Abstract: This paper proposes a fault diagnosis strategy for secondary circuits in intelligent substations using SV/GOOSE technology. A multidimensional diagnostic method was developed by analyzing SV and GOOSE message data, including data quality assessment, waveform feature analysis, state variable displacement, and temporal logic analysis. The strategy utilizes evidence theory and an improved fuzzy reasoning algorithm for multi-source information fusion, creating a fault diagnosis decision system. Experimental results demonstrate over 92% diagnostic accuracy for typical faults and an average response time under 50 ms, highlighting its practical value.