Weichai Power (China)

With advancements in simulation technology, fluid–thermal interaction (FTI) has become a vital tool in machinery powertrain development. Traditional engine cooling systems, with mechanically coupled components like water pumps and fans, lack adaptive cooling control. Electronic cooling systems, however, use variable-speed components to enhance performance. Combining FTI simulations with intelligent optimization algorithms offers a novel approach to designing control strategies for these systems. This study establishes a multi-objective optimization model for pump and fan speed control in electronic cooling systems. Using MATLAB/Simulink 2018 and Fluent 2022R1, co-simulations were performed, and an elite-strategy-based NSGA-II algorithm was implemented. Different weights were assigned to optimization objectives based on engine performance requirements. The results provide fitted functions for heat exchange capacity and cylinder liner temperature versus flow rates, along with optimal solutions for a 65 kW engine under three weight configurations. These findings support control strategy design and demonstrate the integration of FTI with genetic algorithms.

This study investigates how the Chishui River acts as a geographical barrier driving microecological divergence in Daqu. Utilizing qu-omics, this study investigated metabolic phenotypes, microbial community composition, and functional differentiation in Daqu from both riverbanks. Results showed significant geographical variations were found in volatile profiles and dominant genera (e.g., Kroppenstedtia, Aspergillus). Network analysis revealed that positive bacterial interactions increased from the right to the left bank, while fungal cooperation markedly decreased. Right-bank Daqu exhibited upregulated oxidative phosphorylation, starch, sucrose, and glutathione metabolism, driven by stochastic fungal assembly. Conversely, left-bank Daqu was characterized by enhanced purine, monobactam, and nitrogen metabolism under deterministic assembly. This study introduces the concept of “ecological isolation” to Daqu microecology for the first time. It highlights how geographical barriers drive functional differentiation, offering vital implications for the regional regulation of Baijiu quality.

In the customer service domain of the power industry, we propose an intelligent digital human framework developed on an optimized Wav2Lip model. The framework integrates multimodal interaction, speech-driven lip synchronization, semantic understanding, and dynamic decision-making technologies to transform traditional customer service processes. By leveraging these capabilities, the digital human not only achieves accurate user intent recognition but also exhibits natural and human-like interaction behaviors, thereby improving user experience and engagement. Experimental evaluations on multiple key indicators demonstrate the effectiveness of the proposed system. Results show that the framework achieves high speech recognition accuracy, fast response times, and timely feedback generation, highlighting its potential for practical deployment in intelligent power customer service scenarios.

Non-destructive testing (NDT) methods are increasingly applied in modern agriculture to enable the rapid, efficient, and non-invasive evaluation of crops and agricultural products. Among these, polarization spectroscopy analysis (PSA) combines polarization information with spectral data to provide detailed insights into plant and soil properties. This review summarizes the principles and key parameters of polarimetry and highlights PSA applications, including crop health monitoring, pest and disease detection, chlorophyll and nutrient estimation, seed quality assessment, and soil moisture and pollution evaluation. PSA demonstrates advantages over conventional spectroscopy by revealing structural information and maintaining robustness in complex environments. Its ability to support precision agriculture through the real-time monitoring and early detection of stress factors underscores its potential for smart agricultural systems. Future efforts should focus on data fusion, model optimization, equipment miniaturization, and enhanced adaptability to fully realize PSA’s role in intelligent agriculture.

Existing methods for stator ground fault detection in generator are unable to perform online measurement of winding ground parameters, accurately identify the nature of ground faults, or achieve precise fault localization. To address these limitations, this paper proposes a real-time measurement method for three-phase asymmetric ground parameters. This method is based on the fundamental and third harmonic components of the neutral point voltage, explicitly considering the inherent asymmetry of the stator winding's three-phase ground capacitance and conductance. This paper introduces a method for determining the fault phase and calculating the ground resistance. By constructing an evaluation equation for single-phase ground fault location in the stator winding, reliable positioning with a resolution down to the specific stator slot is achieved. Finally, the nature of the ground fault is accurately distinguished by performing a secondary measurement of the ground resistance value. PSCAD/EMTDC simulation results validate the reliability of the proposed methodology.