While-drilling monitoring device of jumbolter and while-drilling identification method of rock stratum interface

Abstract

The invention provides a roof bolter monitoring-while-drilling device and a rock stratum interface identification-while-drilling method, and relates to the technical field of rock and soil drilling. The device comprises a fixed frame, a telescopic frame, a thrust sensor, a torque rotating speed sensor, a laser range finder and a data processing unit, thrust, torque, rotating speed and displacement signals in the drilling process of the jumbolter are synchronously collected in real time by integrating the sensors, the data processing unit calculates net drilling specific work, and a rock stratum interface and thickness distribution are recognized based on changes of the net drilling specific work. The invention also provides a rock stratum interface identification while drilling method, which comprises the following steps of: performing moving average filtering on net drilling specific work data, automatically identifying discrete points by adopting a clustering algorithm, and further calibrating the position of the rock stratum interface and calculating the thickness of each rock stratum. The method can accurately identify the rock stratum interface and thickness distribution in real time, has the advantages of strong robustness and good adaptability, and provides a reliable basis for dynamic design of roadway anchor bolt support.

Description

Technical Field

[0001] This invention relates to the field of rock and soil drilling technology, specifically to a monitoring device for anchor drilling rigs and a method for identifying rock strata interfaces during drilling. Background Technology

[0002] Accurate identification of rock strata structure is a crucial prerequisite for anchor bolt support design during coal mine roadway excavation. Traditional methods for identifying rock strata interfaces mainly rely on geological drilling and core sampling. Rock mass structural characteristics are obtained through core observation and laboratory testing to create borehole columnar sections. However, this method has significant shortcomings: firstly, the limited number of boreholes makes it difficult to comprehensively reflect the spatial variations of the rock strata; secondly, the core sampling and testing process is time-consuming and costly, failing to meet the real-time geological information requirements of rapid coal mine roadway excavation. As coal mining depths increase and roadway geological conditions become increasingly complex, the limitations of traditional methods in terms of accuracy and timeliness become increasingly prominent.

[0003] During the construction of rock bolt support, a large number of rock bolt holes are drilled. The drilling parameters of the rock bolt drilling rig change accordingly when drilling into different rock strata. Real-time monitoring of these drilling parameters is crucial for obtaining rock strata information to identify rock strata interfaces. This plays a vital role in optimizing the design of rock bolt support in coal mine roadways and is a key link in promoting intelligent coal mine roadway excavation. However, in practical applications, problems exist such as poor adaptability of data processing methods and the influence of different rock strata properties, drilling rig models, and operator differences. The variation patterns of drilling parameters are often unstable and difficult to directly use for rock strata interface identification.

[0004] Therefore, it is urgent to develop a drilling monitoring device that can be adapted to bolt drilling rigs and to establish a robust rock interface identification method to achieve rapid and accurate acquisition of rock interface and thickness, providing a reliable basis for dynamic design of roadway bolt support. Summary of the Invention

[0005] The purpose of this invention is to provide a monitoring device for anchor drilling rigs and a method for identifying rock strata interfaces during drilling, so as to identify rock strata interfaces and thickness distribution in real time and accurately.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A monitoring device for anchor drilling rigs during drilling, comprising: A fixed frame, the lower end of which is provided with a first assembly part; The telescopic frame is slidably fitted with the fixed frame. The telescopic frame can extend and retract relative to the fixed frame. The upper end of the telescopic frame is provided with a second assembly part, and the telescopic frame is also provided with a third assembly part. A thrust sensor, located in the first assembly section, is used to collect thrust signals during the drilling process of the anchor drilling rig. A torque and speed sensor, located in the second assembly section, is used to collect torque and speed signals during the drilling process of the anchor drilling rig. A laser rangefinder, installed on the third assembly section, is used to collect displacement signals during the drilling process of the anchor drilling rig. The data processing unit is connected to the thrust sensor, torque and speed sensor, and laser rangefinder signals respectively. It is used to receive and process thrust signals, torque signals, speed signals and displacement signals to obtain net drilling specific power, and to identify rock layer interfaces and thickness distribution based on changes in net drilling specific power.

