Mud delivery blockage early warning method and system in soil rock drilling

Abstract

The application provides a method and system for early warning of sludge conveying blockage in soil rock drilling. A plurality of single-point pressure sensors are arranged in the middle of a drill pipe for conveying sludge. The outlet cross section of the drill pipe is divided into grids according to a preset rule, and the projection of the outlet of the drill pipe coincides with the corresponding grid. An axial attenuation model is combined, and the pressure values of each grid on the outlet cross section are reconstructed based on the original pressure values collected by each single-point pressure sensor. Early warning of sludge conveying blockage is performed based on the pressure values of each grid on the outlet cross section. The application eliminates the interference of sensor arrangement on sludge conveying, realizes accurate acquisition of outlet cross section pressure, and effectively improves the accuracy and timeliness of early warning of sludge conveying blockage.

Description

Technical Field

[0001] This invention relates to the field of drilling in soil and rock formations, and particularly to a method and system for early warning of blockages in the transport of excavated soil during drilling in soil and rock formations. Background Technology

[0002] In drilling projects in soil and rock layers, blockage of the drill rod for transporting excavated soil is a potential cause of construction interruption and reduced efficiency. This is especially true in special scenarios such as deep hole drilling, high-pressure transportation, or bends / diameter changes. If the local accumulation of excavated soil inside the drill rod is not detected in time, it can quickly develop into a complete blockage, causing equipment damage and project delays. The optimal solution for monitoring blockages in construction waste transportation is to deploy pressure sensors at the cross-sections of the drill pipe inlet and outlet to determine the pressure distribution at the inlet and outlet, and then monitor the distribution of construction waste through multiple sets of signals covering the entire cross-section. However, densely arranged pressure sensors on a single cross-section can lead to reverse blockages caused by construction waste, while setting a single pressure sensor on the side wall of the drill pipe results in insufficient early warning accuracy. Therefore, there is currently a lack of technical solutions that can both avoid blockages caused by sensor deployment and achieve accurate blockage early warning. Summary of the Invention

[0003] The key technical problem that this invention aims to solve is: how to avoid blockage and accurately warn of blockage during drilling in soil and rock layers.

[0004] The first aspect of this application provides a method for early warning of blockage in the transport of excavated soil during drilling in soil and rock layers, including: Multiple single-point pressure sensors are deployed in the drill rod for conveying excavated soil. The cross-section of the drill rod outlet is divided into grids according to a preset rule, and the orthographic projection of the multiple single-point pressure sensors at the drill rod outlet coincides with the corresponding grid. Combining the axial attenuation model, the pressure values ​​of each grid on the outlet cross section are reconstructed based on the original pressure values ​​collected by each single-point pressure sensor. Early warning of slag and soil transport blockage is generated based on the pressure values ​​of each grid on the outlet cross section.

[0005] Optionally, before reconstructing the pressure values ​​of each grid on the outlet cross-section using the axial attenuation model, the method further includes: The parameters of the axial attenuation model are calibrated. The parameters include pressure baseline, axial attenuation coefficient and slag accumulation adaptation factor. The pressure baseline is the static stable pressure value of the corresponding grid sensor when there is no slag flow. The axial attenuation coefficient is a parameter reflecting the rate of attenuation of slag pressure along the drill rod axis. The slag accumulation adaptation factor is a parameter reflecting the influence of soil layer rock slag particle morphology and accumulation characteristics on pressure transmission.

[0006] Optionally, calibrating the pressure baseline includes: keeping the drill pipe free of debris flow and under normal operating conditions, collecting multiple consecutive frames of raw pressure values ​​from each single-point pressure sensor, and taking the average value under stable operating conditions as the pressure baseline for the grid corresponding to each single-point pressure sensor.

[0007] Optionally, calibrating the axial attenuation coefficient includes: Transport standard construction waste under normal operating conditions to keep the flow rate and accumulation status of the construction waste stable. Temporary pressure sensing elements were deployed at the grid positions corresponding to the outlet cross-section, and the actual outlet pressure of the grid was measured. The original pressure values ​​of the upstream single-point pressure sensors corresponding to the temporary pressure sensing elements are collected synchronously. Combined with the calibrated pressure baseline, the soil accumulation adaptation factor, the actual outlet pressure of the temporary pressure sensing elements, and the axial distance between the single-point pressure sensors and the corresponding temporary pressure sensing elements, the axial attenuation coefficient of each grid is obtained by inverse solution. The average value of the axial attenuation coefficients of all grids is taken as the final axial attenuation coefficient.

[0008] Optional, the calibration of spoil stockpiling adaptation factors includes: Typical slag samples covering three deposition states—loose, medium-dense, and high-dense—were selected for drilling scenarios in soil and rock layers. Typical slag samples of each stacking state were transported separately, and the original pressure values ​​of the corresponding single-point pressure sensors and the actual pressure values ​​of the corresponding grid at the outlet were collected. By combining the calibrated pressure baseline, axial attenuation coefficient, and axial distance between the sensor and the outlet, the soil accumulation adaptation factor for each accumulation state is obtained by inverse solution. Weights are assigned according to the frequency of occurrence of each stockpiling state in actual working conditions, and the mean value of the slag stockpiling adaptation factor under all stockpiling states is calculated as the final slag stockpiling adaptation factor.

[0009] Optionally, reconstructing the pressure values ​​of each grid on the outlet cross section using the axial attenuation model includes: substituting the filtered effective pressure value into the axial attenuation model, which takes the effective pressure value, axial attenuation coefficient, axial distance between the sensor and the outlet, and slag pile adaptation factor as inputs, corrects the pressure transmission efficiency through the slag pile adaptation factor, and then calculates the true outlet pressure value of each grid by combining the axial attenuation coefficient corresponding to the axial distance.

[0010] Optionally, determining the pressure value of each grid on the outlet cross-section includes: arranging and combining the actual outlet pressure values ​​of all grids in a preset grid coordinate order to form a complete pressure matrix covering the outlet cross-section. Each element of the pressure matrix corresponds one-to-one with the corresponding grid, and the set of all elements in the pressure matrix is ​​the pressure value of each grid on the outlet cross-section.

