Exploration method and system using drilling machine impactor excitation wave as excitation signal

Abstract

The exploration method using the excitation wave of the drilling machine impactor as the excitation signal comprises the following steps: acquiring mechanical data of a drilling machine in a drilling process; based on the mechanical data, the state of the surrounding rock is judged, and if exploration conditions are met, excitation wave signals generated by a drilling machine impactor and a vibration signal sequence which is propagated, refracted and reflected by the excitation wave signals through the stratum are collected; based on the excitation wave signal and the vibration signal sequence, advanced geological forecast is formed; and correcting and updating the advanced geological forecast based on the surrounding rock state. The method has the advantages that the accuracy and reliability of advanced geological forecast of tunnel construction can be remarkably improved, interference of personal errors can be effectively avoided, and meanwhile negative effects on the construction progress and potential safety risks are reduced.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration technology, and in particular to an exploration method and system using a drilling rig impactor excitation wave as an excitation signal. Background Art

[0002] (1) Advanced geological prediction technology During the preparatory phase of tunnel excavation, comprehensive and in-depth exploration of the geological conditions along the route is the cornerstone for ensuring smooth construction. This process requires not only a detailed understanding of the properties of the soil and rock strata, as well as their water content (including the dynamic changes in water volume and pressure), but also the precise identification of potential geological hazards such as cavities, fracture zones, faults, silt, and quicksand. Failure to fully explore these complex geological conditions before construction can lead to a series of serious safety incidents, ranging from impeding excavation progress to causing damage to machinery, casualties, and even the collapse of the entire tunnel project. Therefore, pre-excavation geological exploration, or advanced geological prediction, is crucial for the safe and smooth progress of tunnel construction.

[0003] Currently, the technical framework for advanced geological prediction primarily includes geological surveys, advanced drilling, advanced pilot pit prediction, and physical exploration. Geological surveys, as a preliminary exploration method, include supplementary surveys of the tunnel surface, geological sketches of the tunnel face and tunnel body, surface-subsurface correlation analysis of stratigraphic boundaries and structural lines, and geological mapping. These methods can provide a preliminary overview of the geology along the tunnel route, providing foundational data for subsequent exploration. However, geological surveys rely heavily on the experience and judgment of geological engineers. While not requiring expensive equipment, the risk of human error is significant.

[0004] Advance drilling, with its advantage of directly obtaining core samples, has become an effective means of revealing key information such as stratum lithology, structure, and interfaces. Combined with auxiliary techniques such as formation testing and rock physics testing, it can provide in-depth analysis of the engineering properties and geostress state of the strata, providing a scientific basis for tunnel construction. While drilling can directly obtain stratum information, the drilling process can affect construction progress and safety, and the limited number of drilling points makes it difficult to fully reflect the complexity of geological conditions.

[0005] The advanced pilot pit prediction method uses actual pilot pit excavation to visually observe and predict the geological conditions ahead. While this method is straightforward, it can impact construction progress and safety, especially as geological hazards may be encountered during pilot pit excavation, posing a threat to construction safety.

[0006] Physical prospecting, a class of techniques that utilize physical principles for advanced geological forecasting, includes elastic wave reflection, electromagnetic wave reflection, transient electromagnetic, high-resolution direct current, and infrared detection. Compared to core drilling, geophysical methods have relatively lower reliability and resolution. Because the physical properties of geological bodies are susceptible to multiple factors, and different geological bodies may have similar physical properties, the geological interpretation of geophysical data is subject to multiple interpretations. Furthermore, the complex and variable geological conditions limit the applicability and accuracy of geophysical methods. High-precision geophysical equipment is expensive and complex to operate, requiring a high level of technical expertise. Furthermore, geophysical methods have limited detection depth and range. For example, while seismic exploration can detect deeper underground structures, it has low resolution for shallower geological bodies. Electrical exploration can be affected by shielding from high-resistance layers, limiting its detection depth. Furthermore, geophysical methods often struggle to capture small geological anomalies or phenomena.

[0007] (2) Drilling rig As a heavy mechanical equipment, drilling rigs are mainly used to drive drilling tools into the ground to obtain physical geological data, such as rock cores, ore cores, rock cuttings, gas samples, liquid samples, etc. These data are crucial for exploring underground geology and mineral resources. Drilling rigs are widely used in geological exploration, mining, civil engineering and tunnel engineering. Figure 4As shown, the drilling rig 1 mainly includes a drill arm 10, a power head 11, a drive motor 12, a drill rod 13, an impactor 14 and a drill bit 15. The power head 11 includes a motor, a reducer, a clutch, a cutter head and a bearing component. Under the action of the reducer, the power is transmitted to the cutter head to achieve cutting and excavation of the working material. During the drilling operation, the power head is responsible for driving the drill rod and the drill bit to rotate and feed. The drive motor 12 provides a powerful power source for the drilling rig, and its performance directly affects the operating efficiency and stability of the drilling rig. Through a precise control system, the drive motor can adjust the output torque and speed according to different operating requirements, thereby optimizing the drilling process. The drill rod 13 serves as a bridge connecting the power head and the drill bit, and its rigidity and wear resistance are crucial. The drill rod needs to withstand the rotational force and feed force from the power head and transmit these forces to the drill bit. At the same time, it also needs to resist the reaction force of the rock formation or working material on the drill bit. The drill arm 10 includes components such as a support bracket, a thruster, and a rock drill. It uses multiple oil cylinders to achieve vertical and horizontal swing angles, and is used to support and control the rock drill during rock drilling operations, ensuring the precise positioning and drilling direction of the drill bit. The length and swing angle of the drill arm determine the range and flexibility of the rock drilling operation. The drill bit acts directly on the rock formation or the surface of the work material, breaking the rock formation or cutting the material through rotation and impact motion. The shape and material of the drill bit 15 are selected according to its use to ensure efficient and accurate drilling operations. The impactor 14 includes an internal impact mechanism and transmission components, which are used to generate high-frequency mechanical impacts, transmit shock waves to the drill rod and drill bit, and improve drilling speed and efficiency. The impactor is particularly suitable for drilling operations in hard rock formations and complex geological conditions. Summary of the Invention

[0008] In response to the numerous challenges faced by existing technologies in the field of advanced geological prediction, such as the human error problem of geological survey methods due to their reliance on manual experience, the difficulty of advanced drilling methods in fully and accurately revealing the complexity of geological conditions due to technical limitations, the potential delays in construction progress and increased safety risks caused by advanced pilot pit prediction methods, and the inability of physical exploration methods to detect deeper underground structures but to provide sufficient resolution for shallow geological bodies. The present invention proposes a method that utilizes the seismic and conductive properties of the drilling rig itself to combine the mechanical data generated by the drilling rig during the drilling operation with the excitation wave signals excited by the impactor during the drilling process, as well as the vibration signal sequences formed by the propagation, refraction, and reflection of these excitation wave signals as they pass through different strata, to identify geological anomalies or potential risks that may be encountered ahead of tunnel construction. Compared with traditional advanced geological prediction technologies, the method proposed in this invention has significant advantages. It can not only significantly improve the accuracy and reliability of advanced geological prediction for tunnel construction, but also effectively avoid the interference of human errors, while reducing the negative impact on construction progress and potential safety risks. In addition, this method can more comprehensively reflect the complexity of geological conditions and provide more accurate geological information support for tunnel construction.