[0007] Furthermore, the lower end of the fixing frame is bent to one side to form the first assembly part, the first assembly part is arranged in a horizontal direction, the bottom of the anchor drilling machine is mounted on the first assembly part, and the thrust sensor is located between the first assembly part and the bottom of the anchor drilling machine.

[0008] Furthermore, the upper end of the telescopic frame is bent to one side to form the second assembly part. The second assembly part is arranged in a horizontal direction. The upper and lower end faces of the rotating end of the torque speed sensor are respectively connected to the first assembly part and the second assembly part. The first assembly part is connected to the drill rod, and the second assembly part is connected to the output shaft of the anchor drilling machine.

[0009] Furthermore, as the air leg of the anchor drilling rig rises and falls, the telescopic frame extends and retracts relative to the fixed frame.

[0010] Furthermore, the data processing unit includes a signal acquisition device and a smart terminal; the smart terminal is connected to the thrust sensor, torque and speed sensor and laser rangefinder via the signal acquisition device, the signal acquisition device is used to receive and convert signals, and the smart terminal is used to calculate the net drilling specific power and execute the rock layer interface and thickness distribution identification algorithm.

[0011] Furthermore, the smart terminal is configured as an explosion-proof smart handheld terminal.

[0012] Furthermore, the formula for calculating the net drilling specific power is as follows: ; In the formula, Net drilling work ratio; t is the thrust of the anchor drilling rig during drilling; v is the drilling speed of the anchor drilling rig, which is obtained from the displacement and drilling time of the anchor drilling rig during drilling; t is the drilling time; N is the rotational speed of the anchor drilling rig during drilling; M is the torque of the anchor drilling rig during drilling; μ is the coefficient of dynamic friction; r is the radius of the borehole inner wall; L is the drilling depth.

[0013] A method for identifying rock strata interfaces while drilling, using the aforementioned monitoring device for anchor drilling rigs while drilling, the method comprising the following steps: S1. Assemble and connect the anchor drilling rig's monitoring device with the anchor drilling rig as a whole; S2. Drill anchor holes into the rock strata using an anchor drilling rig, and collect thrust signals in real time during the drilling process using a thrust sensor, torque and speed signals in real time using a torque and speed sensor, and displacement signals in real time using a laser rangefinder. S3. The data processing unit receives and processes thrust signals, torque signals, rotational speed signals, and displacement signals to obtain net drilling specific power. The formula for calculating the net drilling specific power is as follows: ; In the formula: Net drilling work ratio; t is the thrust of the anchor drilling rig during drilling; v is the drilling speed of the anchor drilling rig, which is obtained from the displacement and drilling time of the anchor drilling rig during drilling; t is the drilling time; N is the rotational speed of the anchor drilling rig during drilling; M is the torque of the anchor drilling rig during drilling; μ is the coefficient of dynamic friction; r is the radius of the borehole inner wall; L is the drilling depth. S4. The net drilling power ratio data is smoothed using a moving average filtering algorithm. S5. Clustering algorithm is used to cluster the filtered net drilling power ratio data; S6. Extract points that exceed the threshold from the clustering results as discrete points. The displacement corresponding to the discrete point is the rock layer interface, and the difference between the distances of adjacent discrete points is the thickness of the rock layer.

[0014] Furthermore, in S4, the moving average filtering algorithm uses a five-point cubic smoothing method, which uses five adjacent data points to calculate new data points to achieve a smoothing effect and remove noise from the net drilling power ratio data. The moving average filtering algorithm is as follows: ; In the formula: y(n) is the new data sequence after filtering; y(i-2), y(i-1), y(i), y(i+1), y(i+2) represent the values ​​of the i-th point in the original data sequence and the two points before and after this point.

[0015] Furthermore, in S5, the clustering algorithm is based on the filtered net drilling power ratio data. Through the elbow rule, it calculates the sum of squared errors within clusters (SSE) for different K values, and plots the elbow diagram of K value and SSE value. The K value corresponding to the maximum inflection point of the slope is the optimal number of clusters, and the data clustering is completed through iteration. The Sum of Squared Errors (SSE) algorithm is as follows: ; In the formula: For the j-th data sample, Let i be the cluster center of the i-th cluster. Let i be the i-th cluster.

