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Aircraft engines are equipped with a huge number of sensors that generate thousands of signals. One of the most important problems, especially during testing, is that the volume of this data is so large that experts are no longer able to process this data. Today, the direction related to the intellectualization of data processing and analysis methods is developing intensively. Intelligent data analysis systems are designed to minimize the effort of the decision maker in the process of data analysis, as well as in configuring analysis algorithms. Many intelligent data analysis systems allow not only to solve classical decision-making problems, but also to identify cause-and-effect relationships, hidden patterns in the system being analyzed. The article deals with the tasks of intellectual processing and analysis of data from the electronic control system (EСS) unit during engine testing. Using machine intelligence methods, the cause-and-effect relationships and regularities of the parameters of the turbojet engine were identified, and a large amount of data was analyzed. The results of data mining will be used for further informed decisionmaking and automation of the expert's analytical activities. Keywords—machine intelligence, principal component analysis, cluster analysis, electronic control system, turbojet engine, data analysis system

Intelligent Data Processing and Analysis During the Engine Test