Architectural heritage faces multiple degradation risks, while traditional preventive conservation often falls short in information integration, dynamic analysis, and regional management. Moreover, existing HBIM research lacks systematic digital approaches for hybrid Sino-Western vernacular heritage. This study addresses these gaps by constructing a preventive conservation HBIM framework for Kaiping Diaolou. A customized parametric component library and a three-level coding system are developed, enabling systematic HBIM application in non-standardized contexts. Moving beyond digital archiving, a closed-loop workflow of “data acquisition → HBIM → multi-physics simulation → targeted intervention” is established, shifting HBIM’s core function from passive documentation to proactive risk forecasting. A value- and risk-driven principle is proposed to define LOD/LOI levels, allowing appropriate modeling resource allocation according to heritage significance and risk grades. A direct data-interaction workflow is developed between HBIM and multi-physics simulations (structural FEM, wind/CFD), enabling quantitative identification of structural weak points and high-risk environmental degradation areas. Enhanced visual expression methods, including 3D defect mapping and a “shadow-element and displacement-decomposition” structural exploded-view technique, are introduced to overcome the limitations of conventional 2D representations. The proposed framework and methods are validated through the case study of Ruishi Tower, demonstrating the feasibility of HBIM in heritage preventive conservation and providing a replicable pathway for the digital preservation of similar vernacular heritage.

The construction industry is characterized by high physical demands, where workers are regularly engaged in manual handling and labor-intensive tasks, making fatigue a common occupational challenge. This study aims to quantify the combined effects of working height and task duration on physical fatigue among construction workers and to establish dynamic fatigue thresholds based on surface electromyography (sEMG) signals. A two-way repeated-measures field experiment was conducted on an actual construction site with eight healthy male workers. Each participant completed four working-height conditions (9, 20, 33, and 46 m), and at each height, physiological and subjective measurements were obtained at four repeated time points (0.5, 1.0, 1.5, and 2.0 h). This yielded 32 participant-by-height trials and 128 repeated observations in total. The results demonstrated a significant interaction between working height and task duration, with the increase in heart rate from 0.5 h to 2 h at 46 m being approximately 2.2-fold higher than that at 9 m during a two-hour working period. Frequency-domain analysis of sEMG signals revealed significant declines in median frequency (MDF) and mean power frequency (MPF) across all monitored muscles over time (p < 0.001), with cubic regression models showing excellent goodness-of-fit (R² up to 0.947). Based on MDF and MPF trends, fatigue progression was classified into three phases: development (0–30 min), stability (30–75 min), and instability (after 75 min), identifying approximately 75 min as an exploratory transition point from compensation to decompensation. These preliminary results provide exploratory empirical evidence that may inform the future optimization of work–rest schedules and real-time fatigue monitoring strategies in high-rise construction operations, pending validation in larger, more diverse populations.