Roof bolter monitoring system and method for rapidly detecting rock stratum state

Abstract

The invention discloses a jumbolter monitoring system and method for rapidly detecting the rock stratum state, and relates to the technical field of engineering monitoring, the monitoring system comprises a multi-source parameter monitoring module, a rock stratum detection module, a geological data module, a data return and remote cooperation module, a central control analysis module, an acousto-optic prompt module, a digital display module and an execution module. According to the monitoring system, through multi-source parameter collaborative acquisition and geological database linkage, different types of rock stratums are accurately recognized, the problem that the embedding depth of an anchoring section cannot be accurately confirmed after the rock stratums are smashed in traditional drilling is solved, the anchoring depth and strength requirements of an end bearing part are guaranteed, the stability and reliability of an anchor rod anchoring foundation are achieved, and the construction efficiency is improved. Engineering potential safety hazards caused by insufficient anchoring depth are avoided from core construction indexes, and key support is provided for long-term stable bearing of anchor rod engineering.

Description

Technical Field

[0001] This invention relates to the field of engineering monitoring technology, specifically to a monitoring system and method for anchor drilling rigs that rapidly detects the state of rock strata. Background Technology

[0002] An anchor drill is a specialized mechanical device used in geotechnical engineering to drill anchor holes. It is mainly used in slope treatment, underground engineering support, tunnel surrounding rock stabilization, and mine roadway anchoring to enhance the stability of geological structures and prevent geological disasters such as landslides and collapses. Anchor drills can be divided into hydraulic and pneumatic types according to their power source. Hydraulic anchor drills use hydraulic power and are suitable for support projects in coal mine roadways and mine tunnels. They are characterized by high torque and a wide adjustment range. Pneumatic anchor drills use compressed air as power and integrate drilling, mixing, and installation functions. They are small in size and light in weight, making them suitable for operation in rock or coal roadways with low hardness.

[0003] Currently, when anchor drilling rigs encounter different rock strata, such as moderately weathered and strongly weathered rock strata, the rock strength is low. After drilling, the rock strata are crushed, making it impossible to accurately determine the embedding depth of the anchor bolt in the anchoring section. This makes it impossible to guarantee the anchoring depth and strength of the end bearing part. At the same time, there may be naturally existing large cracks or cavities around the rock strata into which the anchor drilling rig is embedded. This poses a risk to the stability of the anchoring and increases the amount of grouting. If the voids are connected to other spaces, the amount of grouting will increase without limit. Such problems often exist in the rock strata for several meters to tens of meters and cannot be detected in advance, which increases the difficulty of construction and also makes the anchor drilling rig equipment very easy to be damaged. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a monitoring system and method for anchor drilling rigs to rapidly detect the state of rock strata, thus solving the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution: The monitoring system includes: a multi-source parameter monitoring module, a rock stratum detection module, a geological data module, a data transmission and remote collaboration module, a central control and analysis module, an audio-visual prompt module, a digital display module, and an execution module; The multi-source parameter monitoring module is used to simultaneously collect data on drilling pressure, drill rod vibration frequency, and rock temperature of the anchor drilling rig. The rock strata detection module is used to accurately detect rock strata fissures and cavities, as well as the volume profiles of fissures and cavities, within a range of 0-50 meters around the borehole. The geological database module: It stores a parameter library of standard pressure thresholds, vibration characteristic spectra, ultrasonic reflection coefficients and permeability for different regions and lithologies. It is updated and iterated through construction data to provide a benchmark for rock layer identification and parameter calculation. The data feedback and remote collaboration module integrates a wired transmission unit and a wireless transmission unit, which is used to transmit multi-source monitoring data back to the local central control module in real time, and at the same time realize the real-time access and data synchronization of remote terminals. The central control analysis module is used to receive multi-source data and combine it with the geological database module to analyze and confirm the rock strata type, anchorage section hole depth, fracture and cavity parameters, generate a multi-dimensional relationship diagram of time and pressure, vibration and temperature, and at the same time use AI algorithms to warn of drill pipe wear, equipment failure and rock strata abrupt change risk. The audio-visual prompt module is used to provide graded prompts with different frequencies and different timbres of sound and light when pressure fault fluctuations occur, cracks and cavities are detected, and equipment failure warnings are issued. The digital display module is used to display multi-dimensional monitoring data, rock strata status, anchorage section hole depth, AI early warning results, and grouting volume reference values ​​for visual viewing. The execution module is used to adjust the drilling speed and torque, and to regulate the grouting pressure and flow rate according to the volume of fractures and cavities and the permeability of the rock strata.

