Abstract:The rotor dynamic structure of a helicopter presents a high value of strategic development. As the vibration caused by rotor operation negatively impacts flying performance, the exploration of rotor vibration control methods is perceived as vital to the improvement of helicopter performance. Regarding the key frontier problem, the principle of active vibration control is scrutinized with the cause of fuselage vibration by rotor and the frequency characteristics of vibration considered. Then, the overall framework of helicopter active vibration control is described. The control methods are divided into frequency-domain and time-domain control on the basis of the periodic property of helicopter vibration. The higher harmonic control method, robust method, and intelligent method are reviewed and summarized, coupled with the related test results. Furthermore, vibration transfer suppression technology is briefly introduced, and active vibration control tests conducted home and abroad are reviewed. By summarizing the shortcomings of vibration control methods, the future research directions for active control methods are suggested: robust adaptive control for stable flight states, intelligent self-learning control for full flight states, and the design of integrated active control systems for performance improvement should be conducted.

Abstract:To investigate the attitude tracking control problem of rigid spacecraft under the action of external disturbances torque with known upper bound, this paper proposes a predefined-time attitude tracking control scheme, in which the tracking accuracy can be specified in advance. Firstly, a predefined-time disturbance observer which can realize high-precision online estimation for the bounded external disturbances within the specified time is designed to compensate the external disturbances using its estimated information. Then based on this observer, a quasi-terminal sliding mode and a continuous nonsingular controller is designed using terminal sliding mode control method. Lyapunov theoretical analysis results show that the upper bounds of observers, sliding modes and the controllers convergence time and the accuracy of attitude tracking all explicitly exist in the relevant parameters, so they can be easily adjusted during the design of the controller without being restricted by the initial conditions. Finally, the performance of proposed control scheme is evaluated by using numerical simulation. Simulation results show that the predefined values are loose upper boundaries, for either convergence speed or tracking accuracy, the actual performance may be far better than predefined values. Furthermore, this algorithm is also quite robust to the uncertainty of system modeling.

Abstract:The manned spacecraft capsule provides a critical safeguard for the safe work and life of astronauts during space missions. To understand the vulnerability characteristics of the pressurized cabin structure and obtain an accurate model of its vulnerability, impact tests of the basalt/aramid fiber-filled Whipple shields were carried out based on two-stage light gas guns. Ballistic limit diameters of three types of test pieces were obtained, and the impact damage characteristics of the bumpers, filling layers and rear wall were analyzed. The results showed that the hole size of the bumper was positively related with the diameter of the projectile. The basalt/aramid fiber filling layers had a strong crushing and energy dissipation effect on the projectile and the debris cloud, which reduced the damage to the pressurized cabin structure. The energy of the debris cloud along the main impact direction was the main factor causing the petal-shaped crack perforation of the rear wall. Based on the test data, the NASA Christiansen equation and the W-S hole size equation were modified using a genetic algorithm and a multivariate linear/nonlinear regression method, improving the prediction accuracy. The overall prediction rate increased from 59.1% to 100%, and the safety prediction rate increased from 81.8% to 100%. Two types of vulnerability models, including the impact limit equation and the hole size equation, were accurately established for the basalt/aramid fiber filled structure of a certain large Chinese manned spacecraft, providing a basis for the risk engineering assessment of on-orbit missions.

Abstract:To enhance the parallel efficiency of solving Navier Stokes equations, a graphic processing unit (GPU) parallel algorithm, ported from Runge-Kutta discontinuous Galerkin (RKDG) method, is presented through constructing element-based or edge-based thread hierarchy and corresponding GPU kernels. The data storage and access of the algorithm are designed to be compatible for the various types of memories with different latencies. In comparison with the structured mesh counterpart, in which the structured domain of data dependence is already quite good for the requirement of coalesced memory access, the irregularity of unstructured mesh shows a negative effect on the performance of memory access. To remedy the negative effect, a multi-layered element reordering approach suitable for high-order finite element method is proposed to achieve further acceleration. Starting with the initial mesh, layer structures of elements or edges are constructed with reordering in a layer-by-layer manner to form the data structures suitable for coalesced memory access. An example of mesh reordering is provided with the implementation process detailed. Numerical results of typical flow simulations reveal that the expected order of accuracy of the proposed algorithm is realized, and the calculated results agree well with experiment data or other computed resules in the existing literature, with the maximum GPU speedups achieved up to 67.47. Moreover, the algorithm exhibits the potential to cope with more complex geometries, and the proposed technique can further achieve reordering acceleration.

