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After running for a long time, isolator switches are prone to be covered with dirt and corrosion. Switch cleaning is necessary for good operation and safety. Laser cleaning technology for rust removal is emerging in recent years. This paper introduces the technical principles of laser cleaning for rust removal in detail, designs a specific process scheme and takes a steel plate sample cleaning and rust removal as a case. The application effect of laser cleaning and rust removal technology is tested and shows that the technology analyzed in this paper can play a great cleaning effect without damaging the equipment base.

The timely and regularly clean for long-time use disconnecting switches are important for prolonging their lifetime. Laser cleaning for metal rust has the advantage of zero pollution. Fast speed and parameters can be adjusted to various sites. This paper introduces the development of laser cleaner for rust on disconnecting switches. Comparing results under different parameters in labs and sites, this paper concludes that when the laser power is 20W and the scanning speed is 2500mm/s, the device has a better cleaning effect.

Wire-based in-situ additive manufacturing (AM) technology is famous for the integration of material preparation and structure manufacturing. In the current study, the simulation method was adopted to study the thermal-stress evolution behavior during the process of the in-situ AM Ti-22Al-25Nb component. A single-layer multi-pass component was deposited firstly to prove the credibility of the simulation model. Then, the temperature-stress field evolution of the multi-layer single-pass component was revealed and analyzed systematically. This research is of great significance for suppressing the generation of cracks during forming process and promoting the wide application of Ti-22Al-25Nb alloys.

Electron beam directed energy deposition (EB-DED) is a promising and efficient additive manufacturing technology, but the vacuum environment challenges the in situ parameters monitoring. In this paper, an in situ beam current monitoring method is developed based on the absorbed electrons. A series of experiments show that there is a linear relationship between the absorbed electron current and the impinging beam current. However, this relationship only holds when the beam power density is relatively low. When the power density is high, the absorbed electron current will be lower than the theoretical value determined by the linear relationship. This is mainly due to the massive generation and ionization of metal vapor. The critical power density depends on the melting point of the material. Nonetheless, the deviation of the absorbed electron current at high power density can roughly determine the relative position between the focal spot and the workpiece surface. In addition, the slope of the linear relationship is material-dependent, so this method can also distinguish different materials.

In this paper, an automatic calibration device for multi-channel resistance strain gauge indicator is designed and its applicability and measurement accuracy are verified at laboratory. The calibration done by original resistance bridge calibrator is time-consuming for its manual operation and complex calibration process. With the intent to increase calibration efficiency, an automatic channel switch device was developed, and the resistance bridge calibrator was automated. The designed calibration device is completely computer controlled enabling a sequence of unmanned measurements. The calibration device was verified at laboratory that the maximum of error is 0.072%. It was applied to calibrate a 60-channel resistance strain gage indicator to approve its practical applicability. The result shows that the designed calibration device can realize automatic calibration and the efficiency is increased by 40%.

As the scale of software and the complexity of programs continue to grow, it is hard to meet development of modern computer technology only by manually extracting program features. In recent years, deep learning has achieved rapid development in different fields. Program representation learning based on deep learning has been widely used in many works, such as software vulnerability analysis, program analysis and malware detection. And it has gradually become a hot research direction in information security. After the deep analysis of existing research work on automatic program security detection, we catalog deep program representation learning for program security based on data representation and provide a comprehensive overview of deep program representation learning for program security under different application scenes. Then, we propose a deep program representation learning framework for program security. Finally, we conduct comparative analysis and summarize the challenges in deep program representation learning for program security.

The continuous improvement of national economic level makes people more and more demanding on machining. The key to realize the task optimization scheduling of machining system is manufacturing development. Machining process is a typical manufacturing process. The mechanical processing system transforms raw materials or semi-finished products into finished products or parts with qualified shape, size and precision through machining process, and consumes a lot of energy and material resources, and produces a large amount of waste materials, noise and other environmental emissions. Electromagnetic compatibility plays an increasingly important role in today’s scientific research and national defense. In the field of electromagnetic compatibility, electromagnetic compatibility analysis and electromagnetic compatibility prediction are important methods for electromagnetic compatibility research at present. Using software technology to deal with analysis and prediction is a general method, and entity modeling is an essential part of EMC simulation software.

In order to obtain the accurate spatial position reconstruction of the drilling bit wear surface, a drilling bit posture measurement system based on visual encoder is proposed in this paper. A tool clamping device with adjustable posture is designed for 3D digital microscope to hold the drilling bit with outer diameter within 6-8mm. The adjustment of the spatial posture of the drill bit is completed by the cooperation of two rotating discs whose axes are perpendicular to each other. The shaft of the vertical rotating disk is consistent with that of the encoder, and its rotation angle is used as the reference and measured accurately. The experimental results show that the angle detection accuracy is 0.1 degree. The accurate angle information provides the basis for the machine.

