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Complementing the method of areas of Gaussian characteristic figures for the rapid diagnosis of the technical condition of the low-pressure gas-phase injectors

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  • Szpica, Dariusz
  • Warakomski, Jakub

Abstract

The Fit for 55 package has significantly reduced CO2 emissions from combustion propulsion sources. Therefore, it is considered important to maintain the efficiency of drive units at the required level. One of the main causes of changes in this area is the failure of the power system. This study focuses on the diagnosis of the gas injector, where the Gauss characteristic figure area method was used. The choice of the method was due to its analytical approach, which is different from the commonly used ones, and its easy interpretation of the results. However, the Gauss method was found to lack sensitivity in certain areas. Hence the proposal to supplement it with a trend line, which is a novelty of the study. The trend line, and in fact its indicators, allowed for improved inference relative to the original Gauss approach. This eliminated the fact of equivalent fields of figures that are rotated or distorted. The trend line indicators accurately identified the position of the characteristic figure and its shape. To confirm the expediency of using the proposed approach, tests were carried out for injectors: brand-new, in-operation, end-of-life and remanufactured, as well as those with artificially simulated deficiencies. The test results and analysis presented in the paper can be useful for further work, but also as a guideline for supplementing existing test stands with the described diagnostic functions. The proposed innovative approach was used for the case of gas injectors, but it is possible to apply it to testing injectors of other fuels.

Suggested Citation

  • Szpica, Dariusz & Warakomski, Jakub, 2025. "Complementing the method of areas of Gaussian characteristic figures for the rapid diagnosis of the technical condition of the low-pressure gas-phase injectors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 209(C).
  • Handle: RePEc:eee:rensus:v:209:y:2025:i:c:s1364032124008396
    DOI: 10.1016/j.rser.2024.115113
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