A drill jumbo control method and device, electronic equipment and storage medium

Abstract

Embodiments of the present application provide a rock drilling jumbo control method and device, electronic equipment and storage medium, through laser radar scanning modeling of the excavation surface, a first point cloud model for the current cycle of the excavation surface is generated; when it is determined that the rock drilling jumbo is not the first operation on the excavation surface, the first point cloud model and a second point cloud model generated in the last cycle operation are used for registration to generate a first target point cloud model; the first target point cloud model is converted into first engineering coordinate parameters, and the first engineering coordinate parameters are determined as first spatial position information of the rock drilling jumbo; first working face point cloud data is obtained based on the first target point cloud model; a first working face projection is determined through the first working face point cloud data; the rock drilling jumbo is controlled through the first spatial position information and the first working face projection, automatic operation of the rock drilling jumbo on the tunnel excavation project is realized, and the engineering efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of drill jumbo control, in particular to a drill jumbo control method, a drill jumbo control device, an electronic device, a computer readable storage medium and a drill jumbo. BACKGROUND

[0002] The tunnel blasting excavation method first drills holes on the tunnel face according to the design requirements, then charges and blasts to realize the tunnel excavation footage. The drill jumbo is commonly used for drilling holes in tunnel blasting excavation. According to the related technology, surveyors need to set out on the tunnel excavation face before drilling, that is, to determine and mark the position of the drilling hole on the excavation face, and then the drill jumbo operator drills holes according to the drilling position, which leads to low construction efficiency. SUMMARY

[0003] The embodiments of the present application provide a drill jumbo control method, device, drill jumbo, electronic device and computer readable storage medium to overcome the above problems or at least partially solve the above problems.

[0004] The embodiments of the present application disclose a drill jumbo control method, wherein the drill jumbo control is configured with a laser radar, comprising:

[0005] The laser radar scans and models the excavation face to generate a first point cloud model for the current cycle of the excavation face;

[0006] When it is determined that the drill jumbo is not the first time for the excavation face, the first point cloud model and a second point cloud model generated in the last cycle are used for registration to generate a first target point cloud model;

[0007] The first target point cloud model is converted into first engineering coordinate parameters, and the first engineering coordinate parameters are determined as first spatial position information of the drill jumbo;

[0008] First face point cloud data is obtained based on the first target point cloud model;

[0009] A first face projection is determined through the first face point cloud data;

[0010] The drill jumbo is controlled through the first spatial position information and the first face projection.

[0011] Optionally, the drill jumbo control is configured with a corresponding surveying and mapping device, further comprising:

[0012] When it is determined that the drill jumbo is the first time for the excavation face, or the registration error is greater than a preset threshold, the surveying and mapping device is controlled to obtain calibration point coordinate information, and a reference model is constructed based on the calibration point coordinate information.

[0013] adopting the first point cloud model and a reference model to perform registration, to generate a second target point cloud model;

[0014] transforming the second target point cloud model into second engineering coordinate parameters, and determining the second engineering coordinate parameters as second spatial position information of the drill jumbo;

[0015] acquiring second working face point cloud data based on the second target point cloud model;

[0016] determining a second working face projection through the second working face point cloud data;

[0017] controlling the drill jumbo through the second spatial position information and the second working face projection.

[0018] Optionally, before the step of modeling the excavation face scanned by the laser radar to generate the first point cloud model for the current cycle of the excavation face, the method further comprises:

[0019] acquiring calibration spatial position data of the drill jumbo in a relative coordinate system with the laser radar as the center;

[0020] generating an initial position movement control signal based on the spatial position data;

[0021] controlling the drill jumbo to reach a position to be operated based on the initial position movement control signal.

[0022] Optionally, the method further comprises:

[0023] determining noise points, abnormal points and outliers of the first point cloud model;

[0024] eliminating the noise points, the abnormal points and the outliers.

[0025] Optionally, the step of acquiring first working face point cloud data based on the first target point cloud model comprises:

[0026] determining a tunnel axis and a normal vector of each point of the first target point cloud model;

[0027] determining a tunnel included angle using the tunnel axis and the normal vector;

[0028] screening out working face target points with a tunnel included angle less than a preset angle threshold, and generating the first working face point cloud data using the working face target points.

[0029] Optionally, the step of determining a first working face projection through the first working face point cloud data comprises:

[0030] creating a plane based on the first face point cloud data; a normal vector of a point of the plane is perpendicular to the tunnel axis;

[0031] determining a position of the plane on the tunnel axis by a least square method to determine a first face projection.

[0032] Optionally, further comprising:

[0033] When the drill jumbo is working, a specific target within a preset safety range is monitored, the drill jumbo is controlled to stop, and an alarm information is generated.

[0034] The embodiment of the application further discloses a drill jumbo control device, the drill jumbo control is configured with a laser radar, and comprises:

[0035] A first point cloud model generation module is configured to model scanning of a working face by the laser radar, and generate a first point cloud model of a current cycle for the working face;

[0036] A first target point cloud model generation module is configured to, when it is determined that the drill jumbo is not working on the working face for the first time, register the first point cloud model and a second point cloud model generated in a previous cycle to generate a first target point cloud model;

[0037] A first spatial position information determination module is configured to convert the first target point cloud model into first engineering coordinate parameters, and determine the first engineering coordinate parameters as first spatial position information of the drill jumbo;

[0038] A first face point cloud data acquisition module is configured to acquire first face point cloud data based on the first target point cloud model;

[0039] A first face projection determination module is configured to determine a first face projection by the first face point cloud data;

[0040] A drill jumbo control module is configured to control the drill jumbo by the first spatial position information and the first face projection.

[0041] The embodiment of the application further discloses an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete communication with each other through the communication bus;

[0042] The memory is used for storing a computer program.

[0043] The processor is used for executing the program stored on the memory to realize the method as described in the embodiment of the application.

