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Wyświetlanie 1-2 z 2
Tytuł:
On line engine oil consumption monitoring via the gaseous total sulfur signal SO2 in the raw exhaust of the engine utilizing the sensitive ion molecule reaction mass spectrometry
Autorzy:
Leidlmair, C.
Weissnicht, A.
Federer, W.
Villinger, J.
Powiązania:
https://bibliotekanauki.pl/articles/133765.pdf
Data publikacji:
2016
Wydawca:
Polskie Towarzystwo Naukowe Silników Spalinowych
Tematy:
engine oil consumption
oil consumption monitoring
spectrometry
zużycie oleju silnikowego
monitorowanie zużycia oleju
spektrometria
Opis:
The dynamic monitoring of oil consumption in IC engines is approached with various techniques ranging from radioactive counting to detection of halogenated tracer compounds or polyaromatic hydrocarbon tracers, to monitoring unburned hydrocarbons as residues from engine oil. This article discusses the method of gaseous SO2 measurement in raw exhaust it's benefits and limitations of today’s status. Modern engines consume about 2 to 5 g/h of engine oil under low and medium load but consumption may go up to 130 g/h in negative load conditions. Particulate filters must be desulfated every 5000 km even when sulfur free fuel is in use. For the oil measurement in the raw exhaust all possible Sulfur compounds are converted to SO2 in a hot oxidizing atmosphere. Additional pure oxygen in the form of ozone is added to the oxidizer for very low lambda engine conditions and the conversion of sulfur on particulates into SO2. A sensitive mass spectrometer operating in an ion molecule ionization mode measures gaseous SO2 from concentrations of 0.02 ppm to 50 ppm in measurement cycles from 2 Hz to 0.2 Hz depending on if long term measurement or dynamic operation is chosen. Technical description of pressure reduction, gas transfer, oxidation efficiencies and lower detection levels of the instrumentation are given as well as data on a complete engine map and data on reproducibility of the SO2 method are presented.
Źródło:
Combustion Engines; 2016, 55, 3; 34-38
2300-9896
2658-1442
Pojawia się w:
Combustion Engines
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Developing automatic recognition system of drill wear in standard laminated chipboard drilling process
Autorzy:
Kurek, J.
Kruk, M.
Osowski, S.
Hoser, P.
Wieczorek, G.
Jegorowa, A.
Górski, J.
Wilkowski, J.
Śmietańska, K.
Kossakowska, J.
Powiązania:
https://bibliotekanauki.pl/articles/200766.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
diagnostic expert systems
neural networks
wavelet packets
wear monitoring
diagnostyczny system ekspercki
sieci neuronowe
pakiety falkowe
monitorowanie zużycia
Opis:
The paper presents an automatic approach to recognition of the drill condition in a standard laminated chipboard drilling process. The state of the drill is classified into two classes: “useful” (sharp enough) and “useless” (worn out). The case “useless” indicates symptoms of excessive drill wear, unsatisfactory from the point of view of furniture processing quality. On the other hand the “useful” state identifies tools which are still able to drill holes acceptable due to the required processing quality. The main problem in this task is to choose an appropriate set of diagnostic features (variables), based on which the recognition of drill state (“useful” versus “useless”) can be made. The features have been generated based on 5 registered signals: feed force, cutting torque, noise, vibration and acoustic emission. Different statistical parameters describing these signals and also their Fourier and wavelet representations have been used for defining the features. Sequential feature selection is applied to detect the most class discriminative set of features. The final step of recognition is done by using three types of classifiers, including support vector machine, ensemble of decision trees and random forest. Six standard drills of 12 mm diameter with tungsten carbide tips were used in experiments. The results have confirmed good quality of the proposed diagnostic system.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2016, 64, 3; 633-640
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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