Faulty Situations Research Articles

Modified Space Vector Modulation for Cascaded H-Bridge Multilevel Inverter with Open-Circuit Power Cells

In this research, a new space vector modulation control algorithm is proposed to increase the reliability of the cascaded H-bridge multilevel inverters in case of faulty situations, where one or several power cells do not function. Methods to detect faults ensure finding open-circuit module exactly, which is fast and easy to program. By giving a detailed analysis of the impact of the faulty power cells, optimal redundant level states are chosen such that highest possible output voltage can be achieved, while the balance of the three-phase line-to-line voltage is maintained and common-mode voltage is reduced. The proposed algorithm is generalized so that it can be applied to H-bridge inverters of any level. The validity of the method is verified by numerical simulations and experiment results with an 11-level cascaded H-bridge inverter.

Comprehensive design analysis of a 3D printed sensor for readiness assessment applications

PurposeThis paper aims to develop a comprehensive model of a magnetic sensor array that will be operational for a multitude of electric components in continuous and nonintrusive condition monitoring (CM) or in readiness assessment (RA) applications.Design/methodology/approachA universal nonintrusive model of a flexible antenna array is introduced to monitor and identify failures in electric machine drives. An adjustable sensor is designed to serve as a RA for a vast range of electrical elements in a typical power system by capturing the low-frequency radiated magnetic fields.FindingsThe optimal placement of the most sensitive radiated fields from several components has been discovered in this case study, enabling the detection of healthy current flow throughout. Thereafter, the short-circuit investigation, representing faulty situations, is implemented and compared with healthy cases.Practical implicationsThis sensing technique can be used for nonintrusive CM of components that are out of reach and cannot have the sensor to be held around it such as components in offshore winds, wind energy generation and power and chemical plants.Originality/valueThe results are provided for three commonly used machines with a single sensor array with numerous settings. The three dimensional (3 D) finite element analysis is applied in the structuring of the sensor, detection of the optimum location and recognition of faults in the machines. Finally, based on the setup design, 3 D printing is used for the construction of the sensor array. Thus, the sensor array with fault detection avoids major component failures and increases system reliability/resiliency.

The Fault Tolerant Control Design of an Intensified Heat-Exchanger/Reactor Using a Two-Layer, Multiple-Model Structure.

The heat-exchanger/reactor (HEX reactor) is a kind of plug-flow chemical reactor which combines high heat transfer ability with good chemical performances. It was designed under the popular trend of process intensification in chemical engineering. Previous studies have investigated its characteristics and developed its nominal model. This paper is concerned with its fault tolerant control (FTC) applications. To avoid the difficulties and nonlinearities of this HEX reactor under chemical reactions, a two-layer, multiple-model structure is proposed for designing the FTC scheme. The first layer focuses on representing the nonlinear system with a bank of local linear models while the second layer uses model banks for approaching faulty situations. Model banks are achieved by system identification, and the corresponding controller banks are designed using model predictive control (MPC). The unscented Kalman filter (UKF) is introduced to estimate the states and form the fault detection and isolation (FDI) section. Finally, the FTC simulation and validation results are presented. The idea of a two-layer, multiple-model structure presents a general framework for FTC design of complex and highly nonlinear systems, such as the HEX reactor, whose mathematical model has been created. It implements the design process in an unusual way and is also worth trying on other cases.

Towards simultaneous localization and mapping tolerant to sensors and software faults: Application to omnidirectional mobile robot

In the last few years, simultaneous localization and mapping became an important topic of research in the robotics community. This article proposes an approach for autonomous navigation of mobile robots in faulty situations. The main objective is to extend the fault tolerance strategy to simultaneous localization and mapping in presence of sensor faults or software faults in the data fusion process. Fault detection and isolation technique is performed based on duplication–comparison method and structured residuals. The proposed fault tolerance approach is based on the extended Kalman filter for simultaneous localization and mapping when an absolute localization sensor is available. The validation of the proposed approach and the extended Kalman filter for simultaneous localization and mapping algorithm is performed from experiments employing an omnidrive mobile robot, equipped with embedded sensors, namely: wheel encoders, gyroscope, two laser rangefinders and external sensor for the absolute position (indoor global positioning system). The obtained results demonstrate the effectiveness of the proposed approach where it was found that its fault tolerance performance is based essentially on the selected residuals and the values of the fault detection thresholds to be used for the fault detection and isolation.