[0006] Preferably, the multi-source parameter monitoring module consists of a pressure sensor, a vibration sensor, and a temperature sensor installed at the end of the drill pipe or jack; The pressure sensor, vibration sensor, and temperature sensor adopt an integrated packaging structure. The sampling frequency of the pressure sensor, vibration sensor, and temperature sensor is ≥100Hz. The signal output terminals of the pressure sensor, vibration sensor, and temperature sensor are connected to the data feedback and remote collaboration module through double-shielded wires.

[0007] Preferably, the rock strata detection module consists of an ultrasonic detection device installed at the end of the drill bit of the anchor drilling rig. The ultrasonic detection device switches the detection frequency according to the rock strata type and environmental parameters. The ultrasonic detection device has a built-in frequency adjustment chip, and the detection frequency can be switched within the range of 20kHz-200kHz. The 50-80kHz low-frequency detection is suitable for strongly weathered rock layers, the 100-150kHz medium-frequency detection is suitable for moderately weathered rock layers, and the 150-200kHz high-frequency detection is suitable for precise quantification of cracks / cavities. The three-dimensional contour of cracks / cavities is reconstructed through ultrasonic echo imaging algorithm.

[0008] Preferably, the execution module includes: a drilling parameter adjustment submodule and a grouting closed-loop control submodule; The drilling parameter adjustment submodule is linked with the anchor drilling rig system and is used to adjust the drilling speed and torque of the anchor drilling rig. The grouting closed-loop control submodule communicates with the grouting equipment of the anchor drilling rig and is used to adjust the grouting pressure and flow rate of the grouting equipment according to the rock fractures, cavity volume and rock permeability.

[0009] Preferably, the drilling parameter adjustment submodule has a preset adjustment strategy, specifically: When the rock strength increases, reduce the drilling speed and increase the torque; when fractures and cavities are detected, reduce the drilling speed and decrease the torque. The grouting closed-loop control submodule obtains the optimal grouting parameters based on the volume of fractures and cavities, rock permeability, and grouting diffusion model, and feeds them back to the grouting equipment. The grouting volume matches the geological defects with a degree of ≥90%.

[0010] Preferably, the central control analysis module includes: a built-in Arduino controller, a timer unit, and an AI algorithm chip. The AI ​​algorithm chip has a built-in fault feature library and a rock strata mutation identification model, which is used to provide early warning of equipment failure information such as drill pipe fatigue wear and drill bit damage. The geological database module supports offline access and online iterative updates. In offline mode, it can access preset regional lithological parameters. In online mode, it can receive construction data and geological exploration data from the same region via 5G network to correct thresholds. Furthermore, it uses blockchain technology to store construction data.

[0011] A rapid monitoring method for rock strata conditions using a bolt drilling rig includes the following steps: S1: An integrated pressure, vibration and temperature sensor is installed at the end of the drill pipe or jack, and an adaptive frequency ultrasonic detection device is installed at the end of the drill bit. The connection and debugging between modules are completed. According to the geological survey report of the construction area, the geological database module is initialized and the corresponding regional lithological parameter thresholds and characteristic spectra are called. S2: Start the drilling rig and monitoring system. The multi-source parameter monitoring module synchronously collects drilling pressure, drill rod vibration frequency and rock temperature data of the anchor drilling rig. The rock detection equipment matches the initial detection frequency to collect rock state data. All collected data are generated into a dataset and transmitted to the central control analysis module and remote terminal through the integrated wired and wireless transmission units. S3: The central control analysis module integrates multi-source data and geological database parameters to confirm the rock strata type and calculate the anchorage section hole depth by combining drilling speed, time and lithology correction coefficient. At the same time, it uses AI algorithms to warn of equipment failure and the risk of sudden changes in rock strata. S4: If an anomaly is detected in the rock, the rock layer detection module dynamically switches to high-frequency mode, quantifies the location and volume of fractures and cavities, and the execution module synchronously adjusts the drilling speed and torque of the anchor drill. Based on the quantified data and rock layer permeability, the optimal grouting parameters are calculated, and the grouting equipment is linked to grout to support the rock layer. S5: During an anomaly, the digital display module shows all the monitoring data and control parameters. At the same time, the audio-visual prompt module issues graded audio-visual prompts according to the anomaly type. The remote terminal checks the operating status based on the anomaly warning and issues adjustment instructions to complete the anomaly handling. S6: During construction, the monitoring system uploads the construction data of the anchor drilling rig to the geological database for iterative optimization. After construction, it exports multi-dimensional data reports and time and parameter relationship diagrams for construction quality review and provides data support for subsequent construction.

[0012] Preferably, in step S3, the rock strata abrupt change identification model uses a machine learning algorithm to optimize parameters using a training set that includes different lithological transitions and hidden fault scenarios; The lithology correction factor is adjusted according to the rock compaction characteristics provided by the geological database module to ensure the accuracy of the calculation of the anchorage section hole depth.

