A novel method based on health index similarity in multiple time scales with autoencoder (AE MTS-HI) was proposed aiming at the shortage of the traditional similarity-based method in extracting health index and similarity matching. Autoencoder was applied to construct the health index based on monitoring data, which can minimize the loss of nonlinear information. The health index in multiple time scales was developed for similarity matching by considering the fluctuation of the length of test degradation trajectories. The method can remove the accuracy limitation caused by fixed time scales and enhance the prediction robustness. Performance of the proposed method was evaluated on public turbofan engines datasets. Results demonstrate that the method can improve the remaining useful life (RUL) prediction accuracy and provide stable support for predictive maintenance.

A front multi-vehicle target tracking algorithm optimized by DeepSort was proposed in order to improve the awareness of autonomous vehicles to the surrounding environment. Gaussian YOLO v3 model was adopted as the front-end target detector, and training was based on DarkNet-53 backbone network. Gaussian YOLO v3-Vehicle, a detector specially designed for vehicles was obtained, which improved the vehicle detection accuracy by 3%. The augmented VeRi data set was proposed to conduct the re-recognition pre-training in order to overcome the shortcomings that the traditional pre-training model doesn't target vehicles. A new loss function combining the central loss function and the cross entropy loss function was proposed, which can make the target features extracted by the network become better in-class aggregation and inter-class resolution. Actual road videos in different environments were collected in the test part, and CLEAR MOT evaluation index was used for performance evaluation. Results showed a 1% increase in tracking accuracy and a 4% reduction in identity switching times compared with the benchmark DeepSort YOLO v3.

The data is easy to be tampered and the access control of data is not flexible in the Internet of Vehicles (IoV). A secure data sharing scheme based on blockchain and ciphertext-policy weighted attribute-based encryption was proposed aming at the above problem. In this scheme, roadside units jointly maintain the generation, verification and storage blocks to achieve distributed storage of data, which ensures the data from being tampered. Attribute-based access control ensures that only authorized entities can access the content of data on the blockchian. A hierarchical access policy formulation method based on multi-attribute was proposed to reduce the complexity of access control policy aiming at the data sharing requirements among the multiple entities and roles in the IoV, by mining the association of attributes in the roles for data access. Experimental results show that the proposed scheme can realize the secure storage and flexible access control of the data in the IoV, and the hierarchical access policy formulation method can effectively reduce the calculation and transmission overhead of vehicles, and meet the access requirements of multiple entities and roles in the IoV.

Traditional and new geotechnical engineering problems such as compressed air energy storage, intercepting water with compressed air, carbon dioxide sequestration and oil and gas underground reserve project are all involving air-water two-phase flow and stress coupling problems. For this engineering reality, based on the weak coupling theory of gas-water two-phase seepage and stress in unsaturated soil, a air-water two-phase percolation-stress coupling calculation program based on coupled TOUGH2 and FLAC3D was developed. The calculation program can simulate real air-water two phase flow, and can investigate the gas-water interaction of seepage process. The calculation program considers the direct interaction between gas-water two-phase seepage and soil skeleton deformation, reflects the process of porosity, permeability, capillary pressure and the change of soil physical and mechanical parameters, and achieve a more perfect gas-water two-phase seepage-stress coupling analysis. Furthermore, by comparing with classical drainage test and model test, it is verified that the program can accurately simulate the gas-water two-phase flow-stress interaction.

A garbage image classification method based on improved MobileNet v2 was proposed aiming at the problems of poor real-time performance and low classification accuracy of existing garbage image classification models. A lightweight feature extraction network based on MobileNet v2 was constructed. The parameter numbers of the model were reduced by adjusting its width factor, channel and spatial attention modules were embedded in the model to enhance the network's ability to refine features, a multi-scale feature fusion structure was designed to enhance the adaptability of the network to scale, and transfer learning was used to optimize the model parameters to further improve the model accuracy. Experimental results show that the average accuracy of the algorithm on the self built dataset was 94.6%, which was 2.0%, 3.4%, 3.2%, 2.3% and 1.2% higher than that of MobileNet v2, VGG16, GoogleNet, ResNet50 and ResNet101 models, respectively. The proposed algorithm achieved good performance in two public image classification datasets, CIFAR-100 and tiny-ImageNet. The parameter numbers of the model was only 0.83 M, which was about 2/5 of the basic model. The single inference on edge device JETSON TX2 took 68 ms, which proved the improvement of inference speed and prediction accuracy.

