688 research outputs found
Changing incentives to publish
No full textMany national governments have implemented policies providing incentives for researchers to publish, especially in highly ranked international journals. Although still the top publishing nation, the United States has seen its share of publications decline from 34.2% in 1995 to 27.6% in 2007 as the number of articles published by U.S. scientists and engineers has plateaued and that of other countries has grown (1, 2). Hicks (3) argues that the two events are not unrelated: The decline in the relative performance of the United States relates to increased international competition engendered by newly adopted incentives that have crowded out some work by U.S. author
A methodology using the spectral coherence and healthy historical data to perform gearbox fault diagnosis under varying operating conditions
No full textCondition monitoring is usually performed over long periods of time when critical rotating machines such as wind turbine gearboxes are monitored. There are many potential signal processing and analysis techniques that can be utilised to diagnose the machine from the condition monitoring data, however, they seldom incorporate the available healthy historical data of a machine systematically in the fault diagnosis process. Hence, a methodology is proposed in this article which supplements the order-frequency spectral coherence with historical data from a healthy machine to perform automatic fault detection, automatic fault localisation and fault trending. This has the benefit that the order-frequency spectral coherence, a very powerful technique for rotating machine fault diagnosis under varying speed conditions, can be utilised without requiring an expert to interpret the results. In this methodology, an extended version of the improved envelope spectrum is utilised to extract features from the order-frequency spectral coherence, whereafter a probabilistic model is carefully used to calculate a diagnostic metric for automatic fault detection and localisation. The methodology is investigated on numerical gearbox data as well as experimental gearbox data, both acquired under time-varying operating conditions with two probabilistic models, namely a Gaussian model and a kernel density estimator, compared as well. The results indicate the potential of this methodology for performing gearbox fault diagnosis under varying operating conditions.sponsorship: S. Schmidt and P.S. Heyns gratefully acknowledge the support that was received from the Eskom Power Plant Engineering Institute (EPPEI) in the execution of the research. K.C. Gryllias gratefully acknowledges the Research Fund KU Leuven. (Eskom Power Plant Engineering Institute (EPPEI))status: Publishe
Telecommunication-Telemedia-Assessment/360_testcontent: v1.0.0
No full text<p>This repository contains some publicly available 360° videos.</p>
<p>If you use any or parts of the material included in this dataset, please cite the following paper:</p>
<p>For material in <code>/EI2019</code>:</p>
<pre><code>@article{hofmeyer2019impacts,
title={Impacts of internal HMD playback processing on subjective quality perception},
