Bolted joints are critical load-transfer components in bridges, wind turbines, aerospace systems, mechanical equipment, and offshore platforms, where preload loss can degrade stiffness, accelerate fatigue, and compromise safety. For structural health monitoring, early monitoring of preload reduction before marked loosening is essential, yet existing ultrasonic guided wave indicators remain affected by frequency dependence, non-monotonic responses, amplitude drift, and environmental disturbances. This study proposes an early-warning-oriented preload identification method that combines broadband excitation, multi-frequency narrowband reconstruction, spectral centroid extraction, optimized weighted fusion, and fixed SC-domain linear calibration from one reference loading group. Using a 20–250 kHz Chirp response, 14 narrowband signals from 50 to 180 kHz were reconstructed for an M20 single-bolt specimen tested over 50–90 N·m. The fused spectral centroid index exhibited a stable, monotonic, and approximately linear relationship with preload. When fixed weights and calibration coefficients were transferred to held-out repeated-loading groups, all Pearson correlation coefficients exceeded 0.99. Feature-level robustness tests showed that the arithmetic mean of the spectral centroid reduced temperature-induced Range% by 98.42–99.08% and RSD by 98.89–99.31% relative to energy-based features. This work provides an interpretable multi-frequency spectral descriptor and a calibration transfer framework for repeatable early warning of preload loss in a controlled single-bolt configuration.

Concrete is the most widely used structural material in modern civil engineering, and its internal integrity is closely related to public safety and service life. Ultrasonic nondestructive testing is essential for concrete structural health monitoring, where acoustic transmission, anti-interference capability, and signal quality strongly affect detection accuracy. To overcome the insufficient integration of acoustic impedance matching, electromagnetic shielding, and signal conditioning in existing embedded piezoelectric ultrasonic sensors, this study develops an integrated ultrasonic sensor based on a previously proposed acoustic matched smart aggregate, incorporating an electromagnetic shielding structure and an on-board preamplifier circuit. By jointly optimizing acoustic transmission, electromagnetic compatibility, and front-end signal conditioning, the sensor improves signal quality and robustness in concrete environments. Experiments demonstrate enhanced signal reception, stable anti-interference performance, and a significantly improved signal-to-noise ratio. Ultrasonic CT imaging further confirms its ability to identify internal defects in concrete, supporting its application in concrete inspection and structural health monitoring.