Momentum wheel is the key mechanical component for attitude control and accuracy maintenance of spacecraft such as satellite. Its micro-vibration seriously affects attitude stability and imaging accuracy of satellite. The non-uniform, non-continous geometric configuration and rotational effects will cause parametric excitation and load excitation of the structural system. For the dynamic model of the momentum wheel structural system with non-uniform characteristic parameters, the micro-vibration mechanism is studied by analyzing the disturbance of each matrix parameter in the dynamic equation. The simulation and experimental results show that there are fundamental frequency and high frequency excitation in the momentum wheel structure system, where the fundamental frequency is mainly from the dynamic load of the fulcrum, and the high frequency is from the bearing rolling; the local vibration of the rim will form the traveling wave.

For improving the braking synchronization performance of tractor and travel trailer during braking, a braking coordination control method based on longitudinal hook force estimation is proposed. Based on the analysis of the straight-line braking kinematics characteristics of the tractor-travel trailer, the straight-line coordinated braking model of the tractor-travel trailer is established considering the electromechanical coupling characteristics of the electromagnetic brake and the flexible connection characteristics of the ball-type tow hitch. Based on Kalman filtering algorithm, the observer for the longitudinal hook force of travel trailer is designed by using signal data obtained from low-cost sensors such as the speed/acceleration of tractor. By introducing terminal sliding mode variable structure control algorithm, the dynamic equation of the error between the estimated value of longitudinal hook force and the target value is established, so that the longitudinal hook force can follow the target value accurately, and on this basis, the brake synchronization controller for travel trailer is developed. Simulation and real vehicle test results show that the proposed estimation scheme can accurately track the state information of travel trailer, and compared to conventional control methods, the maximum hook force using the proposed control method is less than 3 kN during tractor and travel trailer braking, which effectively ensures the stability of both braking.

A geometric optimization algorithm is proposed based on velocity obstacle method to solve the problem of flight collision resolution and track recovery. We gave a rigorous mathematical description of the problem. Firstly, according to the relative position and speed relationship between the aircraft, the collision type and whether the conditions of each release strategy are met are determined, and the corresponding resolution strategy is adopted. After the collision was resolved, the plane resumed its flight on the original route. The model can effectively solve flight collision through geometric analysis and theoretical derivation. In addition, the track recovery point and the parameter solving process involved are given in detail. Finally, in the simulation, the algorithm chooses the collision resolution strategy independently according to different scenes. The results show that this method is simple and efficient, and the track recovery redirects the ownership to its original target waypoint without introducing new flight collision.

In view of the complicated system structure of current weapon equipment, the existing testability verification method based on the testability prior information of the equipment system is difficult to apply, and the testability verification method based on the testability prior information of the subsystem cannot process the prior information effectively, which lead to the low credibility of the testability verification results, so a three-dimensional Bayes network testability verification model for complex systems is proposed. The model can fully utilize the conditional independence contained in the various hierarchical structures of the equipment, effectively reduce the complexity of constructing the Bayesian network model, and at the same time integrate the prior information of each hierarchical unit. Through the given conditional probability learning method and G/M-H algorithm of the three-dimensional Bayes network, the underlying unit data can be integrated through the model to obtain the posterior distribution of the top-level testability indicators, and the top-level posterior distribution is further used to obtain the fault sample size. The results show that the model can fully consider the system structure of the complex system and the prior information of each hierarchical unit, and the posterior distribution of the testability indicators can be used to reduce the fault sample size of testability verification.

The cylinder block is the crucial part of the aviation piston pump, which can directly affect the function of aviation piston pump. In view of the drawbacks of long test period and lacking theoretical approaches, a method for fatigue analysis and life prediction of the cylinder block is proposed based on finite element method and linear cumulative damage theory. Firstly, the mechanical model of the cylinder block is established using theoretical mechanics and material mechanics, and the force analysis calculation is implemented on MATLAB. Then, the finite element model of the cylinder block is established on ANSYS platform in order to simulate the stress and strain. Further, the results of stress and strain are imported into nCode to find out the weak parts of the cylinder block and investigate the affecting factors of the fatigue life based on linear cumulative damage theory. Finally, the verification test is carried out. The result shows that the outer wall of the piston chamber near the side of the distribution plate is weak and prone to fatigue damage, and the damage part of the experimental pump is approximately coincident with the simulation, which can validate the correctness of method for the fatigue analysis and life prediction of the cylinder block. The study findings of this paper can provide guidelines for designing the cylinder block of compact piston pumps.