Multi-agent trajectory prediction is one of the core modules of unmanned driving and intelligent robots. The traditional method is difficult to measure the relationship between multiple agents, and the modeling ability is rigid. Nowadays, most of the methods make less use of geographic information, and social relationship modeling is not sufficient. Our model uses Graph Neural Network (GNN) to measure social relationships to improve its usability. The model is built by the basic Conditional Auto-encoder (CVAE) framework, using Gaussian Mixture Model to mix multiple Gaussian distributions and the possibility of obtaining more potential space through dynamic integration to make the model achieve better results. Our model has achieved excellent results on the Stanford Drone Dataset. The evaluation by average displacement error (ADE) and final displacement error (FDE) metrics has exceeded the majority of existing models.

The simulated p-nitrophenol (PNP) wastewater was treated by micro-electrolysis. The Box-Behnken experimental design model in response surface method was adopted with iron-carbon as a micro-electrolytic filler. Factors such as iron chip dosage, initial pH value of solution and reaction time were used as investigation indexes to study the influence of single factors and their interactions on the PNP wastewater removal rate. The final optimization results show that the experiment has a good removal rate of PNP, with only a small difference from the predicted value. It can be seen that the response surface method is feasible and suitable forthe process optimizion of p-nitrophenol wastewatertreatment by micro-electrolysis, which can be applied to engineering practice through further research and improvement.

In order to further improve the infrastructure management level of power grid projects and promote the fine management and scientific organization of power grid projects. Based on the basic framework of digital power grid, this paper uses UAV remote sensing, geographic information system, 3D virtual simulation, mobile Internet, Internet of things, intelligent sensor and other technical means to build a intelligent management and control platform integrating monitoring, early warning, command and emergency response. Exploring the application scenarios in terms of project schedule, quality, safety, special project, and on-site Internet of things perception. Practice shows that the construction of the platform can effectively improve the overall control of the power grid construction site and all kinds of information control level and risk prevention and control capabilities..

Low-cycle fatigue (LCF) behavior of a novel near β titanium alloy Ti-6Mo-5V-3Al-2Fe (wt%) with various types of secondary α phase was investigated. Results indicate that No.1 microstructure containing crossed and fine intragranular α, as well as discontinuous GB α, is obtained through low temperature (480 °C) aging treatment. No.2 microstructure containing parallel and coarse intragranular α, as well as parallel WGB α, forms after high temperature (600 °C) aging treatment. Under all strain amplitudes, stress amplitudes and LCF life of the samples with No.1 microstructure are higher than those of the samples with No.2 microstructure. For the samples with No.1 microstructure, more and deeper secondary cracks and dimples form in fatigue crack propagation and fast fracture regions, respectively. Such fatigue fracture behavior reflects a longer LCF life.

Since most of the traditional elderly assistant system cannot achieve remote control and send immediate notifications to their families when falling of the elderly occurs, a somatosensory interactive and remote controllable elderly assistant & custody system is designed and realized based on Kinect and Gizwits in this paper. Old people’s falling can be detected via the depth images and skeleton information captured by Kinect sensor and notified to their family members through web service. Remote control of the simulated smart home appliance through the mobile APP can be achieved via Data Points set in Gizwits cloud platform. Because of the remote control of the domestic appliance and accurate identification of falling-down action, the presented system can provide the elderly people with great convenience and ensure their living safety.

At present, the research on the performance of CFRP reinforced concrete structures at home and abroad mainly focuses on the ductility of individual members, especially FRP reinforced beams and columns, while the research on the ductility and seismic performance of FRP reinforced concrete frame structures is relatively less. Firstly, the finite element model of the shaking table test scale model of CFRP reinforced concrete frame structure is established by using SAP2000 finite element analysis software. Then, the non-linear dynamic time-history load condition is defined for the model, and the dynamic elastic-plastic time-history analysis is carried out to obtain the acceleration response and displacement response of the model under different levels of earthquake. The results show that the CFRP reinforced concrete frame structure is damaged and its stiffness deteriorates seriously. The lateral deformation of the structure is mainly caused by the bending deformation of the beam and column, while the lateral displacement of the column caused by the axial deformation is relatively small.

In this project, we combine Ga+ focused ion beam (FIB) patterning and self-assembly of InGaAs quantum dots in order to produce regular quantum dot (QD) arrays. The GaAs substrate is patterned before transporting into molecular beam epitaxy growth chamber to do anneal and overgrowth. The thickness of deposited InAs is precisely controlled. Quantum dots are expected to nucleate at specific locations, where the ion beam has previously implanted gallium atoms. The properties of the quantum dots formed are related to the FIB beam parameters, which include accelerating voltage, probe current, dwell time and pitch. We studied and statistically analyzed the relationship, focusing on their diameter, height and distribution. Scanning electronic microscope (SEM) and atomic force microscope (AFM) images have been used to analyze the patterns and QDs before and after overgrowth. Micro-PL study was performed to test the QD opto-electronic property. Scanning transmission electron microscope (STEM) cross sectional analysis and X-ray mapping is performed.