a total of 66 patients. An in-house written computer application selected a region of interest in the images, separated the pixel color values, calculated relative values, and normalized them. We followed patients until the enrolled wounds were surgically closed, quantifying the number of wounds that dehisced (defined as wound failure or infection requiring return to the operating room after closure) or healed.ResultsWound failure occurred in 20% (19 of 96) of traumatic wounds. Normalized intensity values for patients with wounds that healed successfully were, on average, significantly different from values for patients with wounds that failed (p ≤ 0.05). Simple thresholding models and partial least squares discriminant analysis models performed poorly. However, a hierarchical cluster analysis model created with 17 variables including 3CCD data, wound surface area, and time from injury predicts wound failure with 76.9% sensitivity, 76.5% specificity, 76.6% accuracy, and a diagnostic odds ratio of 10.8 (95% confidence interval: 2.6–45.9).ConclusionsImaging using 3CCD technology may provide a non-invasive and cost-effective method of aiding surgeons in deciding if wounds are ready for closure and could potentially decrease the number of required débridements and hospital days. The process may be automated to provide real-time feedback in the operating room and clinic. The low cost and small size of the cameras makes this technology attractive for austere and shipboard environments where space and weight are at a premium.

Wednesday, September 26, 2018 7:35 AM–9:00 AM ePosters: P110. The impact of chronic steroid and dmard therapy on atlanto-axial fusion rates in patients with rheumatoid arthritis: a multicenter review

BACKGROUND CONTEXT Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease of the immune system primarily affecting the synovial joints leading to progressive joint destruction with a 1%–2% worldwide prevalence. The cervical spine is commonly affected in patients with RA leading to atlantoaxial subluxation (AAS), basilar invagination (BI), and subaxial subluxation. These patients commonly require stabilization of their AAS requiring either Occipitocervical or C1–C2 arthrodesis. RA has historically been treated with steroid therapy and although this has been falling out of favor with the advent of disease modifying anti-rheumatic drugs (DMARDs); however, some patients are unable to wean from steroids. Although DMARDs have become increasingly popular for treatment of RA there is a growing concern that the cytotoxicity of these agents may compromise wound healing and arthrodesis. Currently there is little information available regarding surgical outcomes in patients on DMARDs. This study aims to identify patients with RA and AAS that underwent surgical intervention. We hypothesize that DMARDS and low dose steroids do not adversely affect patient outcome. PURPOSE To identify the sigficance of impact that chronic steroid and/or DMARD therapy has on RA patients underdoing posterior arthrodesis for atlanto-axial instability. STUDY DESIGN/SETTING Multicenter retrospective review. PATIENT SAMPLE Patients with the diagnosis of RA requiring surgery for atlanto-axial pathology. Patients undergoing occipital–cervical and atlanto-axial arthrodesis were included. OUTCOME MEASURES Primary outcome measure was return to the OR. METHODS This study was a multicentered retrospective review from seven hospitals. All patients with the diagnosis of RA that underwent cervical spine surgery were identified and reviewed. All patients that underwent C1–C2 or occipital–cervical fusion for treatment of AAS dating back to January 2008 were identified and included in the review. Perioperative medications were reviewed for use of steroids, DMARDs, bisphosphonates and hormone therapy. Patients were stratified among 2 groups, those that had their steroids or DMARDs held perioperatively and those that did not. End point measurement was return to the operating room (OR) for wound failure, pseudoarthrosis, infection, or other reasons. RESULTS A total of 40 patients were idenitifed for inclusion in the review. There were two patients in the cohort that required return to the OR, one for pseudoarthrosis and one for wound failure. The patient with pseudoarthrosis maintained their anti-RA medications in the perioperative period while the patient with wound failure had their anti-RA medications held in the perioperative period. There was note however of patients experiencing RA flare-ups when the anti-RA medications were held. CONCLUSIONS Our cohort demonstrated a 5% return to OR rate in RA patients undergoing surgery for atanto-axial instability. There was no demonstrable affect on outcome with respect to holding or continuing anti-RA medications in the peri-operative period in our cohort. The overall affect these medications in this patient population may be benign. However, more studies are warranted to further investigate the impact these medications have in the perioperative period and overall outcome.

ОЦЕНКА ТЕХНИЧЕСКОГО СОСТОЯНИЯ ЭЛЕКТРОМЕХАНИЧЕСКИХ СИСТЕМ С ПОМОЩЬЮ ЭНЕРГЕТИЧЕСКИХ ПОКАЗАТЕЛЕЙ

The article presents the results of evaluating technical state of electromechanical transport systems with ДК-211БМ traction electric engine. Resolution of the problem of increasing operation efficiency of land and water transport can be achieved in many respects by implementation of advanced tools of automation and control over diagnostic parameters of electromechanical systems. Reducing operating costs due to the application of energy-saving technologies in maintenance of electromechanical systems on land and water transport is one of the main requirements of the industrial scientific and technical program. Electromechanical transport systems comprise a large number of sensors and actuators located directly on production sites in operation conditions. In this regard, there appears a need to bring electromechanical systems in conformity with modern requirements of operational safety on the basis of scientifically substantiated design concepts, scientific achievements in the field of new materials, production, technologies and automation controlof technical conditions of transport systems. One of the essential tasks of building an adaptive automation control system of monitoring technical state of electromechanical systems is selection of diagnostic parameters. The selection of diagnostic parameters of control of technical state of traction electric machines is suggested to carry out using mathematical modeling of power indexes. With the help of a simulation model of electromechanical system of control over electrical DC machines type ДК-211БМ there were obtained diagnostic energy parameters of the city electromotive vehicles moving at different speeds. Application of the obtained diagnostic parameters helps to control the faults and failures in armature windings of dc electric machines of transport electromechanical systems.