With the rapid development of graphic processing unit (GPU), the parallel computing technology could be easily applied in the numerical simulation of ultrasonic sound field based on compute unified device architecture (CUDA). The calculating efficiency could be greatly promoted by using the parallel computing technology. The theory of elastodynamic finite integration technology (EFIT) is illustrated in this article. An EFIT 2D ultrasonic sound field model with point source and absorption boundary in steel material is established by CPU, and on the basis of CPU code, the GPU model is built with parallel computing technology. The flow design procedure and parameter optimization method of GPU model are introduced, including the texture memory use, absorption boundary optimization and data transmission optimization. Based on the comparison of time consumption and average calculating efficiency, the efficiency promotion of EFIT model of CPU and GPU version are quantitatively analyzed. The result reveal that the EFIT model with GPU has much higher calculating efficiency. According to the comparison result, the calculation speed of EFIT model is promoted significantly with the parallel computing technology. And it has broad application prospects in complicated acoustic field simulation.

Anomaly events detection (AED) is quite important in space field for the complex space environment, difficult technology, high risk and strictly safe and reliable requirements. Since there are few space anomaly events samples and they are hard to obtain, it is necessary to carry out targeted AED. In order to prevent space accidents and find anomaly events that may lead to fault as soon as possible, a novel approach for space anomaly events detection based on generative adversarial nets (GAN) is proposed in this paper. Normal event samples are generated by normal GAN, anomaly event samples are generated by anomaly GAN. We proposed a reasonable algorithm to calculate the divergence of Euclidean distance between input events and simulated normal events generated by normal GAN, and Euclidean distance between input events and simulated abnormal events generated by anomaly GAN.As a result, abnormal events is detected accurately. The method is trained and tested using the Mixed National Institute of Standards and Technology (MNIST) database. The test results show that the key technical indexes, such as precision rate and recall rate of comprehensive evaluation index (F1) and precision recall curve (PRC), are at least 31% and 11% higher than the traditional variational autoencoder (VAE) method. In addition, we evaluated the method by collected data in real environment which simulated space audio data. The abnormal event detection performance is very good, which proved that the proposed method could detect anomaly event in real environments.

Nonlinear problem has always been an obstacle in dynamic analysis domain due to its complexity and high computational cost. This paper aims to present a simple, accurate and efficient nonlinear modal analysis method which can be applied to some common nonlinear systems, including Duffing system, dry friction, nonlinear material and so on. The kernel technique of this numerical method lies in establishing the variation law of the nonlinear modal parameters in function of modal amplitude:on the one hand, the steady-state problem is simplified into one-dimensional algebraic nonlinear problem, resulting in a significant simplification in numerical computation; on the other hand, the analysis of nonlinear modal parameters in function of modal amplitude provides a modal overview for the comprehension of system's nonlinear dynamic behavior. Following a description of the theoretical aspects and numerical simulation process of this method, it has been proven to be efficient in analyzing a Duffing system with real nonlinear mode, a dry friction system with complex nonlinear mode and a multi-physics system integrating piezoelectric material. A reduction method based on the proposed strategy is then presented, which is simple in mathematical form and efficient in numerical computations for analyzing large complex nonlinear systems. It has significant advantages in computational efficiency when combined with the mode synthesis method to solve the dynamic behavior of large complex nonlinear systems.

To solve the instability of the path planning system caused by vehicle driving data loss and lag, a novel real-time regional path decision method based on the cooperative vehicle infrastructure system (CVIS) was presented in this paper. Firstly, the current road section resistance value was calculated dynamically through acquiring the real-time driving data of connected vehicles, combing with the traffic signal timing and path steering information, and considering the non-free flow situation which vehicles may encounter when passing through the intersection. Secondly, the travel time of each alternative route was predicted in real time according to the current road resistance statistics and the road network topology structure. After that, the predicted route with the least travel time was selected as the optimal vehicle driving path. Finally, the typical regional road network data of Wangjing area in Beijing was selected as the test scenario. 150 sets of tested results show that the average travel time in different periods of the optimized route obtained by this method is 9.52 seconds, 13.39 seconds and 20.65 seconds shorter than recommended route of the navigation system respectively, which proves the feasibility of the proposed method.

