A Machine Vision-Based Deformation Detection Method for High-Voltage Cable Protective Sleeves

High-precision deformation detection of cable protection sleeves is crucial for ensuring the reliable operation of high-voltage lines. However, contact-based detection methods present risks associated with working at heights and suffer from low efficiency, while vision-based non-contact methods are prone to image blurring issues during long-distance imaging. To address these challenges, a lightweight super-resolution imaging-based digital image correlation (DIC) method is proposed for achieving high-precision deformation detection of cable protective sleeves. The proposed method first employs a dual-camera vision system to synchronously capture low-resolution deformation speckle patterns of the cable protection sleeve during tensile deformation. Subsequently, the clarity of the speckle images is enhanced using a lightweight super-resolution imaging technique. Finally, DIC technology is applied to perform stereo matching calculations on the super-resolution speckle images before and after deformation, thereby obtaining high-precision three-dimensional deformation data of the cable protection sleeve. To validate the performance of the proposed method, simulation verification and uniaxial tensile experiments were conducted. The results demonstrate that images processed with super-resolution exhibit high accuracy in both displacement and deformation detection, meeting the precision requirements for cable sheath inspection. This method demonstrates significant performance advantages in the field of cable inspection.