High-wind-pressure rock drilling tooth performance testing method and system based on noise analysis, storage medium and equipment

Abstract

The invention provides a noise analysis-based high-wind-pressure rock drilling tooth performance test method and system, a storage medium and equipment, and the method comprises the steps: building a quantitative model among time distribution, a wear function and a performance constant through noise signal analysis, i.e., converting the working noise data of a high-wind-pressure rock drilling tooth into the working time of a working tunneling unit length, and carrying out the calculation of the working noise data of the high-wind-pressure rock drilling tooth. The wear efficiency is defined accordingly; according to the method, multiple wear efficiency functions are obtained through a hypothesis method, an adaptive function is screened out through substitution verification, then a working performance function is constructed, quantitative characterization of the working performance of the high-wind-pressure rock drilling tooth is achieved, and the method overcomes the defects that an existing characterization mode is inaccurate and cannot truly reflect the actual working performance. The method has the advantages of being high in scientificity, high in accuracy, good in operability and the like, scientific basis can be provided for research and development, quality control and model selection application of the high-wind-pressure rock drilling teeth, the engineering operation efficiency can be improved, and the production cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of performance testing technology for mining rock drilling tools, and in particular to a method, system, storage medium, and equipment for testing the performance of high-pressure rock drilling teeth based on noise analysis. Background Technology

[0002] In modern large-scale infrastructure construction and mineral resource extraction projects, high-pressure rock drills are widely used in rock drilling operations and are key consumables to ensure smooth construction. With the continuous expansion of project scale and the increasing complexity of construction environments, the performance requirements for high-pressure rock drills are becoming increasingly stringent. On the one hand, the large differences in rock hardness and geological conditions require the drills to maintain high rock-breaking efficiency under strong impact and high wear conditions; on the other hand, to improve construction efficiency and reduce costs, the drills need to have a long service life and high reliability.

[0003] Currently, methods for evaluating the performance of high-pressure ball teeth have significant shortcomings. Traditional testing relies primarily on manual visual inspection, judging surface wear and cracks based on experience. This is highly subjective and fails to detect subtle internal defects, making it impossible to accurately assess potential performance issues. While hardness testing reflects surface hardness, it cannot reflect the ball teeth's comprehensive performance under actual complex working conditions, such as impact resistance, wear resistance, and fatigue life. In simulated working condition testing, existing methods struggle to realistically reproduce extreme operating environments like high wind pressure, strong impacts, and variable rock characteristics, leading to significant discrepancies between test results and actual performance. Furthermore, the various evaluation methods are independent and lack systematic integration, failing to provide a comprehensive, accurate, and mutually verifiable evaluation system for ball tooth performance. This results in a lack of sufficient scientific basis for ball tooth research and development, quality control, and selection, severely hindering engineering construction efficiency and quality improvement. Therefore, there is an urgent need to develop a scientific, comprehensive, and accurate testing method for the performance of high-pressure ball teeth. Summary of the Invention

[0004] Therefore, the purpose of this invention is to provide a method, system, storage medium and equipment for testing the performance of high wind pressure rock drilling teeth based on noise analysis, so as to fundamentally solve the problem that current methods are unable to truly reproduce extreme working environments such as high wind pressure, strong impact and variable rock characteristics, resulting in a large deviation between test results and actual working performance.

[0005] According to an embodiment of the present invention, a high-pressure rock drilling tooth performance testing method based on noise analysis is used to obtain the working noise data and corresponding total tunneling length of a benchmark model rock drilling tool within its complete service life. Based on a preset noise threshold, effective tunneling noise segments are identified and extracted from the working noise data to obtain multiple effective tunneling time periods corresponding to the total tunneling length. Based on the effective tunneling time period and its distribution, a wear efficiency function with wear state as the independent variable is constructed, and based on the wear efficiency function and the statistical distribution of the effective tunneling time period, a performance quantification function of the benchmark rock drilling tool is established. The working performance quantification function is used to calculate the working performance quantification value of the rock drilling tool to be evaluated. The working performance quantification value of the rock drilling tool to be evaluated is compared with the preset benchmark value of the benchmark rock drilling tool to quantify and evaluate the relative working performance of the rock drilling tool to be evaluated.

