Fault detection and diagnosis technique for a SRM drive based on a multilevel converter using a machine learning approach

Trabalho apresentado em 12th International Conference on Renewable Energy Research and Applications (ICRERA 2023), 29 augusto-1 setembro 2023, Oshawa, CanadaSRM drives based on multilevel converters is now a solution well accepted due to their interesting features like extended voltage range and capability to fault tolerance. However, one aspect that is fundamental to ensure fault tolerance or preventive maintenance is the fault detection and diagnosis of failures in power semiconductors. In this way, in this paper it is presented a new diagnostic method for the failure of those semiconductors in asymmetric neutral point clamped converters. The proposed method will be based on the development of specific patterns that are associated to each semiconductor and fault type. The procedures presented here are based on the image identification of the currents patterns in the multilevel converter that allow the identification of distinct fault type. The pattern recognition system uses visual-based efficient invariants features for continuous monitoring of multilevel converter The proposed method will be verified through several tests in which were used a simulation tool and an experimental prototype.N/

Water Pumping System Supplied by a PV Generator and with a Switched Reluctance Motor Using a Drive Based on a Multilevel Converter with Reduced Switches

Funding Information: This work was supported by national funds through the FCT—Fundação para a Ciência e a Tecnologia with reference UID/CEC/50021/2020 and UID/EEA/00066/2020. Publisher Copyright: © 2023 by the authors.Pumping systems play a fundamental role in many applications. One of the applications in which these systems are very important is to pump water. However, in the real world context, the use of renewable energies to supply this kind of system becomes essential. Thus, this paper proposes a water pumping system powered by a photovoltaic (PV) generator. In addition, due to its interesting characteristics, such low manufacturing cost, free of rare-earth elements, simple design and robustness for pumping systems, a switched reluctance motor (SRM) is used. The power electronic system to be used in the PV generator and to control the SRM consists of a DC/DC converter with a bipolar output and a multilevel converter. The adopted DC/DC converter uses only one switch, so its topology can be considered as a derivation of the combination of a Zeta converter with a buck–boost converter. Another important aspect is that this converter allows continuous input current, which is desirable for PV panels. The topology selected to control the SRM is a multilevel converter. This proposed topology was adopted with the purpose of reducing the number of power semiconductors. A maximum power point algorithm (MPPT) associated with the DC/DC converter to obtain the maximum power of the PV panels is also proposed. This MPPT will be developed based on the concept of the time derivative of the power and voltage. It will be verified that with the increase in solar irradiance, the generated power will also increase. From this particular case study, it will be verified that changes in the irradiance from 1000 W/m2 to 400 W/m2 will correspond to a change in the motor speed from 1220 rpm to 170 rpm. The characteristics and operation of the proposed system will be verified through several simulation and experimental studies.publishersversionpublishe

Incipient Fault Diagnosis of a Grid-Connected T-Type Multilevel Inverter Using Multilayer Perceptron and Walsh Transform

Publisher Copyright: © 2023 by the authors.This article deals with fault detection and the classification of incipient and intermittent open-transistor faults in grid-connected three-level T-type inverters. Normally, open-transistor detection algorithms are developed for permanent faults. Nevertheless, the difficulty to detect incipient and intermittent faults is much greater, and appropriate methods are required. This requirement is due to the fact that over time, its repetition may lead to permanent failures that may lead to irreversible degradation. Therefore, the early detection of these failures is very important to ensure the reliability of the system and avoid unscheduled stops. For diagnosing these incipient and intermittent faults, a novel method based on a Walsh transform combined with a multilayer perceptron (MLP)-based classifier is proposed in this paper. This non-classical approach of using the Walsh transform not only allows accurate detections but is also very fast. This last characteristic is very important in these applications due to their practical implementation. The proposed method includes two main steps. First, the acquired AC currents are used by the control system and processed using the Walsh transform. This results in detailed information used to potentially identify open-transistor faults. Then, such information is processed using the MLP to finally determine whether a fault is present or not. Several experiments are conducted with different types of incipient transistor faults to create a relevant dataset.publishersversionpublishe

A Fault Diagnosis Scheme Based on the Normalized Indexes of the Images eccentricity for a Multilevel Converter of a Switched Reluctance Motor Drive

Trabalho apresentado em ICRERA 2022, 18-21 setembro 2022, Istambul, TurquiaThis paper addresses the fault detection and diagnosis of a fault in the switches of the Switched Reluctance Machine (SRM) power electronic converter. Due to the advantages of using multilevel converters with these machines, a fault detection and diagnosis algorithm is proposed for this converter. The topology under consideration is the asymmetric Neutral Point Clamped (ANPC), and the algorithm was developed to detect open and short circuit faults. The proposed algorithm is based on an approach that discriminates eccentricity of the images formed by the converter voltages. This discrimination is realized through the development of normalized indexes based on the entropy theory. Besides the different fault type the algorithm is also able to detect the transistor under fault. The possibility to implement the proposed approach will be verified through simulation tests.N/

