Dredging, filling, aeration and boosting pipeline slurry transportation pressure regulating system

Abstract

The present invention discloses a slurry conveying pressure regulating system for dredging, blowing, filling, and aerating pipelines, which belongs to the field of port and waterway engineering technology, and comprises: a data acquisition module for collecting real-time data of slurry conveying in dredging, blowing, filling, and aerating pipelines; a data processing module for processing real-time data of slurry conveying in dredging, blowing, filling, and aerating pipelines; an analysis and prediction module for analyzing and identifying characteristic data of slurry conveying in dredging, blowing, filling, and aerating pipelines; and a regulating and controlling module for regulating the slurry conveying pressure in dredging, blowing, filling, and aerating pipelines. The present invention solves the problem that the existing system cannot adjust the conveying pressure in real time according to the slurry conveying conditions in dredging, blowing, filling, and aerating pipelines, resulting in low slurry conveying efficiency in dredging, blowing, filling, and aerating pipelines. The present invention can adjust the conveying pressure in real time according to the slurry conveying conditions in dredging, blowing, filling, and aerating pipelines, and can improve the slurry conveying efficiency in dredging, blowing, filling, and aerating pipelines.

Description

Technical Field

[0001] The present invention relates to the technical field of port and waterway engineering, in particular to a slurry conveying pressure regulating system for a dredging, blowing, filling, and aeration-assisted pipeline. Background Art

[0002] Cutter suction dredgers are the primary equipment for dredging and filling in port and waterway projects. For fine silt (typical soil), the design row span of a cutter suction dredger is generally 2-3 km. When filling is performed at a distance from the filling area, where the ship's pump power is generally insufficient, relay pumps are typically added to achieve long-row filling operations. The transport resistance of the dredging pipeline is the primary energy drain on dredged material pumps. To reduce this energy consumption and achieve a green transition to enhanced fill technology, compressed air generated by an air compressor is injected into the pipeline through an ejector installed on a dedicated aeration line on the dredged material discharge pipeline. This reduces pipeline resistance and enables long-distance transport of dredged material.

[0003] The Chinese patent with publication number CN119434185A discloses an environmentally friendly dredging and filling method, including: obtaining actual environmental information of the area to be dredged and filled, and determining the construction area and conservation area based on the actual environmental information and construction drawing information; transferring the resources to be conserved in the construction area, and carrying out dredging and filling operations after implementing protective measures in the conservation area; carrying out maintenance and construction operations in the conservation area. By obtaining detailed actual environmental information of the area to be dredged and filled, it is possible to comprehensively evaluate the impact of construction on the surrounding environment, so that sufficient planning and preparation can be made before construction, and the construction area and conservation area can be clearly divided to ensure that construction activities will not directly damage or interfere with natural resources or ecological environments that need to be protected. The resources to be conserved in the construction area are transferred, and special protective measures are implemented in the conservation area, which effectively reduces the negative impact of construction activities on the ecology and protects biodiversity. However, this patent has the following defects:

[0004] The existing technology cannot adjust the delivery pressure in real time according to the slurry delivery situation of the dredging, blowing, filling and aeration-assisted pipeline, resulting in low slurry delivery efficiency of the dredging, blowing, filling and aeration-assisted pipeline. Summary of the Invention

[0005] The purpose of the present invention is to provide a dredging blowing, filling, and aeration-assisted pipeline slurry conveying pressure regulation system, which can adjust the conveying pressure in real time according to the slurry conveying situation of the dredging blowing, filling, and aeration-assisted pipeline, thereby improving the slurry conveying efficiency of the dredging blowing, filling, and aeration-assisted pipeline, and solving the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The dredging, blowing, filling and aeration-assisted pipeline slurry conveying pressure regulating system includes:

[0008] Data acquisition module, used to collect real-time data on slurry transportation in dredging, blowing, filling and aeration-assisted pipelines;

[0009] A data processing module is used to process the real-time data of slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline, and determine the characteristic data of slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline;

[0010] The analysis and prediction module is used to construct a mathematical model for predicting the slurry delivery pressure of the dredged blowing, filling and aeration-assisted pipeline, analyze and identify the characteristic data of the slurry delivery of the dredged blowing, filling and aeration-assisted pipeline, and determine the prediction results of the slurry delivery pressure of the dredged blowing, filling and aeration-assisted pipeline;

[0011] The regulation control module is used to adjust the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline according to the prediction result of the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline, so as to realize the precise regulation and closed-loop control of the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline.

[0012] Preferably, the slurry delivery pressure of the dredging, blowing, filling and aeration boosting pipeline is adjusted, including:

[0013] Based on the prediction results of the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline, a slurry delivery pressure regulation plan for the dredging, blowing, filling and aeration-assisted pipeline is formulated, which is achieved by adjusting the gas injection volume flow rate, injection pressure and slurry flow rate;

[0014] When the slurry delivery pressure prediction result of the dredging, blowing, filling and aeration boosting pipeline is too high, the gas injection volume flow rate, injection pressure or slurry flow rate should be increased;

[0015] When the slurry delivery pressure prediction result of the dredging, blowing, filling and aeration boosting pipeline is too low, the gas injection volume flow rate, injection pressure or slurry flow rate should be reduced;

[0016] At the same time, the slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline after pressure adjustment is monitored in real time, and the slurry transportation pressure in the dredging, blowing, filling and aeration-assisted pipeline is adjusted according to the monitoring feedback, thereby forming precise adjustment and closed-loop control of the slurry transportation pressure in the dredging, blowing, filling and aeration-assisted pipeline.

