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.

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.

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.

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.

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.

An adaptive control strategy based on the general nonlinear relative motion equation was proposed by considering the uncertainty of the spacecraft rendezvous model. A parameterization via adaptive neural networks was implemented for the linear and nonlinear uncertainties in the complex nonlinear system caused by the external disturbances and the orbital parameters of the target spacecraft. Both the backstepping technique and the Lyapunov method were utilized to achieve the control targets and guarantee the asymptotic stability of the resulting closed-loop system. An auxiliary control system was proposed to analyze the effect of input constraints in order to explore the adaptive control design of the spacecraft relative motion in the presence of both model uncertainty and input constraints. The adaptive control strategy proposed for relative motion ensured the stability of the closed-loop system, as well as the uniform ultimate boundedness of the adaptive estimation of the unknown parameters. The effectiveness of the proposed method was verified by the numerical results via the analysis and comparison of different cases.

The structure scheme of heavy-duty intelligent stacking equipment was proposed aiming at the goods handling requirements of heavy duty, high precision, high reliability and long distance. The calculation method of the comprehensive stiffness of stacking equipment based on the calculation method of the contact force of V-type roller was proposed through the analysis of working principle and bearing force of stacking equipment. A calculation example of stacking equipment was given. The finite element method was used to solve contact stiffness of V-type guide rail and comprehensive deformation of stacking equipment compared with the theoretical calculation results. The accuracy of the theoretical method was verified. The structure of the gantry column and the three-level cargo fork was optimized by establishing optimization models for maximizing stiffness as optimization objective. The optimal structure of the column and the optimal section parameters of fork were obtained. The actual operation of stacking equipment was conducted, and its comprehensive deflections under static loads were tested. Results show that the optimized stacking equipment can meet the requirements of engineering applications.

Aiming at the difficulty of matching the special track structure and installation mode of the tram, a contour matching algorithm for embedded trough track was presented, in order to grasp the track status of tram lines in real time, and guide the line operation and maintenance more effectively. By analyzing the wear law and structural characteristics of the track, the matching reference area of the slotted rail was defined, and a automatic segmentation method of the region was presented. In order to solve the problem of the matching region locating, a two-step iterative closest point (ICP) matching algorithm was designed, which realized the exact matching of contour. The Kalman filter was used to predict the rotation and translation parameters to solve the problem of abnormal matching in special cases. The reliability of the algorithm was verified by actual line experiments. Experimental results show that the algorithm is fast, accurate and robust, and it can effectively overcome the matching difficulties caused by the special structure and embedded installation of groove rail.

Based on Navier-Stokes equations for incompressible fluids and magnetohydrodynamics (MHD) basic equations, a complete transfer function model for Hartmann flow of metallic fluid in a rectangular annular tube under current and voltage control mode were built up, and the effects of viscous force and boundary layer on the output performance of the momentum wheel were analyzed. By using the finite element simulation software COMSOL, the fluid motion characteristics and velocity distribution were simulated and verified. The influencing factors of output indexs, including current, magnetic field and characteristic parameters of the fluid, were totally analyzed. In current control mode, the angular momentum output scale factor of the momentum wheel is about 9.68×10^-5 N·m·s/A, which can provide the basis for the design and optimization of the momentum wheel.

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 semi-supervised Chi-square self-interactive detection decision tree (SSCHAID) and a semi-supervised back-propagation neural network (SSBPNN) were used for landslide susceptibility prediction (LSP) by taking the Nankang of Jiangxi Province as a case, in order to overcome the shortcomings such as insufficient landslide inventories, difficulty in expanding landslide inventories and subjectively randomly selected non-landslides have low accuracy. Based on the known landslides and randomly selected non-landslides, the initial LSP was divided into different levels by supervised machine learning. The high-resolution remote sensing image was superimposed with the very high susceptibility area in the initial landslide susceptibility map, and a certain number of potential landslide grids were selected to expand landslide inventories. Non-landslide grids were selected from very low susceptibility areas and combined into new output variables. The new output variables were imported into supervised machine learning to obtain the final LSP and evaluate its accuracy. Results show that the accuracy of LSP by semi-supervised machine learning is significantly higher than that of supervised machine learning.