[0044] The embodiment of the present application also discloses a computer readable storage medium, which stores instructions, and when executed by one or more processors, causes the processor to perform the method according to the embodiment of the present application.

[0045] A drill jumbo comprises:

[0046] one or more processors;

[0047] and one or more machine readable media storing instructions, which when executed by the one or more processors, cause the drill jumbo to perform one or more methods as described above.

[0048] The embodiment of the present application has the following advantages:

[0049] The embodiment of the present application comprises the following advantages: BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 is a step flow chart of a drill jumbo control method provided in the embodiment of the present application;

[0051] Figure 2 is a structure schematic diagram of a point cloud model registration provided in the embodiment of the present application;

[0052] Figure 3 is a structure schematic diagram of a drill jumbo positioning based on a surveying device provided in the embodiment of the present application;

[0053] Figure 4 is a step flow chart of another drill jumbo control method provided in the embodiment of the present application;

[0054] Figure 5 is a space state structure schematic diagram of a drill jumbo provided in the embodiment of the present application;

[0055] Figure 6 is a structure block diagram of a drill jumbo control device provided in the embodiment of the present application;

[0056] Figure 7 is a hardware structure block diagram of an electronic device provided in an embodiment of the present application;

[0057] Figure 8 is a schematic diagram of a computer readable medium provided in an embodiment of the present application. DETAILED DESCRIPTION

[0058] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0059] Referring to Figure 1 , a step flowchart of a drill jumbo control method provided in an embodiment of the present application is shown, which can specifically include the following steps:

[0060] Step 101, modeling the excavation face by scanning the excavation face by the laser radar, to generate a first point cloud model for the current cycle of the excavation face;

[0061] In a specific implementation, the drill jumbo control of the present embodiment is configured with a laser radar.

[0062] Laser radar is a sensor that can emit laser and receive reflected signals to measure the distance and angle of an object. Through laser radar, a vehicle can obtain three-dimensional point cloud data of the surrounding environment, including information such as the position and shape of obstacles. These information is crucial for the automatic control of the working vehicle.

[0063] In the automatic control system of the working vehicle, laser radar data is usually fused with other sensor data, such as global positioning system GPS, inertial measurement unit IMU, etc., to obtain more accurate environmental perception information. Then, the automatic control system will plan the motion trajectory of the vehicle according to these information, and control the actuators of the vehicle, such as steering, braking, etc., to finally realize the automatic operation of the vehicle.

[0064] Both the excavation face and the tunnel face are terms in tunnel construction, and they are closely related.

[0065] The excavation face refers to the interface of the surrounding rock formed after tunnel excavation.

[0066] The tunnel face refers to the working face of the tunnel that has been excavated during the tunnel excavation process. The tunnel face is the starting position of tunnel excavation and also the starting position of tunnel support. During the tunnel excavation process, the tunnel face will continuously advance forward.

[0067] The main difference between the excavation face and the tunnel face is:

[0068] Different positions: the excavation face is located at the tunnel surrounding rock that has not been excavated, while the tunnel face is located at the tunnel working face that has been excavated.

[0069] Different states: the excavation face is the unexcavated rock mass, while the face is the excavated rock mass.

[0070] Different roles: the excavation face is the potential space for tunnel excavation, while the face is the actual working face for tunnel excavation.

[0071] The relationship between the excavation face and the face is as follows:

[0072] The excavation face is the predecessor of the face.

[0073] The face is the successor of the excavation face.

[0074] As the tunnel continues to excavate, the excavation face will gradually become the face and then disappear.

[0075] In tunnel construction, both the excavation face and the face are important concepts. For the excavation face, geological investigation and evaluation are needed to determine the excavation plan of the tunnel; for the face, support and monitoring are needed to ensure the safe construction of the tunnel.

[0076] In the embodiment of the application, the laser radar can be used to scan and model the excavation face to generate a first point cloud model for the current cycle of the excavation face. In the tunnel excavation project, multiple cycles of excavation are needed, and the first point cloud model is the point cloud model for the current cycle.

[0077] In step 102, when it is determined that the drill jumbo is not working on the excavation face for the first time, the first point cloud model and a second point cloud model generated in the last cycle are used for registration to generate a first target point cloud model.

[0078] The point cloud model collected this time is registered with the point cloud model of the last cycle, and the purpose is to make the two point cloud models as consistent as possible, so as to better reflect the changes of the target object.

[0079] Common point cloud registration algorithms include:

[0080] Iterative Closest Point (ICP) algorithm: This algorithm realizes registration by iteratively minimizing the point-to-point distance between two point cloud models. ICP algorithm is a classic point cloud registration algorithm, which has the advantages of strong robustness and high computational efficiency.

[0081] Normal Distribution Transform (NDT) algorithm: This algorithm represents the point cloud model as a normal distribution and realizes registration by minimizing the difference between two normal distributions. NDT algorithm is robust to noise and local distortion, but its computational efficiency is slightly lower than that of ICP algorithm.

[0082] Feature matching algorithm: This algorithm first extracts the features of the point cloud model, and then calculates the registration transformation according to the matching relationship between the features. The feature matching algorithm has high computational efficiency, but requires high extraction and matching of features.

[0083] The specific operation steps are as follows:

[0084] 1. Select the registration algorithm

[0085] According to the characteristics of the point cloud model and the requirements of the registration task, select the appropriate registration algorithm. For example, if the point cloud model has noise or local distortion, you can choose the NDT algorithm; if you need high computational efficiency, you can choose the ICP algorithm.

[0086] 2. Parameter setting

[0087] Set appropriate parameters for the selected registration algorithm. For example, for the ICP algorithm, you need to set parameters such as maximum iteration number, distance threshold, etc.; for the NDT algorithm, you need to set parameters such as voxel size, search radius, etc.

[0088] 3. Perform registration

[0089] Use the selected registration algorithm to register two point cloud models.

