摘要:To effectively suppress operating system virus propagation in the network, a time-delay propagation model and the suppression strategy of operating system virus are proposed aiming at the characteristics of operating system virus, such as strong target and delay of infection. Based on the SIRS model, a new state and the infection time delay are introduced. The time-delay model of the operating system virus is constructed. The equilibrium point and the basic regeneration number are given. The global stability of network system at the virus-free equilibrium point is proved by direct Lyapunov method. According to Hopf bifurcation theory, the threshold of bifurcation is calculated, and the Hopf bifurcation behavior is analyzed at the virus equilibrium point. To solve the oscillation in the case of too high infection time delay, the virus propagation suppression strategy is designed. The oscillation can be eliminated by fine-tuning the switching frequency of the operating system. When the number of infected nodes is stable, switching frequency of the operating system is renewed with reference to the basic regeneration number. to eliminate virus completely. The theoretical and simulation results show that when the basic regeneration number is less than 1, the network can be globally asymptotically stable at the virus-free equilibrium point. The network can eliminate the operating system virus relying on its own immunity. When the basic regeneration number is greater than 1 and the time delay is greater than the corresponding threshold, the number of infected nodes has periodic oscillation. It is difficult to determine the network environment at this time. The oscillation can be eliminated by fine-tuning the operating system switching frequency. When the basic regeneration number is greater than 1 and the time delay is less than the corresponding threshold, the network is locally asymptotically stable at the virus equilibrium point, and the network security situation is clear. At this time, the operation switching frequency can be adjusted according to the basic regeneration number to ensure network security.
摘要:In order to overcome the disadvantages of the computational fluid dynamics(CFD)method such as high computational cost and the inability to reuse the computational results, a steady prediction model of pressure and velocity fields for NACA0018 airfoil in α=2°-8°, Re=0.1×106-1.6×106 is established based on deep-learning method using 132 sets of two-dimensional flow data. The energy conservation equation of incompressible flow at low velocity is used as the constraint condition. Considering the correlation between lift drag and surface pressure, an activation function is proposed. The results show that for pressure field prediction the average error of the traditional neural network is about 2.77%, but for velocity field prediction that of the traditional neural network is 11% and the maximum is 26.993%, while the average error of the improved neural network is only 2.77%. Compared with the traditional activation function, the improved activation function neural network is more accurate in predicting airfoil velocity field and the flow field transition is more uniform. Compared with the traditional CFD method, the neural network can obtain the flow field in a few seconds, which can greatly reduce the calculation time.
关键词:neural network;deep learning;flow field prediction;multi task regression
摘要:Based on the experimental data of 10 air-cooled thick-wall ribbed channels with different structures, the comprehensive effects of channel aspect ratio(0.25-4), rib angle(30°-90°)and Reynolds number(10 000-60 000)on the flow and heat transfer performance of ribbed channels were analyzed. The empirical correlations about the channel friction coefficient and the average Nusselt number related to channel aspect ratio, rib angle and Reynolds number were fitted. The results show that the friction coefficient of the thick-walled ribbed channels increases with the increase of channel aspect ratio and rib angle. The average Nusselt number and comprehensive thermal coefficient both increase first and then decrease with the rib angle, and both have a fluctuating trend of increasing first, decreasing second, then increasing again and final decreasing with the increase of channel aspect ratio. At different Reynolds numbers, the maximum value of average Nusselt number occurs approximately at the channel aspect ratio of 1.75-2.75 and rib angle of 55°-65°. The highest comprehensive thermal coefficient occurs when the channel aspect ratio is about 0.75 and 2, and the rib angle is about 60°. The mean fitting deviation of the average Nusselt number correlation is 6.96%, and the mean fitting deviation of the friction coefficient correlation is 12.75%. The results may provide references for the cooling structure design of advanced gas turbine blade in the future.
