Research And Implementation Of The Method For Evaluating The Quality Of The Seismic Network Records

In recent years, observation data of regional digital seismic network has also been applied to deep low frequency tremor monitoring, typhoon vibration monitoring and background noise tomography, in addition to being used for earthquake location and magnitude determination. So it has a wide range of applications. However, the quality of the data is undoubtedly the foundation and guarantee in the application process. Th e changes of system, instrument and environment will cause problems on quality of th e observation data in the process of data recording and production. So, it has become an urgent need to solve the problem that how to understand and evaluate the quality of the real time data recorded by regional digital seismic network.In view of the above problems, the paper studies the quality assessment method of data observation and the implementation of the evaluation system. First, it researches the method for evaluating the quality of the observation data based on background noise, mainly including using data step method to determine the continuity, integrity and availability; adopts the method of Power spectrum probability density function to monitor the status of the data recorded in the station; realizes the real time calculation of pedestal background noise level; uses the background noise auto correlation function to evaluate the parameters of observation system. Secondly, relying on digital seismic network system in Jiangsu Province, it uses Matlab platform to develop the system of data quality analysis and evaluation on the basis of JOPENS system. So, it can be realized that the continuously recorded data will be automatically read from the server of the digital seismic network center, and be calculated and analyzed. The timing analysis results can be automatically generated for researcher to analyze and study.The above research better achieved objective assessment of digital seismic network data recording quality and the real-time monitoring of observed system. You can discover the problems in the data, find solutions, and thus improve the quality of observed data, and improve the reliability of the relevant scientific research. At the same time, the calculation results of the evaluation process automatically generated graphs, charts, etc. can be directly applied to daily work and research.