Abstract:

Abstract: Due to the complex structure of parallel robot, the joint torque solved by the design parameters cannot drive the parallel robot to achieve the ideal position and pose. However, the pose accuracy of parallel robot directly affects the work quality. To improve the model accuracy of the parallel robot, the kinematic error model was established for the designed 3-RPS parallel robot. In addition, on the basis of the traditional differential evolution (DE), a competitive multi-mutation differential evolution (CMDE) algorithm was proposed to calibrate the model parameters. In this algorithm, two populations were designed for the local exploitation and global exploration, where each population contained three mutation strategies. Moreover, a competitive system was developed in each population to select the better strategy in the calibration process, which could obtain the best optimal parameters. The kinematic parameters by calibration were used to modify the inverse kinematics model, and the accuracy of the modified model was verified by Adams software. The simulation results show that the proposed CMDE could achieve 50% faster convergence speed and smaller final convergence value in comparison to DE method. Also, compared with PSO and DE algorithms, the proposed CMDE had the strongest anti-interference ability in the evolution process. Moreover, compared with calibration before, the improvements of 3-RPS parallel robot with three degrees of freedom were 73.5%, 88.7% and 95.2%, respectively.

Abstract: Remote sensing image super-resolution reconstruction based on deep learning is one of the most important methods in computer vision. The traditional super-resolution reconstruction method of remote sensing image could not meet the needs of ground object recognition, detailed land detection and other applications, This study aimed to solve the problem by using deep learning to reconstruct the resolution of remote sensing image. After reviewing the latest research status at home and abroad, this paper divides deep learn-based remote sensing image super-resolution reconstruction methods were classified into three categories, includeing single remote sensing image, multi-remote sensing image and multi-hyperspectral remote sensing image super-resolution reconstruction methods. The methods of super-resolution reconstruction of single remote sensing image based on deep learning were systematically examined, including multi-scale feature extraction method, combined with wavelet transform method, hourglass generation network method, edge enhancement network method and cross-sensor method. The current mainstream methods of multi-remote sensing image and multi-hyperspectral remote sensing image super-resolution reconstruction were also examined based on deep learning. Through the analysis of the experimental results, the best single image reconstruction method is based on GAN, but the effect of multi-remote sensing image and multi-hyperspectral remote sensing image reconstruction was still not good enough, there were several prablems, such as registration fusion, multi-source information fusion and other soon. Finally, the future development trend of remote sensing image super-resolution reconstruction method based on deep learning was explored, The future research trend could be building neural network structure according to the characteristics of remote sensing image, unsupervised learning remote sensing image super-resolution reconstruction method, and multi-source remote sensing image super-resolution reconstruction method.

Abstract: A permutation flow shop scheduling problem with machine availability was studied. An improved genetic algorithm was proposed by introducing CDS heuristic algorithm and local search so that the total weighted completion time and total weighted tardiness were minimized. To improve the quality of the initial job processing sequence group, the CDS heuristic algorithm is applied to generate 40% of the group and the remaining 60% of the initial job processing sequence group was yielded by random procedure. For the job processing sequence after crossover and mutation, three generation schemes of neighborhood solutions based on pair-wise exchange, single-job insertion and multiple-job insertion were designed to carry out local search in order to extend the search space. The proposed improved genetic algorithm was tested with three genetic algorithm based heuristic algorithms. The results showed that the target improvement rate of the proposed algorithm was 5.05%, 3.09% and 7.33% in the average 77.65 s, compares with other algorithms. It also showed that the proposed algorithm could obtain better target values in a shorter time. With the increase of the problem scale, the improvement effect was better.

Abstract: In order to solve the problem that enterprise could not identify key points of the increasing volume of vulnerability and repair them effctively, this paper proposed a model of vulnerability utilization prediction based on the decision tree algorithm, a boosting framework LightGBM (light gradient boosting machine). This model could predict whether there were exploits in a large number of security vulnerabilities or newly disclosed vulnerabilities, so that companies could give priority to such vulnerabilities. At first, studies related to the exploitation of vulnerabilities were reviewed. The exploitable vulnerabilities were found to complied with Baredo′s law, and the exploitable intelligence prediction of public vulnerabilities could be realized through machine learning algorithms. Then CVE vulnerability information in the past 5 a and vulnerability exploitation data obtained from mainstream vulnerability intelligence platforms such as Sebbug and Exploit-DB were collected, to extract relevant features, and construct a new set of data sets. Secondly, the vulnerability exploitation prediction work was integrated into two classification problems, and fully considered the actual working scenarios of the algorithm model and the ability of massive data processing. Algorithm models used in the field of network security were selected, including LightGBM, SVM, etc., and modeling learning was carried out. Finally, after many simulation experiments and parameter optimization, it was found that this model algorithm was superior to other models in terms of accuracy and recall rate, reaching 83% and 76%, respectively, indicating that the model had good prediction effects and application value. At the same time, the results of this paper could also provide certain construction ideas and data references for enterprise information security work.

