A method and system for real-time measurement of a ball bit wear value of a down-the-hole drill

Abstract

This invention relates to the field of down-the-hole (DH) drill bit wear measurement technology, specifically a method and system for real-time measurement of DH drill bit wear values. The method involves optimizing and registering an initial three-dimensional model to obtain the overall quantitative wear value of the DH drill bit; analyzing the mapping relationship between drilling parameters and the overall quantitative wear value, and constructing a database of drilling parameters and drill bit wear values; deriving dimensionless variables based on dimensional analysis methods and the database, and combining and filtering these variables with second-order polynomials and cross terms to determine the combination of dimensionless variables affecting drill bit wear; and substituting this combination of dimensionless variables into a multiple linear regression model to establish a mathematical relationship model between drill bit wear and drilling parameters, thereby achieving real-time measurement of the DH drill bit wear value. This invention, based on dimensional analysis to obtain dimensionless variables of drilling parameters and combined with multiple linear regression to construct a model for real-time measurement of DH drill bit wear values, improves construction efficiency and safety.

Description

Technical Field

[0001] This invention relates to the field of down-the-hole drill bit wear measurement technology, specifically a method and system for real-time measurement of wear value of down-the-hole drill bit. Background Technology

[0002] In open-pit mining, geological exploration, and other engineering fields, down-the-hole (DH) drilling rigs determine operational efficiency and construction safety, significantly impacting overall project progress and costs. DH drill bit wear affects drilling accuracy, leading to issues such as borehole position deviations and non-compliant hole diameters. It also impacts drilling speed, with severely worn drill bits drastically reducing drilling efficiency. Furthermore, drill bit wear is closely linked to equipment energy consumption, maintenance costs, and operational safety. As drill bit wear intensifies, the equipment requires more energy to maintain drilling, increasing energy consumption. Simultaneously, rapid drill bit wear shortens its lifespan, increasing the frequency of drill bit replacements and thus raising maintenance costs. When drill bit wear is excessive, drilling efficiency drops sharply, the risk of stuck drill increases significantly, and in extreme cases, it may even cause equipment damage, resulting in serious safety accidents and economic losses.

[0003] Currently, the industry's methods for monitoring the wear value of down-the-hole drilling rig bits are significantly insufficient, making it difficult to meet the real-time and precise needs of engineering sites. The current monitoring methods mainly rely on offline manual inspection. After the machine is stopped during the working interval, the diameter of the drill bit is measured using special equipment or the wear status of the alloy teeth is observed by the naked eye. This method cannot capture the dynamic changes in drill bit wear during drilling in real time, but can only obtain the static wear situation at the time of shutdown. It cannot reflect the wear trend of the drill bit during continuous operation in a timely manner, and it is difficult to provide an effective basis for dynamic adjustments during construction.

[0004] Some estimates are based on empirical formulas, combined with parameters such as rock hardness and drilling time to estimate the wear of the drill bit. However, in actual working conditions, geological conditions are complex and variable, rock hardness is unevenly distributed, and the drilling process is affected by a variety of factors, resulting in a large deviation between the estimated wear and the actual value, which cannot accurately reflect the true wear condition of the drill bit.

[0005] Based on the technical problems in obtaining the wear value of down-the-hole drill bits mentioned above, a practical solution is needed to achieve real-time and accurate monitoring of the wear value of ball tooth drill bits in down-the-hole drills, thereby ensuring the efficient and safe progress of the project. Summary of the Invention

[0006] To address the shortcomings of existing methods and the limitations of practical applications, in the operation process of down-the-hole drilling rigs, the wear state of the drill bit is in a dynamic evolution process due to the continuous interaction between the drill bit and the rock. In order to capture the dynamic changes of drill bit wear in real time during drilling, the wear value of the ball tooth drill bit of the down-the-hole drilling rig is measured in real time, reducing the deviation between the wear estimate and the actual wear value, and effectively presenting the true wear condition of the drill bit. In a first aspect, this invention provides a method for real-time measurement of wear value of ball-tooth drill bits in down-the-hole (DHH) drilling rigs. The method includes the following steps: constructing an initial three-dimensional model of the ball-tooth drill bit based on full-size three-dimensional laser scanning information; optimizing and registering the initial three-dimensional model to obtain the overall wear quantification value of the ball-tooth drill bit; obtaining the drilling parameters of the ball-tooth drill bit; analyzing the mapping relationship between the drilling parameters and the overall wear quantification value; constructing a database between the drilling parameters and the drill bit wear value based on the mapping relationship; deriving dimensionless variables based on dimensional analysis methods and the database; introducing second-order polynomials and cross terms to combine and screen the dimensionless variables, and determining the combination of dimensionless variables affecting drill bit wear; substituting the combination of dimensionless variables into a multiple linear regression model to establish a mathematical relationship model between drill bit wear and drilling parameters; and using the mathematical relationship model to achieve real-time measurement of the wear value of the ball-tooth drill bit in a DHHH drilling rig.

[0007] The dimensional analysis method of this invention can transform drilling parameters and drill bit wear values ​​with different dimensions into dimensionless variables, eliminating the influence of dimensions on the model. The mathematical model has a wider range of applicability, is not limited by specific measurement units and magnitudes, and can be applied and promoted in different engineering scenarios and equipment conditions, enabling the measurement method of this invention to more accurately reflect the actual situation.