The drive-control modes of multi-phase permanent magnet synchronous motor (PMSM) consist of the redundant mode and fault-tolerant mode. To research the difference of multi-phase PMSM performance caused by drive-control modes, a redundant PMSM system and a fault-tolerant PMSM system are built respectively based on a six-phase PMSM. On this basis, the influence mechanism and influence law of the redundant and fault-tolerant drive-control modes on the six-phase PMSM system performance are studied, including the speed range and dynamic performance. Simulation and experimental results show that, compared with the redundant drive-control mode, the six-phase PMSM with fault-tolerant drive-control mode has wider speed range and better dynamic performance.

In order to curb kernel matrix expansion and track the time-varying dynamic characteristics when kernel extreme learning machine (KELM) is applied to online condition prediction, a sparse KELM online prediction algorithm with forgetting factor is proposed. By introducing forgetting factor, a new objective function is constructed, which makes every element in sparse dictionary has different weights related to timestamp and ensures the effective tracking of the dynamic changes. By minimizing the fast leave-one-out cross-validation (FLOO-CV) error, key nodes with predetermined size are selected to form a dictionary. At the same time, the online recursive updating of model parameters is realized based on the elementary transformation of matrix and the inverse formula of block matrix. The proposed algorithm is compared with the recently proposed three online sequential KELM algorithms. The experimental results of aero-engine condition prediction show that the average training time of the proposed algorithm on six monitoring items is reduced by 7.5%, 62.0% and 81.9% respectively, and the average prediction accuracy is improved by 44.0%, 19.9% and 50.9% respectively.

The moment-tensor inversion method utilizes acoustic-emission signal to obtain cracking information and is regarded as an effective tool to monitor the dynamic growth of cracks. However, in engineering practices, the signal, got by sensors, is always contaminated by noise. The noise will reduce moment-tensor accuracy, and even cause completely wrong results. Sensor arrangements are studied to suppress the effect of noise on moment-tensor accuracy. Based on the first-arrival polarity method, the theory of choosing sensor locations is analyzed. The sensitivity of moment-tensor inversion accuracy to noise is investigated with different sensor arrangements by the use of synthetical acoustic-emission signal. The results show that the pentagonal arrangement of sensors is a superior form, where five sensors locate on a circle, the azimuthal angle between adjacent sensors is 72°, and the sixth sensor locates at the center of the circle. Then the condition number of the equation set achieves a relative small value. When the wave amplitude is changed by noise, the moment-tensor result is quite stable and achieves high accuracy. For the determination of sensor arrangement in moment-tensor inversion, the guidelines and theoretical basis of engineering practices are provided in the study.

A new second-order sliding-mode guidance law with finite time stability is proposed for the design of the guidance law of surface-to-air missile attacking maneuvering target. Based on the relative motion model of the missile and the target, guidance problem is transformed into control problem of first-order system. A fast adaptive super-twisting (FAST) algorithm is proposed by introducing linear terms and a new parameter adaptive law in super-twisting (ST), which improves convergence speed without the prior knowledge of upper bound parameters of uncertainties. A quadratic Lyapunov function is adopted to verify the stability of the system in finite time and compute the convergence time. A comparison with adaptive sliding mode guidance, ST guidance and smooth second-order sliding-mode guidance shows that the proposed method can improve the convergence speed of sliding variable and avoid the difficulty of choosing parameters, and can guarantee the guidance accuracy at the same time.

In order to improve the accuracy of service modeling and combinatorial optimal-selection in cloud manufacturing, a multi-level modeling methodology is proposed to describe manufacturing services, which subdivided the service into three fine-grained levels:resource service, function service and process service. From the perspective of QoS indexes, the relationship among execution, time service cost and user evaluation for different service levels are analyzed and elaborated, and the corresponding evaluation objective functions of services composition are established. A niching behavior based gravitational search algorithm (NGSA) is designed to address manufacturing services composition problem, in which the niche crowding factor and fitness sharing technology are applied to gravitational search algorithm (GSA) to improve its convergence speed and accuracy. Finally, the simulation research results demonstrate that the NGSA algorithm can search better solution with less time-consumption than the traditional algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) algorithm.

