The infrared thermal imaging detection method has unique advantages inthe diagnosis of low/zero-valued porcelain insulators. However, anEHV/UHV porcelain insulator string is generally too long (even 10 meters or above) to be entirely displayed in a single infrared imageshotbyan industrial handheld/airborne thermal camera, which causes serious difficulties to the intelligent diagnosis of deterioration based on the whole string temperature characteristics. To solve this problem, this article proposes a double-segmenttemperature curve splicing method based on weighted data fusion. This methodcan solve the problems of target missing byapplying general infrared image splicingtechnology, and can obtainhigher fitting accuracy compared with curve splicing methods such as rounding and midpoint splicing. The basic algorithm and process of the proposed curve splicing method are illustrated through an example ofa 1 000 kV insulator string.A comparative study of various curve splicing methods is carried out by taking a 500 kV insulator string into account.Therefore,the effectiveness and feasibility of the proposed method are verified.