摘要:In order to study the quantitative relationships of the rotor clearance and the number of rotor blades with the aerodynamic characteristic curve of the cam-type gas circulating pump, and to obtain the distribution rule of the radial excitation force of the rotor with different blade numbers, based on the symmetry principle, the arc involute arc rotor profile equations of 3 to 6 blades rotor are derived by using mathematical analysis method and coordinate transformation method, with five different rotor clearances selected to study. Based on dynamic mesh technology and RNG k-ε turbulence model, three-dimensional unsteady numerical simulation on the rotors with different blade numbers and clearances are performed. The influences of rotor clearance and number of blades on the flow rate/pressure characteristics and excitation force of gas circulating pump are revealed and verified by experiments. The results show that with the increase of rotor clearance from 0.1 mm to 0.3 mm, the average flow rate and volumetric efficiency of the rotor outlet with different blade numbers show a downward trend, and the three-blade rotor has the largest decline, decreased 0.009 4 kg·s-1 and 28.6% respectively. The three-blade and four-blade rotors have the lowest flow pulsation intensity when the clearance is 0.15 mm; and the five-blade and six-blade rotors have the lowest flow pulsation intensity when the clearance is 0.25 mm. The average flow rate and the average total pressure at the outlet are inversely proportional to the number of rotor blades. With the increase of the number of blades, the pressure distribution in the rotor cavity is improved, and the internal pressurization process is more stable. As the number of blades increases, the pulsation amplitude and intensity of the rotor radial excitation force component Fx are significantly reduced, but the influence of the number of blades on the rotor radial excitation force component Fy is not significant.
关键词:cam gas circulating pump;rotor clearance;aerodynamic performance;radial exciting force
摘要:Aiming at the actual constraints of existing spiking neural networks(SNN)for image classification such as high resource occupancy and complex operation, a new kind of discrete-time-scheduling based SNN model for image self-classification is proposed to find a kind of machine vision solution with weight reduction and high energy efficiency. The transformation from the gray image to pulse sequences is implemented with normalized difference of Gaussians and time-to-first-spike coding, and the self-classified network is realized via the combination of classical spike-time-dependent-plasticity algorithm and mechanism of reinforcement learning with feedbacks of reward and penalty. Simultaneously, the competitive mechanism and dual constraints are also introduced to ensure the sparseness of spike transmission and the specificity of learning features, which effectively inhibits the occurrence of overfitting. Compared with the traditional SNN classification models, the experimental results on the Face/Moto dataset show that the complexity of the weight updating algorithm is reduced form O(n2) to O(1) while the coding patterns of spike are simplified by nearly 90% and the trainable parameters of the network are decreased by over 60%; the weights nearly converge after 6 iterations, and the classification accuracy quickly rises from 40% to 90% and becomes stable after 20 iterations, finally reaches 93.4%; the accuracy can hold steady at 80% while the proportion of training samples drops to 40% of the original. The proposed model is beneficial for edge computing realization of high-efficiency and low-power minimalistic intelligent hardware terminals.
关键词:spiking neural networks;machine vision;spike time dependent plasticity;reinforcement learning;discrete time scheduling;edge computing
摘要:A novel serial united Reed-Solomon(RS)decoder is proposed to deal with the idle time that exists in the decoding process of pipeline united RS decoder. To eliminate the idle time in the pipelining stage, the timing chart of decoder is adjusted to a serial structure. Through the multiplexing design of decoding modules, a time-sharing mSPCF module is designed to realize different module functions. The mSPCF module could be utilized both in decoding random errors and single burst error. Then, a serial united RS decoder based on mSPCF module is proposed and the delay analysis of the decoder is carried out. Furthermore, the decoder is synthesized by SMIC 0.13μm CMOS technology library. The simulation results show that compared with the pipeline united RS decoder, the proposed decoder can reduce hardware resource consumption by about 9.4%. For decoding random errors and single burst error in the range of 6.2-7.4 dB SNRs, the average decoding delay can be reduced by 73.45% and 45.65%, respectively, and the throughput can be increased by 236.76% and 64.49%, respectively. In conclusion, the proposed serial united RS decoder has better performance and more advantages in practical applications.
