Multidimensional prognostics for rotating machinery: A review

open access articleDetermining prognosis for rotating machinery could potentially reduce maintenance costs and improve safety and avail- ability. Complex rotating machines are usually equipped with multiple sensors, which enable the development of multidi- mensional prognostic models. By considering the possible synergy among different sensor signals, multivariate models may provide more accurate prognosis than those using single-source information. Consequently, numerous research papers focusing on the theoretical considerations and practical implementations of multivariate prognostic models have been published in the last decade. However, only a limited number of review papers have been written on the subject. This article focuses on multidimensional prognostic models that have been applied to predict the failures of rotating machinery with multiple sensors. The theory and basic functioning of these techniques, their relative merits and draw- backs and how these models have been used to predict the remnant life of a machine are discussed in detail. Furthermore, this article summarizes the rotating machines to which these models have been applied and discusses future research challenges. The authors also provide seven evaluation criteria that can be used to compare the reviewed techniques. By reviewing the models reported in the literature, this article provides a guide for researchers considering prognosis options for multi-sensor rotating equipment

HIGH RESOLUTION X-RAY SPECTROSCOPY OF THE LOCAL HOT GAS ALONG THE 3C 273 SIGHTLINE

National Natural Science Foundation of China [11243001, 11273021]; Fundamental Research Funds for the Central Universities [2013121008]X-ray observations of highly ionized metal absorption lines at z = 0 provide critical information on the hot gas distribution in and around the Milky Way. We present a study of more than 10 yr of Chandra and XMM-Newton observations of 3C 273, one of the brightest extragalactic X-ray sources. Compared with previous works, we obtain much tighter constraints on the physical properties of the X-ray absorber. We also find a large, non-thermal velocity at similar to 100-150 km s(-1), the main reason for the higher line equivalent width when compared with other sightlines. Using joint analysis with X-ray emission and ultraviolet observations, we derive a size of 5-15 kpc and a temperature of ( 1.5-1.8) x 10(6) K for the X-ray absorber. The 3C 273 sightline passes through a number of Galactic structures, including radio loops I and IV, the North Polar Spur, and the neighborhood of the newly discovered "Fermi bubbles." We argue that the X-ray absorber is unlikely to be associated with the nearby radio loops I and IV; however, the non-thermal velocity can be naturally explained as the result of the expansion of the "Fermi bubbles." Our data imply a shock-expansion velocity of 200-300 km s(-1). Our study indicates a likely complex environment for the production of the Galactic X-ray absorbers along different sightlines, and highlights the significance of probing galactic feedback with high resolution X-ray spectroscopy

A novel multi-information fusion grey model and its application in wear trend prediction of wind turbines

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The small and fluctuating samples of lubricating oil data render the wear trend prediction a challenging task in operation and maintenance management of wind turbine gearboxes. To deal with this problem, this paper puts forward a method to enhance the prediction accuracy and robustness of the grey prediction model by introducing multi-source information into traditional grey models. Multi-source information is applied by creating a mapping sequence according to the sequence to be predicted. The significance of the key parameters in the proposed model was investigated by numerical experiments. Based on the results from the numerical experiments, the effectiveness of the proposed method was demonstrated using lubricating oil data captured from industrial wind turbine gearboxes. A comparative analysis was also conducted with a number of selected other models to illustrate the superiority of the proposed model in dealing with small and fluctuating data. Prediction results show that the proposed model is able to relax the quasi-smooth requirement of data sequence and is much more robust in comparison to exponential regression, linear regression and non-equidistance GM(1,1) models

White Dwarfs with Infrared Excess from LAMOST Data Release 5

Infrared excess is an important probe of sub-stellar companions and/or debris disks around white dwarfs (WDs). Such systems are still rare for in-depth understanding of their formation and long-term evolution. One of the largest spectroscopic surveys carried out by the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) recently released more than $3000$ WDs, a significant fraction of which have not undergone excess search. Here we present cross-correlation of LAMOST DR5 WD catalog with the Pan-STARRS, SDSS, UKIDSS, 2MASS, and {\it WISE}. By performing SED (spectral energy distribution) fitting for 846 WDs with $WISE$ detections, we identify 50 candidates with infrared excess, including 7 candidate WD+M dwarf binaries, 31 candidate WD+brown dwarf (BD) binaries and 12 candidate WD+dust disk systems. 8 of the dust disk systems are our new identifications. Utilizing a systematic survey with accurate stellar parameters derived from spectral fitting, our work is an important addition to previous searches for infrared excess from SDSS and {\it Gaia} WDs, and provides a significant ($\gtrsim8\%$) complement to current database of WDs with candidate BD companions and dust disks. The frequencies of WD+BD binaries and WD+dust disk systems are constrained to be $\lesssim3.7\%$ and $\sim1.4\%$, respectively. The properties of candidate dust disk systems are discussed. All of our candidates require follow-up observations for confirmation owing to limited spatial resolution of {\it WISE}.Comment: 15 pages, 7 figures, 3 tables; accepted for publication in Ap

Similarity-based information fusion grey model for remaining useful life prediction of aircraft engines

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose Online health monitoring of large complex equipment has become a trend in the field of equipment diagnostics and prognostics due to the rapid development of sensing and computing technologies. The purpose of this paper is to construct a more accurate and stable grey model based on similar information fusion to predict the real-time remaining useful life (RUL) of aircraft engines. Design/methodology/approach First, a referential database is created by applying multiple linear regressions on historical samples. Then similarity matching is conducted between the monitored engine and historical samples. After that, an information fusion grey model is applied to predict the future degradation trajectory of the monitored engine considering the latest trend of monitored sensory data and long-term trends of several similar referential samples, and the real-time RUL is obtained correspondingly. Findings The results of comparative analysis reveal that the proposed model, which is called similarity-based information fusion grey model (SIFGM), could provide better RUL prediction from the early degradation stage. Furthermore, SIFGM is still able to predict system failures relatively accurately when only partial information of the referential samples is available, making the method a viable choice when the historical whole life cycle data are scarce. Research limitations/implications The prediction of SIFGM method is based on a single monotonically changing health indicator (HI) synthesized from monitoring sensory signals, which is assumed to be highly relevant to the degradation processes of the engine. Practical implications The SIFGM can be used to predict the degradation trajectories and RULs of those online condition monitoring systems with similar irreversible degradation behaviors before failure occurs, such as aircraft engines and centrifugal pumps. Originality/value This paper introduces the similarity information into traditional GM(1,1) model to make it more suitable for long-term RUL prediction and also provide a solution of similarity-based RUL prediction with limited historical whole life cycle data

A Wideband Low-Profile All-Metal Cavity Slot Antenna With Filtering Performance for Space-Borne SAR Applications

This letter presents a wideband all-metal cavity slot antenna with a filtering performance for space-borne synthetic aperture radar applications. The proposed antenna element consists of a metal cavity and several radiation slots. It is fabricated by aluminium through milling and welding process, the techniques of which are reliable for the space environment. Benefiting from multiresonances of the cavity and slots, the antenna is able to obtain a wide operating bandwidth. Additionally, the cavity has a very low profile of 2.8 mm, equivalent to 0.093 wavelength at the central operating frequency. An 8 × 12 antenna array is designed, fabricated, and measured for performance verification. The measured impedance bandwidth with S 11 <;-10 dB is achieved from 7.2 to 12.2 GHz, giving a relative bandwidth of 51%. Furthermore, it shows good filtering characteristic with more than 20 dB out-of-band rejections, which is capable to suppress unwanted interferences and contribute to a good electromagnetic compatibility desig