[0009] The exploration method disclosed in the present invention using the drilling rig impactor excitation wave as an excitation signal at least includes: Obtain mechanical data of the drilling rig during the drilling process; Based on the mechanical data, the surrounding rock state and the drill bit state are judged. If the exploration conditions are met, the excitation wave signal generated by the drilling rig impactor and the vibration signal sequence resulting from the propagation, refraction and reflection of the excitation wave signal through the formation are collected. forming an advanced geological prediction based on the excitation wave signal and the vibration signal sequence; Based on the surrounding rock state, the advanced geological forecast is corrected and updated.

[0010] In a preferred embodiment, the mechanical data includes the drilling depth L d , propulsion force F of power head p , drill pipe torque T, water pressure P and drilling speed v.

[0011] In a preferred embodiment, judging the state of the surrounding rock and the state of the drill bit based on the mechanical data specifically includes the following steps: Obtain the friction coefficient f between different types of surrounding rock and steel; Get the drilling rig parameters, including the weight of the drill rod per unit length G L , maximum thrust F pmax , Maximum drilling speed V max ; By the friction coefficient f, the weight per unit length of the drill pipe G L and drilling depth L d Calculate the torque parameter range corresponding to different types of surrounding rock; By the maximum propulsion force F pmax Calculate the propulsion force parameter range corresponding to different types of surrounding rock; By the maximum drilling speed V max Calculate the drilling speed parameter range corresponding to different types of surrounding rock; If the drill pipe torque T and power head propulsion force F during the drilling process p and the drilling speed v are all within the torque parameter range, propulsion force parameter range, and drilling speed parameter range corresponding to the same surrounding rock type, then the current surrounding rock state is judged to be the corresponding surrounding rock type; The torque parameter range, the propulsion force parameter range, and the drilling speed parameter range form standard rock breaking data; Based on the surrounding rock type, the drill rod torque T and the power head thrust F of the drilling rig during the drilling process are calculated. p The drilling speed v is compared with the standard rock breaking data to judge the drill bit status.

[0012] In a preferred embodiment, judging the state of the surrounding rock and the state of the drill bit based on the mechanical data further includes the following steps: If the drilling speed v of the drilling rig is between 90%×Vmax~Vmax during the drilling process, the drilling rig propulsion force F p The state is judged, if F p If the value is less than 10%×Fpmax, the state of the water pressure P is judged. If the amplitude of the water pressure P decreases, it is judged that the drill bit has entered a cavity and an alarm is sent.

[0013] In a preferred embodiment, the torque parameter ranges corresponding to different types of surrounding rock are specifically calculated using the following method: ; Among them, f is the friction coefficient between different types of surrounding rock and steel, G L is the weight per unit length of drill pipe, L d is the drilling depth of the drill, a1 is the maximum torque threshold corresponding to different types of surrounding rock, and a2 is the minimum torque threshold corresponding to different types of surrounding rock; the torque parameter range is T min ~T max .

[0014] In a preferred embodiment, the drilling speed parameter range is specifically achieved by the following calculation method: ; Among them, V max is the maximum drilling speed of the drilling rig, b1 is the maximum drilling speed threshold corresponding to different types of surrounding rock, and b2 is the minimum drilling speed threshold corresponding to different types of surrounding rock; the drilling speed parameter range is v min ~v max .

[0015] In a preferred embodiment, the propulsion force parameter range is specifically achieved by the following calculation method: ; Among them, F pmax is the maximum thrust of the drilling rig, c1 is the maximum thrust threshold corresponding to different types of surrounding rock, c2 is the minimum thrust threshold corresponding to different types of surrounding rock, and the thrust parameter range is F min ~F max .

[0016] In a preferred embodiment, the surrounding rock state includes silt, soil and rock, and the friction coefficient f includes the friction coefficient f between silt and steel. m , the friction coefficient between soil and steel f s , and the friction coefficient f between rock and steel r .

[0017] In a preferred embodiment, the maximum torque threshold a1, minimum torque threshold a2, maximum drilling speed threshold b1, minimum drilling speed threshold b2, maximum propulsion force threshold c1, and minimum propulsion force threshold c2 corresponding to the different types of surrounding rock are predicted by the constructed regression model, which is specifically achieved by the following method: Collect a large amount of surrounding rock state data in actual projects such as geological exploration and tunnel excavation to build a data set; Constructing a regression model to learn the relationship between different surrounding rock characteristics and thresholds based on the data set; Through the trained regression model, the parameters of the maximum torque threshold a1, minimum torque threshold a2, maximum drilling speed threshold b1, minimum drilling speed threshold b2, maximum propulsion force threshold c1 and minimum propulsion force threshold c2 corresponding to different surrounding rock types are predicted.

[0018] In a preferred embodiment, the maximum torque threshold a1 corresponding to the sludge is set to 1.2, the minimum torque threshold a2 is set to 0.8, the maximum drilling speed threshold b1 is set to 1, the minimum drilling speed threshold b2 is set to 0.8, the maximum propulsion force threshold c1 is set to 0.6, and the minimum propulsion force threshold c2 is set to 0; The maximum torque threshold value a1 corresponding to the soil is set to 1.2, the minimum torque threshold value a2 is set to 0.8, the maximum drilling speed threshold value b1 is set to 1, the minimum drilling speed threshold value b2 is set to 0.6, the maximum thrust force threshold value c1 is set to 0.6, and the minimum thrust force threshold value c2 is set to 0; The maximum torque threshold value a1 corresponding to the rock is set to 1.2, the minimum torque threshold value a2 is set to 0.8, the maximum drilling speed threshold value b1 is set to 0.5, the minimum drilling speed threshold value b2 is set to 0.1, the maximum thrust force threshold value c1 is set to 1, and the minimum thrust force threshold value c2 is set to 0.6.

[0019] In a preferred embodiment, the surrounding rock state is soil or rock, and the drill bit state meets the standard rock breaking data, thereby meeting the exploration condition; and the excitation wave signal generated by the drill hammer has a specific waveform or pulse sequence after being coded.