[0090] 4. Evaluate the results

[0091] Evaluate the registration results to ensure their accuracy and correctness. Common evaluation methods include:

[0092] Visual inspection: Observe whether the two point cloud models after registration overlap together.

[0093] Distance error calculation: Calculate the point pair distance between the two point cloud models after registration.

[0094] Application test: Apply the registration results to actual tasks to evaluate their performance.

[0095] The accuracy of point cloud registration has a great influence on subsequent point cloud processing tasks. Therefore, when performing point cloud registration, you need to carefully select the registration algorithm and parameters, and evaluate the results.

[0096] In addition to the above general registration algorithms, there are also some point cloud registration algorithms for specific applications, such as point cloud registration algorithms for outdoor scenes, point cloud registration algorithms for industrial scenes, etc.

[0097] Reference Figure 2 , Figure 2 is a structural diagram of a point cloud model registration provided in an embodiment of the present application;

[0098] The first point cloud model and the second point cloud model generated in the last cycle of operation can be used for registration to generate a first target point cloud model when non-first drilling operation is performed and the automatic positioning accuracy of the rock drilling jumbo does not need to be corrected.

[0099] In step 103, the first target point cloud model is converted into first engineering coordinate parameters, and the first engineering coordinate parameters are determined as the first spatial position information of the rock drilling jumbo.

[0100] In addition to determining the face projection, it is also necessary to convert the registered point cloud model into engineering coordinates, mainly for the following reasons:

[0101] 1. The face projection is usually local information, while the engineering coordinate is global information.

[0102] The face projection only reflects the excavation surface information of the current construction, while the engineering coordinate is the spatial position information of the entire tunnel. Converting the point cloud model into engineering coordinates can associate the excavation surface of the current construction with the entire tunnel, thereby better managing the construction progress and safety monitoring.

[0103] 2. Engineering coordinates can be used for other construction tasks.

[0104] In tunnel construction, in addition to excavation operations, other construction tasks such as support, measurement, grouting, etc. are also needed. These tasks require engineering coordinates. Therefore, converting the point cloud model into engineering coordinates can provide basic data for subsequent construction tasks.

[0105] 3. Converting engineering coordinates can improve data accuracy.

[0106] The coordinate system of the point cloud model is usually a relative coordinate system, while the engineering coordinate is an absolute coordinate system. Converting the point cloud model into engineering coordinates can eliminate errors between relative coordinate systems and improve data accuracy.

[0107] Determining the face projection is the premise of excavation construction, while converting the point cloud model into engineering coordinates is the basis of excavation construction. The two are interrelated and mutually reinforcing.

[0108] Converting the point cloud model into engineering coordinates usually requires using coordinate transformation methods. Common coordinate transformation methods include translation transformation, rotation transformation, and scaling transformation, etc.

[0109] In practical applications, the relative coordinate system of the point cloud model refers to the coordinate system centered on the laser radar, and the spatial position information refers to the position and attitude information of the vehicle in the laser radar coordinate system.

[0110] Therefore, in the embodiment of the present invention, the first target point cloud model can be converted into first engineering coordinate parameters, and the first engineering coordinate parameters can be determined as the first spatial position information of the drilling rig.

[0111] Step 104: acquiring first tunnel face point cloud data based on the first target point cloud model;

[0112] Step 105: determining a first tunnel face projection using the first tunnel face point cloud data;

[0113] To determine the tunnel face projection plane for this round of construction, the following steps need to be followed:

[0114] 1. Data Preparation

[0115] Ensure that the point cloud model of the excavation surface of this round of construction and the point cloud model of the excavation surface of the previous round of construction have been obtained.

[0116] The two sets of point cloud models need to be preprocessed, such as filtering and denoising, to ensure the quality of the data.

[0117] 2. Point Cloud Registration

[0118] The excavation surface point cloud model of this round of construction is aligned with the excavation surface point cloud model of the previous round of construction.

[0119] The purpose of registration is to make the two point cloud models as consistent as possible so that the position and shape of the current wheel face can be accurately calculated.

[0120] Commonly used point cloud registration algorithms include ICP algorithm, NDT algorithm, etc.

[0121] 3. Palm face extraction

[0122] Based on the registered point cloud model, the point cloud data of the current round of tunnel face is extracted.

[0123] There are many methods for tunnel face extraction, such as threshold-based segmentation and region growing-based segmentation.

[0124] The selection of an appropriate tunnel face extraction method can be based on the specific point cloud data characteristics and application requirements.

[0125] 4. Projection calculation

[0126] Projection calculation is performed on the extracted point cloud data of the current round of tunnel face to obtain the current round of tunnel face projection plane.

[0127] There are many methods for projection calculation, such as plane fitting, least squares method, etc.

[0128] The appropriate projection calculation method can be selected based on the specific point cloud data characteristics and application requirements.

[0129] 5. Result evaluation

[0130] The obtained current round of face projection plane is evaluated to ensure its accuracy and correctness.

[0131] The evaluation method can include visual inspection, distance error calculation, etc.

[0132] If the evaluation result is not satisfactory, the previous steps need to be re-performed until a satisfactory result is obtained.

[0133] Exemplarily:

[0134] When performing point cloud registration, ICP algorithm or NDT algorithm can be selected. ICP algorithm has strong robustness but low computational efficiency; NDT algorithm has high computational efficiency but is sensitive to noise and local distortion.

[0135] When performing face extraction, threshold-based segmentation method or region growing-based segmentation method can be selected. Threshold-based segmentation method is simple and easy to implement, but is sensitive to threshold selection; region growing-based segmentation method is more robust.

[0136] When performing projection calculation, plane fitting method or least squares method can be selected. Plane fitting method is simple and easy to implement, but has high requirements for the quality of point cloud data; least squares method is more robust.

[0137] Step 106, controlling the drill jumbo through the first spatial position information and the first face projection.

