Fault sensor information reconstruction method based on measured value association degree

A fault sensor and information reconstruction technology, which is applied in the field of information processing and civil engineering structure health monitoring, can solve the problems of insignificant long-term fault prediction effect, less time-consuming, and ineffective fault reconstruction effect, etc.

Active Publication Date: 2015-09-02
卢伟
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Problems solved by technology

However, this method takes less time, and due to the neural network recovery method, it is mainly aimed at data reconstruction of short-term sensor failures, and has no obvious effect on sensors with high sampling rates and long-term failure prediction.
[0004] By analyzing the research of domestic and foreign scholars on data reco

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  • Fault sensor information reconstruction method based on measured value association degree
  • Fault sensor information reconstruction method based on measured value association degree
  • Fault sensor information reconstruction method based on measured value association degree

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Embodiment Construction

[0080] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings.

[0081] Such as figure 1 As shown, the present invention provides a method for reconstructing faulty sensor information based on the degree of correlation of measured values, the method comprising the following steps:

[0082] S1. For the faulty sensor, calculate the correlation degree between the response of the measuring point where the sensor is in normal operation and the responses of other measuring points;

[0083] S2. By comparing the degree of correlation, determine the response variables required for establishing the correlation model;

[0084] S3. Further, the partial least squares method is used to establish a reconstruction model of the reconstruction variable and the response variable, and the structural health monitoring measured data is used to reconstruct the fault sensor response information ...

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Abstract

The invention provides a fault sensor information reconstruction method based on measured value association degree. The method comprises the following steps: S1, aimed at a fault sensor, calculating association degree of response of a measuring point where a sensor is on in normal operation and other measuring points; S2, through comparing association degree values, determining an association model, establishing required response variables; S3, and using a partial least squares to establish a reconstruction model of reconstruction variables and the response variables, and using measured data of structural health monitoring, performing fault sensor response information reconstruction on the fault sensor. The method has very good effect on fault sensor information reconstruction, obviously reduces reconstruction errors, and ensures variation trend of the reconstruction values to keep consistent with variation trends of practical values. The method has obvious integrated structure reliability.

Description

technical field [0001] The invention belongs to the fields of civil engineering structure health monitoring and information processing, and in particular relates to a fault sensor information reconstruction method based on the correlation degree of measured values. Background technique [0002] Data acquisition is a very important link in the structural health monitoring system, and the analysis of structural safety performance depends on the reliability of data acquisition. In the actual operation process of civil structure health monitoring, due to factors such as equipment aging, it is inevitable that some sensors will fail and cause data distortion. At the same time, some sensors are not easy to replace, resulting in data loss and reducing the reliability of the overall data. The overall analysis of the structure leads to decision-making mistakes and loses the meaning of structural monitoring; at the same time, structural monitoring will generate a large amount of data, ...

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Application Information

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IPC IPC(8): G01D18/00G06F19/00
Inventor 卢伟滕军李超
Owner 卢伟
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