[0008] Optionally, the step of constructing an initial 3D model of the down-the-hole drill ball-tooth bit based on full-size 3D laser scanning information, optimizing and registering the initial 3D model, and obtaining the overall wear quantification value of the down-the-hole drill ball-tooth bit includes: using a handheld 3D laser scanning device to perform a full-size 3D laser scan of the down-the-hole drill ball-tooth bit after each drilling operation to obtain full-size 3D laser scanning information; constructing an initial 3D model of the down-the-hole drill ball-tooth bit based on the full-size 3D laser scanning information; trimming and optimizing the initial 3D model to obtain an effective drill bit 3D model; selecting a standard ball-tooth drill bit 3D model of the same type, and registering and aligning the effective drill bit 3D model and the standard ball-tooth drill bit 3D model of the same type to obtain the target drill bit 3D model. The 3D model of this invention can comprehensively and accurately present the actual shape of the down-the-hole drill ball-tooth bit, providing a reference and analytical basis for subsequent wear analysis.

[0009] Optionally, the step of constructing an initial three-dimensional model of the down-the-hole drill bit based on full-size three-dimensional laser scanning information, optimizing and registering the initial three-dimensional model, and obtaining the overall wear quantification value of the down-the-hole drill bit includes: comparing the local areas of the alloy teeth in the target drill bit's three-dimensional model to obtain the wear quantification value of a single alloy tooth; and integrating the wear quantification values ​​of the single alloy teeth to obtain the overall wear quantification value of the down-the-hole drill bit. This invention analyzes the local areas of the alloy teeth, which is beneficial for accurately measuring the deformation and damage degree of the ball-tooth drill bit.

[0010] Optionally, the step of acquiring the drilling parameters of the down-the-hole (DOH) drill bit, analyzing the mapping relationship between the drilling parameters and the overall wear quantification value, and constructing a database between the drilling parameters and the drill bit wear value based on the mapping relationship includes: acquiring the drilling parameters of the DOH drill bit using a measurement-while-drilling (MSW) system; removing noise signals from the drilling parameters based on a data threshold to obtain valid data of the drilling parameters of the DOH drill bit; and performing cumulative averaging processing on the valid data of the drilling parameters to obtain target information of the drilling parameters of the DOH drill bit. This invention improves the efficiency and accuracy of data processing and provides a data foundation for subsequent drill bit wear prediction.

[0011] Optionally, the step of analyzing the mapping relationship between the drilling parameters and the overall wear quantification value, and constructing a database between the drilling parameters and the drill bit wear value based on the mapping relationship, includes: obtaining the depth range of the overall wear quantification value; performing a corresponding analysis on the target information of the drilling parameters and the overall wear quantification value with reference to the depth range to obtain the mapping relationship between the drilling parameters and the overall wear quantification value; and constructing a database between the drilling parameters and the drill bit wear value based on the mapping relationship. This invention further constructs a database based on the mapping relationship between the drilling parameters and the drill bit wear value, which can improve the reliability and accuracy of the data, thereby better reflecting the actual situation and providing a more reliable reference for drill bit wear prediction and construction decisions.

[0012] Optionally, deriving dimensionless variables based on the dimensional analysis method and the database includes: introducing implicit functional equations:

[0013] The implicit functional equation satisfies the following relationship:

[0014] ,

[0015] in, It is an implicit function equation. This represents the sum of the cumulative wear values ​​of the alloy teeth of the ball-tooth drill bit along its axial height. To accumulate drilling depth, For drilling speed, For drilling axial force, This is the drilling torque. To impact wind pressure, The impact frequency is defined as follows: a variable dimension matrix is ​​constructed based on the implicit function equation, the dimensional analysis method, and the database.

[0016] The implicit function equation of this invention can reflect the influence of complex interactions between different factors on drill bit wear, avoiding the limitations of single-factor analysis and making the research results closer to the actual situation.

[0017] Optionally, deriving dimensionless variables based on the dimensional analysis method and the database includes: deriving the dimensionless variable expression based on the variable dimensional matrix and the implicit function equation;

[0018] The dimensionless variable expression satisfies the following relationship:

[0019] ,

[0020] in, This represents the cumulative wear strength coefficient of the drill bit per unit drilling depth. This represents the sum of the cumulative wear values ​​of the alloy teeth of the ball-tooth drill bit along its axial height. To accumulate drilling depth, This is the drilling speed-impact frequency adaptation coefficient. For drilling speed, For the impact frequency, The torque-axial force-depth coupling factor. This is the drilling torque. For drilling axial force, The impact wind pressure-axial force-depth synergistic factor, To determine the impact wind pressure, the dimensionless variable is obtained using the aforementioned dimensionless variable expression and the aforementioned database.

[0021] This invention reflects the intrinsic relationship between various physical quantities based on the principle of dimensional analysis, and reveals the proportional relationship between the total cumulative wear value of the drill bit and the cumulative drilling depth. This allows for a clearer understanding of the intensity variation law of drill bit wear at different drilling depths.

[0022] Optionally, the step of introducing second-order polynomials and interaction terms to combine and screen the dimensionless variables and determine the combination of dimensionless variables affecting drill bit wear includes: establishing a model function between drill bit wear and drilling parameters based on the dimensionless variables; transforming the model function to obtain a logarithmic form model function; introducing second-order polynomials and interaction terms of the dimensionless variables; and combining and screening the second-order polynomials and interaction terms with the logarithmic form model function to determine the combination of dimensionless variables affecting drill bit wear. This invention introduces second-order polynomials and interaction terms, enabling the model function to capture the quadratic effects and interactions between dimensionless variables.

