基于卷积神经网络的运载火箭测发网络流量异常检测技术

运载火箭测发网络是维系各型号运载火箭远距离测试及发射控制的重要国防基础设施,对测发网络流量进行异常检测是保证其正常工作的关键举措。近年来,随着测发网络功能的拓展,其面临的网络安全威胁越来越严重,而当前的安全检测主要依赖于基于异常特征库匹配的流量异常检测方法,这种检测方法对一些新型攻击检测能力非常有限。本文结合运载火箭测发网络实际特点,针对以使用用户数据报协议(UDP)为主的测发网络流量,设计一种新的基于固定数据包数目的流量图片样本生成方法,首次提出在测发网络流量异常检测问题上使用卷积神经网络,以原始网络流量作为输入,避开难以解决的人工特征集设计问题。通过测发网络真实网络流量数据进行实验,取得了较高的精度、召回率和准确率,验证了本方法具备一定的实用性。     

A multi-order method for predicting stability of a multi-delay milling system considering helix angle and run-out effects

In this paper, a multi-delay milling system considering helix angle and run-out effects is firstly established. An exponential cutting force model is used to model the interaction between a work-piece and a cutting tool, and a new approach is presented for accurately calibrating exponential cutting force coefficients and cutter run-out parameters. Furthermore, based on an implicit multi-step Adams formula and an improved precise time-integration algorithm, a novel stability prediction method is proposed to predict the stability of the system. The involved time delay term and periodic coefficient term are integrated as a comprehensive state term in the integral response which is approximated by the Adams formula. Then, a Floquet transition matrix with an arbitrary-order form is constructed by using a series of matrix multiplication, and the stability of the system is determined by the Floquet theory. Compared to classical semi-discretization methods and full-discretization methods, the developed method shows a good performance in convergence, efficiency, accuracy, and multi-order complexity. A series of cutting tests is further carried out to validate the practicability and effectiveness of the proposed method. The results show that the calibration process needs a time of less than 5 min, and the stability prediction method is effective.     

基于PSO-ELM的军用飞机维修保障系统效能评估研究

维修保障系统效能评估是军用飞机精细化、规范化管理的一项重要措施,科学的维修保障系统效能评估是精细化保障的基础,是提升战斗力的保证。针对军用飞机的维修保障系统效能评估问题,在总结军用飞机维修保障系统效能评估体系的基础上,提出基于粒子群优化极限学习机算法(PSO-ELM)的维修保障系统效能评估模型;并通过实例进行验证。结果表明:该算法应用于军用飞机维修保障系统的效能评估是可行的,可为军用飞机维修保障效能评估提供借鉴。     

航空发动机机匣摆线粗加工轨迹规划方法

针对机匣零件粗加工过程中凸台多、加工余量大、材料难切削、刀具磨损快、加工周期长等特点,提出了一种机匣摆线粗加工刀具轨迹规划方法,该方法能有效控制切削过程中刀具负载的变化,改善刀具切削过程中的加热-冷却循环,减缓刀具的磨损,提高机匣粗加工效率。首先,通过对两种摆线模型的分析,建立了摆线铣数学模型,并分析了摆线铣的优缺点;其次,结合机匣零件特点,将模型在精度范围内离散为点模型,利用圆锥将模型展开并建立展开模型与原始模型间的映射关系。通过对可加工区域的划分和平面逼近,生成了适用于机匣零件的摆线粗加工刀具轨迹。最后,分别通过摆线铣刀具磨损实验、平面型腔摆线铣实验和机匣摆线铣实验,验证了摆线铣在降低刀具磨损、延长刀具寿命方面的有效性,以及本文轨迹生成算法在航空发动机机匣实际加工中的正确性和高效性。研究成果能有效缩短加工周期、降低加工成本,提升机匣零件的粗加工效率。     

飞机蒙皮镜像铣加工稳定性分析

镜像铣技术是近年来提出的一种针对大尺寸薄壁件的加工方法,其加工环保、高效,具有逐步取代传统化铣加工的趋势。针对飞机蒙皮镜像铣加工过程中的颤振问题,首先,根据镜像铣加工特点,建立工艺系统颤振稳定性极限的预测模型;其次,通过有限元方法对蒙皮工件进行模态分析,分析蒙皮不同加工位置动力学特性变化导致的铣削稳定性变化,并通过实验测量获取工件动力学参数,对不同加工位置的稳定性做出预测;最后,开展加工实验,基于非接触测量方法,在线监测镜像铣加工区域的振动位移,通过时、频域信号对加工状态进行辨识,揭示了镜像铣加工过程的稳定性变化及失稳机制,验证了所提方法的准确性,在工程领域具有较高的实用价值。     

Framework and development of data-driven physics based model with application in dimensional accuracy prediction in pocket milling