[0006] Furthermore, the effective tunneling noise segment is the time period during which the noise value continuously exceeds the preset noise threshold, and the number of extracted effective tunneling noise segments is consistent with the number of tunneling units corresponding to the total tunneling length.

[0007] Further, the step of identifying and extracting effective tunneling noise segments from the working noise data based on a preset noise threshold to obtain multiple effective tunneling time periods corresponding to the total tunneling length includes: The extracted multiple valid tunneling time periods were sorted and segmented by duration to obtain the frequency distribution of each time interval, and denoted as follows: , ,..., ,in, This represents the number of segments.

[0008] Further, the step of constructing a wear efficiency function with wear state as the independent variable based on the effective tunneling time period and its distribution, and establishing a performance quantification function of the benchmark rock drilling tool based on the wear efficiency function and the statistical distribution of the effective tunneling time period includes: The formula for the performance quantification function is: ; The wear efficiency function is: or The performance quantification function is: , It is a positive integer.

[0009] Furthermore, the wear efficiency function is determined by establishing a function model and fitting parameters. The assumed function model type includes, but is not limited to, a linear function, a quadratic function, a cubic function, a logarithmic function, or a composite function of the above.

[0010] Furthermore, the step of determining the wear efficiency function by establishing a function model and performing parameter fitting also includes: Assumption The specific functional form of contains multiple undetermined coefficients; Distribution data of effective tunneling time periods of multiple sets of the aforementioned benchmark rock drilling tools and the corresponding wear condition Based on the aforementioned performance quantification function formula, the undetermined coefficients are obtained to determine a candidate coefficient. and corresponding .

[0011] Furthermore, the effective drilling time period distribution data of multiple sets of the aforementioned benchmark rock drilling tools are utilized. and the corresponding wear condition Based on the aforementioned performance quantification function formula, the undetermined coefficients are obtained to determine a candidate coefficient. and corresponding Following these steps, the following are also included: Validate candidates using additional data from the aforementioned benchmark rock drilling tools. Calculate the function's output value; Comparing different candidates The output value is compared to the baseline value of 1000, and the closest corresponding value is selected. This serves as the final determined wear efficiency function. A high-pressure rock drilling tooth performance testing system based on noise analysis according to an embodiment of the present invention, the system comprising: The information acquisition module is used to acquire the working noise data and corresponding total tunneling length of the benchmark model rock drilling tool during its complete service life. The data extraction module is used to identify and extract effective tunneling noise segments from the working noise data based on a preset noise threshold, so as to obtain multiple effective tunneling time periods corresponding to the total tunneling length. The function calculation module is used to construct a wear efficiency function with wear state as the independent variable based on the effective tunneling time period and its distribution, and to establish a performance quantification function of the benchmark rock drilling tool based on the wear efficiency function and the statistical distribution of the effective tunneling time period. The evaluation module is used to calculate the quantitative value of the working performance of the rock drilling tool to be evaluated through the working performance quantification function, and compare the quantitative value of the working performance of the rock drilling tool to be evaluated with the preset benchmark value of the benchmark rock drilling tool to quantify the relative working performance of the rock drilling tool to be evaluated.

[0012] The present invention also proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for testing the performance of high-pressure rock drilling teeth based on noise analysis.

[0013] The present invention also proposes a high-pressure rock drilling tooth performance testing device based on noise analysis, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, to implement the above-mentioned high-pressure rock drilling tooth performance testing method based on noise analysis.