[0017] Preferably, the slurry delivery pressure of the dredging, blowing, filling and aeration boosting pipeline is adjusted according to the monitoring feedback, including:

[0018] When the predicted result of the slurry delivery pressure of the dredging, blowing, filling, and aeration-assisted pipeline is that the delivery pressure is too high or too low, and the corresponding slurry delivery pressure of the dredging, blowing, filling, and aeration-assisted pipeline after the adjustment operation still cannot meet the actual slurry delivery pressure adjustment requirement of the dredging, blowing, filling, and aeration-assisted pipeline, the gas injection volume flow rate and the slurry flow rate are adjusted;

[0019] Performing ratio processing on the gas injection volume flow rate and the slurry flow rate to obtain gas-slurry relationship parameters;

[0020] comparing the gas-slurry relationship parameter with a preset parameter range;

[0021] When the gas-slurry relationship parameter is within the preset parameter range, the slurry delivery pressure of the dredging, blowing, filling, and aeration boosting pipeline is temporarily not adjusted in real time;

[0022] When the gas-slurry relationship parameter is not within the preset parameter range, the gas-liquid mixing efficiency coefficient currently used for the reaction gas distribution uniformity is retrieved;

[0023] Performing ratio processing on the gas-slurry relationship parameter and a preset parameter range to obtain a gas-slurry parameter proportional coefficient, and performing normalization processing on the gas-slurry parameter proportional coefficient to obtain the normalized gas-slurry parameter proportional coefficient;

[0024] The normalized air-slurry parameter proportional coefficient is compared with the gas-liquid mixing efficiency coefficient, and the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline is adjusted according to the comparison result of the normalized air-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient.

[0025] Preferably, the slurry delivery pressure of the dredging, blowing, filling, and aeration-assisted pipeline is adjusted according to the comparison result of the normalized gas-slurry parameter ratio coefficient and the gas-liquid mixing efficiency coefficient, including:

[0026] When the difference between the normalized gas-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient does not exceed the preset difference ratio, the normalized gas-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient are used to adjust the slurry delivery pressure in the dredging, blowing, filling and aeration boosting pipeline;

[0027] When the difference between the normalized gas-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient exceeds a preset difference ratio, the current slurry density and air density are retrieved;

[0028] Performing ratio processing on the current slurry density and air density to obtain a density coefficient;

[0029] Comparing the density coefficient with the gas-liquid mixing efficiency coefficient, taking the coefficient parameter with the larger coefficient value between the density coefficient and the gas-liquid mixing efficiency coefficient as the first coefficient, and taking the coefficient parameter with the smaller coefficient value between the density coefficient and the gas-liquid mixing efficiency coefficient as the second coefficient;

[0030] Retrieving the current gas injection volume flow rate and the slurry flow rate, and normalizing the current gas injection volume flow rate and the slurry flow rate to obtain the normalized gas injection volume flow rate and the slurry flow rate;

[0031] The first coefficient and the second coefficient are combined with the normalized gas injection volume flow rate and the slurry flow rate to adjust the slurry delivery pressure of the dredging, blowing, filling and aeration boosting pipeline.

[0032] Preferably, the analysis and identification of the slurry transportation characteristic data of the dredging, blowing, filling and aeration-assisted pipeline includes:

[0033] Deploy the mathematical model for predicting the slurry delivery pressure of dredged, blown, and aerated pipelines. Deploy the mathematical model in the actual slurry delivery pressure prediction environment.

[0034] The slurry transportation characteristic data of the dredged blowing, filling and aeration-assisted pipeline are input into the mathematical model for predicting the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline. Based on the mathematical model for predicting the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline, the slurry transportation characteristic data of the dredged blowing, filling and aeration-assisted pipeline are analyzed and identified, and the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline is effectively predicted, thereby determining the prediction result of the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline.

[0035] Preferably, the prediction performance of the mathematical model for predicting the slurry delivery pressure in the dredging, filling, and aeration-assisted pipeline is evaluated, including:

[0036] The test set is input into the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, and aerated pipelines to determine whether the deep learning-based mathematical model can achieve the expected effect of effectively predicting the slurry delivery pressure of dredged, blown, and aerated pipelines.

[0037] When the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines cannot achieve the expected effect of effectively predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines, the parameters of the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines are continuously adjusted, and the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines is iteratively optimized until the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines can achieve the expected effect of effectively predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines, thereby determining the optimal mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines.

[0038] Preferably, a mathematical model for predicting the slurry delivery pressure in a dredging, blowing, filling, and aeration-assisted pipeline is constructed, including:

[0039] Collect historical data on slurry transportation in dredging, blowing, filling, and aeration-assisted pipelines, and divide the collected historical data into training sets and test sets;

[0040] Based on deep learning technology, a training set is used to train the deep learning model. The deep learning model can autonomously learn the prediction behavior of slurry delivery pressure in dredged, blown, filled, and aerated pipelines from the training set, and effectively predict the slurry delivery pressure in dredged, blown, filled, and aerated pipelines. Thus, a mathematical model for predicting slurry delivery pressure in dredged, blown, filled, and aerated pipelines based on deep learning is determined.

[0041] The deep learning-based mathematical model for predicting slurry delivery pressure in dredged, blown, and aerated pipelines was tested based on the test set to evaluate the prediction performance of the model and determine the model test evaluation results.

[0042] According to the model test evaluation results, the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines is optimized to determine the optimal mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines.

