To address the problem of poor wine quality caused by wine seal ring defects and improve defect detection efficiency, an online detection method for wine seal ring defects is developed. According to the structure and position of the wine seal rings and the inner diameter and depth of the bottle caps, an online detection system based on machine vision dual-field and dual-station collaboration methods is proposed. Given that it is difficult to extract the contour defects of wine seal rings from two-dimensional information, we transform the two-dimensional information of a wine seal ring contour into an one-dimensional vector. Then, the one-dimensional vector theory is applied to analyze and deal with the defects, and the wavelet modulus maxima method is used to extract and determine them. The experimental results show that the system can effectively detect defects at any position of a wine ring and that its detection accuracy is 99.89%. The efficiency of the method described in this paper is six times higher than that of manual inspection. It meets the requirements of production and expected R&D, and provides a new technique for the non-destructive online detection of wine seal ring defects.