Types Of Cracks Research Articles

Study on mechanical properties of large deformation segmental cement-based honeycomb structure

Honeycomb structures provide a new means of controlling and supporting the tunnel envelope. However, traditional honeycomb structures have low strength and poor stability, and are prone to stress concentration and instability, further limiting their application in deep tunnel support projects. In this paper, a new type of segmental cementitious honeycomb structure is investigated, its performance under different loading rates is tested, and its application in deep large deformation tunnel support is discussed. Firstly, the honeycomb model was drawn and the honeycomb skeleton was prepared. Then, the cement suspension technique was optimised. Secondly, the effects of different loading rates on the performance of segmented cement-bonded honeycomb structures were investigated by laboratory experiments. The results show that when the loading rate is 3 mm/min, the structure has the maximum load capacity and the best energy absorption performance. It is worth noting that too fast or too slow loading rate will affect the performance of the structure. Finally, the damage mechanism of the segmented honeycomb structure was further investigated by using an acoustic emission system, and the acoustic emission characteristics showed that the segmented cementitious honeycomb structure firstly went through a relatively stable stage of microcrack development under the action of the loads in all bands, and then a large area of damage was observed in the top layer of the honeycomb skeleton when the peak load was reached, resulting in the collapse of the whole layer of the honeycomb structure, which led to the collapse of the whole layer of the honeycomb skeleton. This led to the collapse of the whole layer of the honeycomb structure and a significant decrease in the bearing capacity, which confirmed the layer-by-layer damage characteristics of segmental cementitious honeycomb structures. In addition, the RA-AF values show that the loading rate has little effect on the crack type, which is almost unchanged with the increase of loading rate. These studies verify the feasibility of using honeycomb structure to support roadway with fast deformation speed and large deformation. It is of great significance to guide the application of honeycomb structure in deep roadway support engineering.

Numerical Simulation of Coal’s Mechanical Properties and Fracture Process Under Uniaxial Compression: Dual Effects of Bedding Angle and Loading Rate

In view of the significant influence of bedding structure on the mechanical characteristics and fracture behavior of coal, uniaxial compression discrete element numerical simulation experiments were carried out on coal samples with bedding angles of 0°, 30°, 60°, and 90°, and loading rates of 10−3/s, 10−2/s, 10−1/s, and 100/s, respectively, using PFC 6.0 software. The dual effects of bedding angle and loading rate on the mechanical properties of coal and its damage behavior were analyzed. The results show that (1) as the loading rate increases, the peak strength of the specimen increases, and the damage intensifies. The counts of the three types of cracks increased exponentially, while the crack growth rate was dramatic. (2) With the increase in loading rate, the density of the compressive stress force chain inside the specimen increases and gathers to the two ends, and the density of the tensile stress force chain is basically unchanged but gathers to the middle. The overall strength of the force chain changes according to the law of decreasing and then increasing. (3) With the increase in the bedding angle, the peak strength decreases and then increases, and the curve is approximately “V” shape. When the bedding angle is 60° and 90°, the peak stress is minimum and maximum, respectively. Shear cracks are dominant in the model, and the crack distribution shows a trend of increasing and then decreasing. (4) With the increase in the bedding angle, the density of the compressive stress force chain gradually decreases, and the density of the tensile stress force chain appears to be aggregated. The overall strength of the force chain changes according to the law of decreasing and then increasing.

Crack Detection and Cost Analyzer Using AI

Crack Vision is an innovative AI-powered Android application developed to detect and analyze wall cracks, providing users with real-time, automated repair cost estimates. By leveraging advanced object detection models such as YOLOv7 and Mask R-CNN, Crack Vision enhances both the accuracy and efficiency of crack detection, enabling precise measurement of crack dimensions, severity assessment, and quick identification of structural issues. This application simplifies the inspection and budgeting process for wall repairs, making it an essential tool for homeowners, contractors, and structural engineers who seek to minimize reliance on manual inspection methods. The core functionality of Crack Vision combines high-resolution image processing with state-of-the-art machine learning algorithms, ensuring reliable detection across various wall types and crack textures. Using computer vision and deep learning techniques, the app can differentiate between structural and non-structural cracks, thereby offering a comprehensive solution for repair prioritization. Furthermore, Crack Vision integrates with a robust backend that stores user data, allowing users to track the condition of their walls over time. This feature aids in preventive maintenance by identifying trends in crack expansion and deterioration, potentially mitigating costly repairs. Additionally, the application provides a detailed breakdown of estimated repair costs based on crack size, depth, and type, empowering users to make informed decisions about necessary repairs. Crack Vision is designed with user-friendliness in mind, featuring an intuitive interface that guides users through the inspection process. The app also supports multilingual options and customizable settings to cater to diverse user needs. In sum, Crack Vision redefines wall crack inspection, offering a rapid, accurate, and accessible solution for both casual users and industry professionals, ultimately contributing to improved building safety and maintenance efficiency