[0043] Preferably, real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines is collected, including:

[0044] Compressed gas is generated by an air compressor and injected into the mud discharge pipe through an ejector. Based on the intelligent data collection equipment, the pipeline diameter, pipeline length, pipeline roughness, slurry concentration, gas injection pressure, gas injection volume flow, slurry flow, slurry flow rate, slurry flow rate, slurry resistance and slurry pressure drop during the slurry transportation process of the dredging, blowing, filling and aeration-assisted pipeline are monitored in real time, and real-time data of slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline are collected.

[0045] Preferably, the real-time data of slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline is processed, including:

[0046] Clean the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines to remove noise from the data and reduce the interference of noise on the pressure prediction of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines;

[0047] Check the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines one by one, identify abnormal values ​​and missing values ​​in the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines, and process the identified abnormal values ​​and missing values;

[0048] Evaluate the identified outliers and missing values ​​to determine their contribution to the prediction of slurry delivery pressure in dredging, filling, and aeration-assisted pipelines;

[0049] When the outliers and missing values ​​have a high contribution to the prediction of slurry delivery pressure in dredging, filling and aeration-assisted pipelines, the outliers are corrected and the missing values ​​are filled;

[0050] When the contribution of outliers and missing values ​​to the prediction of slurry delivery pressure in dredging, filling and aeration-assisted pipeline is low, the outliers and missing values ​​are deleted.

[0051] Preferably, the processing of real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines further includes:

[0052] Normalize the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines to remove the dimension differences in the real-time data and form standardized real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines;

[0053] Feature extraction is performed on the real-time data of slurry transportation in dredged blowing, filling and aeration-assisted pipelines. Feature vectors related to the pressure prediction of slurry transportation in dredged blowing, filling and aeration-assisted pipelines are extracted from the real-time data of slurry transportation in dredged blowing, filling and aeration-assisted pipelines. The extracted feature vectors are weightedly fused to form the feature data of slurry transportation in dredged blowing, filling and aeration-assisted pipelines.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The present invention monitors the pipeline diameter, pipeline length, pipeline roughness, slurry concentration, gas injection pressure, gas injection volume flow, slurry flow, slurry flow rate, slurry resistance and slurry pressure drop in the slurry transportation process of the dredging, blowing, filling and aeration-assisted pipeline in real time, collects the real-time data of the slurry transportation of the dredging, blowing, filling and aeration-assisted pipeline, processes the real-time data of the slurry transportation of the dredging, blowing, filling and aeration-assisted pipeline, determines the characteristic data of the slurry transportation of the dredging, blowing, filling and aeration-assisted pipeline, and constructs a slurry transportation pressure prediction system for the slurry transportation of the dredging, blowing, filling and aeration-assisted pipeline. The mathematical model analyzes and identifies the characteristic data of slurry transportation in dredged blowing, filling and aeration-assisted pipelines, determines the prediction results of slurry transportation pressure in dredged blowing, filling and aeration-assisted pipelines, and adjusts the slurry transportation pressure in dredged blowing, filling and aeration-assisted pipelines according to the prediction results, thereby realizing precise adjustment and closed-loop control of the slurry transportation pressure in dredged blowing, filling and aeration-assisted pipelines. The transportation pressure can be adjusted in real time according to the slurry transportation conditions in dredged blowing, filling and aeration-assisted pipelines, thereby improving the slurry transportation efficiency in dredged blowing, filling and aeration-assisted pipelines. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a module diagram of the slurry conveying pressure regulating system for dredging, blowing, filling, and aerating pipelines according to the present invention;

[0057] Figure 2This is a flow chart of the slurry delivery pressure regulating system for dredging, blowing, filling, and aerating pipelines according to the present invention. DETAILED DESCRIPTION

[0058] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0059] In order to solve the existing problem that the delivery pressure cannot be adjusted in real time according to the slurry delivery situation of the dredging, blowing, filling and aeration boosting pipeline, resulting in low slurry delivery efficiency of the dredging, blowing, filling and aeration boosting pipeline, please refer to Figure 1-Figure 2 , this embodiment provides the following technical solutions:

[0060] The dredging, blowing, filling and aeration-assisted pipeline slurry transportation pressure regulating system includes: a data acquisition module, a data processing module, an analysis and prediction module and a regulation and control module.

[0061] Among them, the data acquisition module is used to collect real-time data on slurry transportation in dredging, blowing, filling and aeration-assisted pipelines.

[0062] In this embodiment, real-time data on slurry transportation in a dredging, blowing, filling, and aeration-assisted pipeline is collected, including:

[0063] Compressed gas is generated by an air compressor and injected into the mud discharge pipe through an ejector. Based on the intelligent data collection equipment, the pipeline diameter, pipeline length, pipeline roughness, slurry concentration, gas injection pressure, gas injection volume flow, slurry flow, slurry flow rate, slurry flow rate, slurry resistance and slurry pressure drop during the slurry transportation process of the dredging, blowing, filling and aeration-assisted pipeline are monitored in real time, and real-time data of slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline are collected.

[0064] Among them, the data processing module is used to process the real-time data of slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline, and determine the characteristic data of slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline.

[0065] In this embodiment, the real-time data of slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline is processed, including:

[0066] Clean the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines to remove noise from the data and reduce the interference of noise on the pressure prediction of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines;

[0067] Check the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines one by one, identify abnormal values ​​and missing values ​​in the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines, and process the identified abnormal values ​​and missing values;

[0068] Evaluate the identified outliers and missing values ​​to determine their contribution to the prediction of slurry delivery pressure in dredging, filling, and aeration-assisted pipelines;

[0069] When the outliers and missing values ​​have a high contribution to the prediction of slurry delivery pressure in dredging, filling and aeration-assisted pipelines, the outliers are corrected and the missing values ​​are filled;

[0070] When the contribution of outliers and missing values ​​to the prediction of slurry delivery pressure in dredging, filling and aeration-assisted pipeline is low, the outliers and missing values ​​are deleted.