Prevention of maloperation of distance relay under severe stressed conditions for series compensated transmission line considering optimal placement of phasor measurement units

This study presents a new protection scheme for a series compensated transmission line, which prevents maloperation of distance relay during severe stressed conditions. The proposed method depends on the calculation of the net angular difference of positive sequence phasors of voltage and current signals acquired from phasor measurement units (PMUs). For fully observable power system network, the minimum number of PMUs required with a maximum number of system observability redundancy index has been identified by the suggested method using binary chemical reaction optimisation technique. The validity of the suggested technique has been confirmed by generating different severe stressed conditions along with faulty situations by modelling IEEE-39 bus system using RTDS/RSCAD software. The proposed technique offers effective discrimination between severe stressed conditions (symmetrical/asymmetrical power swing, load encroachment, voltage instability) and faulty situation even against wide variation in fault type, fault resistance, fault inception angle, degree of compensation and location of the series capacitor (middle or both ends). The accomplished results disclose higher discriminating capability between severe stressed conditions and faulty situation of the proposed technique in comparison with those of the several existing techniques.

Energy-Efficient Information and Communication System for Smart Meter

The objective of this work is to develop an electricity Smart Meter, allowing the bi-directional energy flow in the Low Voltage (LV) grid. The developed prototype can be deployed in a Photovoltaic (PV) micro-production installation, being able to cooperate with the Distribution System Operator (DSO) regarding remote readings and dynamic voltage control procedures, while keeping the prosumer informed about the active power, as well as odd or faulty situations (e.g., no production). To accomplish the result proposed with functionalities that are useful in the distributed energy grid, this paper offers a device that is standard compliant by using DLMS, providing specific technical information to the DSO. Additionally, it has two low power wireless communication technologies: Bluetooth Low Energy (BLE), for short range local readings and configuration by the prosumer or maintenance teams; and Sigfox, a long range low power technology, which has a permanent storage and facilitates consultation of past and current records. The latter can be accessed by an Android application from a remote location.

Comparative Study of Winding Configurations of a Five-Phase Flux-Switching PM Machine

This paper introduces a general method for determination of the most suitable winding configurations for five-phase flux-switching permanent magnet (FSPM) machines, associated with feasible stator/rotor-pole combinations. Consequently, the effect of winding configurations on the performance of a five-phase outer-rotor FSPM machine is thoroughly investigated, including non-overlapping concentrated windings (single-layer, double-layer, and multi-layer) as well as distributed winding. The electromagnetic characteristics in the low-speed region, the flux-weakening capability in the high-speed region, and the fault-tolerant capability under faulty situations are evaluated and compared in detail. This work shows that compared with the conventional single-layer or double-layer concentrated windings, the FSPM machine with multi-layer type winding exhibits lower torque ripple and losses. Meanwhile, the motor with distributed windings possesses higher torque density and larger inductance. Finally, a prototype is manufactured, and the analysis results are validated by experiments.

