This paper aims to present a novel airflow-induced acoustic piezoelectric generator that can be used to solve the problem of insufficient power supply of modern intelligent fuzes. The sound waves induced by airflow are the key to power generation performance. It is proposed that an edge tone frequency equal to the acoustic mode frequency is a sufficient condition for evoked acoustic waves, and a design idea and scheme for a universal fuze power supply is provided. We establish the vibration model of the airflow-induced acoustic piezoelectric generator. According to the model, the experimental research on the power generation performance shows that the sound pressure frequency, vibration displacement frequency, and output voltage frequency are consistent. The model provides a design idea for a vibration sensor. At the flow rate of 100.8 m/s, the output power is 45.3 mW, which is much higher than the fuze power sources such as the magnetic backseat generator. Therefore, the airflow-induced piezoelectric generator can effectively solve the problem of the modern fuze less types of power supply and low output energy.

This paper aims at the power generation requirements of the fuze airflow-induced acoustic generator, analyzes the influence of structural parameters on the fluid power sound source, which is related to the power generation performance and use performance of the generator. In this paper, the orthogonal experiment method is used to study the sensitive parameters that control fluid dynamic sound sources. The results show that the annulus, the confronting distance, and cavity length can all have an impact on the sound pressure amplitude, and the sound pressure amplitude is most sensitive to the change of the confronting distance. However, the length of the resonant cavity has the most significant effect on the sound pressure frequency. The size of the annulus has a weak effect on the sound pressure frequency, and the confronting distance has almost no effect on the sound pressure frequency. The optimal combination scheme with the highest output power is selected according to the sensitive parameters. In addition, the empirical formula for the vibration frequency of the airflow-induced acoustic generator in the short resonant cavity was revised, and the influence of the annular gap on the vibration frequency was added, and the influence factor α = 0.3 was determined. The corrected frequency empirical formula has the smallest error between the theoretical value and the experimental value, and can be used as an effective method for estimating the vibration frequency. This provides a reference for the engineering design of the fuze airflow-induced acoustic generator, which has high military value and application prospects.

In order to reduce space occupation and improve reliability, the modularization and integration of micro switches and their components are a necessary path for development. In this paper, a scheme for an alloy metal inertial micro switch using 3D printing technology is proposed for an integrated design. The switch realizes the turn-on function by causing the deformable electrodes to undergo plastic deformation and make close contact with the outer sleeve under the columnar block extrusion. The influence of electrode structure parameters on electrode contact performance was studied by the orthogonal experimental method. And the best parameter combination scheme for the electrode was determined. The aluminum alloy switch and titanium alloy switch were processed by SLM (selective laser melting) technology. The plastic deformation of the 3D-printed titanium alloy electrode occurred later than that of the 3D-printed aluminum alloy electrode under the same impact. The aluminum alloy electrode underwent plastic deformation and realized stable contact with a response time of 5 µs when the impact load was applied with an amplitude of 627 N and a pulse width of 2.7 ms (simulating high acceleration), which meets the application requirement of the response time being no more than 20 µs. The feasibility of 3D printing technology in high-precision and complex-structure micro switch manufacturing was verified. The research in this paper will provide guidance and reference for engineering applications.

This paper proposes a dynamic compensation method for laser ranging based on pulse width for the miniaturization and high-precision requirements of the initiation device in precision-guided aircraft. The study aims to improve the measurement accuracy of the laser ranging unit in the initiation device system and ensure the accuracy and reliability of its fixed-distance initiation decision. The variation in echo pulse width is analyzed by studying laser echo characteristics. The pulse width and the detection distance exhibit an approximately linear negative correlation within the middle range of the applicable distance range. A dynamic compensation method is proposed based on a dual-correction approach using a static lookup table and dynamic compensation. This method establishes the mapping relationship between pulse width and distance deviation, and achieves distance correction by adding distance deviation compensation to the basic value from the static lookup table. The dynamic compensation system integrated with calibration and correction is designed and implemented, and the feasibility of the dynamic compensation method is verified by testing. The relative error between the calculated correction distance and the actual distance is small, and the average relative error is about 1.33%. The proposed method provides key technical support for the establishment of miniaturized and intelligent initiation devices.

To address the challenges of limited annotated datasets, strong demand for few-shot adaptation, and insufficient feature representation of traditional backbone networks in Mars rover onboard surface scene classification, this study proposes a classification framework that integrates a channel attention mechanism with meta-transfer learning. The work consisted of two main components. First, a dedicated annotated dataset for core Mars rover onboard surface scenes was constructed based on publicly available Mars Science Laboratory (MSL) Mastcam RGB imagery, providing a standardized experimental benchmark. Second, a classification model was developed based on ResNet50. Transfer learning with ImageNet pre-trained weights was employed to improve feature initialization, and an Squeeze-and-Excitation (SE) attention module was incorporated to enhance channel-wise feature representation. Furthermore, an appropriate activation function was selected under engineering constraints. Finally, a meta-learning strategy based on Model-Agnostic Meta-Learning (MAML) was introduced to improve adaptation capability in few-shot scenarios. Experimental results showed that the SE-ResNet model achieved a validation accuracy of 95.52%, representing an improvement of 17.41% over the baseline model. After integrating meta-transfer learning, the proposed SE-ResNet-MTL (SE-Enhanced ResNet Meta-Transfer Learning) model achieved accuracies of 90.5% and 91.5% in 1-shot and 5-shot tasks, respectively, outperforming traditional fine-tuning methods by 42.8% and 25.4%. These improvements were obtained with only a 5.47% decrease in full-dataset accuracy. Overall, the proposed method effectively balances full-dataset performance and few-shot generalization, providing a practical and efficient solution for Mars rover onboard surface scene recognition and other extraterrestrial visual tasks.