As the carrier transport layer in planar perovskite solar cells, metal oxide films have important influence on device properties. The requirements of metal oxide films for planar solar cells in the respect of the morphology, electrical, optical, chemical and thermal properties were systematically overviewed. Worthwhile, the materials characteristic and representative work involving the most promising metal oxide film work as electron transport layer or hole transport layer material were summarized. Research progress of adopting methods such as element doping of metal oxides, surface modification of film and design of composite metal oxide film to improving film mobility, minimizing surface defects and adjusting energy level were proposed. Moreover, the future requirement and the improvement direction of metal oxide thin film deposition technology were discussed after summarizing the advantages and disadvantages of the deposition technology. Finally, the application of low-temperature deposited metal oxide films in flexible devices was expected.

The full-coverage film cooling was analyzed for the high temperature area on combustor in order to prolong the service life of the micro gas turbine combustor. The effects of arrangements and outer ring expansion film holes on the film cooling and the overall performance of combustor were compared under the actual conditions based on the test of KJ-66 micro gas turbine. Results showed that the average overall cooling efficiency of the order arrangement was lower than that of the cross arrangement in the actual micro gas turbine model, but the comprehensive cooling effect was higher. The film cooling effect was gradually improved as the outlet diameter of expansion holes increased, but the uniformity of temperature distribution at the combustor outlet was decreased. The secondary flow into the mainstream was deflected due to the influence of the cooling holes at the back of the combustor, which can improve the effects of film cooling. The full-coverage film cooling has a good cooling effect on the combustor wall under actual combustion conditions. Expansion film holes can effectively improve the film cooling effects of the combustor outer ring.

The components of the aircraft assembly line and the business logic were analyzed, and a digital twin based modeling framework for the aircraft assembly line was proposed, in order to realize the real-time interaction and deep integration of physical space and information space in the final assembly line of aircraft manufacturers. The modeling and the implementation of the key elements of assembly line were elaborated from the six-dimensional perspective of “human, machine, material, method, environment, and measurement”. Correspondingly, the technical process of the three-dimensional visualization and the information integration platform of the aircraft assembly line was proposed. A three-dimensional digital model of the workshop was established in CATIA. Then, a virtual space was built up based on the browser-based framework and WebGL technology and the real-time mapping of physical entities to virtual space was achieved by collecting process data from the shop-floor. An aircraft final assembly line was taken as an example, the synchronous mapping between the assembly workshop and virtual visualization, webServices service and information query service were realized, which improves the assembly efficiency and can provide scientific references for manual decision.

A new three-port DC-DC converter and its decoupling control method were proposed, in order to reduce the coupling degree of different control loops of multiple power paths and optimize the dynamic performance of the integrated three-port DC-DC converter. Dual Buck/Boost and LCL resonant dual active bridge were combined by reusing primary switching units. Switch devices were reused in the converters and power density was improved. Power transmission between three ports was controlled flexibly by PWM and dual phase-shift control mode. Power was transfered with fundamental power factor of 1 based on LCL resonant characteristics. The working principle, control mode and harmonic performance of the converter were analyzed. A simple and effective decoupling control method was proposed according to the fundamental analysis method, which can effectively reduce the coupling degree of different control loops of multiple power paths and improve the dynamic response ability of the system. Finally, a 400 W experimental prototype was built. Control mode comparison test, typical working mode switching test and decoupling control comparison test were carried out to verify the feasibility of the converter and the effect of the decoupling control method.

The vibration detection technology of ball screws used in automobile braking systems was studied. The vibration detection method of ball screws was proposed and the vibration detection equipment was developed, according to structure, size and motion characteristics of ball screws used in automobile braking systems. The expressions of balls’ rotation and revolution velocities and frequency of balls passing through reversers were derived under the condition of nut rotation based on kinematics. Then, the axial and radial vibration of ball screws used in an electric power braking system was measured under the conditions of different nut rotation speeds. The time-frequency distribution characteristics of vibration amplitude were analyzed, and results showed that the measured ball screws had prominent magnitudes near the frequency of balls passing through reversers and its multiplication orders. Lastly, the vibration levels of ball screws were evaluated by using root mean square (RMS) values in octave bands, and the energy distribution characteristics of vibration were obtained in octave bands under different nut rotation speed conditions.