[0016] Compared with the prior art, the anchor drilling rig monitoring device and rock interface identification method of the present invention have achieved the following significant technical effects: 1. The device of the present invention integrates a thrust sensor, a torque and speed sensor and a laser rangefinder and is adapted to the anchor drilling rig. It can collect thrust, torque, speed and displacement signals in real time during the drilling process of the anchor drilling rig. It realizes accurate monitoring of key parameters in the entire process of anchor drilling, provides high-resolution basic data support for rock interface identification, and overcomes the defects of poor timeliness and discontinuous information in traditional geological drilling core sampling methods.

[0017] 2. This invention identifies rock strata interfaces based on the comprehensive index of net drilling power. Compared with directly using a single drilling parameter, net drilling power can more fundamentally reflect the energy consumption characteristics of the rock fracturing process, and has higher sensitivity and stability to changes in rock strata. It effectively reduces interference caused by factors such as differences in drilling rig models and different operator techniques, and significantly improves the robustness and universality of rock strata interface identification.

[0018] 3. In the data processing stage, this invention first uses a moving average filtering algorithm to smooth and reduce noise in the net drilling power ratio data, and then combines it with a clustering algorithm to automatically identify discrete points in the data, thereby accurately calibrating the location of rock strata interfaces and calculating the thickness of each rock stratum. It eliminates the need for manually setting fixed thresholds, adapts to data distribution characteristics under different geological conditions, and provides objective and repeatable identification results, making it particularly suitable for the complex and variable rock strata conditions in coal mine roadways.

[0019] 4. This invention designs the monitoring device and the anchor bolt drilling rig as a prefabricated integrated structure, allowing for on-the-spot measurement without interfering with normal anchor bolt drilling operations. Furthermore, the intelligent terminal can be an explosion-proof handheld terminal, facilitating on-site operation and real-time display underground. This method, combined with the device, can quickly and accurately obtain the depth and thickness distribution of rock strata interfaces, providing a reliable basis for the dynamic optimization design of roadway anchor bolt support parameters, and is of great significance for promoting the intelligentization of coal mine roadway excavation. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the structure of the anchor drilling rig monitoring device according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of the anchor drilling rig monitoring device assembled and connected to the anchor drilling rig according to an embodiment of the present invention; Figure 3This is a flowchart of the drilling interface identification method according to an embodiment of the present invention; Figure 4 This is a diagram showing the distribution of rotational speed as a function of displacement during the drilling process of the anchor drilling rig according to an embodiment of the present invention. Figure 5 This is a diagram showing the torque distribution as a function of displacement during the drilling process of the anchor drilling rig according to an embodiment of the present invention. Figure 6 This is a diagram showing the distribution of drilling speed as a function of displacement during the drilling process of the anchor drilling rig according to an embodiment of the present invention. Figure 7 This is a distribution diagram of the net drilling specific power as a function of displacement during the drilling process of the anchor drilling rig according to an embodiment of the present invention; Figure 8 This is a clustering result diagram of an embodiment of the present invention; Figure 9 This is a clustering group displacement diagram according to an embodiment of the present invention; In the picture, 11. Fixed frame; 111. First assembly section; 12. Telescopic frame; 121. Second assembly section; 122. Third assembly section; 2. Thrust sensor; 3. Torque and speed sensor; 4. Laser rangefinder; 5. Anchor drilling rig; 51. Drill rod; 61. First assembly set; 62. Second assembly set. A. Softer rock with a design strength of 20 MPa and an actual strength of 18.15 MPa; B. Soft rock with a design strength of 10 MPa and an actual strength of 9.82 MPa; C. Extremely soft rock with a design strength of 5 MPa and an actual strength of 4.79 MPa. Detailed Implementation

[0021] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the invention will be further described in detail below with reference to specific embodiments and the accompanying drawings. Certain embodiments of the invention will be described more fully below with reference to the accompanying drawings, and some, but not all, of these embodiments will be shown. In fact, various embodiments of the invention can be implemented in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided to enable the invention to meet applicable legal requirements.

[0022] In the description of this invention, it should be noted that the terms "inner," "outer," "upper," "lower," "front," and "rear," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0023] In this embodiment of the invention, a monitoring device for anchor bolt drilling rigs and a method for identifying rock strata interfaces during drilling are provided. Please refer to [reference needed]. Figures 1 to 9 As shown.

