Rake head flushing parametric modeling system and method for clay type rake head excavator

Abstract

The invention discloses a rake head flushing parametric modeling system and method for a clay type rake head excavator, and relates to the technical field of excavators. In order to solve the problems of unstable dredging quality, high energy consumption, quick abrasion, low digging efficiency and the like caused by the fact that the traditional drag head design often depends on experience to adjust flushing parameters and lacks scientific theoretical guidance and parametric modeling. Through accurate parameter input and soil characteristic analysis, the optimal flushing parameter configuration can be provided for the drag head, so that the dredging efficiency is improved, the flushing amount and pressure are dynamically adjusted, it is ensured that efficient soil cleaning and soil adhesion reduction can be achieved under different soil conditions, and the cleaning and maintenance cost is reduced; the real-time monitoring and feedback system can respond to the change of soil characteristics in time, predict the soil change and the flushing effect, improve the prediction accuracy and reliability of operation, accurately control the flushing pressure and flow, adapt to different types of soil and improve the universality and adaptability of the dredger.

Description

Technical Field

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

[0002] In sticky soil environments such as clay, the operating efficiency and wear resistance of the excavator rake head become the key. Traditional rake head design often relies on experience to adjust the flushing parameters, relying on the operator's experience and intuition, lacking scientific theoretical guidance and parametric modeling, and it is difficult to accurately match the requirements of different working conditions, resulting in unstable dredging quality, high energy consumption, rapid 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 a clay-type water flushing excavator, which automatically adjusts the water flushing parameters according to different soil characteristics and excavation requirements, significantly improves the excavation efficiency and reduces blockage. Based on numerical simulation, it improves the accuracy and real-time performance of parameter calculation to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions: The drag head flushing parametric modeling system of the clay drag head excavator includes: 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; 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 volume and flushing pressure, and adjust the flushing parameters according to the real-time feedback data, including adjusting the flushing volume of the wear-resistant block, optimizing the flushing angle of the rake teeth, improving the active hood flushing mode, etc., as well as adjustment suggestions for the high-pressure flushing system.

[0005] Furthermore, the parameter input unit includes: 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 sensors installed on the rake head, monitor the working status of the rake head, and ensure that the model reflects the actual situation more accurately; 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.

[0006] Furthermore, the parameter input unit further 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.

[0007] Furthermore, the soil property analysis unit includes: 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 based on soil mechanical parameters and flushing parameters, compare the change information of soil mechanical properties before and after, and provide a theoretical basis for optimizing the flushing system; 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 rules of the soil under the action of water flushing, and provide guidance for the dynamic adjustment of water flushing parameters.

[0008] Furthermore, the flushing system modeling unit comprises: 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.

[0009] Furthermore, the flushing simulation control unit comprises: 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 and adjust the spray pressure, flow rate and angle of the nozzle according to the sensor data and the prediction results of the correlation model; The fault diagnosis module is used to monitor the system operation status, diagnose potential faults, and provide corresponding early warnings and maintenance suggestions.

[0010] Furthermore, the flushing simulation control unit further 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, 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.

[0011] Furthermore, the flushing simulation control unit further includes: 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; The response time stability coefficient is obtained by the following formula:

[0012] 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 It indicates the average element change display response duration corresponding to n display element changes; The abnormality determination module is used to determine whether there is an abnormality in the operation of the visualization module according to the response time stability coefficient.

[0013] Furthermore, 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; The operation evaluation coefficient is obtained by the following formula:

[0014] 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 nirepresents 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 change of the i-th display element; 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.

[0015] The present invention provides another technical solution, a drag head flushing parameterized modeling method of a clay type drag head excavator, comprising the following steps: 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.