Aiming at the problem that the Coulomb and viscous friction model cannot really reflect the nonlinear characteristics of friction in the process of robot motion, an improved Stribeck friction model was used to describe the joint friction, and a method of model parameter identification based on the combination of hybrid genetic algorithm and cosine trajectory was proposed. First, different cosine trajectories were used to excite the robot joints, and the friction torque of the joints was determined using the known dynamic equations of the robot, so as to establish the mapping relationship between the robot joint velocity and the joint friction torque. Second, the simulated annealing hybrid genetic algorithm was used to identify the friction parameters. Finally, a multi-joint series robot was used as the research object, and the friction parameter identification experiments were carried out to verify the effectiveness of the proposed method. Experimental results indicate that compared with the traditional Coulomb and viscous friction model, the improved Stribeck friction model can reduce the calculation error of the joint torque by 17.7% to 33.6%, and can further improve the accuracy of the robot dynamic model.

In order to promote the transformation of industrial cyber security defense mode from static passive defense to active defense, and alleviate the contradiction between the serious shortage of security experts and the sharp increase of cyber security demands, a cyber security active defense system framework of digital twin system was built from the perspective of bionics, and then five kinds of key technologies focusing on active defense were proposed based on the digital twin security brain (DTSB), including security data interaction and systems collaborative defense based on cloud-edge collaboration, cyber security active defense model of parallel digital twin system, situation awareness of parallel digital twin systems based on digital twin security brain, active defense and control technical framework for digital twin system based on immune system, and anti-attack intelligent recognition of digital twin system based on artificial intelligence. A case study of a digital twin workshop was given to demonstrate the successful application of digital twin cyber security in smart manufacturing.

By simulating the atmosphere of NH₄Cl in coal-fired power plants, the rules that how NH₄Cl caused ash deposition to affect the heat flux density of the heat-transfer surfaces were studied. A drop tube furnace system was used to simulate the boiler tail flue, an oil circulation system for temperature control, a probe system for ash deposition, the temperature inside and outside of the probe was monitored in real time to obtain the heat flux density on the probe surface. NaOH, Mg(OH)₂, and Ca(OH)₂ were used as additives to study the removing effect of three alkaline hydroxides on NH₄Cl in the flue gas. Results showed that NH₄Cl had a weak adhesion ability to ash, and the decrease in heat flux density on the heat-transfer surface was mainly caused by the deposition of NH₄Cl. Among the three additives, Ca(OH)₂ could narrow the decrease of heat flux density on the top of the probe, reducing the ratio of the decrease to 3.61%, while NaOH could narrow the decrease of the heat flux density at the bottom of the probe, reducing the ratio of the decrease to 6.46%. Although Mg(OH)₂ could reduce the decrease of the heat flux density at the top of the probe, it would enlarge the decrease of the heat flux density at the bottom of the probe.

An algorithm of fractional frequency phase locked loop (PLL) output signal phase synchronization was proposed, in order to realize the phase synchronization of PLL on multiple transceiver chips or a single transceiver chip in a multi-channel radio frequency (RF) communication system. A selection algorithm of sampling points for phase accumulation was designed. The sampling points selected by the algorithm were used to accumulate the triangulation results of PLL’s output signal under sampled by reference clock and reference signal generated by NC oscillator (NCO), so as to eliminate the high-order harmonic component and reduce the error of the phase difference calculation result effectively. According to the size of the phase difference, the fractional frequency ratio of the input of delta-sigma modulator (DSM) in PLL was adjusted by feedback, so that the phase of PLL output signal was adjusted linearly, and the phase synchronization of multiple PLL output signals with reference signal was realized. The correctness of the algorithm is verified by simulation, and the phase error is 0.35 ° after the final phase synchronization, and the time required to complete the synchronization is 210 ms.

