## 1 Introduction  
A hidden frame glass curtain wall (HPGCW) is a key component of modern architecture, primarily composed of a structural sealant, glass panel, and supporting frame. In the service process, the structural sealant would be damaged [1, 2, 3], which poses a risk for maintenance and potential accidents such as glass panel detachment. The damage location identification methods of structural sealants can be mainly classified as destructive and non-destructive detection methods [4, 5]. Destructive detection methods, such as the balloon method and the suction cup method [6, 7, 8, 9, 10], involve dismantling decorative cover plates to directly inspect the structural sealant. These methods can provide detailed information about the damage location of the structural sealant. However, it would destroy the sample and is only suitable for small-scale testing of a limited number of panel units. Non-destructive detection methods allow for identifying the defects without removing the decorative cover plate. Common non-destructive testing methods include dynamic-based testing, ultrasonic testing, X-ray testing, infrared testing, etc. [11, 12, 13]. Ultrasonic testing has real-time capability, but it is not intuitive; the detection results are easily affected by subjective and objective factors. X-ray testing and infrared testing can accurately pinpoint the damage and location, but they can only detect surface defects and cannot identify hidden damages. Based on the characteristics of being global and fast, the dynamic method is widely used in detecting damage in bridges and structures [14, 15]. Changes in the modal parameters and dynamic response between the undamaged and damaged panel units are often used to identify the damage to structural sealants. [PERSON] et al. [16, 17, 18] detected the damage to the structural sealant by comparing the measured natural frequencies and theoretic ones. However, natural frequencies provide only overall characteristics and lack specific damage location information. Recently, dynamic responses, which contain responses of higher modes, were used to identify the damage. [PERSON] et al. [19] utilized the difference in frequency response function to identify the damage to structural sealant. [PERSON] et al. [20] proposed the statistical baseline model to identify the damage to structural sealant. [PERSON] et al. [21] proposed the wavelet transform method to identify the damage to structural sealant. By analyzing the changes in the response of the glass panel, the changing of state of the glass panel can be analyzed to further identify the damage to the structural sealant [22; 23; 24; 25]. To identify the damage location of structural sealants, the modal characteristics are a potential indicator. [PERSON] et al. [26; 27] demonstrated that changes in vibration modes could be used to identify damage. [PERSON] and [PERSON] [28] calculated the curvature mode difference in the glass panel to identify the damage location of the structural sealant. To identify the structural sealant damage on the boundary, [PERSON] et al. [29] introduced the variation in the average boundary mode assurance criterion (BMAC), the average difference in the boundary modal curvature, and the average boundary mode strain energy with the increase in the damage severity of structural sealant. The testing results show that these damage identification methods based on boundary modes can identify the damaged edge of structural sealant, but cannot determine the exact location of the damage. According to the current study, it is a challenge to point out the specific damage location of structural sealant. The aim of this paper is to develop a two-stage damage localization method to identify the exact damage location of structural sealant. In the first stage of such an identification method, the concept of assurance criterion of boundary modal curvature (ACBMC) is proposed. Then, the damaged edges are identified using the ACBMC.