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    LI Ren-Xing, ZHANG Yi, BAI Lian-Fa, CHEN Qian, GU Guo-Hua. Morphological Filtering Slightness Crack Detection and Objects Identification[J]. Nondestructive Testing, 2009, 31(10): 796-799.
    Citation: LI Ren-Xing, ZHANG Yi, BAI Lian-Fa, CHEN Qian, GU Guo-Hua. Morphological Filtering Slightness Crack Detection and Objects Identification[J]. Nondestructive Testing, 2009, 31(10): 796-799.
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    Morphological Filtering Slightness Crack Detection and Objects Identification

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    • Received Date: December 30, 2008
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      • Abstract
    • Magnetic powder detection is an important method for work-piece superficial crack detection. Traditional magnetic powder crack detection is manpower consuming, time consuming, high expenses, low precision, and fallibility. Modern industrial detection technology requires work-piece crack auto-detection. Because of exterior status, veritable or feigned crack object, site condition, etc., existing method can not successfully auto-detect and identify work-piece cracks. Fluorescent magnetic powder image and crack image characteristics are analyzed, morphological grads arithmetic operators image fringe detection based on sub-area threshold is studied, crack identification arithmetic based on Fisher linear discrimination is designed according to long-width ratio and round shape degree character. Cart-wheel-axis crack detection line equipped with this auto-detection and identification technology got an efficient crack detection ratio as high as 90%.
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