Anchor rod positioning method and system of digging and anchoring all-in-one machine based on attitude adjustment and medium

Abstract

The invention discloses an anchor rod positioning method and system of a digging and anchoring all-in-one machine based on posture adjustment and a medium, and relates to the technical field of underground engineering construction.The method comprises the steps that a preset operation posture time sequence and geological survey feature distribution are received for geological space response analysis, and a first response analysis unit is constructed; based on the operation posture time sequence and the geological feature distribution, geological risk response analysis is executed, and a second response analysis unit is constructed; operation attitude data are collected in real time, the first response analysis unit is called for real-time response, and the second response analysis unit is called for deviation analysis and attitude adjustment. The technical problems that an existing digging and anchoring integrated machine anchor rod positioning technology is insufficient in positioning precision and weak in dynamic adjustment capacity under the complex geological condition are solved, and the purpose of positioning the anchor rod through high-precision dynamic posture adjustment and real-time geological risk early warning is achieved. And the positioning precision and the operation safety of the digging and anchoring all-in-one machine in a complex geological environment are improved.

Description

Technical Field

[0001] This invention relates to the field of underground engineering construction technology, specifically to a method, system, and medium for anchor bolt positioning in an integrated tunneling and anchoring machine based on attitude adjustment. Background Technology

[0002] In underground engineering projects such as mines and tunnels, roadheader-anchor (BAR) machines are widely used for excavation and support operations in roadways or tunnels. However, their operating environments typically feature complex geological conditions, such as soft rock, faults, and fractures. These conditions not only challenge the excavation efficiency and safety of BAR machines but also place higher demands on the accuracy of anchor bolt positioning. Traditional methods rely mainly on manual measurement and experience-based judgment, which suffers from low positioning accuracy, difficulty in adapting to rapid changes in geological conditions, and excessive human intervention. With the continuous expansion of project scale and the increasing demands for construction precision, traditional methods are no longer sufficient to meet the needs of modern engineering. Summary of the Invention

[0003] This application provides a method, system, and medium for anchor bolt positioning of integrated tunneling and anchoring machines based on attitude adjustment, which is used to solve the technical problems of insufficient positioning accuracy and weak dynamic adjustment capability of existing anchor bolt positioning technology for integrated tunneling and anchoring machines under complex geological conditions.

[0004] The first aspect of this application provides a method for anchor bolt positioning of a roadheader-anchor machine based on attitude adjustment. The method includes: receiving a predetermined operating attitude sequence of the roadheader-anchor machine and the distribution of geological survey features for a predetermined operating area; determining a positioning component configured on the roadheader-anchor machine, performing geological spatial response analysis on the positioning component, and constructing a first response analysis unit; performing geological risk response analysis on the predetermined operating attitude sequence and the distribution of geological survey features, and constructing a second response analysis unit; using the positioning component to collect real-time operating attitude sensing data of the roadheader-anchor machine, and calling the first response analysis unit to perform real-time response and output actual operating attitude information; and calling the second response analysis unit to perform deviation analysis and attitude adjustment on the actual operating attitude information based on the predetermined operating attitude sequence.

[0005] A second aspect of this application provides a bolt positioning system for a roadheader-anchor machine based on attitude adjustment. The system includes: a predetermined information receiving module for receiving predetermined operating attitude timing of the roadheader-anchor machine and the geological survey feature distribution for a predetermined operating area; a geological spatial response analysis module for determining the positioning component configured on the roadheader-anchor machine, performing geological spatial response analysis on the positioning component, and constructing a first response analysis unit; a geological risk response analysis module for performing geological risk response analysis on the predetermined operating attitude timing and the geological survey feature distribution, and constructing a second response analysis unit; a real-time response module for using the positioning component to collect operating attitude sensing data of the roadheader-anchor machine in real time, and calling the first response analysis unit for real-time response, outputting actual operating attitude information; and an attitude deviation adjustment module for calling the second response analysis unit to perform deviation analysis and attitude adjustment on the actual operating attitude information based on the predetermined operating attitude timing.

[0006] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method of the first aspect.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application provides a method, system, and medium for anchor bolt positioning of a tunneling and anchoring machine based on attitude adjustment, which relates to the field of underground engineering construction technology. By collecting the operating attitude data of the tunneling and anchoring machine in real time, and combining it with the predetermined operating attitude sequence and geological survey characteristics, a two-level response analysis unit is constructed. The first response analysis unit is used to correct the operating attitude data in real time, and the second response analysis unit is used to adjust the attitude deviation according to geological risk analysis. This solves the technical problems of insufficient positioning accuracy and weak dynamic adjustment capability of existing anchor bolt positioning technology for tunneling and anchoring machines under complex geological conditions. It achieves the technical effect of improving the positioning accuracy and operational safety of the tunneling and anchoring machine in complex geological environments through high-precision dynamic attitude adjustment and real-time geological risk early warning. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1A schematic flowchart of the anchor bolt positioning method for an integrated tunneling and anchoring machine based on attitude adjustment, provided in an embodiment of this application; Figure 2 A schematic diagram of the anchor bolt positioning system for an integrated tunneling and anchoring machine based on attitude adjustment, provided in an embodiment of this application.

