Additive manufacturing technology is developing in many industries, including aviation, automotive and others. 3D printing offers new possibilities in the field of designing and manufacturing of machines and devices’ components. The paper presents the results of tribological investigations of components produced in FDM printing technology. The authors presented the evaluation of sliding properties of the model friction couple – block on ring type – of available thermoplastic polymers and polymers’ composites under dry friction conditions. The authors assessed the influence of material type and printed structure on resistance to motion of prepared samples.
This article discusses the possibility of assessing the technical condition of rolling bearings based on tribological tests of oil samples. The problem is to define diagnostic levels, especially when has a relatively small number of measurements (3, 4, 5 etc.). Rating variance of measurements can be performed using the dimensionless factor covariance () and the dimensionless coherence function 2(). The set is compact enough when () and 2() will be close enough to oscillate around the value of 1 [1,3]
Lubricated tribosystems such as main-shaft bearings in gas turbines have been successfully diagnosed by oil sampling for many years. In practice, the interpretation of wear debris analysis results can pose a challenge due to the intricate structure of power transmission systems and the varying degrees of sensitivity among test methods. In this work, oil samples acquired from the fleet of M601T turboprop engines were tested with optical emission spectrometry and analyzed with a correlative model. Customized alarm limits were determined for iron by binning aluminum and zinc concentration into four levels. Two-way analysis of variance (ANOVA) with interaction analysis and post hoc tests was carried out to study the impact of aluminum and zinc concentration on iron concentration. A strong correlation between iron and aluminum, as well as a weaker but still statistically significant correlation between iron and zinc, was observed. When the model was applied to evaluate a selected engine, deviations of iron concentration from the established limits indicated accelerated wear long before the occurrence of critical damage. Thanks to ANOVA, the assessment of engine health was based on a statistically proven correlation between the values of the dependent variable and the classifying factors.
Measurements of signals received from ambient environment is a difficult task for technical diagnostics and becomes even infeasible in a series of cases. It is why the issues related to elimination of ambient factors from the identification process of diagnostic thresholds are truly justified. The method for elimination of environment impact is disclosed in this paper and consists in displacement of a specific set of measured diagnostic parameters (the initial set) in relation to the subsequent set of diagnostic parameters (the target set). Then the square of amplitude gain and the phase shift are calculated for these two mutually shifted data sets, which makes it possible to evaluate “cohesion” density of results obtained for diagnostic signals and thus their suitability for calculation of diagnostic thresholds. The method is characterized by the peculiarity that it takes account for ambient “environment” with no need to measure its parameters [6, 7, 8, 12, 13, 14].
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