摘要:To solve the problems that rate control in high efficiency video coding(HEVC)standard does not consider the inter-frame reference dependency when calculating the target bitrate allocation weight, and the coding efficiency is low, a picture level rate control method considering all of the inter-frame reference dependency for HEVC coded surveillance videos is proposed. A new distortion model for surveillance video is constructed following the investigation of the reference dependency between the coding frame and all of its referenced inter-frames in the low-delay structure of HEVC. Adopting the Lagrangian rate-distortion(R-D)optimization theory, the Lagrangian R-D cost function is established according to the constructed distortion model. The optimized bit allocation weights for pictures are solved from the R-D cost function, and a picture level rate control algorithm for surveillance videos is obtained. Compared with the rate control algorithm in HEVC test model using equal target bitrate allocation weights, the proposed algorithm achieves a more accurate bitrate estimation. Moreover, the Bjøntegaard delta-rate(ΔR)of the proposed algorithm can be reduced by 9.54% on average.
关键词:high efficiency video coding;rate control;surveillance video;all of the inter-frame reference dependency;target bitrate allocation weight
摘要:Aiming at the problems of pure lag, large inertia and variable parameter models in gas-fired power boilers, an improved particle swarm optimization(PSO)fuzzy generalized predictive control strategy for main steam pressure is designed. The main steam pressure model is identified by the forgetting factor recursive least squares method(FFRLS), and a generalized predictive control(GPC)is introduced to overcome system inertia, time delay and parameter time-varying via multi-step prediction, rolling optimization and real-time feedback technology. To improve the stability and dynamic response quality of the main steam pressure control system, the fuzzy self-tuning design of the control weighting coefficient in the GPC algorithm is carried out. Then an improved particle swarm algorithm is introduced to optimize the control variable increment of the generalized predictive control and obtain the optimal control law. Compared with the improved PSO-GPC strategy and the dynamic matrix control(DMC)strategy, the improved PSO-fuzzy GPC strategy reduces the stability time of model adaptation and mismatch by up to 94.5 s and 132 s respectively under disturbed condition. The overshoot is decreased by up to 5.1% and 8% respectively. Engineering application shows that the main steam pressure control deviation of the control scheme is lower than ±0.15 MPa, the system is less affected by model mismatch, and the stability and anti-disturbance ability are significantly promoted.
摘要:In order to accurately predict the primary frequency regulation capability of the power system, a method for predicting the primary frequency regulation capability of hydrothermal power systems using a deep belief network is proposed. System frequency, active load, power vacancy, disturbance type, load level, generator set inertia time constant, reserve capacity and total reserve capacity are used as input characteristic values of the network to provide data support for network parameter training. The combination of unsupervised pre-training and supervised parameter fine-tuning is used to train the network parameters, build a deep belief network, output the output adjustment curve of the system's primary frequency modulation to predict the primary frequency modulation ability of the hydrothermal power system. Compared with the traditional network model, the results show that: in the New England 39-bus system, the average relative error and root mean square error of the maximum power compensation are 1.49% and 4.04 MW, respectively. In the hydrothermal power system of the electric power company, the average error and the root mean square error of the maximum power compensation are 1.18% and 18.3 MW, respectively, which are smaller than the average error of 1.41% and the root mean square error of the cyclic neural network of 21.6 MW. Compared with the traditional network prediction methods, the layer-by-layer training of deep belief networks solves the problem of parameter optimization and avoids falling into local optimality and long training periods. This model can provide information support for the dispatch center to formulate protection and control failure strategies in the event of sudden failures.
关键词:primary frequency modulation capability;deep belief neural network;hydrothermal power system;prediction
摘要:In order to improve the meshing performance of spiral bevel gears, this paper proposes a design method of large contact ratio with contact path along tooth width. The auxiliary tooth surface of pinion is generated by using the wheel as the imaginary shaping and presetting the symmetric parabolic function of transmission error. The modification along contact path is firstly calculated, and then the modification of grid points on the tooth surface along contact lines is obtained according to the elastic deformation under light-load condition and the major semi-axis of the contact ellipse, superimposing both modifications on the auxiliary tooth surface of pinion to obtain the target tooth surface of the pinion. Finally, the machine-tool settings corresponding to the target tooth surface of the pinion are solved by the genetic algorithm. The numerical example shows that a large contact ratio can be obtained by designing the contact path along the tooth width, and the contact ratio is only related to the tooth width; the contact path along mid line of tooth width provides better meshing performance than along pitch line, which can avoid early edge contact. The tooth contact pattern is distributed along the tooth width direction, so as to avoid internal diagonal contact and reduce the relative sliding velocity between the meshing tooth surfaces, the tooth contact pattern moves along tooth height direction under the assemble errors.