[0011] Optionally, before issuing an early warning for the blockage of the excavated soil transport based on the pressure values ​​of each grid on the outlet cross-section, the method further includes: The feed inlet adopts a grid division and sensor deployment scheme that is completely consistent with the outlet, so that the grids of the feed inlet and the outlet correspond one-to-one. The original pressure values ​​of the sensors corresponding to each grid at the feed inlet are collected. The pressure baseline, axial attenuation coefficient, slag pile adaptation factor, and axial attenuation model calculation logic consistent with those at the outlet are used to determine the pressure values ​​of each grid at the feed inlet.

[0012] Optionally, an early warning system for the blockage of the excavated soil conveying is provided based on the pressure values ​​of each grid on the outlet cross-section, including: The transmission delay time of the slag from the inlet to the outlet is determined by the working condition calibration, and the pressure value of each grid at the inlet is time-aligned with the pressure value of the corresponding grid at the outlet based on the transmission delay time. Calculate the pressure difference for each corresponding grid, where the pressure difference is the difference between the pressure value of the grid at the inlet and the pressure value of the corresponding grid at the outlet; If the total pressure difference of all grids exceeds the preset proportional threshold, a global blockage warning is triggered. If the pressure difference of multiple consecutive adjacent grids exceeds the preset threshold, a local blockage warning is triggered.

[0013] Another aspect of this application provides an early warning system for clogging of excavated soil during drilling in soil and rock layers, comprising: The grid division module deploys multiple single-point pressure sensors in the drill rod that transports excavated soil. The cross-section of the drill rod outlet is divided into grids according to a preset rule, and the orthographic projection of the multiple single-point pressure sensors at the drill rod outlet coincides with the corresponding grid. The reconstruction module, combined with the axial attenuation model, reconstructs the pressure values ​​of each grid on the outlet cross-section based on the original pressure values ​​collected by each single-point pressure sensor. The early warning module provides early warning of blockage in the transport of excavated soil based on the pressure values ​​of each grid on the outlet cross-section.

[0014] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application provides a method and system for early warning of blockage in excavated soil transportation during drilling in soil and rock layers. First, the drill pipe outlet cross-section is divided into grids according to a preset rule. Multiple single-point pressure sensors are deployed in the drill pipe, with the orthographic projection of each sensor at the outlet coinciding with its corresponding grid. This disperses the sensors at different axial positions, preventing them from concentrating on the flow area of ​​the same cross-section and avoiding reverse blockage caused by sensor deployment. Next, using an axial attenuation model, the original pressure values ​​upstream of the corresponding grid collected by each sensor are converted into pressure values ​​for the corresponding grid at the outlet cross-section, reconstructing the complete pressure distribution of each grid at the outlet cross-section. Finally, blockage warning is issued based on the reconstructed full-section grid pressure values, accurately reflecting the actual accumulation state of excavated soil at the outlet. Through the sequential coordination of these steps, interference from sensor deployment on excavated soil transportation is eliminated, and accurate acquisition of the full-section pressure at the outlet is achieved, effectively improving the accuracy and timeliness of excavated soil transportation blockage warning. Attached Figure Description

[0015] Figure 1 This application provides a flowchart illustrating a method for early warning of blockage in the transport of excavated soil during drilling in soil and rock layers, according to one embodiment of the present application. Figure 2 This is a schematic diagram of a soil and rock drilling and spoil transportation scenario provided in one embodiment of this application; Figure 3 This application provides a schematic flowchart of the calibration of the axial attenuation coefficient for a method for early warning of clogging of excavated soil during drilling in soil and rock layers, according to one embodiment of the present application. Figure 4 This application provides a schematic flowchart of a method for calibrating the soil accumulation adaptation factor in a method for early warning of soil blockage during soil and rock drilling. Figure 5 This application provides a schematic diagram of the process before providing an early warning method for muck conveying blockage in soil and rock drilling, based on the pressure values ​​of each grid on the outlet cross section. Figure 6 This application provides a schematic flowchart of a method for early warning of muck conveying blockage in soil and rock drilling, which is based on the pressure values ​​of each grid on the outlet cross section to provide early warning of muck conveying blockage. Figure 7 This application provides a schematic diagram of the structure of a clogging warning device for excavated soil transport in soil and rock drilling, according to one embodiment. Detailed Implementation

[0016] To better understand this application, various aspects of this application will be described in more detail with reference to the accompanying drawings. It should be understood that these detailed descriptions are merely illustrative of exemplary embodiments of this application and are not intended to limit the scope of this application in any way. Throughout the specification, the same reference numerals refer to the same elements. Descriptions and / or include any and all combinations of one or more of the associated listed items.

[0017] It should be noted that, where there is no conflict, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0018] The first aspect of this application provides a method for early warning of blockage in the transport of excavated soil during drilling in soil and rock layers, such as... Figure 1 As shown, it includes: S100: Multiple single-point pressure sensors are deployed in the drill rod for conveying excavated soil, wherein the cross-section of the drill rod outlet is divided into grids according to a preset rule, and the orthographic projection of the multiple single-point pressure sensors at the drill rod outlet coincides with the corresponding grid.

[0019] S200: Combining the axial attenuation model, the pressure values ​​of each grid on the outlet cross section are reconstructed based on the original pressure values ​​collected by each single-point pressure sensor.

[0020] S300: Provides early warning of slag and soil conveying blockage based on the pressure values ​​of each grid on the outlet cross section.

[0021] In this embodiment, the cross-section of the drill pipe outlet is first divided into grids according to a preset rule. The grid division is adapted to the inner diameter of the drill pipe and the detection range of the sensor, ensuring that each grid can independently reflect the soil accumulation status of the corresponding area, and avoiding pressure sensing overlap or blind spots due to improper grid size.

