Pipe blockage prediction method and device for long-distance foam concrete conveying pipeline

Abstract

The invention belongs to the technical field of pipeline condition prediction, and discloses a long-distance foam concrete conveying pipeline blockage prediction method and device, and the method comprises the steps: collecting first wet density data and second wet density data of foam concrete slurry at an inlet end and an outlet end of a field pipeline respectively; the defoaming rate of the foam concrete slurry in the pipeline conveying process is calculated according to the first wet density data and the second wet density data; predicting the real-time conveying pressure of the pipeline according to the function relationship between the conveying pressure of the pipeline and the defoaming rate; calculating a pipeline blockage risk coefficient according to the real-time conveying pressure of the pipeline; according to the pipeline blockage risk coefficient, the pipeline blockage risk grade and the corresponding risk measure are determined, the function relation between the pipeline conveying pressure and the defoaming rate is constructed, accurate blockage prediction of the long-distance pipeline is achieved, extra monitoring equipment or professional technicians do not need to be added, and only wet density data need to be collected and analyzed, so that the pipeline blockage prediction accuracy is improved. And the problem of long-term maintenance of a large amount of monitoring equipment is avoided.

Description

Technical Field

[0001] The present application relates to the technical field of pipeline condition prediction, and in particular, to a method and device for predicting blockage of a long-distance foamed concrete conveying pipeline. Background Art

[0002] Foamed concrete is a lightweight fluid filling material. Due to its good lightness, fluidity and self-hardening properties, it has currently been widely used in fields such as road abutment backfilling, mine filling, pipeline backfilling, etc. According to incomplete statistics, the annual scale of the domestic foamed concrete sub-market has reached 20 million cubic meters at present, and with the growth of the scale of road infrastructure reconstruction and expansion and the expansion of emerging markets such as oil and gas pipeline filling, its annual scale is still continuously increasing. The construction method of foamed concrete is mainly pipeline pumping. As the key carrier for transporting foamed concrete, the pipeline directly affects the normal production and construction and safety of foamed concrete. Once the conveying pipeline is blocked, it will not only cause the interruption of normal construction operations, but may also cause dangerous accidents such as pipe explosion when the blockage pressure is too high; at the same time, when the blockage repair time is too long, the foamed concrete slurry retained in the pipeline hardens, resulting in a larger area of blockage, and may also cause equipment damage and safety accidents, causing great economic losses and casualties.

[0003] At present, the detection of blockage of foamed concrete conveying pipelines often mainly relies on manual inspection. In ground engineering construction scenarios such as road bridges and municipal transportation, due to the large operation space and short single conveying distance (generally less than 500m), it is feasible to manually inspect the pipeline. However, in engineering construction scenarios such as mine filling and long-distance oil and gas pipeline tunnel filling, due to the underground operation being concealed, the operation space being narrow, and the linear construction distance being long (generally exceeding 10km), the method of manually inspecting the pipeline often fails to detect blockages in a timely manner due to low timeliness, and difficulties in maintenance lead to chain disasters such as pipe explosion, equipment failure and casualties caused by blockages, bringing great safety hazards to the long-distance pumping construction of foamed concrete. In addition, CN117709519A discloses a method and device for predicting blockage of a long-distance pipeline in the field of mine filling, but this method requires additional installation of unequal numbers of pressure sensors, flow meters and other devices according to the pipeline conveying distance, resulting in a great increase in prediction costs, and there are also problems such as distortion of monitoring data collection when the conveying distance is too long and difficulties in maintaining a large number of monitoring devices during long-term monitoring. Therefore, for the long-distance conveying of foamed concrete pipelines, there is an urgent need for an efficient, accurate and easy-to-operate pipeline blockage prediction method to timely predict and evaluate the blockage state of the conveying pipeline and avoid causing pipe blockage or secondary chain disasters. Summary of the Invention

[0004] To solve the problems of low detection efficiency of pipe blockage, untimely risk prediction, and high safety risks in the existing long-distance pipeline transportation of foamed concrete, this application proposes a method for predicting pipe blockage in long-distance foamed concrete transportation pipelines, which can accurately predict the blockage state of foamed concrete transportation pipelines, reduce the risk of pipe blockage during the pumping of foamed concrete, and only need to collect and analyze the data of the wet density, which is an essential measurement index of foamed concrete. This greatly reduces the monitoring and prediction cost of foamed concrete pipe blockage and has the characteristics of simple operation and strong practicability.

[0005] In the first aspect, this application provides a method for predicting pipe blockage in long-distance foamed concrete transportation pipelines, including the following steps: S1: Collect the first wet density data and the second wet density data of the foamed concrete slurry at the inlet end and the outlet end of the on-site pipeline respectively, and calculate the defoaming rate of the foamed concrete slurry during pipeline transportation according to the first wet density data and the second wet density data; S2: Predict the real-time pipeline transportation pressure according to the functional relationship between the pipeline transportation pressure and the defoaming rate; S3: Calculate the pipe blockage risk coefficient according to the real-time pipeline transportation pressure; S4: Determine the pipe blockage risk level and corresponding risk measures according to the pipe blockage risk coefficient.

[0006] The method for predicting pipe blockage in long-distance foamed concrete transportation pipelines provided by this application measures the easily obtainable wet density data of foamed concrete and calculates the defoaming rate, then predicts the real-time pipeline transportation pressure and the pipe blockage risk coefficient, and finally determines the pipe blockage risk level and risk measures. It does not require additional complex and expensive sensor equipment, has simple operation, and can effectively predict the pipe blockage risk of long-distance foamed concrete transportation pipelines.

[0007] Preferably, step S1 includes: Calculate the defoaming rate according to the following formula : ; In the formula is the first wet density data, is the second wet density data.

[0008] The defoaming rate calculation formula provides a quantitative and operable calculation method. Through this formula, the defoaming rate can be quickly and accurately calculated based on the measured first wet density data and second wet density data, laying a foundation for predicting the real-time pipeline transportation pressure based on the defoaming rate in subsequent step S2 and calculating the pipe blockage risk coefficient in step S3, making the entire pipe blockage prediction method more complete and practical.

[0009] Preferably, the first wet density data and the second wet density data are obtained by the measuring cup method. The measuring cup has a standard volume of 1L and is made of a material selected from glass, stainless steel, or plastic.

[0010] The measuring cup method is a standardized density test method, which ensures the standardization of the test process and the accuracy of the test results. By using a measuring cup with a standard volume, the sampling volume can be effectively controlled, reducing errors caused by inconsistent sampling volumes. Limiting the material of the measuring cup can avoid chemical reactions or physical adsorption between the material of the measuring cup and the foamed concrete slurry, thus affecting the accuracy of the test results, ensuring the standardization and accuracy of obtaining density data, further improving the reliability of defoaming rate calculation, and providing data guarantee for the accurate prediction of subsequent pipe blockage risks.

[0011] Preferably, step S2 includes: Constructing a functional relationship between the pipeline transportation pressure and the defoaming rate: ; In the formula is the pipeline transportation pressure value at the i-th level, is the defoaming rate value of the foamed concrete slurry corresponding to the pipeline transportation pressure at the i-th level. i is a positive integer and its value range satisfies 1 ≤ i ≤ N, where N is the total number of pipeline transportation pressure levels and N ≥ 3. a is the first coefficient and b is the second coefficient.

