Parameterized Modeling System and Method for Rake Head Flushing of Clay-Type Rake Head Excavators

Abstract

The present invention discloses a parameterized modeling system and method for the flushing water of a clay-type draghead excavator, relating to the technical field of excavators. In order to solve the problems that traditional draghead design often relies on empirical adjustment of flushing water parameters, lacks scientific theoretical guidance and parameterized modeling, resulting in unstable dredging quality, high energy consumption, fast wear, low excavation efficiency, etc.; through precise parameter input and soil property analysis, the best flushing water parameter configuration can be provided for the draghead, thereby improving the dredging efficiency, dynamically adjusting the flushing water volume and pressure, ensuring efficient soil cleaning and reducing soil adhesion under different soil conditions, reducing the cleaning and maintenance costs, the real-time monitoring and feedback system can respond in a timely manner to the changes in soil properties, predict soil changes and flushing water effects, improve the prediction accuracy and reliability of operations, precisely control the flushing water pressure and flow rate, can adapt to different types of soil, and improve the versatility and adaptability of the dredger.

Description

Technical Field

[0001] The present invention relates to the technical field of excavators, and particularly to a parameterized modeling system and method for the water flushing of the rake head of a clay-type rake head excavator. Background Art

[0002] In a viscous soil environment such as clay, the operation efficiency and wear resistance of the excavator rake head become crucial. Traditional rake head designs often rely on empirical adjustment of the water flushing parameters, depending on the experience and intuition of the operator, lacking scientific theoretical guidance and parameterized modeling, and it is difficult to accurately match the requirements of different working conditions, resulting in problems such as unstable dredging quality, high energy consumption, fast wear, and low excavation efficiency. Summary of the Invention

[0003] The purpose of the present invention is to provide a parameterized modeling system and method for the water flushing of the rake head of a clay-type rake head excavator, which can automatically adjust the water flushing parameters according to different soil characteristics and excavation requirements, significantly improve the excavation efficiency and reduce the blockage phenomenon, and based on numerical simulation, improve the accuracy and real-time performance of parameter calculation, so as to solve the problems raised in the above background art.

[0004] To achieve the above purpose, the present invention provides the following technical solutions.

[0005] A parameterized modeling system for the water flushing of the rake head of a clay-type rake head excavator, comprising:

[0006] A parameter input unit, which is used to input the fixed parameters and water flushing parameters of the rake head, determine the parameters of the high-pressure water pump, and obtain the mechanical parameters of the soil and the dredging operation parameters in real time based on sensors;

[0007] A soil characteristic analysis unit, which is used to calculate the behavior change of the soil under the action of water flushing according to the input mechanical parameters of the soil, extract key features based on the behavior change, and analyze the soil characteristics based on the extraction results;

[0008] A water flushing system modeling unit, which is used to establish a geometric model of the water flushing system according to the fixed parameters and water flushing parameters of the rake head, calculate the minimum water flushing volume and pressure at the nozzle in combination with the parameters of the high-pressure water pump and the pipeline characteristics, and dynamically adjust the water flushing volume and water flushing pressure according to the water flushing parameters of the rake head and the soil characteristic analysis results;

[0009] A water flushing simulation control unit, which is used to predict the injection pressure, velocity and soil change at the nozzle based on the dynamically adjusted water flushing volume and water flushing pressure, and adjust the water flushing parameters according to the real-time feedback data, including adjusting the water flushing volume of the wear-resistant block, optimizing the water flushing angle of the rake teeth, improving the water flushing mode of the movable cover, etc., as well as the adjustment suggestions for the high-pressure water flushing system.

[0010] Furthermore, the parameter input unit includes:

[0011] The draghead parameter input module is used to obtain the structural parameters of the actively input draghead, including the fixed parameters and flushing parameters of the draghead, obtain the rated speed of the high-pressure flush pump and the curve parameters at different speeds, as well as the working range and efficiency information of the high-pressure flush pump;

[0012] The attitude data input module is used to obtain the draghead attitude information and drag tooth load data through the sensors installed on the draghead, monitor the working state of the draghead, and ensure that the model more accurately reflects the actual situation;

[0013] The soil parameter input module is used to actively obtain the mechanical parameters of the soil and the corresponding dredging operation parameters based on the sensors.

[0014] Furthermore, the parameter input unit further includes:

[0015] Obtain the attitude information and drag tooth load data collected by the sensors, and perform quality inspection on the collected attitude information and drag tooth load data based on the correlation between the attitude information and the drag tooth load data to obtain qualified collected parameters;

[0016] Classify the qualified collected parameters to obtain equipment operation parameters and dredging operation parameters, where the equipment operation parameters include the draghead inclination angle, drag tooth angle, and temperature, and the dredging operation parameters include the actual draghead rotation speed, excavation depth, and tunneling speed parameters;

[0017] Establish a correlation operation parameter threshold based on the equipment performance characteristics, and judge whether the equipment operation state is within the correlation operation parameter threshold according to the equipment operation parameters. If so, judge that the equipment is operating normally; otherwise, judge that the equipment operation state is abnormal and give an alarm reminder.