[0071] In this embodiment, the real-time data of slurry transportation in a dredging, blowing, filling, and aeration-assisted pipeline is processed, and the following steps are also included:

[0072] Normalize the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines to remove the dimension differences in the real-time data and form standardized real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines;

[0073] Feature extraction is performed on the real-time data of slurry transportation in dredged blowing, filling and aeration-assisted pipelines. Feature vectors related to the pressure prediction of slurry transportation in dredged blowing, filling and aeration-assisted pipelines are extracted from the real-time data of slurry transportation in dredged blowing, filling and aeration-assisted pipelines. The extracted feature vectors are weightedly fused to form the feature data of slurry transportation in dredged blowing, filling and aeration-assisted pipelines.

[0074] Among them, the analysis and prediction module is used to construct a mathematical model for predicting the slurry transportation pressure of dredged blowing, filling and aeration-assisted pipelines, analyze and identify the characteristic data of slurry transportation in dredged blowing, filling and aeration-assisted pipelines, and determine the prediction results of the slurry transportation pressure of dredged blowing, filling and aeration-assisted pipelines.

[0075] In this embodiment, a mathematical model for predicting the slurry delivery pressure in a dredging, blowing, filling, and aeration-assisted pipeline is constructed, including:

[0076] Collect historical data on slurry transportation in dredging, blowing, filling, and aeration-assisted pipelines, and divide the collected historical data into training sets and test sets;

[0077] Based on deep learning technology, a training set is used to train the deep learning model. The deep learning model can autonomously learn the prediction behavior of slurry delivery pressure in dredged, blown, filled, and aerated pipelines from the training set, and effectively predict the slurry delivery pressure in dredged, blown, filled, and aerated pipelines. Thus, a mathematical model for predicting slurry delivery pressure in dredged, blown, filled, and aerated pipelines based on deep learning is determined.

[0078] The deep learning-based mathematical model for predicting slurry delivery pressure in dredged, blown, and aerated pipelines was tested based on the test set to evaluate the prediction performance of the model and determine the model test evaluation results.

[0079] According to the model test evaluation results, the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines is optimized to determine the optimal mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines.

[0080] The test set is input into a deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, and aerated pipelines to determine whether the deep learning-based mathematical model can achieve the expected effect of effectively predicting the slurry delivery pressure of dredged, blown, and aerated pipelines.

[0081] When the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines cannot achieve the expected effect of effectively predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines, the parameters of the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines are continuously adjusted, and the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines is iteratively optimized until the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines can achieve the expected effect of effectively predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines, thereby determining the optimal mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines.

[0082] In this embodiment, analysis and identification of slurry transport characteristic data of dredging, blowing, filling and aeration-assisted pipelines include:

[0083] Deploy the mathematical model for predicting the slurry delivery pressure of dredged, blown, and aerated pipelines. Deploy the mathematical model in the actual slurry delivery pressure prediction environment.

[0084] The slurry transportation characteristic data of the dredged blowing, filling and aeration-assisted pipeline are input into the mathematical model for predicting the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline. Based on the mathematical model for predicting the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline, the slurry transportation characteristic data of the dredged blowing, filling and aeration-assisted pipeline are analyzed and identified, and the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline is effectively predicted, thereby determining the prediction result of the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline.

[0085] Among them, the regulation and control module is used to adjust the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline according to the prediction results of the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline, so as to realize the precise regulation and closed-loop control of the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline.

[0086] In this embodiment, the slurry delivery pressure in the dredging, blowing, filling, and aeration-assisted pipeline is adjusted, including:

[0087] Based on the prediction results of the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline, a slurry delivery pressure regulation plan for the dredging, blowing, filling and aeration-assisted pipeline is formulated, which is achieved by adjusting the gas injection volume flow rate, injection pressure and slurry flow rate;

[0088] When the slurry delivery pressure prediction result of the dredging, blowing, filling and aeration boosting pipeline is too high, the gas injection volume flow rate, injection pressure or slurry flow rate should be increased;

[0089] When the slurry delivery pressure prediction result of the dredging, blowing, filling and aeration boosting pipeline is too low, the gas injection volume flow rate, injection pressure or slurry flow rate should be reduced;

[0090] At the same time, the slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline after pressure adjustment is monitored in real time, and the slurry transportation pressure in the dredging, blowing, filling and aeration-assisted pipeline is adjusted according to the monitoring feedback, thereby forming precise adjustment and closed-loop control of the slurry transportation pressure in the dredging, blowing, filling and aeration-assisted pipeline.