[0023] Optionally, the step of substituting the dimensionless variables into a multiple linear regression model to establish a mathematical relationship model between drill bit wear and drilling parameters, and using the mathematical relationship model to achieve real-time measurement of the wear value of the ball tooth drill bit of the down-the-hole drilling rig, includes:

[0024] The mathematical relation model satisfies the following relationship:

[0025] ,

[0026] in, This represents the sum of the cumulative wear values ​​of the alloy teeth of the ball-tooth drill bit along its axial height. To accumulate drilling depth, For drilling speed, For the impact frequency, This is the drilling torque. For drilling axial force, To impact wind pressure.

[0027] In actual drilling operations, this invention can quickly calculate the total cumulative wear value of the alloy teeth of the ball tooth drill bit along the axial height based on the real-time collected drilling parameters and mathematical relationship model. It can monitor the wear status of the drill bit in real time, detect potential wear problems in a timely manner, and avoid accidents such as reduced drilling efficiency and stuck drill bit caused by excessive wear of the drill bit.

[0028] Secondly, the present invention also provides a real-time measurement system for the wear value of ball-tooth drill bits in down-the-hole drilling rigs, which can efficiently execute the real-time measurement method for the wear value of ball-tooth drill bits in down-the-hole drilling rigs provided by the present invention. The system includes an input device, a processor, an output device, and a memory, wherein the input device, processor, output device, and memory are interconnected. The memory includes a computer-readable storage medium as described in the first aspect of the present invention, and the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to call the program instructions. The real-time measurement system for the wear value of ball-tooth drill bits in down-the-hole drilling rigs provided by the present invention has a compact structure, strong applicability, and greatly improves operating efficiency. Attached Figure Description

[0029] Figure 1 This is a flowchart of the real-time measurement method for the wear value of the ball tooth drill bit of the down-the-hole drilling rig according to the present invention;

[0030] Figure 2 This is a schematic diagram illustrating the process of obtaining the three-dimensional model of the target drill bit of the present invention;

[0031] Figure 3 This is a scatter plot showing the distribution of actual drill bit wear and predicted drill bit wear in the test set of this invention.

[0032] Figure 4 This is a schematic diagram of the structure of the real-time measurement system for the wear value of the ball tooth drill bit of the down-the-hole drill rig according to the present invention. Detailed Implementation

[0033] Specific embodiments of the present invention will now be described in detail. It should be noted that the embodiments described herein are for illustrative purposes only and are not intended to limit the invention. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that these specific details are not necessary to practice the invention. In other instances, well-known circuits, software, or methods have not been specifically described to avoid obscuring the invention.

[0034] Throughout this specification, references to "an embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with that embodiment or example is included in at least one embodiment of the invention. Therefore, the phrases "in an embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily refer to the same embodiment or example. Furthermore, specific features, structures, or characteristics can be combined in one or more embodiments or examples in any suitable combination and / or sub-combination. Moreover, those skilled in the art will understand that the illustrations provided herein are for illustrative purposes and are not necessarily drawn to scale.

[0035] Please see Figure 1 In the actual operation of down-the-hole drilling rigs, the drill bit continuously interacts with the rock, and its wear state is in a dynamic evolution process. Existing measurement methods are unable to accurately capture the dynamic changes in drill bit wear during drilling in real time, resulting in a large deviation between the estimated wear and the actual wear value, and failing to effectively present the true wear condition of the drill bit. To solve the above problems and limitations, this invention proposes a real-time measurement method for the wear value of ball-tooth drill bits for down-the-hole drilling rigs. The method includes the following steps:

[0036] S1. Construct an initial 3D model of the down-the-hole drill rig's ball tooth drill bit based on full-size 3D laser scanning information. Optimize and register the initial 3D model and obtain the overall wear quantification value of the down-the-hole drill rig's ball tooth drill bit. The implementation details are as follows:

[0037] First, a three-dimensional model of the target drill bit for a down-the-hole drilling rig ball tooth drill bit is constructed based on full-size three-dimensional laser scanning information.

[0038] The first step involves using a handheld 3D laser scanning device to perform a full-size 3D laser scan of the down-the-hole drill bit after each drilling operation to obtain full-size 3D laser scan information. In this embodiment, a handheld 3D laser scanning device is used to perform a comprehensive and detailed full-size 3D laser scan of the down-the-hole drill bit after each drilling operation. During the scanning process, it is necessary to ensure that the scanning device maintains a suitable distance and angle from the drill bit to obtain complete and accurate scan data, thereby obtaining full-size 3D laser scan information.

[0039] The second step is to construct an initial 3D model of the down-the-hole drill bit based on the full-size 3D laser scan information. Using the obtained full-size 3D laser scan information, existing 3D modeling software or algorithms are employed to generate an initial 3D model of the down-the-hole drill bit. This model should accurately represent the overall shape and structural features of the drill bit.

[0040] The third step is to trim and optimize the initial 3D model to obtain an effective drill bit 3D model. This involves trimming and optimizing the generated initial 3D model using relevant functions in model processing software to remove noise points, redundant data, and ineffective scan areas. In an optional embodiment, abnormal data points caused by environmental interference or equipment errors during scanning, as well as invalid scan parts unrelated to the actual drill bit structure, are removed, thus obtaining an effective drill bit 3D model. This improves the accuracy and usability of the 3D model.