author={Hofmeyer, Frank and Fremerey, Stephan and Cohrs, Thaden and Raake, Alexander},
journal={Electronic Imaging},
volume={31},
pages={1--7},
year={2019},
publisher={Society for Imaging Science and Technology}
}
</code></pre>
Catalytic P-H activation by Ti and Zr catalysts
No full textCatalytic dehydrocoupling of phosphines was investigated using the anionic zirconocene trihydride salts [Cp*Zr-2(mu-H)(3)Li](3) (1a) or [Cp*Zr-2(mu-H)(3)K(thf)(4)] (1b), and the metallocycles [CpTi(NPtBu3)(CH2)(4)] (6) and [Cp*M(NPtBu3)(CH2)(4)] (M = Ti 20, Zr 21) as catalyst precursors. Dehydrocoupling of primary phosphines RPH2 (R = Ph, C6H2Me3, Cy, C10H7) gave both dehydrocoupled dimers RP(H)P(H)R or cyclic oligophosphines (RP)(n) (n = 4, 5) while reaction of tBu(3)C(6)H(2)PH(2) gave the phosphaindoline tBu(2)(Me2CCH2)C6H2PH (9). Stoichiometric reactions of these catalyst precursors with primary phosphines afforded [Cp*Zr-2((PR)(2))H][K(thf)(4)] (R = Ph 2, Cy 3, C6H2Me3 4), [Cp*Zr-2((PPh)(3))H] [K(thf)(4)] (5), [CpTi(NPtBu3)(PPh)(3)] (7) and [CpTi(NPtBu3)(mu-PHPh)](2) (8), while reaction of 6 with (C(6)H(2)tBu3)PH2 in the presence of PMe3 afforded [CpTi(NPtBu3)(PMe3)(p(C(6)H(2)tBu(3))] (10). The secondary phosphines Ph2PH and (PhHPCH2)(2)CH2 also undergo dehydrocoupling affording (Ph2P)(2) and (PhPCH2)(2)CH2. The bisphosphines (CH2PH2)(2) and C6H4(PH2)(2) are dehydrocoupled to give (PCH2CH2PH)(2) (12) and (C6H4P(PH))(2) (13) while prolonged reaction of 13 gave (C6H4P2)(8) (14). The analogous bisphosphine Me2C6H4(PH)(2) (17) was prepared and dehydrocoupling catalysis afforded (Me2C6H2P(PH))(2) (18) and subsequently [(Me2C6H2P2)(2)(mu-Me2C6H2P2)](2) (19). Stoichiometric reactions with these bisphosphines gave [Cp*Zr-2(H)(PH)(2)C6H4] [Li(thf)(4)] (22), [Cp*Ti(NPtBu3)(PH)(2)C6H4](2) (23) and [Cp*Ti(NPtBu3)(PH)(2)C6H4] (24). Mechanistic implications are discussed.PT: J; CR: ALBRAND JP, 1976, J CHEM SOC CHEM COMM, P876 ANSELME JP, 1969, TETRAHEDRON, V25, P855 BASULI F, 2003, J AM CHEM SOC, V125, P10170 BAUDLER M, 1976, Z NATURFORSCH B, V31, P558 BAUDLER M, 1978, CHEM BER, V111, P1210 BAUDLER M, 1978, CHEM BER, V111, P1217 BAUDLER M, 1983, CHEM BER, V116, P2711 BAUDLER M, 1984, Z NATURFORSCH B, V39, P438 BAZAN GC, 1991, J AM CHEM SOC, V113, P6899 BOHM VPW, 2001, ANGEW CHEM, V113, P4832 CHAUVIN Y, 1971, MAKROMOL CHEM, V141, P161 COREY JY, 2004, ADV ORGANOMET CHEM, V51, P1 COURET C, 1986, ORGANOMETALLICS, V5, P113 COWLEY AH, 1984, TETRAHEDRON LETT, V25, P2125 COWLEY AH, 1990, INORG SYNTH, V27, P235 CROMER DT, 1974, INT TABLES CRYSTALLO, V4, P71 ETKIN N, 1997, J AM CHEM SOC, V119, P11420 ETKIN N, 1997, J AM CHEM SOC, V119, P2954 ETKIN N, 1997, ORGANOMETALLICS, V16, P3504 FEHLNER TP, 1992, INORGANOMETALLLICS FERMIN MC, 1995, J AM CHEM SOC, V117, P12645 FERMIN MC, 1995, ORGANOMETALLICS, V14, P4247 FU GC, 1993, J AM CHEM SOC, V115, P9856 GAUVIN F, 1998, ADV ORGANOMET CHEM, V42, P363 GRAHAM TW, 2004, ORGANOMETALLICS, V23, P3309 GRUBBS RH, 1972, J AM CHEM SOC, V94, P2538 GRUBBS RH, 2003, HDB METATHESIS HEY E, 1988, CHEM BER, V121, P561 HEY E, 1989, J ORGANOMET CHEM, V378, P375 HO JW, 1991, ORGANOMETALLICS, V10, P3001 