[0018] Furthermore, the soil characteristic analysis unit includes:

[0019] The soil parameter processing module is used to extract the soil type and parameter threshold from the received soil mechanical parameters, and perform soil classification and characteristic evaluation based on the extraction results;

[0020] The flushing effect analysis module is used to simulate the behavior change of the soil under the action of flushing based on the soil mechanical parameters and flushing parameters, compare the change information of the mechanical properties of the soil before and after, and provide a theoretical basis for optimizing the flushing system;

[0021] The feature extraction and analysis module is used to extract key features based on the change information of the mechanical properties of the soil, obtain the behavior change law of the soil under the action of flushing, and provide guidance for the dynamic adjustment of the flushing parameters.

[0022] Furthermore, the flushing system modeling unit includes:

[0023] The flushing model construction module is used for:

[0024] Establish a geometric model of the flushing system based on the structural parameters of the drag head, integrate the parameters of the pipeline and the high-pressure flushing pump into the model, and calculate the flow state of the fluid in the pipeline and the nozzle;

[0025] Calculate the water flow distribution at different nozzle angles based on the dynamic simulation results of the geometric model, determine the nozzle angle, and determine the number of nozzles according to the size of the drag head and the flushing requirements;

[0026] Calculate the minimum pressure at the nozzle according to the parameters of the high-pressure flushing pump and the pressure loss, combined with the angle, number of nozzles and soil properties;

[0027] The model optimization output module is used to calculate the optimal flushing water volume and pressure at the nozzle according to the behavior change law of the soil under the action of flushing and the drag tooth load data, and output the optimized flushing parameters and configuration suggestions.

[0028] Furthermore, the flushing simulation control unit includes:

[0029] The correlation model construction module is used to construct a correlation model between the flushing parameters, soil properties and dredging operation parameters, and determine the interaction and influence between the flushing parameters, soil properties and dredging operation parameters;

[0030] The real-time control module is used to adjust the working state of the flushing system in real time according to the sensor data and the prediction results of the correlation model, and adjust the injection pressure, flow rate and angle of the nozzle;

[0031] The fault diagnosis module is used to monitor the system operation state, diagnose potential faults, and provide corresponding early warnings and maintenance suggestions.

[0032] Furthermore, the flushing simulation control unit also includes:

[0033] The adaptive adjustment module is used to compare the real-time dredging operation parameters with the preset dredging operation parameters according to the soil property analysis results, the output results of the flushing system modeling unit and the real-time feedback data of the sensor, and adjust the parameter configuration of the flushing system according to the comparison results;

[0034] The real-time feedback and correction module is used to input the real-time obtained feedback data into the flushing effect analysis module for flushing effect evaluation, and feedback the evaluation results to the adaptive adjustment module. The adaptive adjustment module corrects and updates the parameter configuration of the flushing system according to the real-time feedback data;

[0035] The visualization module is used to graphically display the operation state, parameter adjustment effect and fault diagnosis information of the flushing system to the operator, including real-time data monitoring, comparison before and after parameter adjustment, fault warning and equipment status indication, etc., to improve the intuitiveness and convenience of operation.

[0036] Further, the flushing simulation control unit further includes:

[0037] A first data time acquisition module, configured to monitor in real time the data change time corresponding to the change of the display element each time the visualization module makes a display element change, as the first data time, where the display element includes the operation state of the flushing system, the parameter adjustment effect, and the fault diagnosis information;

[0038] A second data time acquisition module, configured to extract in real time the display time when the visualization module displays the changed display element after the data change of the display element, as the second data time;

[0039] An element change display response duration acquisition module, configured to obtain the element change display response duration corresponding to the visualization module by using the first data time and the second data time;

[0040] A response duration stability coefficient acquisition module, configured to obtain a response duration stability coefficient for the element change display response duration corresponding to each display element change;

[0041] Wherein, the response duration stability coefficient is obtained through the following formula:

[0042]

[0043] Wherein, S represents the response duration stability coefficient; n represents the total number of data changes of the display element; T bi represents the standard deviation of the element change display response duration corresponding to x elements that change in the i-th display element change; T fmax represents the maximum value of the amplitude of the element change display response duration corresponding to x elements that change in the i-th display element change; C bi represents the standard deviation of the element change data volume corresponding to x elements that change in the i-th display element change; C fmax represents the maximum value of the difference in the element change data volume corresponding to x elements that change in the i-th display element change; T i represents the element change display response duration corresponding to the i-th display element change; T max and T min represent the maximum and minimum values of the element change display response duration corresponding to n display element changes; T v represents the average value of the element change display response duration corresponding to n display element changes;

[0044] An abnormal determination module, configured to determine whether there is an abnormality in the operation of the visualization module according to the response duration stability coefficient.

[0045] Further, the abnormal determination module includes:

[0046] A first comparison module for comparing the response duration stability coefficient with a preset response duration stability coefficient threshold;

[0047] A resource occupancy parameter acquisition module for extracting the resource occupancy parameters of the visualization module when the response duration stability coefficient is not lower than the preset response duration stability coefficient threshold, where the resource occupancy parameters include CPU occupancy rate and memory occupancy rate;

[0048] An operation evaluation coefficient acquisition module for obtaining an operation evaluation coefficient of the visualization module by combining the CPU occupancy rate and the memory occupancy rate with the response duration stability coefficient;

[0049] Wherein, the operation evaluation coefficient is obtained through the following formula:

[0050]

[0051] Wherein, Y represents the operation evaluation coefficient; S represents the response duration stability coefficient; n represents the total number of data changes of the display elements; P ci and P ni represent the CPU occupancy rate and the memory occupancy rate corresponding to the i-th display element change; R i represents the change delay rate generated corresponding to the i-th display element change; C yi represents the data redundancy ratio generated corresponding to the i-th display element change;

[0052] A second comparison module for comparing the operation evaluation coefficient with a preset operation evaluation coefficient threshold;

[0053] An abnormal determination and alarm module for determining that there is an abnormality in the operation of the visualization module and performing an abnormal alarm when the operation evaluation coefficient is lower than the preset operation evaluation coefficient threshold.

