Trend automatic extraction method based on data block

An automatic extraction and trend extraction technology, applied in the field of data processing, can solve problems such as loss of data features, data results affecting trend results, and difficulty in determining the degree of data smoothness.

Active Publication Date: 2019-11-22
上海金润联汇数字科技有限公司
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Problems solved by technology

[0003] The purpose of the present invention is to provide a method for automatically extracting trends based on data blocks, which solves the problem in the prior art that data processing methods such as filtering and smoothing are...

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  • Trend automatic extraction method based on data block
  • Trend automatic extraction method based on data block
  • Trend automatic extraction method based on data block

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Embodiment Construction

[0028] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0029] In the case of large fluctuations in industrial data collection due to the influence of noise, data processing methods such as filtering and smoothing are first used on the collected data before the trend is extracted. The processed data results will directly affect the trend results, and the degree of data smoothing is difficult to determine , the problem of loss of data characteristics will be caused by excessive smoothing, how to accurately extract data trends on the basis of respecting the original data and maintaining data characteristics, in order to solve this problem, an automatic trend extraction method based on data blocks is established.

[0030] A method for automatically extracting trends based on data blocks in the present invention, the flow chart is as follows figure 1 As shown, the specific steps are as follows:

[00...

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Abstract

The invention aims to provide a trend automatic extraction method based on a data block. The method comprises the following steps: firstly, collecting axle temperature data of a certain train as original data, and then drawing an original data curve; searching for an optimal segmentation value of the original data, extracting a data envelope center line, and searching for a local extreme point ofthe data envelope center line; and finally, dividing the data into data blocks according to the obtained local extreme points, and performing trend extraction analysis in each data block to provide atheoretical basis for further predicting axle temperature change, judging train faults and the like. The method solves the problems that in the prior art, the trend is extracted after data processingmethods such as filtering and smoothing are adopted for the collected data, the processed data result directly influences the trend result, the data smoothness degree is difficult to determine, and data features are lost during excessive smoothing.

Description

technical field [0001] The invention belongs to the technical field of data processing, and in particular relates to an automatic trend extraction method based on data blocks. Background technique [0002] With the development of big data, the field of data processing and analysis technology is also constantly developing. The trend of data represents the changing state of parameters. On the basis of existing massive data, data trend extraction and analysis can provide guidance for subsequent behaviors. and decision making. How to accurately extract the trend of the data on the basis of respecting the original data has become a major problem to be solved. The data collected directly from the industry fluctuates greatly due to the influence of noise, and it is difficult to directly extract the trend. If the collected data is first processed by filtering and smoothing and then extracting the trend, the processed data results will directly affect Trend results, and the smoothn...

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Application Information

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IPC IPC(8): G06F17/50
Inventor 谢国李锦妮黑新宏费蓉姬文江赵金伟马维纲李鑫上官安琪
Owner 上海金润联汇数字科技有限公司
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