Intelligent vibration control method and system for shield concrete segment

Abstract

The present application provides an intelligent vibration control method and system for shield concrete segments, which relates to the field of concrete vibration control technology. The method includes: performing mold damage analysis based on the concrete ratio in multiple stages to determine the maximum flow rate of vibration in multiple stages; taking the maximum flow rate of vibration in multiple stages as a constraint, optimizing the vibration parameters based on the vibration indicators in multiple stages, and determining the optimized vibration scheme for vibration operation; collecting real-time pressure data during the operation and feeding it back to the control unit; performing pressure deviation analysis based on the PID control algorithm, and generating feedback adjustment parameters to optimize the opening of the regulating valve. This application can solve the technical problem that the accuracy and timeliness of the control parameter adjustment are poor, resulting in poor vibration quality, due to the inability to set matching vibration control parameters according to the changing state during the concrete vibration process, and can achieve the effect of improving the vibration quality and concrete compaction quality and extending the service life of the mold.

Description

Technical Field

[0001] The present application relates to the technical field of concrete vibration control, and in particular to an intelligent vibration control method and system for shield concrete segments. Background Art

[0002] In the prefabrication production process of shield concrete segments, concrete vibration and compaction is the core link and key process of segment casting production. At present, the vibration is mostly carried out by the attached vibration technology, that is, a pneumatic attached vibrator is installed on the segment mold and connected to compressed air to realize the vibration of the vibrator to achieve the effect of concrete compaction.

[0003] At present, the existing vibration control method of shield concrete segments is unable to set matching vibration control parameters according to the actual changing state of concrete during the vibration process, resulting in poor accuracy and timeliness of vibration control parameter adjustment, causing poor vibration quality, and affecting the concrete compaction effect and mold service life. Summary of the invention

[0004] The purpose of this application is to provide an intelligent vibration control method and system for shield concrete segments, so as to solve the technical problem that the existing vibration control method of shield concrete segments cannot set matching vibration control parameters according to the actual changing state of the concrete vibration process, resulting in poor accuracy and timeliness of vibration control parameter adjustment, causing poor vibration quality, and affecting the concrete compaction effect and mold service life.

[0005] In view of the above problems, the present application provides an intelligent vibration control method and system for shield concrete segments.

[0006] In the first aspect, the present application provides an intelligent vibration control method for shield concrete segments, and the method is implemented by an intelligent vibration control system for shield concrete segments, wherein the method includes: obtaining concrete property information, target vibration indicators and mold property information, wherein the concrete property information includes mix ratio and slump, the target vibration indicators include density indicator, uniformity indicator and porosity indicator, and the mold property information includes mold shape, mold size and mold material; based on the concrete property information, the target vibration indicator and the mold property information, the target concrete vibration process is divided through a vibration analysis model, a plurality of vibration stages are determined, and a plurality of stage vibration indicators and a plurality of stage concrete proportions of the plurality of vibration stages are obtained; based on the concrete property information and the mold attribute information, performing stage mold damage analysis according to the concrete proportions of the multiple stages, and determining the maximum flow rates of vibration in the multiple stages; taking the maximum flow rates of vibration in the multiple stages as constraints, optimizing the vibration parameters based on the vibration indicators of the multiple stages, and determining an optimized vibration scheme, wherein the optimized vibration scheme includes multiple optimized vibration parameters, the optimized vibration parameters correspond to the vibration stages one by one, and the vibration parameters are compressed air flow rates; performing vibration operations in the multiple vibration stages according to the optimized vibration scheme, and during the vibration operation, collecting real-time pressure data through a pressure sensor and feeding it back to a control unit; in the control unit, performing pressure deviation analysis based on a PID control algorithm, generating feedback adjustment parameters, and optimizing the opening of the electric control valve according to the feedback adjustment parameters until the vibration operation is completed.

