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Time sequence key value type industrial process data parallel analysis method

A technology of industrial process and analysis method, which is applied in the field of parallel analysis of time series key-value industrial process data, and can solve the problems of long time series data and lack of consideration of time series trend characteristics

Inactive Publication Date: 2018-09-07
CHONGQING UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The collected time series data are usually long and high-dimensional, and need to be effectively and quickly segmented. Most complex segmentation algorithms must consider the challenges brought by the length of the time series. The current time series data analysis methods lack the characteristics of time series trends. consideration

Method used

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  • Time sequence key value type industrial process data parallel analysis method
  • Time sequence key value type industrial process data parallel analysis method
  • Time sequence key value type industrial process data parallel analysis method

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Experimental program
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Embodiment

[0045] Example: such as figure 1 Shown; A time series key-value type industrial process data parallel analysis method, it includes:

[0046] S1: Obtain time series data;

[0047] S2: data preprocessing;

[0048] S3: Split the time series data in parallel, obtain the turning points and corresponding slopes as key data points, and construct the key data points as a new time series.

[0049] S4: Based on the dynamic time warping method, the improved distance measure and the parallel calculation of the curved path matrix are used for similarity discrimination and classification, as shown in Table 1.

[0050] Table 1 Parallel computing curved path table

[0051]

[0052] Among them, S1, S2, and S3 are subsequences of the time series S, and C is the time series. The shortest curved path is: The font in bold in Table 1, namely (S 2 , C)=(71,69) is 2 and 3; (S 2 , C)=(73,73) is 5; (S 2 , C)=(73,75) is 4; (S 2 , C)=(80,79) is 35; (S 2, C)=(80,80) is 35; (S 2 , C)=(80,79) i...

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Abstract

The invention discloses a time sequence key value type industrial process data parallel analysis method. The method comprises the steps that S1, time sequence data is acquired; S2, the data is preprocessed; S3, the time sequence data is parallelly partitioned; and S4, turning points obtained after segmentation and corresponding slopes are used as key data points to establish sets respectively, distance measurement is improved, a dynamic warping distance is parallelly calculated based on a dynamic time warping method, similarity discrimination is performed, and then classification is performed.The method has the advantages that the time sequence data can be parallelly partitioned, key data in an industrial process can be obtained, and the dynamic warping distance can be parallelly calculated.

Description

technical field [0001] The invention relates to the technical field of industrial data analysis, in particular to a method for parallel analysis of time-series key-value industrial process data. Background technique [0002] With the continuous development of industrial manufacturing level, data has shown explosive growth. Massive sensors are used to monitor the operating status of corresponding components, and the frequency of sensor collection is getting faster and faster. The collected time series data are usually long and high-dimensional, and need to be effectively and quickly segmented. Most complex segmentation algorithms must consider the challenges brought by the length of the time series. The current time series data analysis methods lack the characteristics of time series trends. consideration. Contents of the invention [0003] In view of the above-mentioned defects in the prior art, the purpose of the present invention is to provide a parallel analysis method...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/23211G06F18/24137G06F18/22
Inventor 张可柴毅夏培峻韩昱辉赵晓航
Owner CHONGQING UNIV