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.     

大型载人空间基础设施商业化运营模式初探

为提高以空间站为代表的大型载人空间基础设施运行效率和运营效益,本文在研究国际空间站(ISS)在轨运营模式及商业化做法的基础上,针对我国现有空间基础设施的在轨运营特点、国家战略和社会商业化需求,提出了引入社会资本建立商业化运营模式和建立商业成果转化基金等建议,成立专门的商业化运营管理机构,进行统筹管理和商业化运营,探索形成一套职责清晰、高质高效、效益突出的商业化运营管理体系,既保证空间基础设施在轨健康运行,高效开展各类空间应用,又降低建设和运营成本。在孕育商业模式和创新项目促进经济社会发展的同时,也具有重要的现实意义和深远的社会效益。     

基于高功率因数控制的永磁同步电机无电解电容驱动系统控制策略

永磁同步电机无电解电容驱动系统因其成本与寿命的优势,在白色家电领域逐步得到广泛的应用。然而,由于使用小容量的薄膜电容取代大容量的电解电容,母线电压会以两倍工频波动,在母线电压处于波谷时,逆变器输出电压容易饱和,导致控制性能恶化,网侧电流畸变。因此,提出了一种基于高功率因数控制的转矩控制环和电压矢量修正策略,能够有效提升网侧功率因数,抑制网侧电流谐波并符合IEC 6100032标准。该算法的有效性通过仿真得以验证。     

电动汽车轮毂电机技术的发展现状与发展趋势

轮毂电机具有结构紧凑、传动效率高、控制和转向灵活等优点。由轮毂电机驱动的电动汽车是新能源汽车重要的发展方向。通过各种电机的对比,认为永磁同步电机效率高、功率密度高、可靠性好,是轮毂驱动电机一个较好的选择。总结了电动汽车轮毂电机国内外的应用概况,介绍了轮毂电机电磁设计优化、控制策略及散热方式和结构方面进行的研究和工作,最后探讨了我国电动汽车轮毂电机研究中存在的问题,展望了轮毂电机未来的发展方向。     

电动汽车用永磁同步电机控制器设计

电动汽车逐渐成为人们出行的交通工具之一,对技术可靠性和安全性的要求较高。电机控制器是实现电池直流电源向三相交流电源转换的装置,驱动永磁同步电机(PMSM)输出力能。设计了一款基于瑞萨单片机的PMSM控制器,从元器件选型、硬件保护电路原理、PCB布局、控制算法、结构强度和热分析方面展开分析。最后生产控制器样机并搭建试验平台,对PMSM控制器进行了效率特性测试、发电测试和温升测试。试验结果验证了设计方案的合理性。     

永磁同步电机无位置估计误差的滑模观测器无速度传感器控制方法

传统滑模观测器(SMO)无速度传感器控制方法在电机的运行速度出现较大变化时,对位置的估计会出现稳态误差。为了消除位置的估计误差,提出了一种带有反动电势修正的SMO无速度传感器控制方法。反电动势的修正律基于永磁同步电机(PMSM)的dq轴电流模型。即使电机运行在速度大幅波动的情况下,也能保持位置估计误差为零,且该方法计算增量较小,易于实现。将所提出的方法在1台1.5 kW的PMSM上进行了仿真和试验,结果验证了位置估计误差能有效地收敛至零。     

某型超精密机床液体静压导轨温控设计与仿真方法研究

针对某型超精密机床液体静压导轨温度控制进行深入研究,提出多种不同的温度控制方法,并应用ANSYS仿真软件分别对液体静压导轨热变形进行了仿真,得出了不同温度控制方法下导轨的热变形大小。仿真结果显示,针对不同使用环境,通过不同的温度控制方法,对液体静压导轨进行热变形控制,从而满足超精密机床的使用要求,提高超精密机床的加工精度。。     

多通道隔离电压采集板设计及验证

本文以卫星地面供配电测试阶段的母线电压及二次电源电压测量为背景,设计了多通道隔离电压采集板卡。首先归纳总结了卫星母线电压、二次电源电压及遥测指令信号典型接口电路,分析了以上几种电路的输出阻抗特点,然后设计了合理的隔离电路及测量电路,最后提出基于成熟的CPCI总线架构的模块化板卡方案实现测试设备的通用化设计及隔离性验证方法;经实际产品研制和系统测试,该板卡能够满足供配电地面测试设备对多通道隔离电压的采集需求。     

反导作战杀伤效果评估方法研究

杀伤效果评估是反导作战必不可少的一个重要环节.本文对反导作战杀伤效果评估方法进行了探讨,分析了反导作战杀伤效果评估与抗击气动目标作战杀伤效果评估的区别,界定了成功拦截的两方面含义,提出了反导杀伤效果评估的准则,建立了反导杀伤效果评估模型,给出了反导杀伤效果判断逻辑.该方法可为反导作战指挥决策提供思路.