• DocumentCode
    1989522
  • Title

    Research on Metal Magnetic Memory Signal Singularity Detection

  • Author

    Mingcheng Yu ; Shaojun Sun ; Song Lin

  • Author_Institution
    91404 Unit, PLA, Qinhuangdao, China
  • fYear
    2012
  • fDate
    27-30 May 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Two novel signal singularity detection (SSD) algorithms for metal magnetic memory (MMM) signal are put forward in this paper: the signal segmented fluctuation and the signal segmented dissimilarity. What the former results from is that the MMM signal corresponding to the stress concentrated area (SCA) fluctuates more heavily than non SCA while the latter is based on the fact that if the MMM signal, which has a definite length, is segmented in a certain interval, the stress concentrated segments (SCS) are generally far less than those which are not stress concentrated by number, and the signals of the non SCSs are similar to each other, but the signals from SCSs are dissimilar to those of non SCSs. The two methods have the advantage in the detection of the metallic work piece which is non defective in looks but fatigued as well as may be helpful to detect the singularity of the signals such as negative pressure wave, ultrasonic wave etc. Experimental result with real data demonstrates the effectiveness of the proposed algorithms. Moreover, the MMM SSD software implementation are considered.
  • Keywords
    magnetic storage; signal detection; MMM SSD software; MMM signal; SCA; SCS; SSD algorithms; metal magnetic memory signal singularity detection; metallic work piece detection; negative pressure wave; signal segmented dissimilarity; signal segmented fluctuation; stress concentrated area; stress concentrated segments; ultrasonic wave; Fluctuations; Low pass filters; Magnetic memory; Metals; Signal processing algorithms; Software; Stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering and Technology (S-CET), 2012 Spring Congress on
  • Conference_Location
    Xian
  • Print_ISBN
    978-1-4577-1965-3
  • Type

    conf

  • DOI
    10.1109/SCET.2012.6341972
  • Filename
    6341972