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In order to solve the problem of defect criterion that can not effectively identify the Stress concentration region and crack defect, wavelet packet transformation was used to multiscale wavelet analysis of Metal Magnetic Memory (MMM) signals. A new signal inspection technology was presented based on energy increment feature and wavelet packet frequency(More)
Metal magnetic memory (MMM) signals can reflect stress concentration and cracks on the surface of ferromagnetic components, but the traditional criteria used to distinguish the locations of these stress concentrations and cracks are not sufficiently accurate. In this study, 22 indices were extracted from the original MMM signals, and the diagnosis results(More)
The technique of metal magnetic memory (MMM) has great advantages in detecting early failures such as stress concentration and fatigue damage of ferromagnetic components, which has been widely applied due to its high efficiency, low requirements for surface preparation and ease of operation. However, research into the quantitative description of defect(More)
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