[0012] This functional relationship takes the defoaming rate as the independent variable of the exponential function and the pipeline transportation pressure as the function value. By adjusting the shape and position of the function curve through the first coefficient and the second coefficient, it can adapt to the prediction of the foamed concrete transportation pressure under different working conditions. When the defoaming rate increases, the exponential function value increases, and the pipeline transportation pressure value also increases accordingly, which is in line with the actual situation that the increase in the defoaming rate leads to an increase in the pipeline transportation pressure. By constructing a functional relationship between the pipeline transportation pressure and the defoaming rate, the real-time prediction of the pipeline transportation pressure can be realized based on the subsequent real-time collected defoaming rate data. By adjusting the values of the first coefficient and the second coefficient, the functional relationship can more accurately reflect the actual relationship between the pipeline transportation pressure and the defoaming rate.

[0013] Preferably, constructing the functional relationship between the pipeline transportation pressure and the defoaming rate includes: Dividing multiple preset pipeline transportation pressures and conducting a foamed concrete pumping and pouring model experiment under multiple preset pipeline transportation pressures; Measuring the defoaming rate under different levels of the pipeline transportation pressure and constructing a functional relationship with the pipeline transportation pressure according to the defoaming rate; Correcting the first coefficient or the second coefficient in the functional relationship.

[0014] The purpose of this method is to solve the problem that the functional relationship may fail during long-distance transportation. Through model experiments, at multiple preset pipeline transportation pressure levels, the corresponding defoaming rates are measured to establish the initial functional relationship between the pipeline transportation pressure and the defoaming rate. This initial functional relationship is obtained based on experimental data and can initially reflect the connection between the two. By using correction coefficients and adjusting and optimizing the functional relationship according to the actual situation, the functional relationship can better fit the actual transportation process, improve the accuracy of pressure prediction, and thus more reliably evaluate the risk of pipe blockage. This correction mechanism takes into account various possible changing factors during long-distance transportation, making the pipe blockage prediction method more adaptable and practical.

[0015] Preferably, correcting the first coefficient or the second coefficient in the functional relationship includes the following steps: Start the timer to start timing, or start the distance counter to start distance counting; Real-time monitor the time of the timer or the distance count value of the distance counter; When it is monitored that the timer reaches the preset time interval or the distance counter reaches the preset distance interval, trigger a functional relationship correction instruction; In response to the functional relationship correction instruction, collect the first wet density data and the second wet density data of the foamed concrete slurry at the inlet end and the outlet end of the pipeline and the data of the current pipeline transportation pressure; According to the collected first wet density data and the second wet density data, calculate the defoaming rate of the foamed concrete slurry in the current pumping stage; Based on the defoaming rate of the foamed concrete slurry in the current pumping stage and the current pipeline transportation pressure data, correct the first coefficient or the second coefficient in the functional relationship to obtain a corrected functional relationship; Update the functional relationship and reset the timer or the distance counter.

[0016] A timer or distance counter is introduced to trigger the function relation correction instruction through a preset time interval or distance interval, realizing the periodic or distance-based correction of the function relation. When the preset condition is reached, the system will re-collect data, calculate the current defoaming rate, and correct the coefficient in the function relation based on the new data to obtain a function relation that better conforms to the current working conditions. This real-time correction mechanism ensures that the function relation can be dynamically adjusted with the actual situation during the pumping process, improving the accuracy of pipeline transportation pressure prediction and further enhancing the reliability of plugging risk prediction. The introduction of the timer or distance counter makes the correction process automated without manual intervention, improving the operation convenience. By continuously updating the function relation, this method can adapt to the changes in the characteristics of foamed concrete materials and the fluctuations in pipeline working conditions during long-distance transportation, ensuring the effectiveness and timeliness of plugging prediction.

[0017] Preferably, the value range of the first coefficient is 1.5 to 2.5, and the value range of the second coefficient is 0.85 to 1.0.

[0018] By limiting the value of the first coefficient to be between 1.5 and 2.5, and the value of the second coefficient to be between 0.85 and 1.0, a reasonable value range for the key parameters in the function relation is provided. This limited range makes the function relation more specific and practical, solving the problem of unclear parameter values in the function relation. The value ranges of the first coefficient and the second coefficient are determined based on the experimental data or theoretical analysis of the transportation characteristics of foamed concrete and the relationship between pipeline transportation pressure and defoaming rate, ensuring that the function relation can more accurately reflect the actual situation and improving the practicality and prediction accuracy of the pipeline plugging prediction method.

[0019] Preferably, step S3 includes: Calculate the pipeline plugging risk coefficient according to the following formula : ; In the formula is the real-time transportation pressure of the pipeline, is the pipeline transportation pressure during normal pumping of foamed concrete, is the pipeline ultimate bearing pressure.

[0020] By comparing the pressure difference with the pressure bearing range, the pipe plugging risk coefficient is obtained. When the real-time pipeline conveying pressure is close to the pipeline conveying pressure during the normal pumping of the foamed concrete slurry, the numerator value is small and the risk coefficient value is small, indicating a low plugging risk. When the real-time pipeline conveying pressure is close to the pipeline ultimate bearing pressure, the numerator value is close to the denominator value and the risk coefficient value is close to 1, indicating a high plugging risk. Based on these parameters such as the real-time pipeline conveying pressure, the pipeline conveying pressure during the normal pumping of the foamed concrete slurry, and the pipeline ultimate bearing pressure, the pipeline plugging risk is quantified, providing data support for the subsequent determination of the plugging risk level and the adoption of risk measures.

[0021] Preferably, the classification of the plugging risk level in step S4 is as follows: When the value of the pipeline plugging risk coefficient is 0 < ≤ 0.4, it is determined as a low risk and normal construction continues; When the value of the pipeline plugging risk coefficient is 0.4 < ≤ 0.6, it is determined as a medium risk, and monitoring is strengthened and the pipeline conveying pressure is reduced; When the value of the pipeline plugging risk coefficient is 0.6 < ≤ 1.0, it is determined as a high risk and pumping is immediately stopped.

[0022] For the value of the pipeline plugging risk coefficient, it is divided into three risk level intervals. By defining the relationship between the risk coefficient value, the risk level, and the corresponding measures, operators can quickly judge the current pipeline plugging risk level according to the risk coefficient value and take corresponding risk measures to ensure the safety of pipeline conveying.

[0023] In a second aspect, the present application provides a device for predicting plugging of a long-distance foamed concrete conveying pipeline. The device includes: A data acquisition module for acquiring the first wet density data and the second wet density data of the foamed concrete slurry; A data processing module for calculating the defoaming rate of the foamed concrete slurry during pipeline conveying according to the first wet density data and the second wet density data, predicting the real-time pipeline conveying pressure according to the functional relationship between the pipeline conveying pressure and the defoaming rate, and calculating the pipeline plugging risk coefficient according to the real-time pipeline conveying pressure; An early warning module for determining the plugging risk level according to the pipeline plugging risk coefficient and triggering an alarm signal.

[0024] As can be seen from the above, a method and device for predicting pipe blockage in a long-distance foamed concrete conveying pipeline provided by the present application are based on the principle of defoaming of internal bubbles in foamed concrete under pressure. By constructing the functional relationship between the pipeline conveying pressure and the defoaming rate of the conveying medium bubbles, accurate prediction of the blockage state of the long-distance pipeline and quantitative characterization of the pipeline blockage risk are achieved. Compared with traditional methods, this method does not require additional monitoring equipment or professional technicians, only needs to collect and analyze the data of the wet density, which is a necessary measurement index of foamed concrete, greatly reducing the monitoring and prediction cost of foamed concrete pipe blockage, and at the same time avoiding the long-term maintenance problem of a large number of monitoring equipment. The prediction principle is simple and easy to understand, convenient for on-site personnel to operate, can realize real-time prediction of the risk of long-distance conveying pipelines, has strong timeliness and high accuracy, and can provide strong support for the safe pumping of long-distance foamed concrete. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 FIG. is a schematic flow chart of a method for predicting pipe blockage in a long-distance foamed concrete conveying pipeline provided by an embodiment of the present application.