Abstract:In an effort to achieve the rapid cooperation of Either micro-satellites or microsatellites and meet the requirements of high sensitivity and fast acquisition of spread spectrum signal proposed by inter-satellite communication link, the principle of common acquisition algorithms was analyzed. In view of the shortcomings of traditional signal acquisition algorithms such as low acquisition sensitivity, long acquisition time and high signal-to-noise ratio requirements, a fast FFT acquisition algorithm for inter-satellite link was proposed. Based on the traditional FFT code phase acquisition method, the algorithm improves the acquisition sensitivity and acquisition speed of the traditional algorithm through multiple parallel architecture, special synchronization sequence, rate reduction decimation, incoherent accumulation and other optimization strategies. In order to test the feasibility of the algorithm, firstly, the limit sensitivity, anti-interference ability and theoretical capture time of the algorithm were derived through theoretical formula. Secondly, the typical task environment was set in MATLAB software to simulate the performance of the algorithm. Finally, the performance of the algorithm was measured by building a hardware test platform. Simulation and hardware tests show that the performance of this algorithm is significantly improved compared with the traditional acquisition algorithm. The ultimate acquisition sensitivity of the improved algorithm is -130 dBm, and the acquisition time is less than 100 ms, which meets the design requirements of satellite communication environment. Its feasibility has been verified in the inter-satellite communication machine of the self-developed tianping-2 satellite. The improved algorithm can also be compatible with different needs of applications in various environments by adjusting the number of parallel paths, non-coherent accumulation times and other elements of the algorithm.

Abstract:To solve the problem that the tradition class-F power amplifier is affected by transistor output capacitance and output inductance, resulting in complicated tuning circuit, a compact output harmonic tuned matching circuit is proposed. By analyzing the impedance characteristics of the fundamental wave matching circuit, equivalent to a finite reactance to the ground at the harmonic frequency, the reactance and the harmonic tuned matching circuit are co-designed to avoid introducing redundant elements and eliminate the influence of fundamental matching network on harmonic matching network, thus reducing the power amplifiers size. Finally, only an LC tuning network is introduced to realize the control of the output the second and third harmonics to improve the output efficiency. Based on this circuit structure, a high efficiency L-band power amplifier using 0.25 μm GaN HEMT transistor is designed and implemented on a 7 mm×8 mm Cu-Mo-Cu Carrier using internal matching technology. The measured results show that under the condition of a drain-source voltage of 28V and the input of 10% duty cycle pulse signal, the amplifier achieves the large-signal performance of 61%-63% PAE and over 26 dB power gain at a saturated power of 48.1-48.4 dBm within 1.18-1.42 GHz. The structure improves the efficiency and reduces the complexity of the circuit.

Abstract:To ensure the stable flight performance and good tracking effect of the morphing aircraft in the case of sensor fault, and improve the accuracy of fault diagnosis and fault-tolerant control capability, an online active fault-tolerant control method based on belief rule base (BRB-r) expert system considering attribute reliability is proposed highly specific for the sensor fault diagnosis and fault-tolerant control of the morphing aircraft. Firstly, the aerodynamic parameter model and longitudinal nonlinear dynamic model of morphing aircraft are presented. Considering the external disturbance and sensor fault, the switched linear parameter varying (LPV) fault model of morphing aircraft is established by using the least fitting method and Jacobian linearization method. Then, based on BRB-r expert system, a sensor fault diagnosis and fault-tolerant control model of morphing aircraft is constructed. The reliability of sensor monitoring index is analyzed by statistical method, and evidence reasoning (ER) algorithm is introduced to improve the accuracy of fault diagnosis and fault-tolerant control effect. Finally, the projection operator covariance matrix adaptive optimization strategy (P-CMA-ES) algorithm is used to optimize the fault diagnosis and fault tolerant control model, which reduces the complexity of the system and improves the efficiency of fault diagnosis. The simulation results show that the sensor fault diagnosis accuracy of the morphing aircraft can reach 98.75%. When the sensor fault degree is less than 50%, the proposed method can effectively overcome the sensor fault and external disturbance, ensuring the stable flight of the morphing aircraft, and exhibiting strong fault-tolerant control capability and robust performance.