[0138] Exemplarily, the specific steps are as follows:

[0139] 1. Excavation area demarcation

[0140] According to the shape and size of the current round of face projection plane, the excavation area of the current round is demarcated. The excavation area should be slightly larger than the area of the face projection plane to leave a certain safety margin.

[0141] 2. Excavation parameter setting

[0142] According to the specific circumstances of the excavation area, set the excavation parameters of the drill jumbo, including excavation depth, excavation angle, excavation speed, etc. The setting of excavation parameters should ensure the balance between excavation efficiency and safety.

[0143] 3. Drill jumbo positioning

[0144] Position the drill jumbo to the excavation area location based on the first engineering coordinate parameters (X, Y, Z), as well as the azimuth angle α, the pitch angle β, and the roll angle θ of the drill jumbo.

[0145] 4. Excavation construction

[0146] The rock drilling jumbo autonomously determines the position of the drilling hole in the point cloud model of the tunnel face according to the drilling design parameters, and controls the drilling mechanical arm to reach the drilling position based on the first spatial position information to carry out drilling operation. During excavation, the operation of the rock drilling jumbo should be closely observed, and the excavation parameters should be adjusted in a timely manner. At the same time, safety precautions should also be paid attention to to prevent accidents. Alternatively, the rock drilling jumbo can monitor whether there is a specific target (such as a construction worker) within a preset safety range through a laser radar, and when there is a specific target within the preset safety range, the rock drilling jumbo is controlled to stop and an alarm information is generated.

[0147] 5. Tunnel face inspection

[0148] After excavation is completed, the rock drilling jumbo can be controlled to obtain the point cloud model of the tunnel face of the current round through the rock drilling jumbo, and the point cloud model of the tunnel face of the current round is converted into engineering coordinates for inspection, to ensure that the shape and size of the tunnel face meet the design requirements. If problems are found, they should be handled in a timely manner.

[0149] In the embodiment of the application, the laser radar scans the excavation surface to generate a first point cloud model for the current round of the excavation surface; when it is determined that the rock drilling jumbo is not performing a first operation on the excavation surface, the first point cloud model and a second point cloud model generated during the last round of operation are used for registration to generate a first target point cloud model; the first target point cloud model is converted into first engineering coordinate parameters, and the first engineering coordinate parameters are determined as first spatial position information of the rock drilling jumbo; first tunnel face point cloud data is obtained based on the first target point cloud model; a first tunnel face projection is determined through the first tunnel face point cloud data; and the rock drilling jumbo is controlled based on the first spatial position information and the first tunnel face projection, thereby realizing automatic operation of the rock drilling jumbo on the tunnel excavation project and improving engineering efficiency.

[0150] On the basis of the above-mentioned embodiments, variant embodiments of the above-mentioned embodiments are proposed. It should be noted that, in order to make the description brief, only the differences from the above-mentioned embodiments are described in the variant embodiments.

[0151] Reference Figure 3 , Figure 3 is a structure diagram of a rock drilling jumbo based on positioning of a surveying and mapping device provided in the embodiment of the application;

[0152] In an optional embodiment of the application, the rock drilling jumbo control is configured with a corresponding surveying and mapping device, and further comprises:

[0153] When it is determined that the drill jumbo is first operated on the excavation face, or the registration error is greater than a preset threshold, the surveying device is controlled to obtain calibration point coordinate information, and a reference model is constructed based on the calibration point coordinate information;

[0154] The first point cloud model and the reference model are used for registration to generate a second target point cloud model;

[0155] The second target point cloud model is converted into second engineering coordinate parameters, and the second engineering coordinate parameters are determined as second spatial position information of the drill jumbo;

[0156] Second stope face point cloud data are obtained based on the second target point cloud model;

[0157] A second stope face projection is determined through the second stope face point cloud data;

[0158] The drill jumbo is controlled through the second spatial position information and the second stope face projection.

[0159] In the first drilling operation, point cloud model registration and stope face projection generation are crucial steps, which lay the foundation for subsequent accurate drilling and safe construction.

[0160] Optionally, the method further comprises:

[0161] Noise points, abnormal points and outlier points of the first point cloud model are determined;

[0162] The noise points, the abnormal points and the outlier points are removed.

[0163] In actual application, there are two cases that require the surveying data obtained by the total station to be used for registration of the first point cloud model. The first case is the first excavation, and the second case is that after multiple excavations, the registration result is insufficient to meet the accuracy requirement. After registration of the first point cloud model and a second point cloud model generated in the last cycle operation, a registration error can be obtained, and the registration error is greater than a preset threshold, which can represent that the registration result is insufficient to meet the accuracy requirement. The third case is that the number of excavations is greater than a preset number threshold.

[0164] In specific implementation, since the first excavation does not have a point cloud model of the last cycle for registration, when it is determined that the drill jumbo is first operated on the excavation face, or the registration error is greater than a preset threshold, the surveying device is controlled to obtain calibration point coordinate information, and a reference model is constructed through the tunnel design data and the calibration point coordinate information of the total station.

[0165] The first point cloud model is converted into engineering coordinate parameters. By comparing the calibration point coordinate information of the total station and the engineering coordinate parameters generated by the conversion of the first point cloud model, the first point cloud model and the reference model are registered, and a second target point cloud model is generated. As known from the above, the second target point cloud model is the target point cloud model of the first round of excavation or the target point cloud model after the automatic positioning accuracy of the trolley needs to be corrected after multiple rounds of excavation. The second target point cloud model is converted into second engineering coordinate parameters, and the second engineering coordinate parameters are determined as the second spatial position information of the rock drilling trolley; the second target point cloud model is used to obtain second working face point cloud data; the second working face projection is determined through the second working face point cloud data; and the rock drilling trolley is controlled through the second spatial position information and the second working face projection.

