Biblio

At present, pavement crack detection mainly depends on manual survey and semi-automatic detection. In the process of damage detection, it will inevitably be subject to the subjective influence of inspectors and require a lot of identification time. Therefore, this paper proposes the research and implementation of artificial intelligence real-time recognition method of crack edge based on zynq, which combines edge calculation technology with deep learning, The improved ipd-yolo target detection network is deployed on the zynq zu2cg edge computing development platform. The mobilenetv3 feature extraction network is used to replace the cspdarknet53 feature extraction network in yolov4, and the deep separable convolution is used to replace the conventional convolution. Combined with the advantages of the deep neural network in the cloud and edge computing, the rock fracture detection oriented to the edge computing scene is realized. The experimental results show that the accuracy of the network on the PID data set The recall rate and F1 score have been improved to better meet the requirements of real-time identification of rock fractures.

Contrary to previous opinion, ‘frost shattering’ is not the only major contributor to rock weathering at mid latitudes and high elevations, more specifically along edges of bedrock escarpments. Lightning is also a significant contributor to land surface denudation. We can show this as lightning strikes on outcrops can dramatically alter the magnetic signature of rocks and is one of the main sources of noise in paleomagnetic studies. Igneous rocks in the highlands of Lesotho, southern Africa (\textgreater 3000 m elevation) provide an ideal study location, as flow lavas remain as prominent ridges that are relatively resistant to weathering. It is well known that lightning strikes can cause large remanent magnetization in rocks with little resultant variation in susceptibility. At two adjoining peaks in the Lesotho highlands, mapped freshly fractured rock correlates with areas of high magnetic intensity (remanent component), but little variation in susceptibility (related to the induced field), and is therefore a clear indicator of lightning damage. The majority of these mapped strike sites occur at the edges of topographic highs. Variations in magnetic intensity are correlated with the much lower resolution national lightning strikes dataset. These data confirm that high elevation edges of peak scarps are the focus of previous lightning strikes. This method of magnetic surveying compared with lightning strike data is a new method of confirming the locations of lightning strikes, and reduces the need for intensive paleomagnetic studies of the area to confirm remanence.