[0013] Preferably, in step S4, the volume calculation of the crack and cavity is performed using ultrasonic echo imaging, and the three-dimensional contour is reconstructed by the time difference and amplitude difference of multiple sets of ultrasonic signals. The grouting diffusion model combines Darcy's law and fracture flow theory to correct the grouting diffusion radius, ensuring that the grouting parameters match the geological defects.

[0014] Preferably, in step S6, the iterative optimization of the geological database module uses a weighted average algorithm to correct the lithological parameter thresholds and supports data sharing among multiple projects, forming a regionalized and specialized geological parameter big data platform. The exported multidimensional data report includes: rock strata identification results, grouting volume matching analysis, and fault early warning records, providing parameter support for subsequent construction in the same area.

[0015] This invention provides a monitoring system and method for rapidly detecting the state of rock strata in anchor drilling rigs. It has the following beneficial effects: (1) This monitoring system accurately identifies different types of rock strata by collecting multi-source parameters in collaboration with the geological database. This reduces the problem that the embedding depth of the anchoring section cannot be accurately confirmed after the rock strata are crushed in traditional drilling. It ensures the anchoring depth and strength requirements of the end bearing part, realizes the stability and reliability of the anchoring foundation, avoids engineering safety hazards caused by insufficient anchoring depth from the core construction indicators, and provides key support for the long-term stable bearing of the anchoring project.

[0016] (2) This monitoring system can detect large cracks and cavities hidden in the rock strata, clarify their distribution status, and prevent the problem of difficult prediction of geological defects during construction. It avoids the risk of anchoring stability caused by cracks or cavities, and provides accurate geological basis for grouting operation. It can reasonably control the amount of grouting, eliminate the waste of unlimited increase in the amount of grouting, and realize the accurate matching of grouting and geological defects. While improving the anchoring quality, it can effectively control the construction cost and reduce unnecessary resource consumption.

[0017] (3) This monitoring system can capture real-time changes in rock strata and related signals of equipment operation. Through intelligent analysis, it can provide early warning of potential geological changes and equipment damage risks, allowing construction personnel to take targeted countermeasures in advance. This avoids blind drilling under complex geological conditions, reduces the difficulty of construction operations, reduces the impact damage of sudden geological problems on anchor drilling machines, ensures the continuity and safety of the construction process, and reduces the operational burden on construction personnel, thereby improving the efficiency and reliability of anchor drilling construction as a whole. Attached Figure Description

[0018] Figure 1 This is a system structure block diagram of the monitoring system of the present invention; Figure 2 This is a flowchart of the monitoring method steps of the monitoring system of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Example 1 Please see Figure 1 This invention provides a monitoring system for anchor drilling rigs that can quickly detect the state of rock strata. To achieve the above objectives, this invention is implemented through the following technical solution: The monitoring system includes: a multi-source parameter monitoring module, a rock strata detection module, a geological data module, a data transmission and remote collaboration module, a central control analysis module, an audio-visual prompt module, a digital display module, and an execution module; Multi-source parameter monitoring module: used to synchronously collect data on drilling pressure, drill rod vibration frequency and rock temperature of anchor drilling rig; Rock strata detection module: used to accurately detect rock strata fissures and cavities, as well as the volume profiles of fissures and cavities, within a range of 0-50 meters around the borehole. Geological Database Module: Inputs and stores a parameter library of standard pressure thresholds, vibration characteristic spectra, ultrasonic reflection coefficients and permeability for different regions and lithologies. It is updated and iterated through construction data to provide a benchmark for rock layer identification and parameter calculation. Data feedback and remote collaboration module: integrates wired and wireless transmission units to transmit multi-source monitoring data back to the local central control module in real time, while enabling real-time access and data synchronization for remote terminals; Central control analysis module: It is used to receive multi-source data and combine it with the geological database module to analyze and confirm the rock strata type, anchoring section hole depth, fracture and cavity parameters, generate multi-dimensional relationship diagrams of time and pressure, vibration and temperature, and at the same time use AI algorithms to warn of drill pipe wear, equipment failure and rock strata change risk. Audio-visual prompt module: used to provide graded prompts with different frequencies and timbres of sound and light when pressure fault fluctuations occur, cracks and cavities are detected, and equipment failure warnings are issued; Digital display module: Used to display multi-dimensional monitoring data, rock strata status, anchorage section hole depth, AI early warning results, and grouting volume reference values ​​for visual viewing; The execution module is used to adjust the drilling speed and torque, and to regulate the grouting pressure and flow rate according to the volume of fractures and cavities and the permeability of the rock formation.