[0022] Specifically, the drill pipe exit cross-section is typically circular, and the size and shape of the mesh can be set according to the area of ​​the drill pipe exit cross-section, such as... Figure 2As shown, preset rules can be set to divide the drill pipe outlet cross-section into a grid, resulting in a grid of the desired size and shape in most of the central area of ​​the cross-section. For example, in a specific example, to balance detection accuracy and cost, a square grid shape can be chosen, with the grid width being one-tenth of the drill pipe outlet cross-sectional area. The preset rule then divides the outlet cross-sectional area into multiple grids arranged in an array using multiple mutually perpendicular horizontal lines and multiple vertical lines. The distance between adjacent horizontal and vertical lines is a preset spacing, which is the width of the grid. Thus, the resulting grids are mostly square grids with a width equal to the preset spacing. Of course, it should be noted that in practical applications, those skilled in the art can set the size and shape of the grid according to actual needs such as control accuracy and cost, and set corresponding preset rules so that dividing the drill pipe outlet cross-section according to the preset rules can yield a grid of the desired size and shape. This application does not limit this. For example, in other embodiments, multiple parallel lines in the two directions of the grid division can be made not mutually perpendicular, thereby obtaining a rhomboid grid.

[0023] In the sensor deployment stage, a single-point pressure sensor is set up for each grid, corresponding one-to-one with each grid, and deployed on the upstream side of the drill pipe axis. The sensor's orthographic projection must be within the target grid. This application disperses the sensors axially within the drill pipe and reconstructs the outlet section pressure using a model, thus avoiding the problem of increased blockage caused by concentrated sensor deployment at the drill pipe outlet. In practical applications, single-point pressure sensors can be positioned on the upstream side of the drill pipe axis corresponding to the corresponding grid using methods such as central suspension. Specifically, a hole can be opened on the side of the pipe, and the sensor can be suspended in the drill pipe through the side opening by using a long rod with a base and fixing the sensor at the top of the rod. The base can then be fixed to the drill pipe with a threaded connection to stabilize the sensor's position. Of course, other fixing methods can also be used to fix the base to the drill pipe, which are conventional techniques in this field and will not be elaborated here. In other optional embodiments, a cross or star-shaped bracket can be set in the drill pipe by welding or drilling, and the sensor can be fixed on the bracket to achieve the purpose of positioning the single-point pressure sensor on the upstream side of the drill pipe axis corresponding to the corresponding grid. The grid division rules can be flexibly adjusted according to the cross-sectional shape of the drill pipe, and this application is not limited to this, as long as the unique correspondence between the sensor and the grid is guaranteed. It should be noted that, in one embodiment, ensuring the sensor's orthographic projection is within the target grid means that the center of the sensor's orthographic projection along the drill pipe axis on the drill pipe exit cross-section coincides with the center of the corresponding grid. In other embodiments, corner points or other feature points of each sensor's orthographic projection can also coincide with pre-selected points within the corresponding grid. Those skilled in the art can set the specific settings for the correspondence between the sensor and the grid according to actual needs, and this application does not limit this.

[0024] The concept of this application is to reconstruct the outlet grid pressure value based on the original pressure value and the axial attenuation model. Specifically, in the embodiments of this application, the axial attenuation model can introduce a slag pile adaptation factor. This allows for the correction of differences in pressure transmission efficiency based on the particle morphology and accumulation characteristics of soil, rock, and slag layers. Specifically, abnormal changes in pressure distribution, such as a sustained increase in local pressure or a decrease in overall pressure uniformity, can be used to identify slag accumulation trends. For example, multiple early warning thresholds can be set.

[0025] The following section discusses the suitability factors for waste soil stockpiling in this application. The embodiments are described in detail.

[0026] Figure 2 This application illustrates a scenario of soil and rock drilling and excavation transport in an embodiment of the present application. Figure 2 As shown, the excavated soil is transported via a conveyor drill pipe. Figure 2 Section AA is the outlet section of the conveying pipe, and section BB is the inlet section of the conveying pipe. Figure 2 The grid diagram in the image is the cross-sectional grid after the AA section is gridded. Since the pressure sensors are located at different cross-sections, they will not cause obstacles to the transport of excavated soil. There will be no problem of reverse blockage caused by the large reduction of the area of ​​a single cross-section due to the arrangement of sensors. If the existing technology needs to accurately detect the pressure at the AA section, it is necessary to deploy multiple sensors on the cross-section at the outlet to form a pressure distribution. This application converts the pressure data at different cross-sections to the same cross-section by combining an axial attenuation model, thereby achieving accurate detection of the outlet pressure distribution without causing blockage.

[0027] In one or more embodiments of this application, before reconstructing the pressure values ​​of each grid on the outlet cross section using the axial attenuation model, the method further includes: calibrating the parameters of the axial attenuation model, the parameters including a pressure baseline, an axial attenuation coefficient, and a spoil accumulation adaptation factor, wherein the pressure baseline is the static stable pressure value of the corresponding grid sensor when there is no spoil flow, the axial attenuation coefficient is a parameter reflecting the rate of attenuation of spoil pressure along the drill pipe axis, and the spoil accumulation adaptation factor is a parameter reflecting the influence of the particle shape and accumulation characteristics of soil rock spoil on pressure transmission.

[0028] In this embodiment, before determining the outlet grid pressure value using the axial attenuation model, the model parameters need to be calibrated. The parameters of the axial attenuation model include the pressure baseline, axial attenuation coefficient, and spoil pile fit factor. These three factors correspond to different physical influencing factors and require targeted calibration to adapt to the conditions of transporting soil, rock, and excavated materials. The pressure baseline is defined as the static stable pressure value of the corresponding grid sensor when there is no excavated material flow; it can compensate for systematic errors caused by sensor temperature drift, installation stress, and environmental static pressure. The axial attenuation coefficient reflects the natural attenuation rate of pressure along the drill pipe axis and is related to pipe wall roughness and transport speed. Excavated material accumulation adaptation factor. This method can quantify the impact of the soil's own packing state on pressure transmission and can be adapted to the characteristics of soil, rock, and slag layers. It should be noted that parameter calibration must be performed under environmental conditions similar to actual operating conditions to avoid parameter inaccuracies due to differences in operating conditions. Parameter calibration can be performed using joint calibration or step-by-step calibration methods; this application is not limited to these methods, as long as the compatibility of the three parameters is ensured. For example, a pressure baseline can be calibrated first, and then the axial attenuation coefficient and the slag packing adaptation factor can be calibrated separately based on the baseline. The rationality of the parameters is verified step by step to improve the overall accuracy of the model.

