Scale-space effect and scale hybridization in image intelligent recognition of geological discontinuities on rock slopes

Geological discontinuity(GD)plays a pivotal role in determining the catastrophic mechanical failure of jointed rock masses.Accurate and efficient acquisition of GD networks is essential for characterizing and understanding the progressive damage mechanisms of slopes based on monitoring image data.Inspired by recent advances in computer vision,deep learning(DL)models have been widely utilized for image-based fracture identification.The multi-scale characteristics,image resolution and annotation quality of images will cause a scale-space effect(SSE)that makes features indistinguishable from noise,directly affecting the accuracy.However,this effect has not received adequate attention.Herein,we try to address this gap by collecting slope images at various proportional scales and constructing multi-scale datasets using image processing techniques.Next,we quantify the intensity of feature signals using metrics such as peak signal-to-noise ratio(PSNR)and structural similarity(SSIM).Combining these metrics with the scale-space theory,we investigate the influence of the SSE on the differentiation of multi-scale features and the accuracy of recognition.It is found that augmenting the image's detail capacity does not always yield benefits for vision-based recognition models.In light of these observations,we propose a scale hybridization approach based on the diffusion mechanism of scale-space representation.The results show that scale hybridization strengthens the tolerance of multi-scale feature recognition under complex environmental noise interference and significantly enhances the recognition accuracy of GD.It also facilitates the objective understanding,description and analysis of the rock behavior and stability of slopes from the perspective of image data.

From the new Austrian tunneling method to the geoengineering condition evaluation and dynamic controlling method

The new Austrian tunneling method （NATM） is widely applied in design and construction of underground engineering projects. When the type and distribution of unfavorable geological bodies （UGBs） associated with their influences on geoengineering are complicated or unfortunately are overlooked, we should pay more attentions to internal features of rocks grades IV and V （even in local but mostly controlling zones）. With increasing attentions to the characteristics, mechanism and influences of engineering construction-triggered geohazards, it is crucial to fully understand the disturbance of these geohazards on project construction. A reasonable determination method in construction procedure, i.e. the shape of working face, the type of engineering support and the choice of feasible procedure, should be considered in order to mitigate the construction-triggered geohazards. Due to their high sensitivity to groundwater and in-situ stress, various UGBs exhibit hysteretic nature and failure modes. To give a complete understanding on the internal causes, the emphasis on advanced comprehensive geological forecasting and overall reinforcement treatment is therefore of more practical significance. Compre- hensive evaluation of influential factors, identification of UGB, and measures of discontinuity dynamic controlling comprises the geoengineering condition evaluation and dynamic controlling method. In a case of a cut slope, the variations of UGBs and the impacts of key environmental factors are presented, where more severe construction-triggered geohazards emerged in construction stage than those predicted in design and field investigation stages. As a result, the weight ratios of different influential factors with respect to field investigation, design and construction are obtained.