Design and experimental validation of MMM-based pipeline stress concentration detection system - Deng Gong; Lunwu Zhao; Gang Han (Results in Engineering)
An intelligent pipeline stress concentration detection system was developed based on the Metal Magnetic Memory (MMM) method, utilizing high-sensitivity anisotropic magnetoresistive (AMR) sensors (HMC5883L). The MMM detection mechanism was analyzed to establish the relationship between stress concentration and self-magnetic leakage fields (SMLF). An embedded hardware system was designed using the S3C2140 ARM processor, combined with a high-sensitivity magnetic sensor array, an embedded Linux software suite, and standardized evaluation algorithms compliant with GB/T 35090-2018. This system ensures real-time monitoring, portability, and automated stress concentration identification. Fatigue testing and X-ray diffraction (XRD) residual stress measurements were conducted to validate the system's performance. Results show that the system can effectively identify stress concentration zones through magnetic anomaly evolution, with a threshold (K = 160) reliably demarcating plastic deformation zones. The stress concentration severity index F enables early warnings 3,200 cycles before final failure (98.3 % fatigue life consumed). The proposed MMM-based stress concentration detection system offers a low cost, operator-independent solution for proactive pipeline integrity management, significantly mitigating failure risks associated with undetected stress concentrations.