[0029] In one or more embodiments of this application, calibrating the pressure baseline includes: keeping the drill pipe free of slag flow and under normal operating conditions, collecting multiple consecutive frames of raw pressure values ​​from each single-point pressure sensor, and taking the average value under stable operating conditions as the pressure baseline of the grid corresponding to each single-point pressure sensor.

[0030] In this embodiment, the calibration of the pressure baseline must meet strict environmental and operational conditions to ensure the stability and reliability of the calibration results. First, it is necessary to keep the drill pipe free of slag flow to avoid continuous pressure interference from residual slag on the sensor. Simultaneously, the environmental conditions must be kept stable, including constant parameters such as temperature, humidity, and air pressure. These factors directly cause zero-point drift in the sensor, affecting baseline accuracy. Specifically, the constantness of parameters such as temperature, humidity, and air pressure in a stable operating state means that the values ​​of these parameters fluctuate within a preset stable state range and do not exceed the stable state value range.

[0031] It should be noted that, in the embodiments of this application, normal operating conditions refer to the drilling rod being in the design-permissible operating state during the drilling of soil and rock, and the flow rate, conveying pressure, drilling speed, propulsion force, as well as the moisture content and particle size distribution of the excavated soil being within the design range. That is, the values ​​of the above parameters are all within the range of values ​​corresponding to the normal operating conditions preset in the design. This indicates that there is no obvious accumulation, no blockage, and no jamming inside the drill rod, the excavated soil flows in a continuous and stable manner, and all components of the equipment operate smoothly without abnormal vibration or abnormal load.

[0032] It should be noted that the specific numerical ranges of the steady state and the normal operating conditions in this application can be set by those skilled in the art according to actual needs in practical applications, and this application does not limit them.

[0033] During the data acquisition phase, multiple consecutive frames of raw pressure values ​​from each sensor need to be acquired. It should be noted that the purpose of acquiring multiple consecutive frames is to cancel out the sensor's instantaneous random noise and ensure that the baseline reflects the sensor's true static output. The number of frames acquired can be adjusted according to the sensor's noise characteristics; when the noise is high, the number of frames can be appropriately increased until the data fluctuation amplitude meets the stability requirements. This application is not limited to this.

[0034] The average value under stable conditions is taken as the pressure baseline for the corresponding grid. In this embodiment, stable conditions refer to the pressure value fluctuation within a preset allowable range for multiple consecutive frames, indicating that the sensor output has reached static equilibrium. It should be noted that due to individual differences in sensors and different installation positions, there may be deviations in the static output. The pressure baseline of each grid sensor can be calibrated individually. Individual calibration can avoid cross-interference, which will not be elaborated on in this application.

[0035] In one or more embodiments of this application, such as Figure 3 As shown, the calibration of the axial attenuation coefficient includes: S210: Transport standard construction waste under normal operating conditions to maintain a stable flow rate and accumulation status of the construction waste.

[0036] S220: Deploy temporary pressure sensing elements at the grid positions corresponding to the outlet cross-section to measure the actual outlet pressure of the grid.

[0037] S230: Synchronously acquire the original pressure value of the upstream single-point pressure sensor corresponding to the temporary pressure sensing element, combine it with the calibrated pressure baseline, the slag pile adaptation factor, the actual outlet pressure of the temporary pressure sensing element and the axial distance between the single-point pressure sensor and the corresponding temporary pressure sensing element, and solve the axial attenuation coefficient of each grid. Take the average value of the axial attenuation coefficients of all grids as the final axial attenuation coefficient.

[0038] In this embodiment, the calibration of the axial attenuation coefficient requires standard slag as the test object. The standard slag must closely match the actual drilling scenario in soil and rock layers, ensuring that its particle size, particle shape, and gradation are consistent with the actual transported slag. During the calibration process, the standard slag must be transported under normal operating conditions to maintain stable slag flow and accumulation state (loose accumulation, medium-dense, or high-dense) to avoid distortion of the pressure attenuation law due to fluctuations in operating conditions. To obtain the true pressure value of the outlet grid, a temporary pressure sensing element can be deployed at the grid position corresponding to the outlet cross-section, and it must be aligned with the target grid. To ensure that the installation method does not affect the slag flow, the same inlet pressure and fluid with the same physicochemical properties can be controlled to align the pressure sensing element with one of the grids within a certain period of time, and the pressure at the grid position can be detected. It should be noted that the temporary pressure sensing element is only used in the calibration stage and can be removed after calibration to avoid long-term deployment affecting the transport efficiency.

[0039] It should be noted that, in this application, consistency and stability refer to the fact that when the corresponding parameter values ​​fluctuate within the corresponding numerical range, they are considered to have reached a consistent and stable state. The range of fluctuation values ​​can be set by those skilled in the art according to actual needs, and this application does not limit it. The data acquisition process requires the simultaneous acquisition of the raw pressure values ​​from the upstream sensors and the actual outlet pressure values ​​from the temporary components. In this embodiment, the inverse formula for the axial attenuation coefficient for each grid is:

[0040] in, This is the axial attenuation coefficient. This is the actual outlet pressure value measured by the temporary sensing element. This is the pressure baseline for the corresponding grid. The raw pressure value collected by the upstream sensor. Adaptation factors for slag and soil accumulation. This represents the axial distance between the sensor and the outlet cross-section. It should be noted that the original pressure value is baseline corrected before inverse kinematics analysis. This ensures that the calculation reflects the attenuation of the effective pressure of the slag. The average of the axial attenuation coefficients of all grids is taken as the final attenuation coefficient. Statistical averaging is used to offset the calibration random errors of individual grids, thereby improving the robustness of the model.

[0041] In one or more embodiments of this application, such as Figure 4 As shown, the calibration factors for spoil stockpiling include: S240: Select typical slag samples covering three stacking states: loose, medium-dense, and high-dense, in the soil and rock drilling scenario.

[0042] S250: Transports typical slag samples for each stacking condition, collects the original pressure value of the corresponding single-point pressure sensor and the actual pressure value of the corresponding grid at the outlet.

[0043] S260: Combining the calibrated pressure baseline, axial attenuation coefficient, and axial distance between the sensor and the outlet, the soil accumulation adaptation factor for each accumulation state is obtained by inverse solution.