[0041] The fourth step involves selecting a 3D model of a standard ball-tooth drill bit of the same type. The effective drill bit 3D model and the standard ball-tooth drill bit 3D model of the same type are then registered and aligned to obtain the target drill bit 3D model. In this embodiment, a standard ball-tooth drill bit 3D model of the same type as the drill bit to be tested is selected as the reference model. Using a 3D model registration algorithm or software tool, the trimmed and optimized effective drill bit 3D model is registered and aligned with the reference model. During the registration process, parameters such as the model's position and orientation are adjusted to ensure that the two models are completely consistent in their positional references within the 3D coordinate system, ultimately obtaining the target drill bit 3D model.

[0042] Furthermore, for the process of obtaining the 3D model of the target drill bit, please refer to [link to documentation]. Figure 2The process involves four steps: Step 1 trimming the initial 3D model to obtain the effective 3D model of the drill bit; Step 2 importing the target 3D model of the drill bit; Step 3 registering and aligning the effective 3D model of the drill bit based on the imported target 3D model of the drill bit; and Step 4 comparing the effective 3D model of the drill bit based on the target 3D model of the drill bit.

[0043] Then, obtain the overall wear quantification value of the ball tooth drill bit of the down-the-hole drilling rig.

[0044] The first step is to compare the local areas of the alloy teeth in the three-dimensional model of the target drill bit to obtain the wear quantification value of a single alloy tooth.

[0045] The embodiment is based on the registered and aligned 3D model of the target drill bit and the 3D model of the standard ball tooth drill bit. For each alloy tooth on the ball tooth drill bit under test, a 3D geometric morphology comparison is performed on its corresponding local 3D region. During the comparison process, professional 3D analysis software is used to accurately calculate the differences between the corresponding local regions of the two models. Simultaneously, for each alloy tooth, the maximum deviation value along the tooth tip normal is extracted from the local 3D comparison results, and this maximum deviation value is defined as the wear quantification value of a single alloy tooth, thereby accurately reflecting the wear degree of each alloy tooth.

[0046] The second step, integrating the wear quantification values ​​of individual alloy teeth, yields the overall wear quantification value of the down-the-hole drill bit. In other words, by integrating the wear quantification values ​​of individual alloy teeth, the overall wear quantification of the down-the-hole drill bit can be derived. In a specific embodiment, the wear quantification values ​​of all alloy teeth are summed, meaning the wear quantification values ​​of each alloy tooth are added together one by one. The summation result is the overall wear quantification value of the drill bit under test. This summation result comprehensively reflects the wear condition of the entire drill bit, thus providing crucial information for subsequent drill bit maintenance and replacement decisions.

[0047] S2. Obtain the drilling parameters of the ball-tooth drill bit of the down-the-hole drilling rig, analyze the mapping relationship between the drilling parameters and the overall wear quantification value, and construct a database between the drilling parameters and the drill bit wear value based on the mapping relationship. The specific implementation content is as follows:

[0048] First, obtain the target information of the drilling parameters for the ball-tooth drill bit of the down-the-hole drilling rig.

[0049] The first step is to use a measurement-while-drilling (MWD) system to obtain the drilling parameters of the ball-tooth drill bit of the down-the-hole drilling rig.

[0050] During down-the-hole drilling (DWD) operations, a measurement-while-drilling (MWD) system is used to collect various MWD parameters of the ball-tooth drill bit in real time. These parameters cover several key indicators, including cumulative drilling depth, which reflects the total distance the drill bit penetrates into the formation during drilling; drilling speed, which reflects the length the drill bit drills per unit time and is an important parameter for measuring drilling efficiency; drilling axial force, which is the axial force exerted on the drill bit in the drilling direction, has a significant impact on drill bit wear and rock breaking effect; drilling torque, which represents the torsional torque experienced by the drill bit during rotation and is closely related to the rotational stability and rock breaking capacity of the drill bit; impact air pressure, which reflects the pressure of compressed air during the operation of the impactor and directly affects the magnitude of impact energy; and impact frequency, which is the number of times the impactor strikes the drill bit per unit time, determines the frequency and intensity of the impact. In this embodiment, the above-mentioned MWD parameters can be obtained comprehensively and accurately, providing a rich data foundation for subsequent analysis and processing.

[0051] The second step involves removing noise signals from the drilling parameters based on data thresholds to obtain valid drilling parameter data for the ball-tooth drill bit of the down-the-hole drilling rig. During actual operation, operations such as changing drill pipes, stuck drill bits, and unloading drill pipes can generate abnormal signal interference, which can affect the accuracy and reliability of the drilling parameters. Therefore, it is necessary to perform noise signal removal processing on the collected drilling parameters based on a pre-set data threshold. In one optional embodiment, a reasonable threshold range is set, and abnormal data exceeding this range is judged and removed, retaining only the valid data closely related to the normal drilling process. During drill pipe changes, parameters such as drilling speed and drilling axial force may experience brief abnormal fluctuations; threshold judgment is used to remove abnormal data, thereby ensuring the accuracy and consistency of the data.

[0052] The third step is to perform cumulative averaging on the effective data of the drilling parameters to obtain the target information of the drilling parameters for the ball tooth drill bit of the down-the-hole drilling rig.

[0053] To further improve the stability and representativeness of the drilling parameter data, the effective data after noise removal is subjected to cumulative averaging. The specific calculation formula is as follows:

[0054] ,

[0055] in, The down-the-hole drilling rig's drilling parameters at the first... The cumulative average data of each data point For the k-th data point in the depth sequence, The down-the-hole drilling rig's drilling parameters at the first... Valid data for each data point This represents the total number of data points in the depth sequence. Cumulative averaging effectively smooths out random fluctuations in the data, yielding more accurate and stable drilling parameter target information, and providing reliable data for subsequent mapping relationship analysis.

[0056] Then, a database is established to link drilling parameters with drill bit wear values.