[0054] The present invention provides another technical solution, a parametric modeling method for the rake head flushing of a clay-type rake head excavator, including the following steps:

[0055] Step 1: Parameter input: An operator actively inputs the fixed parameters and flushing parameters of the rake head;

[0056] Step 2: Sensor data acquisition: Obtain the rated speed of the high-pressure flushing pump and the curve parameters at different speeds, as well as the working range and efficiency information of the high-pressure flushing pump through sensors. At the same time, obtain the mechanical parameters of the soil, the rake head attitude information, and the rake tooth load data;

[0057] Step 3: Soil property analysis: Extract the soil type and parameter thresholds from the received soil mechanical parameters, conduct soil classification and property evaluation, the analysis module simulates the behavioral changes of the soil under the flushing action, and extracts key features;

[0058] Step 4: Flushing system modeling: Based on the drag head parameters and the results of soil property analysis, establish a geometric dynamic model of the flushing system, calculate the nozzle layout and flushing water volume, output the optimized flushing parameters and configuration suggestions, and automatically adjust the parameter configuration of the flushing system;

[0059] Step 5: Flushing simulation control: Construct an association model between the flushing parameters, soil properties, and dredging operation parameters. Based on the prediction results and data feedback of the association model, adjust the working state of the flushing system in real time, diagnose potential faults, and provide early warnings and maintenance suggestions.

[0060] Compared with the prior art, the beneficial effects of the present invention are as follows

[0061] Through accurate parameter input and soil property analysis, the optimal flushing parameter configuration can be provided for the drag head, thereby improving the dredging efficiency, dynamically adjusting the flushing water volume and pressure to ensure efficient soil cleaning and reduce soil adhesion under different soil conditions, reducing the cleaning and maintenance costs. The real-time monitoring and feedback system can respond in a timely manner to changes in soil properties, predict soil changes and flushing effects, improve the prediction accuracy and reliability of the operation, reduce equipment failures caused by improper operation, precisely control the flushing pressure and flow rate, avoid equipment damage caused by excessive flushing pressure, and can adapt to different types of soil, improving the versatility and adaptability of the dredger. Description of the Drawings

[0062] Figure 1 It is a module diagram of the drag head flushing parametric modeling system for the clay-type drag head excavator of the present invention;

[0063] Figure 2 It is a flowchart of the drag head flushing parametric modeling method for the clay-type drag head excavator of the present invention. Detailed Embodiments

[0064] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0065] To solve the technical problems that traditional draghead designs often rely on empirical adjustment of flushing parameters, relying on the experience and intuition of operators, lacking scientific theoretical guidance and parametric modeling, and being difficult to precisely match the requirements of different working conditions, resulting in unstable dredging quality, high energy consumption, fast wear, low excavation efficiency, etc., please refer to Figure 1 , this embodiment provides the following technical solutions:

[0066] A parametric modeling system for the flushing of a draghead of a clay-type draghead excavator, comprising:

[0067] A parameter input unit, used to input the fixed parameters of the draghead (draghead size, drag tooth angle, wear-resistant block parameters, etc.) and flushing parameters (number of nozzles, nozzle position, nozzle angle, nozzle diameter, nozzle injection pressure, etc.), determine the parameters of the high-pressure flushing pump, that is, the curve parameters at the rated speed, and obtain the mechanical parameters of the soil (shear strength, cohesion, internal friction angle, permeability coefficient, etc. of clay or saturated sand) and dredging operation parameters in real time based on sensors, such as dredging depth, dredging speed, navigation speed, etc., including:

[0068] A draghead parameter input module, used to obtain the structural parameters of the actively input draghead, including the fixed parameters and flushing parameters of the draghead, obtain the rated speed of the high-pressure flushing pump and the curve parameters at different speeds, as well as the working range and efficiency information of the high-pressure flushing pump;

[0069] An attitude data input module, used to obtain attitude information such as draghead inclination angle and drag tooth angle and drag tooth load data through sensors installed on the draghead, monitor the working state of the draghead, and ensure that the model more accurately reflects the actual situation;

[0070] A soil parameter input module, used to actively obtain the mechanical parameters of the soil based on the sensors, as well as the corresponding dredging operation parameters, such as excavation depth and speed, and also includes parameters such as draghead rotation speed, draghead cylinder pressure, and wave compensator pressure;

[0071] A soil characteristic analysis unit, used to calculate the behavior changes of the soil under the action of flushing according to the input mechanical parameters of the soil, such as improved fluidity and reduced resistance, extract key features based on the behavior changes, and analyze the soil characteristics based on the extraction results, including:

[0072] A soil parameter processing module, used to extract the soil type and parameter thresholds from the received mechanical parameters of the soil, and classify and evaluate the soil characteristics based on the extraction results;

[0073] A flushing effect analysis module, used to simulate the behavior changes of the soil under the action of flushing based on the mechanical parameters of the soil and the flushing parameters, such as improved fluidity and reduced resistance, compare the change information of the mechanical characteristics of the soil before and after, and provide a theoretical basis for optimizing the flushing system;

[0074] The feature extraction and analysis module is used to extract key features based on the change information of the mechanical properties of the soil, such as the improvement degree of soil fluidity, the specific value of resistance reduction, etc., to obtain the behavioral change law of the soil under the flushing action, and provide guidance for the dynamic adjustment of the flushing parameters;

[0075] The flushing system modeling unit is used to establish a geometric model of the flushing system according to the fixed parameters of the rake head and the flushing parameters, calculate the minimum flushing water volume and pressure at the nozzle in combination with the parameters of the high-pressure flushing pump and the pipeline characteristics, so as to ensure effective cleaning and reduce wear, optimize the flushing layout, ensure that each rake tooth can receive sufficient flushing coverage, reduce soil adhesion, and dynamically adjust the flushing water volume and pressure according to the flushing parameters of the rake head and the analysis results of the soil characteristics;

[0076] The flushing simulation control unit is used to predict the injection pressure, velocity and soil changes at the nozzle based on the dynamically adjusted flushing water volume and pressure, and adjust the flushing parameters according to the real-time feedback data, including adjusting the flushing water volume of the wear-resistant block, optimizing the flushing angle of the rake teeth, improving the flushing mode of the movable cover, etc., as well as the adjustment suggestions for the high-pressure flushing system, such as adjusting the nozzle pressure, nozzle angle, flushing flow rate, etc., to ensure the best flushing effect.

[0077] In this embodiment, through precise parameter input and soil characteristic analysis, the best flushing parameter configuration can be provided for the rake head, thereby improving the dredging efficiency, dynamically adjusting the flushing water volume and pressure, ensuring efficient soil cleaning and reducing soil adhesion under different soil conditions, reducing the cleaning and maintenance costs, the real-time monitoring and feedback system can respond in a timely manner to the changes in soil characteristics, predict soil changes and flushing effects, improve the prediction accuracy and reliability of the operation, reduce equipment failures caused by improper operation, precisely control the flushing pressure and flow rate, avoid equipment damage caused by excessive flushing pressure, be able to adapt to different types of soil, and improve the versatility and adaptability of the dredger.

[0078] In this embodiment, the parameter input unit further includes:

[0079] Obtain the attitude information and rake tooth load data collected by the sensor, and perform quality inspection on the collected attitude information and rake tooth load data based on the association between the attitude information and the rake tooth load data to obtain qualified collected parameters;

[0080] Classify the qualified collected parameters to obtain equipment operation parameters and dredging operation parameters, where the equipment operation parameters include the rake head inclination angle, rake tooth angle and temperature, and the dredging operation parameters include the actual rake head rotation speed, excavation depth and tunneling speed parameters;

[0081] Based on the device performance characteristics, associated operating parameter thresholds are established. According to the device operating parameters, it is judged whether the device operating state is within the associated operating parameter thresholds. If so, it is judged that the device is operating normally; otherwise, it is judged that the device operating state is abnormal and an alarm reminder is given.

[0082] In this embodiment, by performing quality inspection on the attitude information and draghead load data collected by the sensors, the accuracy and reliability of the input data are ensured, reducing operation errors caused by data errors. The classification of device operating parameters and dredging operation parameters helps to more accurately understand the device state and operation efficiency. Based on the correlation analysis of attitude information and draghead load data, the operating state of the device can be monitored in real time, potential problems can be discovered in time, and it can be effectively judged whether the device operating state is normal, and an alarm reminder can be given in time to prevent the device from being damaged due to exceeding the safe operating range, improving the safety and efficiency of the entire dredging operation.

[0083] In this embodiment, the flushing system modeling unit includes:

[0084] The flushing model construction module is used for:

[0085] Establish a geometric model of the flushing system according to the structural parameters of the draghead, integrate the parameters of the pipeline and the high-pressure flushing pump into the model, and calculate the flow state of the fluid in the pipeline and the nozzle;

[0086] Based on the dynamic simulation results of the geometric model, calculate the water flow distribution at different nozzle angles, determine the nozzle angle, and determine the number of nozzles according to the draghead size and flushing requirements;

[0087] According to the parameters and pressure loss of the high-pressure flushing pump, combined with the angle, number of nozzles and soil characteristics, calculate the minimum pressure at the nozzle;

[0088] The model optimization output module is used to calculate the optimal flushing water volume and pressure at the nozzle according to the behavior change law of the soil under flushing action and the draghead load data, and output the optimized flushing parameters and configuration suggestions.