[0091] Specifically, the slurry delivery pressure in the dredging, blowing, filling and aeration booster pipeline is adjusted based on monitoring feedback, including:

[0092] When the predicted result of the slurry delivery pressure of the dredging, blowing, filling, and aeration-assisted pipeline is that the delivery pressure is too high or too low, and the corresponding slurry delivery pressure of the dredging, blowing, filling, and aeration-assisted pipeline after the adjustment operation still cannot meet the actual slurry delivery pressure adjustment requirement of the dredging, blowing, filling, and aeration-assisted pipeline, the gas injection volume flow rate and the slurry flow rate are adjusted;

[0093] Performing ratio processing on the gas injection volume flow rate and the slurry flow rate to obtain gas-slurry relationship parameters;

[0094] comparing the gas-slurry relationship parameter with a preset parameter range;

[0095] When the gas-slurry relationship parameter is within the preset parameter range, the slurry delivery pressure of the dredging, blowing, filling, and aeration boosting pipeline is temporarily not adjusted in real time;

[0096] When the gas-slurry relationship parameter is not within the preset parameter range, the gas-liquid mixing efficiency coefficient currently used for the reaction gas distribution uniformity is retrieved;

[0097] Performing ratio processing on the gas-slurry relationship parameter and a preset parameter range to obtain a gas-slurry parameter proportional coefficient, and performing normalization processing on the gas-slurry parameter proportional coefficient to obtain the normalized gas-slurry parameter proportional coefficient;

[0098] The normalized air-slurry parameter proportional coefficient is compared with the gas-liquid mixing efficiency coefficient, and the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline is adjusted according to the comparison result of the normalized air-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient.

[0099] The technical effect of the above technical solution is that if the pressure still does not meet the target after initial adjustment, the system fine-tunes it by monitoring the gas-slurry ratio parameters. The gas-liquid mixing efficiency coefficient reflects the uniformity of gas dispersion in the slurry. Good mixing reduces interphase slip velocity, minimizes energy loss, and thus optimizes pressure distribution. Comparing the gas-slurry ratio parameters with the preset range essentially assesses whether the current gas-liquid ratio is in the optimal flow state. For example, when Qg / Qs is too high, gas plugs may form, increasing flow resistance; when Qg / Qs is too low, the drag-reducing effect of the gas is insufficient. Normalizing the gas-slurry ratio coefficient and comparing it with the mixing efficiency coefficient eliminates dimensional effects and more accurately reflects the synergistic effect of the two. For example, when the difference between the two is small, it indicates that the gas-liquid ratio and mixing effect are well matched, and pressure can be adjusted directly using the formula. However, when the difference is large, more complex corrections such as the density coefficient are required, thereby improving the accuracy and precision of pressure correction. Furthermore, the above technical solution combines parameters such as gas flow rate, slurry flow rate, mixing efficiency, and density to achieve multi-dimensional and precise pressure control. For example, by comparing the gas-slurry parameter ratio coefficient with the mixing efficiency coefficient, it is possible to identify whether the gas-liquid mixing state deviates from the optimal value and adjust the pressure accordingly. Based on the monitoring results, the system automatically switches the adjustment mode (preliminary adjustment or fine adjustment) to adapt to different operating conditions. For example, when the gas-slurry relationship parameters exceed the preset range, a more complex density coefficient correction is initiated to improve the adjustment accuracy. Closed-loop control can monitor pressure changes in real time and compensate for interference factors in a timely manner to avoid equipment damage or transmission interruptions caused by large pressure fluctuations. By adjusting the gas-liquid ratio and mixing efficiency, a stable flow pattern is maintained, pressure mutations caused by flow pattern changes are reduced, and energy waste caused by excessive gas is effectively avoided.

[0100] Specifically, the slurry delivery pressure of the dredging, blowing, filling, and aeration-assisted pipeline is adjusted according to the comparison result of the normalized gas-slurry parameter ratio coefficient and the gas-liquid mixing efficiency coefficient, including:

[0101] When the difference between the normalized gas-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient does not exceed the preset difference ratio, the normalized gas-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient are used to adjust the slurry delivery pressure in the dredging, blowing, filling and aeration boosting pipeline;

[0102] The adjusted slurry delivery pressure of the dredging, blowing, filling and aeration boosting pipeline is obtained by the following formula:

[0103]

[0104] Among them, P t represents the slurry delivery pressure of the dredged blowing and filling aeration booster pipeline after adjustment; P0 represents the slurry delivery pressure of the dredged blowing and filling aeration booster pipeline before adjustment; k represents the gas-slurry parameter proportional coefficient after normalization; s represents the gas-liquid mixing efficiency coefficient, the coefficient range is (0, 1); x represents the data scaling coefficient, the value range is 0.1-1.5; specifically, the denominator Nonlinear scaling of synergy effects, Reflects the degree of synergistic matching between the gas-slurry ratio and the gas-liquid mixing efficiency; This formula quantifies the impact of the difference between the air-slurry ratio (k) and mixing efficiency (s) on pressure, and adapts to engineering scenarios through logarithmic calculations and a scaling factor x. This formula transforms the complex flow characteristics of gas-liquid two-phase flow (air-slurry ratio, mixing efficiency) into a quantifiable and calibrable mathematical model. This model captures the impact of the synergy / difference between the air-slurry ratio and mixing efficiency on pressure, avoiding the one-sidedness of single-parameter adjustment. Furthermore, through logarithmic buffering and scaling factors, it adapts to the variability of pipelines and slurry during dredging and filling, making pressure regulation more precise and practical.

[0105] When the difference between the normalized gas-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient exceeds a preset difference ratio, the current slurry density and air density are retrieved;

[0106] Performing ratio processing on the current slurry density and air density to obtain a density coefficient;

[0107] Comparing the density coefficient with the gas-liquid mixing efficiency coefficient, taking the coefficient parameter with the larger coefficient value between the density coefficient and the gas-liquid mixing efficiency coefficient as the first coefficient, and taking the coefficient parameter with the smaller coefficient value between the density coefficient and the gas-liquid mixing efficiency coefficient as the second coefficient;

[0108] Retrieving the current gas injection volume flow rate and the slurry flow rate, and normalizing the current gas injection volume flow rate and the slurry flow rate to obtain the normalized gas injection volume flow rate and the slurry flow rate;

[0109] The first coefficient and the second coefficient are combined with the normalized gas injection volume flow rate and the slurry flow rate to adjust the slurry delivery pressure of the dredging, blowing, filling and aeration boosting pipeline.

