Transient tracking of low and high-order eccentricity-related components in induction motors via TFD tools

[EN] The present work is focused on the diagnosis of mixed eccentricity faults in induction motors via the study of currents demanded by the machine. Unlike traditional methods, based on the analysis of stationary currents (Motor Current Signature Analysis (MCSA)), this work provides new findings regarding the diagnosis approach proposed by the authors in recent years, which is mainly focused on the fault diagnosis based on the analysis of transient quantities, such as startup or plug stopping currents (Transient Motor Current Signature Analysis (TMCSA)), using suitable time-frequency decomposition (TFD) tools. The main novelty of this work is to prove the usefulness of tracking the transient evolution of high-order eccentricity-related harmonics in order to diagnose the condition of the machine, complementing the information obtained with the low-order components, whose transient evolution was well characterised in previous works. Tracking of high-order eccentricity-related harmonics during the transient, through their associated patterns in the time-frequency plane, may significantly increase the reliability of the diagnosis, since the set of fault-related patterns arising after application of the corresponding TFD tool is very unlikely to be caused by other faults or phenomena. Although there are different TFD tools which could be suitable for the transient extraction of these harmonics, this paper makes use of a WignerVille distribution (WVD)-based algorithm in order to carry out the time-frequency decomposition of the startup current signal, since this is a tool showing an excellent trade-off between frequency resolution at both high and low frequencies. Several simulation results obtained with a finite element-based model and experimental results show the validity of this fault diagnosis approach under several faulty and operating conditions. Also, additional signals corresponding to the coexistence of the eccentricity and other non-fault related phenomena making difficult the diagnosis (fluctuating load torque) are included in the paper. Finally, a comparison with an alternative TFD tool the discrete wavelet transform (DWT) applied in previous papers, is also carried out in the contribution. The results are promising regarding the usefulness of the methodology for the reliable diagnosis of eccentricities and for their discrimination against other phenomena. © 2010 Elsevier Ltd.All rights reserved.This work was supported by the Spanish 'Ministerio de Educacion y Ciencia', in the framework of the 'Programa Nacional de proyectos de Investigacion Fundamental', project reference DP12008-06583/DPI.Climente Alarcón, V.; Antonino-Daviu, J.; Riera-Guasp, M.; Pons Llinares, J.; Roger-Folch, J.; Jover-Rodriguez, P.; Arkkio, A. (2011). Transient tracking of low and high-order eccentricity-related components in induction motors via TFD tools. Mechanical Systems and Signal Processing. 25(2):667-679. https://doi.org/10.1016/j.ymssp.2010.08.008S66767925

Fault Diagnosis in Induction Motors using the Hilbert-Huang Transform

[EN] The work carried out by the authors consists of applying a modern time-frequency decomposition (TFD) tool, the Hilbert-Huang Transform (HHT), to the diagnosis and the evaluation of electromechanical faults in induction machines. These machines are widely spread nowadays, being involved in many industrial processes as well as in power generation installations such as nuclear plants. The core of the proposed methodology is the analysis of the current demanded by the stator winding of the machine during its connection process known as startup transient. Once the current is analyzed, characteristic patterns caused by the evolution of certain components created by the corresponding faults are identified; this evolution is due to the dependence of these fault-related components on the slip s, a quantity varying during a direct startup transient from 1 to near 0. In the present paper, the HHT is applied to the diagnosis of two different faults: rotor bar breakages and mixed eccentricities. In comparison with other TFD tools, the HHT provides certain advantages that are discussed in the work. The validity of the approach is proven through several experimental tests on real machines with different sizes and characteristics. The results show the potential of the methodology for reliable fault diagnosis and for correct discrimination between the different electromechanical failures.Antonino Daviu, J.; Riera-Guasp, M.; Pineda Sánchez, M.; Puche Panadero, R.; Pérez, RB.; Jover-Rodriguez, P.; Arkkio, A. (2011). Fault Diagnosis in Induction Motors using the Hilbert-Huang Transform. Nuclear Technology. 173(1):26-34. doi:10.13182/NT11-A11481S2634173

Bulk micromegas detectors for large TPC applications

A large volume TPC will be used in the near future in a variety of experiments including T2K. The bulk Micromegas detector for this TPC is built using a novel production technique particularly suited for compact and robust low mass detectors. The capability to pave a large surface with a simple mounting solution and small dead space between modules is of particular interest for these applications. We have built several large bulk Micromegas detectors (27 x 26 cm2) and we have tested them in the former HARP field cage setup with a magnetic field. Cosmic ray data have been acquired in a variety of experimental conditions. Good detector performances and space point resolution have been achieved

