Intelligent fault detection and predictive diagnosis method suitable for vibration table

The invention discloses an intelligent fault detection and predictive diagnosis method suitable for a vibration table. The method comprises the following steps: data acquisition; performing feature extraction based on expert knowledge base evaluation joint correlation analysis; fault detection and predictive diagnosis based on a neighborhood adaptive learning algorithm; according to the method, full and effective extraction of local fine features and intelligent fault detection and predictive diagnosis of a system with high-dimensional, nonlinear and time-varying characteristics are realized, the problems of high operation and maintenance cost, safety risk of field personnel and the like caused by non-planned shutdown maintenance due to frequent abnormal faults of vibration test equipment are effectively solved, and the method is suitable for large-scale popularization and application. The method can be used for improving the reliability of continuous normal operation of equipment and the accuracy of fault de