[0110] The adjusted slurry delivery pressure of the dredging, blowing, filling and aeration boosting pipeline is obtained by the following formula:

[0111]

[0112] Among them, P t It represents the slurry delivery pressure of the dredging, blowing, filling and aeration boosting pipeline after adjustment; P0 represents the slurry delivery pressure of the dredging, blowing, filling and aeration boosting pipeline before adjustment; Q g and Q s represents the normalized gas injection volume flow rate and slurry flow rate; f 01 and f 02 Represent the first coefficient and the second coefficient respectively; y represents the slurry density correction index, which is used to reflect the sensitivity of density to pressure, and its value range is 0.5-3.0. Specifically, middle The gas-liquid flow ratio reflects the matching relationship between gas injection volume and slurry delivery volume: It is to map the nonlinear change of flow ratio into pressure correction demand; at the same time, Obtained by "comparison of density coefficient and gas-liquid mixing efficiency coefficient" (such as f 01 Take the larger value, f 02 Take the smaller value), reflecting the combined influence weight of the physical properties of the gas-liquid two-phase (density difference) and the flow characteristics (mixing efficiency); y (slurry density correction index) reflects the strengthening / weakening of the sensitivity of slurry density to pressure. The flow ratio correction term (logarithmic link) quickly responds to the "matching degree of gas-liquid injection scale" and solves the "pressure surge / inefficiency problem caused by excessive / insufficient gas"; the density-coefficient correction term (fractional link) deeply associates the "gas-liquid physical properties and mixing characteristics" and solves the "pressure demand difference problem caused by slurry density difference and uneven mixing". Logarithmic operations are adapted to "pressure surges when the flow ratio deviates extremely" (such as the risk of gas plugs at the inlet of dredging pipelines) and "smooth corrections when the deviation is moderate" (such as fine-tuning of the flow rate in the middle of transportation); the density correction index y and the coefficient f 01 / f 02Adapting to the differences in pressure sensitivity of "different slurries (such as dredging slurry, tailings slurry) and different pipelines (such as long-distance transportation and high-drop filling)", the above-mentioned adaptation measures effectively improve the matching between the slurry transportation pressure adjustment of the dredging, filling and aeration-assisted pipeline and the current actual situation and the rationality of the pressure adjustment.

[0113] The technical effect of the above technical solution is to distinguish whether the difference between k and s exceeds the limit and provide two adjustment modes:

[0114] When the difference is small, the gas-slurry ratio and mixing efficiency are coordinated to adapt to the working conditions where the gas-liquid mixing is stable and the flow characteristics can be dominated by the gas-slurry parameters;

[0115] When the difference is large, it switches to coordinated regulation of density and flow to adapt to complex working conditions where gas-liquid mixing is more significantly affected by medium density differences and flow scale (such as high-concentration slurry and large flow fluctuation scenarios).

[0116] It covers the variable gas-liquid flow state in dredging and filling, improves the adaptability of pressure regulation to working conditions, and reduces the adjustment deviation caused by changes in working conditions.

[0117] At the same time, through the coupled calculation of multiple parameters such as k and s, density coefficient, and flow rate, the key factors affecting the delivery pressure are captured from different dimensions of gas-liquid interaction (parameter ratio-mixing efficiency synergy, density-flow synergy). The complex phase distribution, energy transfer, and flow resistance in the gas-liquid two-phase flow are converted into a basis for pressure regulation, ensuring that the pipeline delivery pressure is more closely aligned with actual flow requirements and reducing the impact of pressure fluctuations on the system (for example, avoiding pipeline wear caused by excessively high pressure and slurry precipitation caused by excessively low pressure). Precise pressure regulation can optimize the gas-liquid two-phase flow pattern (for example, avoiding gas plugs and disordered transitions between stratified flows), reducing pipeline blockages and energy waste caused by sudden flow pattern changes. For example, by controlling pressure to maintain a stable annular flow of gas and liquid, the gas "cushion" effect reduces friction between the slurry and the pipe wall, improving delivery efficiency and reducing energy consumption. Combining the "prediction-regulation-monitoring-feedback" logic, a closed pressure regulation loop is formed. When the initial adjustment fails to meet expectations (the difference exceeds the limit), it automatically switches to a more refined density-flow coordination mode to avoid pressure loss caused by the failure of a single mode, ensure the continuity and stability of dredging and filling operations, reduce the risk of equipment failure (such as pump overload and pipeline vibration), and improve system reliability and economy. Parameters such as k, s, density, and flow are all measurable and adjustable quantities that can be obtained in the project through sensors (such as flow meters and densitometers) or model calculations. The coefficients (x, y) in the formula can be calibrated on-site according to the pipeline material and slurry characteristics (such as particle size and viscosity). It has engineering feasibility and is easy to integrate into the automatic control system. For special scenarios such as low gas-liquid mixing efficiency and large density differences (such as gas-liquid separation at the end of long-distance transmission pipelines and high-concentration tailings transportation), the density coefficient and flow are coordinated to correct, solving the problem of traditional single flow / pressure regulation being difficult to adapt, thereby improving the quality and efficiency of slurry transportation in dredging and filling projects.

