The integral modeling method is usually used in dynamic research of multi-stage planetary gear system. But it is not convenient for the analysis of dynamic performance and for the selection of transmission scheme. The dynamic model has to be rebuilt when the transmission scheme is changed. So based on the modular method, four general modules are established with meshing stiffness, damping, friction, backlash and bearing supporting stiffness of planets considered. Then the nonlinear dynamical differential equations of multi-stage planetary gear trains are generated automatically by calling in the four modules. According to the modular method, the dynamic characteris-tics of the four-stage planetary gear train used in space manipulator are analyzed. In order to verify the applicability and availability of the modularly designed model, the calculation results of the modularly designed model and those of the integrally designed model are compared.

Objective: To investigate the effect of transcutaneous electrical acupoint stimulation(TEAS) on T lymphocyte subgroup, natural killer cell(NK cells) and its related cytokines secretion in perioperative lung cancer patients undergoing lobectomy.Method: Forty patients with pulmonary carcinoma were randomly divided into surgical group and TEAS surgical group. The patients in TEAS surgical group received TEAS stimulation for 30 min from 30 min before operation to 1, 2 and 3 days after operation. The levels of blood CD3+, CD4+, CD8+and CD4+/CD8+ratio as well as NK cells, and the concentrations of sIL-2R, IL-2, IFN-γ and IL-10 were determined at 30 min before operation, at the end of operation and at 1, 3 and 5 d after operation.Result: The levels of CD3+, CD4+, CD4+/CD8+ratio and NK cells in TEAS surgical group increased significantly at postoperative 1, 3 and 5 days compared with in surgical group. The expressions of CD8+, sIL-2R and IL-10 decreased significantly at postoperative 3 and 5 days, while the expressions of IL-2 and IFN-γ increased significantly(P0.05).Conclusion: TEAS may enhance the immune function of perioperative patients with lung cancer, strengthen the postoperative analgesia effect and reduce the analgesic consumption of postoperation.

The remote string driven type of the hyper-redundant DOF robot has the advantages of low cost and small volume compared with the direct driven type with motors placed near or inserted in the joints.It puts forward a new remote string driven hyper-redundant DOF robot structure scheme,which has the unique feature that the antagonistic string pair’s end connection points are all located in the extension line of the rotating joint(Hooke joint)axis.So the stretching and contracting displacements of the two antagonistic strings are approximately equal.Therefore these two strings can be connected at their driven ends and driven by single motor.So the number of driving motors can be reduced by 50% which can reduce the robot cost.It presented in detail the structure scheme and the equation of string stretching and contracting displacement,which is validated by selecting different link parameters.

To improve the efficiency of triangle mesh surface reconstruction in neural network,an improved Kohonen neural network is put forward,which combines Kohonen neural network and faintness clustering algorithm,and by which large scale scattered point clouds triangle mesh surface and vase surface reconstruction have been done.Characteristics comparison is carried out between the improved algorithm and general one,and the results show that the improved algorithm avoids repeat circulation in general algorithm,reduces calculation time,improves the efficiency and rate of the triangle mesh surface reconstruction.Simulation reconstruction result indicates that the improved arithmetic can realize sparse and dense triangle mesh surface reconstruction and data condensation under preconditions with primary data characteristics.The improved arithmetic has fast network convergence speed.

Based on the exactly solution for the wheel/rail contact point and the contact force, a vehicle/rail coupling model for analyzing dynamic derailment is developed in MATLAB as DDSHV (Dynamic Derailment Simulation for High-speed Vehicle). The calculation process of the simulation system is presented in detail, and the best solution conditions are also discussed to quickly obtain results. Two common types of dynamic derailment are studied in DDSHV. There exists a critical point in the process of wheel climb, and the dynamic weakening effect will promote the wheel-climbing rail. Meanwhile, some main factors, such as the speed, the rail condition and the wheel unload rate, have been studied on the dynamic weakening effect. The collision speed of the wheelset is the most important factor affecting impact derailment. As time becomes shorter, the collision can be investigated using LS-DYNA. The results confirm the equation for the critical impact speed used in this paper. DDSHV can also be used to find the vehicle running stability. Through the design of uplink and downlink algorithms, two critical running speeds, the critical speed and the nonlinear critical speed have been found. Yet, the changes in suspension parameters will directly influence these critical speeds. Therefore, an accurate configuration in vehicle will help to reduce the disturbances while an inaccurate configuration may lead to an incident. Although it is dangerous and difficult to make a derailment online test, the effectiveness of DDSHV has been verified by the known dynamic cases and lab tests. In conclusion, DDSHV has assisted in understanding the process of derailment, finding the important factors affecting derailment and exploring the mechanism of dynamic derailment. (C) 2012 Elsevier Ltd. All rights reserved.