[0089] In this embodiment, by accurately calculating the nozzle angle and number, the water flow distribution is ensured to be uniform, the flushing efficiency is improved, the soil adhesion is reduced, the nozzle configuration is determined according to the draghead size and flushing requirements, ensuring that each drag tooth is effectively covered by flushing, reducing wear, ensuring that the pressure at the nozzle meets the operation requirements, preventing the decline of operation efficiency or device damage caused by insufficient pressure, dynamically adjusting the flushing parameters according to different soil characteristics and operation conditions, enhancing the adaptability of the system to complex environments, providing the optimal flushing water volume and pressure, improving the accuracy and efficiency of the dredging operation, and adjusting the flushing parameters in real time according to the data to ensure the continuity and stability of the operation.

[0090] In this embodiment, the flushing simulation control unit includes:

[0091] An associated model construction module, configured to construct an association model between the flushing parameters, soil properties, and dredging operation parameters, and determine the interaction and influence between the flushing parameters, soil properties, and dredging operation parameters;

[0092] A real-time control module, configured to adjust the working state of the flushing system in real time according to the sensor data and the prediction results of the association model, and regulate the injection pressure, flow rate, angle, etc. of the nozzle;

[0093] A fault diagnosis module, configured to monitor the system operation state, diagnose potential faults, and provide corresponding early warnings and maintenance suggestions;

[0094] An adaptive adjustment module, configured to compare the real-time dredging operation parameters with the preset dredging operation parameters according to the soil property analysis results, the output results of the flushing system modeling unit, and the real-time feedback data of the sensor, and adjust the parameter configuration of the flushing system (such as nozzle pressure, angle, flow rate, etc.) according to the comparison results. This kind of adaptive adjustment can ensure that the flushing system always maintains the best working state under different soil types and operating conditions;

[0095] A real-time feedback and correction module, configured to input the real-time obtained feedback data into the flushing effect analysis module for flushing effect evaluation (such as soil cleaning degree, change in draghead load, etc.), and feedback the evaluation results to the adaptive adjustment module. The adaptive adjustment module corrects and updates the parameter configuration of the flushing system according to the real-time feedback data to ensure the accuracy and reliability of the model;

[0096] A visualization module, configured to display the operation state, parameter adjustment effect, and fault diagnosis information of the flushing system to the operator in a graphical manner, including real-time data monitoring, comparison before and after parameter adjustment, fault warning, and equipment status indication, etc., to improve the intuitiveness and convenience of operation.

[0097] In this embodiment, by obtaining the interaction and influence between various parameters, and using the sensor data and the prediction results of the association model, the immediate adjustment of the working state of the flushing system is realized, ensuring that parameters such as the injection pressure, flow rate, and angle of the nozzle can adapt to the current operating conditions at any time, improving the operation efficiency and effect. The established adaptive mechanism enables the flushing system to automatically optimize its parameter configuration under different soil types and operating conditions, maintain the best working state, significantly improve the operation efficiency of the clay-type draghead excavator, reduce soil adhesion, lower energy consumption and wear. At the same time, through fault warning and maintenance support, equipment failures and downtime are reduced, and the operation cost is further reduced.

[0098] Specifically, the flushing simulation control unit further includes:

[0099] The first data time acquisition module is used to monitor in real time the data change time corresponding to the change of the display element each time the visualization module makes a display element change, and use it as the first data time, where the display element includes the operating state of the flushing system, the parameter adjustment effect, and the fault diagnosis information;

[0100] The second data time acquisition module is used to extract in real time the display time when the visualization module displays the changed display element after the data of the display element changes, and use it as the second data time;

[0101] The element change display response duration acquisition module is used to obtain the element change display response duration corresponding to the visualization module by using the first data time and the second data time;

[0102] The response duration stability coefficient acquisition module is used to obtain the response duration stability coefficient for the element change display response duration corresponding to each change of the display element;

[0103] Among them, the response duration stability coefficient is obtained through the following formula:

[0104]

[0105] Among them, S represents the response duration stability coefficient; n represents the total number of data changes of the display element; T bi represents the standard deviation of the element change display response duration corresponding to the change of x elements corresponding to the i-th display element change; T fmax represents the maximum value of the amplitude of the element change display response duration corresponding to the change of x elements corresponding to the i-th display element change; C bi represents the standard deviation of the element change data volume corresponding to the change of x elements corresponding to the i-th display element change; C fmax represents the maximum value of the difference in the element change data volume corresponding to the change of x elements corresponding to the i-th display element change; T i represents the element change display response duration corresponding to the i-th display element change; T max and T min represent the maximum and minimum values of the element change display response duration corresponding to n display element changes; T v represents the average value of the element change display response duration corresponding to n display element changes;

[0106] The abnormal determination module is used to determine whether there is an abnormality in the operation of the visualization module according to the response duration stability coefficient.

[0107] The technical effects of the above technical solution are as follows: Through the first data time acquisition module and the second data time acquisition module, it is possible to monitor in real time the data change times of the display elements (such as operating status, parameter adjustment effects, and fault diagnosis information) in the flushing system visualization module and the display times after these changes are shown. This ensures that the system can quickly capture data changes and respond. The element change display response duration acquisition module can calculate the response duration of the visualization module to the data changes of the display elements, which is an important indicator for evaluating system performance. The response duration stability coefficient acquisition module calculates through the above formula, comprehensively considering multiple factors such as the standard deviation of the element change display response duration, the maximum value, the standard deviation of the data volume, and the maximum difference value, as well as the maximum value, minimum value, and average value of the overall response duration, so as to comprehensively and accurately evaluate the stability of the visualization module operation. The abnormal determination module can determine whether there is an abnormality in the operation of the visualization module according to the response duration stability coefficient. This helps to promptly discover and solve potential problems, preventing operation errors or data errors caused by system instability. By continuously monitoring and analyzing the response duration stability coefficient, key factors affecting system performance can be identified, and targeted optimization and improvement can be carried out. For example, the data processing process can be adjusted, the algorithm can be optimized, or the hardware configuration can be enhanced, etc., to improve the overall performance and stability of the system. A stable visualization module can ensure that users can obtain information such as the operating status and parameter adjustment effects of the flushing system in real time and accurately, thereby enhancing the user's operation experience and satisfaction.

