High-SNR Balanced Field Electromagnetic Detection Method for Subsea Pipeline Cracks Based on Sampling Optimization

During crack detection in subsea oil and gas pipelines under strong-noise conditions, balanced field electromagnetic technique (BFET) exhibits limited capability to reconstruct the amplitude and phase features of crack signals and produces a relatively low signal-to-noise ratio (SNR). To address these limitations, a high-SNR detection method based on the joint optimization of sampling parameters and reference accuracy is proposed. A finite-element model of the balanced field electromagnetic sensor was established. The time-domain voltage signal of the crack detection signal and its amplitude–phase features were then obtained. By fitting the crack detection signals and introducing Gaussian white noise and quantization noise, the effects of different sampling frequencies, sampling accuracies, and reference accuracies on the reconstruction accuracy of the amplitude–phase features and on the SNR of the detection signals were systematically investigated. The experimental results show that, at an excitation frequency of 1 kHz, a sampling frequency of 64 kHz, and both a sampling accuracy and reference accuracy of 16 bits, the amplitude and phase errors of the crack detection signals are significantly reduced, while the SNR exceeds 31.74 dB. The proposed method provides a reference for evaluating the influence of sampling parameters and reference accuracy on the detection SNR and the reconstruction accuracy of amplitude–phase features.