Hydrostatic rotary tables are key mechatronic components in high-precision manufacturing equipment, and their thermal evolution affects operating stability and machining-related accuracy. This study presents a sensing-driven digital twin monitoring framework that integrates multi-point thermal sensing, future temperature prediction, spatial thermal-state reconstruction, and virtual-physical visualization. Experimental temperature data from fifteen structural monitoring positions are organized using a chronological file-level split to avoid temporal leakage in time-series evaluation. Five forecasting models are compared, and a causal temporal convolutional network is selected as the predictive module. The final model uses the preceding 30 min temperature sequences of T1-T15 to forecast their temperatures 5 min ahead, achieving an RMSE of 0.0673 degrees C and an MAE of 0.0461 degrees C on the independent test subset. Measurement-constrained region-aware reconstruction reduces RMSE from 0.1816 to 0.1628 degrees C; strict sensor omission validates spatial recovery, while Unity updates 64,000 voxels in 13.42 ms.
In recent years, LED-based technologies for flowering light regulation have advanced rapidly. However, there is still a lack of systematic research on the factors affecting illumination uniformity in LED supplemental lighting and their quantitative evaluation. In this study, three key parameters, including divergence angle, vertical distance between light source and illuminated surface, and LED array spacing, were adjusted separately using the control variable method to clarify their quantitative relationship with illumination uniformity. An evaluation model named LED-IUE was established and validated, and sensitivity analysis was performed. The results confirmed the high accuracy of the model and indicated that divergence angle and source-surface distance impose more significant effects. Taking Beijing as an example, the influence of illumination uniformity on greenhouse lighting energy consumption was further investigated. The findings contribute to optimizing flower cultivation, increasing productivity, and reducing energy consumption of supplemental lighting in greenhouses.
Traditional human tissue heat-transfer models often oversimplify the heterogeneous thermal behavior of facial tissues, whereas more refined models suffer from low computational efficiency and unstable inversion. To address these limitations, we propose a discrete-element geometric model that enables non-uniform parameter allocation while preserving model simplicity. A vectorized parameterization strategy is introduced to avoid spatial discontinuities, together with physics-guided constraints derived from the heat transfer equation to ensure parameter validity. One-dimensional equations are further employed for efficient parameter initialization. Inversion experiments demonstrate lower reconstruction error, fewer abnormal parameter estimates, fewer iterations to convergence, and greater stability under noise perturbations. Simulation results show better agreement with real facial temperature distributions. Furthermore, the model is applied to thermal infrared image generation, effectively enhancing face recognition performance under cross-thermal conditions, with recognition accuracy improved by more than 10%. This work bridges heat transfer modeling and thermal infrared face recognition, enabling their effective cross-application.
We present a tolerance-sensitivity-driven, manufacturability-aware strategy integrating optical design and alignment for optomechatronic imaging, validated in a fluorescence laparoscope. A chromatically corrected, structurally optimized design achieves near co-focal imaging across 450-1000 nm and anchors tolerance analysis and alignment planning. Simulations show strong axial-misalignment sensitivity, with decentering tolerances as tight as +/- 0.01 mm, near fabrication limits. We implement a hybrid alignment approach combining active compensation with passive constraints and validate it on batch prototypes. Five units were fabricated, aligned, and evaluated per YY 0068.1-2008; all met specification (100% yield), with central angular resolution similar to 8.9 cycles/deg in the visible (spec >= 7.92 ) and similar to 6.0 cycles/deg near 1000 nm (spec >= 4.18 ), a 75 degrees field of view, and distortion <= 4 % . The co-optimization preserves broadband image quality and high optical resolving power without tightening manufacturing tolerances, enabling scalable production and offering a transferable methodology for related endoscopic systems.
