## 1 Introduction  
The HFGCW consists of glass panels bonded to an attached frame with structural sealant, which is then connected to beams and columns using pressure blocks and bolts. Due to its lightweight, simple structure, and aesthetic appeal, HFGCWs are widely used in modern buildings [1]. As the building's peripheral protective structure, curtain walls are continuously exposed to wind loads, rain, and other environmental factors during service. Over time, a structural sealant exhibits aging and damage, potentially leading to safety hazards such as glass panel detachment [2]. Thus, assessing the damaged state of structural sealant in HFGCWs is critical for monitoring safety performance and preventing structural instability [3]. Various non-destructive evaluation methods have been explored for structural sealant inspection. Active thermography, laser Doppler vibrometry, and nonlinear ultrasonic modulation have demonstrated potential for bonding strength assessment and debonding detection [4, 5, 6]. Lamb wave propagation and laser thermography have shown particular efficacy in interfacial defect characterization [7, 8]. While fiber optic sensing and pulse-echo ultrasonics offer high sensitivity, their field applicability is limited by equipment complexity and operational constraints [9, 10]. Vibration-based non-destructive testing detected damage by analyzing a structure's vibration response [11, 12]. Signal processing and feature extraction techniques are used to conduct in-depth analysis of the dynamic response signals of structures or equipment to achieve non-destructive identification and evaluation of faults or anomalies [13; 14]. Compared to the detection methods mentioned above, vibration-based non-destructive testing enabled structural health assessment through comparative analysis of dynamic characteristics pre- and post-damage, demonstrating particular advantages for internal damage detection [15]. The extraction and analysis of vibration signal characteristics have emerged as predominant methodologies for detecting structural adhesive damage in HFGCWs. The vibration response signal of a glass curtain wall was acquired using a laser Doppler vibrometer and decomposed via wavelet packet transform. The wavelet packet frequency band energy square difference was calculated as the damage index. Through numerical simulation and experimental validation, this method was shown to identify and locate sealant damage effectively [16]. A vibration analysis method based on Driving-point Acceleration Conductance was proposed to identify the construction defects or debonding damage of structural sealant by statistical means (e.g., cumulative difference or relative cumulative difference index) [17; 18]. A damage identification method for glass curtain walls was developed based on the Hilbert-Huang Transform (HHT) and transfer function analysis. The HHT was employed to decompose the vibration response signals of the glass curtain wall into Intrinsic Mode Functions (IMFs), after which damage-sensitive parameters were established by evaluating variations in the IMFs' transfer functions. Damage detection was achieved by integrating the vibration transfer rate function, enabling the effective identification of structural anomalies [19]. A damage identification method for structural sealants in glass curtain walls was developed based on the vibration transfer rate and discrete wavelet transform. The vibration response of the glass curtain wall was simulated using ANSYS R17.0 finite element software, with the frequency response function and vibration transfer rate serving as damage assessment parameters. The discrete wavelet transform was applied to decompose vibration signals and extract damage-sensitive features. Finally, damage identification was achieved by integrating the transfer rate change of vibration signals [20]. Modal parameters demonstrate exceptional sensitivity to stiffness variations induced by structural damage.