Method for realizing online monitoring of gas analyzer based on nonlinear filtering algorithm

A non-linear filtering and gas analyzer technology, applied in the direction of analyzing materials, instruments, measuring devices, etc., can solve the problems of complex calculation, unfavorable engineering implementation, high cost, fast response time, online monitoring, white noise and Gaussian The effect of noise suppression

Pending Publication Date: 2022-06-03
安荣信科技(南京)有限公司
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Problems solved by technology

[0003] At present, common filtering algorithms cannot perfectly balance stability and real-time performance, and many existing improved filtering algorithms are complex in calculation and high in cost,

Method used

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  • Method for realizing online monitoring of gas analyzer based on nonlinear filtering algorithm
  • Method for realizing online monitoring of gas analyzer based on nonlinear filtering algorithm
  • Method for realizing online monitoring of gas analyzer based on nonlinear filtering algorithm

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Example Embodiment

[0032] Example:

[0033] First, in step 1, set the filter coefficient according to the actual situation of the data to be processed The count value of the initial filter counter is 0, the initial noise threshold value is 0.8, and the initial filter value of the concentration change is 0.2. The above parameters are determined based on the response speed and filtering effect of the actual concentration data filtering process.

[0034] In step 2, the concentration data C is collected every second t , when the acquisition time exceeds 11s, the concentration change at time t is calculated, and n is 11, then the fitting slope is

[0035]

[0036] Denoted as the concentration change Δ at time t t .

[0037] In step 3, the filter counter is updated by comparing the concentration variation at time t with the noise threshold value. If Δ t If it is greater than the noise threshold, the count value of the filter counter is increased by 1 on the original basis. Otherwise, it is fu...

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Abstract

The invention discloses a method for realizing online monitoring of a gas analyzer based on a nonlinear filtering algorithm. The method comprises the following steps: presetting a filtering coefficient of a self-adaptive filtering algorithm, setting a count value of an initial filtering counter to be 0, initializing a noise threshold value and initializing a concentration variation filtering value; performing real-time data sampling to obtain the concentration value of the analyzer at the moment t, and calculating the concentration variation at the moment t; updating the count value of the filter counter; carrying out nonlinear filtering on the concentration variable quantity at the moment t and the concentration value at the moment t; and updating the noise threshold value. The method is short in response time, white noise and Gaussian noise are obviously inhibited, when the method is applied to automatic monitoring of the pollution gas concentration of a gas analyzer, the filtering result can follow up in time when the gas concentration is subjected to step change, and the filtering result can tend to be stable when the gas concentration tends to be stable, so that the method is suitable for automatic monitoring of the pollution gas concentration of the gas analyzer. The stability and the sensitivity are perfectly considered, and the requirement of online monitoring is met.

Description

technical field [0001] The invention relates to the technical field of on-line monitoring of gas concentration, in particular to a method for realizing on-line monitoring of a gas analyzer based on a nonlinear filtering algorithm. Background technique [0002] The original signal of linear filtering and the filtering result are an arithmetic operation, which is realized by operations such as addition, subtraction, multiplication and division, while the original signal and filtering result of nonlinear filter are a logical relationship, that is, realized by logical operation. In real life, the gas concentration detected by optical instruments is actually nonlinear. On the one hand, in the process of collecting data, the sensor will inevitably generate abnormal values ​​due to various disturbances, resulting in the introduction of more spectra into the collected spectrum. Noise, it is necessary to use a filtering algorithm to reduce noise, but this will inevitably lead to a de...

Claims

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Application Information

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IPC IPC(8): G01N33/00H03H21/00
CPCG01N33/0062H03H21/0043G01N2033/0068
Inventor 丁小洁王辉
Owner 安荣信科技(南京)有限公司
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