Increasing the efficiency of manufacturing products from dolerite of the Severo-Buskunskoye deposit by gluing them with polymer composites

The North Buskun dolerite deposit is located 10 km from Sibai RB. This deposit belongs to highly decorative stones, which is due to the uniformity and saturation of its black color and good polishability. At the same time, the main disadvantage of the North Baksan deposit is the low yield of usable products from mined blocks, which is approximately 35% of the extracted stone. The paper examines the types of cracks on the dolerite and the possibility of gluing them with polyester-based glue. It has been established that sawn blanks do not break through glued small cracks when they are ground and polished on a knee-lever machine. At the same time, frost resistance, color, tonality, uniformity, quality of polishing and stuffing of drawings on glued blanks with small cracks practically did not differ from the indicated quality indicators in areas of dolerite without defects.The restoration of the quality indicators of the dolerite of the North Baksan deposit due to the gluing of small cracks with polymer composites ensured an increase in the yield of usable products from 35 to 85%.

Rock fragmentation of simulated transversely isotropic rocks under static expansive loadings

Rock fragmentation is a critical process for mineral extraction and for mitigating overstressed rock in geotechnical applications. In this study, 3D-printed concrete was used to simulate the stratified rock mass, and experimental and numerical methods were employed to investigate crack propagation under static expansive loadings in transversely isotropic rocks. Two types of cracks were observed in the experiments: P-type (a crack propagates primarily along the weak layer) and T-type (a crack propagates across the weak layers) cracks. The findings revealed that the orientation of layers significantly influenced the initiation and propagation of cracks, with P-type cracks commonly observed in simpler P-P mode fragmentations and more complex P-P-T modes emerging under higher expansive loadings. P-T-T modes were characterized by the simultaneous presence of the T-type crack after an initial P-type crack. The AE energy levels in the P-P-T and P-T-T modes were much higher than those in the P-P mode. 2D-DDA models were further built to understand the effects of the loading scales, layer angles, and locations of weak layers on the cracking sequences. The results provided detailed insights into stress evolutions and the impact of expansive loadings on crack initiation and propagation.

Automatic Method for Detecting Deformation Cracks in Landslides Based on Multidimensional Information Fusion

As cracks are a precursor landslide deformation feature, they can provide forecasting information that is useful for the early identification of landslides and determining motion instability characteristics. However, it is difficult to solve the size effect and noise-filtering problems associated with the currently available automatic crack detection methods under complex conditions using single remote sensing data sources. This article uses multidimensional target scene images obtained by UAV photogrammetry as the data source. Firstly, under the premise of fully considering the multidimensional image characteristics of different crack types, this article accomplishes the initial identification of landslide cracks by using six algorithm models with indicators including the roughness, slope, eigenvalue rate of the point cloud and pixel gradient, gray value, and RGB value of the images. Secondly, the initial extraction results are processed through a morphological repair task using three filtering algorithms (calculating the crack orientation, length, and frequency) to address background noise. Finally, this article proposes a multi-dimensional information fusion method, the Bayesian probability of minimum risk methods, to fuse the identification results derived from different models at the decision level. The results show that the six tested algorithm models can be used to effectively extract landslide cracks, providing Area Under the Curve (AUC) values between 0.6 and 0.85. After the repairing and filtering steps, the proposed method removes complex noise and minimizes the loss of real cracks, thus increasing the accuracy of each model by 7.5–55.3%. Multidimensional data fusion methods solve issues associated with the spatial scale effect during crack identification, and the F-score of the fusion model is 0.901.