HO JW, 1994, INORG CHEM, V33, P865 HOFFMAN PR, 1975, INORG CHEM, V14, P1997 HOSKIN AJ, 2001, ANGEW CHEM, V113, P1917 HOU ZM, 1993, ORGANOMETALLICS, V12, P3158 INAGAKI Y, 1980, B CHEM SOC JPN, V53, P205 ISSLEIB K, 1972, ANGEW CHEM, V84, P582 ISSLEIB K, 1987, J ORGANOMET CHEM, V330, P17 JACOBSEN EN, 1988, J AM CHEM SOC, V110, P1968 KATSUKI T, 1980, J AM CHEM SOC, V102, P5974 KAUFFMANN T, 1984, TETRAHEDRON LETT, V25, P1963 KAUFFMANN T, 1985, CHEM BER, V118, P1022 KITAMURA M, 1988, J AM CHEM SOC, V110, P629 KNOWLES WS, 1983, ACCOUNTS CHEM RES, V16, P106 KOEPF H, 1981, CHEM BER, V114, P2731 KOHLER EP, 1935, J AM CHEM SOC, V57, P367 KYBA EP, 1983, ORGANOMETALLICS, V2, P1877 MILLER AR, 1976, J AM CHEM SOC, V98, P1860 MILLER SJ, 1996, J AM CHEM SOC, V118, P9606 MIYASHITA A, 1980, J AM CHEM SOC, V102, P7932 MURDZEK JS, 1987, ORGANOMETALLICS, V6, P1373 NGUYEN ST, 1992, J AM CHEM SOC, V114, P3974 NGUYEN ST, 1993, J AM CHEM SOC, V115, P9858 NOVAK BM, 1988, J AM CHEM SOC, V110, P960 OHKUMA T, 1995, J AM CHEM SOC, V117, P2675 OHTA T, 1988, INORG CHEM, V27, P566 OSHIKAWA T, 1985, CHEM IND-LONDON, P126 ROCKLAGE SM, 1981, J AM CHEM SOC, V103, P1440 SCHOLL M, 1999, TETRAHEDRON LETT, V40, P2247 SCHROCK RR, 1974, J AM CHEM SOC, V96, P6796 SCHROCK RR, 1980, J MOL CATAL, V8, P73 SCHROCK RR, 1988, J MOL CATAL, V46, P243 SCHROCK RR, 1990, J AM CHEM SOC, V112, P3875 SCHWAB P, 1995, ANGEW CHEM INT EDIT, V34, P2039 SCHWAB P, 1995, ANGEW CHEM, V107, P2179 SCHWAB P, 1996, J AM CHEM SOC, V118, P100 SENDERIKHIN AI, 1988, ZH OBSHCH KHIM+, V58, P1662 SENDERIKHIN AI, 1989, ZH OBSHCH KHIM+, V59, P2141 SEYFERTH D, 1969, J ORG CHEM, V34, P1483 SHELDRICK GM, 2000, SHELXTL SHU RH, 1998, J AM CHEM SOC, V120, P12988 SMIT CN, 1983, TETRAHEDRON LETT, V24, P2031 SOUFFLET JP, 1973, CR ACAD SCI C CHIM, V276, P169 STEPHAN DW, 2000, ANGEW CHEM, V112, P322 STEPHAN DW, 2005, ORGANOMETALLICS, V24, P2548 STRADIOTTO M, 2001, HELV CHIM ACTA, V84, P2958 TILLEY TD, 1990, COMMENTS INORG CHEM, V10, P37 TILLEY TD, 1993, ACCOUNTS CHEM RES, V26, P22 TVERDOMED SN, 2003, RUSS J GEN CHEM+, V73, P319 VANDENWINKEL Y, 1991, J ORGANOMET CHEM, V405, P183 WATERMAN R, 2006, ANGEW CHEM INT EDIT, V45, P2926 WATERMAN R, 2006, ANGEW CHEM, V118, P2992 WEAST RC, 1974, HDB CHEM PHYS, P2436 WOOD CD, 1979, J AM CHEM SOC, V101, P3210 WU Z, 1995, J AM CHEM SOC, V117, P5503 XIN SX, 1997, J AM CHEM SOC, V119, P5307; NR: 85; TC: 0; J9: CHEM-EUR J; PG: 12; GA: 113PJSource type: Electronic(1
Investigation of the effects of welding parameters on the tensile strength and fatigue life of the structural welded joints S355J2+N steel plate
No full textDissertation (MSc (Mechanical Engineering))--University of Pretoria, 2023.The railway industry wants to obtain structural welded joints that have optimum weld strength and fatigue life. Since the variance of welding parameters producing welding defects and weak structural integrity, there are uncertainties in the selecting the welding parameters that produce a good structural welded joint with the necessary weld quality. This necessitates the optimisation of the welding parameters to produce welded joints with improved mechanical properties.