An underwater image enhancement algorithm was proposed based on generative adversarial networks (GAN) and improved convolutional neural networks (CNN) in order to solve the problems of haze blurring and color distortion of underwater image. Generative adversarial network was used to synthesize underwater images to effectively expand the paired underwater data set. The underwater image was decomposed by multi-scale wavelet transform without losing the feature resolution. Then, combined with CNN, the compact learning method was used to extract features from multi-scale images, and skip connection was used to prevent gradient dispersion. Finally, the fog blur effect of the underwater image was resolved. In order to improve the color correction ability of the model and overcome the problem of color distortion of underwater images, the correlation between different channels of color images was learned by using the style cost function. Experimental results show that, in subjective visual and objective indicators, the proposed algorithm is superior to the contrast algorithm in comprehensive performance and robustness.

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 fault detection method combining the hoop nuts detector-net (HND-Net) and Mask_RCNN instance segmentation was proposed aiming at the problem of U-shaped hoop nut fault in the flat arm structure of high-speed railroad contact network. The proposed HND-Net target detection algorithm achieved the initial localization of the area where the U-shaped hoop of the flat wrist arm was located, and performed the pixel-level Mask_RCNN instance segmentation of the localized U-shaped hoop area in order to quickly obtain the precise localization and classification information of the four nuts of the U-shaped hoop of the flat wrist arm. The proposed segmentation algorithm achieved reliable fault diagnosis of U-shaped hoop nuts by using the obtained localization information. The experimental verification shows that the nut fault of U-type clamping hoop can be accurately located and detected in complex suspension images with good adaptability and high detection efficiency for shooting angle and shooting distance.

A shear horizontal corrugated steel plate concrete composite shear wall (CSPCW) was designed, in order to study the feasibility of rapid recovery of damaged corrugated steel plate concrete composite shear wall. First, a certain initial damage was applied to the CSPCW, then the damaged part of the wall toe was repaired and reformed to become a renewable corrugated steel plate composite shear wall (RCSPCW), and quasi-static loading was carried out. In order to verify the replaceable of the damper, the specimen was subjected to quasi-static loading again after replacing the damper when the interlayer displacement angle of RCSPCW reached 1.25%. Test results show that RCSPCW can concentrate the damage on the damper and improve the ductility and energy dissipation capacity of the shear wall. Moreover, the hysteretic curve of the specimen after the second damper replacement was fuller than that of the first damper replacement, which proves the feasibility of replacing the damper under rare earthquakes. ABAQUS was used to carry out numerical expansion analysis on the lateral stiffness of RCSPCW. It is found that the shear span ratio has the greatest influence and the volume steel content has the smallest influence.

A mixed integer programming model was constructed for parallel disassembly line balancing problem aiming at the problem that the task definition of each disassembly line is unclear and the mathematical models are conceptual models in the existing parallel disassembly line. The difference of operators between workstations was considered. The number of workstations, the number of robots, disassembly cost and idle time balancing index were minimized. An improved brain storm optimization algorithm was proposed. A feasible disassembly sequence was constructed through double-layer coding, and the original operation was discretized. A mutation and crossover mode was designed corresponding to the generation mechanism of a single individual and two individuals. The operation strategy of four-point crossover was designed in order to increase the diversity of population individuals. Pareto solution set and crowding distance were introduced to screen non-inferior solutions of multi-objectives aiming at the multiplicity of optimization objectives. CPLEX and LINGO were used to solve the exact solution of small-scale examples. The correctness of the model and the effectiveness of the algorithm were verified compared with the results of the algorithm. The algorithm was applied to solve P25 classic examples and compared with the results of many existing literatures. The superiority of the algorithm was verified. The proposed model and algorithm were applied to the parallel disassembly line of TV and refrigerator, and the advantages of the proposed algorithm were verified by different comparative experiments.