[0118] In summary, by constructing a mathematical model for predicting the slurry conveying pressure of dredged blowing, filling and aeration-assisted pipelines, the characteristic data of slurry conveying in dredged blowing, filling and aeration-assisted pipelines are analyzed and identified, the prediction results of the slurry conveying pressure of dredged blowing, filling and aeration-assisted pipelines are determined, and the slurry conveying pressure of dredged blowing, filling and aeration-assisted pipelines is adjusted according to the prediction results, so as to realize the precise adjustment and closed-loop control of the slurry conveying pressure of dredged blowing, filling and aeration-assisted pipelines, and the conveying pressure can be adjusted in real time according to the slurry conveying conditions of dredged blowing, filling and aeration-assisted pipelines, thereby improving the slurry conveying efficiency of dredged blowing, filling and aeration-assisted pipelines.

[0119] It should be noted that, in this document, relational terms such as first and second, etc., are used only 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. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0120] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. Dredging, blowing, filling, and aeration-assisted pipeline slurry delivery pressure regulating system, characterized by: include: Data acquisition module, used to collect real-time data on slurry transportation in dredging, blowing, filling and aeration-assisted pipelines; A data processing module is used to process the real-time data of slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline, and determine the characteristic data of slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline; The analysis and prediction module is used to construct a mathematical model for predicting the slurry delivery pressure of the dredged blowing, filling and aeration-assisted pipeline, analyze and identify the characteristic data of the slurry delivery of the dredged blowing, filling and aeration-assisted pipeline, and determine the prediction results of the slurry delivery pressure of the dredged blowing, filling and aeration-assisted pipeline; The regulating control module is used to regulate the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline according to the prediction result of the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline, so as to realize the precise regulation and closed-loop control of the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline; Adjust the slurry delivery pressure in the dredging, filling, and aeration booster pipeline, including: Based on the prediction results of the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline, a slurry delivery pressure regulation plan for the dredging, blowing, filling and aeration-assisted pipeline is formulated, which is achieved by adjusting the gas injection volume flow rate, injection pressure and slurry flow rate; When the slurry delivery pressure prediction result of the dredging, blowing, filling and aeration boosting pipeline is too high, the gas injection volume flow rate, injection pressure or slurry flow rate should be increased; When the slurry delivery pressure prediction result of the dredging, blowing, filling and aeration boosting pipeline is too low, the gas injection volume flow rate, injection pressure or slurry flow rate should be reduced; At the same time, the slurry delivery in the dredging, blowing, filling, and aeration boosting pipeline after pressure adjustment is monitored in real time, and the slurry delivery pressure in the dredging, blowing, filling, and aeration boosting pipeline is adjusted according to the monitoring feedback, thus forming a precise regulation and closed-loop control of the slurry delivery pressure in the dredging, blowing, filling, and aeration boosting pipeline; Adjust the slurry delivery pressure of the dredging, filling, and aeration booster pipeline based on monitoring feedback, including: When the predicted result of the slurry delivery pressure of the dredging, blowing, filling, and aeration-assisted pipeline is that the delivery pressure is too high or too low, and the corresponding slurry delivery pressure of the dredging, blowing, filling, and aeration-assisted pipeline after the adjustment operation still cannot meet the actual slurry delivery pressure adjustment requirement of the dredging, blowing, filling, and aeration-assisted pipeline, the gas injection volume flow rate and the slurry flow rate are adjusted; Performing ratio processing on the gas injection volume flow rate and the slurry flow rate to obtain gas-slurry relationship parameters; comparing the gas-slurry relationship parameter with a preset parameter range; When the gas-slurry relationship parameter is within the preset parameter range, the slurry delivery pressure of the dredging, blowing, filling, and aeration boosting pipeline is temporarily not adjusted in real time; When the gas-slurry relationship parameter is not within the preset parameter range, the gas-liquid mixing efficiency coefficient currently used for the reaction gas distribution uniformity is retrieved; Performing ratio processing on the gas-slurry relationship parameter and a preset parameter range to obtain a gas-slurry parameter proportional coefficient, and performing normalization processing on the gas-slurry parameter proportional coefficient to obtain the normalized gas-slurry parameter proportional coefficient; The normalized air-slurry parameter proportional coefficient is compared with the gas-liquid mixing efficiency coefficient, and the slurry delivery pressure of the dredging, blowing, filling and aeration-assisted pipeline is adjusted according to the comparison result of the normalized air-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient.

2. The dredging, blowing, filling, and aeration-assisted pipeline slurry conveying pressure regulating system according to claim 1 is characterized in that: According to the comparison result of the normalized gas-slurry parameter ratio coefficient and the gas-liquid mixing efficiency coefficient, the slurry delivery pressure of the dredging, blowing, filling and aeration boosting pipeline is adjusted, including: When the difference between the normalized gas-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient does not exceed the preset difference ratio, the normalized gas-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient are used to adjust the slurry delivery pressure in the dredging, blowing, filling and aeration boosting pipeline; When the difference between the normalized gas-slurry parameter proportional coefficient and the gas-liquid mixing efficiency coefficient exceeds a preset difference ratio, the current slurry density and air density are retrieved; Performing ratio processing on the current slurry density and air density to obtain a density coefficient; Comparing the density coefficient with the gas-liquid mixing efficiency coefficient, taking the coefficient parameter with the larger coefficient value between the density coefficient and the gas-liquid mixing efficiency coefficient as the first coefficient, and taking the coefficient parameter with the smaller coefficient value between the density coefficient and the gas-liquid mixing efficiency coefficient as the second coefficient; Retrieving the current gas injection volume flow rate and the slurry flow rate, and normalizing the current gas injection volume flow rate and the slurry flow rate to obtain the normalized gas injection volume flow rate and the slurry flow rate; The first coefficient and the second coefficient are combined with the normalized gas injection volume flow rate and the slurry flow rate to adjust the slurry delivery pressure of the dredging, blowing, filling and aeration boosting pipeline.