[0007] In the second aspect, the present application also provides an intelligent vibration control system for shield concrete segments, which is used to execute an intelligent vibration control method for shield concrete segments as described in the first aspect, wherein the system includes: an information acquisition module, which is used to acquire concrete property information, target vibration indicators and mold property information, wherein the concrete property information includes mix ratio and slump, the target vibration indicators include density indicator, uniformity indicator and porosity indicator, and the mold property information includes mold shape, mold size and mold material; a vibration process division module, which is used to divide the target concrete vibration process through a vibration analysis model based on the concrete property information, the target vibration indicator and the mold property information, determine multiple vibration stages, and obtain multiple stage vibration indicators and multiple stage concrete proportions of the multiple vibration stages; a mold damage analysis module, which is used to divide the target concrete vibration process based on the concrete property information, the target vibration indicator and the mold property information, determine multiple vibration stages, and obtain multiple stage vibration indicators and multiple stage concrete proportions of the multiple vibration stages; The invention provides a vibration parameter optimization module, which is used to optimize the vibration parameters based on the vibration indicators of the multiple stages and the maximum flow rate of the vibration in the multiple stages, and determine the optimized vibration scheme, wherein the optimized vibration scheme includes multiple optimized vibration parameters, the optimized vibration parameters correspond to the vibration stages one by one, and the vibration parameters are compressed air flow rates; a pressure data feedback module, which is used to perform the vibration operation in the multiple vibration stages according to the optimized vibration scheme, and collect real-time pressure data through the pressure sensor during the vibration operation and feed it back to the control unit; an opening optimization control module, which is used to perform pressure deviation analysis based on the PID control algorithm in the control unit, generate feedback adjustment parameters, and optimize the opening of the electric control valve according to the feedback adjustment parameters until the vibration operation is completed.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] By acquiring concrete property information, target vibration index and mold property information, wherein the concrete property information includes mix ratio and slump, the target vibration index includes density index, uniformity index and porosity index, and the mold property information includes mold shape, mold size and mold material; based on the concrete property information, the target vibration index and the mold property information, the target concrete vibration process is divided through a vibration analysis model to determine multiple vibration stages, and multiple stage vibration indexes and multiple stage concrete proportions of the multiple vibration stages are acquired; based on the concrete property information and the mold property information, stage mold damage analysis is performed according to the multiple stage concrete proportions to determine multiple The maximum flow rate of stage vibration; taking the maximum flow rates of the multiple stage vibration as constraints, optimizing the vibration parameters based on the multiple stage vibration indicators, and determining an optimized vibration scheme, wherein the optimized vibration scheme includes multiple optimized vibration parameters, the optimized vibration parameters correspond to the vibration stages one by one, and the vibration parameters are compressed air flow rates; performing vibration operations in the multiple vibration stages according to the optimized vibration scheme, and during the vibration operation, collecting real-time pressure data through a pressure sensor and feeding it back to a control unit; in the control unit, performing pressure deviation analysis based on a PID control algorithm, generating feedback adjustment parameters, and optimizing the opening of the electric control valve according to the feedback adjustment parameters until the vibration operation is completed. That is to say, a vibration analysis model is constructed based on the concrete property information and the mold property information, and then the target vibration index is input into the vibration analysis model to divide the vibration process, so as to obtain multiple vibration stages, and then multiple stage vibration indexes and multiple stage concrete proportions of the multiple vibration stages are obtained; further simulation modeling is performed based on the concrete property information and the mold property information to construct a vibration twin model, and the vibration twin model is used to perform stage mold damage analysis in combination with multiple stage concrete proportions to determine the maximum flow rate of vibration in multiple stages; then, the maximum flow rate of vibration in multiple stages is used as a constraint, and vibration parameters are optimized for multiple vibration stages according to the vibration indexes in multiple stages to obtain multiple optimized The vibration parameters are used to generate an optimized vibration plan; finally, the vibration operation is performed in multiple vibration stages according to the optimized vibration plan, and during the vibration operation, the collected real-time compressed air pressure data is fed back to the control unit, and in the control unit, a pressure deviation analysis is performed based on the PID control algorithm, and feedback adjustment parameters are generated to optimize the opening of the electric control valve until the vibration operation is completed; the accuracy and rationality of the vibration control parameter setting can be improved, and at the same time, intelligent feedback adjustment of the vibration control parameters can be realized during the vibration control process, making the vibration control more accurate and reliable, thereby achieving the technical effect of improving the vibration quality and concrete compaction quality and extending the service life of the mold.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0012] Figure 1 A schematic flow chart of an intelligent vibration control method for a shield concrete segment in this application;

[0013] Figure 2 A schematic diagram of a process for determining multiple vibration stages in an intelligent vibration control method for a shield concrete segment of the present application;

[0014] Figure 3 This is a structural schematic diagram of an intelligent vibration control system for shield concrete segments in this application.

[0015] Description of reference numerals:

[0016] Information acquisition module 11, vibration process division module 12, mold damage analysis module 13, vibration parameter optimization module 14, pressure data feedback module 15, opening optimization control module 16. DETAILED DESCRIPTION

[0017] This application provides an intelligent vibration control method and system for shield concrete segments, which solves the technical problem that the existing vibration control method for shield concrete segments cannot set matching vibration control parameters according to the actual change state during the concrete vibration process, resulting in poor accuracy and timeliness of vibration control parameter adjustment, poor vibration quality, and affects the concrete compaction effect and mold service life. The accuracy and rationality of vibration control parameter setting can be improved, and intelligent feedback adjustment of vibration control parameters can be achieved during the vibration control process, making vibration control more accurate and reliable, thereby achieving the technical effect of improving vibration quality and concrete compaction quality and extending mold service life.