A wall-climbing quadruped robot for pipeline inner wall with negative pressure adsorption was investigated, which was used to detect the inside of gas insulated switchgear (GIS). The kinematics of the legs and body of the robot was analyzed, and an improved Newton iteration method was used to solve the complex problem of the body’s forward kinematics. The gait planning of the robot climbing along the axial and circumferential direction of the pipeline was carried out, and a zero-impact trajectory planning method was proposed. Adams was applied for motion simulation, and the omnidirectional wall climbing experiments of horizontal and vertical pipelines were carried out with the robot prototype. Results showed that the robot’s trajectory was consistent with the planned gait, and there was no sudden change in velocity and acceleration during the movement. The movement process was stable without noticeable impact. The correctness of the kinematic model and the rationality of the planned gait were verified. The robot was applied to the actual detection of the GIS pipeline, and the stable wall climbing motion and detection under different working conditions were realized.

To deeply understand the mechanism of flow induced noise excitation source of waterjet pump and to support the low-noise design of waterjet pump, the acoustic performance of a two-stage propulsion pump was researched. Based on the measured radiated noise under multiple rotational speeds, the modulation mechanism of flow induced noise of this waterjet pump and the extraction method of flow induced noise source were studied. The radiated noise of this two-stage waterjet pump was measured in a cavitation tunnel, and the cyclostationary analysis was conducted to demodulate and extract the characteristic frequency of the flow-induced noise source. The unsteady numerical simulation of the internal flow field of the two-stage propulsion pump was carried out to analyze the distribution characteristics of the transient internal flow field and the characteristics of three-dimensional exciting force. Combining the signal processing results with the internal flow field simulation results, the key characteristics and formation principle of the flow induced noise source of the propulsion pump were studied. Results show that the guide vane plays a key role in the radiated noise characteristics of the two-stage waterjet pump, and the modulation intensity is decided by the incoming flow conditions and operating conditions of the waterjet pump. The matching design of the impeller and guide vane takes a decisive position in the noise and vibration control of waterjet pump.

An efficient ShuffleNetv2 and YOLOv3 integrated network static gesture real-time recognition method was proposed to reduce the computing power requirements of the model on the hardware aiming at the characteristics of limited computing resources and small storage space under the mobile terminal platform. The computational complexity of the model was reduced by replacing Darknet-53 with the lightweight network ShuffleNetv2 as the backbone network. The CBAM attention mechanism module was introduced to strengthen the network’s attention to space and channels. The K-means clustering algorithm was used to regenerate the aspect ratio and number of Anchors, so that the regenerated Anchors size can accurately locate the target to improve the detection accuracy of the model. The experimental results showed that the average recognition accuracy of the proposed algorithm on gesture recognition was 99.2%, and the recognition speed was 44 frames/s. The inference time of a single 416×416 picture on the GPU was 15 ms, and the inference time on the CPU was 58 ms. The memory occupied by the model was 15.1 MB. The method has the advantages of high recognition accuracy, fast recognition speed, and low memory occupancy rate, which is conducive to the deployment of models on mobile terminals.

A novel technology of pre-heating the pulverized coal air flow before the pulverized coal entering the combustion chamber was proposed to reduce the cooling effect of the primary air on the furnace and accelerate the combustion of the pulverized coal. A shell-and-tube heat exchanger with finned plate that used heat transfer oil to preheat pulverized coal air flow was designed. A pilot scale test bench was constructed to experimentally analyze the effects of oil temperature, oil mass flow, air temperature, air speed, and coal-air mass ratio on the heat transfer characteristics of the system and the resistance characteristics of the test bench. The experimental results verified the technical feasibility of the heat exchanger using heat transfer oil to preheat the primary pulverized coal air flow. The proposed preheating technology had practical significance for environmental protection and energy saving. The experimental results showed that the heat transfer oil at 190 ℃ could preheat the pulverized coal air flow from 58. 4 ℃ to above 113 ℃ when the coal-air mass ratio was 0.15. The proposed preheating process was beneficial to improve the ignition performance of the pulverized coal air flow and promote the low-load stable combustion of the pulverized coal boiler.