Detection of crack on concrete surfaces using image processing techniques

Cracks on the concrete surface are one of the earliest indications of structural disintegration under maintenance; further the continual exposure can cause severe harm to the environment. The manual method of crack detection is time-consuming. Since the manual approach fully depends on the specialist’s data and experience, it lacks perspicacity within quantitative analysis. This study establishes a MATLAB® programme on image process techniques for automatic crack recognition and analyses. An image pre-processing theme combines multiple adaptive filtering and contrast enhancement based on the image that may improve the removal of background noise. Then, for removing isolated noise spots, it tends to develop a local adaptive threshold segmentation formula combined with an image morphological operator. The goal of this Gray intensity adjustment methodology is to improve the accuracy of the crack detection results. Furthermore, the results show that the target crack is identified on the concrete surface, additionally classified as its crack type and its properties are extracted.

Partially insulated cracks in orthotropic materials under steady state thermo-mechanical loadings

An attempt has been made to investigate the cracked composite medium with thermally conducting multiple cracks at its interface of the dissimilar orthotropic media subjected to thermal and mechanical loadings. The present article examines the governing equations, the associated differential constraints and boundary conditions those govern the temperature field and stress field. Fourier integral transforms, together with their corresponding inverses, have been employed to convert the singular integral equations into a set of linear equations by using the concept of orthogonality and completeness. The numerical technique, namely the Schmidt method, which employs a polynomial expansion of the unknown functions, is used to solve algebraic equations to determine the desired temperature and stress fields. The semi-analytical findings of the expressions for heat flux intensity factor (HFIF), stress intensity factor (SIF), and crack displacements have been mentioned in the article. Both mode-I and II types of cracks have been studied to investigate the effect of thermal conductivity. Detailed graphical representations effectively illustrate the numerical results and the interrelations between crack lengths, bonded strip width, and the partial conductivity coefficient of the crack surface. As the thermal conductivity coefficient increases, the temperature difference tends to zero. The results reveal that an increase in thermal conductivity decreases the SIFs.

Automated Surface Crack Identification of Reinforced Concrete Members Using an Improved YOLOv4-Tiny-Based Crack Detection Model

In recent times, the deployment of advanced structural health monitoring techniques has increased due to the aging infrastructural elements. This paper employed an enhanced You Only Look Once (YOLO) v4-tiny algorithm, based on the Crack Detection Model (CDM), to accurately identify and classify crack types in reinforced concrete (RC) members. YOLOv4-tiny is faster and more efficient than its predecessors, offering real-time detection with reduced computational complexity. Despite its smaller size, it maintains competitive accuracy, making it ideal for applications requiring high-speed processing on resource-limited devices. First, an extensive experimental program was conducted by testing full-scale RC members under different shear span (a) to depth ratios to achieve flexural and shear dominant failure modes. The digital images captured from the failure of RC beams were analyzed using the CDM of the YOLOv4-tiny algorithm. Results reveal the accurate identification of cracks formed along the depth of the beam at different stages of loading. Moreover, the confidence score attained for all the test samples was more than 95%, which indicates the accuracy of the developed model in capturing the types of cracks in the RC beam. The outcomes of the proposed work encourage the use of a developed CDM algorithm in real-time crack detection analysis of critical infrastructural elements.

Corrosion effects on flexural behaviour of EPS sandwich concrete panels: a study using acoustic emission technique

The experimental research utilized expanded polystyrene (EPS) panels sized at 1300 × 600 × 130 mm (length × width × thickness) and induced with corrosion via an impressed current method. Varied extents of corrosion were applied for 120, 240, 360, and 480 h, resulting in mass loss percentages of 6.67%, 8.41%, 10.76%, and 18.13% of reinforcement in different panels. The flexural testing along with acoustic emission (AE) monitoring were performed for evaluation of EPS panels. Results obtained defend the correlation of AE energy with the load energy in the EPS panels. The AE parameters of rise angle and average frequency assist in distinguishing between tensile and shear crack types. The energy released during tensile crack formation in EPS panels is minimal compared to that during shear crack formation. These findings are a basis for further AE investigations into EPS panels and developing AE sensor-based methods for identifying corrosion-induced degradation in EPS panels within structures.