[0026] Figure 2 FIG. is a schematic diagram of the functional relationship between the pipeline conveying pressure and the defoaming rate of a method for predicting pipe blockage in a long-distance foamed concrete conveying pipeline provided by an embodiment of the present application.

[0027] Figure 3 FIG. is a schematic structural diagram of a device for predicting pipe blockage in a long-distance foamed concrete conveying pipeline provided by an embodiment of the present application.

[0028] Reference numerals: 300, device for predicting pipe blockage in a long-distance foamed concrete conveying pipeline; 301, data acquisition module; 302, data processing module; 303, early warning module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and illustrated herein can be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of the present application provided herein is not intended to limit the scope of the present application claimed, but merely represents selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts shall fall within the scope of protection of the present application.

[0030] It should be noted that similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, terms such as "first" and "second" are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0031] Foamed concrete is a lightweight fluid filling material. Due to its good lightness, fluidity and self-hardening properties, it has currently been widely used in fields such as road abutment backfilling, mine filling, pipeline backfilling, etc. According to incomplete statistics, the annual scale of the domestic foamed concrete sub-market has reached 20 million cubic meters. Moreover, with the growth of the scale of road infrastructure reconstruction and expansion and the expansion of emerging markets such as oil and gas pipeline filling, its annual scale is still continuously increasing. The construction method of foamed concrete is mainly pipeline pumping. As the key carrier for transporting foamed concrete, the pipeline directly affects the normal production and construction and safety of foamed concrete. Once the conveying pipeline is blocked, it will not only cause the interruption of normal construction operations, but also may trigger dangerous accidents such as pipe explosion when the blockage pressure is too high; at the same time, when the pipe blockage repair time is too long, the foamed concrete slurry retained in the pipeline hardens, resulting in a larger area of blockage, and may also cause equipment damage and safety accidents, causing great economic losses and casualties.

[0032] Currently, the detection of blockage in foamed concrete conveying pipelines often mainly relies on manual inspection. In ground engineering construction scenarios such as road bridges and municipal transportation, due to the large operation space and short single conveying distance (generally less than 500m), it is feasible to manually inspect the pipeline. However, in engineering construction scenarios such as mine filling and long-distance oil and gas pipeline tunnel filling, due to the underground operation being concealed, the operation space being narrow, and the linear construction distance being long (generally exceeding 10km), the method of manually inspecting the pipeline often fails to detect blockages in a timely manner due to low timeliness, and it is difficult to repair, resulting in chain disasters such as pipe explosion, equipment failure and casualties caused by blockage, bringing great safety hazards to the long-distance pumping construction of foamed concrete. Therefore, for the long-distance foamed concrete pipeline transportation, there is an urgent need for an efficient, accurate and easy-to-operate pipeline blockage prediction method to timely predict and evaluate the blockage state of the conveying pipeline and avoid causing pipe blockage or secondary chain disasters.

[0033] Please refer to Figure 1 , a method for predicting blockage in a long-distance foamed concrete conveying pipeline provided by the present application includes the following steps: S1: Respectively collect the first wet density data and the second wet density data of the foamed concrete slurry at the inlet end and the outlet end of the on-site pipeline, and calculate the defoaming rate of the foamed concrete slurry during pipeline transportation according to the first wet density data and the second wet density data; S2: Predict the real-time pipeline transportation pressure according to the functional relationship between the pipeline transportation pressure and the defoaming rate; S3: Calculate the pipeline blockage risk coefficient based on the real-time pipeline transportation pressure; S4: Determine the blockage risk level and corresponding risk measures according to the pipeline blockage risk coefficient.

[0034] Among them, in step S1, the first wet density data and the second wet density data of the foamed concrete slurry are collected at the inlet end and the outlet end of the pipeline. Through the wet density data collected at the inlet end and the outlet end, the defoaming rate of the foamed concrete slurry during pipeline transportation is calculated. In step S2, the real-time pipeline transportation pressure is predicted according to the pre-established functional relationship between the pipeline transportation pressure and the defoaming rate, and this functional relationship reflects the influence of the change in transportation pressure on the defoaming rate. In step S3, the pipeline blockage risk coefficient is calculated based on the predicted real-time pipeline transportation pressure. The pipeline blockage risk coefficient can quantify the risk degree of pipeline blockage. In step S4, the blockage risk level is determined according to the calculated pipeline blockage risk coefficient, and corresponding risk measures are formulated and implemented according to different risk levels to timely respond to possible pipeline blockage problems.

[0035] Specifically, this method aims to solve the problem that it is difficult to effectively predict the blockage of long-distance foamed concrete transportation pipelines. The working principle is based on the fact that during the pipeline transportation of foamed concrete slurry, the pipeline pressure will cause foam defoaming, and there is a correlation between the defoaming degree and the blockage risk. First, the wet density data of the foamed concrete slurry is collected at both the inlet and outlet ends of the pipeline. The inlet end of the pipeline is in the mixing tank, and the data at the inlet end is the first wet density data, and the data at the outlet end is the second wet density data. Then, based on the first wet density data and the second wet density data, the defoaming rate of the foamed concrete slurry during transportation is calculated, and the defoaming rate reflects the defoaming degree of the foamed concrete after being transported in the pipeline. Further, using the pre-set functional relationship between the pipeline transportation pressure and the defoaming rate, the real-time pipeline transportation pressure can be predicted, and the predicted real-time pipeline transportation pressure is a key parameter for evaluating the blockage risk. Thus, the pipeline blockage risk coefficient can be calculated according to the predicted real-time pipeline transportation pressure, and the pipeline blockage risk coefficient can quantitatively represent the likelihood of pipeline blockage. Finally, according to the magnitude of the pipeline blockage risk coefficient, the blockage risk level is divided, and corresponding risk measures are taken according to the risk level. For example, when the risk level is high, measures such as reducing the pumping pressure or stopping pumping can be taken to avoid or mitigate the occurrence of pipeline blockage problems. Through the above steps, this method realizes the effective prediction of the blockage risk of long-distance foamed concrete transportation pipelines. The whole method does not require additional complex sensor devices, is easy to operate, and can provide guarantee for the safe operation of long-distance foamed concrete transportation pipelines.

[0036] This application further proposes that step S1 includes: Calculate the defoaming rate according to the following formula : ; In the formula is the first wet density data, is the second wet density data.

[0037] Among them, the wet density data at the inlet end and the wet density data at the outlet end respectively represent the first wet density data and the second wet density data collected for the foamed concrete slurry at the inlet end and the outlet end of the pipeline. The formula obtains the defoaming rate of the foamed concrete slurry during transportation by taking the difference between the wet density data at the inlet end and the wet density data at the outlet end, and then taking the ratio of this difference to the wet density data at the inlet end. The data is obtained through on-site measurement. For example, the measuring cup method is used for measurement. The value of the defoaming rate can reflect the defoaming degree of the foamed concrete slurry during transportation.

[0038] Specifically, based on the actually measured first wet density data and second wet density data, the defoaming rate can be quickly calculated. The calculation result of the defoaming rate can provide a data basis for the subsequent step S2 to predict the real-time pipeline transportation pressure based on the defoaming rate, and step S3 to calculate the pipeline blockage risk coefficient, making the entire pipeline blockage prediction method achievable and applicable in the calculation link of the defoaming rate.