Abstract:T-shape rubber damper has nonlinearity in both type of construction and rubber material. The two-level nonlinear dynamic model with piecewise linear stiffness, damping and cubic stiffness is established. The equivalent stiffness and damping of the piecewise linear system are derived from the equivalent linearization method. The nonlinear frequency response functions of piecewise linear stiffness system and cubic stiffness system under sinusoidal sweep excitation of external load are simulated by harmonic balance method. The results show that lower excitation load can lead to gradual softening of structure type, while higher excitation load can lead to dynamic softening of rubber material. Through the transfer characteristic test of T-shape rubber damper system, it is verified that T-shape rubber damper has the nonlinear characteristics of asymptotic stiffness and asymptotic damping. The correctness of the model is verified by the comparison between the calculation results and the experimental results of sinusoidal sweep excitation of base displacement. From the perspective of aerospace engineering application, the method of precompression design for large overload and strong vibration environment is proposed.

Abstract:To fully develop the potential characteristics of electric load historical data and improve the prediction accuracy of the short-term load forecasting model, a residual AM-Bi-LSTM prediction model combining improved residual network (ResNetPlus), attention mechanism (AM) and bi-directional long short-term memory network(Bi-LSTM) is proposed in this paper. This model takes historical load, temperature and the features of the predicted date as input. First, based on the Bi-LSTM prediction model, multi-layer improved residual networks are introduced to extract the hidden features of input data, which solves the problem of network degradation caused by the deepening of hidden layers of neural networks, and greatly improves the back propagation ability of the model. Second, the attention mechanism is used to analyze the correlation between input information and current load in the network and highlight the impact of important information, thus improving the speed and accuracy of the model. Third, the Snapshot strategy is used to integrate multiple models that converge on different local minima, in order to improve the accuracy and robustness of the model. Finally, the US ISO-NE Dataset is used to verify the performance of the model. The experimental results show that the proposed model has achieved an average prediction accuracy of 98.27%. The average prediction accuracy over 12 consecutive months with the proposed model has improved by 2.87% compared to the traditional LSTM model. In addition, the average prediction accuracy under different seasons based on the proposed model has improved by 1.03% and 1.16% compared to the AM-Bi-LSTM and ResNetPlus models, respectively. This indicates that compared to the contrast model, the residual AM-Bi-LSTM model has higher accuracy, robustness and generalization ability.

Abstract:To overcome the significant challenges to accurate numerical simulations of water entry problems, like the treatment of the moving boundaries, the description of highly distorting free water surface and the reflection of strong coupling effect between fluid and solids, a CFD-DEM-IBM approach, which incorporates the computational fluid dynamics-discrete element method (CFD-DEM), the immersed boundary method (IBM) and the improved conservation level set (ICLS) method, is proposed for the precise prediction of water entry phenomenon. Fixed Cartesian grids are used to discretize the computational domain, with CFD and DEM used to describe the motion of fluid and the motion of solid bodies, respectively. IBM is introduced to track the solid boundaries and obtain accurate fluid-solid interaction forces. The free water surface is captured using the ICLS method which can ensure both the validity of interface properties and the conservation of mass. A partitioning algorithm is employed to perform multiple alternating iterations within a time step to reflect the strong coupling effect between fluid and solid, establishing a high-resolution CFD-DEM-IBM numerical model. Water entry of a cylinder with prescribed motion, symmetric and asymmetric water entry of a wedge and water entry of multiple bodies are then performed. The results show that the detailed resolution of the fluid phase along with the strong coupling effect can be reasonably reflected by the CFD-DEM-IBM approach, and it is remarkable in addressing water entry problems even when multiple rigid bodies are involved.