[0057] The first step is to obtain the depth range of the overall wear quantification value. In this embodiment, referring to the pre-acquired cumulative wear data, the depth range corresponding to the overall wear quantification value is determined, which forms the basis for analyzing the mapping relationship between drilling parameters and the overall wear quantification value.

[0058] The second step involves performing a correspondence analysis between the target information of the drilling parameters and the overall wear quantification value within a specified depth range to obtain the mapping relationship between the drilling parameters and the overall wear quantification value. In an optional embodiment, the cumulative average data within a specified depth range is averaged, and the calculated average value is mapped one-to-one with the wear data of the drill bit within that depth range. Through this correspondence analysis, the inherent connection and variation law between the drilling parameters and the overall wear quantification value can be clearly discovered. It may be found that as the cumulative drilling depth increases, the drilling speed gradually slows down, while the overall wear quantification value gradually increases, and there is a certain functional relationship between the two. Analyzing the mapping relationship provides an accurate theoretical basis for subsequent database construction.

[0059] The third step is to construct a database linking drilling parameters and drill bit wear values ​​based on the mapping relationship. During database creation, a reasonable data structure needs to be designed, clearly defining the meaning and type of each data field. Fields such as depth, cumulative drilling depth, drilling speed, drilling axial force, drilling torque, impact air pressure, impact frequency, and overall wear quantification value can be set. Then, the drilling parameters and overall wear quantification value data obtained through corresponding analysis are stored and managed according to the designed data structure.

[0060] Meanwhile, in order to improve the database's query efficiency and data management capabilities, appropriate data storage methods and indexing technologies can be adopted to provide strong data support for the operation optimization of down-the-hole drilling rigs and drill bit maintenance.

[0061] S3. Based on dimensional analysis methods and databases, dimensionless variables are derived. Second-order polynomials and cross terms are introduced to combine and screen the dimensionless variables, and the combination of dimensionless variables affecting drill bit wear is determined. The specific implementation details are as follows:

[0062] First, we analyze to obtain dimensionless variables.

[0063] The first step is to introduce implicit function equations.

[0064] In this embodiment, based on the principle of dimensional analysis, the cumulative wear of the ball tooth drill bit has a complex intrinsic relationship with multiple related variables. The above relationship can be expressed by an implicit function equation, which satisfies the following relationship:

[0065] ,

[0066] in, It is an implicit function equation. This represents the sum of the cumulative wear values ​​of the alloy teeth of the ball-tooth drill bit along its axial height. To accumulate drilling depth, For drilling speed, For drilling axial force, This is the drilling torque. To impact wind pressure, The impact frequency;

[0067] The total cumulative wear value of the alloy teeth of the ball tooth drill bit along the axial height, in millimeters. This reflects the overall wear level of the drill bit;

[0068] Cumulative drilling depth reflects the total distance the drill bit penetrates into the formation during drilling operations;

[0069] Drilling speed, which is the length of the drill bit that is drilled per unit time, is a key indicator for measuring drilling efficiency.

[0070] F-axis force in drilling refers to the axial force exerted on the drill bit in the drilling direction, which has a significant impact on the wear of the drill bit and the rock breaking effect.

[0071] Drilling torque represents the torsional moment experienced by the drill bit during rotation, and it is closely related to the rotational stability and breaking capacity of the drill bit.

[0072] The impact air pressure reflects the pressure of the compressed air when the impactor is working, and directly affects the magnitude of the impact energy.

[0073] Impact frequency, which is the number of times the impactor strikes the drill bit per unit time, determines the frequency and intensity of the impact.

[0074] The second step involves constructing a variable dimension matrix based on implicit functional equations, dimensional analysis methods, and a database. Based on the implicit functional equations and dimensional analysis methods, and in conjunction with the constructed database, the length is selected... ,quality and time Using the three physical quantities as the basic units, the variable dimension matrix of the functional relationship is constructed, and the relevant information is shown in Table 1.

[0075] Table 1. Variable Dimension Matrix Information Table

[0076]

[0077] The third step is to derive the dimensionless variable expression based on the dimensional matrix of the variables and the implicit functional equation. In the functional relationship of the down-the-hole drilling rig's drilling parameters, there are a total of 7 variables. Calculations show that the rank of the aforementioned dimensional matrix is ​​3. According to dimensional theory... Theorem, choosing the borehole diameter axial force and rotation degree As a fundamental physical quantity, using The theorem can be used to solve for the remaining four dimensionless variables ( The dimensionless variable expressions for the above four are as follows:

[0078] ,

[0079] in, This represents the cumulative wear strength coefficient of the drill bit per unit drilling depth. This represents the sum of the cumulative wear values ​​of the alloy teeth of the ball-tooth drill bit along its axial height. To accumulate drilling depth, This is the drilling speed-impact frequency adaptation coefficient. For drilling speed, For the impact frequency, The torque-axial force-depth coupling factor. This is the drilling torque. For drilling axial force, The impact wind pressure-axial force-depth synergistic factor, To impact wind pressure;

[0080] The cumulative wear strength coefficient of the drill bit per unit drilling depth has the physical meaning of characterizing the coupling relationship between the wear degree of the drill bit and the drilling depth, and reflects the relative magnitude of the cumulative axial wear of the alloy teeth when drilling a unit length of rock.

[0081] The drilling speed-impact frequency matching coefficient characterizes the dynamic matching relationship between drilling speed and impact frequency, reflecting the synergistic effect between the periodic action of impact load and drill bit feed speed.