Fault ride-through capability of star-connected cascaded multilevel converter based hybrid energy storage system under unbalanced grid failure

This paper proposes a fault-tolerant control method for star-connected cascaded multilevel converter (CMC) based hybrid energy storage system (HESS) to enhance its fault ride-through capability under unbalanced grid failure. In this topology, battery and capacitor are used as two types of dc sources. Unbalanced grid will lead to uneven power flow among three-phase links, so it's challenging to distribute active power between different types of converter cells to perform voltage balancing control. With proposed control method, battery cells and capacitor cells respectively perform unbalanced voltage tracking and zero sequence voltage (ZSV) injection. The system can maintain dc-side voltages, allowing system to ride through faulty situations and enhance its reliability. Proposed method is implemented in the DSP and verified by a 5 MW/35 kV system based on RT-LAB HIL (hardware-in-loop) platform, experimental results validate the reliability of system has been enhanced.

Phase-to-phase fault detection method for synchronous reluctance machine using MEC method

This paper presents a novel technique for synchronous reluctance machines model (SynRMs). The model can be used in both healthy and faulty situations with phase-to-phase fault. The machine properties such as the number of poles and slots, as well as rotor and stator dimension, can be selected arbitrarily in the proposed model. Therefore, various SynRMs with selective properties can be modeled by the proposed method. Considering the nonlinear magnetic equivalent circuit, the healthy and faulty saturable machine with phase-to-phase fault between various windings is also studied. Validation is performed by finite-element method (FEM). Regarding the performed validation, very shorter processing time is obtained compared to FEM.

Voltage Ride through Control Strategy of Modular Multilevel Converter under Unbalanced Voltage Sag

This paper develops modeling and describes a control strategy for a modular multilevel converter (MMC) for grid-connected renewable energy systems. The proposed model can be used to simulate MMC activity during normal and faulty situations. Firstly, a dynamic model of a grid-connected MMC (GC-MMC), based upon the symmetrical component of voltages and currents, was designed. Then an adaptive robust control approach was established in order to follow the reference currents of the converter and stabilize the submodule (SM) capacitor voltage. The positive and negative sequences of reference currents that were given from the demanded active and reactive power during grid voltage disturbance and a normal situation were then utilized in control loops. Finally, the numerical results for the performance of the MMC throughout voltage sag conditions and the effect of uncertainties on the filter parameters during changing power demands were evaluated. The results specified that the current control strategy is more potent under voltage sag situations and able to fulfill the stability requirements of the MMC.

Fault and Noise Tolerance in the Incremental Extreme Learning Machine

The extreme learning machine (ELM) is an efficient way to build single-hidden-layer feedforward networks (SLFNs). However, its fault tolerant ability is very weak. When node noise or node failure exist in a network trained by the ELM concept, the performance of the network is greatly degraded if a countermeasure is not taken. However, this kind of countermeasure for the ELM or incremental learning is seldom reported. This paper considers the situation that a trained SLFN suffers from the coexistence of node fault and node noise. We develop two fault tolerant incremental ELM algorithms for the regression problem, namely node fault tolerant incremental ELM (NFTI-ELM) and node fault tolerant convex incremental ELM (NFTCI-ELM). The NFTI-ELM determines the output weight of the newly inserted node only. We prove that in terms of the training set mean squared error (MSE) of faulty SLFNs, the NFTI-ELM converges. Our numerical results show that the NFTI-ELM is superior to the conventional ELM and incremental ELM algorithms under faulty situations. To further improve the performance, we propose the NFTCI-ELM algorithm. It not only determines the output weight of the newly inserted node, but also updates all previously trained output weights. In terms of training set MSE of faulty SLFNs, the NFTCI-ELM converges, and it is superior to the NFTI-ELM.

Speed Estimation Based on Rotor Slot Harmonics in Multiphase Induction Machines Under Open-Phase Fault