The revised Bethesda guidelines: extent of utilization in a university hospital medical center with a cancer genetics program

<p>Abstract</p> <p>Background</p> <p>In 1996, the National Cancer Institute hosted an international workshop to develop criteria to identify patients with colorectal cancer who should be offered microsatellite instability (MSI) testing due to an increased risk for Hereditary Nonpolyposis Colorectal Cancer (HNPCC). These criteria were further modified in 2004 and became known as the revised Bethesda Guidelines. Our study aimed to retrospectively evaluate the percentage of patients diagnosed with HNPCC tumors in 2004 who met revised Bethesda criteria for MSI testing, who were referred for genetic counseling within our institution.</p> <p>Methods</p> <p>All HNPCC tumors diagnosed in 2004 were identified by accessing CoPath, an internal database. Both the Tumor Registry and patients' electronic medical records were accessed to collect all relevant family history information. The list of patients who met at least one of the revised Bethesda criteria, who were candidates for MSI testing, was then cross-referenced with the database of patients referred for genetic counseling within our institution.</p> <p>Results</p> <p>A total of 380 HNPCC-associated tumors were diagnosed at our institution during 2004 of which 41 (10.7%) met at least one of the revised Bethesda criteria. Eight (19.5%) of these patients were referred for cancer genetic counseling of which 2 (25%) were seen by a genetics professional. Ultimately, only 4.9% of patients eligible for MSI testing in 2004 were seen for genetic counseling.</p> <p>Conclusion</p> <p>This retrospective study identified a number of barriers, both internal and external, which hindered the identification of individuals with HNPCC, thus limiting the ability to appropriately manage these high risk families.</p

Experimental study of the atmospheric neutrino backgrounds for proton decay to positron and neutral pion searches in water Cherenkov detectors

The atmospheric neutrino background for proton decay to positron and neutral pion in ring imaging water Cherenkov detectors is studied with an artificial accelerator neutrino beam for the first time. In total, about 314,000 neutrino events corresponding to about 10 megaton-years of atmospheric neutrino interactions were collected by a 1,000 ton water Cherenkov detector (KT). The KT charged-current single neutral pion production data are well reproduced by simulation programs of neutrino and secondary hadronic interactions used in the Super-Kamiokande (SK) proton decay search. The obtained proton to positron and neutral pion background rate by the KT data for SK from the atmospheric neutrinos whose energies are below 3 GeV is about two per megaton-year. This result is also relevant to possible future, megaton-scale water Cherenkov detectors.Comment: 13 pages, 16 figure

Measurement of single charged pion production in the charged-current interactions of neutrinos in a 1.3 GeV wide band beam

Single charged pion production in charged-current muon neutrino interactions with carbon is studied using data collected in the K2K long-baseline neutrino experiment. The mean energy of the incident muon neutrinos is 1.3 GeV. The data used in this analysis are mainly from a fully active scintillator detector, SciBar. The cross section for single $\pi^{+}$ production in the resonance region ($W<2$ GeV/$c^2$) relative to the charged-current quasi-elastic cross section is found to be 0.734 $^{+0.140}_{-0.153}$. The energy-dependent cross section ratio is also measured. The results are consistent with a previous experiment and the prediction of our model.Comment: 15 pages, 12 figures, 7 tables. Uses revtex4. Minor revisions to match version accepted for publication in Physical Review

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Consistency of impact assessment protocols for non-native species

Standardized tools are needed to identify and prioritize the most harmful non-native species (NNS). A plethora of assessment protocols have been developed to evaluate the current and potential impacts of non-native species, but consistency among them has received limited attention. To estimate the consistency across impact assessment protocols, 89 specialists in biological invasions used 11 protocols to screen 57 NNS (2614 assessments). We tested if the consistency in the impact scoring across assessors, quantified as the coefficient of variation (CV), was dependent on the characteristics of the protocol, the taxonomic group and the expertise of the assessor. Mean CV across assessors was 40%, with a maximum of 223%. CV was lower for protocols with a low number of score levels, which demanded high levels of expertise, and when the assessors had greater expertise on the assessed species. The similarity among protocols with respect to the final scores was higher when the protocols considered the same impact types. We conclude that all protocols led to considerable inconsistency among assessors. In order to improve consistency, we highlight the importance of selecting assessors with high expertise, providing clear guidelines and adequate training but also deriving final decisions collaboratively by consensus