[0044] S270: Set weights according to the frequency of occurrence of each stacking state in actual working conditions, calculate the mean value of the slag and soil stacking adaptation factor under all stacking states, and use it as the final slag and soil stacking adaptation factor.

[0045] In this embodiment of the application, the soil and waste accumulation adaptation factor The calibration needs to cover typical stockpiling states of soil, rock, and slag. Therefore, typical slag samples with loose, medium-dense, and high-dense stockpiling states are selected. These three states can cover the main stockpiling forms of slag in actual working conditions, ensuring the accuracy of the calibration. It has full compatibility.

[0046] The parameters for loose, medium-dense, and high-dense packing states are shown in Table 1. Typical slag samples for the different packing states can be set according to the parameter range in Table 1.

[0047] Table 1

[0048] During calibration, typical waste soil samples must be transported separately for each stacking condition to maintain flow rate and stacking stability under each condition and avoid cross-interference between different conditions. Simultaneously, the raw pressure values ​​of the corresponding sensors and the actual pressure values ​​at the outlet grid are collected. The actual pressure values ​​are still obtained through temporary sensing elements, and the acquisition logic is consistent with the axial attenuation coefficient calibration. Waste soil stacking adaptation factor. The inverse solution requires combining the calibrated pressure baseline, axial attenuation coefficient, and axial distance between the sensor and the outlet. The inverse solution formula is:

[0049] It should be noted that weights are assigned based on the frequency of occurrence of each stockpiling state in actual working conditions, and the average value is calculated as the final soil stockpiling suitability factor. If a certain type of accumulation state accounts for a very high proportion in a particular working condition, the weight allocation can be adjusted or that state can be calibrated separately. This application is not limited to further improving compatibility.

[0050] In one or more embodiments of this application, reconstructing the pressure values ​​of each grid on the outlet cross section using an axial attenuation model includes: substituting the filtered effective pressure value into the axial attenuation model, wherein the axial attenuation model takes the effective pressure value, axial attenuation coefficient, axial distance between the sensor and the outlet, and slag pile adaptation factor as inputs, corrects the pressure transmission efficiency through the slag pile adaptation factor, and then calculates the true outlet pressure value of each grid by combining the axial attenuation coefficient corresponding to the axial distance.

[0051] In this embodiment of the application, when calculating the true outlet pressure value using the axial attenuation model, the filtered effective pressure value can be used as input. It should be noted that the effective pressure value is the result of the original pressure value after baseline correction. If the corrected value is negative, it is forcibly set to zero to ensure that the pressure value input to the model can truly reflect the working state of the slag.

[0052] The expression for the axial attenuation model is:

[0053] in: This represents the actual pressure value of the grid corresponding to the outlet cross-section. This represents the effective pressure value after baseline correction and non-physical value filtering. The logic of this model is based on the soil accumulation adaptation factor. Correct the transmission efficiency of the effective pressure value, and then pass through the exponential decay term. The natural pressure decay along the axial direction is corrected to ensure that the calculation results closely match the composite decay law of material conveying. It should be noted that the model input parameters must be consistent, i.e., the effective pressure value, , , They all correspond to the same grid.

[0054] In one or more embodiments of this application, determining the pressure value of each grid on the outlet cross-section includes: arranging and combining the actual outlet pressure values ​​of all grids in a preset grid coordinate order to form a complete pressure matrix covering the outlet cross-section, wherein each element of the pressure matrix corresponds one-to-one with the corresponding grid, and the set of all elements in the pressure matrix is ​​the pressure value of each grid on the outlet cross-section.

[0055] In this embodiment, forming a complete pressure matrix covering the outlet cross-section requires arranging the actual outlet pressure values ​​of all grids according to a preset grid coordinate order. For example, the coordinate order can be a Cartesian coordinate order from left to right and from top to bottom, or a polar coordinate order from center to edge and from 0° to 360°. This application does not limit this, as long as the grid position corresponds one-to-one with the matrix element.

[0056] The dimensions of the pressure matrix are exactly the same as the number of mesh divisions in the outlet cross-section, i.e., the number of mesh divisions is... At that time, the pressure matrix is ​​a two-dimensional matrix with M rows and N columns, and the matrix elements are... The pressure matrix directly corresponds to the actual pressure value of the grid in the i-th row and j-th column. It should be noted that the pressure matrix is ​​generated without additional interpolation or fitting operations, as each element is derived from the sensor data of the corresponding grid through model correction, avoiding accuracy loss caused by interpolation. This application is not limited to this; if it is necessary to improve the visual continuity of the pressure distribution in practical applications, the pressure values ​​of adjacent grids can be slightly smoothed, but this must be done without compromising the authenticity of the original measurement data. The pressure matrix integrates the scattered grid pressure values ​​into structured data, facilitating subsequent visualization of the pressure distribution.

[0057] In one or more embodiments of this application, such as Figure 5 As shown, before issuing an early warning for the blockage of the excavated soil conveying based on the pressure values ​​of each grid on the outlet cross-section, the method further includes: S310: The feed inlet adopts a grid division and sensor deployment scheme that is completely consistent with the outlet, so that the grids of the feed inlet and the outlet correspond one-to-one.

[0058] S320: Collects the original pressure values ​​of the sensors corresponding to each grid at the feed inlet, and uses the same pressure baseline calibration, axial attenuation coefficient calibration, slag pile adaptation factor calibration, and axial attenuation model calculation logic as the outlet to determine the pressure value of each grid at the feed inlet.

[0059] In this embodiment, to achieve effective comparison between the inlet and outlet pressure values, the inlet must adopt a grid division and sensor deployment scheme completely consistent with the outlet—the number, size, and coordinate rules of the grids are the same, and the sensor models and installation methods are identical. After collecting the original pressure values ​​of each grid sensor at the inlet, the grid pressure value at the inlet must be determined using parameter calibration and model calculation logic consistent with the outlet. It should be noted that the pressure baseline and axial attenuation coefficient at the inlet need to be calibrated separately because the environmental conditions and drill rod characteristics at the inlet differ from those at the outlet; separate calibration can improve data accuracy. (Slag and soil accumulation adaptation factor) The correlation with drill pipe position is relatively small, and the soil accumulation adaptation factor is relatively small. The final value consistent with the export value can be used.

