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    Wyświetlanie 1-11 z 11
    Tytuł:
    Faults detection based on fuzzy concepts for vibrations monitoring in gas turbine
    Autorzy:
    Alili, Bachir
    Hafaifa, Ahmed
    Iratni, Abdelhamid
    Powiązania:
    https://bibliotekanauki.pl/articles/327804.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    faults detection
    fuzzy logic
    decision making
    vibration monitoring
    gas turbines
    turbina gazowa
    logika rozmyta
    wykrywanie uszkodzeń
    podejmowanie decyzji
    monitorowanie drgań
    Opis:
    The use of new technologies in modern industry improves productivity but induces complexity in the industrial system. This complexity makes it vulnerable to faults, which requires significant expense in terms of safety, reliability and availability. Indeed, a diagnostic operation is essential for the operational safety and availability of these industrial systems. This diagnostic operation is based on two important functions which are the detection and localization of anomalies, which consists to verifying the consistency of the data taken in real time from the installation with a reliable model, to ensure the good performance of the monitoring system. Hence, the diagnosis of gas turbines is a main component for making maintenance decisions for this type of machine. In this paper, the faults detection approach based on fuzzy logic is applied for the vibrations monitoring of a gas turbine, in order to monitor their operating state by including the detection and occurrence of vibration faults, thus using determined fault indicators based on the input/output variables of the examined gas turbine. In this work, the investigation results of fuzzy fault detection approach applied on gas turbine vibration are presented, based on the actual data recorded in the different gas turbine operating modes. However, analysis of the defect detection results was performed in order to determine the influence of these vibration defects on the deferent operating modes of the examined machine. This makes it possible to find the causes of failures and then to deduce the actions to follow the operational safety of the examined turbine.
    Źródło:
    Diagnostyka; 2020, 21, 4; 67-77
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    DWT-PSD extraction feature for defect diagnosis of small wind generator
    Autorzy:
    Noureddine, Lahcène
    Noureddine, Mustapha
    Hafaifa, Ahmed
    Kouzou, Abdellah
    Powiązania:
    https://bibliotekanauki.pl/articles/327498.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    discrete wavelet transform
    BRB defects diagnosis
    PSD estimation
    renewable energy system
    dyskretna transformacja falkowa
    diagnostyka
    wykrywanie defektów
    energia odnawialna
    Opis:
    In this paper, the ability to detect broken rotor bar (BRB) defects in a small renewable energy system (based on a squirrel cage induction generator (SCIG)) by the digital signal processing of captured phase currents, is presented. The new approach proposed in this study is a combination of two techniques. The first technique is a discrete wavelet transform (DWT) by the decomposition of the phase current signal in multilevel frequency bands. This is performed with the analysis of some selected approximations and/or details, which contain both the lower and upper sideband components presenting the characteristic frequency of the BRB fault. The second technique is power spectral density (PSD) analysis. This approach provides the ability to optimize the diagnosis of rotor defects in electrical generators. The results obtained by the proposed DWT-PSD approach are proved and improved by comparing them with the results of the PSD analysis, obtained from the original phase current signal delivered by the 5.7-kW squirrel cage induction generator, based on a small wind energy conversion system.
    Źródło:
    Diagnostyka; 2019, 20, 3; 45-52
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Monitoring and control of energy management system for fuel cell hybrid in electrical vehicle using fuzzy approach
    Autorzy:
    Tifour, Benali
    Boukhnifer, Moussa
    Hafaifa, Ahmed
    Tanougast, Camel
    Powiązania:
    https://bibliotekanauki.pl/articles/327624.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    energy monitoring
    fuel cell hybrid
    particle swarm
    fuel economy
    fuzzy logic
    monitorowanie energii
    zarządzanie energią
    ogniwo paliwowe
    zużycie paliwa
    logika rozmyta
    Opis:
    Recently, the reduction of fuels consumption is a global challenge, in particular for significant investments in the automotive sector, in order to optimize and control the parameters involved for the partial or total electrification of vehicles. Thereby, the energy management system remains the axis of progress for the development of fuel cell hybrid electric vehicles. The fuzzy controller has been widely adopted for energy monitoring, where the determination of its parameters is still challenging. In this work, this problem is investigated through a secondary development of a fuzzy energy monitoring system based on the Advisor platform and particle swarm optimization. The latter is used to determine, for different driving conditions, the best parameters that increase the fuel economy and reduce the battery energy use. As a result, five tuned fuzzy energy monitoring system models with five sets of parameters are obtained. Evaluation results confirm the effectiveness of this strategy, they also show slight differences between them in terms of fuel economy, battery state of charge variations, and overall system efficiency. However, the fuzzy energy monitoring system tuned under multiple conditions is the only one that can guarantee the minimum of the state of charge variations, no matter the driving conditions.
