基于三因素模型的企业持续经营高风险预测研究

随着竞争的日趋激烈，企业持续经营不确定性显著增加，尽旱识别企业持续经营面临的风险，对于企业管理者、投资者来说都具有重要意义。现有的持续经营高风险研究依然没有摆脱“资料驱动型”的困境，文章根据三因素模型建立持续经营高风险预测模型。     

潜在电路分析中的拓扑模式识别算法研究

在网络树拓扑识别理论的分析方法与算法基础上 ,推导出网络树特定的五种基本拓扑模式识别的工程算法 ,以解决计算机对电路网络树进行自动拓扑识别问题。     

京津廊区域金融合作发展的问题研究

随着京津廊经济一体化进程的不断升级，区域金融合作也在快速发展。本文阐述了区域金融合作的主要原因，较全面地分析了京津廊区域金融合作现状，指出了目前京津廊区域金融合作存在的问题并提出了建议。     

机载风切变系统告警准则研究

根据风切变对飞机飞行影响的机理,以及FAA对CATⅠ类着陆最坏条件下的边界要求,推导了风切变的危险程度判据。通过计算,分析了垂直风切变与水平风切变对飞行性能的影响的异同,并通过对危险判据与性能恶化参数的相关性研究,提出了适用于机载风切变探测告警系统的告警准则。     

EXPERIMENT RESEARCH ON DYNAMIC LOAD IDENTIFICATION TECHNOLOGY BASED ON GENERALIZED ORTHOGONAL POLYNOMIAL THEORY (GOPT)

Dynamicloadisoneoftheimportantoriginalparametersinstructuraldynamicanalysis.Ithasobviousinfluencestodynamicsdesign,vibrationcontrols,activecontroltechnologyandsoon.Sincel97O,manyresearchitemsinthisfieldhavebeenaccomplishedintheworld-Sometheoriesandexperimentalmethodsofdynamicloadidentificationhadbeencreatedinfrequencydomain[l'2J-Howeverftherearesomedisadvantagesthattheycouldbeadaptedonlytoidenti-fythesteady-stateloadandnottoidentifythetransientload,suchasshockloadwithshortsampling.Forvarious…     

Quantitative assessment and visualization of flight risk induced by coupled multi-factor under icing conditions

Aircraft icing has been proven to be one of the most serious threats to flight safety. During the analysis of flight risk under icing conditions, quantitative assessment and visualization of flight risk are quite essential as they provide safe manipulation strategies in intricate conditions. However, they are rarely studied. Since the icing flight accidents are the result of the coupling of multiple unfavorable factors, in present study, we have proposed a method to quantitatively assess flight risk induced by multi-factor coupling under icing conditions by Monte-Carlo simulation and multivariate extreme value theory. The results demonstrate that the flight risk probability increases with the rise of unfavorable factors. Besides, a flight risk visualization method named flight safety window has been presented to build the flight risk distribution cloud maps in different complex conditions. The cloud maps show that the icing would give rise to atrophy of the safety scope, and the consequence would be even more severe when coupled with other more unfavorable factors. The proposed methods in this study would be useful in flight risk analysis under icing conditions and can enhance the pilot's situational awareness in selecting correct strategies within the safety zone to avoid unsafe manipulation.     

基于CMPSO算法的永磁同步电机转动惯量识别研究

永磁同步电机(PMSM)是一种具有很强非线性的动态系统,在工业驱动应用中发挥着重要作用。实时辨识转动惯量对于高精度PMSM系统控制和稳定性状态监测具有重要意义,但传统转动惯量识别方法精度较低。在传统离散模型参考自适应理论基础之上,用柯西变异粒子群优化(CMPSO)算法代替待辨识参数自适律设计环节,以实现PMSM转动惯量识别。该转动惯量辨识方法充分利用了CMPSO算法的快速高效收敛性,仿真结果和试验结果表明了可行性、正确性和准确性。     

Inverse identification of constitutive parameters of Ti2AlNb intermetallic alloys based on cooperative particle swarm optimization

Ti₂AlNb intermetallic alloy is a relatively newly developed high-temperature-resistant structural material, which is expected to replace nickel-based super alloys for thermally and mechanically stressed components in aeronautic and automotive engines due to its excellent mechanical properties and high strength retention at elevated temperature. The aim of this work is to present a fast and reliable methodology of inverse identification of constitutive model parameters directly from cutting experiments. FE-machining simulations implemented with a modified Johnson-Cook (TANH) constitutive model are performed to establish the robust link between observables and constitutive parameters. A series of orthogonal cutting experiments with varied cutting parameters is carried out to allow an exact comparison to the 2D FE-simulations. A cooperative particle swarm optimization algorithm is developed and implemented into the Matlab programs to identify the enormous constitutive parameters. Results show that the simulation observables (i.e., cutting forces, chip morphologies, cutting temperature) implemented with the identified optimal material constants have high consistency with those obtained from experiments, which illustrates that the FE-machining models using the identified parameters obtained from the proposed methodology could be predicted in a close agreement to the experiments. Considering the wide range of the applied unknown parameters number, the proposed inverse methodology of identifying constitutive equations shows excellent prospect, and it can be used for other newly developed metal materials.     

A new bearing fault diagnosis method based on modified convolutional neural networks

Fault diagnosis is vital in manufacturing system. However, the first step of the traditional fault diagnosis method is to process the signal, extract the features and then put the features into a selected classifier for classification. The process of feature extraction depends on the experimenters’ experience, and the classification rate of the shallow diagnostic model does not achieve satisfactory results. In view of these problems, this paper proposes a method of converting raw signals into two-dimensional images. This method can extract the features of the converted two-dimensional images and eliminate the impact of expert’s experience on the feature extraction process. And it follows by proposing an intelligent diagnosis algorithm based on Convolution Neural Network (CNN), which can automatically accomplish the process of the feature extraction and fault diagnosis. The effect of this method is verified by bearing data. The influence of different sample sizes and different load conditions on the diagnostic capability of this method is analyzed. The results show that the proposed method is effective and can meet the timeliness requirements of fault diagnosis.     

基于Hilbert-Huang变换的航天器发射段力学环境分析

文章基于Hilbert-Huang变换,对某载人航天器发射过程中整流罩分离期间测量的力学环境参数进行处理分析,利用HHT的基函数自适应性特点,得到振动时间历程信号的时频域Hilbert谱,准确识别出信号主频率及对应时间范围。此应用案例可为地面力学试验条件制定以及运载接口条件确定提供参考。