[0024] A monitoring device for anchor drilling rigs includes a fixed frame 11, a telescopic frame 12, a thrust sensor 2, a torque and speed sensor 3, a laser rangefinder 4, and a data processing unit.

[0025] The fixed frame 11 is provided with a sleeve structure arranged vertically, and the telescopic frame 12 is embedded in the sleeve structure. The telescopic frame 12 is slidably engaged with the fixed frame 11, and the telescopic frame 12 can extend and retract relative to the fixed frame 11. In particular, after the drilling monitoring device is assembled and connected to the anchor drilling rig, the telescopic frame 12 extends and retracts relative to the fixed frame 11 as the air leg of the anchor drilling rig 5 rises and falls.

[0026] The lower end of the fixed frame 11 is provided with a first assembly part 111, the upper end of the telescopic frame 12 is provided with a second assembly part 121, and the side wall of the telescopic frame 12 is provided with a third assembly part 122.

[0027] The thrust sensor 2 is located in the first assembly part 111. The thrust sensor 2 is used to collect the thrust signal during the drilling process of the anchor drill 5.

[0028] The lower end of the fixing frame 11 is bent to one side to form a first assembly part 111. The first assembly part 111 is arranged in a horizontal direction. The bottom of the anchor drilling machine 5 is mounted on the first assembly part 111. The thrust sensor 2 is located between the first assembly part 111 and the bottom of the anchor drilling machine 5.

[0029] The torque and speed sensor 3 is installed in the second assembly part 121. The torque and speed sensor 3 is used to collect torque and speed signals during the drilling process of the anchor drilling machine 5.

[0030] The upper end of the telescopic frame 12 is bent to one side to form a second assembly part 121. The second assembly part 121 is arranged in a horizontal direction. The upper and lower end faces of the rotating end of the torque speed sensor 3 are respectively connected to the first assembly part 61 and the second assembly part 62. The first assembly part 61 is connected to the drill rod 51, and the second assembly part 62 is connected to the output shaft of the anchor drilling machine 5.

[0031] The laser rangefinder 4 is a two-way laser rangefinder, which is mounted on the third assembly part 122. The laser rangefinder 4 is used to collect displacement signals during the drilling process of the anchor drilling rig 5. During the drilling process of the anchor drilling rig 5, as the air leg of the anchor drilling rig 5 rises and falls, the telescopic frame 12 extends and retracts relative to the fixed frame 11, and the laser rangefinder 4 measures the displacement signals in real time.

[0032] The data processing unit is connected to the thrust sensor 2, torque and speed sensor 3, and laser rangefinder 4 via signal cables. The data processing unit receives and processes thrust, torque, speed, and displacement signals to obtain net drilling specific power, and identifies rock strata interfaces and thickness distribution based on changes in net drilling specific power.

[0033] The data processing unit includes a signal acquisition unit and a smart terminal, which is an explosion-proof smart handheld terminal. The smart terminal is connected to the thrust sensor, torque and speed sensor, and laser rangefinder via the signal acquisition unit. The signal acquisition unit receives and converts signals (thrust signal, torque signal, speed signal, and displacement signal) and uploads them to the smart terminal. The smart terminal is used to calculate the net drilling specific power and execute the rock layer interface and thickness distribution identification algorithm.

[0034] The formula for calculating net drilling specific power is as follows: ; In the formula, Net drilling work ratio; t is the thrust of the anchor bolt drilling rig during drilling; v is the drilling speed of the anchor bolt drilling rig, which is obtained from the displacement and drilling time of the anchor bolt drilling rig during drilling; t is the drilling time; N is the rotational speed of the anchor bolt drilling rig during drilling; M is the torque of the anchor bolt drilling rig during drilling; μ is the coefficient of dynamic friction, taken as 0.2; r is the inner radius of the borehole; L is the drilling depth.

[0035] A method for identifying rock strata interfaces while drilling, using the anchor drilling rig monitoring device described in this embodiment, includes the following steps: S1. Assemble and connect the anchor drilling rig's monitoring device with the anchor drilling rig 5 as a whole.

[0036] S2. The anchor drill rig 5 drills into the rock strata to make anchor holes. The thrust sensor 2 collects the thrust signal of the anchor drill rig 5 in real time during the drilling process. The torque and speed sensor 3 collects the torque and speed signals of the anchor drill rig 5 in real time during the drilling process. The laser rangefinder 4 collects the displacement signal of the anchor drill rig 5 in real time during the drilling process.

