Forecasting the geomagnetic activity of the Dst index using multiscale radial basis function networks

The Dst index is a key parameter which characterises the disturbance of the geomagnetic field in magnetic storms. Modelling of the Dst index is thus very important for the analysis of the geomagnetic field. A data-based modelling approach, aimed at obtaining efficient models from limited input–output observational data, provides a powerful tool for analysing and forecasting geomagnetic activities including the prediction of the Dst index. In this study, the process of the Dst index is treated to be a structure-unknown system, where the solar wind parameter (VBs) and the solar wind dynamic pressure (P) are the system inputs, and the Dst index is the system output. A novel multiscale RBF (MSRBF) network is introduced to represent such a two-input and single-output system, where the Dst index is related to the solar wind parameter and the dynamic pressure, via a hybrid network model consisting of two submodels: a linear part that reflects the linear relationship between the output and the inputs, and a nonlinear part that captures the effect of the interacting contribution of past observations of the inputs and the output, on the current output. The proposed MSRBF network can easily be converted into a linear-in-the-parameters form and the training of the linear network model can easily be implemented using a forward orthogonal regression (FOR) algorithm. One advantage of the new MSRBF network, compared with traditional single scale RBF networks, is that the new network is more flexible for describing complex nonlinear dynamical systems.     

基于LSTM和CNN的高速柱塞泵故障诊断

针对高速轴向柱塞泵容易发生空化，且目前空化故障诊断方法存在依赖手工特征提取、鲁棒性不高的问题，提出了一种基于长短时记忆（LSTM）和一维卷积神经网络（1D-CNN）相结合的空化故障诊断方法。搭建了柱塞泵故障实验台，采集柱塞泵在不同空化等级下的壳体振动信号。利用LSTM和1D-CNN搭建的分类模型对不同进口压力情况下的振动信号进行空化等级识别。实验结果表明：提出的方法能够准确地识别出4类不同的空化等级，准确率高达99.5%，同时在不附加降噪方法的情况下，具有良好的鲁棒性，在0 dB信噪比的情况下，识别准确率高达87.3%。     

企业文化定量评价方法的研究

针对目前评价企业文化的方法在定量分析方面的不足，应用模糊数学理论建立了一个企业文化模糊综合评价模型是一个企业文化产例加以说明，为企业家决策提供科学依据。     

基于遗传算法的加速度控制PID参数自整定研究

详细介绍了加速度试验系统加速度PID参数自整定方法。首先利用过程辨识将控制系统数学模型近似为二阶振荡环节形式,得到传递函数表达式,然后利用遗传算法进行PID参数整定,使整定精确度和效率得到很大提高。     

用一台实验发动机测试发动机性能参数的方法

通过设计一台专用实验发动机进行试验，并应用参数辩识技术，商量确定发动机动态燃速、平均燃速、比冲等参数。通过理论分析和试验结果表明，该方法能准确测量性能参数，并能有效降低试验费用和缩短试验周期。     

飞行器参数辨识的最优方波形输入信号设计

用动态规划法设计了旨在提高飞行器气动参数辨识精度的最优方波形输入信号。设计出的信号不仅在工程上易于实现,还在精度意义上达到了最优。为了避免加输入信号后飞行器状态离开线性工作点,从而导致模型失效,该设计方法还考虑了输出约束。用于某型飞行器的输入信号设计结果表明,该法是有效的。     

采样时间序列的滑动递推容错预报算法

在导出线性模型系数递推最优辨识算法的基础上，探讨了滑动线性预报器的容错改进，建立了简洁、实用的滑动递推容错预报算法。通过仿真计算验证了算法的有效性。     

模式识别与模糊三值逻辑推理探讨

本文介绍了模式识别的概念与基本方法,形象思维与模式识别的关系和模糊逻辑与模糊推理,提出模糊三值逻辑的推理方法,旨在进一步探讨模式识别的方法和模糊逻辑推理理论,并附应用实例。     

基于脉冲包络前沿波形的雷达辐射源个体识别

提出了以脉冲包络前沿波形作为辐射源的“指纹”进行雷达辐射源个体识别的思路。首先将提取出的已知雷达脉冲包络前沿波形进行统计,求出一条能代表雷达辐射源的“标准”前沿波形曲线,然后将被测雷达脉冲包络前沿波形与求出的“标准”前沿波形曲线进行相像程度比较,识别出雷达辐射源个体。理论分析和实验结果表明利用雷达脉冲包络前沿波形可以较好地进行辐射源个体识别。     

NOVEL RADAR SIGNAL SORTING METHOD BASED ON GEOMETRIC COVERING

With the increase of complexity of electromagnetic environment and continuous appearance of advanced system radars, signals received by radar reconnaissance receivers become even more intensive and complex. There- fore, traditional radar sorting methods based on neural network algorithms and support vector machine （SVM） cannot process them effectively. Aiming at solving this problem, a novel radar signal sorting method based on the cloud model theory and the geometric covering algorithm is proposed. By applying the geometric covering algo- rithm to divide input signals into different covering domains based on their distribution characteristics, the method can overcome a typical problem that it is easy for traditional sorting algorithms to fall into the local extrema due to the use of complex nonlinear equation to describe input signals. The method uses the cloud model to describe the membership degree between signals to be sorted and their covering domains, thus it avoids the disadvantage that traditional sorting methods based on hard clustering cannot deinterleave the signal samples with overlapped param- eters. Experimental results show that the presented method can effectively sort advanced system radar signals with overlapped parameters in complex electromagnetic environment.