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Sensor dynamic compensation method and system

A dynamic compensation and sensor technology, applied in the field of sensors, can solve the problems of high sensor model dependence, high identification algorithm requirements, sensor model dependence, etc., and achieve the effect of changing the dynamic response and noise suppression ability

Pending Publication Date: 2021-09-21
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method has accurate compensation and can meet the compensation requirements with a small working frequency band, but it relies heavily on the sensor model and has high requirements on the identification algorithm, which has certain limitations.
The second is the inverse modeling method that does not depend on the sensor model. This type of method does not need to identify the sensor model. It only needs to set an appropriate objective function according to the input and output data of the sensor, and the corresponding compensation filter can be obtained through a certain optimization algorithm. , but the compensation accuracy is slightly worse, and the working frequency band of the system is expanded after compensation. Commonly used algorithms include particle swarm algorithm, fireworks algorithm, etc.
However, the realization of high resolution (code size) of digital sensors is ultimately limited by thermal noise, noise in the signal conditioning link, and digital noise in the digital processing link. In order to suppress noise, it is required to limit the operating frequency band of the system. Therefore, sensor dynamic compensation and denoising are contradictory
The current compensation algorithm may not be able to take into account both at the same time, or it is more dependent on the sensor model, and the design is more complicated

Method used

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Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0068] A sensor dynamic compensation method, comprising the following steps:

[0069] (1) According to the requirements of sensor dynamic compensation, the standard particle swarm optimization algorithm is used to design a dynamic compensation digital filter, that is, the compensator, and the transmission coefficient of the compensator (a i ,b i );

[0070] (2) According to the transmission coefficient of the compensator (a i ,b i ), calculate the zero point q of the compensator i and the pole pi;

[0071] (3) Keep the zero point of the compensator unchanged, choose the pole of the compensator, add a suitable pole, and change the size of the working frequency band of the entire sensing system composed of the sensor and the compensator after compensation;

[0072] (4) Adjust the magnitude of the output signal amplitude of the compensator; by multiplying the discrete transfer function of the compensator by a coefficient k 0 to adjust the amplitude of the output signal afte...

Embodiment 2

[0074] According to a kind of sensor dynamic compensation method described in embodiment 1, its difference is:

[0075] In step (1),

[0076] Suppose the z-domain transfer function H(Z) of the compensator is shown in formula (I):

[0077]

[0078] In formula (I), q and p represent the order of the compensator; Z is the Z transformation operator, and b0...bq, a0...ap represent the parameters of the compensator, that is, the Z-domain transfer function of the compensator , where the subscripts q and p represent the order of the compensator.

[0079] Using the standard particle swarm algorithm to design a dynamic compensation digital filter, that is, a compensator, the transmission coefficient of the compensator (a i ,b i ), the specific steps include:

[0080] [1] Randomly initialize the particle swarm, including the size N of the particle swarm, the initial velocity V of the particle and the boundary of the velocity [Vmin, Vmax], the position X and the optimization range ...

Embodiment 3

[0097] According to a kind of sensor dynamic compensation method described in embodiment 2, its difference is:

[0098] In step (2), the zero point q of the compensator i And the calculation method of the pole pi is as follows:

[0099] The coefficient a in the denominator of the compensator z-domain transfer function i Arranged in the matrix A according to the descending power of Z, the coefficient b in the numerator of the transfer function in the z domain of the compensator i It is also arranged in the matrix B according to the descending power of Z. Using the roots function in matlab, the roots (A) can obtain the pole pi of the compensator, and the roots (B) can obtain the zero point qi of the compensator.

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Abstract

The invention relates to a sensor dynamic compensation method and system, and the method comprises the following steps: (1), designing a dynamic compensation digital filter through a standard particle swarm algorithm according to the compensation requirements; (2) calculating a zero point and a pole of the compensator; (3) keeping the zero point of the compensator unchanged, selecting and rejecting the poles of the compensator to a certain extent, and adding proper poles to change the size of the working frequency band of the compensated system; and (4) adjusting the amplitude of the output signal of the compensator. According to the method, the advantages of the standard particle swarm algorithm applied to dynamic compensation of the sensor and the advantages of the pole-zero assignment method are combined, and the novel method for dynamic compensation of the sensor is designed, compared with a standard particle swarm algorithm and a zero pole assignment method, the method does not depend on a sensor model, and the dynamic response and noise suppression capability of a sensing system can be improved at the same time.

Description

technical field [0001] The invention relates to the technical field of sensors, in particular to a sensor dynamic compensation method and system. Background technique [0002] Measurement and control technology has been an indispensable part of people's life and production since ancient times. In ancient times, people used sundials to measure time for production and life, and used compass to identify directions outdoors. With the progress of the times and the development of science and technology, measurement and control technology has been widely used in scientific experiments, military defense, aerospace and other fields, which are of great significance to maintaining national security and accelerating the development of high technology. [0003] As the main device for detecting and converting physical information such as temperature, humidity and pressure, the sensor is the primary link for the measurement and control technology to obtain external information and the basi...

Claims

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Application Information

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IPC IPC(8): G06F30/25G06F111/06G06F119/02
CPCG06F30/25G06F2111/06G06F2119/02
Inventor 陈涤付芹
Owner SHANDONG UNIV