Barrier dam surface layer particulate matter detection method based on deep learning

Abstract

The invention discloses a barrier dam surface layer particulate matter detection method based on deep learning, which comprises the following steps: acquiring a color image of barrier dam surface layer particulate matter, and establishing a training image data set and a test image data set; preprocessing the training image data set to form a standard training image data set; labeling particulate matters on the surface layer of the barrier dam in the standard training image data set to generate a labeling file set; training the standard training image data set and the annotation file set based on a deep learning algorithm to generate a deep learning model; using a deep learning model to carry out target identification on barrier dam surface layer particulate matters in the test image data set; based on a three-dimensional reconstruction algorithm, carrying out particle size measurement and calculation on the identified target; and evaluating the model by adopting the recognition precision and the particle size measurement and calculation precision. The method provided by the invention is used for automatically detecting particulate matters on the surface layer of the barrier dam, and has the characteristics of simple process, reliable calculation, high identification speed, high accuracy and strong robustness.

Description

technical field [0001] The invention relates to the technical field of emergency rescue of barrier dams, in particular to a method for detecting particulate matter on the surface of barrier dams based on deep learning. Background technique [0002] The barrier dam is a special dam body formed by blocking valleys and rivers and storing water after landslides, collapses, debris flows, volcanic karst flows, and moraines caused by rainfall, earthquakes, volcanoes, and glacier activities. Large, large water storage capacity, and large security threats. The structural characteristics of the barrier dam after formation are the important data basis for stability analysis and emergency rescue. The structure of the barrier dam depends on the material source, the topography of the river valley and the movement and accumulation process. Its material composition generally has the characteristics of uneven distribution of soil and rock, uneven particle size of rocks, and uneven density, ...

AI Technical Summary

Problems solved by technology

The structure of the barrier dam depends on the material source, the topography of the river valley and the movement and accumulation process. Its material composition generally has the characteristics of uneven distribution of soil and rock, uneven particle size and uneven density of rocks, which increases the possibility of effective detection. difficulty

[0003] At present, the detection of particulate matter on the surface of barrier dams is mainly carried out manually, with a low degree of automation and poor timeliness, which is difficult to meet the needs of emergency rescue

Images