The impact of various welding parameters (i.e. wire-feed speed (WFS), voltage and travel speed) on the ultimate tensile strength (UTS) and fatigue life of S355J2+N single V butt weld produced by metal inert gas (MIG) robotic welding was experimentally investigated. The design of experiments (DOE) approach was used to optimise the welding parameters to ensure the reliability of the experimental results. A removable ceramic weld backing bar was used to improve weld root penetration and minimise the risk of lack of fusion. To ensure weld quality and reliability of the experimental results the flush ground welded joints were used to minimise the geometric notch effect. A minimum number of two specimens for each number of experiments were tested to ensure the correct evaluation of welds. The magnetic particle testing (MT) technique was used to detect the welding defects that might have an impact on the material properties of the welded joints. Analysis of variance (ANOVA) was used to precisely demonstrate which welding parameters had the greatest impact on the performance output of the welded joint and to determine interactions between welding parameters.
It was observed that varying the welding parameters had an impact on the weld quality. An increase in voltage and travel speed at lower WFS are the primary contributing factors to weld defects. Only the defect-free specimens were tested to avoid making the experimental results inconclusive for statistical analysis. According to the ANOVA results, voltage and travel speed interact to affect the welded joint’s UTS. Increasing voltage increases the UTS of the welded joints at the higher ranges of travel speed, while decreasing the UTS in the lower and medium range of travel speed. The most influential welding parameter that affects the UTS of the welded joint is travel speed. The fatigue life of the welded joint is affected by interactions between WFS and travel speed, as well as the voltage and travel speed. Increasing WFS increases the fatigue life at the medium range of travel speed. When welding at lower speed, the fatigue life duration becomes longer as the voltage increases. The fatigue life of the welded joint is significantly influenced by the WFS. The optimal welding parameters for the welded joint is A2B1C1 (i.e. WFS at level 2, voltage at level 1 and travel speed at level 1) for better UTS and fatigue life.
This research reduces uncertainties in the selection of optimum settings of welding parameters of a MIG welded joint. The welding parameters that significantly affect the welded joint mechanical properties performance were identified. The optimum welding parameters selection for UTS and fatigue life can be developed. Undesirable welding defects that affect the structural integrity of the welded joint can be minimised by an improved selection of welding parameters.Transnet EngineeringMechanical and Aeronautical EngineeringMSc (Mechanical Engineering)UnrestrictedFaculty of Engineering, Built Environment and Information Technolog
Recognition by forensic facial approximation: Case specific examples and empirical tests
No full textCopyright © 2005 Elsevier Ireland Ltd All rights reserved.The skeletal remains of one individual found near Adelaide in 1994, although not known at the time, were the first evidence of what was to be a serial killing reported to have resulted in the highest casualty list to date in Australia (12 victims). Since the usual methods of identification could not be used or were unsuccessful on these remains, facial approximations were produced and advertised over the 4-year period following their discovery, in an attempt to help to identify them. However, no identification was made. In 1999, the remains were reported to be identified by radiographic comparison. Approximately 3 months before this identification was made, another facial approximation was produced by the first author (CNS), but this face was never advertised in the media. Although rarely reported in the literature, this paper provides an example where facial approximation methods were not successful in a forensic scenario. The paper also reports on empirical tests of the facial approximation created by the first author to determine if this facial approximation might have been useful had it been advertised. The results provide further evidence that high resemblance of a facial approximation to the target individual does not indicate recognizability, as the facial approximation was poorly recognized even though it bore good resemblance to the target individual. The usefulness of facial approximation techniques is discussed within the context of this case and more broadly. Methods used to assess the accuracy of facial approximations are also discussed and further evaluated.C.N. Stephan and M. Henneberghttp://www.elsevier.com/wps/find/journaldescription.cws_home/505512/description#descriptio