Abstract: In order to reduce the intelligent cost in the enterprise, the hardware equipment with low cost and low computing power was used to detect the defects of products through the object detection algorithm model in deep learning. Based on the YOLOv5s network in target detection, this study adopts the idea of structure cutting, sparsely training the network based on the BN layer, and cuting the sparsely trained model corresponding to the layer with small weight value, so as to reduce the number of calculation parameters and the size of model file and to achieve the effect of lightweight. Finally, the trained pruning model was hierarchically fused using NVIDIA′s accelerated framework TensorRT to realize the reasoning acceleration effect. The experimental results showed that the weight file size of this model was reduced by about 70% compared with the original YOLOv5s model, and the detection accuracy on the public dataset NEU-DET reached 74.2%. In the high-performance experimental platform built in this study, the single graph inference speed was improved by 11.3% compared with the original model, and the network had no accuracy loss. In the low-performance experimental platform compared with the original network model, the inference speed of this model increased by 165%, which was more significantly improved than the results in the high-performance experimental platform, indicating that this model perform well in low computing power hardware devices. Then the model was tested by using the open top view data set of submersible pump impeller. At last, the inference acceleration framework TensorRT is used to accelerate the model in this study, and the inference time of single figure 5.8 ms can be achieved on the high-performance experimental platform. The experimental results showed that the inference speed of this model could be greatly improved on low computing power hardware equipment, which could help enterprises reduce their budget.

Abstract: Fluid motion in oxygenator has an important influence on its performance, but it is difficult to observe its internal hemodynamics directly. In order to understand the fluid movement characteristics in an oxygenator and predict its performance, this study analyzed the distribution of blood velocity, pressure and wall shear stress in a typical oxygenator through pressure drop experiment and CFD numerical simulation. The hemolysis performance of the oxygenator was evaluated by the hemolysis prediction model. The research results indicated that in the low flow range, the simulated value of the isotropic porous media model was the same as the experimental value，and the model could well simulate the flow of blood in the oxygenator fiber bundle，but with the increase of flow，the deviation increases gradually; the internal velocity of the compound oxygenator was in a gradient form; the internal pressure was concentric and uniform, and the pressure value was positively correlated with the flow rate. The porous medium area was the main area of pressure loss，accounting for 87% of the overall pressure drop; the high incidence of blood damage was located at the blood inlet and outlet. Under the experimental flow, the standard hemolysis index NIH was 0.049 2 g/100 L, which conformed to the general design requirements of oxygenator. The results were helpful for researchers to understand the influence of fluid motion characteristics on the performance of oxygenator, and could provide a reference for further performance improvement of oxygenator.

Abstract: In order to predict the performance of the designed radial inflow turbine in design and off-design conditions, the three-dimensional computational fluid dynamics (CFD) simulation of radial inflow turbine was carried out by ANSYS CFX. The effects of turbine inlet temperature, rotational speed and pressure ratio on its performance were analyzed, and the CFD simulation results were verified by experimental data. The results showed that under the design condition, the CFD calculation results were very consistent with the one-dimensional design parameters, and the relative errors of isentropic efficiency and output power were 0.36% and 4.85%, respectively. Under the design rotational speed, the isentropic efficiency reached maximum 77.6% with the inlet temperature was 368 K.The output power increased with the increase of inlet temperature, the isentropic efficiency had a slight change and had high output power when the turbine was operating at 0.9 to 1.1 of the rotational speed ratio. The pressure ratio had a great influence on the isentropic efficiency of the turbine. Meanwhile, the turbine could better deal with the change of pressure ratio when operating at the design rotational speed and design inlet temperature. Taking the pressure ratio, isentropic efficiency and temperature drop as evaluation indexes, the experimental data were compared with the CFD calculation results. The results showed that the maximum relative errors were less than 10%, which could verify the reliability of CFD numerical simulation for turbine performance prediction.