[0014] Compared with existing technologies, the high-pressure rock drill tooth performance testing method based on noise analysis in the above embodiments of the present invention establishes a quantitative model between "time distribution-wear function-performance constant" through noise signal analysis. This involves converting the working noise data of the high-pressure rock drill tooth into the working time per unit length of tunneling, and defining the wear efficiency accordingly. Multiple wear efficiency functions are obtained through a hypothesis method, and a suitable function is selected through substitution and verification. This leads to the construction of a working performance function, achieving a quantitative characterization of the working performance of the high-pressure rock drill tooth. This method overcomes the shortcomings of existing characterization methods, such as inaccuracy and inability to truly reflect actual working performance. It possesses advantages such as strong scientific rigor, high accuracy, and good operability. It can provide a scientific basis for the research and development, quality control, and selection of high-pressure rock drill teeth, helping to improve engineering operation efficiency and reduce production costs. It also solves the problem that current methods cannot accurately reproduce extreme working environments such as high wind pressure, strong impact, and variable rock characteristics, leading to significant deviations between test results and actual working performance. Attached Figure Description

[0015] Figure 1 This is a flowchart of the high wind pressure rock drilling tooth performance testing method based on noise analysis in the first embodiment of the present invention; Figure 2 This is a schematic diagram of the high wind pressure rock drilling tooth performance testing system based on noise analysis in the second embodiment of the present invention; Figure 3 This is a schematic diagram of the high wind pressure rock drilling tooth performance testing device based on noise analysis in the third embodiment of the present invention.

[0016] Figure 4 This refers to the drill bit excavation data of the high wind pressure rock drilling tooth performance testing equipment based on noise analysis in the first embodiment of the present invention.

[0017] Figure 5 This is a formula diagram of the high wind pressure rock drilling tooth performance testing device based on noise analysis in the first embodiment of the present invention.

[0018] The following detailed description of the embodiments will further illustrate the present invention in conjunction with the above-described accompanying drawings. Detailed Implementation

[0019] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0020] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0022] Example 1 Please see Figure 1 The figure shows a high wind pressure rock drilling tooth performance testing method based on noise analysis in the first embodiment of the present invention. The method specifically includes steps S01-S04.

[0023] Step S01: Obtain the working noise data and corresponding total tunneling length of the benchmark rock drilling tool during its complete service life.

[0024] In practice, under the same working conditions and equipment parameters, continuous working noise data of a model A rock drill bit (hereinafter also referred to as "benchmark model rock drill tool") as a performance benchmark is collected from the start of use to complete scrapping, and its total tunneling length throughout its entire life cycle is accurately recorded. The equipment used to collect working noise data and tunneling length can be, but is not limited to, a noise data acquisition device installed at the detection position on the rock drill equipment, and an infrared rangefinder set at the rock drill opening.

[0025] Step S02: Based on a preset noise threshold, identify and extract effective tunneling noise segments from the working noise data to obtain multiple effective tunneling time periods corresponding to the total tunneling length.

[0026] In practical implementation, a noise threshold is set, such as 105 dB. From continuous noise data, all time periods where the noise intensity continuously exceeds this threshold are identified. It should be noted that, as is understood in this field, a rock drill generates such a high-noise time period for every meter it advances. Therefore, the total number of time periods identified should equal the total number of meters drilled. In other words, the effective tunneling noise segment refers to the time period where the noise value continuously exceeds the threshold. The number of these extracted segments is consistent with the number of tunneling units (e.g., "meters") corresponding to the total tunneling length, thus obtaining multiple effective tunneling time periods.

[0027] Step S03: Based on the effective tunneling time period and its distribution, construct a wear efficiency function with wear state as the independent variable, and based on the wear efficiency function and the statistical distribution of the effective tunneling time period, establish a quantitative function for the working performance of the benchmark rock drilling tool.

[0028] Step S04: Calculate the quantitative value of the working performance of the rock drilling tool to be evaluated using the working performance quantification function, and compare the quantitative value of the working performance of the rock drilling tool to be evaluated with the preset benchmark value of the benchmark rock drilling tool to quantify the relative working performance of the rock drilling tool to be evaluated.

