多重激励下机匣振动能量传递规律与耦合特性

为了研究机匣振动能量的传递规律和转子多重不平衡激励能量在机匣上的耦合特性，采用有限元法建立了包括压气机机匣、燃烧室机匣和涡轮机匣组件在内的航空发动机整机机匣模型，应用结构声强法计算分析了机匣在不同激励频率下振动能量的传递规律和耦合特性。结果表明：（1）机匣共振时，振动能量的穿透力最强，主要以纵波和剪切波的形式穿过机匣安装边向其他部件传递。（2）机匣的模态振型与其振动能量传递特性有关，振动幅值较大的机匣组件同时也是主要参与振动能量传递的机匣组件。（3）振动能量在机匣上的传递具有解耦特性，多重激励同时作用下的机匣振动能量传递特性可以分解为多个单一激励作用下机匣振动能量的线性矢量和。     

一种新的飞行器运输振动负荷确定方法浅探

指出了飞行器实物运输试验面临的问题，提出了采用等比模型实物进行运输试验的方法。通过对该方法的基本原理及关注重点予以阐释，在充分运用试验数据的基础上，对提高飞行器运输状态下抗振动冲击设计能力提出建议。     

Online condition diagnosis for a two-stage gearbox machinery of an aerospace utilization system using an ensemble multi-fault features indexing approach

China manned space station is designed to operate for over ten years. Long-term and sustainable research on space science and technology will be conducted during its operation. The application payloads must meet the ‘‘long life and high reliability" mission requirement. Gearbox machinery is one of the essential devices in an aerospace utilization system, failure of which may lead to downtime loss even during some disastrous catastrophes. A fault diagnosis of gearbox has attracted attentions for its significance in preventing catastrophic accidents and guaranteeing sufficient maintenance. A novel fault diagnosis method based on the Ensemble Multi-Fault Features Indexing(EMFFI) approach is proposed for the condition monitoring of gearboxes. Different from traditional methods of signal analysis in the one-dimensional space, this study employs a supervised learning method to determine the faults of a gearbox in a two-dimensional space using the classification model established by training the features extracted automatically from diagnostic vibration signals captured. The proposed method mainly includes the following steps. First, the vibration signals are transformed into a bi-spectrum contour map utilizing bi-spectrum technology,which provides a basis for the following image-based feature extraction. Then, Speeded-Up Robustness Feature(SURF) is applied to automatically extract the image feature points of the bi-spectrum contour map using a multi-fault features indexing theory, and the feature dimension is reduced by Linear Discriminant Analysis(LDA). Finally, Random Forest(RF) is introduced to identify the fault types of the gearbox. The test results verify that the proposed method based on the multi-fault features indexing approach achieves the target of high diagnostic accuracy and can serve as a highly effective technique to discover faults in a gearbox machinery such as a two-stage one.     

Virtual sensing method for monitoring vibration of continuously variable configuration structures using long short-term memory networks

Vibration monitoring by virtual sensing methods has been well developed for linear time-invariant structures with limited sensors. However, few methods are proposed for Time-Varying (TV) structures which are inevitable in aerospace engineering. The core of vibration monitoring for TV structures is to describe the TV structural dynamic characteristics with accuracy and efficiency. This paper propose a new method using the Long Short-Term Memory (LSTM) networks for Continuously Variable Configuration Structures (CVCSs), which is an important subclass of TV structures. The configuration parameters are used to represent the time-varying dynamic characteristics by the “freezing” method. The relationship between TV dynamic characteristics and vibration responses is established by LSTM, and can be generalized to estimate the responses with unknown TV processes benefiting from the time translation invariance of LSTM. A numerical example and a liquid-filled pipe experiment are used to test the performance of the proposed method. The results demonstrate that the proposed method can accurately estimate the unmeasured responses for CVCSs to reveal the actual characteristics in time-domain and modal-domain. Besides, the average one-step estimation time of responses is less than the sampling interval. Thus, the proposed method is promising to on-line estimate the important responses of TV structures.     

航天器柔性太阳翼最优PPF主动振动抑制方法

针对采用可变速控制力矩陀螺(VSCMG)进行柔性太阳翼振动抑制问题，提出一种基于求解非光滑 H∞ 综合问题的最优参数正位置反馈(PPF)控制方法。首先，建立考虑VSCMG和柔性太阳翼耦合的振动模型，得到了线性化的约束陀螺柔性板动力学模型，基于同位控制思想推导了以角度陀螺为测量装置的约束陀螺柔性板全阶状态空间模型。针对被控对象特性，确定最优PPF控制器的结构构型和待优化参数。进而，通过对约束陀螺柔性板全阶状态空间模型进行降阶、修正和加权处理，将PPF控制器参数优化问题转化为在PPF控制器构型约束条件下的非光滑H∞综合问题，并应用一阶下降算法进行寻优求解，实现最优PPF控制器的设计。该方法能够实现对各阶陀螺模态的独立控制，在保证快速性和鲁棒性的前提下，实现最优PPF参数的稳定高效求解。仿真结果表明，所提出的最优PPF控制方法能够快速、鲁棒地实现航天器柔性太阳翼的主动振动抑制。     

振动控制中的理想特征结构及其最优配置

本文依据系统响应与其特征结构的关系，提出了振动控制的最优反馈特征结构配置方法，它针对结构承受的载荷，利用多目标优化理论，确定系统的理想特征结构，并文献的方法配置初始反馈，为了达到最优控制，文中建立了满足理想特征结构配置的目标函数，并且将保证最优控制的Ｌｙａｐｕｎｏｖ方程作为约束条件，使得反馈在满意的控制品质下，消耗的控制能最小。     

卫星次承力结构设计对振动响应的影响

以风云二(FY-2)气象卫星为例，分析了设计中卫星次承力结构类型、连接、梁形式、功能单机结构和材料等对结构动态性能的影响，并提出了针对性设计改进。试验结果验证了改进的有效性。     

用2032信号分析系统诊断滚动轴承损伤类故障

本文从理论上提出了用共振解调法诊断滚动轴承损伤类故障时所得包络信号及其频谱图的基本特征,并用2032信号分析系统对滚动轴承实施了共振解调诊断,验证了理论分析的正确性.     

微小孔加工试验及刀具磨损机理

由于钛合金和印刷电路板的难加工性使得微小孔的加工精度和表面质量难以保证,刀具技术成为提高加工效率的主要障碍。本文应用3种不同涂层钻头对钛合金和印刷电路板进行微小孔钻削对比试验,研究了进给速度与切削力和扭矩的关系,分析了刀具的磨损特征以及孔的表面质量和孔入口处的毛刺情况。结果表明:钻削印刷电路板的临界进给速度为1 591.2 mm/m in,涂层对钻削力和扭矩的影响不明显;类金钢石(DLC)涂层硬质合金钻头比普通硬质合金钻头和T iC涂层硬质合金钻头更适合加工钛合金材料微小孔。     

系统级产品振动试验仿真

本文利用有限元建模技术，建立了振动台、试验夹具、系统级产品精细的有限元模型，对各部件模型进行了振动特性计算，并通过部件模态试验和振动试验结果及总体综合分析相结合的方法对有限元模型进行了多次修正，得到了总体有限元模型。根据此模型进行了产品的振动试验仿真，并用试验结果对仿真结果进行了验证，验证结果表明系统级产品振动试验仿真结果与振动台试验实测数据是具有可比性的，振动响应的均方根值误差基本上小于lO％，功率谱曲线趋势近似，误差在工程允许的范围内。