[0166] It should be noted that the specific execution method of the above registration process, the target point cloud model generation process, the engineering coordinate parameter conversion process, the spatial position information determination process, the working face point cloud data acquisition process, the working face projection determination process, and the control process of the rock drilling trolley can be the same as the execution process of the rock drilling trolley when the first point cloud model and the second point cloud model generated in the last cycle are registered to generate a first target point cloud model; the first target point cloud model is converted into first engineering coordinate parameters, and the first engineering coordinate parameters are determined as the first spatial position information of the rock drilling trolley; the first target point cloud model is used to obtain first working face point cloud data; the first working face projection is determined through the first working face point cloud data; and the execution process of the rock drilling trolley is controlled through the first spatial position information and the first working face projection in the same way.

[0167] Exemplarily:

[0168] 1. Obtain point cloud data:

[0169] Use a laser radar scanner or other 3D scanning device to scan the tunnel space and obtain raw point cloud data.

[0170] Ensure that the point cloud data is of good quality, containing sufficient information and accuracy.

[0171] 2. Point cloud preprocessing:

[0172] Clean up the raw point cloud data (first point cloud model), remove noise, abnormal points and outliers.

[0173] Filter, simplify and splice the point cloud data as needed to obtain a high-quality point cloud model.

[0174] 3. Tunnel space registration:

[0175] Establish a reference model of the tunnel space, which can be a tunnel design drawing combined with calibration point coordinate information obtained by surveying and mapping devices including total stations, to establish a tunnel space model.

[0176] The acquired first point cloud data is registered with the reference model to make them as consistent as possible. Common registration methods include Iterative Closest Point (ICP) algorithm, point feature matching, etc.

[0177] 4. Face extraction:

[0178] Using the registered second target point cloud model, the face point cloud of the current excavation cycle is extracted. Common methods include normal calculation, curvature analysis, etc.

[0179] The face point cloud should accurately reflect the tunnel surface area that needs to be excavated.

[0180] 5. Face projection generation:

[0181] Based on the second target point cloud model, the second face point cloud data is obtained; the second face projection is determined through the second face point cloud data. The projection can be a plane projection or a curved surface projection, depending on the needs of the drilling operation.

[0182] The face projection should clearly and accurately show the shape and size of the face, providing a reference for the drilling operation.

[0183] 6. Visualization and quality control:

[0184] Visualize the point cloud model, face point cloud and face projection, check if the registration and extraction results meet the expectations.

[0185] Perform quality control to ensure the accuracy and reliability of the point cloud data and projection results.

[0186] Notes:

[0187] Since the first drilling operation has no ready-made face reference, special attention should be paid to the accuracy of the point cloud model registration.

[0188] The choice of face extraction and projection method should be based on the specific tunnel structure and construction requirements.

[0189] The point cloud data and projection results should be checked regularly to ensure that their data quality meets the construction needs.

[0190] In addition, existing drilling data or other auxiliary information can be used to assist point cloud model registration and face extraction.

[0191] For complex-shaped tunnels, more advanced registration algorithms and point cloud processing techniques can be used.

[0192] Professional point cloud processing software can be used to perform the above operations, which can improve efficiency and accuracy.

[0193] In an alternative embodiment of the present application, before the step of modeling the scanning of the excavation face by the laser radar, generating a first point cloud model for the current cycle of the excavation face, the method further comprises:

[0194] acquiring spatial position data of the drill jumbo in the relative coordinate system centered on the laser radar;

[0195] generating an initial position movement control signal based on the spatial position data;

[0196] controlling the drill jumbo to reach the position to be operated based on the initial position movement control signal.

[0197] In the field of automatic control of operation vehicles, when the vehicle reaches the vicinity of the target position, the vehicle-mounted laser radar is used to perceive the surrounding environment, and the spatial position data of the vehicle in the laser radar coordinate system obtained by the laser radar is used for automatic control.

[0198] The embodiment of the present application can make the vehicle carry a laser radar with a ranging error of millimeter level and an angle accuracy of 0.009°. Before operation, the spatial position data of the drill jumbo in the relative coordinate system centered on the laser radar can be calibrated. After acquiring the spatial position data of the drill jumbo in the relative coordinate system centered on the laser radar, an initial position movement control signal is generated based on the spatial position data, and the drill jumbo is controlled to reach the position to be operated based on the initial position movement control signal, thereby improving the operation efficiency.

[0199] In an alternative embodiment of the present application, the step of acquiring first working face point cloud data based on the first target point cloud model comprises:

[0200] determining a tunnel axis and a normal vector of each point of the first target point cloud model;

[0201] determining a tunnel included angle using the tunnel axis and the normal vector;

[0202] screening out working face target points with a tunnel included angle less than a preset angle threshold, and generating the first working face point cloud data using the working face target points.

[0203] Illustratively, the tunnel axis can be determined by the design data of the tunnel, for example:

[0204] Based on the cylindrical fitting method: the basic principle of this method is to fit the point cloud data to a cylinder, and then take the center axis of the cylinder as the tunnel axis.

[0205] Line fitting based on RANSAC method: the basic principle of this method is to randomly select three groups of points from the point cloud data using the RANSAC method, then calculate the straight line determined by the three groups of points, and select the straight line with the maximum support as the tunnel axis.

[0206] In addition to using the point neighborhood-based normal calculation method, other methods can also be used to calculate the normal, for example:

[0207] Curved surface fitting-based normal calculation method: the basic principle of this method is to fit the point cloud data to a curved surface, and then calculate the normal vector of the curved surface at each point.

[0208] Deep learning-based normal calculation method: this method can use a deep learning model to directly predict the normal vector of each point cloud point.

[0209] After determining the tunnel angle between the tunnel axis and the normal vector, the tunnel angle of the tunnel face target point less than the preset angle threshold is screened out, and the first tunnel face point cloud data is generated by using the tunnel face target point, for example, the normal information of the point cloud in the calculation model is calculated, and the point is considered to be a tunnel face target point when the tunnel angle between the normal and the tunnel axis is less than 25°. The first tunnel face point cloud data is generated by using the tunnel face target point, thereby improving the effectiveness and reliability of the first tunnel face point cloud data.

