Dense fog monitoring method based on wireless microwave attenuation characteristic transfer learning

Abstract

The invention discloses a dense fog monitoring method based on wireless microwave attenuation characteristic transfer learning. Wavelet transformation is carried out on the preprocessed microwave attenuation signal intensity data to obtain a time-frequency diagram; the size of the time-frequency diagram is adjusted; obtaining an adjusted image, inputting the training set into an Alexnet network for training; when the Alexnet network reaches a preset requirement, the Alexnet network is started; determining an Alexnet network model according to the current network parameters of the Alexnet network; the Alexnet network model is used to detect the test set; outputting a network detection result of each adjustment image in the test set; calculating the dense fog liquid water content of each adjustment image in the test set according to the network detection result and a preset inversion formula; the visibility corresponding to each adjustment image in the test set is calculated according tothe liquid water content of each dense fog, so that the monitoring flexibility of dense fog parameters such as visibility can be improved, and the accuracy of the obtained dense fog parameters such as visibility is improved.

Description

technical field [0001] The invention relates to the technical field of meteorological factor monitoring, in particular to a dense fog monitoring method based on transfer learning of wireless microwave attenuation characteristics. Background technique [0002] Dense fog is a meteorological phenomenon that has a great impact on human production and life: on the one hand, dense fog will reduce visibility and have a huge impact on transportation, causing serious loss of life and property; on the other hand, air pollutants and Dense fog combined to form smog can be harmful to flora and fauna. Commonly used dense fog monitoring methods include manual observation, transmissometer, instrument for measuring scattering coefficient and satellite monitoring. Among them, manual observation is to estimate the visibility through the appearance or occlusion of objects at a known distance from the observer's current position, which is greatly affected by human subjectivity, and cannot give ...

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Problems solved by technology

Among them, manual observation is to estimate the visibility through the appearance or occlusion of objects at a known distance from the observer's current position, which is greatly affected by human subjectivity, and cannot give an accurate magnitude of dense fog; the transmissometer measurement calculates the level The average extinction coefficient of the direction is used to estimate the concentration of dense fog: the transmitter emits a modulated magnetic flux of light with a constant average power, and the receiver contains a photodetector to measure the light falling on it. Although this instrument is very accurate, But very expensive; instruments that measure the scattering coefficient of light By concentrating a beam of light on a small volume of air, the proportion of light scattered at sufficiently large angles and in non-critical directions can be determined photometrically

However, this technique only allows the measurement of small sample volumes, so the visibility obtained is poorly representative; satellite monitoring has the advantage of large spatial coverage, however, this technique is difficult to provide accurate ground-based monitoring data, and it is difficult to distinguish observations Whether it is actual fog or cloud

It can be seen that the traditional dense fog monitoring often has limitations, and the accuracy of the corresponding monitoring results is low

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