[0108] In summary, through means such as real-time monitoring, performance evaluation, abnormal detection, and optimization and improvement, the above technical solution effectively improves the stability and performance of the flushing system visualization module, providing a strong guarantee for the safe and efficient operation of the system.

[0109] Specifically, the abnormal determination module includes:

[0110] The first comparison module is used to compare the response duration stability coefficient with a preset response duration stability coefficient threshold;

[0111] The resource occupancy parameter acquisition module is used to extract the resource occupancy parameters of the visualization module when the response duration stability coefficient is not lower than the preset response duration stability coefficient threshold, where the resource occupancy parameters include CPU occupancy rate and memory occupancy rate;

[0112] The operation evaluation coefficient acquisition module is used to obtain the operation evaluation coefficient of the visualization module by combining the CPU occupancy rate and the memory occupancy rate with the response duration stability coefficient;

[0113] Among them, the operation evaluation coefficient is obtained through the following formula:

[0114]

[0115] Among them, Y represents the operation evaluation coefficient; S represents the response duration stability coefficient; n represents the total number of data changes of the display elements; P ci and P ni represent the CPU occupancy rate and memory occupancy rate corresponding to the change of the display element in the i-th time; R i represents the change delay rate generated corresponding to the change of the display element in the i-th time; C yi represents the data redundancy ratio generated corresponding to the change of the display element in the i-th time;

[0116] A second comparison module is configured to compare the operation evaluation coefficient with a preset operation evaluation coefficient threshold;

[0117] An abnormality determination and alarm module is configured to determine that there is an abnormality in the operation of the visualization module and perform an abnormality alarm when the operation evaluation coefficient is lower than the preset operation evaluation coefficient threshold.

[0118] The technical effects of the above technical solution are as follows: Through the first comparison module, comparing the response duration stability coefficient with a preset threshold can initially determine whether the operation state of the visualization module is stable. This step provides a basis for subsequent abnormality determination. When the response duration stability coefficient does not meet the requirements, the resource occupancy parameter acquisition module extracts key resource occupancy parameters such as the CPU occupancy rate and memory occupancy rate of the visualization module. These parameters are important indicators for evaluating the system performance and help to deeply understand the operation state of the system. The operation evaluation coefficient acquisition module calculates the operation evaluation coefficient through the above formula using multiple factors such as the CPU occupancy rate, memory occupancy rate, response duration stability coefficient, change delay rate, and data redundancy ratio. This coefficient can comprehensively and accurately reflect the overall operation status of the visualization module. The second comparison module compares the operation evaluation coefficient with a preset operation evaluation coefficient threshold. By setting different thresholds, the abnormality determination criteria can be flexibly adjusted according to actual needs to meet the application requirements in different scenarios. When the abnormality determination and alarm module detects that the operation evaluation coefficient is lower than the preset threshold, it immediately determines that there is an abnormality in the operation of the visualization module and performs an abnormality alarm. This function can timely detect and handle potential problems, prevent the problems from further deteriorating, and ensure the stable operation of the system. By continuously monitoring the operation evaluation coefficient and abnormality alarm information, problems and bottlenecks in the operation of the visualization module can be timely discovered and solved. This helps to optimize the system configuration, improve the system performance, and reduce the maintenance cost. A stable visualization module can ensure that users can obtain the required information in real time and accurately, improving the user's operation experience and satisfaction. At the same time, timely abnormality alarm and handling can also enhance the user's trust and dependence on the system.

[0119] In summary, through means such as precise anomaly detection, comprehensive performance evaluation, integrated operation assessment, flexible threshold setting, timely anomaly alarm, and optimized system maintenance, the technical solution effectively improves the stability and performance of the visualization module, providing a strong guarantee for the safe and efficient operation of the system.

[0120] The present invention provides another technical solution, a parametric modeling method for the rake head flushing of a clay-type rake head excavator, comprising the following steps:

[0121] Step 1: Parameter input: The operator actively inputs the fixed parameters and flushing parameters of the rake head.

[0122] Step 2: Sensor data acquisition: Obtain the rated speed and curve parameters at different speeds of the high-pressure flushing pump through sensors, as well as the working range and efficiency information of the high-pressure flushing pump. At the same time, obtain the mechanical parameters of the soil, attitude information such as the rake head inclination angle and rake tooth angle, and rake tooth load data.

[0123] Step 3: Soil characteristic analysis: Extract the soil type and parameter thresholds from the received soil mechanical parameters, conduct soil classification and characteristic evaluation, and the analysis module simulates the behavior changes of the soil under the action of flushing water and extracts key features.