[0029] Based on the specific implementation of steps S03 to S04, all identified high-noise time periods are sorted from shortest to longest according to their duration. Then, this ordered time series is divided into several ( (Number) consecutive time intervals, and count the number of time intervals contained in each interval, denoted as _____. , ,..., And finally, the working time distribution of the benchmark rock drilling tool under different drilling speeds (fast and slow correspond to different time lengths) was obtained; Based on the above data, a performance function for a benchmark rock drilling tool was constructed. Because the time taken by the drill bit to excavate a unit length is functionally related to the rock hardness, and the rock hardness is functionally related to the wear of the drilling teeth, the time taken by the drill bit to excavate a unit length is functionally related to the wear of the drilling teeth. Let's assume the wear coefficient for the time taken per unit length of excavation is denoted as the function... In this application, the formula is derived by setting the overall wear rate of the benchmark rock drilling tool to 1000: , For positive integers, multiple sets of data from the benchmark rock drilling tool are input. From the middle After that, multiple groups Substitute return The working performance functions of multiple benchmark rock drilling tools were obtained. Then, data from other benchmark rock drilling tools were substituted into multiple sets. In the middle, filter out Values ​​closer to 1000 function; Furthermore, regarding the specific calculation of the performance quantification function formula, an example is given to construct the performance function of a benchmark rock drilling tool. Then, let's assume the wear coefficient function is as follows: , Substitute into the formula: , It is a positive integer. The number of time periods. For the corresponding The wear coefficient of the serial number can be used to obtain the corresponding coefficient: (1) When the wear coefficient is: At that time, the working data A1 and A2 of the benchmark model rock drilling tool (regarding the working data of A1 and A2, such as...) Figure 4 Substitute the drilling data of each drill bit into the formula. We can obtain:

[0030] Find: =0.015252, =0.201385, Performance function of Model A rock drill teeth .

[0031] (2) When the wear coefficient is: At that time, substitute the working data A1 and A2 of the benchmark rock drilling tool into the formula. We can obtain:

[0032] Find: =0.345158, =-1.67962, Performance function of Model A rock drill teeth .

[0033] Input the working data of A3 rock drilling teeth , In the middle, filter those whose function values ​​are closer to 1000, such as Figure 5 As shown.

[0034] according to Figure 5 As shown, when the wear coefficient is When the function value is closer to 1000, the performance function of rock drill A is more accurate. .

[0035] Finally, the rock drilling tool of the model to be tested (abbreviated as: B rock drilling tooth) can be brought into the test room in the manner described above. The function value is obtained from And based on the benchmark model rock drilling tool and the B rock drilling tooth, data comparison was carried out; like If the value is less than 1000, the working performance of the B-type rock drill tooth is insufficient compared to the performance of the benchmark rock drill tool. like =1000, then the working performance of the B-type rock drill tooth is the same as that of the benchmark rock drill tool. like If the value is greater than 1000, then the performance of the B-type rock drill tooth is stronger than that of the benchmark rock drill tool.

[0036] In summary, the high-pressure rock drilling tooth performance testing method based on noise analysis in the above embodiments of the present invention establishes a quantitative model between "time distribution - wear function - performance constant" through noise signal analysis. This involves converting the working noise data of the high-pressure rock drilling tooth into the working time per unit length of tunneling, and defining the wear efficiency accordingly. Furthermore, it obtains various wear efficiency functions through a hypothetical method. After substitution and verification, suitable functions are selected, and then working performance functions are constructed. This method enables the quantitative characterization of the working performance of high-pressure rock drills. It overcomes the shortcomings of existing characterization methods, which are inaccurate and cannot truly reflect actual working performance. It has the advantages of strong scientificity, high accuracy, and good operability. It can provide a scientific basis for the research and development, quality control, and selection and application of high-pressure rock drills, and help improve engineering operation efficiency and reduce production costs. It solves the problem that current methods are unable to truly reproduce extreme working environments such as high wind pressure, strong impact, and variable rock characteristics, which leads to a large deviation between test results and actual working performance.