[0018] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0019] Embodiment 1

[0020] Please see attached Figure 1 The present application provides an intelligent vibration control method for a shield concrete segment, wherein the method is applied to an intelligent vibration control system for a shield concrete segment, and the method specifically comprises the following steps:

[0021] Step 1: Acquire concrete property information, target vibration index and mold property information, wherein the concrete property information includes mix ratio and slump, the target vibration index includes density index, uniformity index and porosity index, and the mold property information includes mold shape, mold size and mold material.

[0022] Specifically, before formulating the vibration plan, detailed data collection of the target concrete is required to ensure that the selection of vibration parameters can meet the performance requirements of the concrete. First, data collection is performed on the target concrete to obtain the concrete property information, target vibration index and mold property information of the target concrete, wherein the concrete property information includes mix ratio and slump, and the mix ratio includes water-cement ratio, coarse aggregate ratio, fine aggregate ratio, admixture type and ratio, additive type and ratio; the slump is an important indicator for measuring the fluidity of concrete, wherein the larger the slump, the better the fluidity of the concrete. At the same time, during the vibration process, concrete with high slump usually requires less vibration, while concrete with low slump requires stronger vibration.

[0023] The target vibration index includes density index, uniformity index and porosity index, wherein the density index refers to the compactness of concrete during the vibration process, and the higher the density, the better the concrete vibration quality; the uniformity index reflects the uniformity of distribution of each component in concrete, and the better the uniformity, the better the concrete vibration quality; the porosity index refers to the number and size of pores in concrete, wherein the lower the porosity, the better the concrete vibration quality. The mold attribute information includes mold shape, mold size and mold material, and the mold material includes material type and material properties, such as vibration resistance, durability, etc.

[0024] Step 2: Based on the concrete property information, the target vibration index and the mold property information, the target concrete vibration process is divided through a vibration analysis model, multiple vibration stages are determined, and multiple stage vibration indexes and multiple stage concrete proportions of the multiple vibration stages are obtained.

[0025] Specifically, with the concrete attribute information and the mold attribute information as constraints, a sample training set is retrieved online, wherein the sample training data is a sample vibration index and a corresponding plurality of sample vibration stages; then, the BP neural network is supervised and trained through the sample training set to obtain a trained vibration analysis model, wherein the vibration analysis model is a neural network model that can be iteratively optimized in machine learning, and includes an input layer, a plurality of hidden layers, and an output layer, wherein the input data of the input layer is a vibration index, and the output data is a plurality of vibration stages. Then, the target vibration index is input into the vibration analysis model, thereby realizing the intelligent division of the target concrete vibration process, and outputting a plurality of vibration stages, including an early vibration stage, an initial vibration stage, a mid-term vibration stage, a final vibration stage, and a supplementary vibration stage, etc. For example, in the initial vibration stage, the amount of concrete in the mold is small and the fluidity is good. At this time, the main goal is to make the concrete flow and fill the corners and gaps of the mold, so the vibration parameters should be set to weak vibration to avoid damage to the mold.

[0026] The vibration operation analysis is further performed on multiple vibration stages to obtain multiple stage vibration indicators and multiple stage concrete ratios of the multiple vibration stages. The purpose of performing the vibration operation analysis on multiple vibration stages is to gain an in-depth understanding of the performance and vibration effect of concrete in each stage, as well as changes in the mold filling state. Each vibration stage includes a stage vibration indicator and a stage concrete ratio. The stage vibration indicator refers to the concrete performance indicator to be achieved in each stage, including stage density, stage uniformity and stage porosity; the stage concrete ratio refers to the ratio of the concrete volume in the mold to the mold volume in each stage.

[0027] Step three: Based on the concrete property information and the mold property information, perform stage mold damage analysis according to the concrete proportions of the multiple stages, and determine the maximum flow rates of vibration in the multiple stages.

