Data processing method based on spline interpolation and data parallelism

Abstract

The invention provides a spline interpolation and data parallel-based data processing method. The method comprises the following steps: dividing an original monitoring data set into Q data subsets in sequence and processing each data subset by adopting a unique corresponding thread, wherein the processing comprises the following flows: generating cubic spline functions for the processed data subsets, collecting data points at equal intervals on spline curves so as to form new data subsets, and replacing data points at corresponding positions of the new data subsets by marked data points of the original data subsets so as to form processed data subsets; and splicing the thread-processed data subsets to form a final data set. The spline interpolation and data parallel-based data processing method provided by the invention has the following advantage that no matter whether the dimensionality of the input original monitoring data is greater than an expected data dimensionality or greater than the expected data dimensionality, the dimensionality of the original monitoring data can be efficiently and rapidly adjusted to the expected data dimensionality, and the information contained in the original data can be kept to the greatest extent.

Description

technical field [0001] The invention belongs to the technical field of data processing, and in particular relates to a data processing method based on spline interpolation and data parallelism. Background technique [0002] The microcomputer monitoring system is an important equipment to ensure the safe operation of the train and monitor the operation status of each signal equipment. The microcomputer monitoring system can detect the safety hazards in the operation of the signal equipment in time by analyzing the collected monitoring data of the signal equipment, and can also analyze each signal. The cause of the failure during the operation of the equipment, so as to guide the on-site maintenance, improve the maintenance level of the signal department and the efficiency of troubleshooting. [0003] However, due to the change of the health status of the signal equipment itself, the interference of environmental factors and other unknown factors, the dimensionality of the mon...

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Problems solved by technology

Otherwise, it will bring great difficulties to the establishment of the model and the realization of the algorithm.

[0005] Therefore, for the original monitoring data whose dimensions are not fixed collected by the microcomputer monitoring system, how to adjust the data dimension to a fixed dimension under the premise of retaining the information contained in the original monitoring data as much as possible, so that it can be input into the intelligent algorithm In the model, it has important practical significance, and no effective solution has appeared in the prior art

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