[0082] The torque-axial force-depth coupling factor integrates the synergistic effects of drilling torque, axial force, and cumulative drilling depth, characterizing the mechanism by which the evolution of mechanical load with drilling depth affects drill bit wear during rock drilling.

[0083] The impact wind pressure-axial force-depth synergy factor, which correlates impact wind pressure, cumulative drilling depth and drilling axial force, reflects the matching relationship between the cumulative effect of impact load and axial force bearing capacity.

[0084] The fourth step involves obtaining dimensionless variables using dimensionless variable expressions and a database. By substituting the relevant data from the database into the aforementioned dimensionless variable expressions, the specific numerical values ​​of the dimensionless variables can be calculated, providing technical support and an information foundation for subsequent analysis and modeling.

[0085] Then, determine the combination of dimensionless variables that affect drill bit wear.

[0086] The first step is to establish a model function relating drill bit wear and drilling parameters based on dimensionless variables. Its expression is:

[0087] ,

[0088] in, This represents the sum of the cumulative wear values ​​of the alloy teeth of the ball-tooth drill bit along its axial height. To accumulate drilling depth, The proportionality coefficient for a combination of dimensionless variables. For drilling speed, For the impact frequency, Dimensionless variable Influence coefficient, This is the drilling torque. For drilling axial force, Dimensionless variable Influence coefficient, To impact wind pressure, Dimensionless variable The influence coefficients are shown in the model function, which intuitively demonstrates the potential relationship between drill bit wear and various dimensionless variables, providing technical support for further analysis.

[0089] The second step is to transform the model function to obtain a logarithmic form model function to facilitate subsequent data fitting analysis, which satisfies the following relationship:

[0090] ,

[0091] Logarithmic model functions can transform nonlinear relationships into linear ones, simplifying subsequent data processing and analysis.

[0092] Thirdly, to more comprehensively consider the complex relationships between dimensionless variables, this embodiment introduces second-order polynomials and cross terms corresponding to the dimensionless variables. The extended logarithmic form model function is shown below:

[0093] ,

[0094] The fourth step involves combining and screening second-order polynomials with cross terms and logarithmic model functions to determine the combination of dimensionless variables affecting drill bit wear.

[0095] In this embodiment, a dimensionless variable combination screening framework is adopted. With the help of the LightGBM machine learning model’s powerful ability to capture nonlinear relationships, the optimal combination of the dimensionless variable with its second-order polynomial and cross term is selected.

[0096] dimensionless variables ( Convert the logarithmic form to logarithmic form, and then apply the logarithmically transformed dimensionless variable ( By combining these terms, we obtain all the cross terms and the second-order polynomial, totaling 9 variables including the single variable itself.

[0097] LightGBM was used to model all nine variables. Bayesian optimization combined with leave-one-out cross-validation was employed, and the optimal model parameters of LightGBM were selected. The Bayesian optimization can intelligently search the parameter space to find the optimal parameter combination, while leave-one-out cross-validation can more accurately evaluate the model performance and avoid overfitting.

[0098] In this embodiment, a strategy of gradually eliminating individual polynomials or cross terms is adopted to reconstruct a simplified model, that is, to reconstruct the corresponding coefficients. By setting the variable to 0, the model is continuously simplified and variables with little impact on model performance are removed, thereby improving the model's simplicity and feasibility.

[0099] By comparing the evaluation indicators of all dimensionless variable combinations, such as mean squared error (MSE) and coefficient of determination (R2), the optimal combination of evaluation indicators is selected for the subsequent construction of a multiple linear regression model. This multiple linear regression model has a clear mathematical expression, which is convenient for theoretical analysis and practical application.

[0100] The above steps ultimately determine the combination of dimensionless variables that have a significant impact on drill bit wear, providing strong support for the accurate prediction and effective control of drill bit wear.

[0101] In one optional embodiment, a granite mine is used as a specific case study. First, a relevant database was constructed, and some of the data is shown in Table 2. Table 2 covers key information such as drilling depth, drilling speed, drilling axial force, drilling torque, impact air pressure, impact frequency, and drill bit wear.

[0102] Table 2: Partial Data from the Database

[0103]

[0104] In the data processing stage, the drill bit wear and corresponding measurement-while-drilling (MWD) data were divided, with drill bit 1 as an example, divided in a 7:3 ratio. Since drill bit wear is a continuous variable, to evaluate the differences in model accuracy and fit under multiple variable combinations, the root mean square error (RMSE) and goodness-of-fit (MOF) were selected in this embodiment. RMSE is used as an evaluation metric. The closer RMSE is to 0, the smaller the model error. The closer the value is to 1, the better the model fit. The RMSE and RMSE values ​​mentioned above indicate this. The calculation formulas are as follows:

[0105] ,

[0106] ,

[0107] In the LightGBM model parameter tuning process, the average RMSE calculated by leave-one-out cross-validation is used as the optimization index.

[0108] An experimental group was set up in the comparative experimental examples. and control group Experimental group Using the existing measurement-while-drilling data, the control group Based on the original data, the data such as axial force, torque, drilling speed, impact frequency, and air pressure are processed by averaging the cumulative values.

[0109] To reduce model complexity and explore the impact of various cross-term combinations on the model, the implementation example uses a stepwise elimination method, removing individual cross-terms or polynomials each time simplification is performed. Table 3 details the comprehensive performance evaluation results of the model under different model and variable combinations, where all variables represent all original dimensionless variables, and the optimal combination represents the optimal variable combination selected under the condition of adding polynomials and cross-terms.