[0021] In this embodiment, the multi-source parameter monitoring module adopts high-precision clock synchronization to allocate a unified sampling trigger signal to multiple sensors, ensuring that the sampling timestamp error is controlled within the microsecond level, realizing spatiotemporal synchronization of data, and ensuring the basis for correlation analysis of multi-source data. The rock strata detection module covers the entire area in front of the drill bit and around the borehole wall. Beamforming technology is used to achieve blind-spot-free coverage of the detection area, ensuring the complete acquisition of geological defect information. The geological database module has a built-in regional geological coding index system. It matches the corresponding geological code to call parameters according to the latitude and longitude of the construction area. At the same time, it updates and iterates through construction data to provide a benchmark for rock strata identification and parameter calculation. The data backhaul and remote collaboration module monitors wireless signal strength and packet loss rate in real time and automatically switches to the optimal transmission link to transmit multi-source monitoring data back to the local central control module in real time. At the same time, it enables real-time access and data synchronization of remote terminals. The central control analysis module adopts multi-data cross-validation logic (weighted judgment of lithological matching results of each parameter) to analyze and confirm rock stratum type, anchoring section hole depth, fracture and cavity parameters, and generate multi-dimensional relationship diagrams of time and pressure, vibration and temperature. At the same time, it uses AI algorithms to warn of drill pipe wear, equipment failure and rock stratum abrupt change risk. Each module adopts a distributed architecture design, and data interaction between modules is achieved through a standardized Modbus communication protocol, which has good scalability and compatibility. It can be adapted to different models and specifications of anchor drilling rigs. By constructing a full-process control link of "multi-source acquisition - precise analysis - intelligent early warning - closed-loop execution", the functional collaboration and technical adaptation of each module can realize comprehensive dynamic perception and control of anchor drilling construction. It solves the limitations of the disconnect between various links in traditional monitoring systems, and solves the problems of unclear geological conditions and blind adjustment of construction parameters in traditional construction, providing systematic guarantee for construction quality and safety.

[0022] Example 2 Specifically: The multi-source parameter monitoring module consists of a pressure sensor, a vibration sensor, and a temperature sensor installed at the end of the drill pipe or jack; The pressure sensor, vibration sensor, and temperature sensor adopt an integrated packaging structure. The sampling frequency of the pressure sensor, vibration sensor, and temperature sensor is ≥100Hz. The signal output terminals of the pressure sensor, vibration sensor, and temperature sensor are connected to the data feedback and remote collaboration module through double-shielded wires.

[0023] The rock strata detection module consists of an ultrasonic detection device installed at the end of the drill bit of the anchor drilling rig. The ultrasonic detection device switches the detection frequency according to the rock strata type and environmental parameters. The ultrasonic detection equipment has a built-in frequency adjustment chip, which can switch the detection frequency in the range of 20kHz-200kHz. The 50-80kHz low-frequency detection is suitable for strongly weathered rock layers, the 100-150kHz medium-frequency detection is suitable for moderately weathered rock layers, and the 150-200kHz high-frequency detection is suitable for precise quantification of cracks / cavities. The three-dimensional contour of cracks / cavities is reconstructed through ultrasonic echo imaging algorithm.

[0024] The execution module includes: a drilling parameter adjustment submodule and a grouting closed-loop control submodule; The drilling parameter adjustment submodule is linked with the anchor drilling rig system to adjust the drilling speed and torque of the anchor drilling rig; The grouting closed-loop control submodule communicates with the grouting equipment of the anchor drilling rig to adjust the grouting pressure and flow rate of the grouting equipment according to the rock fractures, cavity volume and rock permeability.

[0025] The drilling parameter adjustment submodule has preset adjustment strategies, specifically: When the rock strength increases, reduce the drilling speed and increase the torque; when fractures and cavities are detected, reduce the drilling speed and decrease the torque. The grouting closed-loop control submodule obtains the optimal grouting parameters based on the volume of fractures and cavities, rock permeability, and grouting diffusion model, and feeds them back to the grouting equipment. The grouting volume matches the geological defects with a degree of ≥90%.