[0039] This application further proposes that step S1 includes: The first wet density data and the second wet density data are obtained by testing with a measuring cup. The measuring cup has a standard volume of 1L and the material is selected from glass, stainless steel or plastic.

[0040] Among them, for the first wet density data and the second wet density data obtained by testing with a measuring cup, the specific implementation process is as follows: Prepare a measuring cup with a standard volume of 1L, and the material of the measuring cup is selected from these materials such as glass, stainless steel or plastic. At the inlet end and the outlet end of the on-site pipeline, use the prepared measuring cup to collect the foamed concrete slurry respectively. During collection, ensure that the measuring cup is filled with the foamed concrete slurry, scrape the edge of the measuring cup flat, remove the excess slurry, and then weigh the total mass of the measuring cup and the slurry. By subtracting the mass of the empty measuring cup from the total mass and then dividing by the volume of the measuring cup, which is 1L, the wet density data of the foamed concrete slurry is calculated. The data collected at the inlet end is used as the first wet density data, and the data collected at the outlet end is used as the second wet density data. Through the above operations, the first wet density data and the second wet density data can be obtained for the subsequent calculation of the defoaming rate.

[0041] Specifically, the measuring cup method is used to test the first wet density data and the second wet density data to ensure the accuracy and reliability of the defoaming rate calculation results. As a standardized density test method, the measuring cup method is adopted to ensure the standardization of the test process. The use of a measuring cup with a standard 1L volume controls the sampling volume and reduces the error caused by inconsistent sampling volumes. The measuring cup material is limited to glass, stainless steel, or plastic to avoid chemical reactions or physical adsorption between the measuring cup material and the foamed concrete slurry, thereby affecting the accuracy of the test results. Thus, the standardization and accuracy of density data acquisition are ensured, the reliability of defoaming rate calculation is improved, and data support is provided for the accurate prediction of subsequent pipe blockage risks.

[0042] The present application further proposes to establish a functional relationship between the pipeline transportation pressure and the defoaming rate: ; In the formula is the pipeline transportation pressure value at the i-th level, is the defoaming rate value of the foamed concrete slurry corresponding to the pipeline transportation pressure at the i-th level. i is a positive integer and its value range satisfies 1 ≤ i ≤ N, where n is the total number of pipeline transportation pressure levels and N ≥ 3. a is the first coefficient and b is the second coefficient.

[0043] Among them, the functional relationship adopts the form of an exponential function, where the defoaming rate is used as the independent variable of the exponential function and the pipeline transportation pressure is used as the function value. The first coefficient and the second coefficient are used to adjust the shape and position of the function curve to adapt to the prediction of the foamed concrete transportation pressure under different working conditions. When the defoaming rate increases, the exponential function value increases, and the pipeline transportation pressure value also increases accordingly, which is consistent with the actual situation that the increase in the defoaming rate leads to an increase in the pipeline transportation pressure. The first coefficient and the second coefficient are preset parameters and are set according to experimental data or experience. The adjustment of the first coefficient and the second coefficient can be based on the actual characteristics of the foamed concrete material and the pipeline transportation conditions. For example, for different types of foamed concrete, the values of the first coefficient and the second coefficient can be adjusted. Another example is that for pipelines of different lengths or materials, the values of the first coefficient and the second coefficient can be adjusted. By adjusting the values of the first coefficient and the second coefficient, the functional relationship can more accurately reflect the actual relationship between the pipeline transportation pressure and the defoaming rate, making the pressure prediction more accurate.

[0044] Specifically, the construction of the functional relationship between the pipeline transportation pressure and the defoaming rate is to achieve the prediction of the real-time pipeline transportation pressure. During the long-distance pipeline transportation of foamed concrete, there is a correlation between the transportation pressure and the defoaming rate of foamed concrete. The transportation pressure compresses the fluidized foamed concrete slurry medium and transfers the transportation pressure to the bubbles wrapped by the slurry medium. The bubble film wall defoams under the extrusion of the pipeline transportation pressure, resulting in an increase in the density of foamed concrete per unit volume. Moreover, the greater the transportation pressure, the easier the bubbles inside the foamed concrete are defoamed under the extrusion of the pressure. After defoaming, the foamed concrete loses the lubrication of the bubbles and is more prone to bleeding and segregation, leading to blockage of the transportation pipeline. Therefore, the defoaming rate can reflect the magnitude of the pipeline transportation pressure. By constructing the functional relationship between the pipeline transportation pressure and the defoaming rate, when the defoaming rate is obtained, the value of the pipeline transportation pressure can be accurately predicted according to the functional relationship, thereby providing data support for the assessment of the pipeline blockage risk. The functional relationship adopts the form of an exponential function, which can better fit the non-linear relationship between the pipeline transportation pressure and the defoaming rate. Through experiments or data analysis, the values of the first coefficient and the second coefficient are determined, and a specific functional relationship can be established. In practical applications, by real-time monitoring and calculating the defoaming rate and substituting it into the functional relationship, the real-time pipeline transportation pressure can be predicted. Through the calculation and prediction using the functional relationship, the prediction of the real-time pipeline transportation pressure based on the defoaming rate is realized. This method does not require additional monitoring equipment, only needs to collect the wet density data of foamed concrete, reduces the monitoring and prediction cost of pipe blockage, and is easy to operate.

[0045] The present application further proposes that constructing the functional relationship between the pipeline transportation pressure and the defoaming rate includes: dividing multiple levels of preset pipeline transportation pressures, and conducting a pumping and pouring model experiment of foamed concrete under multiple levels of preset pipeline transportation pressures; measuring the defoaming rate under different levels of pipeline transportation pressures, and constructing a functional relationship with the pipeline transportation pressure according to the defoaming rate; and correcting the first coefficient or the second coefficient in the functional relationship.

[0046] Among them, dividing the multi-level preset pipeline conveying pressure is to simulate the different pressure environments that foamed concrete may encounter in actual pipeline conveying. The classification of the pipeline conveying pressure levels can be determined according to the actual needs of the project and the pressure-bearing capacity of the pipeline. For example, it can be divided into three levels: low pressure, medium pressure, and high pressure, or more refined multiple pressure levels. Conducting a pumping and pouring model experiment of foamed concrete under multi-level preset pipeline conveying pressure means building a simulated pipeline conveying system in the laboratory and using foamed concrete for pumping experiments in this system. During the experiment, the pipeline conveying pressure is controlled at multiple preset pressure levels to simulate different conveying pressure conditions in actual projects. Measuring the defoaming rate under different pipeline conveying pressures means that in the model experiment, for each preset pipeline conveying pressure level, measure the wet density of the foamed concrete before and after conveying, and calculate the defoaming rate based on the wet density data. The defoaming rate can be calculated using the formula given above, and then a functional relationship with the pipeline conveying pressure is constructed. Modifying the first coefficient or the second coefficient in the functional relationship is to make the functional relationship better adapt to the complex situations and changing factors in actual projects. The modification process can be carried out in the model experiment stage or in the initial stage of the actual project. The modification method can be based on experimental data or actual project data, and mathematical methods such as regression analysis and numerical optimization can be used to adjust the first coefficient or the second coefficient in the functional relationship to make the functional relationship more accurately reflect the relationship between the pipeline conveying pressure and the defoaming rate.

