Monitoring based on time-frequency tracking of estimated harmonic series and modulation sidebands

International audienceThe installation of a Condition Monitoring System (CMS) on a mechanical machine (e.g., on a wind turbine) aims to reduce the operating costs by applying a predictive maintenance strategy. The CMS is composed of sensors acquiring signals from which system health indicators are computed and monitored. Part of those indicators are predefined depending on the monitored system kinematic and are computed by averaging large or narrow spectral bands. The averaging and the need for predefined thresholds for default detection may induce lots of false alarms while reducing the ability to detect the default early. To get precise health indicators reflecting each local meaningful spectral content, the AStrion software proposes a new data-driven monitoring strategy without any a priori on the measured signals. First, an automatic spectral analysis is applied to detect, characterize and classify the different spectral structures of the successive measured signals. These spectral structures can be either single spectral peaks, either peaks grouped in harmonic series or in modulation sidebands [1]. Second, these spectral structures are characterized by several features, including for example the number of peaks, the characteristic frequencies and the energy. This gives a snapshot of the system health at the signal acquisition time. To perform an automatic diagnosis of the system, the spectral evolution should be tracked along the time snapshots. In this paper, we propose a time tracking method based on McAulay & Quatieri algorithm [2] which has been designed originally for speech signals acquired on a continuous temporal basis. We have adapted [2] in order to account not only for single spectral peak evolution but also for the evolution of more complex structures such as harmonic series or modulation sidebands, even in the case of signals acquired on a non-regular temporal basis, as it is often the case. Moreover, an added sleep state makes the proposed method robust against nondetected spectral structures at a given time. Finally, the temporal evolution of the spectral structure features can be monitored and used as precise health indicators. The following figure is a result of the proposed method applied on real signals coming from a test bench designed in KAStrion project for simulating a wind turbine operation and for which the inner race of the main bearing has been damaged. Above, the time frequency map displays a zoom of the spectral peaks detected (around 20.000 per snapshot, represented by circles) and shows in blue the tracking from 44 to 189 operating hours of a spectral peak at 3.45 Hz. This particular peak evolves at 129 hours to become an harmonic series with more and more peaks and energy. Its energy evolution (plotted below) shows an increase which mirrors out a failure. In a following step [3], this spectral structure has been associated with the ball pass frequency of the inner ring of the main bearing. A dismantling of this bearing has confirmed the failure. This result shows the potential of the proposed data-driven method to create automatically relevant health indicators

NGSQC: cross-platform quality analysis pipeline for deep sequencing data

Abstract Background While the accuracy and precision of deep sequencing data is significantly better than those obtained by the earlier generation of hybridization-based high throughput technologies, the digital nature of deep sequencing output often leads to unwarranted confidence in their reliability. Results The NGSQC (N ext G eneration S equencing Q uality C ontrol) pipeline provides a set of novel quality control measures for quickly detecting a wide variety of quality issues in deep sequencing data derived from two dimensional surfaces, regardless of the assay technology used. It also enables researchers to determine whether sequencing data related to their most interesting biological discoveries are caused by sequencing quality issues. Conclusions Next generation sequencing platforms have their own share of quality issues and there can be significant lab-to-lab, batch-to-batch and even within chip/slide variations. NGSQC can help to ensure that biological conclusions, in particular those based on relatively rare sequence alterations, are not caused by low quality sequencing.http://deepblue.lib.umich.edu/bitstream/2027.42/112794/1/12864_2010_Article_3466.pd

INTEGRATE: Gene fusion discovery using whole genome and transcriptome data

While next-generation sequencing (NGS) has become the primary technology for discovering gene fusions, we are still faced with the challenge of ensuring that causative mutations are not missed while minimizing false positives. Currently, there are many computational tools that predict structural variations (SV) and gene fusions using whole genome (WGS) and transcriptome sequencing (RNA-seq) data separately. However, as both WGS and RNA-seq have their limitations when used independently, we hypothesize that the orthogonal validation from integrating both data could generate a sensitive and specific approach for detecting high-confidence gene fusion predictions. Fortunately, decreasing NGS costs have resulted in a growing quantity of patients with both data available. Therefore, we developed a gene fusion discovery tool, INTEGRATE, that leverages both RNA-seq and WGS data to reconstruct gene fusion junctions and genomic breakpoints by split-read mapping. To evaluate INTEGRATE, we compared it with eight additional gene fusion discovery tools using the well-characterized breast cell line HCC1395 and peripheral blood lymphocytes derived from the same patient (HCC1395BL). The predictions subsequently underwent a targeted validation leading to the discovery of 131 novel fusions in addition to the seven previously reported fusions. Overall, INTEGRATE only missed six out of the 138 validated fusions and had the highest accuracy of the nine tools evaluated. Additionally, we applied INTEGRATE to 62 breast cancer patients from The Cancer Genome Atlas (TCGA) and found multiple recurrent gene fusions including a subset involving estrogen receptor. Taken together, INTEGRATE is a highly sensitive and accurate tool that is freely available for academic use