[0210] In an optional embodiment of the present application, the step of determining the first tunnel face projection through the first tunnel face point cloud data comprises:

[0211] Creating a plane based on the first tunnel face point cloud data; the normal vector of the points of the plane is perpendicular to the tunnel axis;

[0212] Determining the position of the plane on the tunnel axis by the least square method to determine the first tunnel face projection.

[0213] In a specific implementation, the embodiment of the present application can construct a plane perpendicular to the tunnel axis, and determine the position of the plane on the tunnel axis by the least square method, so that the distance from the tunnel face point to the plane reaches a minimum value, that is, the tunnel face projection plane parameters of the first tunnel face projection are obtained, thereby determining the first tunnel face projection.

[0214] In order for those skilled in the art to better understand the embodiments of the present application, the following describes the embodiments of the present application with an example.

[0215] Reference Figure 4 , Figure 4 is a step flow chart of another drill jumbo control method provided in the embodiments of the present application;

[0216] (1) The drill jumbo reaches the vicinity of the tunnel excavation face to prepare for drilling operation, and the laser radar installed on the jumbo has been calibrated, that is, the spatial position data of the jumbo in the relative coordinate system centered by the laser radar is calibrated.

[0217] (2) The three-dimensional laser radar carried by the jumbo performs scanning modeling to collect the point cloud model of the tunnel near the excavation face.

[0218] Reference Figure 5 , Figure 5 is a kind of jumbo space state structure schematic diagram provided in the embodiment of the application;

[0219] (3) When the first drilling operation or the automatic positioning accuracy of the jumbo needs to be corrected, the calibration point coordinates of the drill jumbo are measured by using a total station instrument to determine the spatial position information of the drill jumbo, and the three-dimensional laser point cloud model is converted to the engineering coordinate system.

[0220] (4) When the first drilling operation or the automatic positioning accuracy of the jumbo does not need to be corrected, the point cloud model collected this time is registered with the point cloud model of the last cycle (which has been converted to the engineering coordinate system). Since the two point clouds are collected at different excavation positions, the excess part of the point cloud model this time can be removed after the first registration, and secondary registration is performed to further reduce the registration error of the model.

[0221] (5) The spatial position information of the drill jumbo is determined based on the registration parameters of the point cloud model.

[0222] (6) The point cloud of the tunnel face is extracted, and a projection plane perpendicular to the tunnel axis is established. The least square method or other methods can be used to calculate the projection plane parameters of the tunnel face.

[0223] (7) The position of the drilling hole in the point cloud model of the tunnel face is determined autonomously according to the design parameters.

[0224] (8) The drill jumbo has an automatic control function of the drilling mechanical arm, and controls the drilling mechanical arm to reach the drilling position based on its own spatial information to carry out drilling operation.

[0225] Through the above-mentioned manner, the following beneficial effects are achieved:

[0226] (1) Only auxiliary measurement positioning is needed when positioning correction is performed after the first drilling or multiple drilling operations, which avoids measuring and lofting every time, and greatly reduces the measurement workload.

[0227] (2) The drilling position is determined based on the high-precision three-dimensional point cloud model of the tunnel face, and the drilling positioning accuracy is higher.

[0228] (3) The autonomous positioning of the drill jumbo can be realized, the positioning method is simple, no auxiliary target needs to be set in the environment, and no various angle sensors need to be set on the jumbo body.

[0229] It should be noted that, for the method embodiments, the series of acts described is merely an example, and the present embodiments are not limited to the order of the acts described. Further, some of the acts described can be performed at the same time, or in a different order than that described. Moreover, some of the acts described can be optional. It should also be noted that the embodiments described are merely exemplary, and the present embodiments are not limited to the acts described.

[0230] Referring to Figure 6 , a structural block diagram of a drill jumbo control device provided by an embodiment of the present application is shown, and can specifically include the following modules:

[0231] A first point cloud model generation module 601 is configured to model scanning of a working face by the laser radar, and generate a first point cloud model for the working face for the current cycle;

[0232] A first target point cloud model generation module 602 is configured to, when it is determined that the drill jumbo is not working on the working face for the first time, register the first point cloud model and a second point cloud model generated in the last cycle to generate a first target point cloud model;

[0233] A first spatial position information determination module 603 is configured to convert the first target point cloud model into first engineering coordinate parameters, and determine the first engineering coordinate parameters as first spatial position information of the drill jumbo;

[0234] A first working face point cloud data acquisition module 604 is configured to acquire first working face point cloud data based on the first target point cloud model;

[0235] A first working face projection determination module 605 is configured to determine a first working face projection through the first working face point cloud data;

[0236] A drill jumbo control module 606 is configured to control the drill jumbo through the first spatial position information and the first working face projection.

[0237] For the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts refer to the part of the description of the method embodiments.

[0238] In addition, an electronic device is also provided by the embodiments of the present application, which includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the processes of the above-mentioned drill jumbo control method embodiments are implemented, and the same technical effects are achieved. To avoid repetition, no further description is given here.

[0239] The embodiment of the present application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, the computer program is executed by a processor to realize each process of the rock drilling jumbo control method embodiment and achieve the same technical effects, and details are not repeated here. The computer readable storage medium includes a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0240] Figure 7 A hardware structure schematic diagram of an electronic device for implementing various embodiments of the present application.

[0241] The electronic device 700 includes, but is not limited to, a radio frequency unit 701, a network module 702, an audio output unit 703, an input unit 704, a sensor 705, a display unit 706, a user input unit 707, an interface unit 708, a memory 709, a processor 710, and a power supply 711, etc. Those skilled in the art can understand that the electronic device structure shown in the figure is not a limitation on the electronic device, and the electronic device can include more or fewer components than the figure, or combine certain components, or different component arrangements. In the embodiments of the present application, the electronic device includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle terminal, a wearable device, and a pedometer, etc. Figure 7 The electronic device structure shown in the figure is not a limitation on the electronic device, and the electronic device can include more or fewer components than the figure, or combine certain components, or different component arrangements. In the embodiments of the present application, the electronic device includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle terminal, a wearable device, and a pedometer, etc.