Automaattiset menetelmät pyörivien koneiden värähtelyyn perustuvaan kunnonvalvontaan
No full textAbstractThe sustainable and safe use of rotating machines can be enhanced by condition monitoring. Acceleration signals are commonly used for the indirect measurement of condition, but their analysis can be complicated in industrial applications. When the number of monitored targets is large, efficiently conducted data analysis is essential.The aim of this research was to develop automated, data-driven methods for the analysis of acceleration signals and related data acquired from rotating machines especially in real measurement environments. Methods that simplify system identification would ease the implementation of algorithms, while online monitoring benefits from methods that detect anomalies automatically.The proposed methods for system identification help to automate the selection of training samples, signal features and signal processing settings by optimizing computational criteria through data exploration. Two of the methods proposed for anomaly detection monitor the residuals of regression models and one applies an adaptive approach based on an autocorrelation-based criterion. Methods that need training data from a target in undamaged condition were studied by using real measurement data from azimuth thrusters and a roller leveler. The autocorrelation-based criterion developed for detecting local faults in slowly rotating rolling element bearings was studied with laboratory and simulation data.The results indicated that automated selection of training samples systematized the identification of anomaly detection models and their operating areas in the case of azimuth thrusters. Automated feature selection revealed previously unknown dependencies between acceleration signals and parameters, such as steel strip properties in roller leveling. In addition, certain patterns of local faults in slowly rotating rolling element bearings could be detected automatically from short time series that contained only a few fault impulses. The findings of this work can be useful in condition monitoring applications in real measurement environments, where repeatability and the automation and facilitation of data analysis are targeted.Original papersOriginal papers are not included in the electronic version of the dissertation.Nikula, R.-P., Ruusunen, M., & Böhme, S. A. (2022). On training data selection in condition monitoring applications—Case azimuth thrusters. Applied Sciences, 12(8), 4024. https://doi.org/10.3390/app12084024Self-archived versionNikula, R.-P., Ruusunen, M., Keski-Rahkonen, J., Saarinen, L., & Fagerholm, F. (2021). Probabilistic condition monitoring of azimuth thrusters based on acceleration measurements. Machines, 9(2), 39. https://doi.org/10.3390/machines9020039Self-archived versionNikula, R.-P., & Leiviskä, K. (2020). Roller leveler monitoring using acceleration measurements and models for steel strip properties. Machines, 8(3), 43. https://doi.org/10.3390/machines8030043Self-archived versionNikula, R.-P., Karioja, K., Pylvänäinen, M., & Leiviskä, K. (2020). Automation of low-speed bearing fault diagnosis based on autocorrelation of time domain features. Mechanical Systems and Signal Processing, 138, 106572. https://doi.org/10.1016/j.ymssp.2019.106572Self-archived versionTiivistelmäPyörivien koneiden kunnonvalvonta voi parantaa niiden kestävää ja turvallista käyttöä. Kiihtyvyyssignaaleja käytetään tavallisesti kunnon epäsuorassa mittauksessa, mutta niiden analysointi voi olla monimutkaista teollisissa sovelluksissa. Kun valvottavia kohteita on useita, on olennaista suorittaa data-analyysi tehokkaasti.Tämän tutkimuksen tarkoituksena oli kehittää automaattisia dataan perustuvia menetelmiä pyörivistä koneista mitattujen kiihtyvyyssignaalien ja niihin liittyvän datan analysointiin erityisesti todellisissa mittausympäristöissä. Järjestelmän