To address spindle thermal error in precision machining, this study proposes a hybrid modeling method. It combines a physical model for linear deformation with a GAT-LSTM network. Experiments show the hybrid model achieved RMSE/MAE of 4.6/4.0 µm under full training (12 conditions), 5.5/4.9 µm under 3 training condition and 4.8/4.3 µm under 1 training condition, substantially reducing the data requirements for thermal error modeling. The compensation experiment conducted using a high real-time surrogate-model-based architecture reduced thermal error by 78% (from 54 µm to 12 µm), demonstrating high precision and minimal data requirements suitable for real-time applications.
Vehicle energy-regenerative suspension can convert part of the vibration energy induced by road excitation into electrical energy. However, there are coupled performance conflicts among energy recovery, ride comfort, and suspension safety, and a fixed-weight LQR controller finds…
Continuous shared control provides an effective approach for intelligent vehicles to balance driving autonomy and system safety boundaries in complex human–machine interaction scenarios. However, existing shared control methods fail to dynamically adapt to the complex and time-va…
Digital twins are becoming essential tools in smart, human-centric manufacturing, yet validated approaches that integrate real human behavior into digital twin models remain limited. This study develops and experimentally validates a digital twin as a tool for evaluating human pe…
Rolling bearings are crucial components in CNC machine tool spindles, and their health condition directly affects machining precision and operational reliability. To address the significant challenges of bearing fault diagnosis in industrial environments, this paper proposes an a…
The growing deployment of connected and autonomous vehicles (CAVs) requires coordinated control strategies that jointly address safety, mobility, and energy efficiency. This paper presents a novel two-stage cooperative control framework for autonomous hybrid electric vehicle (HEV…
Unrecognized mechanical faults and emergency sounds in vehicles can compromise safety, particularly for individuals with hearing impairments and in sound-insulated or autonomous driving environments. As intelligent transportation systems (ITSs) evolve, there is a growing need for…