Modelling Solar Energetic Neutral Atoms from Solar Flares and CME-driven Shocks

We examine the production of energetic neutral atoms (ENAs) in solar flares and CME-driven shocks and their subsequent propagation to 1 au. Time profiles and fluence spectra of solar ENAs at 1 au are computed for two scenarios: 1) ENAs are produced downstream at CME-driven shocks, and 2) ENAs are produced at large-scale post-flare loops in solar flares. Both the time profiles and fluence spectra for these two scenarios are vastly different. Our calculations indicate that we can use solar ENAs as a new probe to examine the underlying acceleration process of solar energetic particles (SEPs) and to differentiate the two accelertion sites: large loops in solar flares and downstream of CME-driven shocks, in large SEP events.Comment: 11 pages, updated figures and paper is accepted by Ap

Amplification schemes and multi-channel DBP for unrepeatered transmission

The performance of unrepeatered transmission of a seven Nyquist-spaced 10 GBd PDM-16QAM superchannel using full signal band coherent detection and multi-channel digital back propagation (MC-DBP) to mitigate nonlinear effects is analysed. For the first time in unrepeatered transmission, the performance of two amplification systems is investigated and directly compared in terms of achievable information rates (AIRs): 1) erbium-doped fibre amplifier (EDFA) and 2) second-order bidirectional Raman pumped amplification. The experiment is performed over different span lengths, demonstrating that, for an AIR of 6.8 bit/s/Hz, the Raman system enables an increase of 93 km (36 %) in span length. Further, at these distances, MC-DBP gives an improvement in AIR of 1 bit/s/Hz (to 7.8 bit/s/Hz) for both amplification schemes. The theoretical AIR gains for Raman and MC-DBP are shown to be preserved when considering low-density parity-check codes. Additionally, MC-DBP algorithms for both amplification schemes are compared in terms of performance and computational complexity. It is shown that to achieve the maximum MC-DBP gain, the Raman system requires approximately four times the computational complexity due to the distributed impact of fibre nonlinearity

Hierarchically Porous Gd3+-Doped CeO2 Nanostructures for the Remarkable Enhancement of Optical and Magnetic Properties

Rare earth ion-doped CeO2 has attracted more and more attention because of its special electrical, optical, magnetic, or catalytic properties. In this paper, a facile electrochemical deposition route was reported for the direct growth of the porous Gd-doped CeO2. The formation process of Gd-doped CeO2 composites was investigated. The obtained deposits were characterized by SEM, EDS, XRD, and XPS. The porous Gd3+- doped CeO2 (10 at% Gd) displays a typical type I adsorption isotherm and yields a large specific surface area of 135 m2/g. As Gd3+ ions were doped into CeO2 lattice, the absorption spectrum of Gd3+-doped CeO2 nanocrystals exhibited a red shift compared with porous CeO2 nanocrystals and bulk CeO2, and the luminescence of Gd3+-doped CeO2 deposits was remarkably enhanced due to the presence of more oxygen vacancies. In addition, the strong magnetic properties of Gd-doped CeO2 (10 at% Gd) were observed, which may be caused by Gd3+ ions or more oxygen defects in deposits. In addition, the catalytic activity of porous Gd-doped CeO2 toward CO oxidation was studied

Gear-Specific Population Demographics of Channel Catfish in a Large Midwestern River

Various gear types have been used to sample populations of channel catfish Ictalurus punctatus in lotic systems. However, these gears produce different population characteristics (i.e., recruitment, growth, and mortality). We compared the population demographics of channel catfish in the Wabash River, Indiana, sampled with baited 25- and 32-mm-bar mesh hoop nets and three-phase alternating current (AC) electrofishing. Based on catch per unit effort, the relative abundance of channel catfish sampled with 32-mm hoop nets was lower than that of fish sampled with 25-mm hoop nets and AC electrofishing. Each gear type also resulted in a different length frequency, mean length increasing progressively in sampling with 25-mm hoop nets, 32-mm hoop nets, and AC electrofishing. Similarly, age-frequency distributions differed among gears. The 25-mm hoop nets biased the age structure toward younger individuals (mean age = 2.5), whereas both 32-mm hoop nets (mean age = 4.0) and AC electrofishing (mean age = 5.8) included older fish. Catch-curve analysis generated different mortality rates for the three gear types, the mortality rate being highest (50%) in fish sampled with 25-mm hoop nets. Gear-specific size and age structures led to differences in von Bertalanffy statistics among the 25-mm hoop nets and AC electrofishing, while the results for 32-mm hoop nets were uninterpretable. Because the different gears led to conflicting parameter estimates, management practices based on sampling with single gears may be contradictory. Given the differences in gear selectivity, biologists need to approach management cautiously until calibration to the true size and age structure is conducted