3. The dredging, blowing, filling, and aeration-assisted pipeline slurry conveying pressure regulating system according to claim 1 is characterized in that: Analyze and identify the characteristic data of slurry transportation in dredging, filling and aeration-assisted pipelines, including: Deploy the mathematical model for predicting the slurry delivery pressure of dredged, blown, and aerated pipelines. Deploy the mathematical model in the actual slurry delivery pressure prediction environment. The slurry transportation characteristic data of the dredged blowing, filling and aeration-assisted pipeline are input into the mathematical model for predicting the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline. Based on the mathematical model for predicting the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline, the slurry transportation characteristic data of the dredged blowing, filling and aeration-assisted pipeline are analyzed and identified, and the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline is effectively predicted, thereby determining the prediction result of the slurry transportation pressure of the dredged blowing, filling and aeration-assisted pipeline.

4. The dredging, blowing, filling, and aeration-assisted pipeline slurry conveying pressure regulating system according to claim 1 is characterized in that: Evaluate the predictive performance of a mathematical model for predicting slurry delivery pressure in dredged fill and aerated pipelines, including: The test set is input into the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, and aerated pipelines to determine whether the deep learning-based mathematical model can achieve the expected effect of effectively predicting the slurry delivery pressure of dredged, blown, and aerated pipelines. When the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines cannot achieve the expected effect of effectively predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines, the parameters of the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines are continuously adjusted, and the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines is iteratively optimized until the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines can achieve the expected effect of effectively predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines, thereby determining the optimal mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines.

5. The slurry conveying pressure regulating system for dredging, blowing, filling and aerating pipeline according to claim 1 is characterized in that: Construct a mathematical model for predicting slurry delivery pressure in dredging, filling, and aeration-assisted pipelines, including: Collect historical data on slurry transportation in dredging, blowing, filling, and aeration-assisted pipelines, and divide the collected historical data into training sets and test sets; Based on deep learning technology, a training set is used to train the deep learning model. The deep learning model can autonomously learn the prediction behavior of slurry delivery pressure in dredged, blown, filled, and aerated pipelines from the training set, and effectively predict the slurry delivery pressure in dredged, blown, filled, and aerated pipelines. Thus, a mathematical model for predicting slurry delivery pressure in dredged, blown, filled, and aerated pipelines based on deep learning is determined. The deep learning-based mathematical model for predicting slurry delivery pressure in dredged, blown, and aerated pipelines was tested based on the test set to evaluate the prediction performance of the model and determine the model test evaluation results. According to the model test evaluation results, the deep learning-based mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines is optimized to determine the optimal mathematical model for predicting the slurry delivery pressure of dredged, blown, filled, and aerated pipelines.

6. The slurry conveying pressure regulating system for dredging, blowing, filling and aerating pipeline according to claim 1 is characterized in that: Collect real-time data on slurry transport in dredging, filling, and aeration-assisted pipelines, including: Compressed gas is generated by an air compressor and injected into the mud discharge pipe through an ejector. Based on the intelligent data collection equipment, the pipeline diameter, pipeline length, pipeline roughness, slurry concentration, gas injection pressure, gas injection volume flow, slurry flow, slurry flow rate, slurry flow rate, slurry resistance and slurry pressure drop during the slurry transportation process of the dredging, blowing, filling and aeration-assisted pipeline are monitored in real time, and real-time data of slurry transportation in the dredging, blowing, filling and aeration-assisted pipeline are collected.

7. The slurry conveying pressure regulating system for dredging, blowing, filling and aerating pipeline according to claim 1 is characterized in that: Processing of real-time data of slurry transportation in dredging, filling and aeration-assisted pipelines, including: Clean the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines to remove noise from the data and reduce the interference of noise on the pressure prediction of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines; Check the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines one by one, identify abnormal values ​​and missing values ​​in the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines, and process the identified abnormal values ​​and missing values; Evaluate the identified outliers and missing values ​​to determine their contribution to the prediction of slurry delivery pressure in dredging, filling, and aeration-assisted pipelines; When the outliers and missing values ​​have a high contribution to the prediction of slurry delivery pressure in dredging, filling and aeration-assisted pipelines, the outliers are corrected and the missing values ​​are filled; When the contribution of outliers and missing values ​​to the prediction of slurry delivery pressure in dredging, filling and aeration-assisted pipeline is low, the outliers and missing values ​​are deleted.

8. The slurry conveying pressure regulating system for dredging, blowing, filling and aerating pipeline according to claim 1 is characterized in that: Processing of real-time data of slurry transportation in dredging, filling and aeration-assisted pipelines, including: Normalize the real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines to remove the dimension differences in the real-time data and form standardized real-time data of slurry transportation in dredging, blowing, filling and aeration-assisted pipelines; Feature extraction is performed on the real-time data of slurry transportation in dredged blowing, filling and aeration-assisted pipelines. Feature vectors related to the pressure prediction of slurry transportation in dredged blowing, filling and aeration-assisted pipelines are extracted from the real-time data of slurry transportation in dredged blowing, filling and aeration-assisted pipelines. The extracted feature vectors are weightedly fused to form the feature data of slurry transportation in dredged blowing, filling and aeration-assisted pipelines.

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