An Ultra-Broadband Microwave Humidity Detection Method Based on Machine Learning

Abstract

Microwave detection is non-destructive, fast, and has good portability, but it faces a severe development bottleneck in the detection of humidity range. Most of the existing microwave moisture detection systems use a single frequency point for humidity measurement, and its measurement range is not high, so it is difficult to use in practice. The invention utilizes the principle of microwave attenuation to obtain the microwave scattering signals of the measured objects with different humidity at broadband frequencies by using ultra-wideband antennas, and use them as the humidity regression training sample set of the measured objects, thereby using a supervised machine learning method to establish the measured Humidity regression model. This patent uses a regression machine learning algorithm to model data, and uses cross-validation to obtain optimal training parameters, so that the obtained model is optimized and the regression error is minimized. The invention greatly increases the range of fabric humidity that can be detected, and lays a foundation for the further application of the microwave detection system.

Description

technical field [0001] The invention relates to an ultra-broadband microwave humidity detection method based on machine learning, which is especially suitable for conveniently and quickly judging the moisture content of fabrics under the conditions of no radiation, no damage, and a wide humidity range, and belongs to the technical field of microwave detection. Background technique [0002] At present, the commonly used methods for testing the moisture content of substances at home and abroad include oven method, DC resistance method, capacitance method and infrared method. Although the result of the oven method is accurate, it is troublesome to use in actual work, it is not real-time online, and it is a destructive test; the DC resistance moisture measurement method is because the DC resistance of the measured object is large, and the plate is easy to polarize in the DC electric field, etc. However, there are shortcomings such as poor test stability, large error, and low ver...

AI Technical Summary

Problems solved by technology

The method of detecting the internal moisture content of objects based on microwave signals generally adopts the microwave transmission method, and mainly uses the microwave attenuation of a single frequency point to measure the moisture content of the material. In actual use, the single frequency point is easily disturbed by the outside world, which leads to an increase in the humidity measurement error.

In addition, there is still a problem that the detection range of humidity is very narrow in the microwave detection of material moisture at present.

In short, the current moisture microwave detection technology is facing a severe development bottleneck in the detection range.

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