Abstract: When high-speed trains pass through or meet in the tunnel, complex compression and expansion waves will be generated. As the carbody cannot be completely sealed, the pressure inside the carbody will follow the changes, causing uncomfort problems for passengers. By establishing a numerical analysis model of the inlet and outlet flow field of high-speed trains, and on the basis of calculating the pressure waves on the surface of the vehicle, the change law of the internal pressure was studied by using the equivalent leakage hole as the interface for the pressure transmission inside and outside of the vehicle. And the calculation method of the dynamic air tightness index of the high-speed train was proposed. Firstly, the effects of slenderness and position on the interior pressure in the modeling of equivalent leakage hole were compared, and the accurate numerical model of the interior and exterior flow field with equivalent leakage hole was determined. Then, the computational fluid dynamics (CFD) model of high-speed train-tunnel intersection was established, and the flow field of high-speed train tunnel intersection was calculated, and the surface pressure wave of train was obtained. Finally, the external surface pressure wave was used as the excitation of the internal and external flow field of the model to calculate the internal pressure change. After fitting the data, the internal pressure change rate and dynamic airtight index were analyzed, and compared with the measured data in the literature. The results showed that the calculation results with slenderness greater than 1∶4 were more reasonable for the modeling of equivalent leakage holes. In the numerical model of air tightness of single vehicle, the location of leakage hole had little effect on the internal pressure. Most of the external flow fields of the train meeting in tunnel were in a negative pressure state, and only the head measurement points have positive pressure. The dynamic air tightness analysis model proposed in this paper could better simulate the pressure fluctuation inside the vehicle. The simulation result of dynamic air tightness index during train passing tunnel in the condition of 7.05 cm2 equivalent leakage area and 1 000 m long tunnel was 66.3, which was approximately consistent with the literature results.

Abstract: In order to explore the impact of hard turning process parameters of 18CrNiMo7-6 steel on work hardening and metallographic structure, PCBN tool was used to hard turning of the arc section of the 18CrNiMo7-6 steel funnel-shaped fatigue sample. The spindle speed n and the turning back ap and feed rate vf were carried out a as single factor experimental study. The surface hardness, work hardening depth of influence and microstructure of the samples under different process conditions were characterized by a microhardness tester and super depth of field 3D microscopy system. The research results showed that hard turning introduced a certain amount of work hardening to the arc segment of the funnel-shaped fatigue specimen, the depth of the hardened layer was 120～200 μm, and the degree of work hardening was 4.31%～8.27%. In the experiment conditions, with the increase of n, the degree of hardening of the sample first increased and then decreased, and the depth of the hardened layer did not change much; with the increase of ap, the depth of the hardened layer and the degree of hardening of the sample increased gradually; vf increased the degree of work hardening of the sample first and then decreased, and there was no obvious rule for the depth of the hardened layer; with the increase of the radial depth, the metallographic structure of the sample changed, and the hardness gradually decreased, and turning parameters had little effect on the metallographic structure of the surface of the sample; when n, ap and vf were 1 200 r/min, 0.15 mm and 50 mm/min, respectively, the surface of the sample softens, and the high-carbon martensite is transformed into a lower hardness tempered troostite. The finding of this study costed extra light on the formulation of hard turning process for 18CrNiMo7-6 hardened steel.

Abstract: In order to solve the problem of valve difference caused by multistage small air compressor, the check valve was applied to carry out flow distribution, the influence of one-way valve parameters on the displacement and pressure pulsation of swash plate compressors was studied, and the valve parameters and compressor speed were optimized. Firstly, the mathematical models of single cylinder of one-way valve and swash plate air compressor were established, and then the influence rules of speed and valve parameters on compressor exhaust volume and pressure pulsation were obtained by changing the rotational speed, spring stiffness and preload of inlet and outlet valves. At the same time, in order to reduce the pressure pulsation and improve the exhaust volume as the goal, the particle swarm optimization algorithm was used to optimize the multistage air compressor, the optimal speed and valve parameters being be matched for each stage of the cylinder were obtained. Then the overall speed was determined, and the optimal parameters of each stage of the cylinder valve were optimized when the speed was consistent. The results showed that the parameters of the inlet valve had a greater effect on the exhaust volume and pressure pulsation than exhaust valve. Increasing the spring stiffness and preload of the inlet valve would reduce the pressure pulsation and exhaust volume, while increasing the stiffness and preload of the exhaust valve would increase the pressure pulsation. In addition, the pressure pulsation of all cylinders was reduced by 26.5% and 36.1% respectively, and the displacement volume increased by 66.9% and 48.9%, respectively.