[0110] Table 3. Overall performance evaluation results of the models under different model and variable combinations.

[0111]

[0112] As shown in Table 3, the cumulative average value was used as the model training data. The group outperformed the group using raw instantaneous data on both the training and test sets. This result fully demonstrates that instantaneous measurement-while-drilling data is insufficient to accurately assess the real-time wear of the drill bit, while cumulative averaging of drilling data can comprehensively consider previous wear levels, thereby improving the accuracy of the identification model.

[0113] After filtering the key polynomials and cross terms using the variable screening framework, four combinations of polynomials and cross terms were selected, namely: , , as well as At the same time, it retains to After adding this combined variable, the RMSE of the test set and The values ​​were 0.0499 and 0.9806 respectively, representing a 34.4% reduction in RMSE compared to the model with all variables. It improved by 3.4% and effectively reduced the overfitting of the model.

[0114] S4. Substitute the dimensionless variables into the multiple linear regression model to establish a mathematical relationship model between drill bit wear and drilling parameters. Use this mathematical relationship model to achieve real-time measurement of the wear value of the ball tooth drill bit of the down-the-hole drilling rig. The specific content is as follows:

[0115] When constructing the model, the key parameters involved were dimensionless to eliminate the influence of differences in the dimensions and orders of magnitude of different parameters on the model, thereby improving the accuracy and stability of the model. Next, by selecting the optimal combination of polynomials and cross terms, they were incorporated into the framework of a multiple linear regression model, based on which a mathematical relationship model between drill bit wear and drilling parameters was established.

[0116] Through a series of rigorous derivations and analyses, a mathematical model of the relationship between drill bit wear and drilling parameters was obtained, which satisfies the following relationship:

[0117] ,

[0118] in, This represents the sum of the cumulative wear values ​​of the alloy teeth of the ball-tooth drill bit along its axial height. To accumulate drilling depth, For drilling speed, For the impact frequency, This is the drilling torque. For drilling axial force, To impact wind pressure.

[0119] The mathematical relationship model between drill bit wear and drilling parameters was further examined, and the relevant content is as follows:

[0120] In an optional embodiment, the wear value of the ball tooth drill bit of the down-the-hole drilling rig is measured in real time by using a mathematical relationship model between drill bit wear and drilling parameters according to the following steps.

[0121] Data acquisition: During drilling, various drilling parameters, including cumulative drilling depth, are collected in real time. Drilling speed Impact frequency Drilling torque Drilling axial force and impact wind pressure .

[0122] Dimensionless processing: Based on the dimensionless form of each parameter in the model, the collected raw data is calculated and processed accordingly to obtain... , , Dimensionless variables.

[0123] Substitution into the model for calculation: Substitute the processed dimensionless variables into the above mathematical relationship model, and obtain the result through calculation. The value of .

[0124] Solve for wear values: For By performing the inverse operation, the total cumulative wear value of the alloy teeth of the ball tooth drill bit along the axial height can be obtained, thus realizing the real-time measurement of the drill bit wear value.

[0125] The above methods can utilize the mathematical relationship model between drill bit wear and drilling parameters to measure the wear value of ball-tooth drill bits in real time and accurately during down-the-hole drilling operations, providing strong support for the optimization and adjustment of drilling parameters and the maintenance and management of equipment.

[0126] Further analysis of the cross-validation RMSE of the mathematical relationship model between drill bit wear and drilling parameters. The values ​​are 0.0526 and 0.9881, respectively. A scatter plot of the actual drill bit wear and predicted drill bit wear on the test set is also presented. Figure 3 The RMSE of the mathematical relational model on the test set and The values ​​are 0.0540 and 0.9779, respectively.

[0127] Please see Figure 4 In an optional embodiment, the present invention also provides a real-time measurement system for the wear value of ball-tooth drill bits in down-the-hole drilling rigs. This system includes a processor, an input device, an output device, and a memory, all interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to call the program instructions and execute the specific steps of the real-time measurement method and related embodiments for the wear value of ball-tooth drill bits in down-the-hole drilling rigs provided by the present invention. The real-time measurement system for the wear value of ball-tooth drill bits in down-the-hole drilling rigs provided by the present invention is structurally complete and objectively stable.

[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for real-time measurement of wear value of ball tooth drill bit in down-the-hole drilling rig, characterized in that, Includes the following steps: An initial three-dimensional model of the ball tooth drill bit of the down-the-hole drilling rig is constructed based on full-size three-dimensional laser scanning information. The initial three-dimensional model is then optimized and registered, and the overall wear quantification value of the ball tooth drill bit of the down-the-hole drilling rig is obtained. Obtain the drilling parameters of the ball tooth drill bit of the down-the-hole drilling rig, analyze the mapping relationship between the drilling parameters and the overall wear quantification value, and construct a database between the drilling parameters and the drill bit wear value based on the mapping relationship; Dimensionless variables are derived based on the dimensional analysis method and the database. Second-order polynomials and cross terms are introduced to combine and screen the dimensionless variables, and the combination of dimensionless variables affecting drill bit wear is determined. Substitute the combination of the dimensionless variables into the multiple linear regression model to establish a mathematical relationship model between drill bit wear and drilling parameters, and use the mathematical relationship model to realize the real-time measurement of the wear value of the ball tooth drill bit of the down-the-hole drilling rig; The mathematical relation model satisfies the following relationship: ， in, This represents the sum of the cumulative wear values ​​of the alloy teeth of the ball-tooth drill bit along its axial height. To accumulate drilling depth, For drilling speed, For the impact frequency, This is the drilling torque. For drilling axial force, To impact wind pressure.

