Research on Predicting the Operational Status and Health Trend of Clock Testers Based on Crystal Oscillator Data Analysis

This paper proposes a method for predicting the operating status and health trend based on crystal oscillator data analysis, addressing the current situation where the measurement results of clock testers in electric energy meter verification work are unreliable due to performance issues with the built-in quartz crystal oscillators. By collecting crystal oscillator output frequency data, employing methods such as time comparison modeling and time series analysis, and combining key indicators such as stability, accuracy, and aging rate, a judgment model is constructed. Experimental results show that this method improves the accuracy of predicting crystal oscillator performance degradation by $23 \%$ compared to traditional monitoring methods. It can effectively avoid time measurement deviations in electric energy meters caused by crystal oscillator failures, providing a scientific basis for preventive maintenance of clock testers.