Online Bearing Remaining Useful Life Prediction Based on a Novel Degradation Indicator and Convolutional Neural Networks

In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining useful life (RUL) for REBs are of crucial importance to ensure the reliability and safety of mechanical systems. To tackle this challenge, model-based approaches are often limited by the complexity of mathematical modeling. Conventional data-driven approaches, on the other hand, require massive efforts to extract the degradation features and construct health index. In this paper, a novel online data-driven framework is proposed to exploit the adoption of deep convolutional neural networks (CNN) in predicting the RUL of bearings. More concretely, the raw vibrations of training bearings are first processed using the Hilbert-Huang transform (HHT) and a novel nonlinear degradation indicator is constructed as the label for learning. The CNN is then employed to identify the hidden pattern between the extracted degradation indicator and the vibration of training bearings, which makes it possible to estimate the degradation of the test bearings automatically. Finally, testing bearings' RULs are predicted by using a $\epsilon$-support vector regression model. The superior performance of the proposed RUL estimation framework, compared with the state-of-the-art approaches, is demonstrated through the experimental results. The generality of the proposed CNN model is also validated by transferring to bearings undergoing different operating conditions

Solar flare hard X-ray spikes observed by RHESSI: a statistical study

Context. Hard X-ray (HXR) spikes refer to fine time structures on timescales of seconds to milliseconds in high-energy HXR emission profiles during solar flare eruptions. Aims. We present a preliminary statistical investigation of temporal and spectral properties of HXR spikes. Methods. Using a three-sigma spike selection rule, we detected 184 spikes in 94 out of 322 flares with significant counts at given photon energies, which were detected from demodulated HXR light curves obtained by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). About one fifth of these spikes are also detected at photon energies higher than 100 keV. Results. The statistical properties of the spikes are as follows. (1) HXR spikes are produced in both impulsive flares and long-duration flares with nearly the same occurrence rates. Ninety percent of the spikes occur during the rise phase of the flares, and about 70% occur around the peak times of the flares. (2) The time durations of the spikes vary from 0.2 to 2 s, with the mean being 1.0 s, which is not dependent on photon energies. The spikes exhibit symmetric time profiles with no significant difference between rise and decay times. (3) Among the most energetic spikes, nearly all of them have harder count spectra than their underlying slow-varying components. There is also a weak indication that spikes exhibiting time lags in high-energy emissions tend to have harder spectra than spikes with time lags in low-energy emissions.Comment: 16 pages, 13 figure

Chromospheric Evaporation in an X1.0 Flare on 2014 March 29 Observed with IRIS and EIS

Chromospheric evaporation refers to dynamic mass motions in flare loops as a result of rapid energy deposition in the chromosphere. These have been observed as blueshifts in X-ray and extreme-ultraviolet (EUV) spectral lines corresponding to upward motions at a few tens to a few hundreds of km/s. Past spectroscopic observations have also revealed a dominant stationary component, in addition to the blueshifted component, in emission lines formed at high temperatures (~10 MK). This is contradictory to evaporation models predicting predominant blueshifts in hot lines. The recently launched Interface Region Imaging Spectrograph (IRIS) provides high resolution imaging and spectroscopic observations that focus on the chromosphere and transition region in the UV passband. Using the new IRIS observations, combined with coordinated observations from the EUV Imaging Spectrometer, we study the chromospheric evaporation process from the upper chromosphere to corona during an X1.0 flare on 2014 March 29. We find evident evaporation signatures, characterized by Doppler shifts and line broadening, at two flare ribbons separating from each other, suggesting that chromospheric evaporation takes place in successively formed flaring loops throughout the flare. More importantly, we detect dominant blueshifts in the high temperature Fe XXI line (~10 MK), in agreement with theoretical predictions. We also find that, in this flare, gentle evaporation occurs at some locations in the rise phase of the flare, while explosive evaporation is detected at some other locations near the peak of the flare. There is a conversion from gentle to explosive evaporation as the flare evolves.Comment: ApJ in pres