[0010] Explanation of reference numerals in the attached diagram: 11 Pre-defined information receiving module, 12 Geological spatial response analysis module, 13 Geological risk response analysis module, 14 Real-time response module, 15 Attitude deviation adjustment module. Detailed Implementation

[0011] This application provides a method, system, and medium for anchor bolt positioning of integrated tunneling and anchoring machines based on attitude adjustment, which is used to solve the technical problems of insufficient positioning accuracy and weak dynamic adjustment capability of existing anchor bolt positioning technology for integrated tunneling and anchoring machines under complex geological conditions.

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0013] It should be noted that the terms "first," "second," etc., in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices.

[0014] Example 1, as Figure 1 As shown, this application provides a method for anchor bolt positioning of an integrated tunneling and anchoring machine based on attitude adjustment. The method includes: P10: Receive the predetermined operating posture sequence of the tunneling and anchoring machine and the geological survey feature distribution for the preset operating area. The tunneling and anchoring machine includes a tunneling unit and an anchoring unit, and the predetermined operating posture sequence includes the coordinated alternating posture sequence of the tunneling unit and the anchoring unit.

[0015] Optionally, the system first needs to receive the pre-set operating posture and timing of the tunneling and anchoring machine, as well as the geological characteristics distribution of the pre-set operating area. This step is the initial step of the entire operation process and can provide basic data for subsequent positioning, posture adjustment, and geological risk analysis.

[0016] Specifically, a tunneling and anchoring machine typically consists of two main units: a tunneling unit and an anchoring unit. The tunneling unit is responsible for excavating the underground tunnel or shaft, while the anchoring unit is responsible for anchoring the tunnel walls after excavation, enhancing structural stability and preventing collapse or deformation. These two units need to work alternately and collaboratively during actual operation. In particular, during tunneling, the tunneling and anchoring machine immediately initiates anchoring operations after each section of tunneling is completed to ensure tunnel safety and construction quality. Therefore, the tunneling and anchoring operations are strictly executed sequentially, forming a coordinated and alternating time sequence. This means that the sequence and frequency of tunneling and anchoring operations must be precisely controlled within a predetermined timeframe to ensure that each working unit can switch at the appropriate time, thereby maintaining high efficiency and stability in the operation.

[0017] In practice, the tunneling and anchoring machine needs to receive the predetermined operational sequence from the work plan, namely the start and stop times of each work unit, as well as the coordinated alternation sequence of each tunneling and anchoring operation. This sequence needs to be dynamically adjusted according to the geological characteristics of the work area. Therefore, the tunneling and anchoring machine also needs to receive the distribution of geological features related to the work area. This geological data includes key information such as the geological type of the work area, the hardness of the soil and rock strata, the groundwater level, and underground obstacles. Through a detailed understanding of the geological conditions, the tunneling and anchoring machine can more accurately formulate work plans and anticipate and avoid potential risks.

[0018] For example, if the geological conditions in the work area are relatively soft, the tunneling unit needs to perform anchoring operations more frequently to ensure the stability of the tunnel walls. In areas with harder rock strata, the tunneling process may be slower, but the frequency of anchoring operations is relatively lower. Therefore, the operating posture and timing of the tunnel boring machine must take into account the differences in geological characteristics to adjust the coordination and alternation time of each working unit, thereby improving work efficiency and safety.

[0019] P20: Determine the positioning component configured in the integrated tunneling and anchoring machine, perform geological spatial response analysis on the positioning component, and construct the first response analysis unit.

[0020] Furthermore, step P20 in this embodiment of the application also includes: P21: Extract multiple positioning sensors within the positioning component; P22: Based on the multiple sensor types of the multiple positioning sensors, collect multiple sets of historical sensor datasets and corresponding multiple historical sensor correction labels under historical excavation and anchoring scenarios; P23: Establish a graph structure using the multiple positioning sensors, and train the first response analysis unit using the multiple sets of historical sensor datasets and the multiple historical sensor correction labels using a graph neural network.

[0021] It should be understood that complex geological conditions may lead to positioning errors. Therefore, it is necessary to determine the positioning components configured in the tunneling and anchoring machine and conduct geological spatial response analysis on them to construct the first response analysis unit, effectively monitor and correct positioning errors, and ensure the accuracy and reliability of the operation process.

[0022] Specifically, the positioning component of the tunneling and anchoring machine consists of multiple types of positioning sensors. These sensors work together to acquire different types of data, ensuring that the equipment can be monitored in real time and accurately in terms of its attitude and position during tunneling and anchoring operations. In this process, the working principles and characteristics of each type of sensor must be considered, and effective data processing must be performed for different geological conditions. The core task of the positioning component is to ensure precise control of the equipment during tunneling and anchoring operations through these sensors. Because errors are prone to occur under complex geological conditions, the data from these sensors must be thoroughly analyzed and optimized.

[0023] To achieve this goal, it is first necessary to extract multiple sensors from the positioning components, namely a laser rangefinder, an inertial measurement unit (IMU), a GPS system, and a total station. The laser rangefinder is used to accurately measure the distance between the equipment and the surrounding rock, and to acquire detailed environmental data through laser scanning, such as the tunnel wall structure and rock strata characteristics. This data provides crucial information for geological spatial analysis, helping the system understand the geological conditions of the work area. The inertial measurement unit (IMU) monitors the equipment's attitude changes in real time through accelerometers, gyroscopes, and magnetometers, ensuring accurate control of key parameters such as angle and depth during tunneling and anchoring. The Global Positioning System (GPS) provides global positioning for the equipment, especially during the calibration phase outside the tunnel, providing a high-precision reference for initial positioning. The total station is used to provide reliable position and attitude data support when high-precision positioning is required inside the tunnel.