[0016] Compared with the prior art, the present invention has the following beneficial effects: Through precise parameter input and soil property analysis, the optimal flushing parameter configuration can be provided for the rake head, thereby improving dredging efficiency, dynamically adjusting the flushing volume and pressure, ensuring efficient soil cleaning and reducing soil adhesion under different soil conditions, and reducing cleaning and maintenance costs. The real-time monitoring and feedback system can respond to changes in soil properties in a timely manner, predict soil changes and flushing effects, improve the prediction accuracy and reliability of operations, reduce equipment failures due to improper operation, accurately control flushing pressure and flow, avoid equipment damage due to excessive flushing pressure, and can adapt to different types of soils, improving the versatility and adaptability of the dredger. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a module diagram of the drag head flushing parameterized modeling system of the clay type drag head excavator of the present invention; Figure 2 The present invention is a flow chart of the parameterized modeling method for water flushing of the drag head of a clay-type drag head excavator. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0019] In order to solve the technical problems that traditional rake head design often relies on experience to adjust flushing parameters, relies on the experience and intuition of operators, lacks scientific theoretical guidance and parametric modeling, and is difficult to accurately match the needs of different working conditions, resulting in unstable dredging quality, high energy consumption, rapid wear, and low excavation efficiency, please refer to Figure 1 , this embodiment provides the following technical solutions: The drag head flushing parametric modeling system of the clay drag head excavator includes: The parameter input unit is used to input fixed parameters of the rake head (rake head size, rake tooth angle, wear block parameters, etc.) and flushing parameters (number of nozzles, nozzle position, nozzle angle, nozzle diameter, nozzle spray 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 such as dredging depth, dredging speed, ship speed, etc. in real time based on sensors, 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 attitude data input module is used to obtain attitude information such as the rake head inclination angle and rake tooth angle and rake tooth load data through the sensors installed on the rake head, monitor the working status of the rake head, and ensure that the model reflects the actual situation more accurately; A soil parameter input module is used to actively obtain soil mechanical parameters based on the sensor, as well as corresponding dredging operation parameters, such as digging depth and speed, and also includes parameters such as rake head speed, rake head cylinder pressure, wave compensator pressure, etc.; The soil property analysis unit is used to calculate the behavior changes of soil under the action of water, such as improved fluidity and reduced resistance, based on the input soil mechanical parameters. It extracts key features based on the behavior changes and analyzes soil properties based on the extracted results, 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 flushing based on soil mechanical parameters and flushing parameters, such as improved fluidity and reduced resistance, and compare the mechanical property change information of the soil before and after to provide a theoretical basis for optimizing the flushing system; The feature extraction and analysis module is used to extract key features based on the change information of soil mechanical properties, such as the degree of improvement of soil fluidity, the specific value of resistance reduction, etc., to obtain the behavior change law of soil under the action of flushing water and provide guidance for the dynamic adjustment of flushing parameters; The flushing system modeling unit is used to establish the 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 to ensure effective cleaning and reduce wear, optimize the flushing layout to ensure that each rake tooth can get enough flushing coverage to reduce soil adhesion, and dynamically adjust the flushing volume and flushing pressure according to the flushing parameters of the rake head and the analysis results of soil characteristics; The flushing simulation control unit is used to predict the injection pressure, speed 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, including adjusting the flushing volume of the wear-resistant block, optimizing the rake tooth flushing angle, improving the movable hood flushing mode, etc., as well as adjustment suggestions for the high-pressure flushing system, such as adjusting the nozzle pressure, nozzle angle, flushing flow, etc., to ensure the best flushing effect.

[0020] In this embodiment, through precise parameter input and soil property analysis, the optimal flushing parameter configuration can be provided for the rake head, thereby improving dredging efficiency, dynamically adjusting the flushing volume and pressure, ensuring efficient soil cleaning and reducing soil adhesion under different soil conditions, reducing cleaning and maintenance costs, and the real-time monitoring and feedback system can respond to changes in soil properties in a timely manner, predict soil changes and flushing effects, improve the prediction accuracy and reliability of operations, reduce equipment failures due to improper operation, accurately control flushing pressure and flow, avoid equipment damage due to excessive flushing pressure, and be able to adapt to different types of soils, thereby improving the versatility and adaptability of the dredger.

[0021] In this embodiment, the parameter input unit further 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.

[0022] In this embodiment, by quality inspection of the posture information and rake tooth load data collected by the sensor, the accuracy and reliability of the input data are ensured, and operational errors caused by data errors are reduced. The classification of equipment operating parameters and dredging operation parameters helps to more accurately understand the equipment status and operation efficiency. Based on the correlation analysis of posture information and rake tooth load data, the operating status of the equipment can be monitored in real time, potential problems can be discovered in time, and it can be effectively judged whether the operating status of the equipment is normal. Timely alarm reminders can be given to prevent the equipment from being damaged due to exceeding the safe operating range, thereby improving the safety and efficiency of the entire dredging operation.

[0023] In this embodiment, the flushing system modeling unit includes: 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.

[0024] In this embodiment, the angle and number of nozzles are accurately calculated to ensure uniform water flow distribution, improve flushing efficiency, and reduce soil adhesion. The nozzle configuration is determined according to the size of the rake head and the flushing requirements to ensure that each rake tooth is effectively covered by flushing and reduce wear. It is ensured that the pressure at the nozzle meets the operating requirements to prevent a decrease in operating efficiency or equipment damage due to insufficient pressure. The flushing parameters are dynamically adjusted according to different soil characteristics and operating conditions to enhance the system's adaptability to complex environments, provide optimal flushing volume and pressure, improve the accuracy and efficiency of dredging operations, and adjust the flushing parameters based on real-time data to ensure operation continuity and stability.

[0025] In this embodiment, the flushing simulation control unit includes: 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; Real-time control module, used to adjust the working state of the flushing system in real time according to the sensor data and the prediction results of the associated model, and adjust the spray pressure, flow rate, angle, etc. of the nozzle; Fault diagnosis module, used to monitor system operation status, diagnose potential faults, and provide corresponding warnings and maintenance suggestions; The 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 (such as nozzle pressure, angle, flow, etc.) according to the comparison results. This adaptive adjustment can ensure that the flushing system always maintains the best working state under different soil types and operating conditions; 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 (such as soil cleaning degree, rake tooth load change, etc.), 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 to ensure the accuracy and reliability of the model; 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, 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.