Stochastic Model Predictive Fault Tolerant Control Based on Conditional Value at Risk for Wind Energy Conversion System

Wind energy has been drawing considerable attention in recent years. However, due to the random nature of wind and high failure rate of wind energy conversion systems (WECSs), how to implement fault-tolerant WECS control is becoming a significant issue. This paper addresses the fault-tolerant control problem of a WECS with a probable actuator fault. A new stochastic model predictive control (SMPC) fault-tolerant controller with the Conditional Value at Risk (CVaR) objective function is proposed in this paper. First, the Markov jump linear model is used to describe the WECS dynamics, which are affected by many stochastic factors, like the wind. The Markov jump linear model can precisely model the random WECS properties. Second, the scenario-based SMPC is used as the controller to address the control problem of the WECS. With this controller, all the possible realizations of the disturbance in prediction horizon are enumerated by scenario trees so that an uncertain SMPC problem can be transformed into a deterministic model predictive control (MPC) problem. Finally, the CVaR object function is adopted to improve the fault-tolerant control performance of the SMPC controller. CVaR can provide a balance between the performance and random failure risks of the system. The Min-Max performance index is introduced to compare the fault-tolerant control performance with the proposed controller. The comparison results show that the proposed method has better fault-tolerant control performance.

Experience With Online Partial-Discharge Measurement in High-Voltage Inverter-Fed Motors

Partial-discharge (PD) testing has long been an important tool for assessing the condition of the high-voltage insulation in motor and generator stator windings. In the past several years, many motors have been powered from inverters, which facilitate variable-speed motor operation. The most common drive used today is the voltage-source pulse-width modulation (VS-PWM) type. VS-PWM drives rated up to 13.8 kV are becoming more common in natural gas processing plants, as well as in other petrochemical facilities. Such drives generate high-voltage impulses in the kilovolt range with rise times in the submicrosecond range. These impulses are a form of severe electrical interference that can make difficult the online detection of PD (with magnitudes 1000 times smaller) due to the overlapping frequency content in PD and in the impulses. Thus, PD detection on medium-voltage VS-PWM systems has been a challenge in spite of the serious stator winding insulation aging that such drives may cause to these motors. This paper discusses the stator winding failure mechanisms that produce PD, including the insulation problems that VS-PWM drives can accelerate. A research project that lasted several years is reviewed. This project culminated in a prototype online PD monitoring system suitable for motors fed by VS-PWM drives.

Hybrid Electric Vehicle Fault Tolerant Control

This paper investigates the supervisory-level, fault tolerant control of a 2004 Prius powertrain. The fault considered is an interturn short circuit (ITSC) fault in the traction drive (a surface mount permanent magnet synchronous machine (SPMSM) for which its rotor is part of the vehicle's driveline). ITSC faults arise from electrical insulation failures in the stator windings where part of a phase winding remains functional while the remaining decoupled windings form a self-contained loop. Because the permanent magnets on the rotor (driveline) shaft are able to induce very large eddy currents in this self-contained loop if its rotational velocity is left unchecked, the maximum allowable driveline speed, and consequently, vehicle speed, must be reduced to avoid exceeding the drive's operational thermal limits. A method for detecting these ITSC faults and the induced eddy current in an SPMSM using a moving horizon observer (MHO) is reviewed. These parameters then determine which previously computed, fault-level-dependent SPMSM input–output power efficiency map and maximum safe operating speed is utilized by the supervisory-level controller. The fault tolerant control is demonstrated by simulating a Prius over a 40 s drive velocity profile with fault levels of 0.5%, 1%, 2%, and 5% detected at the midpoint of the profile. For comparison, the Prius is also simulated without a traction motor fault. Results show that the control reduces vehicle velocity upon detection of a fault to an appropriate safe value.

Modeling of Transformer Windings for Fast Transient Studies: Experimental Validation and Performance Comparison

Fast front pulses from lightning and switching conditions produce transient overvoltages and dielectric stresses that can result in premature deterioration or failure of transformer windings. Predicting these conditions in new transformer designs requires the implementation of internal winding models. This paper analyzes the accuracy and performance of different transformer winding models available in the literature, by means of comparisons with time- and frequency-domain measurements on a 2000-turns disk-type winding prototype, as well as evaluation of the computer time needed by each model to perform the corresponding simulation of the same prototype. The results show that including the frequency dependence of the model parameters is a decisive factor to accurately reproduce the measurements. They also show that a lumped parameter model described in a turn-by-turn basis can provide accurate results and requires shorter simulation time than a distributed parameter model.