[0020] The application also provides an exploration system using the excitation wave generated by the drill hammer as an excitation signal, which implements the exploration method using the excitation wave generated by the drill hammer as an excitation signal according to any one of the above, and at least includes: A data acquisition module, which is used to acquire mechanical data of the drill during drilling, and to acquire the excitation wave signal generated by the drill hammer and the vibration signal sequence propagated, refracted and reflected by the excitation wave signal through the stratum; A data judgment module, which is used to judge the surrounding rock state based on the mechanical data, to generate a geological forecast in advance based on the excitation wave signal and the vibration signal sequence, and to correct and update the geological forecast in advance based on the surrounding rock state.

[0021] In a preferred embodiment, the data acquisition module includes at least one drilling depth measuring device installed on the drill boom to measure the drilling depth, at least one thrust force sensor installed between the drill boom and the power head to measure the thrust force of the power head or a pressure sensor used to detect the driving hydraulic pressure of the power head, at least one torque sensor installed on the drill driving motor to measure the torque of the drill rod or a pressure sensor used to detect the driving hydraulic pressure of the power head, and at least one pressure sensor installed on the waterway of the drill to measure the water pressure.

[0022] In a preferred embodiment, the data acquisition module further includes at least one acoustic vibration sensor used to acquire the excitation wave signal generated by the drill hammer, and a plurality of high-sensitivity vibration acoustic sensors used to acquire the vibration signal sequence propagated, refracted and reflected by the excitation wave signal through the stratum; The acoustic vibration sensor is installed on the drill hammer or the drill rod or a drill component connected with the drill hammer and the drill rod; The high-sensitivity vibration acoustic wave sensor is arranged on the tunnel wall.

[0023] In a preferred embodiment, the high-sensitivity vibration acoustic wave sensors are evenly distributed on the tunnel wall along the circumferential direction, with a number of 5 to 9.

[0024] Compared with the prior art, the exploration method and system disclosed in the present invention that utilizes the drilling rig impactor excitation wave as the excitation signal have the following beneficial effects: (1) The present invention discloses an exploration method using the excitation wave of the drill impactor as an excitation signal, and uses the excitation wave generated by the drill impactor as an excitation signal. During the drilling process, the mechanical data of the interaction between the drill and the formation are obtained in real time, and these data provide a solid foundation for in-depth analysis of the formation characteristics and subsequent judgment. Through a detailed analysis of the mechanical data, the state of the surrounding rock can be accurately judged. If the state of the surrounding rock meets the exploration requirements, the excitation wave signal generated by the drill impactor is collected, and the propagation, refraction and reflection process of the excitation wave signal in the formation is collected to form a vibration signal sequence. This step not only ensures the validity and accuracy of the collected signal, but also provides a more comprehensive and reliable information basis for advanced geological prediction through the organic combination of mechanical data and excitation wave signals. This multi-source information fusion strategy greatly enhances the reliability of the prediction and effectively reduces the risk of prediction errors caused by errors in a single information source. It can provide a deeper insight into the geological characteristics of the formation, thereby reducing uncertainty when facing geological complexity and significantly improving the accuracy of advanced geological prediction. In addition, the advanced geological forecast is dynamically revised and updated based on real-time changes in the surrounding rock conditions. This approach ensures that the forecast results closely match actual conditions, providing timely and accurate guidance for tunnel construction. This not only improves construction efficiency but also significantly enhances construction safety, effectively reducing delays and risks that may be caused by geological uncertainties. This method relies entirely on the seismic and electrical conductivity characteristics of the drilling rig itself for advanced geological forecasting, eliminating the need for additional exploration equipment and personnel. This feature significantly reduces exploration costs, improves overall economic benefits, and provides a more economical and efficient exploration solution for engineering fields such as tunnel construction.

[0025] (2) The maximum torque threshold a1, the minimum torque threshold a2, the maximum drilling speed threshold b1, the minimum drilling speed threshold b2, the maximum thrust force threshold c1, and the minimum thrust force threshold c2 corresponding to different types of surrounding rock are predicted by the regression model. By collecting a large amount of surrounding rock state data in actual engineering, a rich data set is constructed, and the regression model can learn the complex relationship between different surrounding rock characteristics and mechanical parameter thresholds. This enables the model to give highly accurate results when predicting the mechanical parameter thresholds corresponding to a specific surrounding rock type, providing a reliable basis for engineering decisions. The regression model learns the common rules of surrounding rock characteristics during the training process, so even if it faces new, unseen surrounding rock types, the model can make relatively accurate predictions based on the existing knowledge base (stratum geotechnical data and typical surrounding rock characteristics). This generalization ability enables the method to maintain high prediction accuracy under different geological conditions and different engineering backgrounds. Compared with traditional experimental testing or empirical estimation methods, using a regression model to predict mechanical parameter thresholds can greatly save time and cost. Model prediction does not require expensive field testing and does not rely on the personal experience of engineers, thereby reducing the overall cost of exploration and excavation. With the continuous accumulation of new data, the regression model can be continuously updated and optimized to improve the accuracy and generalization ability of the prediction. This flexibility enables the method to adapt to changing engineering environments and geological conditions. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 FIG. 1 is a schematic diagram of the principle of embodiment one of the exploration method of the present application using the drill impactor excitation wave as the excitation signal; Figure 2 FIG. 2 is a flowchart of embodiment one of the exploration method of the present application using the drill impactor excitation wave as the excitation signal; Figure 3 FIG. 3 is a schematic diagram of the installation of a high-sensitivity vibration acoustic sensor of embodiment two of the exploration system of the present application using the drill impactor excitation wave as the excitation signal; Figure 4 FIG. 4 is a schematic diagram of the structure of the prior art drill.

[0027] BRIEF DESCRIPTION OF DRAWINGS 1 - drill; 10 - drill boom; 11 - power head; 12 - drive motor; 13 - drill pipe; 14 - impactor; 15 - drill bit. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0029] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein in the specification of this application are intended only to describe specific embodiments and are not intended to limit this application. The term "or / and" as used herein includes any and all combinations of one or more of the associated listed items.

[0031] In addition, in the present invention, descriptions such as "first" and "second" are only used for descriptive purposes and do not specifically refer to the order or sequence, nor are they used to limit the present invention. They are only used to distinguish components or operations described with the same technical terms, and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0032] Example 1

[0033] The exploration method of this embodiment uses the drilling rig impactor excitation wave as the excitation signal, such as Figure 1 and Figure 2 Shown, including: Step S1, obtaining mechanical data of the drilling rig during the drilling process.