Investigating crack evolution, and failure precursor warning in sandstones with different water contents from the perspective of tensile-shear crack separation

To investigate the effect of water on the crack evolution and damage mode of sandstone, uniaxial compression experiments were conducted using samples with different water contents. The damage evolution process of sandstones with different water contents was investigated based on acoustic emission (AE) and digital image correlation (DIC) techniques. Further, the crack evolution was conducted using the RA-AF distribution method. The results showed that the brittleness of sandstone weakened with increasing water content, and the uniaxial compressive strength (UCS) and elastic modulus decreased significantly. The percentage of shear cracks increased continuously from 21.1% when dry to 36.53% when saturated and the evolution of these cracks through AE signals correlates closely with DIC observations. However, the influence of water on the development of these cracks differs significantly. Through the separation analysis of the two types of cracks, the damage evolution law of sandstone is clearer. Based on the critical slowing down theory (CSDT), the point at which both tensile and shear crack signals undergo abrupt fluctuation serves as an early warning indicator. The early warning point identification results of the sandstone with different water contents are all in the crack extension stage, the stress levels are all near 0.9 and demonstrate reliable predictive capabilities. Furthermore, the mechanism of water’s impact on the transition of crack types and the differences in damage modes in sandstone during the initial and later loading stages is explained by analyzing the characteristics of tensile and shear crack emergence and expansion.

A comprehensive study of the effect of scanning strategy on IN939 fabricated by powder bed fusion-laser beam

This study provides a comprehensive investigation into the effects of different scanning strategies on the material properties of IN939 fabricated using the PBF-LB process. The scanning strategies examined included alternating bi-directional scanning with rotation angles of 0°, 45°, 67°, and 90° between adjacent layers (named as shown), as well as alternating chessboard scanning with rotation angles of 67° and 90° (named as Q67° and Q90°). The results revealed that the 45° and 67° samples had the highest relative density, while the 0° and Q67° samples showed the highest average porosity. Moreover, various types of cracks, including solidification, solid-state, and oxide-induced cracks, were observed. Among the bi-directional scan samples, the 0° sample displayed the most extensive cracking and the highest σmax residual stress values in both XZ and XY planes. Conversely, the 45° and 67° samples exhibited fewer cracks. Notably, the lowest σmax residual stress in the XZ planes among the bi-directional scan samples was observed in the 67° sample. Additionally, microstructural analyses indicated differences in grain size and morphology, among the samples. Texture analysis indicated that the 0° and 90° samples exhibited strong cube textures, whereas the texture intensity weakened for the 45° and 67° samples. Moreover, the alternating chessboard scanning strategy led to rougher surfaces (higher Sa and Sz values) compared to the alternating bi-directional scanning strategy, regardless of the rotation angles. Furthermore, the microhardness values among the samples showed minimal variance, ranging between 321 ± 14 HV and 356± 7 HV.

Crack coalescence and failure behaviors in slate specimens containing a circular cavity and a pre-existing flaw pair under uniaxial compression

The flaws (fractures) widely existing in rock mass pose a threat on the stability of many underground cavities. This study aims at investigating the failure process of a cavity affected by adjacent flaws. A number of slate specimens containing a circular cavity and a pre-existing flaw pair were tested under uniaxial compression. Varied flaw configurations were obtained by changing the flaw inclination angle with respect to horizontal and the spacing between flaw pair and cavity. Three main types of cracks emanated from the pre-existing flaw tips, and played a dominant role in the failure process of cavity, comprising primary wing cracks (tensile cracks) and two types of secondary cracks (quasi-coplanar shear cracks and oblique shear cracks). The initiation and propagation of these cracks were highly dependent on the flaw pair configurations. When the pre-existing flaw pairs were non-parallel to the loading direction, (1) mostly, coalescence occurred both in the tensile and compressive stress concentration regions around cavity; (2) in most cases, the quasi-coplanar and oblique shear cracks were the predominant cracks leading to the coalescence between the compressive stress concentration regions of cavity and the pre-existing flaw pair tips. When the pre-existing flaws were parallel to the loading direction, the combination of inclined shear cracks and tensile cracks or inclined shear cracks only dominated the failure of cavity. The initiation angles of wing cracks, quasi-coplanar shear cracks and oblique shear cracks agreed well with the theoretical predictions by the maximum tangential strain criterion (MTSN), Mohr-Coulomb criterion (M−C) and maximum shear stress criterion (MSS), respectively.