[0026] In this embodiment, by obtaining the interactions and influences between various parameters and using sensor data and correlation model prediction results, the working state of the flushing system is adjusted instantly, ensuring that the nozzle's injection pressure, flow rate, angle and other parameters can adapt to the current operating conditions at any time, thereby improving operating efficiency and effectiveness. 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 operating efficiency of the clay-type rake head excavator, reduce soil adhesion, and reduce energy consumption and wear. At the same time, through fault warning and maintenance support, equipment failures and downtime are reduced, further reducing operating costs.

[0027] Specifically, the flushing simulation control unit also includes: 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; The response time stability coefficient is obtained by the following formula:

[0028] 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 minIndicates the maximum and minimum element change display response duration corresponding to n display element changes; T v It indicates the average element change display response duration corresponding to n display element changes; The abnormality determination module is used to determine whether there is an abnormality in the operation of the visualization module according to the response time stability coefficient.

[0029] The technical effect of the above technical solution is: through the first data moment acquisition module and the second data moment acquisition module, the data change moment of the display elements (such as operating status, parameter adjustment effect and fault diagnosis information) in the visualization module of the flushing system and the display moment after these changes can be monitored in real time. This ensures that the system can quickly capture the changes in data and respond. The element change display response time acquisition module can calculate the response time of the visualization module to the change of the display element data, which is an important indicator for evaluating the performance of the system. The response time stability coefficient acquisition module calculates through the above formula, comprehensively considering multiple factors such as the standard deviation, maximum value, standard deviation and maximum difference value of the element change display response time, as well as the maximum value, minimum value and average value of the overall response time, so as to comprehensively and accurately evaluate the stability of the operation of the visualization module. The abnormality determination module can determine whether there is an abnormality in the operation of the visualization module according to the response time stability coefficient. This helps to discover and solve potential problems in a timely manner and prevent operational errors or data errors caused by system instability. By continuously monitoring and analyzing the response time stability coefficient, the key factors affecting the system performance can be identified, so as to optimize and improve them in a targeted manner. For example, the data processing flow can be adjusted, the algorithm can be optimized, or the hardware configuration can be enhanced to improve the overall performance and stability of the system. A stable visualization module can ensure that users can obtain real-time and accurate information such as the operating status of the flushing system and the effect of parameter adjustment, thereby improving the user's operating experience and satisfaction.

[0030] In summary, this technical solution effectively improves the stability and performance of the flushing system visualization module through real-time monitoring, performance evaluation, anomaly detection and optimization and improvement, providing a strong guarantee for the safe and efficient operation of the system.

[0031] Specifically, 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; The operation evaluation coefficient is obtained by the following formula:

[0032] 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 change of the i-th display element; 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.

[0033] The technical effect of the above technical solution is: by comparing the response time stability coefficient with the preset threshold through the first comparison module, it is possible to preliminarily determine whether the operation state of the visualization module is stable. This step provides a basis for subsequent abnormal judgment. When the response time 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 system performance and help to gain a deep understanding of the system's operating status. The operation evaluation coefficient acquisition module uses multiple factors such as CPU occupancy rate, memory occupancy rate, response time stability coefficient, change delay rate and data redundancy rate to calculate the operation evaluation coefficient through the above formula. 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 the preset operation evaluation coefficient threshold. By setting different thresholds, the standard for abnormal judgment can be flexibly adjusted according to actual needs to meet the application needs in different scenarios. When the abnormal judgment and alarm module detects that the operation evaluation coefficient is lower than the preset threshold, it will immediately determine that the operation of the visualization module is abnormal and issue an abnormal alarm. This function can promptly discover and deal with potential problems, prevent the problem from further deteriorating, and ensure the stable operation of the system. By continuously monitoring the operation evaluation coefficient and abnormal alarm information, problems and bottlenecks in the operation of the visualization module can be discovered and resolved in a timely manner. This helps optimize system configuration, improve system performance, and reduce maintenance costs. A stable visualization module can ensure that users can obtain the required information in real time and accurately, improving their operating experience and satisfaction. At the same time, timely abnormal alarms and processing can also enhance users' trust and dependence on the system.

[0034] In summary, this technical solution effectively improves the stability and performance of the visualization module through precise anomaly detection, comprehensive performance evaluation, comprehensive operation evaluation, flexible threshold setting, timely anomaly alarm and optimized system maintenance, providing a strong guarantee for the safe and efficient operation of the system.

[0035] The present invention provides another technical solution, a drag head flushing parameterized modeling method of a clay type drag head excavator, comprising the following steps: 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 inclination angle of the rake head, the angle of the rake teeth and other posture information 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.

[0036] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which 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 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 real-time feedback data.

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, comprising: 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 drag head excavator according to 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 flush simulation control unit also includes: 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; 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 It indicates the average element change display response duration corresponding to n display element changes; The abnormality determination module is used to determine whether there is an abnormality in the operation of the visualization module according to the response time stability coefficient.

9. The drag head flushing parameterized modeling system of a clay drag head excavator as claimed in claim 8, characterized in that: 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; 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 change of the i-th display element; 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.

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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