[0047] Specifically, the function relationship between the pipeline transportation pressure and the defoaming rate is constructed to predict the real-time pipeline transportation pressure and then evaluate the pipe blockage risk. The construction of the function relationship first requires model experiments. In the model experiments, first, according to the engineering requirements and pipeline characteristics, multiple pipeline transportation pressure levels are preset, such as 0.5 MPa, 1.0 MPa, 1.5 MPa, and 2.0 MPa. Then, a model experimental system for pumping and pouring foamed concrete is built in the laboratory. This system needs to be able to simulate the actual pipeline transportation process and can accurately control the pipeline transportation pressure. In the model experiments, for each preset pipeline transportation pressure level, multiple foamed concrete pumping experiments are carried out. In each experiment, the wet densities of the foamed concrete at the inlet and outlet ends of the pipeline need to be measured, and the defoaming rate is calculated. At the same time, the pipeline transportation pressure data values during the experiment are recorded. Through the analysis of the experimental data from multiple experiments, the defoaming rate data corresponding to different pipeline transportation pressures can be obtained. Based on these experimental data, methods such as regression analysis can be used to fit the function relationship between the pipeline transportation pressure and the defoaming rate, and the initial values of the first coefficient and the second coefficient in the function relationship are determined. To improve the accuracy and adaptability of the function relationship, the first coefficient or the second coefficient also needs to be corrected. The correction can be carried out in the model experiment stage. For example, after the initial function relationship is constructed, experiments with new pipeline transportation pressure levels can be added, or the experiments with existing pressure levels can be repeated to obtain more experimental data, and the first coefficient or the second coefficient is corrected based on the new data. The correction can also be carried out in the initial stage of the actual project. After the actual project starts, the actual pipeline transportation pressure and defoaming rate data can be collected and compared with the predicted values of the function relationship obtained from the model experiments. If there is a deviation between the predicted value and the actual value, the first coefficient or the second coefficient needs to be corrected to reduce the prediction deviation and improve the accuracy of the function relationship.

[0048] In some specific embodiments, in order to construct a functional relationship between the pipeline transportation pressure and the defoaming rate, five preset pipeline transportation pressure levels can be divided first, which are 0.6 MPa, 0.8 MPa, 1.0 MPa, 1.2 MPa, and 1.4 MPa respectively. Then, a horizontal pipeline pumping and pouring model simulation experiment system with a length of 20 meters is built. The pipeline material is selected as stainless steel, and the inner diameter is 80 mm. In this experimental system, foam concrete pumping experiments are carried out respectively under the above five pipeline transportation pressure levels. The pumping time for each experiment is 30 minutes, and each pressure level is repeated three times. In each experiment, the wet density of the foam concrete at the inlet end and the outlet end of the pipeline is measured by the measuring cup method, and the defoaming rate is calculated. When processing the experimental data, the average value of the three repeated experiments is taken as the defoaming rate at this pressure level. Using the regression analysis method, with the pipeline transportation pressure as the independent variable and the defoaming rate as the dependent variable, a functional relationship is fitted, and the initial value of the first coefficient is determined to be 1.8, and the initial value of the second coefficient is 0.9. In the initial stage of actual engineering application, the actual pipeline transportation pressure and defoaming rate data are collected every 2 hours and compared with the predicted values of the functional relationship. If the deviation of the continuously collected data exceeds 15% for three consecutive times, the latest actual data is used, and the first coefficient or the second coefficient is corrected by the least squares method to obtain the corrected functional relationship and update the application. Thus, a more accurate functional relationship between the pipeline transportation pressure and the defoaming rate that can adapt to the actual engineering situation can be obtained, and then a more reliable prediction of the pipe blockage risk can be realized.

[0049] The present application further proposes that correcting the first coefficient or the second coefficient in the functional relationship includes the following steps: Start the timer to start timing, or start the distance counter to start distance counting; Real-time monitor the time of the timer or the distance count value of the distance counter; When it is monitored that the timer reaches the preset time interval or the distance counter reaches the preset distance interval, trigger the functional relationship correction instruction; In response to the functional relationship correction instruction, collect the first wet density data and the second wet density data of the foam concrete slurry at the inlet end and the outlet end of the pipeline and the current pipeline transportation pressure data; According to the collected first wet density data and the second wet density data, calculate the defoaming rate of the foam concrete slurry in the current pumping stage; Based on the defoaming rate of the foam concrete slurry in the current pumping stage and the current pipeline transportation pressure data, correct the first coefficient or the second coefficient in the functional relationship to obtain the corrected functional relationship; Update the functional relationship and reset the timer or the distance counter.

[0050] Among them, a timer or a distance counter is used to start and record time or distance. The timer can be an electronic timing device, and the distance counter can be an odometer or an encoder installed on the pipeline. After the timer or the distance counter starts working, the values of time or distance are monitored in real time. The preset time interval or the preset distance interval is a preset time value or distance value. For example, the preset time interval can be set to 30 minutes, and the preset distance interval can be set to 100 meters. When the time recorded by the timer reaches the preset time interval, or the distance recorded by the distance counter reaches the preset distance interval, the system automatically triggers a function relationship correction instruction. The node that starts the timer or the distance counter can be based on an actual pipeline blockage, or can perform timing or distance counting according to the variation law of the function relationship to update the function relationship. The distance refers to the distance that the foamed concrete slurry is transported in the pipeline. In response to the function relationship correction instruction, the first wet density data and the second wet density data of the foamed concrete slurry at the inlet end and the outlet end of the pipeline and the current pipeline conveying pressure data are collected. The wet density data can be obtained through on-site testing by the measuring cup method. Based on the newly collected wet density data, the defoaming rate is recalculated, and combined with the current pipeline conveying pressure data, mathematical methods such as the least squares method are used to correct the first coefficient or the second coefficient in the function relationship to obtain the corrected function relationship. The corrected function relationship is updated into the system for subsequent real-time pipeline conveying pressure prediction and blockage risk coefficient calculation. The timer or the distance counter is reset after completing one function relationship correction and starts timing or distance counting again to prepare for the next function relationship correction.

[0051] Specifically, to ensure the accuracy of pipeline transportation pressure prediction, the functional relationship needs to be dynamically corrected according to the actual working conditions. The introduction of a timer or a distance counter enables the periodic or distance-based correction of the functional relationship coefficients. For example, at the start of the foamed concrete pumping, the timer is activated and starts timing. The system presets a time interval of 1 hour. When the pumping time reaches 1 hour and the timer reaches the preset time interval, a functional relationship correction instruction is triggered. In response to this instruction, the wet density data at the inlet and outlet ends and the current pipeline transportation pressure data are collected. The current defoaming rate is calculated based on the newly collected wet density data, and in combination with the current pipeline transportation pressure data, the first coefficient in the preset functional relationship is corrected. The correction method can be, for example, keeping the second coefficient unchanged, inversely calculating the new value of the first coefficient through the current defoaming rate and pipeline transportation pressure data, and updating the original value of the first coefficient to the newly calculated value of the first coefficient. After completing the correction of the first coefficient, the system updates the functional relationship, resets the timer to zero, and starts timing again. During the subsequent pumping process, whenever the timer reaches the preset time interval, the above correction process is repeated, thereby achieving the periodic correction of the functional relationship. The working principle of the distance counter is similar to that of the timer, except that the condition for triggering the functional relationship correction instruction becomes that the distance counter reaches the preset distance interval. Through this real-time correction mechanism, the functional relationship can be dynamically adjusted with the changes in material properties and pipeline working conditions during the pumping process, ensuring the accuracy of pipeline transportation pressure prediction and thus enhancing the reliability of blockage risk prediction.