Multiphase (i.e., with more than three phases) induction machines (MIMs) are particularly attractive for safety-critical applications, because they are able to operate under open-phase fault. On the other hand, algorithms for sensorless speed estimation are of great interest, since, e.g., they improve reliability and decrease cost and maintenance. Among these methods, the approach based on rotor slot harmonics (RSHs) is especially popular, due to advantages such as its independence from time-varying parameters (e.g., resistances and inductances). In healthy machines, usually the fundamental or any given harmonic component has ideally equal magnitude in all stator phases. The previous RSH-based techniques rely on this characteristic. Conversely, under open-phase fault there is current imbalance. Moreover, due to the postfault strategies for optimum current reference generation, such imbalance varies with the load. Thus, the existing RSH-based methods are not suitable for open-phase fault, and alternative ones should be developed. This paper addresses the sensorless speed estimation based on RSHs for MIMs under open-phase fault. The main RSHs obtained in faulty situations are studied. Then, accordingly, a speed estimation technique for MIMs under open-phase fault is developed, able to work with good accuracy despite the variable current imbalance. Finite-element and experimental results are provided.

New Fault-Tolerant Control Strategy of Five-Phase Induction Motor with Four-Phase and Three-Phase Modes of Operation

The developed torque with minimum oscillations is one of the difficulties faced when designing drive systems. High ripple torque contents result in fluctuations and acoustic noise that impact the life of a drive system. A multiphase machine can offer a better alternative to a conventional three-phase machine in faulty situations by reducing the number of interruptions in industrial operation. This paper proposes a unique fault-tolerant control strategy for a five-phase induction motor. The paper considers a variable-voltage, variable-frequency control five-phase induction motor in one- and two-phase open circuit faults. The four-phase and three-phase operation modes for these faults are utilized with a modified voltage reference signal. The suggested remedial strategy is the method for compensating a faulty open phase of the machine through a modified reference signal. A modified voltage reference signal can be efficiently executed by a carrier-based pulse width modulation (PWM) system. A test bench for the execution of the fault-tolerant control strategy of the motor drive system is presented in detail along with the experimental results.

Bad Data Detection Using Linear WLS and Sampled Values in Digital Substations

Smart Grids employ intelligent control applications that require high quality data: fast, secure, and error free. Several researchers have focused on providing techniques for low latency and secured data links for these applications. Bad data detection is however generally provided only at the central level due to limitations in legacy technologies employed in many substations. With the introduction of IEC61850 data sharing within the substation becomes more flexible and transparent allowing more sophisticated management of data quality. Hence, this paper proposes a substation level bad data detection algorithm to facilitate also these types of requirements from applications. The algorithm is based on automatically detecting the substation topology by parsing standard substation description files and online state of circuit breakers and disconnectors. By applying linear weighted least square based state estimation algorithm, bad data from failing current transformers (CT) can be detected. By conducting the verification of different types of bad data, the results show the output of bad data detection algorithm provides higher accuracy than output from both measurement and protective CT in both static and faulty situations.

Fault Tolerant Control of Internal Faults in Wind Turbine: Case Study of Gearbox Efficiency Decrease

This paper presents a method to control the rotor speed of wind turbines in presence of gearbox efficiency fault. This kind of faults happens due to lack of lubrication. It affects the dynamic of the principal shaft and thus the rotor speed. The principle of the fault tolerant control is to find a bloc that equalizes the dynamics of the healthy and faulty situations. The effectiveness decrease impacts on not only the dynamics but also the steady state value of the rotor speed. The last reason makes it mandatory to add an integral term on the steady state error to cancel the residual between the measured and operating point rotor speed. The convergence of the method is proven with respect to the rotor parameters and its effectiveness is evaluated through the rotor speed.

Real-time monitoring of a coffee roasting process with near infrared spectroscopy using multivariate statistical analysis: A feasibility study

This work proposes the use of near infrared (NIR) spectroscopy in diffuse reflectance mode and multivariate statistical process control (MSPC) based on principal component analysis (PCA) for real-time monitoring of the coffee roasting process. The main objective was the development of a MSPC methodology able to early detect disturbances to the roasting process resourcing to real-time acquisition of NIR spectra. A total of fifteen roasting batches were defined according to an experimental design to develop the MSPC models. This methodology was tested on a set of five batches where disturbances of different nature were imposed to simulate real faulty situations. Some of these batches were used to optimize the model while the remaining was used to test the methodology. A modelling strategy based on a time sliding window provided the best results in terms of distinguishing batches with and without disturbances, resourcing to typical MSPC charts: Hotelling's T2 and squared predicted error statistics. A PCA model encompassing a time window of four minutes with three principal components was able to efficiently detect all disturbances assayed. NIR spectroscopy combined with the MSPC approach proved to be an adequate auxiliary tool for coffee roasters to detect faults in a conventional roasting process in real-time.