[0028] Specifically, digital twin technology is a technology that accurately maps physical entities through digital models. This digital model can reflect the state, performance and behavior of physical entities in real time in a virtual environment. It has the characteristics of real-time synchronization, faithful mapping and high fidelity. Digital twin integrates multiple technologies such as collaborative modeling, data mining, and human-computer interaction, and realizes collaborative interaction between the physical world and the digital world. Based on digital twin technology, simulation modeling is performed according to the concrete attribute information and the mold attribute information to generate a vibration twin model, which can simulate the vibration process of the target concrete. Then, through the vibration twin model, the stage mold damage analysis is performed according to the concrete proportions of multiple stages. The purpose of performing the stage mold damage analysis according to the concrete proportions of multiple stages is to evaluate the pressure and deformation of the mold during the vibration process, and how these factors affect the service life and performance of the mold; obtain the maximum vibration parameter corresponding to each stage; then, according to the mapping relationship between the vibration control parameters of the pneumatic attached vibrator and the compressed air flow rate, determine the maximum vibration flow rate corresponding to the maximum vibration parameter, wherein the maximum vibration flow rate refers to the maximum compressed air flow rate; obtain the maximum vibration flow rates of multiple stages of multiple vibration stages.

[0029] Step 4: Taking the maximum flow rate of the vibration in the multiple stages as a constraint, optimizing the vibration parameters based on the vibration indicators in the multiple stages, and determining an optimized vibration scheme, wherein the optimized vibration scheme includes multiple optimized vibration parameters, the optimized vibration parameters correspond to the vibration stages one by one, and the vibration parameters are compressed air flow rates.

[0030] Specifically, the flow rate constraint of the vibration stage is then taken as less than the maximum flow rate of the stage vibration, and the optimization algorithm is used to optimize the vibration parameters of each stage for the purpose of meeting the stage vibration index, wherein the vibration parameter is the compressed air flow rate, and multiple optimized vibration parameters are obtained, wherein the optimized vibration parameters correspond to the vibration stage one by one, and an optimized vibration scheme is constructed according to multiple optimized vibration parameters. By taking less than the maximum flow rate of the stage vibration as a constraint condition, the damage to the mold during the vibration process can be reduced and the service life of the mold can be extended; then the vibration parameters are optimized for the purpose of meeting the stage vibration index, which can improve the adaptability of the optimized vibration parameters and the actual stage vibration index, thereby improving the accuracy and rationality of the vibration parameter setting.

[0031] Step 5: Perform the vibration operation in the multiple vibration stages according to the optimized vibration scheme, and during the vibration operation, collect real-time pressure data through the pressure sensor and feed it back to the control unit.

[0032] Step six: In the control unit, pressure deviation analysis is performed based on the PID control algorithm to generate feedback adjustment parameters, and the opening of the electric control valve is optimized and controlled according to the feedback adjustment parameters until the vibration operation is completed.

[0033] Specifically, the vibration operation of the target concrete in multiple vibration stages is performed according to the optimized vibration scheme. At the same time, during the vibration operation, the real-time compressed air pressure data is collected by the pressure sensor arranged in the compressed air output pipeline, and the real-time pressure data is fed back to the control unit. Finally, in the control unit, the pressure deviation is determined according to the real-time pressure data and the stage target pressure data, and then the pressure deviation analysis is performed based on the PID control algorithm, wherein the PID control algorithm is a classic control algorithm widely used in industrial process control. It adjusts the output of the controller through three control items: proportional (P), integral (I) and differential (D) to achieve stable control of the process variable (PV). The basic idea of ​​the PID control algorithm is to adjust the output of the controller according to the deviation between the process variable and the set value, so as to control the controlled variable (CV) to achieve the expected value.

[0034] First, the PID controller is designed, including the parameters of the proportional (P), integral (I) and differential (D) controllers. The proportional controller controls according to the current pressure deviation, the integral controller accumulates the past pressure deviation, and the differential controller predicts the change trend of the future pressure deviation. Then, the real-time pressure deviation value is analyzed by the PID controller, and the dynamic response of the control system is analyzed to ensure that the system is stable and quickly reaches the target pressure value. Finally, according to the output of the PID controller, the feedback adjustment parameter is generated. The feedback adjustment parameter is used to adjust the opening of the electric control valve in real time to compensate for the pressure deviation and maintain the target pressure value; finally, the feedback adjustment parameter is input into the control system of the electric control valve, and the electric control valve adjusts the opening according to the feedback adjustment parameter to realize the control of the compressed air flow. The compressed air gas flow is controlled by the opening of the regulating valve, and then the vibration force of the pneumatic vibrator on the mold is adjusted, so as to realize the precise control of the vibration of the shield concrete segment.