[0024] Furthermore, data acquisition and analysis are performed on multiple positioning sensors within the positioning component. Specifically, multiple sets of historical sensor datasets from historical excavation and anchoring scenarios need to be collected. These datasets reflect the actual operating status and output data of various positioning sensors under different geological conditions. Simultaneously, multiple corresponding historical sensor correction labels are collected. These correction labels are accurate data corrected manually or automatically based on historical data and can serve as a reference standard for training the model. Analysis of this historical data and correction labels allows for the evaluation of the performance variation patterns of the positioning sensors under different geological conditions, providing data support for subsequent model training.

[0025] After data acquisition, a graph structure needs to be built based on multiple positioning sensors, and a graph neural network (GNN) is used to train the first response analysis unit. In this graph structure, each sensor acts as a node, and nodes are connected by edges, which more clearly expresses the interactions and data transmission between sensors. Then, the GNN is used to train this data, learning how to adjust and correct positioning errors using historical sensor datasets and correction labels. The GNN can optimize the correlation between sensor data by learning from the graph structure, thereby improving the accuracy of data analysis. After training, the first response analysis unit can promptly detect and correct positioning errors based on real-time sensor data during actual operations, ensuring that the equipment maintains accurate positioning and attitude adjustment even in complex geological environments.

[0026] Furthermore, in establishing a graph structure using the multiple positioning sensors, step P23 of this embodiment also includes: P23-1: Analyze the sensing relationships between the multiple positioning sensors based on the multiple sets of historical sensing datasets; P23-2: Generate the graph structure using the multiple positioning sensors as nodes and the sensing relationships as edges.

[0027] Specifically, in order to further optimize the performance of the positioning components and improve their adaptability to complex geological conditions, the process of establishing a graph structure using multiple positioning sensors can be further refined.

[0028] First, the interrelationships between sensors in multiple sets of historical sensor datasets were analyzed. The aim of this analysis was to optimize positioning data by exploring the complementary and collaborative relationships between different sensors. For example, there is a significant correlation between IMUs (Inertial Measurement Units) and laser rangefinders. IMUs provide attitude and displacement information by monitoring changes in acceleration and angle, but they may accumulate errors over long periods, especially without external calibration. In this case, laser rangefinders, through precise distance measurements, can correct the errors in attitude and displacement calculations by the IMU. Therefore, in actual operation, the combination of IMUs and laser rangefinders can effectively improve positioning accuracy. Similarly, there is a strong correlation between IMUs and GPS systems. IMUs can continue to provide positioning and attitude information even when GPS signals are lost, and when GPS signals are restored, IMU data can be used to correct GPS positioning deviations, thus achieving complementarity and optimization between the two. By analyzing the correlations between these sensors, we can reveal how they work collaboratively in complex geological environments, further improving the reliability and accuracy of the positioning system. This analysis of correlations not only helps to understand the performance of each sensor in different environments, but also provides an important basis for the subsequent establishment of graph structures.

[0029] After analyzing the sensor correlations, a graph structure is generated based on these correlations. Specifically, multiple positioning sensors are used as nodes in the graph, while the sensor correlations between them are represented as edges. This graph structure can intuitively represent the interactions and data flow relationships between sensors. For example, the complementary relationship between an IMU and a laser rangefinder can be represented by an edge, the weight of which can be determined based on the strength of their correction effects in historical data. Similarly, the correlation between an IMU and GPS can also be represented by an edge, the weight of which reflects the IMU's correction capability when GPS signals are lost. The edges in the graph not only reflect the physical connectivity between sensors but also express their synergistic effects in specific tasks or environments.

[0030] For example, in a graph structure, the edge between an IMU node and a laser rangefinder node represents their complementary relationship; that is, IMU data can be corrected by the laser rangefinder, and laser rangefinder data can also enhance the IMU's positioning accuracy to some extent. Similarly, the edge between an IMU node and a GPS node indicates that when GPS signals are lost, the IMU can provide transitional data to maintain the stability of the positioning system. Once the GPS signal is restored, IMU data can be used to correct the GPS position, thereby strengthening the positioning cooperation between the two.

[0031] The establishment of the graph structure provides a data foundation for subsequent graph neural network training. Graph neural networks (GNNs) can utilize the relationships between sensor nodes and edges in these graph structures for information propagation and optimization, further improving positioning accuracy during operations. When the tunneling and anchoring machine is in a complex geological environment, the graph neural network will perform real-time error correction and adjustment based on sensor data between nodes in the graph, ensuring that the equipment can accurately control its attitude and position during tunneling and anchoring. In this way, the first response analysis unit can analyze the performance changes of the positioning components under complex geological conditions in real time and provide corresponding correction suggestions, thereby reducing positioning errors and improving the accuracy and reliability of anchor positioning.

[0032] Furthermore, by using a graph neural network to train the first response analysis unit with the multiple sets of historical sensor datasets and the multiple historical sensor correction labels, step P23 of this embodiment further includes: P23-3: Construct a graph neural network based on the graph structure, and use the multiple sets of historical sensor datasets and the multiple historical sensor correction labels to perform update correction relationship training between adjacent nodes to generate an initial response network; P23-4: Based on the initial response network, continue to use the multiple sets of historical sensor datasets and the multiple historical sensor correction labels to perform coupled update training of multiple neighboring nodes under the same node to generate the first response analysis unit.

