Incremental online characteristic extraction and analysis method and system
A feature extraction and analysis method technology, applied in the field of data analysis, can solve problems such as poor performance, large time overhead, and unclear feature structure, and achieve the effects of good scalability, poor scalability, and high efficiency
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Embodiment 1
[0028] The system architecture realized by the incremental online feature extraction and analysis method of the present invention is as follows: figure 1 shown, including the following specific steps:
[0029] (1) The incremental online feature extraction method of the present invention first sets up a database system module, the database system module mainly stores the relevant original time series data of industrial control, and the database system module provides data connection query with other modules simultaneously; The module includes multiple database tables, which mainly store time-series data, and the data storage structure is complex.
[0030] (2) The data preprocessing module performs data preprocessing on the original time series data set in step (1). The original time series data is incomplete and noisy, so the data preprocessing module can process these rough data and finally get a complete Correct timing data.
[0031] The data preprocessing module includes t...
Embodiment 2
[0040] (1) In this embodiment, the time-series data of the production of a certain drug is selected as the original data, and a corresponding database system is established.
[0041] (2) Preprocess the original data. The preprocessing mainly eliminates error values, null values and values with low acquisition frequency. The preprocessed values are visualized as figure 2 and image 3 As shown, it corresponds to the data signal of the temperature of the upper part of the heating and the steam pressure of the heating in the process of drug production and refining.
[0042] (3) Feature extraction For time series data, the benchmark features are: average value, variance and time length, and the extracted feature data is stored in the feature data table.
[0043] (4) The trigger threshold of the incremental trigger is set to 1000, that is, when the amount of data corresponding to the database system module increases to 1000, a feature extraction operation is triggered to inc...
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