[0037] Example 2 In another aspect, this invention provides a high-wind-pressure rock drilling tooth performance testing system based on noise analysis. Please refer to [link / reference]. Figure 2 The figure shows a high-wind-pressure rock drilling tooth performance testing system based on noise analysis in the second embodiment of the present invention. The system includes: Information acquisition module 11 is used to acquire the working noise data and corresponding total tunneling length of the benchmark model rock drilling tool during its complete service life. The data extraction module 12 is used to identify and extract effective tunneling noise segments from the working noise data based on a preset noise threshold, so as to obtain multiple effective tunneling time periods corresponding to the total tunneling length. The function calculation module 13 is used to construct a wear efficiency function with wear state as the independent variable based on the effective tunneling time period and its distribution, and to establish a quantitative function of the working performance of the benchmark rock drilling tool based on the wear efficiency function and the statistical distribution of the effective tunneling time period. Evaluation module 14 is used to calculate the quantitative value of the working performance of the rock drilling tool to be evaluated through the working performance quantification function, and compare the quantitative value of the working performance of the rock drilling tool to be evaluated with the preset benchmark value of the benchmark rock drilling tool to quantify the relative working performance of the rock drilling tool to be evaluated.

[0038] Example 3 In another aspect, this invention also proposes a high-wind-pressure rock drilling tooth performance testing device based on noise analysis. Please refer to [link to relevant documentation]. Figure 3 The image shows a high-pressure rock drill tooth performance testing device based on noise analysis according to the third embodiment of the present invention, including a memory 20, a processor 10, and a computer program 30 stored in the memory and executable on the processor. When the processor 10 executes the computer program 30, it implements the high-pressure rock drill tooth performance testing method based on noise analysis as described above.

[0039] Specifically, the high wind pressure rock drilling tooth performance testing equipment based on noise analysis can be a processor 10. In some embodiments, it can be a central processing unit (CPU), controller, microcontroller, microprocessor or other data processing chip, used to run program code stored in memory 20 or process data, such as executing access restriction programs.

[0040] The memory 20 includes at least one type of readable storage medium, such as flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 20 can be an internal storage unit of the high-pressure rock drill performance testing system based on noise analysis, such as the hard disk of the system. In other embodiments, the memory 20 can be an external storage system of the system, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the system. Furthermore, the memory 20 can include both internal storage units and external storage systems. The memory 20 can be used not only to store application software and various data installed on the system, but also to temporarily store data that has been output or will be output.

[0041] It should be pointed out that, Figure 3 The structure shown does not constitute a limitation on the high wind pressure rock drill performance testing system based on noise analysis. In other embodiments, the high wind pressure rock drill performance testing system based on noise analysis may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0042] This invention also proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the high-wind-pressure rock drilling tooth performance testing method based on noise analysis as described above.

[0043] Those skilled in the art will understand that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, system, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, system, or device). For the purposes of this specification, "computer-readable medium" can mean any system that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, system, or device.

[0044] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic systems) with one or more wires, portable computer disk drives (magnetic systems), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic systems, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0045] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0046] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0047] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A method for testing the performance of high-wind-pressure rock drilling teeth based on noise analysis, characterized in that, The method includes: Obtain the operating noise data and corresponding total tunneling length of the benchmark rock drilling tool over its complete service life. Based on a preset noise threshold, effective tunneling noise segments are identified and extracted from the working noise data to obtain multiple effective tunneling time periods corresponding to the total tunneling length. Based on the effective tunneling time period and its distribution, a wear efficiency function with wear state as the independent variable is constructed, and based on the wear efficiency function and the statistical distribution of the effective tunneling time period, a performance quantification function of the benchmark rock drilling tool is established. The working performance quantification function is used to calculate the working performance quantification value of the rock drilling tool to be evaluated. The working performance quantification value of the rock drilling tool to be evaluated is compared with the preset benchmark value of the benchmark rock drilling tool to quantify and evaluate the relative working performance of the rock drilling tool to be evaluated.