In the manufacturing of thin wall components for aerospace industry, apart from the side wall contour error, the Remaining Bottom Thickness Error (RBTE) for the thin-wall pocket component (e.g. rocket shell) is of the same importance but overlooked in current research. If the RBTE reduces by 30%, the weight reduction of the entire component will reach up to tens of kilograms while improving the dynamic balance performance of the large component. Current RBTE control requires the off-process measurement of limited discrete points on the component bottom to provide the reference value for compensation. This leads to incompleteness in the remaining bottom thickness control and redundant measurement in manufacturing. In this paper, the framework of data-driven physics based model is proposed and developed for the real-time prediction of critical quality for large components, which enables accurate prediction and compensation of RBTE value for the thin wall components. The physics based model considers the primary root cause, in terms of tool deflection and clamping stiffness induced Axial Material Removal Thickness (AMRT) variation, for the RBTE formation. And to incorporate the dynamic and inherent coupling of the complicated manufacturing system, the multi-feature fusion and machine learning algorithm, i.e. kernel Principal Component Analysis (kPCA) and kernel Support Vector Regression (kSVR), are incorporated with the physics based model. Therefore, the proposed data-driven physics based model combines both process mechanism and the system disturbance to achieve better prediction accuracy. The final verification experiment is implemented to validate the effectiveness of the proposed method for dimensional accuracy prediction in pocket milling, and the prediction accuracy of AMRT achieves 0.014 mm and 0.019 mm for straight and corner milling, respectively.     

Loop细分曲面精加工刀具轨迹生成

细分曲面既能表示连续的几何设计模型也能表示离散的加工模型,避免了模型转换的复杂中间过程.细分曲面除了对于构造具有任意拓扑结构的复杂零件具有巨大的优势外,对于数字化制造也极具发展潜力.因此,对基于Loop细分曲面的精加工刀具轨迹生成算法进行了研究.首先利用基于弦长误差的自适应插值Loop细分得到精加工模型;然后利用等斜率跟踪法将精加工模型分割为平坦区域和非平坦区域.对各个区域依次进行处理,不同区域实施不同的刀具轨迹规划.据此,既避免了因细分过程数据量过大而导致的曲面精度不足或表面质量降低的问题,又可顺利计算整张曲面相对均匀残留高度的刀具轨迹.最后,为验证该算法的可行性进行铣削加工实验.      

镜像铣削加工奇异区域刀具路径优化

在大型薄壁件镜像铣削加工中,由奇异点引起的旋转轴运动不连续会影响加工质量,降低加工效率。针对此问题,分析了镜像铣削加工奇异点存在的原因,提出了一种奇异区域内的刀具路径优化方法。首先,针对镜像铣削系统的铣削头和支撑头分别建立了其旋转轴运动学变换模型,推导旋转轴微分运动关系,据此分析奇异点存在的原因及其对加工质量和效率的影响,定义了机床行程内的奇异区域范围。分析结果表明在镜像铣削系统行程范围内,仅铣削头存在奇异区域,而支撑头不存在奇异区域。然后,在镜像铣削加工刀路约束条件下,基于刀路光顺性指标建立了刀路优化模型。通过在加工曲面参数域内对跨越铣削头奇异区域的刀路进行调整,使得优化后的刀路更加光顺,以提高加工精度和表面质量,减少奇异区域附近的加工时间。最后,通过镜像铣削加工实验验证所提方法的有效性。     

Laser-induced oxidation assisted micro milling of high aspect ratio microgroove on WC-Co cemented carbide

Severe tool wear and poor surface quality are the main problems during micro machining of cemented carbide. In this work, an innovative hybrid process of laser-induced oxidation assisted micro milling (LOMM) was proposed to solve the problems. A nanosecond laser was utilized to induce oxidation of the WC-20%Co material, producing loose oxide which was easy to remove. The micro machinability of the material was improved by laser-induced oxidation. The oxidation mechanisms of cemented carbide were studied. A microgroove with a depth of 2.5 mm and aspect ratio of 5 was fabricated successfully. The milling force, surface quality and tool wear mechanisms were investigated. For comparison, a microgroove was also fabricated with conventional micro milling (COMM) using identical milling parameters. Results revealed that in LOMM the milling force and tool wear rate were extremely low during removing the oxide. The machined surface quality and dimensional accuracy achieved by LOMM were superior to those obtained by COMM. The surface roughness S_a of the microgroove bottom reached 88 nm in LOMM, while the cross-sectional geometry of the microgroove was a trapezoid. Perpendicularity of the microgroove sidewall machined by LOMM was better than that by COMM. The tool wear forms in LOMM were coating spalling and slight tool nose breakage. Compared with COMM, the tool life in LOMM was prolonged significantly. It indicates that the proposed hybrid process is an effective and efficient way to fabricate high aspect ratio micro-features with high dimensional accuracy.     

航天器单层板结构弹道极限的支持向量机预测模型

提出了一种基于非线性不可分支持向量机（SVM）方法的航天器单层板结构弹道极限预测模型。利用实验数据对SVM进行训练,建立穿透点和未穿透点的分隔面,进而预测新结构弹道极限特性。SVM的训练问题是以实验点分类正确性为约束,预测置信度最大化为目标的二次规划问题,用Lagrange对偶方法有效求解了该训练问题,并通过附加Lagrange乘子的上限约束处理不可分数据集。引入二次核函数将线性SVM推广到非线性,有效实现了实验点的分类。利用超高速碰撞实验数据对SVM弹道极限预测模型进行了验证,计算对比表明SVM方法有效预测了弹道极限,并且精度高于NASA JSC单层板弹道极限方程。对分离面方程分离变量,建立了基于SVM的弹道极限方程显式表达式。