Clustering Research on Ship Fault Phenomena Based on K-means Algorithm

Use data mining to extract useful information and knowledge of equipment fault repair information data, so as to provide equipment design and maintenance support services more fully. This is of great significance for strengthening the management and design of equipment, improving the integrity of equipment and the effectiveness of maintenance support. Based on the characteristics of historical maintenance data of a ship's equipment, this paper proposes a data mining method based on K-means clustering, and analyzes the fault phenomenon in equipment maintenance historical data. and analyzes the distribution of equipment failure modes. The situation provides effective data support for the analysis of equipment failure causes and the design requirements acneration of the support features.