In the application of global navigation satellite system (GNSS) common view (CV) technology, the simulation of the GNSS CV signal is needed to reduce the cost of testing the CV receiver and the CV algorithm. For this reason, a channel multiplexing method of signal simulation of GNSS CV signal is proposed. First, the principle of GNSS CV technology is analyzed. The GNSS CV signal simulation method based on GNSS direct signal simulator was designed, and the possible errors in the process of CV signal transmission were analyzed. Finally, the CV signal of the simulation under zero base line, short base line and long base line, as well as the experimental data collected by an experiment were verified and analyzed. The result of verification shows that the simulated GNSS CV signal is located accurately and the positioning accuracy is in meter level. The result of CV comparison shows that the accuracy of root mean square (RMS) is better than 12 ns. The time transfer of CV method can be carried out, which proves that the proposed CV signal simulation method can be effectively used to generate GNSS CV signal. It has certain theoretical reference significance and practical application value for the development of GNSS CV signal simulator and CV receiver and for the study of CV algorithm.

During the return progress of the detector from the extraterrestrial celestial body after sampling, the ascent engine plume flows back to the ascender after the reflection from the launching pad upper surface, which causes aerodynamic effect and disturbing torque effect on the ascender. Numerical simulations have been done with the computational fluid dynamics and direct simulation Monte Carlo (CFD/DSMC) coupling method to analyze the plume aerodynamic effect during the takeoff. The influences of takeoff distance of 200-700 mm and deflection angle from 0° to 5° of ascender on plume aerodynamic effects have been considered in this paper. It has been found that with the increase of takeoff distance and deflection angle, the torque of the ascendere has been changed from positive to reverse, which seriously affects the takeoff stability. The reason of this phenomenon is considered to be that, when deflection angle increases, the impact point between the plume on the further side of the ascender from the launching pad and the launching pad has moved from the cone flame deflection to the plane. This phenomenon causes plume flow direction to change suddenly from close to the launching pad and flow to the side to rebound from the launching pad and flow to the bottom of the ascender. Eventually, the side of the ascender far from the launching pad is subjected to a higher torque than the side closer to the launching pad, and a reverse torque is generated.

As a kind of new inertial navigation system, the hybrid inertial navigation system has the characteristics of three-axis physical platform, strapdown attitude algorithm and installed self-calibration. Based on these characteristics and in order to improve the accuracy of hybrid inertial navigation system the attitude quaternion is used to replace the traditional Euler angle to represent the rotation of three-axis physical platform in the continuous self-calibration, and the attitude quaternion continuous self-calibration model of hybrid inertial navigation system based on the gimbal angle equation is established for its error coefficient estimation.Then a quaternion unscented Kalman filter based on singular value decomposition (SVD-QUKF) is proposed by improving the traditional unscented Kalman filter (UKF) based on the characteristics of the attitude quaternion model. The simulation and experimental results prove that the proposed attitude quaternion continuous self-calibration model based on the SVD-QUKF can calibrate all the error coefficients of hybrid inertial navigation system with the relative error less than 1%, and the calibration precision and the computing speed are better than the traditional gimbal angle model based on UKF.

A new maneuvering group target tracking algorithm based on adaptive correlation gate for solving measurement loss and increasing estimation error of centroid group tracking (CGT) algorithm when tracking maneuvering group target in clutter is proposed in this paper. First, CGT algorithm is combined with interacting multiple model (IMM) algorithm and the latest measurement information is used to modify the transition probability matrix. Second, a new adaptive correlation gate is designed when tracking overall and split maneuvering by the covariance of model innovation to guarantee valid measurements existing in the gate. The simulation results show that the proposed algorithm decreases the estimated error of traditional IMM algorithm with fixed transition probability matrix and increases the probability of dominant model from 0.58 to 0.7 on the one hand. On the other hand, the loss-target rate of adaptive gate designed in this paper is reduced by 30% compared to traditional gate on account of decreasing valid measurement during target maneuvering. The proposed algorithm has a certain practical value in engineering.

In order to achieve the control of a class of nonlinear systems in feedback form, the system is studied. First, according to LaSalle's invariance principle, the convergence of a class of autonomous systems is proved. The error function is introduced, and the Lyapunov function of the error function is used to find the controller which makes the error function asymptotically stable. Then, according to the lemma, the trajectories tracked by the system states are all converged, so that the system states are bounded and the output of the system converges to input. The condition and the proof of the stability of the closed-loop system are given. Finally, an example of longitudinal dynamics of an fixed-wing aircraft flight control system is presented, and the controller is designed according to the proposed method. The simulation is verified under the Simulink module of MATLAB. The results show that, for step signals and sinusoidal signals, the proposed controller can enable the pitch angle of aircraft to quickly converge the tracking command.