[0034] During the drilling process, the mechanical data of the interaction between the drilling rig and the formation are obtained in real time. These data provide a solid foundation for in-depth analysis of formation characteristics and subsequent judgment. In this embodiment, the mechanical data include the drilling depth L d , propulsion force F of power head p , drill pipe torque T, water pressure P and drilling speed v.

[0035] Among them, the hole depth L dThis refers to the depth of the formation from the starting point of the borehole to the current drilling position. It directly reflects the depth of the drilling operation and the degree of penetration of the formation. As the drilling depth increases, the formation often exhibits different lithology and physical properties. By recording and analyzing mechanical data at different depths, the stratification of the formation can be identified, providing key information for geological exploration.

[0036] Power head propulsion force F p This reflects the thrust required by the drill rig during drilling and is closely related to the hardness and resistance of the formation. By monitoring changes in thrust, we can understand the formation hardness and the difficulty of drilling. Drill pipe torque (T) is the resistance torque that the drill pipe must overcome during rotation. It is related to the friction of the formation and the rotation efficiency of the drill pipe. Changes in torque can reveal the uniformity of the formation and possible anomalies.

[0037] During the drilling process, water pressure P is primarily used for drill bit cooling, cuttings cleaning, and geological exploration. By monitoring changes in water pressure, we can indirectly understand the surrounding rock's permeability and the extent of fracture development. A sudden decrease in water pressure may indicate that the borehole has encountered relatively fragmented surrounding rock or areas with developed fractures, making it difficult to maintain water pressure. Adjusting water pressure can also control drilling speed, avoiding drilling problems caused by excessive or slow drilling.

[0038] Drilling speed (v) reflects the rate at which the drill bit breaks rock and is related to factors such as surrounding rock hardness, the development of joints and fissures, and drill bit wear. By monitoring changes in drilling speed, it is possible to determine changes in the hardness and integrity of the surrounding rock. For example, if the drilling speed suddenly slows down under the same thrust and torque, it may indicate that the drill bit has encountered harder rock.

[0039] During the drilling process, mechanical data of the interaction between the drilling rig and the formation are obtained in real time. These data provide a solid foundation for in-depth analysis of formation characteristics and subsequent judgments.

[0040] Step S2, based on the mechanical data, the surrounding rock state and the drill bit state are judged. If the exploration conditions are met, the excitation wave signal generated by the drill rig impactor and the vibration signal sequence of the excitation wave signal propagating, refracting and reflecting through the stratum are collected. Through a detailed analysis of the mechanical data, the state of the surrounding rock can be accurately judged. If the surrounding rock state meets the exploration requirements, the excitation wave signal generated by the drill rig impactor is collected, and the propagation, refraction and reflection process of the excitation wave signal in the stratum is collected to form a vibration signal sequence. This step not only ensures the validity and accuracy of the collected signals, but also provides a more comprehensive and reliable information basis for advanced geological prediction through the organic combination of mechanical data and excitation wave signals. This multi-source information fusion strategy greatly enhances the reliability of the prediction and effectively reduces the risk of prediction errors caused by errors in a single information source. It can provide a deeper insight into the geological characteristics of the stratum, thereby reducing uncertainty when facing geological complexity and significantly improving the accuracy of advanced geological prediction.

[0041] In this embodiment, the surrounding rock state and the drill bit state are judged based on the mechanical data, specifically including the following steps: Step S201: Obtain the friction coefficient f corresponding to different types of surrounding rocks and steel.

[0042] Determining the friction coefficient f between different types of surrounding rock and steel (typically drill bit material) is a crucial task in engineering. This is because, during drilling, excavation, or other operations involving subsurface rock interaction, the friction coefficient between the surrounding rock and the drill bit directly impacts operational efficiency, energy consumption, and drill bit wear. The range of friction coefficients between different surrounding rock and steel varies depending on factors such as the surrounding rock type, surface properties, roughness, and interaction. Table 1 below shows the friction coefficients between common surrounding rock and steel: Table 1 Friction coefficient between surrounding rock types and steel

[0043] In this embodiment, taking mud, soil and rock as examples, the surrounding rock state includes mud, soil and rock. The friction coefficient f obtained includes the friction coefficient f between mud and steel. m , the friction coefficient between soil and steel f s , and the friction coefficient f between rock and steel r .

[0044] Step S202: Obtain drilling rig parameters, including the weight per unit length of drill pipe G L , maximum thrust F pmax , Maximum drilling speed V max .

[0045] Among them, the weight of drill pipe per unit length is G LRefers to the weight of the drill rod per meter of the drilling rig, which affects the sagging and bending degree of the drill rod during the drilling process, thereby indirectly affecting the torque requirement. pmax Refers to the maximum propulsion force that the drilling rig can generate during the drilling process, usually in kilonewtons (kN). This parameter reflects the drilling capacity of the drilling rig and its ability to overcome formation resistance. Maximum drilling speed V max Refers to the maximum drilling speed that a drilling rig can achieve during the drilling process, usually in meters per hour (m / h) or meters per minute (m / min). This parameter reflects the drilling efficiency and operating speed of the drilling rig.

[0046] Step S203, through the friction coefficient f, the weight per unit length of the drill rod G L and drilling depth L d Calculate the torque parameter range corresponding to different types of surrounding rock.

[0047] In this embodiment, the torque parameter ranges corresponding to different types of surrounding rock are specifically calculated using the following method: ; Among them, f is the friction coefficient between different types of surrounding rock and steel, G L is the weight per unit length of drill pipe, L d is the drilling depth of the drill, a1 is the maximum torque threshold corresponding to different types of surrounding rock, and a2 is the minimum torque threshold corresponding to different types of surrounding rock; the torque parameter range is T min ~T max .

[0048] Step S204, through the maximum propulsion force F pmax Calculate the propulsion force parameter range corresponding to different types of surrounding rock.

[0049] In this embodiment, the propulsion force parameter ranges corresponding to different types of surrounding rock are specifically calculated using the following method: ; Among them, F pmax is the maximum thrust of the drilling rig, c1 is the maximum thrust threshold corresponding to different types of surrounding rock, c2 is the minimum thrust threshold corresponding to different types of surrounding rock, and the thrust parameter range is F min ~F max .

[0050] Step S205, through the maximum drilling speed V max Calculate the drilling speed parameter range corresponding to different types of surrounding rock.

[0051] In this embodiment, the drilling speed parameter ranges corresponding to different types of surrounding rock are specifically calculated using the following method: ; Among them, V max is the maximum drilling speed of the drilling rig, b1 is the maximum drilling speed threshold corresponding to different types of surrounding rock, and b2 is the minimum drilling speed threshold corresponding to different types of surrounding rock; the drilling speed parameter range is v min ~v max .