2. The method for testing the performance of high-pressure rock drilling teeth based on noise analysis according to claim 1, characterized in that, The effective tunneling noise segment is the time period in which the noise value continuously exceeds the preset noise threshold, and the number of effective tunneling noise segments extracted is consistent with the number of tunneling units corresponding to the total tunneling length.

3. The method for testing the performance of high-pressure rock drilling teeth based on noise analysis according to claim 2, characterized in that, The step of identifying and extracting effective tunneling noise segments from the working noise data based on a preset noise threshold, and obtaining multiple effective tunneling time periods corresponding to the total tunneling length, includes: The extracted multiple valid tunneling time periods were sorted and segmented by duration to obtain the frequency distribution of each time interval, and denoted as follows: , ,..., ,in, This represents the number of segments.

4. The method for testing the performance of high-pressure rock drilling teeth based on noise analysis according to claim 3, characterized in that, The steps of constructing a wear efficiency function with wear state as the independent variable based on the effective tunneling time period and its distribution, and establishing a performance quantification function for the benchmark rock drilling tool based on the wear efficiency function and the statistical distribution of the effective tunneling time period, include: The formula for the performance quantification function is: ; The wear efficiency function is: or The performance quantification function is: , It is a positive integer.

5. The method for testing the performance of high-pressure rock drilling teeth based on noise analysis according to claim 4, characterized in that, The wear efficiency function is determined by setting up a function model and fitting parameters. The assumed function model type includes, but is not limited to, a linear function, a quadratic function, a cubic function, a logarithmic function, or a composite function.

6. The method for testing the performance of high-pressure rock drilling teeth based on noise analysis according to claim 5, characterized in that, The wear efficiency function is determined by setting up a function model and performing parameter fitting, and further includes: Assumption The specific functional form of contains multiple undetermined coefficients; Distribution data of effective tunneling time periods of multiple sets of the aforementioned benchmark rock drilling tools and the corresponding wear condition Based on the aforementioned performance quantification function formula, the undetermined coefficients are obtained to determine a candidate coefficient. and corresponding .

7. The method for testing the performance of high-pressure rock drilling teeth based on noise analysis according to claim 6, characterized in that, The effective advance time period distribution data of multiple sets of the benchmark rock drilling tools were utilized. and the corresponding wear condition Based on the aforementioned performance quantification function formula, the undetermined coefficients are obtained to determine a candidate coefficient. and corresponding Following these steps, the following are also included: Validate candidates using additional data from the aforementioned benchmark rock drilling tools. Calculate the function's output value; Comparing different candidates The output value is compared to the baseline value of 1000, and the closest corresponding value is selected. This serves as the final determined wear efficiency function.

8. A high-pressure rock drilling tooth performance testing system based on noise analysis, characterized in that, The system includes: The information acquisition module is used to acquire the working noise data and corresponding total tunneling length of the benchmark model rock drilling tool during its complete service life. The data extraction module is used to identify and extract effective tunneling noise segments from the working noise data based on a preset noise threshold, so as to obtain multiple effective tunneling time periods corresponding to the total tunneling length. The function calculation module is used to construct a wear efficiency function with wear state as the independent variable based on the effective tunneling time period and its distribution, and to establish a performance quantification function of the benchmark rock drilling tool based on the wear efficiency function and the statistical distribution of the effective tunneling time period. The evaluation module is used to calculate the quantitative value of the working performance of the rock drilling tool to be evaluated through the working performance quantification function, and compare the quantitative value of the working performance of the rock drilling tool to be evaluated with the preset benchmark value of the benchmark rock drilling tool to quantify the relative working performance of the rock drilling tool to be evaluated.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the high wind pressure rock drilling tooth performance testing method based on noise analysis as described in any one of claims 1-7.

10. A high-pressure rock drilling tooth performance testing device based on noise analysis, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the high wind pressure rock drilling tooth performance testing method based on noise analysis as described in any one of claims 1-7.

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