Vision system for detection of defects in the electrical connector of electric motors: test rig and algorithms

Electric motors are used in a great number of applications. These machines are mainly composed of a rotor and a stator. Regarding induction motors, the rate of defects in the stator manufacturing process is greater than in the rotor one, due to its higher complexity. To identify these faulty situations, the most common scenario is human operators performing inspections, but they are subjected to fatigue and lack of attention. This paper presents three redundant automatic vision systems and a mechanical test rig to inspect the force-induced disconnection of the stator power cables inside the electrical connector, a common defect of electric motor parts in assembly lines. These defects are typically not detected by electric tests, since in many situations the disconnection occurs after these tests, in operation, thus characterizing a field failure of the motor. A detailed description of each software routine for implementing the proposed inspection principles is presented. The test rig components and its operation to evidence the defects are also herein described. A case study using 20 connectors of real motors was proposed for evaluating the developed system and the achieved results are discussed, showing that the system could correctly identify 100% of the defects.

AFRM: Adaptive and Fault-Tolerant Routing Method for 2D Network-on-Chip

High reliability against undesirable effects is one of the key objectives in the design for Network-on-Chip (NoC). As a result, designing reliable and efficient routing method is highly desirable. This paper presents a novel turn model called NMad-y using one and two virtual channels along the [Formula: see text]- and [Formula: see text]-dimensions, respectively, and Adaptive and Fault-tolerant Routing Method (AFRM) which is designed based on the NMad-y turn model. AFRM can effectively tolerate multiple faulty routers and links in more complicated faulty situations by the link status of neighbor routers within two hops. AFRM is able to impose the reliability of network without losing the performance of network. Simulation results show that AFRM achieves better saturation throughput (0.83% on average) than a state-of-the-art fault-tolerant routing method and maintains high reliability of more than 97.43% on average.

A comparative study of energetic model-based fault detection using HBG and COG formalisms

Summary The problem of modeling and fault detection in an electromechanical system having a graphical representation is considered. For this system's dynamics, motivated by a desire to provide a precise fault detection procedure using a unified energy-based framework, 2 energy-based graphical formalisms are presented and compared: the Hamiltonian Bond Graph and the Causal Ordering Graph. Firstly, easily calculated from the Hamiltonian Bond Graph representation covering the causal energetic paths, the energetic residual generators are systematically deduced by comparing the energy quantity in both normal and faulty situations. Secondly, the causal and structural properties of the Causal Ordering Graph tool can be used to design an observer devoted to fault detection so as to derive directly energy-based residual generators in terms of faults. To highlight the effectiveness and applicability of 2 proposed approaches, simulation results on DC motor are provided and discussed. The performances of these fault detection schemes are compared and discussed in detail with respect to existing methods.

Hybrid method for remaining useful life prediction in wind turbine systems

Abstract This paper deals with fault prognosis of wind turbine in presence of multiple faults. First, a physical model is presented and used for structural analysis, sensor placement, and clusters generation characterizing the normal operation and the relevant faulty situations. Then, each cluster is surrounded by a spherical envelope to take into account modeling and parameter uncertainties. To perform fault prognosis, the geolocation principal is used to predict the Remaining Useful Lifetime, where the Euclidean distance between normal and faulty clusters, the degradation direction and velocity are calculated. The obtained results, using real wind data, are evaluated using the Prognosis Horizon and the Relative Accuracy metrics.