The high chemical activity, low thermal conductivity, and high strength of titanium alloys lead to severe tool wear during cutting. The coating applied to the tool surface insulates the effect of heat and chemical reactions. TiAlSiN coating and AlCrN coating are two representative coatings with excellent properties in TiN-based and CrN-based applications, respectively. Three types of nanocoatings—TiAlSiN monolayer, AlCrN monolayer, and TiAlSiN/AlCrN multilayer—were prepared, and the microstructure, mechanical properties, oxidation resistance, diffusion properties with titanium alloy, and cutting performance of the coatings were investigated utilizing SEM, TEM, XRD, TGA, GD-OES, nanoindentation, and scratching instruments. The hardness, elastic modulus, and adhesion strength of TiAlSiN/AlCrN multilayer coatings are between TiAlSiN monolayer and AlCrN monolayer coatings, which meet the “law of mixtures”. Adhesion strength is the primary condition for cutting applications and should have a minimum threshold value. Ti and N elements are the most significant in the diffusion between coatings and titanium alloys. The nitride coating containing Cr aggravates the loss of N in contact with the titanium alloy. In addition, multilayer structural coatings can lead to more severe diffusion than monolayer coatings due to their inherent interlayer defects. Although diffusion between titanium alloys and coated tools is more severe than with other workpiece materials, the main factor affecting tool cutting life is still the H³/E*² value determined by the hardness and modulus of elasticity together.

In extremely dark conditions, low-light imaging may offer spectators a rich visual experience, which is important for both military and civic applications. However, the images taken in ultra-micro light environments usually have inherent defects such as extremely low brightness and contrast, a high noise level, and serious loss of scene details and colors, which leads to great challenges in the research of low-light image and object detection and classification. The low-light night vision image used as the study object in this work has an excessively dim overall picture and very little information about the screen’s features. Three algorithms, HE, AHE, and CLAHE, were used to enhance and highlight the image. The effectiveness of these image enhancement methods is evaluated using metrics such as the peak signal-to-noise ratio and mean square error, and CLAHE was selected after comparison. The target image includes vehicles, people, license plates, and objects. The gray-level co-occurrence matrix (GLCM) was used to extract the texture features of the enhanced images, and the extracted image texture features were used as input to construct a backpropagation (BP) neural network classification model. Then, low-light image classification models were developed based on VGG16 and ResNet50 convolutional neural networks combined with low-light image enhancement algorithms. The experimental results show that the overall classification accuracy of the VGG16 convolutional neural network model is 92.1%. Compared with the BP and ResNet50 neural network models, the classification accuracy was increased by 4.5% and 2.3%, respectively, demonstrating its effectiveness in classifying low-light night vision targets.

With the rapid advancement of next-generation communication technology, traditional Quad Flat No-leads (QFN) packaging is facing challenges to meet functional requirements. Due to its high integration and excellent thermal performance, the Multi-chips Module combined with Quad Flat No-leads (MCM-QFN) packaging is gaining popularity. However, the structural complexity of MCM-QFN packaging and the thermal coupling effect between multiple dies make it challenging to analyze the steady-state thermal distribution of MCM-QFN packaging, which is necessary for assessing the reliability and optimizing the layout design of the multi-chips module. By analyzing the heat dissipation path from each die to the ambient, this paper proposes an analytical thermal resistance network model for calculating each mean die temperature of MCM-QFN packaging. The thermal coupling effect among the multi-chips, the thermal spreading resistance between critical layers, and the boundary conditions and cooling conditions are all considered. All thermal resistances in the model are expressed analytically, and the mean temperature of each chip can be calculated within 0.1 s using MATLAB programming. To validate the accuracy of the proposed model, finite element method (FEM) simulations are conducted to provide a reference for the mean temperature of each chip under four sets of thermal conditions. The data comparison demonstrates that the analytical model is fast and accurate in calculating each mean die temperature of MCM-QFN packaging, with a maximum error of 3.72%, and the calculation speed increased by about 600× compared to that of FEM simulation. Furthermore, the analytical model is able to offer a direction for optimizing the layout design and material selection of MCM-QFN packaging.

To bridge the gap that exists in the key equipment of the new subsea production control system, the all-electric subsea gate valve actuator, and exploit subsea oil and gas resources with high reliability and safety while saving energy, this paper proposes a novel concept prototype of an all-electric subsea gate valve actuator which has the key functions of a redundant drive, failsafe closing, auxiliary override, position indication, and low-power position holding. It satisfied the electrically-driven requirements of the subsea gate valves and achieved Safety Integrity Level 3. The prototype was developed and tested successfully. The all-electric subsea gate valve actuator is suitable for controlling subsea gate valves with various sizes and rated working pressures to minimize the power consumption for the purpose of keeping the valves open and safely closing them in the event of the electrical failure. An override and position-indicating mechanism is equipped for emergency operation and the visual indication of the status of subsea gate valves.

To bridge the gap in the research on the control and drive methods of the key equipment of the new subsea production control system, all-electric subsea gate valve actuator, and to solve the problems of the valve control and drive system in the traditional subsea production system, this paper proposed a full-featured and feasible electrical system of the all-electric subsea gate valve actuator containing the control system and the drive system. The key functions were realized, including status monitoring, redundant communication, redundant power supply, redundant drive, and low-power open-position holding. The electrical system is suitable for monitoring and controlling all-electric subsea gate valve actuators with various specifications and is highly integrated, open, efficient, and real-time. The electrical system prototype was developed and successfully tested for several functions. The results showed that the all-electric subsea gate valve actuator electrical system was capable of controlling and driving the actuator, monitoring the status information of the internal and external environment of the system, as well as the power output information of the drive system, and having redundancy features.