Abstract: In order to further explore the rheological properties of saturated clay, the fraction-order Merchant model modified by Koeller′s spring-pot element was introduced to describe the viscoelastic deformation of soil, and the non-Darcy flow equation described by non-Newtonion index was introduced to describe the pore water flow during consolidation. The one-dimensional rheological consolidation equation of saturated clay under semi-permeable boundary was re-derived. The numerical solution of consolidation equation was obtained by the implicit finite difference method. The effectiveness of the numerical method was verified by comparing with the results of degradation models in related literature. On this basis, the effects of the parameters of semi-permeable boundary, non-Darcy flow and fractional-order Merchant′s rheological model on rheological consolidation process were investigated. The calculation results illustrated that the increase of semi-permeable boundary parameter could accelerate the dissipation of pore pressure and settlement of foundation. In the parameters of the fractional-order Merchant model, the order of fractional derivative and the viscosity coefficient have more significant effects on the settlement rate of foundation, and the influence on the settlement rate of foundation is mainly concentrated in the middle and late stages of consolidation process. The ratio of modulus of Kelvin′s body to independent spring had a major effect on the consolidation process in the middle stage, and with the increase of modulus ratio, the consolidation process of foundation gradually accelerated. In addition, the consolidation rate of soil layer was delayed by non-Darcy flow, and the consolidation of layer was gradually slowed down with the increase of non-Newtonian index.

Abstract: In order to study the force change of the inclined column steel structure of the prestressed tie beam foundation during the construction process, a finite element analysis model was established by Midas Gen based on the entire construction process of a large site protection building. The calculated results of the model displacement were close to the measured data, which verified the correctness of the model. Through the real-time tracking calculation of the changes of internal force and foundation horizontal displacement in each stage of the structure, the analysis of the influence of the number of foundation beams, section size and prestress on the stress of the superstructure and the horizontal displacement of pile top, this study provided a reasonable scheme for foundation displacement control. The results showed that the number of foundation beams and section size had little effect on the stress of the upper structure; the horizontal displacement of the pile top decreased with the increase of the number of foundation beams, and the maximum reduction was about 60% of the design control value，but the reduction range of displacement decreased with the further increase of the number of tie beams; The change of the tie beam section diameter had little effect on pile top displacement. Increasing the thickness of beam could effectively reduce the pile top displacement. The pre-stress has a greater influence on the control structure stress and foundation displacement, the maximum reduction of critical section stress of inclined column was 20%; the foundation deformation would develop to the center of multi pile cap after prestressed tensioning, and the maximum change of foundation displacement was 140%, the prestress scheme could significantly reduce the risk of pile shear failure, and there would be more conducive to displacement control and structural safety.

Abstract: In order to examine the smoke exhaust effect of three mechanical smoke exhaust systems with different smoke outlet orientations, an FDS physical model was established by taking a smoke prevention zone of the car garage, and numerical simulations were carried out for the three smoke extraction systems. The flow field, temperature distribution, as well as the heat exhaust and smoke exhaust efficiency of the three smoke exhaust systems were compared. The characteristics of the three smoke extraction systems and the differences in the smoke exhaust effect were analyzed. The results showed that, from the perspective of flow field and temperature distribution, the flow field distribution of the three smoke extraction systems was quite different, but the temperature distribution was very similar. From the perspective of smoke exhaust efficiency and heat exhaust, the mechanical smoke exhaust system with the exhaust port upward was about 4% higher in the exhaust efficiency and about 10% higher in the heat exhaust than the system with the opening downward. From the perspective of the change of exhaust heat when the height of the exhaust port was different, for the smoke exhaust system with the downward opening, the heat exhaust increased significantly with the increase of the height of the exhaust port, while the smoke exhaust system with the upward opening, the heat exhaust increased not obviously with the increase of the height of the exhaust port. For the smoke exhaust system with the upward opening, when the height of the exhaust outlet was lower than 4.5 m, the smoke exhaust efficiency increased gradually with the increase of the upward height of the smoke exhaust outlet. However, when the height of the exhaust outlet exceeded 4.5 m, the smoke exhaust was disturbed by the ceiling due to the short distance between the smoke exhaust outlet and the ceiling, which led to the smoke exhaust efficiency reduced.

