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Adaptive data reduction method based on piecewise transient recognition

A self-adaptive and segmented technology, applied in electronic digital data processing, structured data retrieval, database management systems, etc., can solve problems such as shortening data length, retaining key data duration, reducing data storage capacity, etc. Effect of data length

Pending Publication Date: 2020-08-28
HANGZHOU ANMAISHENG INTELLIGENT TECH CO LTD
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Problems solved by technology

[0004] Aiming at the problem that the down-sampling method in the prior art cannot retain the duration of key data while retaining trend information, the present invention proposes an adaptive data reduction method based on segmental transient recognition, which can extract large data samples The key information of the key information, select representative information points to save, and keep the overall trend and key mutation signal information in the signal, shorten the data length, and finally realize data downsampling and reduce the amount of data storage

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  • Adaptive data reduction method based on piecewise transient recognition
  • Adaptive data reduction method based on piecewise transient recognition
  • Adaptive data reduction method based on piecewise transient recognition

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Embodiment

[0026] An adaptive data reduction method based on segmental transient recognition, taking the speed information of a certain motor as an example, the sampling frequency of the speed data is 1Hz.

[0027] Include steps:

[0028] A) Speed ​​data length N 1 is 3900000, the target length after reduction is N 2 for 30000. Divide the data segment S into 150 segments, i represents the i-th segment data, 1≤i≤50. The length L of each piece of data is 78000, and the length T of each piece of data after reduction is 600.

[0029] B) Establish the proportional coefficient α of the subsection method and the transient method 1 and alpha 2 . Take the value in the most efficient direction, α 1 set to 0.5, α 2 It is set to 0.5, that is, the length of the reduced data by the segmentation method and the transient method are both 300.

[0030] C) The segmentation method is adopted for each segment of the signal, the data length L2 of each segment is 78000, the data length after reduction...

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Abstract

The invention discloses an adaptive data reduction method based on piecewise transient recognition, which comprises the following steps of: A, determining the number of segments and the length of eachsegment of reduced data according to the total data length and the reduced target length; b, establishing proportionality coefficients of a segmentation method and a transient method; c, according tothe proportionality coefficient, adopting a segmentation method for each segment of signals, and obtaining screened data and corresponding timestamps; d, according to the proportionality coefficient,adopting a transient method for each section of signal to obtain screened data and a corresponding timestamp, wherein the step D and C are not sequential; and E, integrating the data obtained by thesegmentation method and the transient method of each section of signal to obtain reduced data. According to the method, the trend information in the signal is extracted by adopting a segmentation method, the mutation information in the signal is extracted by adopting a transient method, and the data length is shortened on the basis that the information of the overall trend in the signal and the information of the key mutation signal are reserved by matching the two modes according to the proportionality coefficient.

Description

technical field [0001] The invention relates to signal and information processing technology, in particular to an adaptive data reduction method based on subsection transient recognition. Background technique [0002] With the rapid development of computer technology, the amount of global data is increasing exponentially, and a large amount of data has been accumulated in various fields, which brings certain challenges to data display and data storage. In the industrial field, working condition data is often stored in units of seconds. Taking flow data as an example, one data point is collected every second, and the total number of data points in five years is 158 million. If you need to pull historical data, it takes too long and affects the user experience. If the equipment continues to be in a stable working condition, the data samples are distributed smoothly, and the data contains a large amount of redundant data and useless data. Therefore, it is increasingly importa...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06F16/2455G06F16/25
CPCG06F16/2477G06F16/2462G06F16/24554G06F16/254
Inventor 李倩杨皓杰孙丰诚赵彤
Owner HANGZHOU ANMAISHENG INTELLIGENT TECH CO LTD
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