Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "defect inspection" wg kryterium: Temat

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-2 z 2
    Tytuł:
    Vision-based Online Defect Detection of Polymeric Film via Structural Quality Metrics
    Autorzy:
    Rawashdeh, Nathir
    Hazaveh, Paniz
    Altarazi, Safwan
    Powiązania:
    https://bibliotekanauki.pl/articles/2201189.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    industrial inspection
    quality control
    defect detection
    polymer film
    vision
    Opis:
    Nondestructive and contactless online approaches for detecting defects in polymer films are of significant interest in manufacturing. This paper develops vision-based quality metrics for detecting the defects of width consistency, film edge straightness, and specks in a polymeric film production process. The three metrics are calculated from an online low-cost grayscale camera positioned over the moving film before the final collection roller and can be imple mented in real-time to monitor the film manufacturing for process and quality control. The objective metrics are calibrated to correlate with an expert ranking of test samples, and results show that they can be used to detect defects and measure the quality of polymer films with satisfactory accuracy.
    Źródło:
    Management and Production Engineering Review; 2023, 14, 1; 61--71
    2080-8208
    2082-1344
    Pojawia się w:
    Management and Production Engineering Review
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Automatic inspection of surface defects in die castings after machining
    Autorzy:
    Świłło, S. J.
    Perzyk, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/380799.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    nondestructive testing
    casting defect
    machined aluminum
    die casting
    image processing algorithm
    vision system inspection
    badania nieniszczące
    wada odlewu
    odlewanie ciśnieniowe
    algorytm przetwarzania obrazu
    inspekcja wizyjna
    Opis:
    A new camera based machine vision system for the automatic inspection of surface defects in aluminum die casting was developed by the authors. The problem of surface defects in aluminum die casting is widespread throughout the foundry industry and their detection is o f paramount importance in maintaining product quality. The casting surfaces are the most highly loaded regions of materials and components. Mechanical and thermal loads as well as corrosion or irradiation attacks are directed primarily at the surface of the castings. Depending on part design and processing techniques, castings may develop surface discontinuities such as cracks or tears, inclusions due to chemical reactions or foreign material in the molten metal, and pores that greatly influence the material ability to withs tand these loads. Surface defects may act as a stress concentrator initiating a fracture point. If a pressure is applied in this area, the casting can fracture. The human visual system is well adapted to perform in areas of variety and change; the visual inspection processes, on the other hand, require observing the same type of image repeatedly to detect anomalies. Slow, expensive, erratic inspection usually is the result. Computer based visual inspection provides a viable alternative to human inspectors. Developed by authors machine vision system uses an image processing algorithm based on modified Laplacian of Gaussian edge detection method to detect defects with different sizes and shapes. The defect inspection algorithm consists of three parameters. One is a parameter of defects sensitivity, the second parameter is a thres hold level and the third parameter is to identify the detected defects size and shape. The machine vision system has been successfully tested for the different types of defects on the surface of castings.
    Źródło:
    Archives of Foundry Engineering; 2011, 11, 3 spec.; 231-236
    1897-3310
    2299-2944
    Pojawia się w:
    Archives of Foundry Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies