Bridge progressive drift data cleaning method based on data difference value

A data cleaning and progressive technology, applied in the direction of electrical digital data processing, special data processing applications, digital data information retrieval, etc., to achieve the effect of reducing data analysis errors, high degree of intelligence, and good real-time performance of the method

Pending Publication Date: 2019-09-27
上海深物控智能科技有限公司
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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a bridge progressive drift data cleaning method based on data difference in view of the deficiencies in the prior art above. This bridge progressive drift data cleaning method based on data difference can accurately and effectively process bridge Progressive drift data problem with relatively stable signal fluctuation in health monitoring

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  • Bridge progressive drift data cleaning method based on data difference value
  • Bridge progressive drift data cleaning method based on data difference value
  • Bridge progressive drift data cleaning method based on data difference value

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Embodiment Construction

[0037] The following is based on Figure 1 to Figure 6 The specific embodiment of the present invention is further described:

[0038] A bridge progressive drift data cleaning method based on data difference, comprising the following steps:

[0039] Step 1: Get sensor raw data.

[0040] Step 1 specifically includes:

[0041] Obtain the raw data collected by the sensors in the bridge health monitoring system{x i}, i=1,2,...,n, where n is the number of original data.

[0042] Step 2: Calculate the difference between the adjacent data between the original data.

[0043] Step 2 specifically includes:

[0044] By calculating {x i},i=1,2,...,n the difference between the adjacent data, get the numerical sequence {d i},i=1,2,...,n-1, where d i =x i+1 -x i .

[0045] Step 3: Extract the trend data from the original difference data through the Super Smoother algorithm, and obtain the difference between the original difference data and the trend data.

[0046] Step 3 specific...

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Abstract

The invention discloses a bridge progressive drift data cleaning method based on a data difference value. The bridge progressive drift data cleaning method comprises the steps of obtaining the sensor original data; calculating a difference value of the adjacent data between the original data; extracting the trend data from the original difference value data through a Super Smart algorithm to obtain a difference value between the original difference value data and the trend data; obtaining a change range of a normal value of a difference value of the original difference value data and the trend data by adopting an interval estimation theory according to a mean value and a standard deviation of the difference value of the original difference value data and the trend data; searching a data position where the difference value of the original difference value data and the trend data is outside the confidence interval, determining the position of the drift abnormal value in the original data, and cleaning the drift abnormal value. According to the present invention, the progressive drift phenomenon in the data with slower signal fluctuation can be accurately identified, the processing efficiency of the original data is improved, the real monitoring data can be restored to the maximum extent, and the effective data is provided for the subsequent structure state analysis.

Description

technical field [0001] The invention belongs to the field of bridge health monitoring data analysis and research, in particular to a bridge progressive drift data cleaning method based on data difference. Background technique [0002] Data cleaning is the basis for subsequent analysis and mining of bridge health monitoring data, and it is also the step to realize the value of monitoring data. With the gradual maturity and widespread use of domestic bridge health monitoring system technology, the importance of data cleaning is also increasing day by day. Among them, the phenomenon of monitoring data drift is relatively common in the process of bridge health monitoring, and its main reason is that the sensor itself is faulty or is interfered by the external environment. The form of data drift is: the monitoring data will have a whole or partial offset, and a partial upward or partial downward offset in a certain period of time in the time domain, a discontinuous situation app...

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Application Information

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IPC IPC(8): G06F16/215
CPCG06F16/215
Inventor 任普
Owner 上海深物控智能科技有限公司
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