2. The method for real-time measurement of wear value of ball tooth drill bit of down-the-hole drill rig according to claim 1, characterized in that, The process of constructing an initial 3D model of the down-the-hole drill bit based on full-size 3D laser scanning information, optimizing and registering the initial 3D model, and obtaining the overall wear quantification value of the down-the-hole drill bit includes: A handheld 3D laser scanning device was used to perform a full-size 3D laser scan of the ball tooth drill bit of the down-the-hole drill after each drilling operation to obtain full-size 3D laser scan information; An initial three-dimensional model of the ball tooth drill bit for down-the-hole drilling rig is constructed based on the full-size three-dimensional laser scanning information. The initial 3D model is trimmed and optimized to obtain an effective 3D model of the drill bit; Select a 3D model of a standard ball tooth drill bit of the same type, and register and align the effective drill bit 3D model with the standard ball tooth drill bit 3D model of the same type to obtain the target drill bit 3D model.

3. The method for real-time measurement of wear value of ball tooth drill bit of down-the-hole drill rig according to claim 2, characterized in that, The process of constructing an initial 3D model of the down-the-hole drill bit based on full-size 3D laser scanning information, optimizing and registering the initial 3D model, and obtaining the overall wear quantification value of the down-the-hole drill bit includes: The wear quantification value of a single alloy tooth is obtained by comparing the local area of ​​the alloy tooth in the three-dimensional model of the target drill bit; The overall wear quantification value of the ball tooth drill bit of the down-the-hole drill rig is obtained by integrating the wear quantification value of the individual alloy teeth.

4. The method for real-time measurement of wear value of ball tooth drill bit of down-the-hole drilling rig according to claim 1, characterized in that, The process of acquiring the drilling parameters of the ball-tooth drill bit of a down-the-hole drilling rig, analyzing the mapping relationship between the drilling parameters and the overall wear quantification value, and constructing a database between the drilling parameters and the drill bit wear value based on the mapping relationship includes: The drilling parameters of the ball-tooth drill bit of the down-the-hole drilling rig are obtained using the measurement-while-drilling system. Based on the data threshold, noise signals are removed from the drilling parameters to obtain the effective drilling parameter data of the ball tooth drill bit of the down-the-hole drilling rig; The target information of the drilling parameters for the ball-tooth drill bit of the down-the-hole drilling rig is obtained by averaging the effective data of the drilling parameters.

5. The method for real-time measurement of wear value of ball tooth drill bit of down-the-hole drill rig according to claim 4, characterized in that, The step of analyzing the mapping relationship between the drilling parameters and the overall wear quantification value, and constructing a database between the drilling parameters and the drill bit wear value based on the mapping relationship, includes: The depth range for obtaining the overall wear quantification value; By referring to the depth range, the corresponding analysis of the drilling parameter target information and the overall wear quantification value is performed to obtain the mapping relationship between the drilling parameters and the overall wear quantification value; A database is constructed based on the mapping relationship between drilling parameters and drill bit wear values.

6. The method for real-time measurement of wear value of ball tooth drill bit of down-the-hole drilling rig according to claim 1, characterized in that, The derivation of dimensionless variables based on the dimensional analysis method and the database includes: Introducing implicit function equations; The implicit functional equation satisfies the following relationship: ， in, It is an implicit function equation. This represents the sum of the cumulative wear values ​​of the alloy teeth of the ball-tooth drill bit along its axial height. To accumulate drilling depth, For drilling speed, For drilling axial force, This is the drilling torque. To impact wind pressure, The impact frequency; A variable dimension matrix is ​​constructed based on the implicit function equation, the dimensional analysis method, and the database.

7. The method for real-time measurement of wear value of ball tooth drill bit of down-the-hole drill rig according to claim 6, characterized in that, The derivation of dimensionless variables based on the dimensional analysis method and the database includes: Based on the variable dimension matrix and the implicit function equation, the dimensionless variable expression is derived; The dimensionless variable expression satisfies the following relationship: ， in, This represents the cumulative wear strength coefficient of the drill bit per unit drilling depth. This represents the sum of the cumulative wear values ​​of the alloy teeth of the ball-tooth drill bit along its axial height. To accumulate drilling depth, This is the drilling speed-impact frequency adaptation coefficient. For drilling speed, For the impact frequency, The torque-axial force-depth coupling factor. This is the drilling torque. For drilling axial force, The impact wind pressure-axial force-depth synergistic factor, To impact wind pressure; Dimensionless variables are obtained using the dimensionless variable expression and the database.

8. The method for real-time measurement of wear value of ball tooth drill bit of down-the-hole drill rig according to claim 7, characterized in that, The process of introducing second-order polynomials and cross terms to combine and screen the dimensionless variables, and determining the combination of dimensionless variables affecting drill bit wear, includes: A model function relating drill bit wear and drilling parameters is established based on the dimensionless variables described above; The model function is transformed to obtain the logarithmic form model function; Introduce dimensionless variables, second-order polynomials, and cross terms; The combination of dimensionless variables affecting drill bit wear is determined by combining and screening the second-order polynomial and cross terms with the logarithmic model function.

9. A real-time measurement system for the wear value of ball-tooth drill bits in a down-the-hole drill rig, characterized in that, The system includes a processor, an input device, an output device, and a memory, which are interconnected. The memory stores a computer program, which includes program instructions. The processor is configured to invoke the program instructions to execute the real-time measurement method for the wear value of the ball tooth drill bit of a down-the-hole drill as described in any one of claims 1-8.

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