Harmonic Detection System and Identification Algorithm for Steel Pipeline Defects

Abstract

Aiming at the problem of defects detection of steel pipeline, a harmonic detection system was developed based on electromagnetic principle, and the target signal identification algorithm was studied. The Advanced RISC Machine (ARM) Cortex-M3 was adopted to design digital adjustable harmonic excitation source, and its effective output power can up to 70 W. The Field Programmable Gate Arrays (FPGA) and ARM Cortex-M4 were introduced to design 15 channels high speed data collector, which parallel local-storage rate of each channel can reach 4.7 kHz. The electromagnetic focusing excitation array and Tunnel Magneto Resistance (TMR) sensors array were constructed to improve the spatial resolution of the detection system. Meanwhile, the system also integrated GPS positioning and LCD real-time display functions. Furthermore, the algorithm combining Empirical Mode Decomposition (EMD) and variable-scale Stochastic Resonance (SR) was proposed to process signal and enhance the targets. The effectiveness of the instrument and algorithm are well verified in both simulation and experiment. The results show that this method has higher integration and better detection effect, which provides a novel method for non-contact detection of metal material defects and is suitable for engineering applications.