identifiointia yksinkertaistavat menetelmät voivat helpottaa algoritmien käyttöönottoa, kun taas jatkuvassa valvonnassa on hyötyä menetelmistä, jotka havaitsevat poikkeavuuksia automaattisesti.Järjestelmän identifiointiin ehdotetut menetelmät auttavat automatisoimaan opetusnäytteiden, signaalin piirteiden ja signaalin prosessointiasetusten valintaa optimoiden laskennallisia kriteerejä datan perusteella. Kaksi esiteltyä menetelmää poikkeavuuksien havaitsemiseen seuraa regressiomallien jäännösvirhettä ja yksi soveltaa mukautuvaa menetelmää, joka perustuu autokorrelaatiosta laskettuun kriteeriin. Menetelmiä, jotka tarvitsevat opetusdataa vauriottomasta kohteesta, tutkittiin todellisella mittausdatalla ruoripotkureista sekä rullaoikaisukoneesta. Hitaasti pyörivien vierintälaakerien paikallisten vikojen havaitsemiseen kehitettyä autokorrelaatioon perustuvaa kriteeriä tutkittiin laboratorio- ja simulointidatalla.Tulokset osoittivat, että opetusdatan automaattinen valinta systematisoi poikkeavuuksien havaitsemiseen kehitettyjen mallien ja niiden toiminta-alueiden identifiointia ruoripotkurien tapauksessa. Automatisoitu piirteiden valinta paljasti ennalta tuntemattomia riippuvuuksia kiihtyvyyssignaaleista ja parametreista, kuten rullaoikaistavan teräsnauhan ominaisuuksista. Lisäksi tietyt vierintälaakereiden paikallisten vikojen piirteet voitiin havaita automaattisesti lyhyistä aikasarjoista, jotka kattoivat vain muutaman vikaimpulssin. Työn tuloksia voidaan hyödyntää todellisten mittausympäristöjen kunnonvalvontasovelluksissa, joissa tavoitellaan toistettavuutta sekä data-analyysin automatisointia ja helpottamista.OsajulkaisutOsajulkaisut eivät sisälly väitöskirjan elektroniseen versioon.Nikula, R.-P., Ruusunen, M., & Böhme, S. A. (2022). On training data selection in condition monitoring applications—Case azimuth thrusters. Applied Sciences, 12(8), 4024. https://doi.org/10.3390/app12084024Rinnakkaistallennettu versioNikula, R.-P., Ruusunen, M., Keski-Rahkonen, J., Saarinen, L., & Fagerholm, F. (2021). Probabilistic condition monitoring of azimuth thrusters based on acceleration measurements. Machines, 9(2), 39. https://doi.org/10.3390/machines9020039Rinnakkaistallennettu versioNikula, R.-P., & Leiviskä, K. (2020). Roller leveler monitoring using acceleration measurements and models for steel strip properties. Machines, 8(3), 43. https://doi.org/10.3390/machines8030043Rinnakkaistallennettu versioNikula, R.-P., Karioja, K., Pylvänäinen, M., & Leiviskä, K. (2020). Automation of low-speed bearing fault diagnosis based on autocorrelation of time domain features. Mechanical Systems and Signal Processing, 138, 106572. https://doi.org/10.1016/j.ymssp.2019.106572Rinnakkaistallennettu versioAcademic dissertation to be presented with the assent of the Doctoral Programme Committee of Technology and Natural Sciences of the University of Oulu for public defence in the OP-Pohjola auditorium (L6), Linnanmaa, on 10 December 2022, at 12 noonAbstract
The sustainable and safe use of rotating machines can be enhanced by condition monitoring. Acceleration signals are commonly used for the indirect measurement of condition, but their analysis can be complicated in industrial applications. When the number of monitored targets is large, efficiently conducted data analysis is essential.
The aim of this research was to develop automated, data-driven methods for the analysis of acceleration signals and related data acquired from rotating machines especially in real measurement environments. Methods that simplify system identification would ease the implementation of algorithms, while online monitoring benefits from methods that detect anomalies automatically.
The proposed methods for system identification help to automate the selection of training samples, signal features and signal processing settings by optimizing computational criteria through data exploration. Two of the methods proposed for anomaly detection monitor the residuals of regression models and one applies an adaptive approach based on an autocorrelation-based criterion. Methods that need training data from a target in undamaged condition were studied by using real measurement data from azimuth thrusters and a roller leveler. The autocorrelation-based criterion developed for detecting local faults in slowly rotating rolling element bearings was studied with laboratory and simulation data.