[0052] In some specific embodiments, the preset time interval is set to 30 minutes, and the preset distance interval is set to 500 meters. The timer uses a high-precision electronic timer, and the distance counter uses a rotary encoder installed on the conveying pipeline. Suppose the initial value of the first coefficient is 2.0, and the initial value of the second coefficient is 0.9. During the first functional relationship correction, keeping the second coefficient at 0.9 unchanged, the corrected value of the first coefficient is calculated to be 1.8 based on the current defoaming rate and pipeline transportation pressure data through the least squares method, and the functional relationship is updated. After the preset time interval or preset distance interval is reached and the second response to the functional relationship correction instruction occurs, data is collected again, and the first coefficient a is corrected using the same method. For example, the corrected value of the first coefficient is 1.9, and the system updates again. Through multiple periodic or distance-based corrections, the functional relationship can gradually approach the optimal functional relationship under actual working conditions, improving the prediction accuracy of pipeline transportation pressure.

[0053] The present application further proposes that the value range of the first coefficient is 1.5 - 2.5, and the value range of the second coefficient is 0.85 - 1.0.

[0054] Among them, the setting of these numerical ranges is determined based on a large amount of experimental data or theoretical analysis of the conveying characteristics of foamed concrete and the relationship between pipeline conveying pressure and defoaming rate. Specifically, during the pipeline conveying process of foamed concrete, the first coefficient and the second coefficient affect the curve shape and parameter sensitivity of the functional relationship between pipeline conveying pressure and defoaming rate. The first coefficient mainly affects the slope of the curve, and its value ranges from 1.5 to 2.5, ensuring that the functional relationship can better reflect the sensitivity of the change in pipeline conveying pressure to the defoaming rate. The second coefficient mainly affects the intercept of the curve, and its value ranges from 0.85 to 1.0, ensuring the applicability of the functional relationship under different initial states.

[0055] Specifically, in the method for predicting pipeline blockage in long-distance foamed concrete conveying pipelines, in order to improve the prediction accuracy and reliability of pipeline conveying pressure, by setting the first coefficient in the range of 1.5 to 2.5 and setting the second coefficient in the range of 0.85 to 1.0, it can be ensured that the functional relationship constructed between pipeline conveying pressure and defoaming rate can more accurately reflect the physical laws in the actual foamed concrete conveying process. When predicting the risk of pipeline blockage, using the functional relationship constructed with the first coefficient and the second coefficient within this limited range can more accurately predict the real-time pipeline conveying pressure, and then accurately calculate the pipeline blockage risk coefficient, and finally achieve an accurate determination of the pipeline blockage risk level. Thus, corresponding risk measures can be taken in a timely manner to avoid pipeline blockage or the occurrence of secondary disasters.

[0056] In some preferred embodiments, the steps for further correcting the first coefficient or the second coefficient in the functional relationship of the present application include: Obtain the mixing ratio parameters of the current foamed concrete slurry and the conveying distance parameters of the pipeline; Compare the mixing ratio parameters of the current foamed concrete slurry with the initial mixing ratio parameters to determine whether the change amount of the foamed concrete slurry mixing ratio parameters exceeds the preset mixing ratio threshold; and compare the conveying distance parameters of the current pipeline with the initial conveying distance parameters to determine whether the change amount of the pipeline conveying distance exceeds the preset distance threshold; If the change amount of the foamed concrete slurry mixing ratio parameters exceeds the preset mixing ratio threshold, then select to correct the first coefficient in the functional relationship; if the change amount of the pipeline conveying distance exceeds the preset distance threshold, then select to correct the second coefficient in the functional relationship; if both the change amount of the foamed concrete slurry mixing ratio parameters and the change amount of the pipeline conveying distance exceed the corresponding preset thresholds, then select to correct both the first coefficient and the second coefficient in the functional relationship; if neither the change amount of the foamed concrete slurry mixing ratio parameters nor the change amount of the pipeline conveying distance exceeds the corresponding preset thresholds, then select to correct both the first coefficient and the second coefficient in the functional relationship; Based on the selected and corrected coefficient, and based on the defoaming rate of the foamed concrete in the current pumping stage and the current pipeline transportation pressure data, use a preset correction algorithm to correct the selected coefficient, and update the corrected coefficient in the function relationship as the corrected coefficient.

[0057] In some preferred embodiments, the steps of selecting and correcting the coefficient include: Obtain the current pipeline blockage risk coefficient; Calculate the average value of the pipeline blockage risk coefficient within N consecutive function relationship correction periods to obtain the average risk coefficient value; Compare the average risk coefficient value with a preset risk threshold; if the average risk coefficient value is less than the preset risk threshold, then decrease the preset mixing ratio threshold and the preset distance threshold; if the average risk coefficient value is greater than or equal to the preset risk threshold, then increase the preset mixing ratio threshold and the preset distance threshold; Update the preset mixing ratio threshold and the preset distance threshold as the adjusted preset mixing ratio threshold and preset distance threshold; Based on the updated preset mixing ratio threshold and preset distance threshold, perform the coefficient selection step: if the change amount of the foamed concrete slurry mixing ratio parameter exceeds the updated preset mixing ratio threshold, then select the first coefficient in the correction function relationship; if the change amount of the pipeline transportation distance exceeds the updated preset distance threshold, then select the second coefficient in the correction function relationship; if both the change amount of the foamed concrete slurry mixing ratio parameter and the change amount of the pipeline transportation distance exceed the corresponding updated preset thresholds, then select to correct both the first coefficient and the second coefficient in the function relationship; if both the change amount of the foamed concrete slurry mixing ratio parameter and the change amount of the pipeline transportation distance do not exceed the corresponding updated preset thresholds, then select to correct both the first coefficient and the second coefficient in the function relationship.

[0058] This application further compares the average risk coefficient value with the preset risk threshold, which includes: Calculate the risk difference between the average risk coefficient value and the preset risk threshold : = - ; where is the average risk coefficient value, is the preset risk threshold.

[0059] If the average risk coefficient value is less than the preset risk threshold, then decrease the preset mixing ratio threshold and the preset distance threshold; if the average risk coefficient value is greater than or equal to the preset risk threshold, then increase the preset mixing ratio threshold and the preset distance threshold.

[0060] For example, if the average risk coefficient value is less than the preset risk threshold, then decreasing the preset mixing ratio threshold and the preset distance threshold includes: Calculate the difference between the average risk coefficient value and the preset risk threshold to obtain a risk difference; determine the preset difference range to which the risk difference belongs, and reduce the preset ratio threshold and the preset distance threshold according to the preset difference range to which the risk difference belongs. Among them, the preset difference range is divided into multiple intervals, and a list of preset difference boundary values is set as: = ……], then the interval into which the risk difference falls satisfies =- , =+ , represent the first interval, the second interval, and the third interval respectively, represents the last interval, n is a positive integer and n≥3. Reduce the preset ratio threshold and the preset distance threshold according to the preset difference range, calculate the adjustment coefficients for reducing the preset ratio threshold and the preset distance threshold corresponding to different intervals into which the risk difference falls, and re-determine the data of the preset ratio threshold and the preset distance threshold according to the adjustment coefficients.

[0061] If the average risk coefficient value is greater than or equal to the preset risk threshold, increasing the preset ratio threshold and the preset distance threshold includes: Calculate the non-linear adjustment coefficient: adjust_factorP=fadjust_P( - ); adjust_factorD=fadjust_D( - ); Among them, adjust_factorP and adjust_factorD are preset non-linear functions (such as exponential functions, piecewise functions, etc.). The non-linear functions in high-risk adjustment can be designed as functions positively correlated with the risk difference (such as linear proportion, exponential growth, etc.), and need to be preset according to actual engineering requirements. Threshold adjustment needs to be performed periodically (for example, every N monitoring cycles) to ensure the real-time nature of risk prediction. Using a threshold model that adaptively adjusts based on the risk difference, compared with the traditional fixed-threshold method, its advantage lies in being able to dynamically adjust the preset ratio threshold and the preset distance threshold according to the real-time risk assessment results, achieving the adaptive optimization of model parameters and improving the robustness of the model under different working conditions.

