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A Particle Filtering Approach for On-Line Failure Prognosis in a Planetary Carrier Plate
Orchard, Marcos E.,Vachtsevanos, George J. Korean Institute of Intelligent Systems 2007 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.7 No.4
This paper introduces an on-line particle-filtering-based framework for failure prognosis in nonlinear, non-Gaussian systems. This framework uses a nonlinear state-space model of the plant(with unknown time-varying parameters) and a particle filtering(PF) algorithm to estimate the probability density function(pdf) of the state in real-time. The state pdf estimate is then used to predict the evolution in time of the fault indicator, obtaining as a result the pdf of the remaining useful life(RUL) for the faulty subsystem. This approach provides information about the precision and accuracy of long-term predictions, RUL expectations, and 95% confidence intervals for the condition under study. Data from a seeded fault test for a UH-60 planetary carrier plate are used to validate the proposed methodology.
A Particle Filtering Approach for On-Line Failure Prognosis in a Planetary Carrier Plate
Marcos E. Orchard,George J. Vachtsevanos 한국지능시스템학회 2007 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.7 No.4
This paper introduces an on-line particle-filtering-based framework for failure prognosis in nonlinear, non-Gaussian systems. This framework uses a nonlinear state-space model of the plant (with unknown time-varying parameters) and a particle filtering (PF) algorithm to estimate the probability density function (pdf) of the state in real-time. The state pdf estimate is then used to predict the evolution in time of the fault indicator, obtaining as a result the pdf of the remaining useful life (RUL) for the faulty subsystem. This approach provides information about the precision and accuracy of long-term predictions, RUL expectations, and 95% confidence intervals for the condition under study. Data from a seeded fault test for a UH-60 planetary carrier plate are used to validate the proposed methodology.
Hunt, M.,Till, A.R.,Blair, G.J.,Bulo, D.,Orchard, P. Asian Australasian Association of Animal Productio 1991 Animal Bioscience Vol.4 No.3
The effects of S fertilization and stocking rate on cattle production from native and sown pastures were studied in South Sulawesi, Indonesia. On the native pasture there was no effect of S application over the three years of the experiment. The per head production was lower at the higher stocking rate (1.0 hd/ha), but the overall production increased by an average of 49%. There was no response to S applied to the clean seedbed pastures in the first year, but significant responses developed in the second and third years. There was an overall higher production from the higher stocked pastures (3.0 hd/ha), but the per head production was lower. There was a mean of about a two-fold increase in animal production from the highest native to the lowest improved pasture and a 3.4 times increase from the low stocking rate native to the high stocking rate sown pasture.
Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 3.0
Deutsch, Eric W.,Lane, Lydie,Overall, Christopher M.,Bandeira, Nuno,Baker, Mark S.,Pineau, Charles,Moritz, Robert L.,Corrales, Fernando,Orchard, Sandra,Van Eyk, Jennifer E.,Paik, Young-Ki,Weintraub, S American Chemical Society 2019 JOURNAL OF PROTEOME RESEARCH Vol.18 No.12
<P>The Human Proteome Organization’s (HUPO) Human Proteome Project (HPP) developed Mass Spectrometry (MS) Data Interpretation Guidelines that have been applied since 2016. These guidelines have helped ensure that the emerging draft of the complete human proteome is highly accurate and with low numbers of false-positive protein identifications. Here, we describe an update to these guidelines based on consensus-reaching discussions with the wider HPP community over the past year. The revised 3.0 guidelines address several major and minor identified gaps. We have added guidelines for emerging data independent acquisition (DIA) MS workflows and for use of the new Universal Spectrum Identifier (USI) system being developed by the HUPO Proteomics Standards Initiative (PSI). In addition, we discuss updates to the standard HPP pipeline for collecting MS evidence for all proteins in the HPP, including refinements to minimum evidence. We present a new plan for incorporating MassIVE-KB into the HPP pipeline for the next (HPP 2020) cycle in order to obtain more comprehensive coverage of public MS data sets. The main checklist has been reorganized under headings and subitems, and related guidelines have been grouped. In sum, Version 2.1 of the HPP MS Data Interpretation Guidelines has served well, and this timely update to version 3.0 will aid the HPP as it approaches its goal of collecting and curating MS evidence of translation and expression for all predicted ∼20 000 human proteins encoded by the human genome.</P> [FIG OMISSION]</BR>