Abstract:To solve the problem that energy management strategy based on optimization in fuel cell hybrid electric buses is difficult to apply to real life vehicles, an energy management strategy based on SOM-K-means driving condition identification is proposed with reference to the analysis of the fixedness and fragmentation of the fuel cell bus (FCHB) driving route. Firstly, the driving route is divided into driving segments according to bus stops. When the vehicle stops, the SOM-K-means second-order clustering model is used to identify the driving condition, and obtain the predictive co-state of the next driving segment. When the vehicle runs in the next driving segment, a predictive co-state is used to complete the real-time application of the minimum fuel equivalent fuel consumption strategy based on the PMP solution. Secondly, the simulation experiments based on the actual driving data of the bus are established. Finally, the proposed strategy is applied to the vehicle control unit (VCU). The results show that compared with the rule-based strategy, the proposed strategy reduces hydrogen consumption by 19.77%. The calculation time of each step in the VCU is about 30 ms, and the calculation results prove to be completely consistent with the simulation results, meeting the requirements of vehicle for the timeliness and accuracy of energy management strategy.

Abstract:To accurately identify the faults of electromechanical systems in a tank autoloader, a fault identification method combining functional data analysis (FDA) and multi-layer kernel extreme learning machine (ML-KELM) is proposed. Firstly, the feature information of time series data with smooth characteristics during the electromechanical system operation is mined from a functional perspective, and the change features of time series data are characterized as feature parameters from different spaces by functional principal component analysis and principal differential analysis. Secondly, the extracted features of the multi-sensor time series data are screened by Relief-F to obtain features strongly correlated with the classification. Finally, ML-KELM is used to perform deep feature learning on the strongly correlated features to achieve a more abstract feature representation, thereby realizing accurate fault identification. The fault identification experiment is carried out using an experimental setup consistent with the principle of the chain conveyor in a tank autoloader. Experimental results show that functional principal component analysis and principal differential analysis can extract effective fault features of time series data from different feature spaces, and the features extracted by the two methods are complementary. The ML-KELM with three hidden layers can realize more accurate fault identification based on the strongly correlated features in the multi-sensor time series data features. The proposed method proves to be feasible and effective, providing a reference for the research on fault identification of the electromechanical systems in the tank autoloader.

Abstract:Traditional chemical cleaning, mechanical sanding, and sandblasting can produce large volumes of hazardous waste and damage the substrate. In addition, the depainting process is low-efficient and labor-intensive. Based on the aircrafts structural shape and paint removal requirements, a robotic laser paint removal system for aircraft maintenance is developed. The robotic laser paint removal system contains the omnidirectional moving unit, the four-degree-of-freedom robot arm unit, the laser cleaning unit, and the measurement and control unit. Firstly, the mechanical structure and control architecture of the laser paint removal robot are designed, based on the shape of the DR-5 unmanned aerial vehicle (UAV), and the robot arms kinematic analysis. Workspace analysis is carried out using the D-H method to verify the reachability of the robot arm. Secondly, the robot arm is tested for repeatability, where the Z-direction repeatability is quantitatively evaluated using laser displacement sensors, and the X andY-direction repeatability is evaluated using an error circle. Finally, based on the bow path, the laser paint removal test is carried out on part of the flat surface and the curved surface of the UAV fuselage. Moreover, the paint removal result is evaluated according to the residual thickness of the surface paint layer. The results show that the repeatability of the laser paint removal robot is 0.039 mm in Z-direction and less than ±2.000 mm in the X and Y-directions; the average residual thickness of the flat surface paint removal experiment is 6.5 μm and the average residual thickness of the curved surface paint removal experiment is 21.3 μm.

