{"title":"Application of Artificial Neural Network for Internal Combustion Engines","authors":"None Eslam Sayed, Nouby M. Ghazaly","doi":"10.52783/kjcs.v1i1.223","DOIUrl":"https://doi.org/10.52783/kjcs.v1i1.223","url":null,"abstract":"In this research, acoustic emission (AE) technology is used to detect faults in the valves in the internal combustion engine, where the cylinder head of a spark ignition engine was used as an experimental setup. The study was conducted on three types of valve damage ((clearance, half-notch, and notch) on valve leakage. The study proved that the acoustic emission technique is an effective method in detecting damage to valves in both the time and frequency domain. The neural network was trained based on time domain analysis using AE parametric features (, number, absolute AE power, maximum signal amplitude, and average signal level).","PeriodicalId":484425,"journal":{"name":"Kuwait Journal of Computer Science","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135950186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}