[0242] It should be understood that in the embodiments of the present application, the radio frequency unit 701 can be used for receiving and sending signals in the process of information or call, specifically, receiving downlink data from a base station and processing it by the processor 710; in addition, sending uplink data to the base station. Generally, the radio frequency unit 701 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, etc. In addition, the radio frequency unit 701 can also communicate with the network and other devices through a wireless communication system.

[0243] The electronic device provides wireless broadband Internet access for users through the network module 702, such as helping users to send and receive emails, browse web pages and access streaming media, etc.

[0244] The audio output unit 703 can convert audio data received by the radio frequency unit 701 or the network module 702 or stored in the memory 709 into an audio signal and output as a sound. Moreover, the audio output unit 703 can also provide audio output related to a specific function performed by the electronic device 700 (for example, a call signal receiving sound, a message receiving sound, etc.). The audio output unit 703 includes a speaker, a buzzer, and a receiver, etc.

[0245] The input unit 704 is configured to receive audio or video signals. The input unit 704 can include a graphic processing unit (GPU) 7041 and a microphone 7042. The graphic processing unit 7041 processes image data of a still picture or a video obtained by an image capture apparatus (e.g., a camera) in a video capture mode or an image capture mode. The processed image frame can be displayed on the display unit 706. The image frame processed by the graphic processing unit 7041 can be stored in the memory 709 (or other storage medium) or transmitted via the radio frequency unit 701 or the network module 702. The microphone 7042 can receive sound, and is capable of processing such sound as audio data. The processed audio data can be converted into a format transmittable to a mobile communication base station via the radio frequency unit 701 in the case of a telephone call mode.

[0246] The electronic device 700 further includes at least one sensor 705, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display panel 7061 according to the brightness of ambient light, and the proximity sensor can turn off the display panel 7061 and / or the backlight when the electronic device 700 is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), and when at rest, can detect the magnitude and direction of gravity, and can be used to identify the electronic device posture (such as screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, knock), and the like. The sensor 705 can also include a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, and the like, which are not described herein.

[0247] The display unit 706 is configured to display information input by a user or information provided to the user. The display unit 706 can include a display panel 7061, which can be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0248] The user input unit 707 can be used to receive inputted digital or character information, and to generate key signal input related to user settings of the electronic device and control of functions. Specifically, the user input unit 707 includes a touch panel 7071 and other input devices 7072. The touch panel 7071, also called a touch screen, can collect a user's touch operation (such as a user's operation on or near the touch panel 7071 using a finger, a stylus, or any suitable object or accessory) on or near it. The touch panel 7071 can include two parts, a touch detection device and a touch controller. The touch detection device detects the user's touch position and detects a signal caused by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into touch coordinates, and sends it to the processor 710, receives commands from the processor 710 and executes them. In addition, the touch panel 7071 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 7071, the user input unit 707 can also include other input devices 7072. Specifically, the other input devices 7072 can include, but are not limited to, a physical keyboard, function keys (such as volume control buttons, on / off buttons, etc.), trackballs, mice, joysticks, and the like, which will not be described here.

[0249] Further, the touch panel 7071 can be overlaid on the display panel 7061, and when the touch panel 7071 detects a touch operation on or near it, it transmits to the processor 710 to determine the type of touch event, and then the processor 710 provides corresponding visual output on the display panel 7061 according to the type of touch event. Although in the Figure 7 In some embodiments, the touch panel 7071 and the display panel 7061 can be integrated to realize the input and output functions of the electronic device, which is not limited here.

[0250] The interface unit 708 is an interface for connecting external devices to the electronic device 700. For example, the external devices can include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input / output (I / O) port, a video I / O port, a headphone port, and the like. The interface unit 708 can be used to receive input (e.g., data information, power, etc.) from external devices and transmit the received input to one or more elements within the electronic device 700, or can be used to transmit data between the electronic device 700 and external devices.

[0251] The memory 709 is used to store software programs and various data. The memory 709 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, application programs (such as a sound playing function, an image playing function, etc.) required by at least one function, etc.; and the data storage area can store data (such as audio data, a phone book, etc.) created according to the use of the mobile phone, etc. In addition, the memory 709 can include a high-speed random access memory, and can also include a nonvolatile memory, for example, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state memory device.

[0252] The processor 710 is the control center of the electronic device, connects all parts of the electronic device through various interfaces and lines, executes various functions of the electronic device and processes data by running or executing software programs and / or modules stored in the memory 709 and calling data stored in the memory 709, and thus monitors the whole electronic device. The processor 710 can include one or more processing units; preferably, the processor 710 can integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and application programs, etc., and the modem processor mainly processes wireless communication. It can be understood that the above-mentioned modem processor can also not be integrated into the processor 710.

[0253] The electronic device 700 can also include a power supply 711 (such as a battery) for supplying power to various components; preferably, the power supply 711 can be logically connected to the processor 710 through a power management system, so as to realize the functions of managing charging, discharging, and power consumption management, etc. through the power management system.

[0254] In addition, the electronic device 700 includes some functional modules which are not shown and will not be described herein.

[0255] It should be noted that, in this document, the term "comprising" or "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article, or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such a process, method, article, or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of additional identical elements in the process, method, article, or device including the element.

[0256] Those skilled in the art can clearly understand that the above-mentioned embodiment method can be realized by means of software and necessary general hardware platform, of course, it can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes a plurality of instructions for making a terminal (which can be a mobile phone, computer, server, air conditioner, or network device) execute the method described in each embodiment of the present application.