In order to improve accuracy and convergence speed for flight trajectory optimization program in flight management computer and enhance its maintainability, an improved particle swarm optimization (PSO) algorithm with object-oriented performance database is proposed. Firstly, an object-oriented performance database is built by Microsoft Visual C++ and MATLAB/SIMULINK mixed software development environment. Through synthetically use class hierarchy and specialized function library, the flight performance data is retrieved and its data file can be replaced with adapt for different aircraft types. Secondly, the mass point motion mathematical model is built according to mass point dynamics and energy states. Objective functions for trajectory optimization in vertical flight profile are acquired by the Minimum Principle of Pontryagin. Thirdly, adaptive inertia weight is introduced, the equality constraints is processed using the penalty function method. Finally, trajectory in vertical flight profile is optimized through using the improved PSO based on the object-oriented performance database. Meanwhile, the PSO algorithm flow for vertical flight profile trajectory optimization is given. Through using of the improved PSO, trajectory optimization of Boeing 737-800 aircraft in vertical flight profile is carried out. Comparison results between optimization results and flight test data show that the calculated results of proposed algorithm rapidly converges to optimal solution with higher precision.

With an increase in speed, a vehicle's dynamic behavior becomes apparent. Increasing speed not only affects the sitting comfort, but also may lead to derailment. However, an accident is difficult to predict, because the derailment mechanism is not thoroughly understood. The reliability of derailment simulations are completely conditional to being able to accurately solve the wheel and rail contact problem. Thus, an improved three-dimensional contact trace method is presented to quickly obtain the correct point. Then, a fast and accurate method for obtaining the contact force, which includes the creep force and the normal force, is improved. The results correspond more closely to realitic solutions compared with those of current methods. Next, a dynamic model of the vehicle and the rail is established. The two models are not independent of each other. The wheel-rail contact calculation is the key consideration for coupling in the two models. Finally, all the dynamic models, which are called dynamic derailment simulation for high-speed vehicle (DDSHV), are developed in MATLAB. To identify two different types of derailment, derailment judgment is embedded in the program package. The simulation system can be used to study the dynamic derailment mechanism, analyze derailment conditions and influence factors, and determine the key cause of the incident. (C) 2012 Elsevier Ltd. All rights reserved.

In order to enhance accuracy and convergence speed for aircraft vertical flight trajectory,an improved particle swarm optimization(PSO) algorithms for flight trajectory optimization is proposed.The point-mass motion mathematical model is built based on point-mass dynamics and energy states.Objective functions for trajectory optimization in vertical flight profile are acquired through Pontryagin minimum principle.Adaptive inertia weight is introduced,the equality constraints is processed using the penalty function method.Trajectory in vertical flight profile is optimized based the improved PSO.The PSO algorithm flow with trajectory optimal in vertical flight profile is finally given.Making use of improved PSO,trajectory optimization of Boeing 737-800 aircraft in vertical flight profile is carried out.Comparison results between optimization results and experiment data show the proposed algorithm converging to optimal solution rapidly.It has merits of fast convergence speed and high precision.

In this paper, the transfer matrix method has been employed to analyze the torsional vibration dynamics of the test rig for closed intersecting axes beveloid gears of helicopter. The torsional vibration dynamic model has been established through adopting the transfer matrix method. At the same time, the mathematical model of the branch nodes and the dynamic analysis of test rig closed system have been also derived. The dynamic simulation principle of the test rig is studied and the corresponding dynamic load coefficients are also solved. Finally, the simulation curve of the vibration load coefficients of the test gears under different speed is drawn. The results shows that both the dynamic character of test rig and the loading precision can meet the test requirement.

To built pilot tracking control strategy model,the combination of sliding model control characteristic and optimal control characteristic is adopted to propose a sliding optimal control method,and the time-varying sliding surfaces are designed so that the system state is on the sliding surface from the beginning of the motion without reaching phase.The system is robust and stable.A parameter selected method of weighting matrix on H∞ control is improved,by which the weighting matrix of linear quadratic optimal control is calculated.To drive the system state variables to the acquisition control switching surface in minimum time,the acquisition control strategy is builed by sliding model control.The main error is regared as a judgement from acquisition control strategy to tracking control strategy.The simulation results show that the pilot variable stategy control is suitable to the real pilot control characteristic.

The characteristic vibration mode behavior loci veering of the two-stage double helical tooth planetary gear was analyzed. The loci veering criteria of the eigen frequency of different vibration modes were proposed by the analysis of the coupling factors characterizing the local curvature. The correctness of the proposed criteria was validated by the case example, providing a theoretical basis for the optimal design of the gear train.

Huge danger to security and stability caused by nonlinear vibration of automotive steering occurs during vehicle running,so,it's very important to reduce the vibration and analyze the parameters acting on system.In order to analyze the issue in the round and eliminate vibration reasonably,four degrees of freedom equivalent nonlinear dynamic model of independent suspension automotive steering is established which includes some important nonlinear factors,e.g.clearance,coulomb friction of automotive steering and lateral force.Going with analyzing Hopf bifurcation of multi-DOF system self-excitation vibration concretely,influence of clearance and coulomb friction on critical speed of vehicle and limit cycle amplitude after Hopf bifurcation is discussed in detail and validated by numerical method.Another research is developed on stability of balanceable position and its stable time.The rule derived from the numerical simulation using different nonlinear conditions has instructive significance to avoiding vibration and controlling Hopf bifurcation behavior of automotive steering.