[0037] S3. The data processing unit receives and processes the thrust signal, torque signal, rotational speed signal, and displacement signal to obtain the net drilling specific power.

[0038] The formula for calculating net drilling specific power is as follows: ; In the formula: Net drilling work ratio; t is the thrust of the anchor bolt drilling rig during drilling; v is the drilling speed of the anchor bolt drilling rig, which is obtained from the displacement and drilling time of the anchor bolt drilling rig during drilling; t is the drilling time; N is the rotational speed of the anchor bolt drilling rig during drilling; M is the torque of the anchor bolt drilling rig during drilling; μ is the coefficient of dynamic friction, taken as 0.2; r is the inner radius of the borehole; L is the drilling depth.

[0039] The data processing unit differentiates the displacement-time curve to obtain the drilling speed-time curve.

[0040] S4. The net drilling power ratio data is smoothed by a moving average filtering algorithm to eliminate random fluctuations in the net drilling power ratio data.

[0041] Among them, the moving average filtering algorithm adopts the five-point cubic smoothing method, which uses five adjacent data points to calculate new data points in order to achieve a smoothing effect and remove noise from the net drilling power ratio data. The moving average filtering algorithm is as follows: ; In the formula: y(n) is the new data sequence after filtering; y(i-2), y(i-1), y(i), y(i+1), y(i+2) represent the values ​​of the i-th point in the original data sequence and the two points before and after this point.

[0042] S5. Clustering algorithm is used to cluster the filtered net drilling power ratio data.

[0043] Among them, the clustering algorithm is based on the filtered net drilling power ratio data. It calculates the sum of squared errors within clusters (SSE) for different K values ​​using the elbow rule, and plots the elbow diagram of K value and SSE value. The K value corresponding to the maximum inflection point of the slope is the optimal number of clusters, and the data clustering is completed through iteration. The Sum of Squared Errors (SSE) algorithm is as follows: ; In the formula: For the j-th data sample, Let i be the cluster center of the i-th cluster. Let i be the i-th cluster.

[0044] S6. Extract points that exceed the threshold in the clustering results as discrete points. The displacement corresponding to the discrete points is the rock layer interface, and the difference between the distances of adjacent discrete points is the thickness H of the rock layer. ; In the formula: This represents the displacement corresponding to the subsequent discrete point; This represents the displacement corresponding to the previous discrete point.

[0045] The present invention has been described in detail above with reference to the accompanying drawings. Based on the above description, those skilled in the art should have a clear understanding of the anchor drilling rig monitoring device and the rock interface identification method of the present invention. Of course, the specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A monitoring device for anchor drilling rigs during drilling, characterized in that, include: A fixed frame, the lower end of which is provided with a first assembly part; The telescopic frame is slidably fitted with the fixed frame. The telescopic frame can extend and retract relative to the fixed frame. The upper end of the telescopic frame is provided with a second assembly part, and the telescopic frame is also provided with a third assembly part. A thrust sensor, located in the first assembly section, is used to collect thrust signals during the drilling process of the anchor drilling rig. A torque and speed sensor, located in the second assembly section, is used to collect torque and speed signals during the drilling process of the anchor drilling rig. A laser rangefinder, installed on the third assembly section, is used to collect displacement signals during the drilling process of the anchor drilling rig. The data processing unit is connected to the thrust sensor, torque and speed sensor, and laser rangefinder signals respectively. It is used to receive and process thrust signals, torque signals, speed signals and displacement signals to obtain net drilling specific power, and to identify rock layer interfaces and thickness distribution based on changes in net drilling specific power.

2. The anchor drilling rig monitoring device according to claim 1, characterized in that, The lower end of the fixing frame is bent to one side to form the first assembly part. The first assembly part is arranged in a horizontal direction. The bottom of the anchor drilling machine is mounted on the first assembly part. The thrust sensor is located between the first assembly part and the bottom of the anchor drilling machine.