A deformability-based mechanical model for predicting shear strength of FRP-strengthened RC beams failed in concrete cover separation

Concrete cover separation (CCS) is frequently happened prior to the yielding of steel stirrups in FRP-strengthened RC beams. However, the debonding mechanism and criterion have not been fully understood. In this study, the typical crack types associated with CCS are comprehensively summarized and investigated in terms of profiles and kinematics of crack. The dowel action and dowelling cracks are proved to be the dominant factors causing CCS. Based on the cracking features, the simplified local debonding strength and average shear strength of fracture interface, which constitutes the contribution of concrete to shear capacity of strengthened RC beams, are analytically derived and verified against the available experiments and code provisions. Through regression analysis of 179 collected shear tests, a formulation based on the Critical Shear Crack Theory (CSCT) is presented to assess the deformability of strengthened RC beams governed by CCS. The commonly overlooked actual stress level in steel stirrups is considered as a function of the rotation capacity of beams and assessed based on the Modified Compression Field Theory (MCFT). Validation of this analytical approach, involving comparison against the empirical models and experimental results from 107 specimens, confirms its superior effectiveness and consistency in predicting CCS and shear strength.

Acoustic assessment of pavement structural health

Determining the in-situ asset condition of a pavement is necessary to programme pavement renewal and life extension work. Concrete pavements can develop different forms of structural faults including variable types of cracking, spalling, slab rocking, corrosion of reinforcement and softening of subgrade. This paper reports on work designed to detect deterioration before it manifests at the surface, in the form of defects that would only then have been picked up through visual inspection. The approach involves non-destructive, real-time monitoring with a Close Proximity (CPX) trailer, utilising both microphones and a tri-axial accelerometer. Dependent on its condition, the concrete pavement and subgrade will respond differently to traffic induced acoustic noise and vibration from the tyres. The variability in response is analysed using specialist spectral and acoustic signal processing techniques, to detect any internal and external cracks in the pavement, as well as to assess the condition of the subgrade. By characterising the pavement into uncracked, lightly cracked and heavily cracked areas, the collected data is used to map crack locations and their severity. Repeated surveys will allow temporal changes to be monitored and its rate of decay to be predicted, enabling the scheduling of renewal and life extension to be optimised.

A fatigue crack prediction method based on inductive semi-supervised learning and Lamb-wave monitoring for orthotropic steel bridge deck

Orthotropic steel bridge deck suffers from fatigue cracking due to its orthotropic configuration and cyclic vehicular load. Hence, fatigue crack monitoring and prediction are crucial for addressing this issue. The Lamb-wave technique has potential in monitoring the growth of fatigue cracks, whereas most of the existing signal processing methods show poor performance in the crack prediction. To improve the accuracy and reliability of fatigue crack prediction, an inductive semi-supervised learning (ISL) approach is proposed in conjunction with Lamb-wave monitoring. The presented method is first verified by conducting a fatigue test of orthotropic steel bridge deck loading by three load conditions which would lead to different types of cracks, where lightweight Lamb-wave monitoring devices were adopted. The approach was further applied in field monitoring to validate its effectiveness in real engineering structures. The results demonstrate that the proposed method can recognize the initiation of fatigue cracks by giving a predicted time interval in which the real initiation moment locates. Similar increasing trends are found between the predicted and real crack lengths during the growth of cracks, while a relative fluctuate is existing in the predicted results, and the prediction accuracy of crack lengths can be regarded as 2 mm. For bridge field monitoring, the real fatigue crack length was also well predicted by the proposed method, exhibiting an average error of 0.82 mm in comparison with the real values. In general, the research findings emphasize the adaptability of the proposed method for fatigue crack prediction in practical engineering.

Experimental study on mechanical and acoustic emission characteristics of red sandstone containing combined flaws of hole-fissure under biaxial compression

To investigate the mechanical behaviour and failure mechanism of flawed rock masses under biaxial stress conditions, a series of biaxial compression experiments are conducted on red sandstone specimens containing combined flaws of the circular hole and perforated symmetric fissure combined with acoustic emission (AE) technology in this work. The results show a close association between the stress-strain curve morphology and confining stress, both the biaxial compression strength and elastic modulus exhibit an upward trend with increasing fissure angle and confining stress. The maximum AE energy and cumulative AE energy both increase with higher confining stress. The crack types in the specimens are identified by analyzing the AF/RA value distribution, revealing a gradual decrease in the percentage of tensile cracks with increasing fissure angle. An AE localization algorithm based on the least absolute value method is applied to pinpoint AE events during biaxial compression, and AE events distribution is analyzed through the Kernel density estimation (KDE). The crack extension behaviour is described based on the movement of the maximum kernel density points, which initially exhibits a progression from both ends of the specimen towards the central region and subsequently from the central fissure tip towards the two ends.

