In order to solve the problems of low efficiency and variety of results in preprocessing massive railway catenary geometric inspection data by manual interaction, this paper proposes an automatic preprocessing method for railway catenary geometric inspection data. A mileage jump point identification method is proposed based on the modified threshold variation algorithm; a data outlier removal method is proposed based on the repeatability inspection algorithm; a mileage automatic calibration method is proposed based on the principle of maximizing data similarity; a calibration evaluation method is proposed based on the principle of minimizing relative error. The above mentioned automatic preprocessing methods are used to preprocess the field test data. The results show that the method can not only identify the abnormal jump points in the inspection data, but also achieve efficient mileage calibration and calibration evaluation functions, which improves the efficiency of preprocessing railway catenary geometric inspection data.
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