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    Tytuł:
    A review of the importance of synchrophasor technology, smart grid, and applications
    Autorzy:
    Baba, Maveeya
    Nor, Nursyarizal B.M.
    Sheikh, Aman
    Nowakowski, Grzegorz
    Masood, Faisal
    Rehman, Masood
    Irfan, Muhammad
    Arefin, Ahmed Amirul
    Kumar, Rahul
    Baba, A. Momin
    Powiązania:
    https://bibliotekanauki.pl/articles/2173713.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    phasor measurement unit
    PMU
    micro-PMU
    Global Positioning System
    GPS
    optimal PMU placement
    smart grid
    SG
    jednostka pomiaru fazorów
    mikro-PMU
    globalny system pozycjonowania
    optymalne rozmieszczenie PMU
    sieć inteligentna
    Opis:
    The electrical network is a man-made complex network that makes it difficult to monitor and control the power system with traditional monitoring devices. Traditional devices have some limitations in real-time synchronization monitoring which leads to unwanted behavior and causes new challenges in the operation and control of the power systems. A Phasor measurement unit (PMU) is an advanced metering device that provides an accurate real-time and synchronized measurement of the voltage and current waveforms of the buses in which the PMU devices are directly connected in the grid station. The device is connected to the busbars of the power grid in the electrical distribution and transmission systems and provides time-synchronized measurement with the help of the Global Positioning System (GPS). However, the implementation and maintenance cost of the device is not bearable for the electrical utilities. Therefore, in recent work, many optimization approaches have been developed to overcome optimal placement of PMU problems to reduce the overall cost by providing complete electrical network observability with a minimal number of PMUs. This research paper reviews the importance of PMU for the modern electrical power system, the architecture of PMU, the differences between PMU, micro-PMU, SCADA, and smart grid (SG) relation with PMU, the sinusoidal waveform, and its phasor representation, and finally a list of PMU applications. The applications of PMU are widely involved in the operation of power systems ranging from power system control and monitor, distribution grid control, load shedding control and analyses, and state estimation which shows the importance of PMU for the modern world.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 6; art. no. e143826
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Vibration-based identification of engine valve clearance using a convolutional neural network
    Autorzy:
    Tabaszewski, Maciej
    Szymański, Grzegorz M.
    Nowakowski, Tomasz
    Powiązania:
    https://bibliotekanauki.pl/articles/2124718.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    combustion engine
    diagnostics
    vibration
    machine learning
    convolutional network
    silnik spalinowy
    diagnostyka
    drgania
    uczenie maszyny
    splotowa sieć neuronowa
    Opis:
    Contemporary operation-related requirements for combustion engines force the necessity of ongoing assessment of their in operation technical condition (e.g. marine engines). The engine efficiency and durability depend on a variety of parameters. One of them is valve clearance. As has been proven in the paper, the assessment of the valve clearance can be based on vibration signals, which is not a problem in terms of signal measurement and processing and is not invasive into the engine structure. The authors described the experimental research aiming at providing information necessary to develop and validate the proposed method. Active experiments were used with the task of valve clearance and registration of vibrations using a three-axis transducer placed on the engine cylinder head. The tests were carried out during various operating conditions of the engine set by 5 rotational speeds and 5 load conditions. In order to extract the training examples, fragments of the signal related to the closing of individual valves were divided into 11 shorter portions. From each of them, an effective value of the signal was determined. Obtained total 32054 training vectors for each valve related to 4 classes of valve clearance including very sensitive clearance above 0.8 mm associated with high dynamic interactions in cylinder head. In the paper, the authors propose to use a convolutional network CNN to assess the correct engine valve clearance. The obtained results were compared with other methods of machine learning (pattern recognition network, random forest). Finally, using CNN the valve clearance class identification error was less than 1% for the intake valve and less than 3.5% for the exhaust valve. Developed method replaces the existing standard methods based on FFT and STFT combined with regression calculation where approximation error is up to 10%. Such results are more useful for further studies related not only to classification, but also to the prediction of the valve clearance condition in real engine operations.
    Źródło:
    Archives of Transport; 2022, 61, 1; 117--131
    0866-9546
    2300-8830
    Pojawia się w:
    Archives of Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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