[0026] The central control and analysis module includes: a built-in Arduino controller, a timer unit, and an AI algorithm chip. The AI ​​algorithm chip has a built-in fault feature library and a rock strata change recognition model to provide early warning of equipment failure information such as drill pipe fatigue wear and drill bit damage. The geological database module supports offline access and online iterative updates. In offline mode, it can access preset regional lithological parameters, and in online mode, it can receive construction data and geological exploration data from the same region through a 5G network to correct thresholds. Furthermore, it uses blockchain technology to store construction data. In this embodiment, the pressure sensor, vibration sensor, and temperature sensor adopt an integrated packaging structure. The sensor chip is encapsulated in a wear-resistant alloy shell using an epoxy resin potting process. The shell is filled with insulating, thermally conductive, and wear-resistant material, which ensures mechanical coupling with the drill pipe, isolates it from dust and water, and achieves heat dissipation to avoid temperature drift. The signal output end is connected to the data feedback and remote collaboration module through a double-layer shielded wire (metal braided mesh and aluminum foil). The shielding structure resists electromagnetic interference and signal attenuation, ensuring the quality of the original data transmission. The ultrasonic detection equipment switches the detection frequency according to the rock type and environmental parameters. The frequency switching principle is as follows: the central control analysis module outputs the lithology identification signal, which is transmitted to the frequency adjustment chip after level conversion. The chip adjusts the capacitance and inductance parameters of the internal oscillation circuit to achieve continuous switching in the range of 20kHz-200kHz. Among them, strong weathered rock layers are adapted to low frequency detection, moderately weathered rock layers are adapted to medium frequency detection, and fissures and cavities are adapted to high frequency detection. Furthermore, the ultrasonic echo imaging algorithm (combined with the superposition analysis of multiple sets of signals) reconstructs the three-dimensional contours of fissures and cavities, improving the realism of the contour reconstruction. The multi-source parameter monitoring module has a built-in backup sensor chip. When the main chip experiences a signal abnormality, the system automatically switches to the backup chip and triggers an early warning. The data return link is also equipped with wired and wireless dual-link redundancy. If one link is interrupted, the other link will automatically take over the data transmission to avoid data loss. In addition, the system integrates an adaptive temperature control unit. When the ambient temperature exceeds the equipment's operating threshold, the temperature control unit will activate a heat dissipation or heat preservation mechanism to maintain the stable operating temperature of the core components of the equipment. Through hardware structure process optimization and software algorithm technical adaptation, the detection accuracy, anti-interference ability, and execution reliability of the monitoring system are improved. This system solves the problems of insufficient stability, data distortion, and control lag of traditional monitoring equipment in complex construction environments. At the same time, through redundancy design and temperature control adaptation, the continuous operation capability of the equipment is greatly improved, reducing construction interruptions caused by equipment failure and providing hardware guarantee for the continuous advancement of anchor bolt construction.

[0027] Example 3 Reference Figure 2This invention provides a rapid method for monitoring rock strata conditions using a bolt drilling rig. To achieve the above objectives, this invention employs the following technical solution, comprising the following steps: S1: An integrated pressure, vibration and temperature sensor is installed at the end of the drill pipe or jack, and an adaptive frequency ultrasonic detection device is installed at the end of the drill bit. The connection and debugging between modules are completed. According to the geological survey report of the construction area, the geological database module is initialized and the corresponding regional lithological parameter thresholds and characteristic spectra are called. S2: Start the drilling rig and monitoring system. The multi-source parameter monitoring module synchronously collects drilling pressure, drill rod vibration frequency and rock temperature data of the anchor drilling rig. The rock detection equipment matches the initial detection frequency to collect rock state data. All collected data are generated into a dataset and transmitted to the central control analysis module and remote terminal through the integrated wired and wireless transmission units. S3: The central control analysis module integrates multi-source data and geological database parameters to confirm the rock strata type and calculate the anchorage section hole depth by combining drilling speed, time and lithology correction coefficient. At the same time, it uses AI algorithms to warn of equipment failure and the risk of sudden changes in rock strata. S4: If an anomaly is detected in the rock, the rock layer detection module dynamically switches to high-frequency mode, quantifies the location and volume of fractures and cavities, and the execution module synchronously adjusts the drilling speed and torque of the anchor drill. Based on the quantified data and rock layer permeability, the optimal grouting parameters are calculated, and the grouting equipment is linked to grout to support the rock layer. S5: During an anomaly, the digital display module shows all the monitoring data and control parameters. At the same time, the audio-visual prompt module issues graded audio-visual prompts according to the anomaly type. The remote terminal checks the operating status based on the anomaly warning and issues adjustment instructions to complete the anomaly handling. S6: During construction, the monitoring system uploads the construction data of the anchor drilling rig to the geological database for iterative optimization. After construction, it exports multi-dimensional data reports and time and parameter relationship diagrams for construction quality review and provides data support for subsequent construction.

[0028] In step S3, the rock strata abrupt change identification model uses a machine learning algorithm to optimize parameters using a training set that includes different lithological transitions and hidden fault scenarios. The lithology correction factor is adjusted according to the rock compaction characteristics provided by the geological database module to ensure the accuracy of the calculation of the anchorage section hole depth.

[0029] In step S4, the volume of the crack and cavity is calculated using ultrasonic echo imaging, and the three-dimensional contour is reconstructed by the time difference and amplitude difference of multiple sets of ultrasonic signals. The grouting diffusion model combines Darcy's law and fracture flow theory to correct the grouting diffusion radius, ensuring that the grouting parameters match the geological defects.

