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.     

Variation of dayside chorus waves associated with solar wind dynamic pressure based on MMS observations

The whistler-mode chorus waves are one of the most important plasma waves in the Earth’s magnetosphere. Generally, the amplitude of whistler-mode chorus waves prefers to strengthen when the energetic fluxes of anisotropic electrons increase outside the plasmapause. This characteristic is commonly associated with the geomagnetic storms or substorms. However, the relationship between the solar wind dynamic pressure (P_sw) and the long-time variation of chorus waves during the quiet period of the geomagnetic activity still needs more detailed investigations. In this paper, based on MMS observations, we present a chorus event just observed in the inner side of magnetopause without obvious geomagnetic storms or substroms. Interestingly, during this time interval, some P_sw fluctuations were recorded. Both the amplitudes and frequencies of chorus waves changed as a response to the variation in P_sw. It proved that the enhancement of P_sw increases the energetic electrons fluxes, which provides free energies for the chorus amplification. Furthermore, the wave growth rates calculated using linear theory increases and the central frequency of the chorus waves shifts to a higher frequency when the P_sw enhancement is greater, which are also consistent well with the observations. The results provide a direct evidence that the P_sw play an important role in the long-time variation of whistler-mode chorus waves inside the magnetopause.     

27-day variation in solar-terrestrial parameters: Global characteristics and an origin based approach of the signals

The Earth and the near interplanetary medium are affected by the Sun in different ways. Those processes generated in the Sun that induce perturbations into the Magnetosphere-Ionosphere system are called geoeffective processes and show a wide range of temporal variations, like the 11-year solar cycle (long term variations), the variation of ～27?days (recurrent variations), solar storms enduring for some days, particle acceleration events lasting for some hours, etc.In this article, the periodicity of ～27?days associated with the solar synodic rotation period is investigated. The work is mainly focused on studying the resulting 27-day periodic signal in the magnetic activity, by the analysis of the horizontal component of the magnetic field registered on a set of 103 magnetic observatories distributed around the world. For this a new method to isolate the periodicity of interest has been developed consisting of two main steps: the first one consists of removing the linear trend corresponding to every calendar year from the data series, and the second one of removing from the resulting series a smoothed version of it obtained by applying a 30-day moving average. The result at the end of this process is a data series in which all the signal with periods larger than 30?days are canceled.The most important characteristics observed in the resulting signals are two main amplitude modulations: the first and most prominent related to the 11-year solar cycle and the second one with a semiannual pattern. In addition, the amplitude of the signal shows a dependence on the geomagnetic latitude of the observatory with a significant discontinuity at approx. ±60°.The processing scheme was also applied to other parameters that are widely used to characterize the energy transfer from the Sun to the Earth: F10.7 and Mg II indices and the ionospheric vertical total electron content (vTEC) were considered for radiative interactions; and the solar wind velocity for the non-radiative interactions between the solar wind and the magnetosphere. The 27-day signal obtained in the magnetic activity was compared with the signals found in the other parameters resulting in a series of cross-correlations curves with maximum correlation between 3 and 5?days of delays for the radiative and between 0 and 1?days of delay for the non-radiative parameters. This result supports the idea that the physical process responsible for the 27-day signal in the magnetic activity is related to the solar wind and not to the solar electromagnetic radiation.     

RPC-MAG The Fluxgate Magnetometer in the ROSETTA Plasma Consortium

The fluxgate magnetometer experiment onboard the ROSETTA spacecraft aims to measure the magnetic field in the interaction region of the solar wind plasma with comet 67P/Churyumov-Gerasimenko. It consists of a system of two ultra light (about 28 g each ) triaxial fluxgate magnetometer sensors, mounted on the 1.5 m long spacecraft boom. The measurement range of each sensor is ±16384 nT with quantization steps of 31 pT. The magnetometer sensors are operated with a time resolution of up to 0.05 s, corresponding to a bandwidth of 0–10 Hz. This performance of the RPC-MAG sensors allows detailed analyses of magnetic field variations in the cometary environment. RPC-MAG furthermore is designed to study possible remnant magnetic fields of the nucleus, measurements which will be done in close cooperation with the ROSETTA lander magnetometer experiment ROMAP.     

杆的纵向振动分析

杆的纵向振动是连续系统的内容，一个连续系统具有分布质量，分丰弹性，分布阻尼，杆的纵向振动可用波动方程来描述，是用空间与时间坐标来描述的，运动方程是偏微方程。     

最坏风模型及对飞机突防航迹跟踪的影响

针对一类非线性动力学系统,本文推导出二次型性能指标下的微分对策解,由此得到一组含有非线性因素的最环风模型,这一模型特别适用于研究作空间机动飞行的飞机受外界环境扰动的灵敏性问题。最后考察了这一变化风场对飞机突防航迹非线性解耦跟踪的影响。     

在二元柔壁自适应风洞中利用面元法进行三元模型实验

简要叙述了在西北工业大学二元柔壁自适应风洞中利用面元法进行二元半机翼模型试验的研究情况，分析了面元法的基本思想和部分试验结果。     

Spectroscopic Measurement of Coronal Compositions

Although the elemental composition in all parts of the solar photosphere appears to be the same this is clearly not the case with the solar upper atmosphere (SUA). Spectroscopic studies show that in the corona elemental composition along solar equatorial regions is usually different from polar regions; composition in quiet Sun regions is often different from coronal hole and active region compositions and the transition region composition is frequently different from the coronal composition along the same line of sight. In the following two issues are discussed. The first involves abundance ratios between the high-FIP O and Ne and the low-FIP Mg and Fe that are important for meaningful comparisons between photospheric and SUA compositions and the second involves a review of composition and time variability of SUA plasmas at heights of 1.0≤h≤1.5R _⊙.     

一万氧压机轴振动控制分析与实践

本文介绍了一种非常规的高速轴振动抑制方法，主要是用振源分析技术，通过确诊设备故障原因来分析影响轴振动的主要因素，调节机器的系统刚度，再通过理论计算修订安装参数，制定设备故障处理对策，在涟源钢铁集团有限公司一万氧压机组上的实践取得了相当满意的效果，很有推广价值。     

飞行器振动智能分析与诊断

本文通过综合多个领域知识，引进功能特征描述概念，运用证据理论，提出了对飞行器等复杂系统进行分析诊断的一个新方法并初步完成了专家系统原型，通过具体实例，再现了故障现象