[0035] The intelligent vibration control method of a shield concrete segment is applied to an intelligent vibration control system of a shield concrete segment, which can solve the technical problem that the existing vibration control method of a shield concrete segment cannot set matching vibration control parameters according to the actual change state during the concrete vibration process, resulting in poor accuracy and timeliness of vibration control parameter adjustment, poor vibration quality, and at the same time affecting the concrete compaction effect and mold service life. First, obtain concrete attribute information, target vibration index and mold attribute information, wherein the concrete attribute information includes mix ratio and slump, the target vibration index includes density index, uniformity index and porosity index, and the mold attribute information includes mold shape, mold size and mold material; then, based on the concrete attribute information, the target vibration index and the mold attribute information, divide the target concrete vibration process through a vibration analysis model, determine multiple vibration stages, and obtain multiple stage vibration indexes and multiple stage concrete ratios of the multiple vibration stages; then, based on the concrete attribute information and the mold attribute information, perform stage mold damage analysis according to the multiple stage concrete ratios, and determine multiple stages. The maximum flow rate of vibration; next, taking the maximum flow rate of vibration in the multiple stages as a constraint, optimizing the vibration parameters based on the vibration indicators of the multiple stages, and determining the optimized vibration scheme, wherein the optimized vibration scheme includes multiple optimized vibration parameters, the optimized vibration parameters correspond to the vibration stages one by one, and the vibration parameters are compressed air flow; further, performing the vibration operation in the multiple vibration stages according to the optimized vibration scheme, and during the vibration operation, collecting real-time pressure data through the pressure sensor and feeding it back to the control unit; finally, in the control unit, performing pressure deviation analysis based on the PID control algorithm, generating feedback adjustment parameters, and optimizing the opening of the electric regulating valve according to the feedback adjustment parameters until the vibration operation is completed. The above method can improve the accuracy and rationality of the setting of the vibration control parameters, and at the same time, can realize intelligent feedback adjustment of the vibration control parameters during the vibration control process, making the vibration control more accurate and reliable, thereby achieving the technical effect of improving the vibration quality and concrete compaction quality, and extending the service life of the mold.

[0036] Further, as attached Figure 2 As shown, step 2 of this application includes:

[0037] The concrete property information is used as a material constraint, and the mold property information is used as an equipment constraint. Information retrieval is performed based on industrial big data networking to obtain a sample training data set, wherein the sample training data includes a sample vibration index and a sample vibration stage set; the sample training data set is divided into N equal parts, and is selected N times without replacement to generate a first training set, and iteratively selected N times to obtain N training sets; the BP neural network is supervised and trained using the N training sets to obtain N vibration analysis units that meet the expected convergence constraints, and the vibration analysis model is constructed based on the N vibration analysis units, wherein the output of the vibration analysis model is the mode of the output results of the N vibration analysis units; the target vibration index is input into the vibration analysis model for stage division, and multiple vibration stages are output.

[0038] Specifically, industrial big data is a series of technologies and methods that enable the value contained in industrial big data to be mined and displayed, including data planning, data collection, analysis and mining, etc., which can improve the accuracy and comprehensiveness of data acquisition. Based on industrial big data technology, the concrete attribute information is used as the material constraint, the mold attribute information is used as the equipment constraint, and information retrieval is performed online to obtain a sample training data set, where the sample training data includes a sample vibration index and a sample vibration stage set, that is, each sample vibration index corresponds to a sample vibration stage set.

[0039] The sample training data set is divided into N equal parts, and the amount of data in each part needs to be roughly equal, so that each training set and validation set can represent the characteristics of the entire data set; then, N parts of the data are selected without replacement N times to generate the first training set, and the same method is used for random selection. After N iterations, N training sets will be obtained. Since the sample training data in each training set are not exactly the same, the generalization ability of the model training process can be improved. Then, the BP neural network is supervised and trained using the N training sets. First, the BP neural network is initialized and appropriate initial weights and biases are selected. Then, each training set is used to supervise the BP neural network. During the training process, the weights and biases of the network are adjusted by the back propagation algorithm to minimize the loss function on the training set. The above training process is repeated until the expected convergence constraint is met. The expected convergence constraint can be set according to the actual situation, such as the model output accuracy index or the number of model iteration training times. The N vibration analysis units that meet the expected convergence constraint are obtained. Then, the vibration analysis model is constructed in parallel based on the N vibration analysis units. The output of the vibration analysis model is the mode of the output results of the N vibration analysis units. The mode is a statistical concept used to describe the value that appears most frequently in a set of data. In the vibration analysis model, the mode is used as the output result, which can reflect the consensus prediction of the model for specific vibration parameters or vibration effects, thereby further improving the accuracy of the output of the vibration analysis model. Finally, the target vibration index is input into the vibration analysis model for stage division to obtain multiple vibration stages.