Abstract:To overcome the lack of sufficient structural statistical information in practical application and obtain the limit values of structural parameters and responses, an interval finite element model updating method based on acceleration frequency response function is proposed. Firstly, the frequency response function is transformed by wavelet transform with the low frequency wavelet coefficients extracted as the response characteristic quantity of the model updating. The parameters to be updated and the response characteristic quantity are respectively input and output to construct the radial basis proxy model. The whale optimization algorithm is used to optimize the variance value of radial basis function model. Secondly, two objective functions for two-step solution of the parameter interval to be updated and one objective function for synchronous solution of the parameter interval to be updated are constructed according to the interval overlap ratio and Bhattacharyya distance, so as to evaluate the distribution similarity and heterogeneity of the two samples. Then, the grey mathematics method is implemented to estimate the interval of characteristic quantity predicted by the radial basis model, and the flower pollination algorithm is adopted to solve the two-step synchronous solutions of the midpoint and radius of the parameter interval to be updated. Finally, two numerical examples and one experimental example are provided to verify the feasibility of the proposed method. The results show that the proposed interval finite element model can effectively update the interval midpoint and radius of structural parameters, and prove to be robust to the parameter interval updating under different test response intervals, thus effectively solving the problem of uncertainty model updating for small test samples.

Abstract:To accurately evaluate the fatigue damage of bimodal Gaussian random process, a new frequency-domain analysis method called as the improved bands method was proposed. The basic idea of the proposed method was developed from the spectral decomposition approach. Firstly, the power spectrum density functions of low-frequency and high-frequency modes were split into a large number of infinitesimal frequency bands. According to the damage equivalence principle, the equivalent conversions were separately performed for the low-frequency and high-frequency components to obtain the corresponding equivalent narrow-band processes. Subsequently, another equivalent conversion from high-frequency equivalent narrow-band process to low-frequency mode was conducted. In order to account for the interaction between the low-frequency and high-frequency modes, a correction factor, which depends on characteristic frequency ratio, energy ratio and material parameter m of the S-N curves, was introduced to modify the summed zero-order spectral moment. When the final equivalent narrow-band process was obtained, the total damage of bimodal Gaussian process could be calculated by the analytical solution of narrow-band fatigue damage. Through numerical tests of ideal rectangular bimodal spectrum and real bimodal spectrum, by taking the fatigue damage estimated by time-domain rain-flow counting method as reference, the accuracy and robustness of the present method was validated against several popular frequency-domain methods. Results showed that the improved bands method is not only more accurate than other traditional frequency-domain methods but also easier to be implemented in computer programming, which also indicates its great potential in actual engineering practice.

Abstract:In the process of natural gas exploitation, liquid water deposition will seriously threaten the gas transmission pipeline. As such, the gas-liquid separation equipment is widely used in the natural gas gathering system. To investigate the separation characteristics of the corrugated plate, which is viewed as an important separation element in the liquid separation side of the gas-liquid separation flash skid, an experimental platform for exploring the separation characteristics of baffles is constructed, coupled with the orthogonal experiment designed for different types of corrugated plate. The separation efficiency and pressure drop of the corrugated plate are taken as the test indexes. The main influencing factors and the best combination scheme are determined by analyzing the influence of the internal components at the liquid separation side on the separation performance under multiple working conditions at room temperature. The results show that the separation efficiency proves to be the best when the horizontal trapezoidal or honeycomb corrugated plate, deflector structural parameters of 180/102/105 or 120/102/105, liquid gas ratio of 2.083‰~2.917‰ and closed connecting pipe are combined. The corrugated plate type is seen as a vital factor affecting the separation efficiency. The pressure drop would be the smallest in the whole gas-liquid separation process when the honeycomb or vertical trapezoid corrugated plate, the deflector structural parameters of 180/102/105 or 120/102/105, the liquid-gas ratio of 3.750‰~4.583‰ and the closed connecting pipe are integrated. The above four factors exert no significant influence on the pressure drop.