[0124] Step 4: Flushing system modeling: Based on the rake head parameters and the results of soil characteristic analysis, establish a geometric dynamic model of the flushing system, calculate the nozzle layout and flushing water volume, output optimized flushing parameters and configuration suggestions, and automatically adjust the parameter configuration of the flushing system.

[0125] Step 5: Flushing simulation control: Construct an association model between the flushing parameters, soil characteristics, and dredging operation parameters. Based on the prediction results and data feedback of the association model, adjust the working state of the flushing system in real time, diagnose potential faults, and provide early warning and maintenance suggestions.

[0126] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, making equivalent substitutions or changes, should be covered by the protection scope of the present invention.

Claims

1. The drag head flushing parameterized modeling system of the clay type drag head excavator is characterized by: include: Parameter input unit, used to input fixed parameters and flushing parameters of the rake head, determine the parameters of the high-pressure flushing pump, and obtain the mechanical parameters of the soil and dredging operation parameters in real time based on sensors; A soil property analysis unit is used to calculate the behavior change of the soil under the action of water according to the input soil mechanical parameters, extract key features based on the behavior change, and analyze the soil properties based on the extraction results; The flushing system modeling unit is used to establish a flushing system geometric model according to the fixed parameters of the rake head and the flushing parameters, calculate the minimum flushing volume and pressure at the nozzle in combination with the high-pressure flushing pump parameters and pipeline characteristics, and dynamically adjust the flushing volume and flushing pressure according to the flushing parameters of the rake head and the soil characteristic analysis results; A flushing simulation control unit, which is used to predict the jet pressure, velocity and soil changes at the nozzle based on the dynamically adjusted flushing volume and flushing pressure, and adjust the flushing parameters according to the real-time feedback data; Flush simulation control unit, including: A first data moment acquisition module is used to monitor in real time the data change moment of the display element corresponding to each display element change performed by the visualization module as the first data moment, wherein the display element includes the operating status of the flushing system, parameter adjustment effect and fault diagnosis information; A second data moment acquisition module is used to extract in real time the display moment when the visualization module displays the changed display element after the data of the display element changes, as the second data moment; An element change display response duration acquisition module, used to acquire an element change display response duration corresponding to a visualization module using the first data moment and the second data moment; A response time stability coefficient acquisition module, used for acquiring a response time stability coefficient from the element change display response time corresponding to each display element change; An abnormality determination module, used for determining whether there is an abnormality in the operation of the visualization module according to the response time stability coefficient; The abnormality determination module includes: A first comparison module, used for comparing the response time stability coefficient with a preset response time stability coefficient threshold; A resource occupancy parameter acquisition module, used for extracting resource occupancy parameters of the visualization module when the response duration stability coefficient is not lower than a preset response duration stability coefficient threshold, wherein the resource occupancy parameters include CPU occupancy rate and memory occupancy rate; An operation evaluation coefficient acquisition module, used to obtain an operation evaluation coefficient of a visualization module by using the CPU occupancy rate and the memory occupancy rate in combination with a response time stability coefficient; A second comparison module, used for comparing the operation evaluation coefficient with a preset operation evaluation coefficient threshold; The abnormality determination and alarm module is used to determine that the operation of the visualization module is abnormal and issue an abnormality alarm when the operation evaluation coefficient is lower than a preset operation evaluation coefficient threshold.

2. The drag head flushing parameterized modeling system of a clay type drag head excavator according to claim 1, characterized in that: Parameter input unit, including: The rake head parameter input module is used to obtain the structural parameters of the rake head that are actively input, including the fixed parameters and flushing parameters of the rake head, the rated speed of the high-pressure flushing pump and various curve parameters at different speeds, as well as the working range and efficiency information of the high-pressure flushing pump; The posture data input module is used to obtain the posture information of the rake head and the load data of the rake teeth through the sensor installed on the rake head; The soil parameter input module is used to actively obtain the mechanical parameters of the soil and the corresponding dredging operation parameters based on the sensor.

3. The drag head flushing parameterized modeling system of a clay type drag head excavator as claimed in claim 2, characterized in that: The parameter input unit also includes: Acquire the posture information and rake tooth load data collected by the sensor, and based on the association between the posture information and the rake tooth load data, perform quality inspection on the collected posture information and rake tooth load data to obtain qualified collection parameters; Classifying the qualified collected parameters to obtain equipment operation parameters and dredging operation parameters, wherein the equipment operation parameters include rake head inclination angle, rake tooth angle and temperature, and the dredging operation parameters include actual rake head speed, excavation depth and excavation speed parameters; Based on the performance characteristics of the equipment, an associated operating parameter threshold is established, and whether the equipment operating status is within the associated operating parameter threshold is determined according to the equipment operating parameters. If so, it is determined that the equipment is operating normally. Otherwise, it is determined that the equipment operating status is abnormal and an alarm is issued.

4. The drag head flushing parameterized modeling system of a clay type drag head excavator as claimed in claim 3, characterized in that: Soil property analysis unit, including: A soil parameter processing module is used to extract soil type and parameter threshold from the received soil mechanical parameters, and to classify and evaluate soil characteristics based on the extracted results; The flushing effect analysis module is used to simulate the behavior changes of soil under the action of flushing water based on soil mechanical parameters and flushing water parameters, and compare the mechanical property change information of the soil before and after; The feature extraction and analysis module is used to extract key features based on the change information of the mechanical properties of the soil and obtain the behavior change rules of the soil under the action of water.

