Uncertain multiobjective redundancy allocation problem of repairable systems based on artificial bee colony algorithm

Based on the uncertainty theory, this paper is devoted to the redundancy allocation problem in repairable parallel-series systems with uncertain factors, where the failure rate, repair rate and other relative coefficients involved are considered as uncertain variables. The availability of the system and the corresponding designing cost are considered as two optimization objectives. A crisp multiobjective optimization formulation is presented on the basis of uncertainty theory to solve this resultant problem. For solving this problem efficiently, a new multiobjective artificial bee colony algorithm is proposed to search the Pareto efficient set, which introduces rank value and crowding distance in the greedy selection strategy, applies fast non-dominated sort procedure in the exploitation search and inserts tournament selection in the onlooker bee phase. It shows that the proposed algorithm outperforms NSGA-II greatly and can solve multiobjective redundancy allocation problem efficiently. Finally, a numerical example is provided to illustrate this approach.     

液体火箭发动机涡轮泵故障诊断的新方法

针对传统的液体火箭发动机涡轮泵故障诊断方法只能在有样本数据并且样本数据充足的情况下才能进行准确诊断以及诊断时难以提取状态特征的缺点,提出一种适用于涡轮泵在线监测及诊断方法,该方法利用生物免疫系统的反面选择机理,利用生物克隆和学习机理使改进型反面选择算法产生的检测器具有不同的检测半径,使其能更有效地覆盖异常空间,能有效地提取涡轮泵的状态特征,避免了检测器产生效率低等问题。实例诊断结果表明:该方法较好地解决了故障样本难以获取及有效地提取涡轮泵的状态特征的问题,能准确监测出涡轮泵各种常见故障所引起的异常并能准确诊断,较高诊断精度表明该方法是可行的,并且具有较好的在线性、准确性及鲁棒性,为液体火箭发动机涡轮泵故障异常检测探索了一条新路。     

基于多处理机系统在超立方体上并行仿真BP神经网

摘 要 本文介绍了人工神经网络的基本实现途径，并对 Intel iPSC860／P超级计算机系统作了简介，给出了在超立方体上实现BP算法并进行并行仿真所得到的结论     

深空探测重力模拟飞行器方案设想

为解决失重环境对航天员生理健康的影响,在调研国内外重力飞行器研究现状的基础上,结合重力模拟飞行器的原理及人造重力舒适度影响因素,提出了一种通过自旋产生人造重力的深空探测飞行器方案设想。最后给出了重力模拟飞行器建设的实施规划、总体方案、在轨组装流程及技术难点。深空探测重力模拟飞行器稳定运转可为空间工作生活的航天员提供与地面无异的重力环境,将为执行深空探测任务提供必要的环境保障。     

航天器规避动态障碍物的自适应人工势函数制导

针对航天器近距离操作中的动态障碍物规避问题,研究了一种燃料较省、精度较高的规避动态障碍物的自适应人工势函数制导方法。首先,对于引入高斯函数形式斥力势会使势函数在收敛点处的值不为零的情况,对斥力势乘以修正项,使得在收敛点的势能为零,消除了平衡点的偏离;在规避静态障碍物的基础上,研究了规避动态障碍物的人工势函数制导。其次,根据速度与引力梯度之间的关系,设计负反馈,使引力势梯度“适应”速度的变化,研究了规避动态障碍物的自适应人工势函数制导。最后,采用精确的数学模型进行数值仿真,验证所设计的制导律的正确性和有效性,并与传统的人工势函数制导对比。仿真结果表明：采用修正势函数提高了收敛精度;自适应人工势函数制导控制脉冲作用施加更加合理,相比人工势函数而言,总速度脉冲消耗可节省30%,精度提高两个数量级。     

利用人工神经网络提前1h预报电离层TEC

提出了一种利用人工神经网络提前1h预报电离层TEC的简便方法. 考虑到实际工程应用要求, 没有使用其他空间天气参数, 而是选择电离层TEC观测数据本身作为输入参数. 输入参数为当前时刻TEC、一阶差分、相对差分和时间, 输出参数为预报时刻TEC. 利用文中介绍的GPS/TEC处理方法解算厦门站2004年电离层TEC观测数据, 对预报方法进行评估, 全年平均相对误差为9.3744%, 预报结果与观测值相关性达到了0.96678. 结果表明, 利用人工神经网络方法提前1h预报电离层TEC有很好的应用前景.      

