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Method for optimizing rail transit data quality through data prism algorithm

A technology of data quality and prism, applied in database indexing, electronic digital data processing, structured data retrieval, etc., can solve problems such as inaccurate data, incomplete data, data loss, etc., and achieve the effect of improving data quality

Pending Publication Date: 2020-01-17
GUANGZHOU DIQING ELECTRONICS TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the following common problems are found in actual use: 1. The data is incomplete, due to factors such as unstable network connections, which lead to over-collection, under-collection, and empty mining; 2. The data is inaccurate, that is, the data is inconsistent with the actual scene , which is mainly reflected in the temperature level, temperature rise rate and temperature difference data, such as temperature jumps, distortions, etc.; 3. The data is not uploaded in real time, that is, the collected data is lost

Method used

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  • Method for optimizing rail transit data quality through data prism algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0027] A method for optimizing the quality of rail transit data through a data prism algorithm, comprising the following steps:

[0028] S1 checks whether the data is complete; when there is missing data, the record is empty, if it is empty for ten consecutive seconds, it is judged as a data problem, and hardware maintenance is performed, otherwise interpolation is performed;

[0029] S2 Check whether the data is accurate; set the normal data range, and correct the data beyond the range;

[0030] S3 checks whether the data is timely; sets the data delay range, and calls the data stored in the terminal to replace the data beyond the range.

[0031] The method of interpolation and completion in S1 is:

[0032] S11 assumes that y=f(x) is a straight line, and obtains the y value through the data of the two points (x0, y0) and (x1, y1) before and after the missing sampling point, and the y value is also the value of the missing point.

Embodiment 2

[0034] A method for optimizing the quality of rail transit data through a data prism algorithm, comprising the following steps:

[0035] S1 checks whether the data is complete; when there is missing data, the record is empty, if it is empty for ten consecutive seconds, it is judged as a data problem, and hardware maintenance is performed, otherwise interpolation is performed;

[0036] S2 Check whether the data is accurate; set the normal data range, and correct the data beyond the range;

[0037] S3 checks whether the data is timely; sets the data delay range, and calls the data stored in the terminal to replace the data beyond the range.

[0038] The method of interpolation and completion in S1 is:

[0039] Assume in the S11 that y=f(x) is a curve, the data of multiple points (x0, y0) ... (xn, yn) before and after the missing sampling point are used to obtain the y value, and the y value is also the value of the missing point value.

Embodiment 3

[0041] A method for optimizing the quality of rail transit data through a data prism algorithm, comprising the following steps:

[0042] S1 checks whether the data is complete; when there is missing data, the record is empty, if it is empty for ten consecutive seconds, it is judged as a data problem, and hardware maintenance is performed, otherwise interpolation is performed;

[0043] S2 Check whether the data is accurate; set the normal data range, and correct the data beyond the range;

[0044] S3 checks whether the data is timely; sets the data delay range, and calls the data stored in the terminal to replace the data beyond the range.

[0045] The method for correcting in the S2 is a look-up table method:

[0046] S21 adds known standard measured values ​​y1...yn one by one, and records the corresponding output readings x1...xn;

[0047] S22 stores the value of the standard input yi (i=1, 2...n) in a certain unit of the memory, uses xi as the address of the storage unit ...

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Abstract

The invention relates to the technical field of rail transit maintenance, in particular to a method for optimizing rail transit data quality through a data prism algorithm. The method comprises the following steps: S1, checking whether data is complete or not; recording the data as null when the data is missed, judging the data as a data problem if the data is null for ten consecutive seconds, andperforming hardware maintenance, otherwise, performing interpolation completion; S2, checking whether the data is accurate or not; setting a normal data range, and correcting the data exceeding the range; and S3, checking whether the data is timely or not; setting a data delay range, and calling the terminal storage data to replace the data exceeding the range. For the method, the acquired data is not lost, and each frame of data is completely reported through a technical means, and the temperature data is consistent with an actual scene, and hopping and distortion do not occur, and data quality is effectively improved.

Description

technical field [0001] The invention relates to the technical field of rail transit maintenance, in particular to a method for optimizing the quality of rail transit data through a data triangular prism algorithm. Background technique [0002] Since various power batteries and other structures in rail transit allow real-time monitoring and prediction, a large number of sensors are provided in the prior art to facilitate data collection. However, the following common problems are found in actual use: 1. The data is incomplete, due to factors such as unstable network connections, which lead to over-collection, under-collection, and empty mining; 2. The data is inaccurate, that is, the data is inconsistent with the actual scene , which is mainly reflected in the temperature level, temperature rise rate and temperature difference data, such as temperature jumps, distortions, etc.; 3. The data is not uploaded in real time, that is, the collected data is lost. [0003] The presen...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/215G06F16/22G06F12/16
CPCG06F16/215G06F16/2282G06F12/16
Inventor 常伟余捷全
Owner GUANGZHOU DIQING ELECTRONICS TECH
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