5. The drag head flushing parameterized modeling system of a clay type drag head excavator as claimed in claim 4, characterized in that: Flush system modeling unit, including: Flush model building blocks for: The geometric model of the flushing system is established according to the structural parameters of the rake head, the parameters of the pipeline and the high-pressure flushing pump are integrated into the model, and the flow state of the fluid in the pipeline and the nozzle is calculated; Calculate the water flow distribution under different nozzle angles based on the dynamic simulation results of the geometric model, determine the nozzle angle, and determine the number of nozzles according to the rake head size and flushing requirements; According to the parameters and pressure loss of the high-pressure flushing pump, combined with the angle, number and soil characteristics of the nozzle, calculate the minimum pressure at the nozzle; The model optimization output module is used to calculate the optimal water flow and pressure at the nozzle according to the behavior changes of the soil under water flushing and the rake tooth load data, and output the optimized water flushing parameters and configuration suggestions.

6. The drag head flushing parameterized modeling system of a clay drag head excavator as claimed in claim 5, characterized in that: Flush simulation control unit, including: A correlation model building module is used to build a correlation model between flushing parameters and soil characteristics and dredging operation parameters, and determine the interaction and influence between flushing parameters and soil characteristics and dredging operation parameters; A real-time control module is used to adjust the working state of the flushing system in real time based on sensor data and the prediction results of the associated model; The fault diagnosis module is used to monitor the system operation status, diagnose potential faults, and provide corresponding early warnings and maintenance suggestions.

7. The drag head flushing parameterized modeling system of a clay type drag head excavator as claimed in claim 6, characterized in that: The flush simulation control unit also includes: An adaptive adjustment module is used to compare the real-time dredging operation parameters with the preset dredging operation parameters according to the soil characteristic analysis results, the output results of the flushing system modeling unit and the real-time feedback data of the sensor, and adjust the parameter configuration of the flushing system according to the comparison results; The real-time feedback and correction module is used to input the feedback data obtained in real time into the flushing effect analysis module to evaluate the flushing effect, and feed back the evaluation results to the adaptive adjustment module. The adaptive adjustment module corrects and updates the parameter configuration of the flushing system according to the real-time feedback data; The visualization module is used to display the operating status of the flushing system, parameter adjustment effects and fault diagnosis information to the operator in a graphical manner.

8. The drag head flushing parameterized modeling system of a clay drag head excavator according to claim 7, characterized in that: The response time stability coefficient is obtained by the following formula: ； Among them, S represents the stability coefficient of response time; n represents the total number of data changes of the display element; T bi T represents the standard deviation of the element change display response time corresponding to the change of x elements corresponding to the i-th display element change; fmax Indicates the maximum value of the element change display response duration corresponding to the change of x elements corresponding to the i-th display element change; C bi represents the standard deviation of the element change data corresponding to the change of x elements corresponding to the change of the i-th displayed element; C fmax Indicates the maximum difference in the amount of element change data corresponding to the change in x elements corresponding to the change in the i-th display element; T i T represents the element change display response time corresponding to the i-th display element change; max and T min Indicates the maximum and minimum element change display response duration corresponding to n display element changes; T v Indicates the average element change display response duration corresponding to n display element changes.

9. The drag head flushing parameterized modeling system of a clay drag head excavator as claimed in claim 8, characterized in that: The operation evaluation coefficient is obtained by the following formula: ； Among them, Y represents the operation evaluation coefficient; S represents the response time stability coefficient; n represents the total number of data changes of the display element; P ci and P ni represents the CPU usage and memory usage corresponding to the change of the i-th display element; R i represents the change delay rate corresponding to the change of the i-th display element; C yi Indicates the data redundancy ratio corresponding to the i-th display element change.

10. A method for parameterized modeling of a water-flushing drag head of a clay-type drag head excavator, which is implemented based on the parameterized modeling system for water-flushing drag head of a clay-type drag head excavator according to claim 9, characterized in that: The following steps are involved: Step 1: Parameter input: The operator actively inputs the fixed parameters and flushing parameters of the rake head; Step 2: Sensor data acquisition: The rated speed of the high-pressure flushing pump and the curve parameters at different speeds, as well as the working range and efficiency information of the high-pressure flushing pump are acquired through the sensor. At the same time, the mechanical parameters of the soil, the attitude information of the rake head and the load data of the rake teeth are acquired; Step 3: Soil property analysis: Extract soil type and parameter thresholds from the received soil mechanical parameters, perform soil classification and property evaluation, and the analysis module simulates the behavior changes of soil under the action of water flushing to extract key features; Step 4: Modeling of flushing system: According to the analysis results of rake head parameters and soil characteristics, a geometric dynamic model of the flushing system is established, the nozzle layout and flushing volume are calculated, the optimized flushing parameters and configuration suggestions are output, and the flushing system parameter configuration is automatically adjusted; Step 5: Flushing simulation control: Build a correlation model between flushing parameters and soil characteristics and dredging operation parameters. Based on the prediction results and data feedback of the correlation model, adjust the working status of the flushing system in real time, diagnose potential faults, and provide early warnings and maintenance suggestions.

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