The self-excited oscillation of an electro-hydraulic servo valve is a crucial factor that affects the operational stability of both the servo valve and the entire servo system. As the intermediary for electromagnetic force, hydraulic force, and feedback force, the dynamic characteristics of the armature assembly play a pivotal role in the emergence of self-excited oscillations. In this article, a mathematical model of the armature assembly is developed using the finite element method (FEM), which establishes a connection between the input signal and the dynamic characteristics of the armature assembly. The structure of the parameter matrix and the recursive relationship of discrete time steps are derived, while the discrete method of the feedback rod and the discrete time format of the FEM model are also analyzed to enhance the prediction accuracy of the model. To validate the efficacy of the FEM model, a numerical simulation model, a classical mathematical model, and an experimental platform are constructed to simulate or measure the dynamic characteristics of the armature assembly. Through the comparison of the dynamic characteristics obtained by the abovementioned methods, it is confirmed that the FEM model effectively predicts both the static and dynamic characteristics of the armature assembly. To suppress the vibration magnitude within the natural frequency range of the armature assembly, the external load that can effectively mitigate the resonance amplitude is calculated based on the FEM model, and the aim of ensuring the stable functionality of the armature assembly throughout its operational range is achieved.

Underwater object detection is important for ocean exploration and marine applications. However, underwater images are often degraded by absorption, scattering, and background interference, which weaken object contours, blur boundaries, and obscure fine texture details, thereby increasing the difficulty of detecting small objects and objects with large shape variations. To address these challenges, we propose WEC-UOD, an underwater object detector that improves structure-sensitive representation learning and multi-scale feature fusion within the detector, without relying on a separate image enhancement stage. In the backbone, the Wavelet–Edge Collaboration (WEC) module first uses wavelet-subband guidance to compensate for degraded structural and texture information and then applies edge-guided spatial correction to refine object boundaries and local geometry. In the neck, the Scale-Selective Fusion (SSF) module adaptively selects informative responses from branches with different receptive fields and further suppresses background interference through channel and spatial recalibration. Experiments on RUOD and DUO show that WEC-UOD achieves mAP@0.5 scores of 87.4% and 86.9%, respectively, consistently outperforming the YOLOv11s baseline. These results demonstrate the effectiveness of combining structural enhancement with selective multi-scale aggregation for underwater object detection.

As a commonly used hydraulic control component, the nozzle-flapper servo valve has the advantages of small structure and sensitive dynamic response. Due to the small size and complex structure of the servo valve, the classical control methods based on various feedback information cannot effectively improve its performance. In order to effectively improve the performance of the servo valve, this paper implemented the feedforward control method to suppress the dynamic performance of the armature assembly of the servo valve. The distributed parameters mathematical models of the armature assembly are established and verified which can accurately predict the vibration of the armature assembly. With the mathematical model, the feedforward control signal is calculated based on the real-time velocity, acceleration, and deflection of the armature assembly, respectively. The applicability of different signals is analyzed and the signals calculated by velocity and deflection are verified which can effectively suppress the vibration amplitude of armature assembly. The numerical simulation and experimental methods are implemented to verify the performance of different control signals and the optimal feedforward control signal under different external loads is obtained.

Uniform and stable droplet generation is critical for accurate and efficient digital nucleic acid analysis (dNAA). In this study, an integrated microfluidic step emulsification device with wide-range droplet generation capability, small device dimensions, convenient fabrication strategy, low contamination and high robustness was developed. A tree-shaped droplet generation nozzle distribution design was proposed to increase the uniformity of droplet generation by equating flow rates, and the flow field in the design was numerically simulated. Theoretical analysis and comparative experiments on droplet size were performed regarding the influences of nozzle dimensions and surface properties. With incubation and hydrophobic reagent treatment, droplets as small as 73.1 μm were generated with multiplex nozzles of 18 μm (h) × 80 μm (w). The droplets were then collected into a standard PCR tube and an on-chip monolayer droplet collection chamber, without manual transfer and sample contamination. The oil-to-sample volume ratio in the PCR tube was recorded during collection. In the end, the droplets generated and collected using the microfluidic device proved to be stable and uniform for nucleic acid amplification and detection. This study provides reliable characteristic information for the design and fabrication of a micro-droplet generation device, and represents a promising approach for the realization of a three-in-one dNAA device under a step emulsification method.