A dynamic detection method and system for train control equipment based on multi-source data fusion
By using a multi-source data fusion detection method, high-precision status monitoring of train control equipment under complex operating conditions was achieved, solving the problem of insufficient detection accuracy in existing technologies and improving the reliability of detection and resource utilization efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHUOHUANG RAILWAY DEV
- Filing Date
- 2026-04-17
- Publication Date
- 2026-07-17
AI Technical Summary
Existing train control equipment testing methods mostly rely on a single data source or static testing methods, which makes it difficult to fully reflect the dynamic performance of train control equipment under real operating conditions. They also lack an effective multi-source data fusion mechanism, resulting in insufficient testing accuracy.
A detection method based on multi-source data fusion is adopted. By monitoring train operation data, multi-source heterogeneous data of train control equipment is collected, and spatiotemporal synchronization and abnormal data removal are performed. The data is divided into data feature streams of different dimensions, and feature fusion is performed using feature extraction network and cross-dimensional collaborative attention network. Finally, the detection result is determined by local temporal feature extraction and gated loop model.
It improves the accuracy and reliability of train control equipment detection, enables high-precision status monitoring under complex operating conditions, and extends the service life of storage and transmission resources.
Smart Images
Figure CN122412909A_ABST