Anomaly Location Model for Aircraft Intensity Detection Based on Multi-source Data Fusion
摘要
An anomaly localization model for aircraft intensities is built using multi-source information fusion in order to completely utilize the enormous data of aircraft intensity and realize their data value. To increase the accuracy and reliability of information, the multi-source strength data from the entire machine level in the “building block” test verification system is first evaluated, cleaned, redundant data, and noise are removed. Then, we can achieve unified integration, efficient access to multi-source data, and improve information integrity and consistency by integrating full spatio-temporal, full-dimensional, and full-factor data and designing a logical architecture for a multi-source heterogeneous intensity testing data cloud platform. Finally, using the three-layer information fusion, it is possible to implement deep analysis and the fusing of intensity test data to accurately identify anomalous positions.