[0052] It should be noted that the maximum torque threshold a1, minimum torque threshold a2, maximum drilling speed threshold b1, minimum drilling speed threshold b2, maximum thrust force threshold c1, and minimum thrust force threshold c2 corresponding to different surrounding rock types can be pre-set or derived through real-time correction and iteration through AI self-learning based on a comprehensive set of parameters. By collecting a large amount of surrounding rock state data from actual projects and constructing a rich dataset, the regression model can learn the complex relationship between different surrounding rock characteristics and mechanical parameter thresholds. This enables the model to provide highly accurate results when predicting the mechanical parameter thresholds for specific surrounding rock types, providing a reliable basis for engineering decision-making. During training, the regression model learns common patterns in surrounding rock characteristics. Therefore, even for new and unseen surrounding rock types, the model can provide relatively accurate predictions based on its existing knowledge base. This generalization capability enables the method to maintain high prediction accuracy across diverse geological conditions and engineering contexts. Compared with traditional experimental testing or empirical estimation methods, using regression models to predict mechanical parameter thresholds can significantly save time and cost. Model predictions do not require expensive field testing or reliance on individual engineers' experience, thereby reducing the overall cost of exploration and excavation. As new data accumulates, the regression model can be continuously updated and optimized to improve prediction accuracy and generalization. This flexibility enables the method to adapt to changing engineering environments and geological conditions.

[0053] In this embodiment, the maximum torque threshold a1 corresponding to silt is set to 1.2, the minimum torque threshold a2 is set to 0.8, the maximum drilling speed threshold b1 is set to 1, the minimum drilling speed threshold b2 is set to 0.8, the maximum propulsion force threshold c1 is set to 0.6, and the minimum propulsion force threshold c2 is set to 0; The maximum torque threshold a1 corresponding to the soil is set to 1.2, the minimum torque threshold a2 is set to 0.8, the maximum drilling speed threshold b1 is set to 1, the minimum drilling speed threshold b2 is set to 0.6, the maximum propulsion force threshold c1 is set to 0.6, and the minimum propulsion force threshold c2 is set to 0; The maximum torque threshold a1 corresponding to rock is set to 1.2, the minimum torque threshold a2 is set to 0.8, the maximum drilling speed threshold b1 is set to 0.5, the minimum drilling speed threshold b2 is set to 0.1, the maximum propulsion force threshold c1 is set to 1, and the minimum propulsion force threshold c2 is set to 0.6.

[0054] Preferably, the maximum torque threshold a1, minimum torque threshold a2, maximum drilling speed threshold b1, minimum drilling speed threshold b2, maximum propulsion force threshold c1, and minimum propulsion force threshold c2 corresponding to different types of surrounding rock are predicted by the constructed regression model, which is specifically achieved by the following method: (1) Collect a large amount of surrounding rock state data in actual projects such as geological exploration and tunnel excavation, and construct a data set.

[0055] Collect sample data on various surrounding rock types from practical engineering projects, geological exploration, and experimental testing. This includes physical properties (hardness, density, toughness, joint development, etc.), geological conditions (burial depth, geostress, hydrogeology, etc.), and related mechanical operating parameters (torque, speed, propulsion force, etc.). The collected data is cleaned to remove outliers and missing values. Feature engineering is performed to extract features useful for prediction, and normalization or standardization is performed. The constructed dataset is divided into training and validation sets, with a training to validation ratio of 4:1.

[0056] (2) Construct a regression model to learn the relationship between different surrounding rock characteristics and thresholds based on the dataset.

[0057] A regression model is constructed to predict the thresholds of maximum torque, rotational speed, and propulsion force for given surrounding rock characteristics. Regression models include deep learning networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), or ensemble learning methods (such as random forests and gradient boosting trees). These are existing technologies and will not be further described here.

[0058] The model is trained using the collected data. During the training process, the model learns the relationship between surrounding rock characteristics and mechanical operating parameter thresholds. The model's performance is evaluated through cross-validation and the model is fine-tuned based on the evaluation results. The model is continuously iterated using new data to improve its predictive accuracy. This includes: The model is initially trained using preprocessed data to obtain preliminary prediction results. In actual applications, the model's predictions are compared with real-time monitored data (such as actual values ​​of torque, speed, and thrust), and the error is calculated and fed back to the model. Based on the feedback error, an optimization algorithm (such as gradient descent) is used to adjust the model's weights and biases, and iterative learning is performed to improve the model's prediction accuracy.

[0059] (3) The maximum torque threshold a1, minimum torque threshold a2, maximum drilling speed threshold b1, minimum drilling speed threshold b2, maximum propulsion force threshold c1, and minimum propulsion force threshold c2 corresponding to different surrounding rock types are predicted through the trained regression model.

[0060] In practical applications, the model's prediction results can be fed back into the control of mechanical operating parameters in real time to achieve real-time adjustment and optimization.

[0061] Step S206: If the drill pipe torque T, power head thrust Fp, and drilling speed v of the drilling rig during the drilling process are all within the torque parameter range, thrust parameter range, and drilling speed parameter range corresponding to the same surrounding rock type, then the current surrounding rock state is determined to be the corresponding surrounding rock type.

[0062] In this embodiment, the maximum torque threshold a1, minimum torque threshold a2, maximum drilling speed threshold b1, minimum drilling speed threshold b2, maximum propulsion force threshold c1, and minimum propulsion force threshold c2 corresponding to different types of surrounding rock are determined using preset parameters to judge the current surrounding rock state, as shown in Table 2: Table 2 Surrounding rock state judgment table

[0063] Step S207: Based on the surrounding rock type, the drill rod torque T, the power head thrust F, and the drilling rig's p The drilling speed v is compared with the standard rock breaking data to judge the drill bit status.

[0064] (1) Data comparison and standards During drilling, drill pipe torque (T) directly reflects the interaction between the drill bit and the rock. Compare the measured torque (T) with the torque range specified in standard rock breaking data. If the actual torque exceeds the standard range, it may indicate that the drill bit is encountering hard rock or is stuck. If it falls below the standard range, it may indicate soft rock or severe drill bit wear.

[0065] Power head propulsion force F p This is the force exerted by the drill rig to propel the drill pipe forward. Comparing this force with standard rock-breaking data allows assessment of the drill bit's penetration capability and rock hardness. If the actual propulsion force exceeds the standard range, it may indicate soft rock or a sharp drill bit. If it falls below the standard range, it may indicate hard rock or a worn drill bit.

[0066] The drilling speed, v, is the depth a drill penetrates into rock in a given time. Compare the actual drilling speed to the speed range specified in standard rock breaking data. If the actual speed is above the standard range, it may indicate soft rock or high drill bit efficiency. If it is below the standard range, it may indicate hard rock or severe drill bit wear.