In order to compensate transport delay of flight simulator,two transport delay adaptive forgetting factor compensation algorithms based on Kalman filter and Stochastic Approximation are presented.To improve prediction of precision and reduce errors,the time varying forgetting factor is regulated by the error,and a regulatory parameter is added in the initial parameter matrix of the two compensation algorithms,the singularity in the initial parameter matrix is avoided.The results imply that the two algorithms are superior to the algorithms of the revised McFarland and the Kalman filter compensation algorithm is the most excellent among the four types of algorithms.

Vehicle derailment is difficult to explore because accidents are caused by many factors. In this paper, derailment behaviors are divided into three categories: friction-type derailment, structure-type derailment, and nonlinear-type derailment. Each category has unique characteristics. Wheel climb is a frequent form of friction-type derailment, resulting from mechanical and generally dynamical behavior between wheel and rail. Dynamic simulation is an important tool for prediction of friction-type derailment. There exists a critical point during wheel climb, and lateral normal force primarily prevents the wheel’s moving up. Structure-type derailment is a result of component failure, appearing as local, then developing into general derailment. Factors affecting the development process, such as failure modes, front wheelset derailment, and vehicle speed, are discussed. Nonlinear-type derailment commonly occurs as impact derailment when the vehicle loses stability beyond a nonlinear critical speed. The critical speed for derailment is derived, and the case of a bifurcation diagram is studied. Although nonlinear-type derailment is sensitive to initial conditions, the possibility of accurate prediction is discussed.

The study on dynamic governing equations of two stage planetary gear train used in ship with double helical tooth was not reported. In this paper, the lateral-torsional coupling dynamic computation model is built, and then considering the factors (such as meshing stiffness, synthetic meshing errors, damping). Based on the compressions of the elastic elements for the first stage and the second stage, the dynamic model of the sub-element is established, and then the integrated dynamic governing equations are achieved.

A novel method, modified particle swarm optimization algorithm, is proposed to compute flight envelope in this paper. According to the principle of thrust method, the problem of solving flight envelope is converted into searching the optimal solution by the particle swarm optimization algorithm (PSO). Combined with adaptive inertia weight factor, the standard PSO algorithm is modified. Applying the modified PSO algorithm, the flight envelope is solved. Numerical simulations results illustrate that the search algorithm is feasible and efficient for solving flight envelop.

The study on natural frequency sensitivities to system parameters of two stage planetary gear train with double helical tooth was not reported,though natural frequency sensitivities of the one stage planetary gear were investigated by some researchers.In this paper,parameters under consideration mainly include mesh stiffnesses.Using the well-defined vibration mode properties of tuned two stage planetary gears,the eigensensitivities are calculated and expressed in simple,exact formulae.These formulae con-nect natural frequency sensitivity with the modal strain and provide efficient means to determine the sensi-tivity to all stiffness parameters by inspection of the modal energy distribution.

高速车辆存在大量非线性因素以及由此带来的复杂动力学行为。基于Shen-Hedrick-Elkins理论计算了轮轨蠕滑力,建立了十自由度半车数学模型。使用多刚体理论模拟轮轨碰撞并获得了跳轨的横向临界速度,在0～180m/s速度范围内绘制了轮对运动分岔图。结果显示,高速车辆在超蛇行临界速度之后存在着对称和非对称的周期运动以及混沌运动。与其他模型相比,半车模型更适合于高速车辆动力学行为研究。

To decrease the dynamic parameter errors of a space robot and improve accuracy of path planning,according to the angular momentum conservation equation,and based on the difference between the angular momentums estimated by nominal dynamic parameters and the real ones,an error model is built for the dynamic parameter identification,then the fitness function used for Genetic Algorithm(GA) is also presented.For early maturityphenomenon easily occurred in the conventional GA,an improved GA is presented based on small bound,big mutation and elite reservation tactics.At last,as an example of a six-joint space robot,a simulation is carried out.The results show that the improved GA increases calculative efficiency and identification accuracy in spite of complicated parameters.

For a space robot there are errors between its nominal dynamic parameters and real dynamic ones because of some factors of machining and assembly. However, Path planning for the space robot is different from that on the ground, since the dynamic parameters exist in the generalized Jacobian matrix, the calculated trajectory will deviate from the really desired one, which will cause some pose errors of the end-effector. According to the angular momentum conservation equation for a free-floating space robot, the base and joints of a two DOF space robot are respectively excited with the cubic polynomial trajectory, then its dynamic parameters are identified respectively using the least-square algorithm based on the error model and the GA (genetic algorithm). The simulation results show that the calculated stability and the dynamic parameters' identification accuracy with GA are better than those with the least square.