摘要:In order to effectively evaluate the damage degree and detect the abnormal life cycle of gear drive system, a damage dynamic model of secondary gear drive system was established, taking into account the influence of the flexibility of drive shaft and the rigidity of bearing support on the response of the transmission system. In modeling, time-varying stiffness of gear mesh with different degree of damage is introduced in combination with finite element method, Newmark integration method is used to solve bearing vibration response under different conditions, and Lempel-Ziv complexity is used to evaluate gear running state. In terms of test, a gear damage degree evaluation algorithm combining variable mode decomposition(VMD)and Lempel-Ziv complexity is put forward to solve the problem of poor signal-to-noise ratio of collected signal. The results show that gear failure causes frequency conversion modulation of vibration signal in time-frequency domain, and with the increase of damage degree, the modulation phenomenon is more obvious and periodic impact is more significant; Lempel-Ziv complexity increases first and then decreases throughout the life cycle of gear, and Lempel-Ziv complexity is the most sensitive in early failure; VMD-Lempel-Ziv algorithm can improve the system in noise environment. An effective deterioration analysis is performed. The analysis results indicate the feasibility and validity of using Lempel-Ziv complexity index to measure gear damage. The research results can provide theoretical basis for gear boxes condition detection.
关键词:gear faults;degree of injury;time-varying meshing stiffness;variational mode decomposition;Lempel-Ziv complexity
摘要:To improve the stability of the mode switching process of the hydro-mechanical transmission(HMT), an HMT mode switching scroll coordinated control method is proposed. By analyzing the principle of HMT mode switching and establishing the switching process model, this method formulates a rolling coordinated control strategy based on model predictive control(MPC)for the torque of the mode switching mechanism and the displacement ratio adjustment of the hydraulic speed control system. Taking reducing the HMT output speed error and vehicle impact as the goal, a rolling coordinated controller with state constraints was designed. Simulation and test results show that, compared with the non-rolling coordinated control method, this method can reduce the output torque and speed fluctuation during the mode switching process; the dynamic load is reduced by 32.9%, the impact degree is reduced by 37.31%, and the mode switching time is reduced by 0.28 s. The displacement ratio adjustment makes the output speed basically consistent before and after the mode switching, which has a better control effect on the mode switching process and can greatly improve the switching quality. The research results provide a reference for the practical application of hydro-mechanical transmission device.
关键词:hydro-mechanical transmission;mode switching;model prediction;rolling coordinated control
摘要:To adjust the dynamic recrystallization related parameters for the hot rolling process of nitrogen-controlled 304 stainless steel, the material was subjected to hot compression experiments at different temperatures and strain rates. The results showed that as the temperature increases and the strain rate decreases, the dynamic recrystallization behavior is more likely to occur. The critical stress σc, saturation stress σs, steady-state stress σss and other characteristic values for dynamic recrystallization are determined by the second derivative of the stress-strain curve. Based on this parameters, the dislocation density evolution equation and Avrami kinetic equation are introduced, and the thermal deformation flow stress model and dynamic recrystallization kinetic model of the material are established. The calculated values of the hot deformation flow stress model are in good agreement with the experimental values. The dynamic recrystallization fraction curve obtained by kinetics model is consistent with the change trend of the grain structure observed in the experiment.