The results indicated that automated selection of training samples systematized the identification of anomaly detection models and their operating areas in the case of azimuth thrusters. Automated feature selection revealed previously unknown dependencies between acceleration signals and parameters, such as steel strip properties in roller leveling. In addition, certain patterns of local faults in slowly rotating rolling element bearings could be detected automatically from short time series that contained only a few fault impulses. The findings of this work can be useful in condition monitoring applications in real measurement environments, where repeatability and the automation and facilitation of data analysis are targeted.Tiivistelmä
Pyörivien koneiden kunnonvalvonta voi parantaa niiden kestävää ja turvallista käyttöä. Kiihtyvyyssignaaleja käytetään tavallisesti kunnon epäsuorassa mittauksessa, mutta niiden analysointi voi olla monimutkaista teollisissa sovelluksissa. Kun valvottavia kohteita on useita, on olennaista suorittaa data-analyysi tehokkaasti.
Tämän tutkimuksen tarkoituksena oli kehittää automaattisia dataan perustuvia menetelmiä pyörivistä koneista mitattujen kiihtyvyyssignaalien ja niihin liittyvän datan analysointiin erityisesti todellisissa mittausympäristöissä. Järjestelmän identifiointia yksinkertaistavat menetelmät voivat helpottaa algoritmien käyttöönottoa, kun taas jatkuvassa valvonnassa on hyötyä menetelmistä, jotka havaitsevat poikkeavuuksia automaattisesti.
Järjestelmän identifiointiin ehdotetut menetelmät auttavat automatisoimaan opetusnäytteiden, signaalin piirteiden ja signaalin prosessointiasetusten valintaa optimoiden laskennallisia kriteerejä datan perusteella. Kaksi esiteltyä menetelmää poikkeavuuksien havaitsemiseen seuraa regressiomallien jäännösvirhettä ja yksi soveltaa mukautuvaa menetelmää, joka perustuu autokorrelaatiosta laskettuun kriteeriin. Menetelmiä, jotka tarvitsevat opetusdataa vauriottomasta kohteesta, tutkittiin todellisella mittausdatalla ruoripotkureista sekä rullaoikaisukoneesta. Hitaasti pyörivien vierintälaakerien paikallisten vikojen havaitsemiseen kehitettyä autokorrelaatioon perustuvaa kriteeriä tutkittiin laboratorio- ja simulointidatalla.
Tulokset osoittivat, että opetusdatan automaattinen valinta systematisoi poikkeavuuksien havaitsemiseen kehitettyjen mallien ja niiden toiminta-alueiden identifiointia ruoripotkurien tapauksessa. Automatisoitu piirteiden valinta paljasti ennalta tuntemattomia riippuvuuksia kiihtyvyyssignaaleista ja parametreista, kuten rullaoikaistavan teräsnauhan ominaisuuksista. Lisäksi tietyt vierintälaakereiden paikallisten vikojen piirteet voitiin havaita automaattisesti lyhyistä aikasarjoista, jotka kattoivat vain muutaman vikaimpulssin. Työn tuloksia voidaan hyödyntää todellisten mittausympäristöjen kunnonvalvontasovelluksissa, joissa tavoitellaan toistettavuutta sekä data-analyysin automatisointia ja helpottamista
TRA8/05 Variations on U-shaped Learning
No full texttutorial article, which has been submitted for publication in a journal or for consideration by the commissioning organization. The report represents the ideas of its author, and should not be taken as the official views of the School or the University. Any discussion of the content of the report should be sent to the author, at the address shown on the cover. JAFFAR, Joxa
Biogeochemical redox proxies in sediments from Dotternhausen during the Toarcian (Early Jurassic)
No full textAuthor contributions:
The lead author is Angela L. Coe. Measurements were performed by Stephan M. Harding, with supervision of Angela L. Coe and Anthony S. Cohen. Measurements were gathered, processed and analysed by Itzel Ruvalcaba Baroni
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