Silicon pressure sensor temperature compensation method based on extreme learning machine

An extreme learning machine and pressure sensor technology, applied in the direction of measuring fluid pressure, instruments, measuring devices, etc., can solve the problems that the compensation accuracy cannot meet the high precision requirements, it is difficult to meet the high precision, and the network training time is long.

Inactive Publication Date: 2014-10-29
XI AN JIAOTONG UNIV
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Problems solved by technology

However, the compensation accuracy of the binary regression method widely used in software methods cannot meet the high-precision requirements, and the currently popular support vector machine, BP neural network, and radial basis network methods have high compensation accuracy, but there are complex configuration parameters. Defects such as long network training time
In short, the existing compensation methods have their own problems, and it is difficult to meet the needs of high precision, easy generalization and engineering

Method used

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  • Silicon pressure sensor temperature compensation method based on extreme learning machine
  • Silicon pressure sensor temperature compensation method based on extreme learning machine
  • Silicon pressure sensor temperature compensation method based on extreme learning machine

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Embodiment Construction

[0026] The implementation of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0027] refer to figure 1 , a silicon pressure sensor temperature compensation method based on extreme learning machine, comprising the following steps:

[0028] Step 1: Collect a set of pressure values ​​P (within the measuring range of the pressure sensor) applied by the pressure sensor at different temperatures (within the working temperature range), such as [-40°C, -30°C,...,80°C], such as [0MPa ,2MPa,...,20MPa], output pressure signal V, temperature sensor output signal T and measured pressure P, and form a data source [V T P];

[0029] Step 2: Select data sources under different temperature and pressure conditions as sample data, and select samples according to the principle of equal intervals, for example, the temperature interval is 20°C, the pressure interval is 5MPa, and the pressure; for each column of the sample data, use Perform n...

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Abstract

The invention provides a silicon pressure sensor temperature compensation method based on an extreme learning machine. The method is characterized in that data sources acquired under different temperature are used as the sample data for building a temperature compensation model of the extreme learning machine, and then silicon pressure sensor temperature compensation model of the extreme learning machine is learnt and verified according to a training sample and a testing sample. The method has the advantages that little characteristic variable is needed, the compensation is fast, the precision is high, and the number of the optimal hidden nodes is independently selected.

Description

technical field [0001] The invention belongs to the technical field of silicon pressure sensors, and in particular relates to a silicon pressure sensor temperature compensation method based on an extreme learning machine algorithm. Background technique [0002] With the maturity of MEMS technology, silicon piezoresistive sensors have wide demand and application prospects in industrial and other fields due to their low cost, small size, high precision and easy processing. The accuracy of the sensor (that is, the precision parameter) plays a decisive role in the performance of the entire measurement system; but the silicon piezoresistive diaphragm as the core is sensitive to temperature changes, so that the zero point and sensitivity of the sensor will drift when measuring at different temperatures . Therefore, in order to reduce the influence brought by the temperature characteristics of silicon itself, it is necessary to use temperature compensation technology to correct it...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01L19/04
Inventor 赵玉龙周冠武李村
Owner XI AN JIAOTONG UNIV
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