[0040] Further, step three of this application includes:

[0041] Based on the digital twin technology, vibration simulation modeling is performed according to the concrete property information and the mold property information to generate a vibration twin model; the first vibration stage is selected from the multiple vibration stages, and the first vibration duration and the first stage concrete ratio of the first vibration stage are obtained, wherein the first stage concrete ratio refers to the volume proportion of concrete in the mold at the end of the first vibration stage; with the purpose of being less than the upper limit of mold damage, based on the first vibration duration and the first stage concrete ratio, vibration simulation is performed through the vibration twin model to determine the first maximum vibration parameter, wherein the first maximum vibration parameter includes a first vibration frequency and a first vibration amplitude; the first stage vibration maximum flow rate is determined based on the first vibration frequency and the first vibration amplitude, and added to the multiple stage vibration maximum flows.

[0042] Specifically, digital twin technology is a technology that accurately maps physical entities through digital models. This digital model can reflect the state, performance and behavior of physical entities in real time in a virtual environment. Based on digital twin technology, vibration simulation modeling is performed according to the concrete attribute information and the mold attribute information to construct a vibration twin model. Then, the first vibration stage is selected from the multiple vibration stages, and the first vibration stage is any one of the multiple vibration stages. The first vibration duration and the first stage concrete ratio of the first vibration stage are obtained, wherein the first stage concrete ratio refers to the volume ratio of concrete in the mold at the end of the first vibration stage, that is, the ratio of the concrete volume to the mold volume.

[0043] The upper limit of mold damage is obtained, which refers to the limit value of the maximum stress, deformation or wear that the mold can withstand during the vibration process, and is determined based on the mold attribute information; then, with the purpose of being less than the upper limit of mold damage, based on the first vibration time and the first stage concrete ratio, vibration simulation is performed through the vibration twin model, wherein the first vibration time reflects the length of time the mold withstands during the vibration process, and the first stage concrete ratio reflects the filling state of the concrete in the mold; the first maximum vibration parameter that is less than the upper limit of mold damage is determined, wherein the first maximum vibration parameter includes the first vibration frequency and the first vibration amplitude. Then, according to the first vibration frequency and the first vibration amplitude, a compressed air flow analysis is performed to determine the maximum flow of the first stage vibration, and the maximum flow of the first stage vibration is added to the maximum flow of multiple stages vibration to obtain the maximum flow of multiple stages vibration.

[0044] Furthermore, the present application also includes the following steps:

[0045] Read the vibration control parameters of the pneumatic attached vibrator, and establish a first mapping relationship between the vibration control parameters and the compressed air flow rate; based on the first mapping relationship, determine the first compressed air flow rate according to the first vibration frequency and the first vibration amplitude, and set the first compressed air flow rate as the maximum flow rate of the first stage vibration.

[0046] Specifically, a pneumatic attached vibrator is a vibration device that uses compressed air as a power source and is widely used in the fields of concrete vibration, material transportation, and anti-loosening of industrial equipment. Pneumatic attached vibrators are usually composed of components such as cylinders, pistons, springs, connectors, and control valves, and generate vibrations through the action of compressed air. Read the vibration control parameters of the pneumatic attached vibrator, and establish a first mapping relationship between the vibration control parameters and the compressed air flow rate. First, collect the vibration control parameter data of the pneumatic attached vibrator, including vibration frequency, amplitude, duration, etc., and collect the corresponding compressed air flow data under different vibration parameters; then use statistical analysis methods, such as regression analysis, to establish a mapping relationship model between the vibration control parameters and the compressed air flow rate, wherein the mapping relationship model can predict the required compressed air flow rate under different vibration parameters, and embed the mapping relationship model into the first mapping relationship.

[0047] Then, the first vibration frequency and the first vibration amplitude are input into the mapping relationship model of the first mapping relationship for matching analysis, and the first compressed air flow rate is output, and the first compressed air flow rate is set as the maximum flow rate of the first stage vibration.

[0048] Further, step 4 of this application includes:

[0049] A first vibration stage is selected from the multiple vibration stages, and a first-stage vibration maximum flow rate and a first-stage vibration index of the first vibration stage are obtained, wherein the first-stage vibration index includes a first density index, a first uniformity index, and a first porosity index; a flow adjustment threshold of the electric regulating valve is obtained, and a plurality of flow values ​​are randomly selected within the flow adjustment threshold with a constraint of being less than the first-stage vibration maximum flow rate, and a plurality of vibration control parameters of the plurality of flow values ​​are determined based on the first mapping relationship; vibration simulation is performed on the plurality of vibration control parameters respectively through the vibration twin model to determine a plurality of stage vibration simulation results, wherein each stage vibration simulation result includes a stage density, a stage uniformity, and a stage porosity; a fitness evaluation is performed on the plurality of stage vibration simulation results respectively using a vibration quality evaluation function to determine a plurality of fitnesses, and a plurality of flow values ​​are sorted from large to small according to the fitnesses, and the flow value is set as an initial solution to generate an initial solution sequence; The first M initial solutions in the initial solution sequence are set as optimal solutions, and the last N initial solutions are set as inferior solutions, wherein the sum of M and N is the number of initial solutions, and N is greater than M; the M optimal solutions are used to randomly cluster the N inferior solutions to generate M solution sets, and within the M solution sets, the superior solutions are used as the optimization direction, and the inferior solutions are updated according to a preset step size to obtain M updated solution sets, wherein the inferior solutions in the updated solution sets must be less than the maximum flow rate of the first stage vibration; M updated solution sets are identified, and if there is an inferior solution whose fitness is greater than or equal to the superior solution in the updated solution set, the superior solution is replaced by the inferior solution; iterative optimization is continued until the preset optimization number constraint is reached, and the current M updated solution sets are output, and the optimal solution of the optimal solution set in the current M updated solution sets is selected as the first optimized vibration parameter, wherein the optimal solution set is the updated solution set with the largest sum of fitness; the first optimized vibration parameter is added to the multiple optimized vibration parameters, and the optimized vibration scheme is composed according to the multiple optimized vibration parameters in the order of stages.

[0050] Specifically, first, a first vibration stage is selected from the multiple vibration stages, the first vibration stage being any one of the multiple vibration stages, and the first stage vibration maximum flow rate and the first stage vibration index of the first vibration stage are obtained, wherein the first stage vibration index includes a first density index, a first uniformity index and a first porosity index. On the other hand, a flow adjustment threshold of the electric regulating valve is obtained, and a plurality of flow values ​​are randomly selected within the flow adjustment threshold with a constraint condition that the flow rate is less than the maximum flow rate of the first stage vibration, and a plurality of vibration control parameters of the plurality of flow values ​​are determined based on the first mapping relationship analysis.

[0051] Then, the target concrete is vibrated and simulated based on the multiple vibration control parameters through the vibration twin model to obtain multiple stage vibration simulation results, wherein each stage vibration simulation result includes stage density, stage uniformity and stage porosity. Then, the fitness of the multiple stage vibration simulation results is evaluated respectively using the vibration quality evaluation function, wherein the greater the stage density, the greater the stage uniformity and the smaller the stage porosity, the greater the corresponding fitness, and multiple fitness of multiple stage vibration simulation results are obtained. Further, multiple flow values ​​are sorted from large to small according to the fitness, and the flow value is set as the initial solution to generate an initial solution sequence.

[0052] First, the first M initial solutions in the initial solution sequence are set as optimal solutions, and the last N initial solutions are set as inferior solutions, where the sum of M and N is the number of initial solutions, and N is much larger than M. Then, the M optimal solutions are used to randomly cluster the N inferior solutions to generate M solution sets, where the number of inferior solutions in each solution set is the same. Then, the optimal solution is used as the optimization direction, and the inferior solutions are updated according to the preset step length, where the preset step length is the flow adjustment step in each optimization process, and M updated solution sets are obtained, where if the inferior solution in the updated solution set is greater than or equal to the maximum flow of the first stage of vibration, it will not be updated. Then identify M updated solution sets. If there is an inferior solution whose fitness is greater than or equal to the fitness of the superior solution in the updated solution set, replace the superior solution with the inferior solution. Use the above method to continuously iterate and search for the best until the preset number of optimization constraints is reached. Then output the current M updated solution sets, calculate the fitness of the M updated solution sets, and set the updated solution set with the largest sum of fitness as the optimal solution set. Finally, select the optimal solution of the optimal solution set in the current M updated solution sets and set it as the first optimized vibration parameter. Finally, add the first optimized vibration parameter to multiple optimized vibration parameters, and form the optimized vibration scheme according to the multiple optimized vibration parameters in the order of stages.

[0053] By using the above optimization algorithm to optimize the vibration parameters, due to the strong global convergence ability of the algorithm, it is possible to avoid falling into the local optimum, improve the comprehensiveness and accuracy of the vibration parameter optimization, and thus improve the accuracy of the target concrete vibration control.

[0054] Furthermore, the present application also includes the following steps:

[0055] The vibration quality evaluation function expression is: ;in, is the fitness of the vibration simulation results of the i-th stage, is the first weight, is the second weight, is the third weight, is the stage density of the vibration simulation result of the i-th stage, is the first density index, is the stage uniformity of the vibration simulation results of the i-th stage, is the first uniformity index, is the porosity of the stage i vibration simulation result, It is the first porosity indicator.