To solve the problem that the random error of the measurement data in the cavity transient heat transfer test is amplified by the differential process of data processing, the influence of random measurement error on the heat transfer characteristics is quantitatively analyzed, and the suppression method is proposed. The results show that the error of the convective heat transfer characteristic of the inner wall of the cavity is most sensitive to the random error of the transient temperature, resulting in high uncertainty of the test results of the heat transfer characteristics. The improved empirical mode decomposition (EMD) algorithm can be used in data differential process to effectively suppress the influence of random errors on the heat transfer characteristics. In the cavity inflation process, the maximum error of the heat transfer characteristics of the cavity wall surface decreases from 129.07% to 63.62% and the time average error decreases from 25.24% to 8.12% with the usage of error suppression method.

The ballistic target will cause superposition and folding of the micro-Doppler curve when moving in the midcourse at high speed, the traditional translation compensation method is not suitable for ballistic target translation compensation. After analyzing the frequency characteristics of each scattering point at the precession, it is found that the frequency at the intersection of the curves is completely caused by the translation. According to this property, a method of using the time-frequency image intersection information to perform translation compensation is proposed. First, the time-frequency skeleton image of the echo signal is obtained, then the Harris corner detection method based on bilateral filter is used to extract the corner points in skeleton and the intersection coordinates in the time-frequency image are obtained. Finally, the coordinates of intersection points are used to estimate the translation parameters for translation compensation. For the problem that the traditional Viterbi algorithm is easy to generate false correlations at the intersection of curves, a segmentation Viterbi algorithm using intersection information is proposed to separate the compensated time-frequency curves. Simulation experiments verify the effectiveness of the proposed method.

Aimed at the shortcomings of the existing data downlink mechanisms for low earth orbit (LEO) remote sensing satellite, such as low effiency, high delay and vulnerable transmission path, a new remote sensing data transmission mechanism was proposed. In the proposed mechanism, earth stations were supported to locate remote sensing image resources in real time on demand, and in the process, the transmission path from the positioning satellite to earth station was established. Taking into account the limited visual time between the cooperative satellite and the earth station, when transmission path is established, a routing algorithm was proposed based on the maximization of the path persistent service time to reduce the transmission delay caused by the change of the cooperative satellite. The designed data transmission mechanism was implemented based on the NS3 simulation platform. The experimental results show that the proposed mechanism can reduce the data transmission delay and data loss compared with the existing data transmission mechanism.

The effects of impact loading on the failure of cement concrete pavement are significantly different from those of traffic loading. This paper investigates the characterization of cement concrete pavement with varied initial crack length and location under impact loading. It is found that the final crack length and settlement generated in the pavement increase with the increase of the initial crack length and decrease with the increase of the distance between the initial crack and the loading center. The penetrating crack is produced when the the ratio of the initial crack length of the pavement to the surface layer thickness exceeds one certain value. The deformation of limestone and loess layer below the surface layer and in the range of about 5 times thickness of cement concrete layer is affected greatly by the initial crack length. The initial crack length and location play a significant role on the settlement of cement concrete pavement within 1 m distance from the loading center.

A full life cycle evaluation model of compressed natural gas (CNG)/gasoline bi-fuel passenger vehicle has been established based on GaBi software, which is adopted to analyze the energy consumption and emission of the bi-fuel vehicle from the raw material acquirement phase to the scrap recycling phase, and the sensitivity of the energy consumption and emission in full life cycle towards the using mileage ratio of the CNG-gasoline, total mileage and electric power structure. The results indicate that, in the full life cycle, the energy consumption and pollutant emission in the using stage are the most, taking up more than 50% of the full life cycle; major pollutants are CO, NO_x, SO₂, etc.; the CNG/gasoline bi-fuel vehicle can effectively cut the environmental influence down with a lower cost, but a CNG special vehicle is more beneficial to the energy saving and emission reduction; the energy consumption and emission of the full life cycle can obviously decrease by recycling the scrapped vehicles, increasing the CNG using mileage ratio of bi-fuel vehicles, and improving the ratio of using renewable energy to generate power.