    Źródło:
    Diagnostyka; 2020, 21, 3; 15-29
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Gas turbine reliability estimation to reduce the risk of failure occurrence with a comparative study between the two-parameter Weibull distribution and a new modified Weibull distribution
    Autorzy:
    Djeddi, Ahmed Zohair
    Hafaifa, Ahmed
    Iratni, Abdelhamid
    Kouzou, Abdellah
    Powiązania:
    https://bibliotekanauki.pl/articles/2096209.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    failure analysis
    malfunction analysis
    availability
    reliability estimation
    failure occurrence
    maintenance plan
    gas turbine
    two-parameter Weibull
    modified Weibull
    analiza uszkodzeń
    dostępność
    ocena niezawodności
    turbina gazowa
    Opis:
    Responding to the needs of quality and robustness of analysis and management of degradation of equipment, to increase their life cycle and to expand these facilities to become more and more sophisticated and agronomic. This work proposes a contribution to increase the survival of a gas turbine, installed in a gascompression plant, with a comparative study between the two-parameter Weibull distribution. A new modified Weibull distribution was proposed also to reduce the risk of occurrence of failure in this rotating machine. A Statistical analysis and validation on the synthesis of turbine's reliability data and failures were considered, with a particular focus on the use of this data to increase the availability of this type of machine. So, developing a maintenance plan based on their reliability indices for scheduled inspections.
    Źródło:
    Diagnostyka; 2022, 23, 1; 1--18
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fault tolerant control of wind turbine via identified fuzzy models prototypes
    Autorzy:
    Djoudi, Habib Chaouki Ben
    Hafaifa, Ahmed
    Djoudi, Dalila
    Guemana, Mouloud
    Powiązania:
    https://bibliotekanauki.pl/articles/328473.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    fault detection
    fault isolation
    fault tolerant control
    Benchmark model
    proportional integral control
    fuzzy control
    turbina wiatrowa
    detekcja uszkodzeń
    lokalizacja uszkodzeń
    sterowanie odporne na uszkodzenia
    sterowanie rozmyte
    Opis:
    The main purpose of this study is the comparison of two control strategies of wind turbine 4.8 MW, using fuzzy control and proportional integral control, taking into account eight kinds of faults that can occur in a wind turbine model. A technique based on fault diagnosis has been used to detect and isolate faults actuators and sensors in this system, it's about an observer applied to the benchmark model. The obtained results are presented to validate the effectiveness of this diagnostic method and present the results of the proposed control strategies.
    Źródło:
    Diagnostyka; 2020, 21, 3; 3-13
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Intelligent fault diagnosis of power transmission line using fuzzy logic and artificial neural network
    Autorzy:
    Touati, Khaled Omer Mokhtar
    Boudiaf, Mohamed
    Merzouk, Imad
    Hafaifa, Ahmed
    Powiązania:
    https://bibliotekanauki.pl/articles/2146743.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    power system diagnosis
    fault detection
    electrical transmission lines
    ANN
    fuzzy logic
    system elektroenergetyczny
    diagnozowanie
    linia elektroenergetyczna
    wykrywanie uszkodzeń
    logika rozmyta
    sztuczne sieci neuronowe
    Opis:
    In the industrial sector, transmission lines are an important part of the electrical grid. Thus it is important to protect it from all the different faults that may occur as soon as possible to supply the electric power continuously. This paper presents a modern solutions and a comparative study of fault detection and identification in electrical transmission lines using artificial neural network (ANN) compare to the fuzzy logic. Faults in transmission line of various types have been created using simulation model. An intelligent monitoring system (IFD: Intelligent Fault Diagnosis) was used at both ends of a 230 kV overhead transmission line, voltage and current measurements exploited as indicator data for this system. Both approaches were found to be robust, accurate and reliable to detect the fault when it occurs, to determine the fault type short circuit or opening of a power line (open circuit), to locate the fault and to determine which phase was faulted.