[0062] Furthermore, in some preferred embodiments, correcting the first coefficient and the second coefficient includes: Obtain the previously corrected first coefficient a_old and second coefficient b_old; Obtain the defoaming rate DR_current of the foamed concrete slurry in the current pumping stage and the collected pipeline conveying pressure data P_current; Set the base learning rates η_a_base and η_b_base and the adaptive learning rate adjustment parameter γ; Calculate the pressure prediction error E, where E = P_current - (a_old * DR_current + b_old); Calculate the learning rate η_a of the first coefficient a and the learning rate η_b of the second coefficient b, where η_a = η_a_base / (1 + γ * |E|), η_b = η_b_base / (1 + γ * |E|); Update the first coefficient a and the second coefficient b according to the learning rates η_a and η_b to obtain the corrected first coefficient a_new and second coefficient b_new, where a_new = a_old + η_a * E * DR_current, b_new = b_old + η_b * E; Compared with the traditional fixed coefficient model, the dual - coefficient adaptive correction adopted in this application can dynamically adjust the first coefficient and the second coefficient in the functional relationship according to the defoaming rate and pipeline conveying pressure data collected in real time, so as to more accurately reflect the conveying characteristics of the foamed concrete slurry under the current working conditions.

[0063] This application further proposes that step S3 includes: Calculate the pipeline blockage risk coefficient according to the following formula : ; In the formula is the real - time pipeline conveying pressure, is the pipeline conveying pressure during normal pumping of foamed concrete, is the pipeline ultimate bearing pressure.

[0064] Among them, the numerator in the formula is obtained by subtracting the pipeline conveying pressure during normal pumping of foamed concrete from the real - time pipeline conveying pressure, and this difference represents the degree to which the current pipeline conveying pressure exceeds the normal pressure. The denominator is obtained by subtracting the pipeline conveying pressure during normal pumping of foamed concrete from the pipeline ultimate bearing pressure, and this difference represents the remaining pressure bearing range of the pipeline. The pipeline blockage risk coefficient is obtained by comparing the pressure difference with the pressure bearing range. The pipeline conveying pressure during normal pumping of foamed concrete is a pre - set parameter, which can be determined through experiments or empirical formulas according to factors such as the mix ratio of foamed concrete, the length and diameter of the pipeline, etc. The pipeline ultimate bearing pressure is the maximum pressure that the pipeline can bear, which is determined by parameters such as the material and wall thickness of the pipeline, and can also be obtained by referring to the technical parameters provided by the pipeline manufacturer or through pressure testing. The real - time pipeline conveying pressure is the actual pressure value inside the pipeline, which is predicted through the above functional relationship.

[0065] Specifically, the calculation process of the pipeline plugging risk coefficient reflects the quantitative assessment of the pipeline blockage risk. When the pipeline conveying pressure approaches the pipeline conveying pressure during the normal pumping of foamed concrete, the molecular value becomes smaller, and thus the risk coefficient value becomes smaller, indicating a lower risk of pipe blockage. On the contrary, when the pipeline conveying pressure approaches the ultimate bearing pressure of the pipeline, the molecular value approaches the denominator value, and thus the risk coefficient value approaches 1, indicating a higher risk of pipe blockage. Through this formula, the pipe blockage risk of the pipeline is quantified into a value between 0 and 1. The larger the value, the higher the risk. This quantification method provides data support for the subsequent determination of the pipe blockage risk level and the adoption of risk measures. For example, the risk coefficient can be divided into different levels, such as low risk, medium risk, and high risk, and each risk level corresponds to different countermeasures.

[0066] This application further proposes the classification of the pipeline plugging risk level as follows: When the pipeline plugging risk coefficient value is 0 < ≤ 0.4, it is determined as low risk, and normal construction continues; When the pipeline plugging risk coefficient value is 0.4 < ≤ 0.6, it is determined as medium risk, and monitoring is strengthened and the pipeline conveying pressure is reduced; When the pipeline plugging risk coefficient value is 0.6 < ≤ 1.0, it is determined as high risk, and pumping is immediately stopped.

[0067] Among them, for the classification of the pipeline plugging risk level, the numerical range of the risk coefficient is divided into three intervals. When the pipeline plugging risk coefficient value is 0 < ≤ 0.4, the pipeline plugging risk level is determined as low risk. At this time, normal construction operations continue; when the pipeline plugging risk coefficient value is 0.4 < ≤ 0.6, the pipeline plugging risk level is determined as medium risk. At this time, it is necessary to strengthen the monitoring of the pipeline conveying state and reduce the pipeline conveying pressure to reduce the risk of pipe blockage; when the pipeline plugging risk coefficient value is 0.6 < ≤ 1.0, the pipeline plugging risk level is determined as high risk. At this time, immediately stop the pumping operation of foamed concrete to avoid pipe blockage or pipe explosion accidents. Thus, by defining the relationship between the risk coefficient value, the risk level, and the corresponding measures, the operator can quickly judge the current pipeline plugging risk level according to the risk coefficient value and take corresponding risk measures to ensure the safety of pipeline transportation.

[0068] Specifically, the purpose of classifying the risk level of pipeline plugging is to provide clear risk indication and operation guidance for operators based on the calculated pipeline plugging risk coefficient value. The pipeline plugging risk coefficient is a numerical index representing the degree of pipeline plugging risk, and the higher the value, the greater the pipeline plugging risk. For the convenience of practical application, the risk coefficient values are divided into different risk levels, and corresponding operation measures are set for each risk level. Through this hierarchical management and control, the pipeline plugging risk can be effectively prevented and addressed, ensuring the safety and smooth progress of the foamed concrete conveying operation.

[0069] Reference Figure 3 , this application provides a pipeline plugging prediction device 300 for long-distance foamed concrete conveying, which includes: A data acquisition module 301 for acquiring the first wet density data and the second wet density data of the foamed concrete slurry; A data processing module 302 for calculating the defoaming rate of the foamed concrete slurry during pipeline conveying based on the first wet density data and the second wet density data, predicting the real-time pipeline conveying pressure according to the functional relationship between the pipeline conveying pressure and the defoaming rate, and calculating the pipeline plugging risk coefficient based on the real-time pipeline conveying pressure; An early warning module 303 for determining the plugging risk level according to the pipeline plugging risk coefficient and triggering an alarm signal.

[0070] Among them, the data acquisition module 301 is used to monitor the wet density of the foamed concrete slurry in real time. The data processing module 302 can adopt a central processing unit, which is programmed to perform the calculations of the defoaming rate, the real-time pipeline conveying pressure, and the pipeline plugging risk coefficient. When calculating the defoaming rate, the data processing module 302 receives the first wet density data and the second wet density data from the data acquisition module 301 and calculates using a preset formula. The prediction of the real-time pipeline conveying pressure can be based on a pre-established functional relationship model between the pipeline conveying pressure and the defoaming rate. The calculation of the pipeline plugging risk coefficient can be based on the predicted real-time pipeline conveying pressure, the pipeline conveying pressure during normal pumping of foamed concrete, and the pipeline ultimate bearing pressure. The early warning module 303 can be connected to a display device and a sound alarm. When the pipeline plugging risk coefficient reaches or exceeds a preset threshold, the early warning module 303 controls the display device to display an alarm message and activates the sound alarm to issue an alarm. The data acquisition module 301, the data processing module 302, and the early warning module 303 perform data transmission and instruction interaction through wired or wireless means to achieve collaborative work.

