Research on Failure Cause Analysis Method Based on Aircraft Maintenance Records

Due to the accumulation of a large amount of maintenance text information recorded by maintenance personnel based on experience in aircraft maintenance, due to its strong professionalism and diverse expression methods, intelligent analysis has not yet been achieved, making it difficult to fully utilize these data. In response to this issue, this article proposes an aircraft maintenance record analysis method based on the ALBERT-TextCNN model, which solves the fault causes to assist maintenance personnel in correct troubleshooting work. Firstly, the vectorization representation of the preprocessed text and the preliminary feature extraction are performed by using ALBERT; Secondly, the TextCNN model is used to extract deeper features to improve the accuracy of model analysis; Finally, compared with other commonly used text analysis models, the results show that the method used in this article can accurately analyze the causes of faults in aircraft maintenance records, effectively improving the accuracy and speed of analysis.