[0033] It should be understood that the process of using graph neural networks in combination with historical sensor datasets and corrected labels to train the first response analysis unit can be further refined. Each node (sensor) learns from neighboring nodes (other sensors) through graph neural networks and continuously obtains information and updates its own features, thereby optimizing the positioning system.

[0034] First, a graph neural network is constructed based on the established graph structure. Each sensor node in the graph structure represents an independent sensor, while the edges between nodes reflect their sensory relationships. Building upon this, the graph neural network (GNN) combines sensor data with the relationships between sensors, learning how different sensors complement and correct each other through information transmission and updates.

[0035] During training, the graph neural network employs multiple historical sensor datasets and various historical sensor correction labels. The historical sensor datasets contain sensor data from different geological conditions and operational scenarios, providing insights into the performance of different sensors in actual operations. The historical correction labels represent corrections made to these sensor data by experts or based on actual measurements, indicating potential biases or errors from the sensors. Using this data, the graph neural network can train update and correction relationships between adjacent nodes. This involves transmitting information and correcting errors based on the relationships between neighboring nodes, generating an initial response network. This network initially learns the correlations between sensors and uses these relationships to correct errors in the sensor data.

[0036] Next, training continues based on the initial response network to further optimize and refine the response analysis. At this point, training is no longer limited to updates between adjacent nodes, but extends to coupled update training of multiple neighboring nodes under the same node. Through this training, each sensor node not only obtains information from its directly adjacent sensor nodes, but also updates its own features through the shared information of multiple neighboring nodes, thereby improving the accuracy and stability of the overall network.

[0037] For example, the angle and acceleration information of an IMU node can help a GPS node correct its position when GPS signals are lost. The IMU provides the device's direction and speed of movement through acceleration and angle measurements, and this data becomes a crucial reference for correcting GPS position when GPS signals are lost. On the other hand, the ranging results from a laser rangefinder node can provide precise distances between the device and the surrounding rock, and this information can help the IMU node correct its position. When the IMU experiences position drift due to long-term use, the laser rangefinder data can be used as a basis for correction, thus ensuring that the data provided by the IMU node is more accurate.

[0038] Through this neighbor node coupled update training, each sensor node acquires information from other sensor nodes. This information helps correct its own positioning data, thereby improving the positioning accuracy of the entire system. During the training process of the graph neural network, the relationships between nodes are continuously adjusted and optimized, ultimately forming a precise first response analysis unit that can monitor and adjust sensor data in real time during operation, performing error correction and attitude optimization.

[0039] P30: Perform geological risk response analysis based on the predetermined operation posture and timing and the distribution of geological survey characteristics, and construct a second response analysis unit.

[0040] Furthermore, step P30 in this embodiment of the application also includes: P31: Call the risk calibration library, traverse the predetermined operation posture time sequence and the geological survey feature distribution, and match any risk deviation feature set of any location geological survey feature. The risk calibration library includes a set of historical operation posture samples and multiple risk deviation features corresponding to historical geological features. P32: For any risk deviation feature set, combine historical deviation correction data to perform correction parameter matching and generate any correction parameter set. P33: Establish a mapping relationship between the geological survey feature at any location, the risk deviation feature set, and the correction parameter set to construct the second response analysis unit.

[0041] Optionally, a geological risk response analysis is performed based on the predetermined operating posture sequence and the distribution of geological survey characteristics, and a second response analysis unit is constructed. This process aims to identify and quantify geological risks in advance by analyzing the potential impact of geological conditions on the operating posture of the tunneling and anchoring machine, and to provide a scientific basis for subsequent posture adjustments.

[0042] Specifically, the process begins by accessing the risk calibration library and iterating through the predetermined operational posture sequence and geological survey feature distribution to match the geological survey features of any operational location with the corresponding set of risk deviation features. The risk calibration library is a database containing multiple sets of historical operational posture samples and corresponding historical geological features. Each set of historical samples includes all possible risk deviation features for that location under specific geological conditions. These risk deviation features reflect the impact of changes in the geological environment (such as soft soil, rock strata movement, and groundwater level fluctuations) on operational accuracy and equipment stability during actual operations, including position errors, posture errors, and operational depth errors. Therefore, by iterating through the predetermined operational posture sequence and corresponding geological feature distribution, the risk deviation feature set that best matches the current operational environment can be found from the risk calibration library.

[0043] After identifying the risk deviation feature set, correction parameters are further matched using historical deviation correction data. This historical data records the specific measures taken to correct deviations under similar geological conditions and their effects. For example, if geological conditions at a certain location lead to a risk of equipment subsidence, historical data may show that adjusting the equipment's support pressure can effectively alleviate this problem. By matching this historical data, a set of correction parameters can be generated for a specific risk deviation feature set, providing specific parameter support for subsequent attitude adjustments.

[0044] Finally, a mapping relationship is established for the geological survey characteristics, risk deviation characteristic set, and correction parameter set of each location to construct a second response analysis unit. This mapping relationship essentially associates geological features with corresponding risk deviation characteristics and correction parameters, thus forming a complete response model. When the tunneling and anchoring machine enters a specific work area, the second response analysis unit can automatically identify potential risks based on geological survey characteristics and historical risk deviation characteristics, and generate necessary correction parameters according to historical correction data, thereby adjusting the working posture in real time to ensure operational accuracy and equipment safety.