[0030] In step S6, the iterative optimization of the geological database module uses a weighted average algorithm to correct the lithological parameter thresholds and supports data sharing among multiple projects, forming a regional and specialized big data platform for geological parameters. The exported multidimensional data report includes: rock strata identification results, grouting volume matching analysis, and fault early warning records, providing parameter support for subsequent construction in the same area.

[0031] In this embodiment, when the anchor drilling rig starts construction and the monitoring system enters the construction process, the central control analysis module will first receive the time series data of drilling pressure, drill rod vibration frequency and rock temperature transmitted by the multi-source parameter monitoring module, and at the same time call the lithological benchmark parameters of the current construction area in the geological database module. The AI ​​algorithm chip loads a pre-trained rock strata mutation identification model (random forest ensemble classification model). It first performs time-series slicing on multi-source data to extract key input features such as the standard deviation of pressure fluctuations, the dominant frequency features of vibration signals, and the slope of temperature changes. Then, it inputs these features into the model. Multiple decision trees in the model will classify lithology based on the features, and finally output the current rock strata type through a majority voting mechanism. If the model identifies that the matching degree between the feature data and the "lithological transition, hidden fault" scenario in the training set exceeds the threshold, it will mark the risk of rock strata abrupt change and simultaneously retrieve the fault feature library to compare the harmonic characteristics of the current drill pipe vibration with the feature templates of "drill pipe fatigue, drill bit damage". If the matching degree meets the standard, it will trigger an equipment fault warning. Meanwhile, the central control analysis module combines the real-time drilling speed fed back by the drilling rig main control system, the drilling time recorded by the timer unit, and the lithology correction coefficient issued by the geological database module based on the current rock compaction characteristics to complete the hole depth calculation using the formula "anchor section hole depth = drilling speed × drilling time × lithology correction coefficient". During the calculation process, the stability of the pressure data is cross-checked. If the pressure fluctuation exceeds the threshold range of the corresponding lithology, the weight of the correction coefficient is automatically adjusted to ensure the accuracy of the hole depth result. If the ultrasonic signal feedback value of the rock strata detection module deviates from the reference ultrasonic reflection coefficient of the geological database, the system will automatically trigger a frequency switching command: the built-in frequency adjustment chip will quickly adjust the oscillation circuit parameters and switch the detection frequency to the high frequency range of 150-200kHz. Subsequently, ultrasonic echo signals from the borehole end and periphery are acquired at a higher sampling density. The central control analysis module receives these high-frequency signals and, by calculating the echo time difference (corresponding to spatial distance) and amplitude difference (corresponding to medium difference) of multiple sets of signals, combined with the propagation speed of ultrasound in the current lithology, reconstructs the three-dimensional spatial contour of the fracture and cavity and quantifies its volume parameters. Subsequently, the central control analysis module will substitute the fracture and cavity volume and the current rock permeability retrieved from the geological database into the grouting diffusion model: first, calculate the seepage velocity in the rock pores based on Darcy's law, then combine the cubic law of fracture flow to correct the flow distribution in the fracture area, establish the functional relationship of "grouting pressure, flow rate and diffusion radius", calculate the optimal grouting parameters to cover the geological defects, and transmit the parameter instructions to the grouting closed-loop control submodule of the execution module; This submodule establishes two-way communication with the grouting equipment, issuing grouting pressure and flow commands on one hand and receiving real-time execution data from the equipment on the other. If the actual grouting diffusion range deviates from the theoretical value by more than 5%, the parameters are dynamically corrected to ensure that the grouting volume is accurately matched with the geological defects. As construction enters its final stage, the monitoring system will automatically extract the corresponding lithology identification results, grouting parameters, early warning records, and other effective data after each anchor bolt is installed. This data will be uploaded incrementally to the geological database module. The database will use a weighted average algorithm to iteratively correct the parameter thresholds: the weight of newly collected construction data (0.7) is higher than that of historical data (0.3). Combined with shared data from other projects in the same area, the system will update the benchmark parameters such as the pressure threshold and vibration characteristic spectrum of the corresponding lithology. All data will be generated into blocks after consensus verification by blockchain nodes to ensure that the data is tamper-proof. After construction is completed, the system will call the data export interface: first, associate the unique number of each anchor rod, integrate the corresponding rock layer identification results, grouting volume and geological defect matching degree analysis, fault early warning records and other information to generate a multi-dimensional data report containing visualization charts and structured tables. At the same time, the geological parameter big data platform will incorporate the updated lithological parameters into the regional database according to the regional code of the current project, and through a hierarchical permission management mechanism, only open data access permissions to authorized subsequent project teams, providing accurate parameter support for anchor rod construction in the same area; Table 1 shows the drilling rod construction monitoring data of the anchor drilling rig (partial reference data): ; ; ; Table 2 shows the grouting parameters for cracks and cavities during anchor drilling (partial reference data): ; ; As can be seen from Tables 1 and 2 above: The monitoring system accurately implemented the technical design goals in actual construction. The data in the table shows that the depth of each anchor bolt hole deviates little from the calculated value of the anchoring section, which confirms the accuracy of hole depth calculation through multi-source parameter fusion and geological database linkage. The grouting material mix ratio, grouting pressure and other parameters remain stable and well-matched, with no loss of control over the grouting volume, which demonstrates the precise matching capability of the system's grouting closed-loop control submodule to geological defects. Meanwhile, no equipment damage occurred due to sudden changes in rock strata during the construction process, indicating that the AI ​​early warning and parameter adaptive adjustment functions effectively avoided risks. Overall, the monitoring system can reliably ensure anchoring quality and improve construction efficiency, fully meeting the expected value of the technical solution.