[0060] The calculation model for the actual pressure value of the inlet grid is consistent with that of the outlet, and the expression is:

[0061] in: This represents the actual pressure value of the grid corresponding to the feed inlet. The effective pressure value at the inlet after baseline correction and non-physical value filtration. The axial attenuation coefficient is calibrated separately for the feed inlet. This is the axial distance between the inlet sensor and the inlet cross-section. This is the pressure baseline of the grid corresponding to the feed inlet.

[0062] In one or more embodiments of this application, such as Figure 6 As shown, early warning of blockage in the construction waste transportation is provided based on the pressure values ​​of each grid on the outlet cross-section, including: S330: Determine the transmission delay time of the slag from the inlet to the outlet through working condition calibration, and align the pressure values ​​of each grid at the inlet with the pressure values ​​of the corresponding grid at the outlet based on the transmission delay time.

[0063] S340: Calculate the pressure difference for each corresponding grid, where the pressure difference is the difference between the pressure value of the inlet grid and the pressure value of the corresponding outlet grid.

[0064] S350: If the total pressure difference of all grids exceeds the preset proportional threshold, a global blockage warning is triggered. If the pressure difference of multiple consecutive adjacent grids exceeds the preset threshold, a local blockage warning is triggered.

[0065] In this embodiment, since there is a transmission delay time when the excavated soil is transported from the inlet to the outlet, it needs to be determined through working condition calibration. This time calibration method can be achieved by simulating the transmission and recording time intervals, calculating the ratio of the transmission speed to the drill rod length, or deriving from the peak pressure time difference of the sensors, ensuring that the accuracy of time alignment matches the accuracy of pressure value calculation. It should be noted that different working conditions correspond to different transmission delay times. For different working conditions, corresponding transmission delay times can be preset. For example, after obtaining experimental data through experimental simulation, the correspondence between parameter values ​​and transmission delay times for different working conditions can be fitted. Therefore, under a given working condition, the corresponding transmission delay time can be determined based on the specific parameter values ​​of the working condition and the preset correspondence.

[0066] Based on transmission delay time Time alignment is performed, specifically by aligning the grid pressure value at time t at the feed inlet. With exit time The corresponding grid pressure value Pairing is necessary to ensure that both time alignment and time synchronization reflect the pressure status of the same batch of excavated soil at different locations. It should be noted that the accuracy of time alignment must be compatible with the sensor sampling rate to avoid pressure value mismatch due to time differences. Both the inlet and outlet pressure values ​​are... Corrections can further improve the reliability of data comparison after alignment.

[0067] After time alignment, the pressure difference for each corresponding grid is calculated. The pressure difference is defined as the difference between the pressure value of the inlet grid and the pressure value of the corresponding outlet grid. The calculation formula is as follows:

[0068] in: The pressure difference is the corresponding grid number (i,j). For the feed inlet, the (i,j) grid is the adaptation factor for the slag-soil accumulation. The actual pressure value after model correction. For the export grid (i,j), the adaptation factor is based on the soil accumulation. The actual pressure value after model correction.

[0069] It should be noted that, due to and All have undergone The correction can accurately reflect the pressure transmission results under different stacking conditions, therefore This method can accurately quantify the pressure loss of the same batch of excavated soil within the drill pipe, avoiding misjudgments of blockage due to distorted pressure calculations. In this embodiment, the pressure difference calculation needs to be performed independently on a grid-by-grid basis, and the pressure difference of each grid serves as the basis for subsequent blockage determination, ensuring that both local and global anomalies can be effectively identified.

[0070] When a global blockage warning is issued, the total pressure difference across all grids can be calculated. If the total pressure difference exceeds a preset proportional threshold, a global blockage warning is triggered. It should be noted that the preset proportional threshold should be set based on the statistical value of the total pressure difference under normal operating conditions, reflecting the critical state of global muck retention in the drill pipe—when the total pressure difference frequently increases, it indicates that a large amount of muck is accumulating inside the drill pipe, obstructing overall flow. This application is not limited to this; the calculation of the total pressure difference can also use a weighted summation method, assigning higher weights to grids in the drill pipe's central area and easily blocked areas to improve warning sensitivity. When a local blockage warning is issued, the pressure difference between consecutive adjacent grids can be detected. If the pressure difference between multiple consecutive adjacent grids exceeds a preset threshold, a local blockage warning is triggered. For example, multiple consecutive adjacent grids can be set to three or more, and the preset threshold should be set based on the fluctuation range of the pressure difference between adjacent grids under normal operating conditions. It should be noted that the local blockage warning identifies continuous accumulation—the pressure difference of a single grid may originate from random interference, while the pressure difference between consecutive adjacent grids frequently indicates that there is continuous muck accumulation in that area, forming a local blockage trend. In this embodiment, the output format of the blockage warning can be set according to engineering requirements, including audible and visual alarms, control system signal output, and visual prompts of the blockage location. It should be noted that the warning threshold is not fixed and can be dynamically adjusted according to changes in operating conditions such as the type of excavated soil and conveying speed. The adjustment logic can refer to the pressure baseline, axial attenuation coefficient, and excavated soil accumulation adaptation factor. The calibration results ensure the adaptability and accuracy of the early warning. This application is not limited to this. It can also optimize the early warning logic by statistically analyzing the rate of change of pressure difference, so as to realize the early prediction of blockage risk and further reduce the losses caused by blockage.

[0071] This application provides a method for early warning of muck transport blockage in soil and rock drilling. The method involves dividing the drill rod outlet cross-section into a grid, and then deploying pressure sensors at different axial positions of the drill rod for each grid. The orthographic projection of the pressure sensor onto the cross-section corresponds to each grid. Because the pressure sensors are positioned differently along the axial direction, monitoring pressure does not interfere with muck transport. The outlet cross-section is then reconstructed using the sensor data from different positions based on an axial attenuation model. This reconstruction yields the pressure values ​​for each grid corresponding to the outlet cross-section, forming a gridded pressure distribution map. This application uses an axial attenuation model to convert pressure data detected at different axial positions of the drill rod to pressure data at the outlet cross-section. The gridded pressure distribution map is then used for outlet pressure detection, allowing for accurate determination of muck transport blockage in soil and rock drilling by combining the difference between inlet and outlet pressures. Furthermore, since the pressure sensors are not located at the same cross-section, muck blockage is prevented.