[0045] Therefore, the second response analysis unit can effectively predict and respond to geological risks, and provide accurate attitude adjustments and error corrections based on real-time and historical data. Through this risk analysis based on geological characteristics, the tunneling and anchoring machine can maintain efficient and stable operation in complex geological environments, minimizing errors caused by geological changes and improving operational safety and reliability.

[0046] In practical applications, the second response analysis unit can be integrated into the control system of the tunnel boring machine (TBM) to achieve automated operation posture adjustment. For example, during tunnel excavation, when the equipment enters a soft rock area, the system can automatically identify geological risks and adjust the equipment's support pressure and excavation speed according to pre-matched correction parameters to ensure that the anchor bolts can be accurately installed in the predetermined positions. This intelligent response mechanism can not only improve construction efficiency but also reduce equipment failures and construction accidents caused by changes in geological conditions.

[0047] P40: The positioning component is used to collect the working posture sensing data of the tunneling and anchoring machine in real time, and the first response analysis unit is called to perform a real-time response and output the actual working posture information.

[0048] Specifically, the positioning component of the tunneling and anchoring machine collects real-time operational posture sensor data and calls the previously constructed first response analysis unit for real-time response, ultimately outputting the actual operational posture information. This process is the core link to ensure that the tunneling and anchoring machine can achieve high-precision positioning and posture adjustment under complex geological conditions.

[0049] Specifically, during the operation of the tunnel boring machine (TBM), the positioning component collects the equipment's position and attitude data in real time through various sensors (such as laser rangefinders, IMUs, GPS systems, and total stations). Each of these sensors performs a different function. For example, the laser rangefinder is used to accurately measure the distance between the equipment and the surrounding rock; the IMU monitors the equipment's attitude changes in real time through accelerometers, gyroscopes, and magnetometers; the GPS system provides global positioning information; and the total station provides high-precision position and attitude measurements within the tunnel.

[0050] During the real-time acquisition of operational attitude sensing data, these sensors work together to ensure the comprehensiveness and accuracy of the data. For example, the IMU can provide real-time attitude change information of the equipment, while the laser rangefinder corrects for potential errors in the IMU through precise distance measurement. The GPS system provides initial positioning reference for the equipment outside the tunnel, while the total station provides high-precision positioning data inside the tunnel, ensuring the positional accuracy of the equipment during excavation and anchoring.

[0051] The acquired operational attitude sensing data is then transmitted to the first response analysis unit. This unit, built on a graph neural network, analyzes the relationships between sensors and historical data to respond to and process current sensor data in real time. During this process, the first response analysis unit not only examines individual sensor data but also considers their correlations and complementarities to reduce errors that may occur under complex geological conditions. For example, when the IMU detects a change in the device's attitude, the first response analysis unit combines data from the laser rangefinder to correct the IMU's errors, thereby providing more accurate attitude information.

[0052] By invoking the first response analysis unit, the system can immediately detect potential attitude deviations during real-time operations and correct them promptly, outputting actual operational attitude information. This information includes not only the equipment's current position and attitude but may also include predictions and correction suggestions for potential errors. For example, if geological conditions at a certain location pose a risk of equipment subsidence, the first response analysis unit will output corrected attitude information based on a pre-trained model and current sensor data, prompting operators or the automated control system to take appropriate measures. This process not only ensures the positioning accuracy of the equipment under complex geological conditions but also provides reliable data support for subsequent attitude adjustments and anchor bolt positioning.

[0053] P50: The second response analysis unit is invoked to perform deviation analysis and attitude adjustment on the actual operation posture information based on the predetermined operation posture timing.

[0054] Furthermore, step P50 in this embodiment of the application also includes: P51: Calculate the attitude deviation vector between the predetermined operation posture timing and the actual operation posture information; P52: Determine whether the attitude deviation vector is within the preset deviation range. If not, input the attitude deviation vector into the second response analysis unit to match the correction parameter whose similarity to the deviation vector is greater than the preset similarity, and generate the target correction parameter; P53: Perform attitude adjustment control using the target correction parameter.

[0055] It should be understood that by calling the second response analysis unit, deviation analysis and attitude adjustment are performed on the actual working attitude information based on the predetermined working attitude sequence, so as to avoid inaccurate operation or equipment damage caused by attitude error, and ensure that the operation process of the tunneling and anchoring machine always meets the predetermined working requirements.

[0056] First, the attitude deviation vector between the predetermined working posture sequence and the actual working posture information is calculated. The predetermined working posture sequence refers to the planned posture changes that the equipment should follow throughout the entire operation, typically designed based on factors such as geological features, operational requirements, and equipment performance. The actual working posture information is the equipment's current state data collected in real-time by the positioning component, including the equipment's angle, depth, and position. This process involves a precise comparison of the predetermined and actual postures, using mathematical methods to calculate the difference between them, resulting in the attitude deviation vector. The attitude deviation vector is a multi-dimensional vector containing attitude deviation information in various directions, such as angular and positional deviations. For example, if the predetermined working posture requires the equipment to maintain a specific tilt angle at a certain moment, but the actual working posture information shows a deviation between the actual tilt angle and the predetermined angle, this deviation will be reflected in the attitude deviation vector.

