Data compression method

Abstract

The invention relates to a data compression method. The method comprises the following steps of: acquiring initial measuring data and an initial acquisition time point of the initial measuring data and setting the type of a fitting curve passing by the initial measuring data; acquiring an initial feasible region of the initial measuring data according to the fitting curve; acquiring first measuring data with a set time interval behind the initial acquisition time point and acquiring a first feasible region of the first measuring data according to the fitting curve; and judging whether an intersection set exists between the initial feasible region and the first feasible region. The data compression method provided by the invention forms the feasible region through the fitting curve which is formed under a set bias restriction, stores the initial measuring data and coordinate values in the corresponding feasible region to acquire discarded measuring data, and the non-linear fitting curve reduces the quantity of data needing storing on the premise that the compressed data has the higher accuracy.

Description

technical field [0001] The invention relates to information processing technology, in particular to a data compression method. Background technique [0002] With the rapid development of industrial production, industrial production sites need to continuously collect and store a large amount of measurement data. In the process of collecting data, the measurement data is always changing constantly, so the measurement data needs to be stored. If it is necessary to continuously store each collected measurement data, it needs to occupy a considerable storage space, which requires a high cost for storing the aforementioned measurement data. On the other hand, due to the large amount of stored data, the retrieval and positioning processing required for reusing the stored measurement data is relatively cumbersome and complicated; this is very important for the real-time processing of measurement data in industrial automation. It is a great obstacle to use. [0003] In order to so...

AI Technical Summary

Problems solved by technology

If the above-mentioned SDT data compression method is applied to the situation where the measurement data is more reflected in a nonlinear relationship, it will cause a situation where the error accuracy and compression efficiency cannot be balanced; that is, if a higher compression ratio is required, it must be The compression accuracy is reduced; on the contrary, to ensure that the compressed measurement data has a high accuracy, the compression efficiency can only be reduced; Can not take into account the relationship between data compression efficiency and precision

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