Semi-supervised gear fault diagnosis using raw vibration signal based on deep learning

In aerospace industry, gears are the most common parts of a mechanical transmission system. Gear pitting faults could cause the transmission system to crash and give rise to safety disaster. It is always a challenging problem to diagnose the gear pitting condition directly through the raw signal of vibration. In this paper, a novel method named augmented deep sparse autoencoder (ADSAE) is proposed. The method can be used to diagnose the gear pitting fault with relatively few raw vibration signal data. This method is mainly based on the theory of pitting fault diagnosis and creatively combines with both data augmentation ideology and the deep sparse autoencoder algorithm for the fault diagnosis of gear wear. The effectiveness of the proposed method is validated by experiments of six types of gear pitting conditions. The results show that the ADSAE method can effectively increase the network generalization ability and robustness with very high accuracy. This method can effectively diagnose different gear pitting conditions and show the obvious trend according to the severity of gear wear faults. The results obtained by the ADSAE method proposed in this paper are compared with those obtained by other common deep learning methods. This paper provides an important insight into the field of gear fault diagnosis based on deep learning and has a potential practical application value.     

Multi-faults diagnosis of rolling bearings via adaptive customization of flexible analytical wavelet bases

Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features, as well as its easy burying in the complex, non-stationary structural vibrations and strong background noises. In this paper, a method based on the flexible analytical wavelet transform (FAWT) possessing fractional scaling and translation factors is proposed to identify multiple faults occurred in different components of rolling bearings. During the route of the proposed method, the proper FAWT bases are constructed via genetic optimization algorithm (GA) based on maximizing the spectral correlated kurtosis (SCK) which is firstly presented and proved to be efficient and effective in indicating interested fault mode. Via using the customized FAWT bases for each interested fault mode, the original vibration measurements are decomposed into fine frequency subbands, and the sensitive subband which enhances the signal-to-noise ratio (SNR) is selected to exhibit the fault signature on its envelope spectrum. The proposed method is tested via simulated signals, and applied to analyze the experimental vibration measurements from the running roller bearings subjected to outrace, inner-race and roller defects. The analysis results validate the effectiveness of the proposed method in identifying multi-faults occurred in different components of rolling bearings.     

Study of highly perturbed spacecraft formation dynamics via approximation

This paper explores methods for approximating and analyzing the dynamics of highly perturbed spacecraft formations with an emphasis on computationally efficient approaches. This facilitates on-board computation or rapid preliminary mission design analysis. Perturbed formation dynamics are often approximated as linear time-varying (LTV) systems, for which Floquet theory can be used to analyze the degree of system instability. Furthermore, the angular momentum of the relative orbital state can be computed with the approximate dynamics to provide additional insight. A general methodology is developed first and then applied to the problem of unstable formation dynamics in asteroid orbits. Here the dominant perturbative effects due to low-order gravitational harmonics and solar radiation pressure are modeled. Numerical simulations validate the approach and illustrate the approximation accuracy achieved.     

Fully distributed time-varying formation tracking control for multiple quadrotor vehicles via finite-time convergent extended state observer

This paper investigates a time-varying anti-disturbance formation problem for a group of quadrotor aircrafts with time-varying uncertainties and a directed interaction topology. A novel Finite-Time Convergent Extended State Observer (FTCESO) based fully-distributed formation control scheme is proposed to enhance the disturbance rejection and the formation tracking performances for networked quadrotors. By adopting the hierarchical control strategy, the multi-quadrotor system is separated into two subsystems: the outer-loop cooperative subsystem and the inner-loop attitude subsystem. In the outer-loop subsystem, with the estimation of disturbing forces and uncertain dynamics from FTCESOs, an adaptive consensus theory based cooperative controller is exploited to ensure the multiple quadrotors form and maintain a time-varying pattern relying only on the positions of the neighboring aircrafts. In the inner-loop subsystem, the desired attitude generated by the cooperative control law is stably tracked under a FTCESO-based attitude controller in a finite time. Based on a detailed algorithm to specify the cooperative control protocol, the feasibility condition to achieve the time-varying anti-disturbance formation tracking is derived and the rigorous analysis of the whole closed-loop multi-quadrotor system is given. Some numerical examples are conducted to intuitively demonstrate the effectiveness and the improvements of the proposed control framework.     

某型装备能源电池异常爆破故障分析

对一起因电池设计缺陷引发装备战训失利的故障进行分析,重点对电池工作机理和设计缺陷展开解析,明确故障定位,并对国内外装备弹上不同体系电池的优缺点进行比较,旨在为产品维护保障、国产化科研等工作提供参考。     

面向学生的智能解题专家系统的研究与设计

探讨了网络在专家系统中的应用 ,给出了一个基于网络的面向学生的智能解题专家系统的模型 ,分析了设计的基本过程。从专家系统出发 ,探讨了基于知识的推理系统。最后 ,从以上设计出发 ,总结了基于该模型的系统需进一步研究的工作。     

基于关联分析的机载电子设备SRU级故障诊断方法

针对机载设备二类检测设备将故障隔离到SRU的要求,对LRU的内部结构进行了分析,提出了点、底项、组底项的概念,用关联值表示点与点之间、点与SRU之间及组底项之间的关联关系;针对多SRU结构UUT,提出逐级排除法故障诊断方法.     

一种用于人体早期病变诊断的仪器

根据探针在人体穴位电流量的变化情况 ,具体分析了该仪器电路设计的工作原理、电路结构及具体的使用方法。     

Calculation of the transonic dip of airfoils using viscous-inviscid aerodynamic interaction method

A numerical procedure for the calculation of the transonic dip of airfoils in the time domain is presented. A viscous-inviscid aerodynamic interaction method is taken to calculate the unsteady aerodynamic loads. In the present case the integral boundary layer equations are coupled with the Transonic Small Disturbance (TSD) Potential Equation. The coupling between structural motion and aerodynamic loads is carried out using State Space equation. It is solved by State Transition Matrix technique. Results are presented for NACA 64A010 and NLR 7301 airfoils with structural data from Isogai and DLR, respectively. Comparisons show good agreement with other numerical results. Certain deviations of experimental data taken from literature need more insight in the detailed test conditions.     

现场动平衡技术在生产中的应用

利用美国恩泰克公司提供的DP1500数据采集仪及现场动平衡软件,以实例说明了现场动平衡技术在锅炉引风机、排粉风机、电动机、机泵等转动设备不平衡故障排除中的应用,介绍了不平衡故障的识别方法,揭示出该技术在生产中的实用性、先进性和经济性.