Automated Solar PV Simulation System Supported by DC–DC Power Converters

Funding Information: This work was funded by Instituto Politécnico de Lisboa, reference code: IPL/2021/ATS2SPV_ISEL. Publisher Copyright: © 2023 by the authors.Solar photovoltaic simulators are valuable tools for the design and evaluation of several components of photovoltaic systems. They can also be used for several purposes, such as educational objectives regarding operation principles, control strategies, efficiency, maintenance, and other aspects. This paper presents an automated solar photovoltaic simulation system with the capability to generate automated tests considering different parameters of solar photovoltaic panels and different operation conditions. The proposed simulator is composed of three buck-boost DC–DC power converters controlled in such a way that will behave similarly to solar photovoltaic panels. It allows to introduce additional variable loads and maximum power point tracker algorithms similar to real systems. Some converters are controlled by a DSP microcontroller connected to a single programmable logic controller which generates the automated tests. Thus, using the presented solution, it is possible to implement the I-V and P-V characteristic curves of solar photovoltaic panels and evaluate different maximum power point tracker algorithms considering different meteorological conditions and load variations, being a useful tool to teach subjects related to renewable energy sources and related applications. Several simulation results using Matlab/Simulink and experimental results are presented to validate the operation of the proposed solution. Experimental results achieve a ripple between 2% and 5% of the desired average current in MPP conditions.publishersversionpublishe

Joint practice guidelines for radionuclide lymphoscintigraphy for sentinel node localization in oral/oropharyngeal squamous cell carcinoma

Involvement of the cervical lymph nodes is the most important prognostic factor for patients with oral/oropharyngeal squamous cell carcinoma (OSCC), and the decision whether to electively treat patients with clinically negative necks remains a controversial topic. Sentinel node biopsy (SNB) provides a minimally invasive method of determining the disease status of the cervical node basin, without the need for a formal neck dissection. This technique potentially improves the accuracy of histological nodal staging and avoids over-treating three-quarters of this patient population, minimizing associated morbidity. The technique has been validated for patients with OSCC, and larger-scale studies are in progress to determine its exact role in the management of this patient population. This article was designed to outline the current best practice guidelines for the provision of SNB in patients with early-stage OSCC, and to provide a framework for the currently evolving recommendations for its use. These guidelines were prepared by a multidisciplinary surgical/nuclear medicine/pathology expert panel under the joint auspices of the European Association of Nuclear Medicine (EANM) Oncology Committee and the Sentinel European Node Trial Committee

Discutindo a educação ambiental no cotidiano escolar: desenvolvimento de projetos na escola formação inicial e continuada de professores

A presente pesquisa buscou discutir como a Educação Ambiental (EA) vem sendo trabalhada, no Ensino Fundamental e como os docentes desta escola compreendem e vem inserindo a EA no cotidiano escolar., em uma escola estadual do município de Tangará da Serra/MT, Brasil. Para tanto, realizou-se entrevistas com os professores que fazem parte de um projeto interdisciplinar de EA na escola pesquisada. Verificou-se que o projeto da escola não vem conseguindo alcançar os objetivos propostos por: desconhecimento do mesmo, pelos professores; formação deficiente dos professores, não entendimento da EA como processo de ensino-aprendizagem, falta de recursos didáticos, planejamento inadequado das atividades. A partir dessa constatação, procurou-se debater a impossibilidade de tratar do tema fora do trabalho interdisciplinar, bem como, e principalmente, a importância de um estudo mais aprofundado de EA, vinculando teoria e prática, tanto na formação docente, como em projetos escolares, a fim de fugir do tradicional vínculo “EA e ecologia, lixo e horta”.Facultad de Humanidades y Ciencias de la Educació

Hand movement recognition based on biosignal analysis

http://www.sciencedirect.com/science/article/B6V2M-4VKDGR2-1/2/17a50f88d895da79aa450c9fb260846

Fault detection in pv tracking systems using an image processing algorithm based on pca

Funding Information: Funding: This research was funded by national funds through FCT-Fundação para a Ciência e a Tecnologia, under projects UIDB/50021/2020 and UIDB/00066/2020. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Photovoltaic power plants nowadays play an important role in the context of energy generation based on renewable sources. With the purpose of obtaining maximum efficiency, the PV modules of these power plants are installed in trackers. However, the mobile structure of the trackers is subject to faults, which can compromise the desired perpendicular position between the PV modules and the brightest point in the sky. So, the diagnosis of a fault in the trackers is fundamental to ensure the maximum energy production. Approaches based on sensors and statistical methods have been researched but they are expensive and time consuming. To overcome these problems, a new method is proposed for the fault diagnosis in the trackers of the PV systems based on a machine learning approach. In this type of approach the developed method can be classified into two major categories: supervised and unsupervised. In accordance with this, to implement the desired fault diagnosis, an unsupervised method based on a new image processing algorithm to determine the PV slopes is proposed. The fault detection is obtained comparing the slopes of several modules. This algorithm is based on a new image processing approach in which principal component analysis (PCA) is used. Instead of using the PCA to reduce the data dimension, as is usual, it is proposed to use it to determine the slope of an object. The use of the proposed approach presents several benefits, namely, avoiding the use of a wide range of data and specific sensors, fast detection and reliability even with incomplete images due to reflections and other problems. Based on this algorithm, a deviation index is also proposed that will be used to discriminate the panel(s) under fault. Several test cases are used to test and validate the proposed approach. From the obtained results, it is possible to verify that the PCA can successfully be adapted and used in image processing algorithms to determine the slope of the PV modules and so effectively detect a fault in the tracker, even when there are incomplete parts of an object in the image.publishersversionpublishe