Highly similar waveforms recorded from repeating earthquakes can be
utilized to evaluate the data quality of a seismic station. We used a
hypothesis testing method to establish a data quality detection model
based on repeating earthquakes. The model effectiveness was verified
using repeating earthquake data from 109 stations in the Global Seismic
Network. A total of 842 permanent broadband stations in mainland China
were evaluated using this model. Eighteen anomalies were found mainly
attributed to calibration, instrument noise, mass recentering, and
regional long-period interference. We found that most of the stations
function well. Moreover, utilizing repeating earthquakes to analyze the
waveform quality can circumvent the need for extensive forward
calculations, as well as greatly reduce the influence of source
parameter uncertainties and structural complexity on the seismogram.
Additionally, the need for detection in other datasets in different
regional networks has broadened the scope of these applications.