[0057] Next, it is determined whether the attitude deviation vector is within the preset deviation range. The preset deviation range is a threshold range set according to actual operational requirements and equipment performance, used to determine whether the equipment's attitude deviation is within an acceptable range. If all components of the attitude deviation vector are within the preset deviation range, the equipment's attitude can be considered to meet the predetermined requirements and no adjustment is needed; conversely, if one or more components of the attitude deviation vector exceed the preset deviation range, it indicates that the equipment's attitude has an unacceptable deviation and adjustment is required.

[0058] When the attitude deviation vector exceeds the preset deviation range, it needs to be input into the second response analysis unit. The unit then matches correction parameters with a similarity greater than the preset similarity to generate target correction parameters. Based on the previously constructed risk calibration library and historical data, the second response analysis unit can identify the characteristics of the current attitude deviation and compare them with historical deviation features in the library. By calculating the similarity between the attitude deviation vector and historical deviation features, it finds the historical deviation feature most similar to the current deviation and extracts the corresponding correction parameters to generate target correction parameters. These correction parameters are derived from experience in successfully correcting similar deviations in historical data. They refer to the amount of adjustment required for the equipment to return to the predetermined attitude under similar conditions, involving corrections to parameters such as the equipment's angle, depth, and direction of movement, providing a scientific basis for current attitude adjustments.

[0059] Finally, attitude adjustment control is performed using target correction parameters. Based on the generated target correction parameters, the attitude of the tunneling and anchoring machine is adjusted. For example, if the target correction parameters indicate that the tilt angle of the equipment needs adjustment, the control system will adjust the equipment's support system, hydraulic system, or other related components to gradually bring the equipment's attitude closer to the predetermined working posture. This process is dynamic and requires real-time monitoring of the equipment's attitude changes and continuous adjustments based on feedback information until the equipment's attitude deviation returns to the preset deviation range.

[0060] This process not only takes into account the impact of geological conditions on equipment posture, but also makes full use of historical data and experience, enabling the system to quickly identify and correct posture deviations, ensuring the accuracy and safety of equipment operation under complex geological conditions.

[0061] Furthermore, before inputting the attitude deviation vector into the second response analysis unit to match the deviation vector similarity with a correction parameter greater than a preset similarity, step P52 of this application embodiment further includes: P52-1a: Based on the geological survey characteristics distribution of the preset work area and the predetermined work posture time sequence, perform posture deviation fitting to generate a warning deviation vector feature for the preset warning event; P52-2a: Determine whether the posture deviation vector satisfies the warning deviation vector feature. If so, generate warning information and send it to the relevant staff.

[0062] In one possible embodiment of this application, before determining whether the attitude deviation vector exceeds the preset deviation range, a warning deviation vector feature can be generated to identify possible risk situations in advance, providing a more comprehensive guarantee for risk management during the operation process.

[0063] First, attitude deviation fitting is required based on the geological survey characteristics of the pre-defined work area and the predetermined work posture time sequence. The purpose of this process is to generate warning deviation vector features for pre-defined early warning events. Specifically, based on the geological survey characteristics and the predetermined work posture time sequence, the system analyzes abnormal attitude deviation patterns that may occur under specific geological conditions. These patterns may be related to potential geological risks, such as groundwater leakage and unstable rock formations. Through attitude deviation fitting, the system can generate early warning deviation vector features, which describe attitude deviation patterns that may lead to serious risks under specific geological conditions.

[0064] Next, it is determined whether the attitude deviation vector meets the characteristics of the early warning deviation vector. If the attitude deviation vector matches the characteristics of the early warning deviation vector, it indicates that the current attitude deviation may be related to a preset early warning event and there is a potential geological risk. For example, if the attitude deviation vector shows that the device has an abnormal subsidence trend in a certain area, and the geological survey characteristics show that there is a risk of groundwater leakage in that area, then the system will consider that the current attitude deviation meets the characteristics of the early warning deviation vector.

[0065] When the attitude deviation vector meets the characteristics of a warning deviation vector, the system generates a warning message and sends it to the relevant personnel. The warning message typically includes the specific details of the attitude deviation, the possible type of risk, and recommended countermeasures. For example, if the warning deviation vector characteristics indicate a risk of groundwater leakage, the warning message might advise personnel to immediately stop tunneling operations, check the equipment's sealing, and take appropriate drainage measures.

[0066] The introduction of this early warning mechanism enables the tunneling and anchoring machine not only to handle routine posture deviations but also to promptly identify potential risks that could lead to serious consequences and intervene in advance. This greatly enhances the safety of the operation process, especially in complex geological environments. By combining geological features and operational posture data, it can provide early warnings and responses before problems occur, avoiding safety accidents caused by equipment errors or geological changes.

[0067] In summary, the embodiments of this application have at least the following technical effects: This application improves operational accuracy by accurately adjusting the working posture of the tunneling and anchoring machine through real-time acquisition of operational posture data and combining it with predetermined operational posture sequence and geological survey characteristics. By constructing a geological risk response analysis unit, it identifies and warns of potential geological risks in real time, significantly enhancing safety during operations. The first response analysis unit provides real-time feedback and deviation correction, automatically adjusting the equipment posture, reducing manual operation, improving operational efficiency, and minimizing human error. The second response analysis unit dynamically adjusts the working posture according to changes in different geological environments, ensuring the equipment adapts to complex geological conditions. Simultaneously, real-time posture adjustment and risk management reduce equipment failures and operational interruptions, improving equipment stability and long-term operational efficiency.