Entropy Stacked Autoencoder based Diffusion Model (ESADM) and Fuzzy Clustering with Semi Supervised Fuzzy Graph Convolutional Network (FC-SSFGCN) for Rail Surface Defect Detection

Rails, fasteners, and other parts of railway track lines eventually develop flaws due to continuous strain from train operations and direct exposure to the environment; these faults directly affect the safety of train operations. Detecting defects on rail surfaces presents a formidable challenge due to the wide array of possible flaws and their unpredictable nature. However, Defect identification errors, massive variances, inadequate training sample availability, and weak contrast between faults and the surrounding background all contribute to the complexity of this procedure. In this work, rail surface and fastener flaws may be detected non-destructively using a multi-crack detection approach based on the Entropy Stacked Autoencoder Diffusion Model (ESADM). A novel approach, ESAFM, has been developed, combining a rail surface image encoder with a multi-layer, Stacked Autoencoder to extract latent materials from images showcasing different types of cracks. This integration reduces the need for significant processing resources by integrating easily into the conventional physically-based image workflow. Additionally, the Zero Shot-Semi Supervised Fuzzy Class Knowledge Graph (ZS-SSFCKG) method proposes Class Knowledge Graph Construction (CKGC), which constructs a CKG to elucidate the connection between defects and non-defects. Class features are learned by using a Fuzzy Clustering with Semi Supervised Fuzzy Graph Convolutional Network (FC-SSFGCN). The method employs a transformer encoder to capture distant relationships, allowing for the extraction of features from defect samples. This facilitates the acquisition of distinct defect image characteristics, as industrial defects vary in shape and size. The experimental results on the public Railway Track Fault Detection (RTFD)and Rail Surface Defect Datasets (RSDDs) with rail surface defects are collected from rail tracks surface defect detection.

Simulation and Experimental Research of V-Crack Testing of Rail Surfaces Based on Laser Ultrasound

Rail surface cracks are widespread damage that can lead to uneven surfaces of railheads and affect traveling safety. Non-destructive testing is needed to inspect rails regularly to ensure the normal operation of railroads. This paper proposes a laser ultrasonic testing method combining variational mode decomposition and diffractive Rayleigh wave time-of-flight to detect tiny cracks on the rail surface quantitatively. The finite element method was combined with experiments to simulate and experimentally investigate cracks of different sizes numerically. In the numerical simulation, the location of the crack was determined by B-scan. Afterward, the interaction between various types of ultrasound and cracks was comparatively analyzed, and the crack size was quantitatively characterized using useful information from the ultrasound signals. The results show that the time-of-flight method can detect arbitrary cracks with low error. Therefore, the experimentally acquired ultrasound signals used the time difference between the diffracted Rayleigh wave and other ultrasound waves to detect the crack information quantitatively. The variational mode decomposition method was used to separate the ultrasonic signals and extract the best surface wave modes to improve the signal-to-noise ratio. The results show that the combination of variational mode decomposition and time-of-flight method can effectively detect the size of cracks.

Experimental Study on Acoustic Emission Features and Energy Dissipation Properties during Rock Shear-Slip Process.

The features of rock shear-slip fracturing are closely related to the stability of rock mass engineering. Granite, white sandstone, red sandstone, and yellow sandstone specimens were selected in this study. The loading phase of "shear failure > slow slip > fast slip" was set up to explore the correlation between fracture type, acoustic emission (AE) features, and energy dissipation during the rock fracturing process. The results show that there is a strong correlation between fracture type, energy dissipation, and AE features. The energy dissipation ratio of tension-shear (T-S) composite, shear, and tensile types is 10:100:1. The fracture types in the shear failure phase are mainly tensile and TS composite types. The differential mechanism of energy dissipation of different rocks during the shear-slip process is revealed from the physical property perspectives of mineral composition, particle size, and diagenetic mode. These results provide a necessary research basis for energy dissipation research in rock failure and offer an important scientific foundation for analyzing the fracture propagation problem in the shear-slip process. They also provide a research basis for further understanding the acoustic emission characteristics and crack type evolution during rock shear and slip processes, which helps to better understand the shear failure mechanism of natural joints and provides a reference for the identification of precursors of shear disasters in geotechnical engineering.