Abstract: In order to solve the problem of random noise in the measuring vibration displacement signals of the discharge guide wall, multi-scale permutation entropy was introduced to reduce the noise of the vibration signal of the discharge guide wall. A signal denoising method based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN) and multi-scale permutation entropy(MPE) was applied to discharge structures. The vibration signal of the guide wall was decomposed by CEEMDAN to obtain a series of intrinsic mode functions (IMFs)，and then the multi-scale permutation entropy (MPE) was introduced to analyze the randomness of each IMF，and MPE value was used as the evaluation index to screen them into noise-dominant IMF and real IMF. The wavelet threshold denoising method was used to denoise the noise-dominant IMF. The processed data was reconstructed with the remaining real IMFs to obtain the pure guide wall vibration signal. The results of simulation signals and engineering examples showed that this method could improve the noise reduction effect of the signal,accurately remove the noise in the vibration signal of the discharge guide wall，and retain the characteristic information of the vibration signal effectively,it had certain feasibility . The noise reduction results of this method could be used as a reliable basis for the safety monitoring of the discharge guide wall, and could be applied to the noise reduction of similar vibration signals of the guide wall.

Abstract: In view of the problems that traditional chemotherapeutic drugs used in current electrochemical therapy have large toxic and side effects on human normal tissues, and traditional Chinese medicine ingredients have little toxic and side effects on human body, but have weak effects. Eicosapentaenoic acid (EPA), a monomer component of traditional Chinese medicine, was selected as an anticancer drug to explore the promoting effect of microsecond pulse electric field on the cytotoxic effect of EPA, and the toxic effect of the combination of the two on lung cancer A-549 cells. Firstly, the permeability of cell membrane under the action of pulsed electric field with different electric field strengths, and the effects of different drug concentrations (50—1 000 μmol/L) and electric field strengths (750—2 000 V/cm) on cell activity were studied. PI staining was used to detect cell membrane permeability, and CCK-8 assay was used to detect cell viability. Then, according to the detection results, the electric field intensity range for subsequent experiments was selected to be 1 000—1 500 V/cm, and the EPA concentration range was 100—400 μmol/L. Finally, the electric field combined with the drug group was set as the experimental group, the blank control group, the pure drug group, and the pure electric group were set as the control group. The experimental study on the cytotoxicity of pulsed electric field combined with EPA on A-549 cells was carried out, and the changes of A-549 cell viability at 24 h (48 h) after the combined action of pulsed electric field and EPA were compared and analyzed. Research shows that microsecond pulsed electric field could significantly enhance the toxic effect of EPA on A-549 cells, and when the concentration of EPA was 300 μmol/L, the combined effect of pulsed electric field and EPA was the best. The enhancement effect of microsecond pulsed electric field on EPA cytotoxicity could reach more than 40%, which provided an important promotion method for the subsequent intervention of traditional Chinese medicine ingredients in the treatment of cancer.

Abstract: As a key in the construction of power Internet of Things, intelligent converter station. faces the problem of insufficient data sharing and fails to fully explore the value of data. Therefore, based on cloud-edge collaboration, this study proposed a data interaction method for the construction of intelligent converter station. Firstly, based on edge computing and container, an edge Iot agent model was proposed, which aimed at the shortest time delay. It used the local universal server computing resource allocation strategy based on weight algorithm. On this basis, the cloud-side collaboration strategy was determined to minimize the time delay. It used the unloading strategy of edge computing tasks to cloud based on task size. Finally, taking the converter station monitoring system in Henan province as an example, the oil chromatographic instrument APP is eventually developed through the local data pretreatment and remote data analysis and mining. The data is firstly pretreated by the station edge Iot agent and then uploaded to the remote cloud platform. The integrity of the data transmission rate and accuracy were 100%. The data transmission delay was controlled in 150 ms with the float up and down in 15 ms. The performance meets the requirements of practical engineering application and verifies the accuracy of the proposed scheme. The method proposed in this paper enables professionals to timely and accurately grasp the transformer operation situation in the station, also improves the stability and safety of the converter station operation, and enhances the data value.