The application discloses a state report improvement measure effect detection method and device, belongs to the
nuclear power field, aims to solve the problem that the traditional detection method is strong in subjectivity, low in efficiency and insufficient in data utilization. The application contains five steps of data collection, preprocessing, index calculation, effect detection and
report generation. First, multi-
source data such as operation logs and fault records are collected, stored after cleaning and
standardization; then, key indexes such as event frequency, severity, average
repair time and average fault interval time are calculated; through statistical and
machine learning algorithms such as multivariate regression model, the index changes before and after improvement are compared; finally, a detection report containing index comparison,
effect analysis and improvement suggestions is generated. The application realizes quantitative detection, improves the objectivity and efficiency of detection, provides data support for
nuclear power station operation decision, helps to improve the
operation safety and efficiency, and has good flexibility and expansibility.