A six-degree-of-freedom model of the aircraft with unidirectional constraint on pavement was established based on the B737-800 aircraft. The simulation calculation of aircraft taxiing were carried out on the pavement with single and stochastic uneven excitation respectively. Results show that, under the single uneven excitation input, the vibration response of the aircraft no longer changes monotonously with the wavelength and amplitude of the pavement deformation and the aircraft taxiing speed but the deformation model of the pavement, which is significantly different from that without considering the unidirectional constraint of pavement. The sensitive band of different taxiing speed is not the same. Under the stochastic uneven excitation input, the time when the wheels disengage from the pavement increases with the deterioration of pavement roughness. When the international roughness index of pavement is 3 m/km and the aircraft taxis at a speed of more than 70 m/s, and the taxing distance of the wheel separated from the pavement accounts for more than 1/4. The main frequency of the aircraft vibration response becomes lower, and the high-frequency vibration is greatly attenuated, and the vibration energy is concentrated to lower frequency. Between the two indexes for evaluating the roughness of pavement, the vertical maximum acceleration of the aircraft’s center of mass increases compared with that without considering the unidirectional constraint, while the root mean square of the vertical acceleration decreases because the downward acceleration response is weakened by the departure of the wheels from the pavement.

Chitosan aerogel has good biocompatibility, non-toxicity, easy degradation and other excellent properties, which can be used as an ideal green oil adsorbent to effectively solve the major problems of oil leakage and pollution. The researching progress of new petroleum adsorbents based on chitosan aerogel was reviewed. Firstly, the advantages and disadvantages of traditional oil treatment methods and oil absorbents were compared and the superiorities of chitosan aerogels as oil adsorbents were summarized. Then the synthesis and modification methods of chitosan aerogels and their advantage as petroleum adsorbents were analyzed and summarized. Finally, the problems existing in the current research and the future research direction were summarized and prospected.

The researches on data security management and privacy protection technologies at home and abroad were analyzed and summarized aiming at current problems in blockchain security, such as unreasonable data management mode, unreliable data sharing scheme, smart contract vulnerabilities not easily fixed and incomplete privacy protection of multiple types of data. Various security problems and reasonable solutions in current blockchain systems were outlined from four aspects: data storage security, data privacy security, data access security and data sharing security. The challenges and future research directions of data security in blockchain were discussed. Some reference for the future work of researchers was provided in the field of blockchain security.

A continuous digital zooming algorithm mainly for dual-focal camera imaging system was proposed. The continuous digital zooming problem of dual-focal camera was divided into the feature transfer problem in the field of view of the long-focus camera and the texture repair problem outside the field of view of the long-focus camera. The texture information of long-focus camera image was used to restore short-focus camera image referring to contextual image restoration algorithm, and a similar network structure was used to reduce the visual difference inside and outside the field of view of the long-focus camera. Experimental results show that compared with other algorithms, the proposed algorithm can improve the quality of images, improve the problem of large gap between the texture details inside and outside the field of view of the long-focus camera, and has higher subjective resolution and better visual clarity. In addition, the algorithm has an obvious repair effect on the texture details outside the field of view of the long-focus camera and also performs well for the actual images.

In order to solve the problems of difficult equipment deployment, velocity measurement and river monitoring in flooding environment, a series of image velocimetry techniques from particle image velocimetry (PIV) to deep learning methods were outlined based on non-invasive, low-cost and efficient measurement means in conjunction with nearly ten years of research in the field of river monitoring. The mechanism and issues of river surface velocimetry were discussed in the sections of image acquisition, image analysis, and image post-processing. By comparing and summarizing the differences of each method, the requirement of the existing methods were proposed, aiming to improve the river flow velocity measurement efficiency.

The forecast ability of the conceptual model was evaluated by the lag and route method to solve the selection problem of appropriate forecast lead time for both black box and conceptual models with hourly time scale. With the same forecast lead time, the flood forecasting was carried out by using the Xin'an jiang model, soil moisture accounting and routing (SMAR) model, back propagation (BP) neural network and Elman neural network and the performance was analyzed according to the set pair analysis method. The forecast ability of the conceptual models was relatively stable in specific watersheds and was corresponding to the size of the watershed. According to the lag and route method, the forecast lead time values for Jinhua and Longquan watersheds were 7 hours and 3 hours, respectively. Results indicated that the BP model and the Elman model produced the best and the worst performance, respectively, for flood forecasting in Longquan basin under the same forecast lead time. Moreover, the Xin'an jiang model and the SMAR model produced the best and the worst performance, respectively, for flood forecasting in Jinhua basin. The set pair analysis method is able to carry out comprehensive evaluation from single criterion to multiple criteria, indicating that the method has better applicability and higher efficiency.