[0067] (2) Drill bit status judgment Normal state: If the drill pipe torque T, power head thrust Fp, and drilling speed v are all within the normal range of standard rock breaking data and have small fluctuations, it can be determined that the drill bit is in normal condition.

[0068] Abnormal status: Drill stuck: If the torque T increases abnormally while the rotational speed and drilling speed v decrease significantly, it may indicate that the drill bit is stuck in the rock. In this case, it is necessary to stop drilling and take appropriate measures to deal with it.

[0069] Drill bit wear: If the torque T and thrust Fp both increase, but the drilling speed v decreases, it may indicate that the drill bit is severely worn. In this case, a new drill bit needs to be replaced.

[0070] Rock hardness changes: If both torque T and drilling speed v change significantly and exceed the standard range, it may indicate that rocks of different hardness are encountered. In this case, the drilling parameters need to be adjusted according to the actual situation.

[0071] In this embodiment, judging the surrounding rock state and the drill bit state based on the mechanical data further includes the following steps: Step S208: During the drilling process, the drilling speed v of the drilling rig is at 90%×V max ~ V max Between, the drilling rig propulsion force F p The state is judged, if F p Less than 10% × F pmax , then the state of the water pressure P is judged. If the amplitude of the water pressure P decreases, it is judged that the drilling rig has entered a cavity and an alarm is sent at the same time.

[0072] As shown in Table 2, if the surrounding rock state is soil or rock and the drill bit state meets the standard rock breaking data, the exploration conditions are met. The excitation wave signal generated by the drill rig impactor and the vibration signal sequence transmitted, refracted and reflected by the excitation wave signal through the stratum are collected. The excitation wave signal generated by the drill rig impactor is encoded with a specific waveform or pulse sequence so that these signals can be accurately identified and decoded at the receiving end. Select a suitable coding scheme based on the application requirements and signal characteristics of the construction site. Coding schemes include amplitude shift keying (ASK), frequency shift keying (FSK) and phase shift keying (PSK). In this embodiment, phase shift keying is used to achieve signal encoding by changing the carrier phase, which has good anti-interference performance.

[0073] Step S3: forming an advanced geological prediction based on the excitation wave signal and the vibration signal sequence.

[0074] The impactor, a core component of a drilling rig, uses a precisely designed piston mechanism to move at extremely high speeds and strike a specific location, generating strong, frequency-specific excitation waves. These waves are rapidly transmitted along the drill pipe, an efficient energy transmission path, to the drill bit. Upon receiving this energy, the drill bit generates high-frequency vibrations powerful enough to break and penetrate the rock or soil in the drilling area, completing the drilling operation. During this process, a sensor captures the initial excitation wave signal generated by the impactor, recording it as the base reference signal S0. This signal forms the basis for subsequent analysis of all reflected and refracted signals.

[0075] When the excitation wave is transmitted from the drill bit into the rock and soil, it propagates in the rock and soil in the form of waves. As the wave propagates, when it encounters different geological structures or interfaces of geological hazards such as rock and soil faults, fracture zones, caves, and water bodies, it will be reflected and refracted. These reflected and refracted waves are captured by multiple pre-arranged sensors (usually n ≥ 3) and form a series of vibration signal sequences S1, S2, ... S n Each signal carries information about the geological structure of a specific location underground.

[0076] After collecting these vibration signal sequences, preprocessing is performed on each sequence (S1, S2, ...Sn), including noise reduction, enhancement, and filtering, to improve signal quality. Signal processing techniques such as waveform analysis, spectrum analysis, and time-frequency analysis are used to analyze the signals in detail. By comparing the differences between the base reference signal S0 and each reflected signal, such as the arrival time, amplitude, and frequency variations of the waves, key information such as the location, morphology, and properties of underground geological structures can be inferred.

[0077] (1) Waveform analysis Waveform analysis, as a cornerstone of signal processing, is of undeniable importance. It plays a crucial role in numerous fields, including geological exploration and nondestructive testing. By carefully comparing the waveform characteristics of the base reference signal S0 with the reflected signals S1, S2, ..., Sn, we can gain insight into the subtle changes that occur during wave propagation. These changes, including waveform broadening, distortion, attenuation, and variations in amplitude and phase, directly reflect the complexity of underground geological structures, the differences in the physical properties of rock and soil layers, and the diversity of wave propagation paths. When a beam encounters a hard rock layer, the amplitude of the reflected wave often increases significantly, and the waveform may become sharper and clearer. Conversely, when the wave passes through soft soil or encounters a highly absorptive medium, the waveform may broaden, blur, and gradually attenuate. Through in-depth analysis of these waveform characteristics, we can provide a preliminary assessment of the general underground geological structure, providing strong support for subsequent geological exploration.

[0078] (2) Spectrum analysis Spectral analysis is a key method for expanding the signal from the time domain to a new perspective in the frequency domain. Using mathematical tools such as the Fourier transform, a signal can be easily decomposed into a superposition of different frequency components, resulting in a spectrum. This spectrum clearly displays the energy distribution of the signal at different frequencies, revealing the signal's characteristics in the frequency domain. By comparing the spectrum differences between the base reference signal and each reflected signal, changes in frequency components can be captured. These changes are often closely related to the impact of underground geological structures on wave propagation characteristics. Different rock and soil layers have different absorption, reflection, and transmission characteristics for waves, which manifest themselves in the spectrum as enhancements or reductions in specific frequency components. A detailed interpretation of the spectrum provides a deeper understanding of the complexity and diversity of underground geological structures.

[0079] (3) Time-frequency analysis Time-frequency analysis is a more sophisticated signal processing method. It combines information from both the time and frequency domains, simultaneously reflecting the signal's temporal and frequency characteristics. Methods such as the short-time Fourier transform (STFT) and wavelet transform are typical examples of time-frequency analysis. By analyzing the reflected signal using these methods, we can observe the frequency variations of the signal along the time axis. These variations are often closely correlated with the location and morphology of underground geological structures. Time-frequency analysis can more accurately locate geological structures and characterize their morphology, providing more precise data support for geological exploration and mineral resource development.

[0080] (4) Difference analysis Difference analysis involves meticulously comparing the differences between the base reference signal and each reflected signal. These differences can manifest themselves in various aspects, including wave arrival time, amplitude, and frequency variations. Accurately identifying and analyzing these differences reveals the underlying mechanisms by which underground geological structures influence wave propagation. By calculating the arrival time difference between the reflected wave and the base wave, the precise distance between the reflection point (i.e., the location of the geological structure) and the drill bit can be estimated. By analyzing amplitude and frequency variations, the physical properties of the rock and soil (such as hardness, density, and elastic modulus) and the type of geological structure (such as faults, fracture zones, and dykes) can be inferred.