摘要:To solve the problem that high brittleness and poor toughness of bioceramics cannot meet the required mechanical properties of bone plate, a method for fabricating absorbable ceramics/polycaprolactone(PCL)composites with excellent strength, toughness and biocomp-atibility is proposed. The method combines digital light processing(DLP)3D printing technology and polymer infiltration method in which molten PCL was infiltrated into 3D printed porous ceramics to fabricate composite structure. The microscopic pore distribution of porous ceramics at different sintering times was studied and the effects of different infiltration times on the microstructure and mechanical properties of glass ceramic/PCL composites were investigated. The strengthening and toughening mechanisms of porous ceramics before and after permeation with PCL and at different permeation times were analyzed. Glass ceramic/PCL composite bone plate was prepared by the proposed method. The experimental results showed that the porous ceramics with higher porosity is beneficial to the infiltration process. The mechanical properties of the composites can be greatly improved by the infiltration of PCL. The compressive and flexural strength of the composites are significantly increased under the combined action of stress shielding and defect repair mechanisms, and the toughness of the composites is also improved due to the toughness of PCL and the crack bridging mechanism. Based on the experimental results, the mechanical properties of the composite material(strength and toughness)reached the optimum when the sintering holding time was 120 min and the infiltration time was 240 min, which provides a feasible scheme for the bio-absorbable bone plate.
关键词:absorbable bone plate;glass ceramic;polycaprolactone;composite material;mechanical property
摘要:A flexible capacitive sensor based on multi-layer(three-layer)dielectrics is proposed to measure finger joint angle with wide range and low threshold. The sensor consists of silicon rubber films and ionic conductors with excellent water retention. When a finger adherent the sensor is bent, the finger joint angle can be obtained from the change in capacitance induced by the strain. The strain sensing principle of the sensor is investigated with experiments and theory. The theoretical model to describe the relationship between input(finger joint angle)and output(change in capacitance)is proposed on the basis of the strain sensing principle. Then the quantitative relationship is verified by experiments, and the results are in a good agreement with the theoretical model. The results show that the sensitivity of the multi-layer sensor is 3.5 times higher than that of the single-layer sensor composed of a dielectric and two ionic conductors, and that this multi-layer sensor has the ability to measure the angles of the finger joint from straight to fully bended state with a resolution less than 1°. Therefore, this multi-layer sensor has the advantages of high sensitivity, wide measurement range and low threshold. It is beneficial to precise measurement of finger joint angles for the rehabilitation training patients and manipulator.
摘要:To improve the steering control accuracy and adaptability of robot-driven vehicle(UDRV)under different conditions, a sliding mode control method with particle swarm optimization(PSO)for the steering control of driving robot based on adaptive curve preview is proposed. Firstly, the dynamics models for the test vehicle and the steering manipulator of driving robot are established, then the two models are coupled together to obtain an integrated system dynamics model of the test vehicle manipulated by driving robot. An adaptive curve preview method is proposed, which can make adaptive adjustment for the preview point according to the curvature of the path and the speed of the vehicle. Based on the above, the sliding mode controller with PSO for steering manipulator of driving robot is designed, then the stability analysis is carried out. With the help of PSO, the feedback gain coefficient of the sliding mode controller's switch item is adjusted online to reduce the control chattering. The simulation and test results show that the proposed method can effectively conduct adaptive adjustment according to the path curvature and vehicle speed under different conditions, and the steering control accuracy of UDRV is verified.
摘要:To overcome the uncertain impedance boundary condition at the combustor exit, a coupling method of thermo-acoustic computation between combustion chamber and turbine is presented. Firstly, the thermo-acoustic network is used to solve the oscillatory behavior in the combustion chamber. Secondly, the actuator disk model is used to solve the propagation of entropy, vorticity and acoustic waves. Finally, inner and outer iterations are conducted to obtain the solution with the equivalent impedance at the interface between combustion chamber and turbine. The coupling method reflects the motion of entropy, vorticity and acoustic waves in both the combustor and turbine. The equivalent acoustic impedance, which is the implicit function of some geometrical and aerodynamic parameters of both the combustor and turbine, is clearly illustrated. Through verification with benchmark models and validation with experiment, the results show that the actuator disk model could accurately measure the equivalent acoustic impedance at the inlet of turbine. Moreover, the coupling strategy can judge about the occurrence of combustion instability, and accurately capture the oscillatory frequency and modes compared with decoupled strategy. The present result provides the theoretical basis for the extension of coupling strategy to high-order models.
关键词:combustion instability;thermal-acoustic network;actuator disk model;coupling