Method for improving measurement precision of air quality detection equipment by segmentation optimal calibration

Abstract

The invention discloses a method for segmentally optimal calibration to improve the measurement accuracy of air quality detection equipment, including (S10) dividing the total range of PM2.5 concentration of the SD to be corrected into at least three sub-ranges from low to high; ( S20) Control the PM2.5 concentration in the calibration room to be within each sub-range for a period of time, use the SD to be calibrated and the standard detection equipment to measure the PM2.5 concentration multiple times at the same time, and record the measurement results; (S30) Use the least square method to fit multiple PM2.5 concentration data measured in each section to obtain the optimal solution of the correction coefficient; (S40) Segmentally calibrate the PM2.5 concentration data in each section of the SD to be corrected Optimal correction factor. The present invention partitions the installation range of the equipment to be corrected, and optimally fits the correction coefficients of each partition by the least square method, thus reducing the influence of random drift errors on the measured values ​​of the equipment, and effectively avoiding some measurements The influence of the dead zone on the accuracy of the equipment, the accuracy is greatly improved.

Description

technical field [0001] The present invention relates to the technical fields of smart home and measurement and detection, and in particular relates to a method for subsection optimal calibration to improve the measurement accuracy of air quality detection equipment, which is mainly applied to smart devices (Smart Devices) for detecting air quality such as air boxes. ) for indoor PM2.5 measurement accuracy. Background technique [0002] Among the existing smart device manufacturers for air PM2.5 measurement, they seldom calibrate their own finished equipment, even if the calibration is performed once according to the requirements of the sensor manufacturer for measuring PM2.5. In this way, the measurement accuracy of the smart device is completely dependent on the accuracy of the sensor when it leaves the factory. This design method leads to low measurement accuracy and large error of PM2.5 on the market, which cannot meet the needs of users. [0003] The whole machine cali...

AI Technical Summary

Problems solved by technology

This correction method introduces the mechanical error, drift error and drift error of the standard instrument of the original sensor, but these errors are not processed in the calibration process, resulting in the low accuracy of the sensor of the air quality smart device shipped from the factory, so , need to solve this problem

At the same time, in the existing correction scheme, since there is no separate correction for different PM2.5 concentration intervals, these SDs have small errors in the intervals where the sensor's ductility is good, and in the intervals where the ductility is poor. large error

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