基于人工神经网络的反射器型面精度预测

基于人工神经网络的预测方法,利用数量适当的有限元计算结果,建立人工神经网络模型,对反射器型面进行精度预测分析,得到在最小型面精度结果下的结构设计参数。计算结果显示训练好的神经网络模型能够较精确地预测格栅反射器的型面精度,节省计算时间,并且以型面精度最小为准则进行参数分析,能够指导反射器的结构设计。     

基于人工免疫算法的编队压制干扰资源分配

通过对舰艇编队雷达有源干扰资源分配问题的研究分析,将免疫算法应用在编队有源压制干扰资源分配中,构建了分配的数学模型.提出了相关定义和一种能有效表达编队有源压制干扰资源分配的抗体染色体矩阵编码方案,并给出了亲和度算法.在假定情况下进行了仿真计算,得到了有效的有源压制资源分配方案,通过实例验证了算法的正确性和有效性,为求解更复杂的编队干扰资源分配问题提供了参考方案.     

Artificial equilibrium points and bi-impulsive maneuvers to observe 243 Ida

In the restricted three-body problem, the traditional Lagrange points L₁ and L₂ are the only equilibrium points near the asteroid 243 Ida. The thrust generated by a solar sail over a spacecraft enables the existence of new artificial equilibrium points, which depend on the position of the spacecraft with respect to the asteroid and the attitude of the solar sail. Such equilibrium points generate new spots to observe the body from above or below the plane of motion. Such points are very good observational locations due to their stationary condition. This work provides a preliminary analysis to observe Ida through the use of artificial equilibrium points as spots combined with transfer maneuvers between them. Such combination can be used to observe the asteroid from more different points of view in comparison to fixed ones. The analyses are made for a spacecraft equipped with a solar sail and capable of performing bi-impulsive maneuvers. The solar radiation pressure is used both to maintain the equilibrium condition and to reduce the costs of the transfers and/or to create transfers with longer duration. This is a new aspect of the present research, because it combines the continuous thrust with initial and final small impulses, which are feasible for most of the spacecraft, because the magnitudes of the impulses are very low. These combined maneuvers may reduce the transfer times of the maneuvers in most of the cases, compared with the maneuvers based only on continuous thrust. Several options involved in these transfers are shown, like to minimize the fuel spent ($\mathrm{\Delta }\mathit{v}$) as a function of the transfer time or to extend the duration of the travel between the points. Extended transfer times can be useful when observations are required during the transfers.     

A combined technique of Kalman filter,artificial neural network and fuzzy logic for gas turbines and signal fault isolation

The target of this paper is the performance-based diagnostics of a gas turbine for the automated early detection of components malfunctions. The paper proposes a new combination of multiple methodologies for the performance-based diagnostics of single and multiple failures on a two-spool engine. The aim of this technique is to combine the strength of each methodology and provide a high success rate for single and multiple failures with the presence of measurement malfunctions. A combination of KF (Kalman Filter), ANN (Artificial Neural Network) and FL (Fuzzy Logic) is used in this research in order to improve the success rate, to increase the flexibility and the number of failures detected and to combine the strength of multiple methods to have a more robust solution. The Kalman filter has in his strength the measurement noise treatment, the artificial neural network the simulation and prediction of reference and deteriorated performance profile and the fuzzy logic the categorization flexibility, which is used to quantify and classify the failures. In the area of GT (Gas Turbine) diagnostics, the multiple failures in combination with measurement issues and the utilization of multiple methods for a 2-spool industrial gas turbine engine has not been investigated extensively.This paper reports the key contribution of each component of the methodology and brief the results in the quantification and classification success rate. The methodology is tested for constant deterioration and increasing noise and for random deterioration. For the random deterioration and nominal noise of 0.4%, in particular, the quantification success rate is above 92.0%, while the classification success rate is above 95.1%. Moreover, the speed of the data processing (1.7 s/sample) proves the suitability of this methodology for online diagnostics.