    Źródło:
    Diagnostyka; 2022, 23, 4; art. no. 2022410
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fault diagnosis-based observers using Kalman filters and Luenberger estimators: Application to the pitch system fault actuators
    Autorzy:
    Zemali, Zakaria
    Cherroun, Lakhmissi
    Hadroug, Nadji
    Nadour, Mohamed
    Hafaifa, Ahmed
    Powiązania:
    https://bibliotekanauki.pl/articles/2174470.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    fault detection
    estimation
    pitch system
    Kalman filter
    Luenberger observer
    wykrywanie uszkodzeń
    estymacja
    filtr Kalmana
    obserwator Luenbergera
    Opis:
    This paper aims to present a robust fault diagnosis structure-based observers for actuator faults in the pitch part system of the wind turbine benchmark. In this work, two linear estimators have been proposed and investigated: the Kalman filter and the Luenberger estimator for observing the output states of the pitch system in order to generate the appropriate residual between the measured positions of blades and the estimated values. An inference step as a decision block is employed to decide the existence of faults in the process, and to classify the detected faults using a predetermined threshold defined by upper and lower limits. All actuator faults in the pitch system of the horizontal wind turbine benchmark are studied and investigated. The obtained simulation results show the ability of the proposed diagnosis system to determine effectively the occurred faults in the pitch system. Estimation of the output variables is effectively realized in both situations: without and with the occurrence of faults in the studied process. A comparison between the two used observers is demonstrated.
    Źródło:
    Diagnostyka; 2023, 24, 1; art. no. 2022110
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A robust fault diagnosis and forecasting approach based on Kalman filter and interval type-2 fuzzy logic for efficiency improvement of centrifugal gas compressor system
    Autorzy:
    Nail, Bachir
    Kouzou, Abdellah
    Hafaifa, Ahmed
    Hadroug, Nadji
    Puig, Vicenç
    Powiązania:
    https://bibliotekanauki.pl/articles/329190.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    fault detection
    diagnosis
    centrifugal gas compressor
    Kalman filter
    interval type-2 fuzzy logic
    experimental data
    ARIMA
    detekcja uszkodzeń
    diagnostyka
    filtr Kalmana
    Opis:
    The paper proposes a robust faults detection and forecasting approach for a centrifugal gas compressor system, the mechanism of this approach used the Kalman filter to estimate and filtering the unmeasured states of the studied system based on signals data of the inputs and the outputs that have been collected experimentally on site. The intelligent faults detection expert system is designed based on the interval type-2 fuzzy logic. The present work is achieved by an important task which is the prediction of the remaining time of the system under study to reach the danger and/or the failure stage based on the Auto-regressive Integrated Moving Average (ARIMA) model, where the objective within the industrial application is to set the maintenance schedules in precisely time. The obtained results prove the performance of the proposed faults diagnosis and detection approach which can be used in several heavy industrial systems.
    Źródło:
    Diagnostyka; 2019, 20, 2; 57-75
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Energy and environmental performance analysis of grid-connected photovoltaic systems under similar outdoor conditions in the Saharan environment
    Autorzy:
    Deriche, Mohammed Amine
    Hafaifa, Ahmed
    Tahri, Ali
    Mohammedi, Kamal
    Tahri, Fatima
    Powiązania:
    https://bibliotekanauki.pl/articles/328057.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    performance assessment
    Saharan outdoor conditions
    grid-connected PV
    thin film photovoltaic modules
    energy payback
    greenhouse gases emissions
    system fotowoltaiczny
    energia
    emisja gazów cieplarnianych
    ocena wydajności
    Sahara
    Opis:
    The aim of this paper is to present a one-year performance analysis of four grid-connected PV systems installed at Ghardaia city in Algeria’s Sahara. The grid-connected PV systems are based on four different PV module technologies which are: monocrystalline silicon (m-Si), multi-crystalline silicon (mc-Si), cadmium telluride (Cd-Te) and amorphous (a-Si) PV module technologies. The PV systems based on the thin film technologies have their performance ratio better throughout the year when the performance ratio of the mc-Si technology is better in the winter season. The a-Si PV system has its performance ratio about 6.13 % more better than mc-Si and 8.90 % better than m-Si. The AC energy produced with the a-Si PV system is 13.32 % more than what the mc-Si system produces. It was found that the a-Si PV system performs better than the other technologies under the Saharan climate conditions of Ghardaia city. The energy payback time (EPBT) and greenhouse gases (GHG) emissions of the different PV systems were analyzed. The EPBT and GHG emissions per year, vary from a minimum value of 2.8 years to a maximum value of 5.73 years and from 13.24 tons to 32.03 tons of CO2/kWh for CdTe and m-Si respectively. The CdTe PV system performs better in terms of EPBT and GHG emissions compared to the other technologies (m-Si, mc-Si and a-Si) due to its low life cycle energy requirement.
