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In response to practical issues such as high requirements for functional and performance verification of the aviation engine PHM system, multiple verification contents, and complex verification business, this paper analyzes the development and verification situation and experience of advanced aviation engine PHM systems abroad, and proposes a design method for a PHM simulation verification platform based on knowledge graph technology. This method utilizes the semi structured, efficient, and intuitive characteristics of knowledge graph to effectively organize and manage a large amount of information knowledge related to engine PHM validation, including fault modes, fault features, algorithm models, and expert knowledge. On this basis, further targeting the demand for large amounts of data and high computational requirements in engine PHM verification, a knowledge graph based aviation engine PHM simulation verification platform has been established using technologies such as big data, data mining, machine learning, and cloud services. Applications such as data mining and information extraction, expert knowledge acquisition, and multi-level fusion diagnosis intelligent guided reasoning have been implemented. Finally, taking a certain type of engine as the object, the PHM simulation verification of the engine was introduced. After analyzing the actual verification results, the PHM simulation verification platform proposed in this article can effectively solve the problems of limited historical fault samples and single verification function that can be verified in the aviation engine PHM system.