[0081] (5) Advanced geological forecast Finally, the information obtained from the above analysis is combined with the geological model to form the advanced geological prediction of geological interpretation and prediction. Through the comprehensive use of waveform analysis, spectrum analysis, time-frequency analysis and difference analysis, etc. The data information obtained can draw the profile or three-dimensional graph of the underground geological structure, which can intuitively show the distribution and morphology of the geological structure. At the same time, according to the physical properties of the rock-soil layer and the type of geological structure, the geological risks that may be encountered during drilling (such as collapse, water gushing, rock burst, etc.) can be predicted, and corresponding preventive measures and response plans can be developed accordingly. In addition, these information can also be used to optimize the drilling path and select appropriate drilling parameters (such as drilling speed, rotation speed, drilling pressure, torque, etc.), to improve the drilling efficiency and safety, and reduce the exploration cost. The comprehensive application of advanced geological prediction provides strong technical support and decision basis for exploration and development.

[0082] Step S4, based on the surrounding rock state, the advanced geological prediction is corrected and updated.

[0083] During the continuous drilling operation, the monitoring of the surrounding rock state needs to be uninterrupted, which includes real-time tracking of mechanical parameters such as drilling depth Ld, power head pushing force Fp, drill pipe torque T, water pressure P and drilling speed v, as well as sensitive capture of any slight variation of the formation structure. When the latest monitoring results of the surrounding rock state are obtained, they are immediately compared with the original advanced geological prediction. Any significant change in the surrounding rock state, such as unexpected faults, fracture zones encountered suddenly, or sudden changes in the physical properties of the formation, will become the key basis for correcting the prediction content. In the face of these new situations, the key information such as the location, shape and properties of the geological structure in the prediction is adjusted to ensure that the prediction content can truly and accurately reflect the actual conditions of the current underground environment.

[0084] In addition, as the drilling operation continues, the surrounding rock state will inevitably change continuously. Therefore, the updating of the advanced geological prediction also needs to be carried out regularly to maintain the accuracy and timeliness of the prediction. In the updating process, not only the newly monitored surrounding rock state information needs to be fully considered, but also the historical data and geological model need to be combined to comprehensively and systematically sort out and optimize the prediction content. In this way, it can be ensured that the advanced geological prediction can always keep up with the drilling progress and provide timely and reliable geological guidance for the construction team, so as to effectively avoid geological risks and ensure the safe and efficient progress of the drilling operation.

[0085] Embodiment two The embodiment shown in the present application also provides an exploration system using drill rig impactor excitation wave as excitation signal, which implements the exploration method using drill rig impactor excitation wave as excitation signal as claimed in any one of the above, and the system at least includes: The data acquisition module is used to collect mechanical data of the drilling rig during the drilling process, as well as the excitation wave signal generated by the drilling rig impactor and the vibration signal sequence caused by the propagation, refraction and reflection of the excitation wave signal through the formation; The data judgment module is used to judge the state of the surrounding rock based on mechanical data, generate advanced geological predictions based on the excitation wave signal and vibration signal sequence, and correct and update the advanced geological predictions based on the state of the surrounding rock.

[0086] In this embodiment, the data acquisition module includes at least one drilling depth measuring device installed on the drill arm of the drilling rig for measuring the drilling depth, at least one thrust sensor installed between the drill arm and the power head for measuring the propulsion force of the power head or a pressure sensor for detecting the hydraulic pressure of the driving power head propulsion, at least one torque sensor installed on the drilling rig drive motor for measuring the torque of the drill rod or a pressure sensor for detecting the hydraulic pressure of the driving power head rotation, and at least one pressure sensor installed in the drilling rig waterway for measuring the water pressure.

[0087] The data acquisition module also includes at least one acoustic vibration sensor for collecting the excitation wave signal generated by the drill impactor, and multiple highly sensitive vibration acoustic sensors for collecting the vibration signal sequence generated by the excitation wave signal propagating, refracting, and reflecting through the stratum. The acoustic vibration sensors are mounted on the drill impactor, drill rod, or a drilling component connected to the drill impactor and drill rod. The highly sensitive vibration acoustic sensors are deployed on the tunnel wall.

[0088] Preferably, the high-sensitivity vibration acoustic wave sensors are evenly distributed on the tunnel wall along the circumferential direction, with a number of 5 to 9. Figure 3 As shown, in this embodiment, five high-sensitivity vibration acoustic wave sensors are evenly distributed along the circumferential direction on the tunnel wall.

[0089] In short, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An exploration method using a drilling rig impactor excitation wave as an excitation signal, characterized in that: include: Obtain mechanical data of the drilling rig during the drilling process; Based on the mechanical data, the surrounding rock state and the drill bit state are judged. If the exploration conditions are met, the excitation wave signal generated by the drilling rig impactor and the vibration signal sequence resulting from the propagation, refraction and reflection of the excitation wave signal through the formation are collected. Based on the excitation wave signal and the vibration signal sequence, forming an advanced geological prediction; Based on the surrounding rock state, the advanced geological forecast is corrected and updated.

2. The exploration method using the drilling rig impactor excitation wave as the excitation signal according to claim 1, characterized in that: The mechanical data include the drilling depth L d , propulsion force F of power head p , drill pipe torque T, water pressure P and drilling speed v.

3. The exploration method using the drilling rig impactor excitation wave as the excitation signal according to claim 2, characterized in that: The judging of the surrounding rock state and the drill bit state based on the mechanical data specifically includes the following steps: Obtain the friction coefficient f between different types of surrounding rock and steel; Get the drilling rig parameters, including the weight of the drill rod per unit length G L , maximum thrust F pmax , Maximum drilling speed V max ; By the friction coefficient f, the weight per unit length of the drill pipe G L and drilling depth L d Calculate the torque parameter range corresponding to different types of surrounding rock; By the maximum propulsion force F pmax Calculate the propulsion force parameter range corresponding to different types of surrounding rock; By the maximum drilling speed V max Calculate the drilling speed parameter range corresponding to different types of surrounding rock; If the drill pipe torque T and power head propulsion force F during the drilling process p and the drilling speed v are all within the torque parameter range, propulsion force parameter range, and drilling speed parameter range corresponding to the same surrounding rock type, then the current surrounding rock state is judged to be the corresponding surrounding rock type; The torque parameter range, the propulsion force parameter range, and the drilling speed parameter range form standard rock breaking data; Based on the surrounding rock type, the drill rod torque T and the power head thrust F of the drilling rig during the drilling process are calculated. p The drilling speed v is compared with the standard rock breaking data to judge the drill bit status.