[0072] The embodiments of this application will be described in detail below with reference to specific scenarios.

[0073] Early Warning System for Blockage in Drill Pipe Transportation of Soil and Rock Excavated Material During Drilling: In a construction project, soil and rock excavated material generated during drilling needs to be transported to a designated stockpile area via drill pipes. Due to the uneven particle size and protruding edges of the excavated material, blockages can easily occur during the transport process, leading to construction interruptions. To ensure continuous transport, this solution implements a blockage early warning system. Before construction, the drill pipe outlet cross-section is divided into several regular grids according to a preset rule, ensuring that each grid can independently cover a region of the outlet cross-section, and that the grid size is compatible with the detection range of the single-point pressure sensor. Subsequently, a single-point pressure sensor is deployed on the upstream side of the drill pipe axis corresponding to each grid. During installation, the sensor position is strictly adjusted so that the sensor's orthographic projection is within the target grid, and the sensor is flush with the inner wall of the drill pipe. This avoids the sensor protruding into the drill pipe and interfering with the flow of excavated material, and also prevents indentation from causing pressure acquisition deviations. At the same time, the drill pipe inlet adopts a grid division and sensor deployment scheme that is completely consistent with the outlet, ensuring a one-to-one correspondence between the inlet and outlet grids.

[0074] When there is no soil flow inside the drill pipe and the construction site environment is stable, the sensor data acquisition system is activated to collect multiple consecutive frames of raw pressure values ​​from each sensor. After the data fluctuation amplitude meets the stability requirements, the average value of each sensor under stable conditions is taken as the pressure baseline for the corresponding grid, which is used to subsequently offset static interferences such as sensor temperature drift and installation stress. Soil samples in loose, medium-dense, and high-dense states are selected and transported through the drill pipe according to each state. During the process, the soil flow rate and state are kept stable, and the raw pressure values ​​of each grid sensor are collected simultaneously. At the same time, temporary pressure sensing elements are deployed at the corresponding grid positions on the outlet cross-section to measure the actual outlet pressure of each grid.

[0075] Based on the calibrated pressure baseline and the preset axial distance between the sensor and the outlet, the soil accumulation adaptation factor η for each grid under each accumulation state is calculated using an inverse kinematics formula. Then, weights are assigned according to the frequency of occurrence of the three accumulation states in actual construction, and the average value of η under all accumulation states is calculated as the final soil accumulation adaptation factor η. Standard soil is transported under normal construction conditions, maintaining stable flow rate and accumulation state, while simultaneously collecting the original pressure values ​​from the upstream sensors of each grid and the actual pressure values ​​from the temporary outlet sensors. Based on the calibrated pressure baseline, soil accumulation adaptation factor η, and axial distance between the sensor and the outlet, the axial attenuation coefficient of each grid is calculated using an inverse kinematics formula. The average value of the axial attenuation coefficients of all grids is taken as the final attenuation coefficient, completing the parameter calibration of the axial attenuation model.

[0076] During construction, sensors continuously collect raw pressure values ​​at a preset sampling rate. The data acquisition system stores data according to grid coordinates, ensuring that each frame of data corresponds to the pressure state at the same moment. Subsequently, the raw pressure value of each sensor is subtracted from the pressure baseline of the corresponding grid to obtain the effective pressure value reflecting the pressure of the excavated soil. If the effective pressure value is negative, it is forcibly set to zero to filter out non-physical interference. The filtered effective pressure value is substituted into the axial attenuation model to calculate the true outlet pressure value of each grid. Simultaneously, after the sensors at the feed inlet collect raw pressure values, they are calibrated using the same pressure baseline as the outlet, axial attenuation coefficient calibration, excavated soil accumulation adaptation factor η calibration, and axial attenuation model calculation logic to determine the true pressure value of each grid at the feed inlet.

[0077] Following a preset grid coordinate order, the actual outlet pressure values ​​of all grids are sequentially arranged and combined to form a complete pressure matrix covering the outlet cross-section, with each element in the matrix corresponding to a specific grid. The transmission delay time of the excavated soil from the inlet to the outlet is determined through operational condition calibration. Based on this delay time, the pressure values ​​of each grid at the inlet are time-aligned with the pressure values ​​of the corresponding grid at the outlet to ensure they correspond to the same batch of excavated soil. Subsequently, the pressure difference is calculated grid by grid to obtain the pressure loss data for each grid.

[0078] The total pressure difference across all grids is calculated. If the total pressure difference exceeds a preset threshold, it indicates a large accumulation of excavated soil within the drill pipe, obstructing overall flow. The system immediately triggers a global blockage warning, issuing an audible and visual alarm and sending a deceleration command to the construction control system. If the pressure difference of multiple adjacent grids exceeds the preset threshold, it indicates a continuous accumulation of excavated soil in that area, forming a local blockage trend. The system triggers a local blockage warning, marking the blockage area on the monitoring interface and prompting operators to conduct targeted troubleshooting. During construction, if the type of excavated soil or the conveying speed is significantly adjusted, technicians restart the parameter calibration process, updating the pressure baseline, axial attenuation coefficient, and excavated soil accumulation adaptation factor η to ensure the axial attenuation model always adapts to the current working conditions, maintaining the accuracy and reliability of the blockage warning.

[0079] The second aspect of this application provides an early warning system for clogging of excavated soil during drilling in soil and rock layers, such as... Figure 7 As shown, it includes: The grid division module 11 deploys multiple single-point pressure sensors in the drill rod that transports excavated soil. The cross-section of the drill rod outlet is divided into grids according to a preset rule, and the orthographic projection of the multiple single-point pressure sensors at the drill rod outlet coincides with the corresponding grid.

[0080] The reconstruction module 12, in conjunction with the axial attenuation model, reconstructs the pressure values ​​of each grid on the outlet cross section based on the original pressure values ​​collected by each single-point pressure sensor.

[0081] The early warning module 13 provides an early warning of blockage in the transport of excavated soil based on the pressure values ​​of each grid on the outlet cross section.

[0082] Since the principle behind this system's problem-solving is similar to the methods described above, the implementation of this system can be found in the implementation of the methods, and will not be repeated here.

