基于部件跟踪滤波器的解析余度技术

研究一种以发动机部件跟踪滤波器(CTF)为基础的解析余度技术, 它将CTF与故障检测、隔离和适应逻辑进行了有效的综合, 以改进发动机数控系统的可靠性。仿真表明, 本文所设计的解析余度技术, 在传感器无故障时, 机载模型能正确跟踪发动机的变化。当传感器发生故障时, 在不损坏机载模型的情况下, 又能及时、有效地进行硬、软故障的检测、隔离与适应。      

转盘-静盘腔内层流流动的相似分析及其N-S方程数值解

对转盘-静盘系统进行的相似分析表明:转盘-静盘腔内层流流场主要受入口流量数、旋转雷诺数、盘腔间隙系数、密封间隙系数和入口孔径比等5个参数影响。采用SIMPLE法对转盘-静盘系统层流流场进行了计算。结果表明:盘腔间隙的大小和密封冠对旋转核的存在具有决定性影响, 当入口流量数减小或旋转雷诺数增大时, 旋转核趋向于生成且转速增大;证明了影响径向速度的主要是惯性力, 而影响周向速度的是惯性力和粘性力共同作用。通过数值计算还得到了防止外燃气“入侵”的最小入口流量数。      

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.     

Aircraft engine fault detection based on grouped convolutional denoising autoencoders

Many existing aircraft engine fault detection methods are highly dependent on performance deviation data that are provided by the original equipment manufacturer. To improve the independent engine fault detection ability, Aircraft Communications Addressing and Reporting System (ACARS) data can be used. However, owing to the characteristics of high dimension, complex correlations between parameters, and large noise content, it is difficult for existing methods to detect faults effectively by using ACARS data. To solve this problem, a novel engine fault detection method based on original ACARS data is proposed. First, inspired by computer vision methods, all variables were divided into separated groups according to their correlations. Then, an improved convolutional denoising autoencoder was used to extract the features of each group. Finally, all of the extracted features were fused to form feature vectors. Thereby, fault samples could be identified based on these feature vectors. Experiments were conducted to validate the effectiveness and efficiency of our method and other competing methods by considering real ACARS data as the data source. The results reveal the good performance of our method with regard to comprehensive fault detection and robustness. Additionally, the computational and time costs of our method are shown to be relatively low.     

在轨服务中的仿生抗冲击结构研究

针对在轨服务航天器末端执行器在抓捕目标时由于速度不匹配而产生的振动问题,本文受自然界中高速奔跑的袋鼠腿部结构启发,将嵌套仿生X形结构安装在服务航天器机械臂和抓捕机构之间,来抑制由碰撞所产生的抓捕后振动。通过对此系统在受到外冲击力下进行建模分析,并与传统的弹簧质量阻尼器和单层仿生X形结构的隔振性能进行对比,仿真结果表明,此嵌套仿生X形结构隔振系统具有更好的振动隔离效果,能够更加有效地抑制航天器抓捕后振动。     

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。     

采用自适应模型跟踪控制的发动机燃油控制系统含实物仿真

在航空发动机控制系统的研制、生产和使用中,各种仿真技术起到了十分重要的作用,尤其是包含控制器、传感器和执行机构实物的发动机控制系统含实物仿真。由于其能展现发动机控制系统的重要性能品质,从而已成为控制系统研制过程中的关键步骤。本文介绍一种基于微机数字控制技术的发动机燃油转速控制系统的含实物仿真,由于采用了自适应模型跟踪控制算法,故有效地提高了发动机燃油控制系统的含实物仿真精度,对增加整个发动机控制系统的含实物仿真置信度起到了重要的作用。     

桁架结构主被动振动控制的时间延迟分析与预估计补偿法

时间延迟是实时振动控制迫切需要解决的问题,以主被动控制组合式桁架结构为研究对象,分析了延迟对实时控制的影响,论述了延迟时间的测定,提出了一种有效的延迟补偿方法。通过一个平面桁架算例验证了该补偿方法的有效性,定量分析了相位滞后与控制效果的关系。     

航天结构的约束阻尼振动抑制优选方案研究

约束阻尼结构的高可靠性和良好的阻尼性能使得它在航天振动控制工程中得到了越来越广泛的应用。但是为实现约束阻尼结构的减重增效 ,需要寻找其优选的方案。本文通过典型的一种耦合结构约束阻尼振动抑制方案研究 ,得到了其优选的振动抑制方案。仿真结果表明 ,约束层和粘弹层相等面积铺设的方案比较保守 ;可以通过合理布置粘弹层而不改变约束层面积的方案来代替 ,实现约束阻尼结构的减重增效。该方案可为约束阻尼振动抑制设计提供参考     

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。