Fractal mathematics applications for wear image analysis of engines using biofuels

Sustainable power generation is of utmost importance now a days. Biofuel applications in engine contributes significant achievement to reach the goal. But sometimes it creates a barrier when life span of component is concerned. Therefore, identification of any failure or gradual degradation of the engine run by unconventional fuels is important for adopting early maintenance strategy. In the present work, a complete case study on engines run by conventional as well as unconventional fuels is shown to compare internal degradation of the engines. Wear, a complex and an internal phenomenon of degradation has been investigated for identification of failure of engines. Images of wear particles have been developed following standard procedures. Though the wear particle images represent some qualitative information but the type of wear and their subsequent severity can be confirmed by an important parameter which is called the fractal dimension. By the application of fractal mathematics, wear particle images have been characterised by finding out their fractal dimensions and thus, maintenance action can be implemented to enhance the life span of the engine. Copyright (C) 2022 Elsevier Ltd. All rights reserved.