[0083] 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 invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for early warning of blockage in the transport of excavated soil during drilling in soil and rock layers, characterized in that, include: Multiple single-point pressure sensors are deployed in the drill rod for conveying excavated soil. The cross-section of the drill rod outlet is divided into grids according to a preset rule, and the orthographic projection of the multiple single-point pressure sensors at the drill rod outlet coincides with the corresponding grid. Combining the axial attenuation model, the pressure values ​​of each grid on the outlet cross section are reconstructed based on the original pressure values ​​collected by each single-point pressure sensor. Early warning of slag and soil transport blockage is generated based on the pressure values ​​of each grid on the outlet cross section.

2. The method according to claim 1, characterized in that, Before reconstructing the pressure values ​​of each grid on the outlet cross section using the axial attenuation model, the following steps are also included: The parameters of the axial attenuation model are calibrated. The parameters include pressure baseline, axial attenuation coefficient and slag accumulation adaptation factor. The pressure baseline is the static stable pressure value of the corresponding grid sensor when there is no slag flow. The axial attenuation coefficient is a parameter reflecting the rate of attenuation of slag pressure along the drill rod axis. The slag accumulation adaptation factor is a parameter reflecting the influence of soil layer rock slag particle morphology and accumulation characteristics on pressure transmission.

3. The method according to claim 2, characterized in that, The calibration pressure baseline includes: keeping the drill pipe free of slag flow and under normal operating conditions, collecting multiple consecutive frames of raw pressure values ​​from each single-point pressure sensor, and taking the average value under stable operating conditions as the pressure baseline of the grid corresponding to each single-point pressure sensor.

4. The method according to claim 2, characterized in that, The calibration of the axial attenuation coefficient includes: Transport standard construction waste under normal operating conditions to keep the flow rate and accumulation status of the construction waste stable. Temporary pressure sensing elements were deployed at the grid positions corresponding to the outlet cross-section, and the actual outlet pressure of the grid was measured. The original pressure values ​​of the upstream single-point pressure sensors corresponding to the temporary pressure sensing elements are collected synchronously. Combined with the calibrated pressure baseline, the soil accumulation adaptation factor, the actual outlet pressure of the temporary pressure sensing elements, and the axial distance between the single-point pressure sensors and the corresponding temporary pressure sensing elements, the axial attenuation coefficient of each grid is obtained by inverse solution. The average value of the axial attenuation coefficients of all grids is taken as the final axial attenuation coefficient.

5. The method according to claim 2, characterized in that, The calibration of the soil and waste stockpiling suitability factors includes: Typical slag samples covering three deposition states—loose, medium-dense, and high-dense—were selected for drilling scenarios in soil and rock layers. Typical slag samples of each stacking state were transported separately, and the original pressure values ​​of the corresponding single-point pressure sensors and the actual pressure values ​​of the corresponding grid at the outlet were collected. By combining the calibrated pressure baseline, axial attenuation coefficient, and axial distance between the sensor and the outlet, the soil accumulation adaptation factor for each accumulation state is obtained by inverse solution. Weights are assigned according to the frequency of occurrence of each stockpiling state in actual working conditions, and the mean value of the slag stockpiling adaptation factor under all stockpiling states is calculated as the final slag stockpiling adaptation factor.

6. The method according to claim 1, characterized in that, The pressure values ​​of each grid on the outlet cross section are reconstructed by combining the axial attenuation model. This includes substituting the filtered effective pressure value into the axial attenuation model, which takes the effective pressure value, axial attenuation coefficient, axial distance between the sensor and the outlet, and slag pile adaptation factor as inputs. The pressure transmission efficiency is corrected by the slag pile adaptation factor, and then the actual outlet pressure value of each grid is calculated by combining the axial attenuation coefficient corresponding to the axial distance.

7. The method according to claim 6, characterized in that, Determining the pressure value of each grid on the outlet cross-section includes: arranging and combining the actual outlet pressure values ​​of all grids in a preset grid coordinate order to form a complete pressure matrix covering the outlet cross-section. Each element of the pressure matrix corresponds one-to-one with the corresponding grid, and the set of all elements in the pressure matrix is ​​the pressure value of each grid on the outlet cross-section.

8. The method according to claim 1, characterized in that, Before issuing an early warning for the blockage of the excavated soil transport based on the pressure values ​​of each grid on the outlet cross-section, the following steps are also included: The feed inlet adopts a grid division and sensor deployment scheme that is completely consistent with the outlet, so that the grids of the feed inlet and the outlet correspond one-to-one. The original pressure values ​​of the sensors corresponding to each grid at the feed inlet are collected. The pressure baseline, axial attenuation coefficient, slag pile adaptation factor, and axial attenuation model calculation logic consistent with those at the outlet are used to determine the pressure values ​​of each grid at the feed inlet.

9. The method according to claim 8, characterized in that, Early warning of blockage in the construction waste transportation is provided based on the pressure values ​​of each grid on the outlet cross-section, including: The transmission delay time of the slag from the inlet to the outlet is determined by the working condition calibration, and the pressure value of each grid at the inlet is time-aligned with the pressure value of the corresponding grid at the outlet based on the transmission delay time. Calculate the pressure difference for each corresponding grid, where the pressure difference is the difference between the pressure value of the grid at the inlet and the pressure value of the corresponding grid at the outlet; If the total pressure difference of all grids exceeds the preset proportional threshold, a global blockage warning is triggered. If the pressure difference of multiple consecutive adjacent grids exceeds the preset threshold, a local blockage warning is triggered.

10. A clogging early warning system for excavated soil transport during drilling in soil and rock layers, characterized in that, include: The grid division module deploys multiple single-point pressure sensors in the drill rod that transports excavated soil. The cross-section of the drill rod outlet is divided into grids according to a preset rule, and the orthographic projection of the multiple single-point pressure sensors at the drill rod outlet coincides with the corresponding grid. The reconstruction module, combined with the axial attenuation model, reconstructs the pressure values ​​of each grid on the outlet cross-section based on the original pressure values ​​collected by each single-point pressure sensor. The early warning module provides early warning of blockage in the transport of excavated soil based on the pressure values ​​of each grid on the outlet cross-section.

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