    Źródło:
    Diagnostyka; 2020, 21, 2; 13-23
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fault detection and diagnosis of photovoltaic system based on neural networks approach
    Autorzy:
    Rahmoune, Ben Mohamed
    Iratni, Abdelhamid
    Amari, Amel Sabrine
    Hafaifa, Ahmed
    Colak, Ilhami
    Powiązania:
    https://bibliotekanauki.pl/articles/2203647.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    photovoltaic system
    fault detection
    neural networks
    diagnostic system
    residue evaluation
    system fotowoltaiczny
    wykrywanie uszkodzeń
    sieci neuronowe
    system diagnostyczny
    Opis:
    Solar energy has become one of the most important renewable energies in the world. With the increasing installation of power plants in the world, the supervision and diagnosis of photovoltaic systems have become an important challenge with the increased occurrence of various internal and external faults. Indeed, this work proposes a new solar power plant diagnosis based on the artificial neural network approach. The developed model was to improve the performance and reliability of the power plant located in Tamanrasset, Algeria, which is subjected to varying weather conditions in terms of radiation and ambient temperature. By using the real data collected from the studied system, this approach allow to increase electricity production and address any issues that may arise quickly, ensuring uninterrupted power supply for the region. Neural networks have shown interesting results with high accuracy. This fault diagnosis approach allows to determine the time of occurrence of a fault affecting the examined PV system. Also, allow an early detection of failures and degradation of the system, which contributes to improving the productivity of this photovoltaic installation. With a significant reduction in the time needed to repair the damage caused by these faults and improve the reliability and continuity of the electrical energy production service.
    Źródło:
    Diagnostyka; 2023, 24, 3; art. no. 2023303
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    ARMAX-based identification and diagnosis of vibration behavior of gas turbine bearings
    Autorzy:
    Mahroug, Youcef
    Khaldi, Belgacem Said
    Guemana, Mouloud
    Hafaifa, Ahmed
    Iratni, Abdelhamid
    Colak, Ilhami
    Powiązania:
    https://bibliotekanauki.pl/articles/11025752.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
    Tematy:
    system identification
    ARMAX
    parametric estimation
    gas turbine
    vibration modelling
    turbina gazowa
    modelowanie drgań
    estymacja parametryczna
    identyfikacja systemu
    Opis:
    Parametric identification approaches play a crucial role in the control and monitoring of industrial systems. They facilitate the identification of system variables and enable the prediction of their evolution based on the input-output relationship. In this study, we employ the ARMAX approach to accurately predict the dynamic vibratory behavior of MS5002B gas turbine bearings. By utilizing real input-output data obtained from their operation, this approach effectively captures the vibration characteristics of the bearings. Additionally, the ARMAX technique serves as a valuable diagnostic tool for the bearings, enhancing the quality of identification of turbine variables. This enables continuous monitoring of the bearings and real-time prediction of their behavior. Furthermore, the ARMAX approach facilitates the detection of all potential vibration patterns that may occur in the bearings, with monitoring thresholds established by the methodology. Consequently, this enhances the availability of the bearings and reduces turbine downtime. The efficacy of the proposed ARMAX approach is demonstrated through comprehensive results obtained in this study. Robustness tests are conducted, comparing the real behavior observed through various probes with the reference model, thereby validating the approach.
    Źródło:
    Diagnostyka; 2023, 24, 3; art. no. 2023310
    1641-6414
    2449-5220
    Pojawia się w:
    Diagnostyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-11 z 11

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