[0032] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A monitoring system for anchor drilling rigs that rapidly detects the state of rock strata, characterized in that: The monitoring system includes: a multi-source parameter monitoring module, a rock strata detection module, a geological data module, a data transmission and remote collaboration module, a central control and analysis module, an audio-visual prompt module, a digital display module, and an execution module; The multi-source parameter monitoring module is used to simultaneously collect data on drilling pressure, drill rod vibration frequency, and rock temperature of the anchor drilling rig. The rock strata detection module is used to accurately detect rock strata fissures and cavities, as well as the volume profiles of fissures and cavities, within a range of 0-50 meters around the borehole. The geological database module: It stores a parameter library of standard pressure thresholds, vibration characteristic spectra, ultrasonic reflection coefficients and permeability for different regions and lithologies. It is updated and iterated through construction data to provide a benchmark for rock layer identification and parameter calculation. The data feedback and remote collaboration module integrates a wired transmission unit and a wireless transmission unit, which is used to transmit multi-source monitoring data back to the local central control module in real time, and at the same time realize the real-time access and data synchronization of remote terminals. The central control analysis module is used to receive multi-source data and combine it with the geological database module to analyze and confirm the rock strata type, anchorage section hole depth, fracture and cavity parameters, generate a multi-dimensional relationship diagram of time and pressure, vibration and temperature, and at the same time use AI algorithms to warn of drill pipe wear, equipment failure and rock strata abrupt change risk. The audio-visual prompt module is used to provide graded prompts with different frequencies and different timbres of sound and light when pressure fault fluctuations occur, cracks and cavities are detected, and equipment failure warnings are issued. The digital display module is used to display multi-dimensional monitoring data, rock strata status, anchorage section hole depth, AI early warning results, and grouting volume reference values ​​for visual viewing. The execution module is used to adjust the drilling speed and torque, and to regulate the grouting pressure and flow rate according to the volume of fractures and cavities and the permeability of the rock strata.

2. The anchor drilling rig monitoring system for rapid detection of rock strata conditions according to claim 1, characterized in that: The multi-source parameter monitoring module consists of a pressure sensor, a vibration sensor, and a temperature sensor installed at the end of the drill pipe or jack. The pressure sensor, vibration sensor, and temperature sensor adopt an integrated packaging structure. The sampling frequency of the pressure sensor, vibration sensor, and temperature sensor is ≥100Hz. The signal output terminals of the pressure sensor, vibration sensor, and temperature sensor are connected to the data feedback and remote collaboration module through double-shielded wires.

3. The anchor drilling rig monitoring system for rapid detection of rock strata conditions according to claim 1, characterized in that: The rock strata detection module consists of an ultrasonic detection device installed at the end of the drill bit of the anchor bolt drilling rig. The ultrasonic detection device switches the detection frequency according to the rock strata type and environmental parameters. The ultrasonic detection device has a built-in frequency adjustment chip, and the detection frequency can be switched within the range of 20kHz-200kHz. The 50-80kHz low-frequency detection is suitable for strongly weathered rock layers, the 100-150kHz medium-frequency detection is suitable for moderately weathered rock layers, and the 150-200kHz high-frequency detection is suitable for precise quantification of cracks / cavities. The three-dimensional contour of cracks / cavities is reconstructed through ultrasonic echo imaging algorithm.

4. The anchor drilling rig monitoring system for rapid detection of rock strata conditions according to claim 1, characterized in that: The execution module includes: a drilling parameter adjustment submodule and a grouting closed-loop control submodule; The drilling parameter adjustment submodule is linked with the anchor drilling rig system and is used to adjust the drilling speed and torque of the anchor drilling rig. The grouting closed-loop control submodule communicates with the grouting equipment of the anchor drilling rig and is used to adjust the grouting pressure and flow rate of the grouting equipment according to the rock fractures, cavity volume and rock permeability.

