Study on influencing factors of ultrasonic testing for lead seal defects in high-voltage cables
Abstract
Lead seals are critical sealing and protective components of high-voltage cable terminations, and their structural integrity directly determines the safe and stable operation of urban power transmission systems. Conventional non-destructive testing methods face inherent limitations such as low penetration depth and susceptibility to heat-shrinkable protective layers, making ultrasonic phased array technology a promising alternative for lead-seal defect detection. However, imaging quality is often severely degraded by practical factors encountered in complex field inspection environments. This study systematically investigates the effects of coupling condition, surface roughness, and surface curvature on ultrasonic imaging performance for lead-seal defects. Three groups of controlled comparative experiments were conducted using artificially fabricated lead-seal specimens with predefined internal defects, varying surface roughness levels, and different curvature radii. A dedicated ultrasonic phased array testing platform equipped with a 5 MHz, 16-element probe was established to quantitatively evaluate imaging quality through metrics including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and bottom-wave amplitude. The results show that the improved flexible film coupling device provides significantly better imaging quality than the conventional rigid wedge, with 28.5% higher SNR and 27.8% higher CNR. In addition, increased surface roughness enhances diffuse reflection and reduces echo coherence, while surface curvature introduces spatial phase deviations that weaken bottom-wave response and increase defect interpretation difficulty. These findings provide essential experimental evidence and practical guidance for optimizing field inspection protocols and improving the reliability of ultrasonic testing for high-voltage cable lead seals.
Copyright (c) 2026 Peng He, Jian Cheng, Fengyin Zhang, Lianbing Wang, Cen Qian

This work is licensed under a Creative Commons Attribution 4.0 International License.
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