3. The anchor drilling rig monitoring device according to claim 1, characterized in that, The upper end of the telescopic frame is bent to one side to form the second assembly part. The second assembly part is arranged in a horizontal direction. The upper and lower end faces of the rotating end of the torque speed sensor are respectively connected to the first assembly part and the second assembly part. The first assembly part is connected to the drill rod, and the second assembly part is connected to the output shaft of the anchor drilling machine.

4. The anchor drilling rig monitoring device according to claim 1, characterized in that, As the air leg of the anchor drilling rig rises and falls, the telescopic frame extends and retracts relative to the fixed frame.

5. The anchor drilling rig monitoring device according to claim 1, characterized in that, The data processing unit includes a signal acquisition instrument and an intelligent terminal; the intelligent terminal is connected to the thrust sensor, torque and speed sensor and laser rangefinder via the signal acquisition instrument. The signal acquisition instrument is used to receive and convert signals, and the intelligent terminal is used to calculate the net drilling specific power and execute the rock layer interface and thickness distribution identification algorithm.

6. The anchor drilling rig monitoring device according to claim 5, characterized in that, The smart terminal is configured as an explosion-proof smart handheld terminal.

7. The anchor drilling rig monitoring device according to claim 5, characterized in that, The formula for calculating the net drilling specific power is as follows: ； In the formula, Net drilling work ratio; t is the thrust of the anchor drilling rig during drilling; v is the drilling speed of the anchor drilling rig, which is obtained from the displacement and drilling time of the anchor drilling rig during drilling; t is the drilling time; N is the rotational speed of the anchor drilling rig during drilling; M is the torque of the anchor drilling rig during drilling; μ is the coefficient of dynamic friction; r is the radius of the borehole inner wall; L is the drilling depth.

8. A method for identifying rock strata interfaces while drilling, using the monitoring device for anchor drilling rigs as described in any one of claims 1 to 7, characterized in that, The method includes the following steps: S1. Assemble and connect the anchor drilling rig's monitoring device with the anchor drilling rig as a whole; S2. Drill anchor holes into the rock strata using an anchor drilling rig, and collect thrust signals in real time during the drilling process using a thrust sensor, torque and speed signals in real time using a torque and speed sensor, and displacement signals in real time using a laser rangefinder. S3. The data processing unit receives and processes thrust signals, torque signals, rotational speed signals, and displacement signals to obtain net drilling specific power. The formula for calculating the net drilling specific power is as follows: ； In the formula: Net drilling work ratio; t is the thrust of the anchor bolt drilling rig during drilling; v is the drilling speed of the anchor bolt drilling rig, which is obtained from the displacement and drilling time of the anchor bolt drilling rig during drilling; t is the drilling time; N is the rotational speed of the anchor bolt drilling rig during drilling; M is the torque of the anchor bolt drilling rig during drilling; μ is the coefficient of dynamic friction; r is the inner radius of the borehole; L is the drilling depth. S4. The net drilling power ratio data is smoothed using a moving average filtering algorithm. S5. Clustering algorithm is used to cluster the filtered net drilling power ratio data; S6. Extract points that exceed the threshold from the clustering results as discrete points. The displacement corresponding to the discrete point is the rock layer interface, and the difference between the distances of adjacent discrete points is the thickness of the rock layer.

9. The method for identifying rock strata interfaces while drilling according to claim 8, characterized in that, In S4, the moving average filtering algorithm uses a five-point cubic smoothing method, which uses five adjacent data points to calculate new data points in order to achieve a smoothing effect and remove noise from the net drilling power ratio data. The moving average filtering algorithm is as follows: ； In the formula: y(n) is the new data sequence after filtering; y(i-2), y(i-1), y(i), y(i+1), y(i+2) represent the values ​​of the i-th point in the original data sequence and the two points before and after this point.

10. The method for identifying rock strata interfaces while drilling according to claim 8, characterized in that, In S5, the clustering algorithm is based on the filtered net drilling power ratio data. It uses the elbow rule to calculate the sum of squared errors within clusters (SSE) for different K values ​​and plots the elbow diagram of K and SSE values. The K value corresponding to the maximum inflection point of the slope is the optimal number of clusters, and the data clustering is completed through iteration. The Sum of Squared Errors (SSE) algorithm is as follows: ； In the formula: For the j-th data sample, Let i be the cluster center of the i-th cluster. Let i be the i-th cluster.

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