[0068] The technology has achieved the goal of improving the positioning accuracy and operational safety of the tunneling and anchoring machine in complex geological environments through high-precision dynamic attitude adjustment and real-time geological risk early warning.

[0069] Example 2 is based on the same inventive concept as the attitude adjustment-based anchor bolt positioning method for tunneling and anchoring machines in the previous examples, such as... Figure 2As shown, this application provides an anchor bolt positioning system for an integrated tunneling and anchoring machine based on attitude adjustment. The system and method embodiments in this application are based on the same inventive concept. The system includes: The predetermined information receiving module 11 is used to receive the predetermined operating posture sequence of the tunneling and anchoring machine and the geological survey feature distribution of the preset operating area. The tunneling and anchoring machine includes a tunneling unit and an anchoring unit, and the predetermined operating posture sequence includes the coordinated alternating posture sequence of the tunneling unit and the anchoring unit.

[0070] The geological spatial response analysis module 12 is used to determine the positioning component configured in the tunneling and anchoring machine, perform geological spatial response analysis on the positioning component, and construct a first response analysis unit.

[0071] The geological risk response analysis module 13 is used to perform geological risk response analysis on the predetermined operation posture sequence and the geological investigation characteristic distribution, and to construct a second response analysis unit.

[0072] The real-time response module 14 is used to collect the working posture sensing data of the tunneling and anchoring machine in real time using the positioning component, and call the first response analysis unit to perform real-time response and output the actual working posture information.

[0073] The attitude deviation adjustment module 15 is used to call the second response analysis unit to perform deviation analysis and attitude adjustment on the actual operation attitude information based on the predetermined operation attitude timing.

[0074] Furthermore, the geological spatial response analysis module 12 is also used to perform the following steps: Extract multiple positioning sensors within the positioning component; based on the multiple sensor types of the multiple positioning sensors, collect multiple sets of historical sensor datasets and corresponding multiple historical sensor correction labels under historical anchoring scenarios; establish a graph structure using the multiple positioning sensors, and train the first response analysis unit using a graph neural network with the multiple sets of historical sensor datasets and the multiple historical sensor correction labels.

[0075] Furthermore, the geological spatial response analysis module 12 is also used to perform the following steps: The sensing relationships between the multiple positioning sensors are analyzed based on the multiple sets of historical sensing datasets; the graph structure is generated by using the multiple positioning sensors as nodes and the sensing relationships as edges.

[0076] Furthermore, the geological spatial response analysis module 12 is also used to perform the following steps: A graph neural network is constructed based on the graph structure. Using the multiple sets of historical sensor datasets and the multiple historical sensor correction labels, the update correction relationship between adjacent nodes is trained to generate an initial response network. Based on the initial response network, the coupling update training of multiple neighboring nodes under the same node is further performed using the multiple sets of historical sensor datasets and the multiple historical sensor correction labels to generate the first response analysis unit.

[0077] Furthermore, the geological risk response analysis module 13 is also used to perform the following steps: The risk calibration library is invoked, and the predetermined operation posture time sequence and the geological survey feature distribution are traversed to match any risk deviation feature set of any geological survey feature at any location. The risk calibration library includes a set of historical operation posture samples and multiple risk deviation features corresponding to historical geological features. For any risk deviation feature set, correction parameters are matched in combination with historical deviation correction data to generate any correction parameter set. A mapping relationship is established between the geological survey feature at any location, the risk deviation feature set, and the correction parameter set to construct the second response analysis unit.

[0078] Furthermore, the attitude deviation adjustment module 15 is also used to perform the following steps: Calculate the attitude deviation vector between the predetermined operation posture timing and the actual operation posture information; determine whether the attitude deviation vector is within a preset deviation range; if not, input the attitude deviation vector into the second response analysis unit to match the correction parameter whose similarity to the deviation vector is greater than the preset similarity, and generate a target correction parameter; use the target correction parameter to perform attitude adjustment control.

[0079] Furthermore, the attitude deviation adjustment module 15 is also used to perform the following steps: Based on the geological survey characteristics distribution of the preset work area and the predetermined work posture time sequence, posture deviation is fitted to generate a warning deviation vector feature for the preset warning event; it is determined whether the posture deviation vector satisfies the warning deviation vector feature, and if so, a warning message is generated and sent to the relevant staff.

[0080] In Embodiment 3, based on the same inventive concept as the anchor bolt positioning method of the integrated tunneling and anchoring machine based on attitude adjustment in the foregoing embodiments, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method as described in Embodiment 1.

[0081] Through the foregoing detailed description of the anchor bolt positioning method for an integrated tunneling and anchoring machine based on attitude adjustment, those skilled in the art can clearly understand the anchor bolt positioning method, system, and medium of this embodiment based on attitude adjustment. Therefore, for the sake of brevity, it will not be described in detail here. As for the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and relevant parts can be referred to in the method section.

[0082] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0083] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0084] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0085] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A method for anchor bolt positioning in a tunneling and anchoring machine based on attitude adjustment, characterized in that, include: Receive the predetermined operating posture and timing of the tunneling and anchoring machine, as well as the geological survey characteristics and distribution of the preset operating area; The positioning components configured in the tunneling and anchoring machine are determined, and a geological spatial response analysis is performed on the positioning components to construct a first response analysis unit; Geological risk response analysis is performed based on the predetermined operation posture and timing and the distribution of geological survey characteristics to construct a second response analysis unit; The positioning component is used to collect the working posture sensing data of the tunneling and anchoring machine in real time, and the first response analysis unit is called to respond in real time and output the actual working posture information. The second response analysis unit is invoked to perform deviation analysis and attitude adjustment on the actual operation posture information based on the predetermined operation posture timing.