4. The exploration method using the drilling rig impactor excitation wave as the excitation signal according to claim 3, characterized in that: The step of judging the surrounding rock state and the drill bit state based on the mechanical data further includes the following steps: If the drilling speed v of the drilling rig is between 90%×Vmax~Vmax during the drilling process, the drilling rig propulsion force F p The state is judged, if F p If the value is less than 10%×Fpmax, the state of the water pressure P is judged. If the amplitude of the water pressure P decreases, it is judged that the drill bit has entered a cavity and an alarm is sent.

5. The exploration method using the drilling rig impactor excitation wave as the excitation signal according to claim 3 or 4, characterized in that: The torque parameter ranges corresponding to the different types of surrounding rock are specifically calculated using the following method: ； Among them, f is the friction coefficient between different types of surrounding rock and steel, G L is the weight per unit length of drill pipe, L d is the drilling depth of the drill, a1 is the maximum torque threshold corresponding to different types of surrounding rock, and a2 is the minimum torque threshold corresponding to different types of surrounding rock; the torque parameter range is T min ~T max .

6. The exploration method using the drilling rig impactor excitation wave as the excitation signal according to claim 5, characterized in that: The drilling speed parameter range is specifically achieved by the following calculation method: ； Among them, V max is the maximum drilling speed of the drilling rig, b1 is the maximum drilling speed threshold corresponding to different types of surrounding rock, and b2 is the minimum drilling speed threshold corresponding to different types of surrounding rock; the drilling speed parameter range is v min ~v max .

7. The exploration method using the drilling rig impactor excitation wave as the excitation signal according to claim 6, characterized in that: The propulsion force parameter range is specifically achieved by the following calculation method: ； Among them, F pmax is the maximum thrust of the drilling rig, c1 is the maximum thrust threshold corresponding to different types of surrounding rock, c2 is the minimum thrust threshold corresponding to different types of surrounding rock, and the thrust parameter range is F min ~F max .

8. The exploration method using the drilling rig impactor excitation wave as the excitation signal according to claim 7, characterized in that: The surrounding rock state includes silt, soil and rock, and the friction coefficient f includes the friction coefficient f between silt and steel. m , the friction coefficient between soil and steel f s , and the friction coefficient f between rock and steel r .

9. The exploration method using the drilling rig impactor excitation wave as the excitation signal according to claim 8, characterized in that: The maximum torque threshold a1, minimum torque threshold a2, maximum drilling speed threshold b1, minimum drilling speed threshold b2, maximum propulsion force threshold c1 and minimum propulsion force threshold c2 corresponding to the different types of surrounding rock are predicted by the constructed regression model, which is specifically achieved by the following method: Collect a large amount of surrounding rock state data in actual projects such as geological exploration and tunnel excavation to build a data set; Constructing a regression model to learn the relationship between different surrounding rock characteristics and thresholds based on the data set; Through the trained regression model, the parameters of the maximum torque threshold a1, minimum torque threshold a2, maximum drilling speed threshold b1, minimum drilling speed threshold b2, maximum propulsion force threshold c1 and minimum propulsion force threshold c2 corresponding to different surrounding rock types are predicted.

10. The exploration method using the drilling rig impactor excitation wave as the excitation signal according to claim 8, characterized in that: The maximum torque threshold a1 corresponding to the silt is set to 1.2, the minimum torque threshold a2 is set to 0.8, the maximum drilling speed threshold b1 is set to 1, the minimum drilling speed threshold b2 is set to 0.8, the maximum propulsion force threshold c1 is set to 0.6, and the minimum propulsion force threshold c2 is set to 0; The maximum torque threshold a1 corresponding to the soil is set to 1.2, the minimum torque threshold a2 is set to 0.8, the maximum drilling speed threshold b1 is set to 1, the minimum drilling speed threshold b2 is set to 0.6, the maximum propulsion force threshold c1 is set to 0.6, and the minimum propulsion force threshold c2 is set to 0; The maximum torque threshold a1 corresponding to the rock is set to 1.2, the minimum torque threshold a2 is set to 0.8, the maximum drilling speed threshold b1 is set to 0.5, the minimum drilling speed threshold b2 is set to 0.1, the maximum propulsion force threshold c1 is set to 1, and the minimum propulsion force threshold c2 is set to 0.

6.

11. The exploration method using a drilling rig impactor excitation wave as an excitation signal according to any one of claims 8 to 10, characterized in that: If the surrounding rock state is soil or rock and the drill bit state conforms to the standard rock breaking data, the exploration conditions are met; the excitation wave signal generated by the drill impactor is encoded to have a specific waveform or pulse sequence.

12. An exploration system using a drilling rig impactor excitation wave as an excitation signal, characterized in that: The system implements the exploration method using the drilling rig impactor excitation wave as an excitation signal as described in any one of claims 1 to 11, and the system at least comprises: A data acquisition module is used to collect mechanical data of the drilling rig during the drilling process, as well as the excitation wave signal generated by the drilling rig's impactor and the vibration signal sequence caused by the propagation, refraction and reflection of the excitation wave signal through the formation; A data judgment module is used to judge the surrounding rock state and the drill bit state based on the mechanical data, generate an advanced geological prediction based on the excitation wave signal and the vibration signal sequence, and correct and update the advanced geological prediction based on the surrounding rock state.

13. The exploration system using the drilling rig impactor excitation wave as the excitation signal according to claim 12, characterized in that: The data acquisition module includes at least one drilling depth measuring device installed on the drill arm of the drilling rig for measuring the drilling depth, at least one thrust sensor installed between the drill arm and the power head for measuring the propulsion force of the power head or a pressure sensor for detecting the hydraulic pressure of the driving power head, at least one torque sensor installed on the drilling rig drive motor for measuring the torque of the drill rod or a pressure sensor for detecting the hydraulic pressure of the driving power head, and at least one pressure sensor installed in the waterway of the drilling rig for measuring the water pressure.

14. The exploration system using the drilling rig impactor excitation wave as the excitation signal according to claim 13, characterized in that: The data acquisition module further includes at least one acoustic vibration sensor for acquiring an excitation wave signal generated by a drilling rig impactor, and a plurality of high-sensitivity vibration acoustic wave sensors for acquiring a vibration signal sequence resulting from the propagation, refraction, and reflection of the excitation wave signal through the formation; The acoustic vibration sensor is installed on the drilling rig impactor or drill rod or a drilling rig component connected to the drilling rig impactor and drill rod; The high-sensitivity vibration acoustic wave sensor is arranged on the tunnel wall.

15. The exploration system using the drilling rig impactor excitation wave as the excitation signal according to claim 14, characterized in that: The high-sensitivity vibration acoustic wave sensors are evenly distributed on the tunnel wall along the circumferential direction, with a number of 5 to 9.

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