[0257] As shown in the above description of the embodiments of the present application, in another embodiment of the present application, a computer readable storage medium 801 is provided, and the computer readable storage medium 801 stores instructions, which, when executed on a computer, cause the computer to perform the rock drilling jumbo control method described in the above embodiments. Figure 8

[0258] The embodiment of the present application also discloses a rock drilling jumbo, which comprises:

[0259] one or more processors;

[0260] and one or more machine readable media having stored thereon instructions that, when executed by the one or more processors, cause the rock drilling jumbo to perform one or more of the methods described above.

[0261] The embodiments of the present application are described above in combination with the drawings, but the present application is not limited to the above-mentioned specific embodiments, and the above-mentioned specific embodiments are only illustrative, not restrictive, and those skilled in the art can make many forms under the inspiration of the present application without departing from the purpose of the present application and the scope protected by the claims, which all belong to the protection of the present application.

[0262] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in the embodiments of the present application can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solutions. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0263] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-mentioned system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0264] ​In the embodiments of the present application, it should be understood that the disclosed apparatus and method can be implemented in other manners. For example, the described apparatus embodiments are merely schematic. The units as divided can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0265] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purposes of the embodiments of the present application.

[0266] In addition, each functional unit in the various embodiments of the present application can be integrated into a processing unit, or each unit can be a physically independent unit, or two or more units can be integrated into one unit.

[0267] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts of the present application that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a ROM, a RAM, a magnetic disk or an optical disk, and various program code storage media.

[0268] The above is merely specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A drilling rig control method, characterized in that: The drilling rig control configuration is equipped with a laser radar, including: Scanning and modeling the excavation surface using the laser radar to generate a first point cloud model of the excavation surface in this cycle; When it is determined that this is not the first operation of the drilling rig on the excavation surface, the first point cloud model and the second point cloud model generated in the previous cycle of operation are aligned to generate a first target point cloud model; the first point cloud model and the second point cloud model are point cloud models for different excavation surfaces; Converting the first target point cloud model into first engineering coordinate parameters, and determining the first engineering coordinate parameters as first spatial position information of the drilling rig; Acquiring first tunnel face point cloud data based on the first target point cloud model; Determining a first tunnel face projection using the first tunnel face point cloud data; The drilling rig is controlled using the first spatial position information and the first tunnel face projection.

2. The method according to claim 1, characterized in that The drilling rig control configuration is equipped with a corresponding surveying and mapping device, and also includes: When it is determined that the drilling rig is operating on the excavation surface for the first time, or the registration error is greater than a preset threshold, controlling the surveying and mapping device to obtain calibration point coordinate information, and constructing a reference model based on the calibration point coordinate information; Using the first point cloud model and the reference model for registration to generate a second target point cloud model; Converting the second target point cloud model into second engineering coordinate parameters, and determining the second engineering coordinate parameters as second spatial position information of the drilling rig; Acquiring second tunnel face point cloud data based on the second target point cloud model; Determining a second tunnel face projection using the second tunnel face point cloud data; The drilling rig is controlled using the second spatial position information and the second tunnel face projection.

3. The method according to claim 2, characterized in that Before the step of scanning and modeling the excavation surface by the laser radar to generate a first point cloud model of the excavation surface in this cycle, the method further includes: Acquire and calibrate spatial position data of the drilling rig in a relative coordinate system centered on the laser radar; generating an initial position movement control signal based on the spatial position data; The drilling rig is controlled to reach a waiting position for operation based on the initial position movement control signal.

4. The method according to claim 2, characterized in that Also includes: Determining noise points, abnormal points, and outliers of the first point cloud model; Eliminate the noise points, abnormal points and outliers.

5. The method according to claim 1, characterized in that The step of acquiring first tunnel face point cloud data based on the first target point cloud model includes: determining a normal vector between the tunnel axis and each point of the first target point cloud model; Determining a tunnel angle using the tunnel axis and the normal vector; The tunnel face target points whose tunnel angle is less than a preset angle threshold are screened out, and the first tunnel face point cloud data are generated by using the tunnel face target points.

6. The method according to claim 5, characterized in that The step of determining the first tunnel face projection by using the first tunnel face point cloud data includes: Creating a plane based on the first tunnel face point cloud data; the normal vectors of the points on the plane are perpendicular to the tunnel axis; The position of the plane on the tunnel axis is determined by the least square method to determine the first tunnel face projection.

7. The method according to claim 1, characterized in that Also includes: When the drilling rig is operating, if a specific target is detected within a preset safety range, the drilling rig is controlled to stop and an alarm message is generated.

8. A rock drilling rig control device, characterized in that: The drilling rig control configuration is equipped with a laser radar, including: A first point cloud model generating module is configured to scan and model the excavation surface using the laser radar, and generate a first point cloud model of the excavation surface in this cycle; a first target point cloud model generating module configured to, when determining that this is not the first operation of the drilling rig on the excavation surface, align the first point cloud model with the second point cloud model generated during the previous cycle of operation to generate a first target point cloud model; the first point cloud model and the second point cloud model are point cloud models for different excavation surfaces; a first spatial position information determining module, configured to convert the first target point cloud model into first engineering coordinate parameters, and determine the first engineering coordinate parameters as first spatial position information of the drilling rig; A first tunnel face point cloud data acquisition module, configured to acquire first tunnel face point cloud data based on the first target point cloud model; A first tunnel face projection determination module, configured to determine a first tunnel face projection using the first tunnel face point cloud data; A drilling rig control module is configured to control the drilling rig using the first spatial position information and the first tunnel face projection.

9. An electronic device, characterized in that: comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; The memory is used to store computer programs; The processor is configured to implement the method according to any one of claims 1 to 7 when executing a program stored in the memory.

10. A computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform the method according to any one of claims 1 to 7.

11. A rock drilling rig, characterized in that: include: one or more processors; and One or more machine-readable media having instructions stored thereon, when executed by the one or more processors, cause the drilling rig to perform the method of any one of claims 1-7.

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