2. The anchor bolt positioning method for an integrated tunneling and anchoring machine based on attitude adjustment as described in claim 1, characterized in that, The integrated tunneling and anchoring machine includes a tunneling unit and an anchoring unit, and the predetermined operating posture sequence includes the coordinated alternating posture sequence of the tunneling unit and the anchoring unit.

3. The anchor bolt positioning method for an integrated tunneling and anchoring machine based on attitude adjustment as described in claim 1, characterized in that, The positioning components configured in the tunneling and anchoring machine are determined, and a geological spatial response analysis is performed on the positioning components to construct a first response analysis unit, including: Extract multiple positioning sensors from the positioning component; Based on the multiple sensor types of the multiple positioning sensors, multiple sets of historical sensor datasets and corresponding multiple historical sensor correction labels are collected for historical anchor excavation scenarios. A graph structure is established using the multiple positioning sensors, and the first response analysis unit is trained using a graph neural network with the multiple sets of historical sensor datasets and the multiple historical sensor correction labels.

4. The anchor bolt positioning method for an integrated tunneling and anchoring machine based on attitude adjustment as described in claim 3, characterized in that, Establishing a graph structure using the plurality of positioning sensors includes: Analyze the sensing correlation relationships among the multiple positioning sensors based on the multiple sets of historical sensor datasets; The graph structure is generated by using the multiple positioning sensors as nodes and the sensor association relationships as edges.

5. The anchor bolt positioning method for an integrated tunneling and anchoring machine based on attitude adjustment as described in claim 3, characterized in that, The first response analysis unit is trained using a graph neural network with the multiple sets of historical sensor datasets and the multiple historical sensor correction labels, including: A graph neural network is constructed based on the graph structure. Using the multiple sets of historical sensor datasets and the multiple historical sensor correction labels, the update correction relationship between adjacent nodes is trained to generate an initial response network. Based on the initial response network, the coupled update training of multiple neighboring nodes under the same node is performed using the multiple sets of historical sensor datasets and the multiple historical sensor correction labels to generate the first response analysis unit.

6. The anchor bolt positioning method for an integrated tunneling and anchoring machine based on attitude adjustment as described in claim 1, characterized in that, Geological risk response analysis is performed based on the predetermined operation posture and timing and the distribution of geological survey characteristics, and a second response analysis unit is constructed, including: The risk calibration library is invoked, and the predetermined operation posture time sequence and the geological survey feature distribution are traversed to match any risk deviation feature set of any geological survey feature at any location. The risk calibration library includes a set of historical operation posture samples and multiple risk deviation features corresponding to historical geological features. For any set of risk deviation characteristics, correction parameters are matched by combining historical deviation correction data to generate any set of correction parameters; A mapping relationship is established between the geological survey characteristics of any location, the risk deviation characteristic set, and the correction parameter set, and the second response analysis unit is constructed.

7. The anchor bolt positioning method for an integrated tunneling and anchoring machine based on attitude adjustment as described in claim 1, characterized in that, The second response analysis unit is invoked to perform deviation analysis and attitude adjustment on the actual operation posture information based on the predetermined operation posture timing, including: Calculate the attitude deviation vector between the predetermined operation attitude timing and the actual operation attitude information; Determine whether the attitude deviation vector is within a preset deviation range. If not, input the attitude deviation vector into the second response analysis unit to match correction parameters whose similarity to the deviation vector is greater than the preset similarity, and generate target correction parameters. Attitude adjustment control is performed using the target correction parameters.

8. The anchor bolt positioning method for an integrated tunneling and anchoring machine based on attitude adjustment as described in claim 7, characterized in that, Before inputting the attitude deviation vector into the second response analysis unit to match the correction parameter where the similarity of the deviation vector is greater than a preset similarity, the method further includes: Based on the geological survey characteristics distribution of the preset work area and the predetermined work posture time sequence, posture deviation is fitted to generate a warning deviation vector feature for the preset warning event; Determine whether the state deviation vector satisfies the characteristics of the early warning deviation vector. If so, generate an early warning message and send it to the relevant staff.

9. An anchor bolt positioning system for an integrated tunneling and anchoring machine based on attitude adjustment, characterized in that, The system includes: The predetermined information receiving module is used to receive the predetermined operating posture sequence of the tunneling and anchoring machine and the geological survey feature distribution of the predetermined operating area; A geological spatial response analysis module is used to determine the positioning components configured in the tunneling and anchoring machine, perform geological spatial response analysis on the positioning components, and construct a first response analysis unit. A geological risk response analysis module is used to perform geological risk response analysis on the predetermined operation posture sequence and the distribution of geological investigation characteristics, and to construct a second response analysis unit. The real-time response module is used to collect the working posture sensing data of the tunneling and anchoring machine in real time using the positioning component, and call the first response analysis unit to perform real-time response and output the actual working posture information. The attitude deviation adjustment module is used to call the second response analysis unit to perform deviation analysis and attitude adjustment on the actual operation attitude information based on the predetermined operation attitude timing.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 8.

Images