5. The anchor drilling rig monitoring system for rapid detection of rock strata conditions according to claim 4, characterized in that: The drilling parameter adjustment submodule has a preset adjustment strategy, specifically: When the rock strength increases, reduce the drilling speed and increase the torque; when fractures and cavities are detected, reduce the drilling speed and decrease the torque. The grouting closed-loop control submodule obtains the optimal grouting parameters based on the volume of fractures and cavities, rock permeability, and grouting diffusion model, and feeds them back to the grouting equipment. The grouting volume matches the geological defects with a degree of ≥90%.

6. The anchor drilling rig monitoring system for rapid detection of rock strata conditions according to claim 1, characterized in that: The central control and analysis module includes: a built-in Arduino controller, a timer unit, and an AI algorithm chip. The AI ​​algorithm chip has a built-in fault feature library and a rock strata mutation identification model, which is used to provide early warning of equipment failure information such as drill pipe fatigue wear and drill bit damage. The geological database module supports offline access and online iterative updates. In offline mode, it can access preset regional lithological parameters. In online mode, it can receive construction data and geological exploration data from the same region via 5G network to correct thresholds. Furthermore, it uses blockchain technology to store construction data.

7. A method for monitoring anchor drilling rigs to rapidly detect the state of rock strata, characterized in that: Includes the following steps: S1: An integrated pressure, vibration and temperature sensor is installed at the end of the drill pipe or jack, and an adaptive frequency ultrasonic detection device is installed at the end of the drill bit. The connection and debugging between modules are completed. According to the geological survey report of the construction area, the geological database module is initialized and the corresponding regional lithological parameter thresholds and characteristic spectra are called. S2: Start the drilling rig and monitoring system. The multi-source parameter monitoring module synchronously collects drilling pressure, drill rod vibration frequency and rock temperature data of the anchor drilling rig. The rock detection equipment matches the initial detection frequency to collect rock state data. All collected data are generated into a dataset and transmitted to the central control analysis module and remote terminal through the integrated wired and wireless transmission units. S3: The central control analysis module integrates multi-source data and geological database parameters to confirm the rock strata type and calculate the anchorage section hole depth by combining drilling speed, time and lithology correction coefficient. At the same time, it uses AI algorithms to warn of equipment failure and the risk of sudden changes in rock strata. S4: If an anomaly is detected in the rock, the rock layer detection module dynamically switches to high-frequency mode, quantifies the location and volume of fractures and cavities, and the execution module synchronously adjusts the drilling speed and torque of the anchor drill. Based on the quantified data and rock layer permeability, the optimal grouting parameters are calculated, and the grouting equipment is linked to grout to support the rock layer. S5: During an anomaly, the digital display module shows all the monitoring data and control parameters. At the same time, the audio-visual prompt module issues graded audio-visual prompts according to the anomaly type. The remote terminal checks the operating status based on the anomaly warning and issues adjustment instructions to complete the anomaly handling. S6: During construction, the monitoring system uploads the construction data of the anchor drilling rig to the geological database for iterative optimization. After construction, it exports multi-dimensional data reports and time and parameter relationship diagrams for construction quality review and provides data support for subsequent construction.

8. The anchor drilling rig monitoring method for rapid detection of rock strata conditions according to claim 7, characterized in that: In step S3, the rock strata abrupt change identification model uses a machine learning algorithm to optimize parameters using a training set that includes different lithological transitions and hidden fault scenarios. The lithology correction factor is adjusted according to the rock compaction characteristics provided by the geological database module to ensure the accuracy of the calculation of the anchorage section hole depth.

9. A method for monitoring anchor drilling rigs for rapid detection of rock strata conditions according to claim 7, characterized in that: In step S4, the volume of the crack and cavity is calculated using ultrasonic echo imaging, and the three-dimensional contour is reconstructed by the time difference and amplitude difference of multiple sets of ultrasonic signals. The grouting diffusion model combines Darcy's law and fracture flow theory to correct the grouting diffusion radius, ensuring that the grouting parameters match the geological defects.

10. A method for monitoring anchor drilling rigs for rapid detection of rock strata conditions according to claim 7, characterized in that: In step S6, the iterative optimization of the geological database module uses a weighted average algorithm to correct the lithological parameter thresholds and supports data sharing among multiple projects, forming a regional and specialized big data platform for geological parameters. The exported multidimensional data report includes: rock strata identification results, grouting volume matching analysis, and fault early warning records, providing parameter support for subsequent construction in the same area.

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