[0071] Specifically, the working principle of the long-distance foam concrete conveying pipeline blockage prediction device 300 is as follows: First, the data acquisition module 301 collects the first wet density data and the second wet density data of the foam concrete slurry at the inlet end and the outlet end of the pipeline in real time. These data are transmitted to the data processing module 302. After receiving the data, the data processing module 302 calculates the defoaming rate of the foam concrete slurry during pipeline transportation based on the first wet density data and the second wet density data. Then, the data processing module 302 predicts the real-time pipeline transportation pressure based on the pre-set functional relationship between the pipeline transportation pressure and the defoaming rate. Further, the data processing module 302 calculates the pipeline blockage risk coefficient according to the predicted real-time pipeline transportation pressure. Finally, the warning module 303 receives the pipeline blockage risk coefficient and determines the blockage risk level of the current pipeline according to the pre-set blockage risk level classification standard. If the risk level reaches medium risk or high risk, the warning module 303 immediately triggers an alarm signal to remind the operator to take corresponding measures, such as reducing the pipeline transportation pressure or stopping the pumping, so as to avoid the occurrence of pipeline blockage or pipe burst accidents, and realizes the real-time and accurate prediction of the blockage risk of the long-distance conveying pipeline.

[0072] The technical solution of this application is based on the defoaming principle of the internal bubbles of foam concrete under the action of pressure. By constructing the functional relationship between the pipeline transportation pressure and the defoaming rate of the bubbles of the transportation medium, it realizes the accurate prediction of the blockage state of the long-distance pipeline and the quantitative characterization of the pipeline blockage risk. Compared with the traditional method, this method does not require additional monitoring equipment or professional technicians. It only needs to collect and analyze the data of the wet density, which is an essential measurement index of foam concrete, greatly reducing the monitoring and prediction cost of foam concrete blockage in the pipeline. At the same time, it avoids the long-term maintenance problem of a large number of monitoring equipment. The prediction method has a simple and easy-to-understand principle and is convenient for on-site personnel to operate, which can realize the real-time prediction of the risk of long-distance conveying pipelines, with strong timeliness and high accuracy, and can provide strong support for the safe pumping of long-distance foam concrete.

[0073] In this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0074] The above description is only for the embodiments of this application and is not intended to limit the protection scope of this application. For those skilled in the art, this application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included in the protection scope of this application.

Claims

1. A method for predicting pipe blockage in a long-distance foam concrete delivery pipeline, characterized in that: The following steps are involved: S1: collecting first wet density data and second wet density data of foamed concrete slurry at the inlet and outlet of the on-site pipeline respectively, and calculating the defoaming rate of the foamed concrete slurry during pipeline transportation according to the first wet density data and the second wet density data; S2: predicting the real-time pipeline delivery pressure according to the functional relationship between the pipeline delivery pressure and the defoaming rate; S3: Calculating the pipeline blockage risk coefficient according to the real-time delivery pressure of the pipeline; S4: Determine the pipe blocking risk level and corresponding risk measures according to the pipeline blocking risk coefficient.

2. The method for predicting pipe blockage in a long-distance foamed concrete delivery pipeline according to claim 1 is characterized in that: The step S1 comprises: The defoaming rate is calculated according to the following formula : ； In the formula is the first wet density data, This is the second wet density data.

3. The method for predicting pipe blockage of a long-distance foamed concrete delivery pipeline according to claim 2 is characterized in that: The first wet density data and the second wet density data are obtained by testing using a measuring cup method, wherein the measuring cup has a standard 1L volume and is made of a material selected from glass, stainless steel or plastic.

4. The method for predicting pipe blockage of a long-distance foamed concrete delivery pipeline according to claim 1, characterized in that: The step S2 comprises: Construct a functional relationship between the pipeline delivery pressure and the defoaming rate: ； In the formula is the transport pressure value of the i-th stage pipeline, is the defoaming rate of the foamed concrete slurry corresponding to the i-th level pipeline delivery pressure, i is a positive integer and its value range satisfies 1≤i≤N, wherein N is the total number of pipeline delivery pressure levels and N≥3, a is the first coefficient, and b is the second coefficient.

5. The method for predicting pipe blockage in a long-distance foam concrete delivery pipeline according to claim 4, characterized in that: The constructing of the functional relationship between the pipeline delivery pressure and the defoaming rate comprises: Dividing the pipeline delivery pressure into multiple levels, and carrying out the foam concrete pumping and pouring model experiment under the multiple levels of preset pipeline delivery pressure; Determine the defoaming rate at different levels of the pipeline delivery pressure, and establish a functional relationship between the defoaming rate and the pipeline delivery pressure; The first coefficient or the second coefficient in the functional relationship is modified.

6. The method for predicting pipe blockage in a long-distance foamed concrete delivery pipeline according to claim 5, characterized in that: The modifying of the first coefficient or the second coefficient in the functional relationship comprises the following steps: Start the timer to start timing, or start the distance counter to start distance counting; monitoring the time of the timer or the distance count value of the distance counter in real time; When it is monitored that the timer reaches a preset time interval or the distance counter reaches a preset distance interval, triggering a function relationship correction instruction; In response to the functional relationship correction instruction, collecting the first wet density data and the second wet density data of the foamed concrete slurry at the inlet end and the outlet end of the pipeline and data of the current pipeline delivery pressure; Calculating the defoaming rate of the foamed concrete slurry in the current pumping stage according to the collected first wet density data and the second wet density data; Based on the defoaming rate of the foamed concrete slurry in the current pumping stage and the current pipeline delivery pressure data, the first coefficient or the second coefficient in the functional relationship is corrected to obtain a corrected functional relationship; The functional relationship is updated and the timer or the distance counter is reset.

7. The method for predicting pipe blockage in a long-distance foamed concrete delivery pipeline according to claim 6, characterized in that: The first coefficient has a value range of 1.5 to 2.5, and the second coefficient has a value range of 0.85 to 1.

0.

8. The method for predicting pipe blockage in a long-distance foamed concrete delivery pipeline according to claim 1, characterized in that: The step S3 comprises: The pipeline blockage risk coefficient is calculated according to the following formula : ； In the formula Delivering real-time pressure to the pipeline, It is the pipeline delivery pressure when the foam concrete slurry is pumped normally. is the ultimate bearing pressure of the pipeline.

9. The method for predicting pipe blockage in a long-distance foamed concrete delivery pipeline according to claim 1, characterized in that: The pipe blocking risk levels in step S4 are divided into: When the pipeline blocking risk coefficient is 0< When ≤0.4, it is judged as low risk and normal construction continues; When the pipeline blocking risk coefficient is 0.4< When ≤0.6, it is judged as medium risk, and monitoring should be strengthened and pipeline transmission pressure should be reduced; When the pipeline blocking risk coefficient is 0.6< When ≤1.0, it is judged as high risk and pumping is stopped immediately.

10. A device for predicting pipe blockage in a long-distance foam concrete delivery pipeline, characterized in that: The device includes: A data acquisition module, used for acquiring first wet density data and second wet density data of foam concrete slurry; a data processing module, configured to calculate the defoaming rate of the foamed concrete slurry during pipeline transportation according to the first wet density data and the second wet density data, predict the real-time pipeline transportation pressure according to the functional relationship between the pipeline transportation pressure and the defoaming rate, and calculate the pipeline blockage risk coefficient according to the real-time pipeline transportation pressure; The early warning module is used to determine the pipe blocking risk level according to the pipeline blocking risk coefficient and trigger an alarm signal.

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