[0056] Specifically, in the vibration quality evaluation function, is the fitness of the vibration simulation result of the i-th stage, where the vibration simulation result of the i-th stage is any one of the vibration simulation results of multiple stages. The higher the fitness, the better the vibration quality. is the first weight, is the second weight, is the third weight, where the sum of the first weight, the second weight and the third weight is 1, and is set based on the importance of the indicator. The higher the importance of the indicator, the greater the corresponding weight; is the stage density of the vibration simulation result of the i-th stage, is the first density index, is the stage uniformity of the vibration simulation results of the i-th stage, is the first uniformity index, is the porosity of the stage i vibration simulation result, It is the first porosity indicator.

[0057] Furthermore, step six of this application includes:

[0058] At a preset node, real-time pressure data is collected through a pressure sensor, and the real-time pressure data is fed back to a control unit, wherein the pressure sensor is arranged in a compressed air output pipeline; the current optimized vibration parameters at the preset node are obtained, a target pressure value is determined based on the current optimized vibration parameters, and a deviation comparison is performed between the target pressure value and the real-time pressure data to determine a real-time pressure deviation value; based on a PID control algorithm, a compensation analysis is performed on the real-time pressure deviation value, and a feedback adjustment parameter is output, wherein the feedback adjustment parameter is a control parameter for adjusting the opening of an electric control valve.

[0059] Specifically, a preset node is configured, and the preset node can be set according to actual conditions, for example: a monitoring node is set every 30 seconds. Then, at the preset node, real-time pressure data is collected through a pressure sensor, and the pressure sensor is arranged in the compressed air output pipeline to monitor the compressed air pressure and feed back the real-time pressure data at the preset node to the control unit. On the other hand, the current optimized vibration parameters at the preset node are obtained, and the target pressure value is determined according to the current optimized vibration parameters, wherein the compressed air flow and the compressed air pressure are correlated, and then the target pressure value and the real-time pressure data are compared for deviation to obtain the real-time pressure deviation value.

[0060] Further based on the PID control algorithm, the real-time pressure deviation value is compensated and analyzed. First, the PID controller is designed, including the parameters of the proportional (P), integral (I) and differential (D) controllers, where the proportional controller controls according to the current pressure deviation, the integral controller accumulates the past pressure deviation, and the differential controller predicts the change trend of the future pressure deviation. Then, the real-time pressure deviation value is analyzed by the PID controller, and the dynamic response of the control system is analyzed to ensure that the system is stable and quickly reaches the target pressure value. Finally, based on the output of the PID controller, the feedback adjustment parameter is generated, and the feedback adjustment parameter is used to adjust the opening of the electric control valve in real time to compensate for the pressure deviation and maintain the target pressure value.

[0061] In summary, the intelligent vibration control method for shield concrete segments provided in this application has the following technical effects:

[0062] 1. A vibration analysis model is constructed based on concrete property information and mold property information, and then the target vibration index is input into the vibration analysis model to divide the vibration process and obtain multiple vibration stages. Then, multiple stage vibration indexes and multiple stage concrete proportions of multiple vibration stages are obtained. Further, simulation modeling is performed based on concrete property information and mold property information to construct a vibration twin model, and the vibration twin model is used to perform stage mold damage analysis in combination with multiple stage concrete proportions to determine the maximum flow rate of vibration in multiple stages. Then, the maximum flow rate of vibration in multiple stages is used as a constraint, and vibration parameters are optimized for multiple vibration stages according to multiple stage vibration indexes to obtain multiple optimized vibration parameters. The optimized vibration scheme is generated based on the tamping parameters; finally, the vibration operation in multiple vibration stages is performed according to the optimized vibration scheme, and during the vibration operation, the collected real-time compressed air pressure data is fed back to the control unit, and in the control unit, the pressure deviation analysis is performed based on the PID control algorithm, and the feedback adjustment parameters are generated to optimize the opening control of the electric control valve until the vibration operation is completed; the accuracy and rationality of the setting of the vibration control parameters can be improved, and at the same time, the intelligent feedback adjustment of the vibration control parameters can be realized during the vibration control process, making the vibration control more accurate and reliable, thereby achieving the technical effect of improving the vibration quality and concrete compaction quality and extending the service life of the mold.

[0063] 2. By taking the maximum flow rate less than the stage vibration as a constraint condition, the damage to the mold during the vibration process can be reduced and the service life of the mold can be extended; then, the vibration parameters are optimized with the purpose of meeting the stage vibration indicators, which can improve the adaptability of the optimized vibration parameters and the actual stage vibration indicators, thereby improving the accuracy and rationality of the vibration parameter setting.

[0064] 3. By using the above-mentioned optimization algorithm to optimize the vibration parameters, due to the strong global convergence ability of the algorithm, it can avoid falling into the local optimum, improve the comprehensiveness and accuracy of the vibration parameter optimization, and thus improve the accuracy of the target concrete vibration control.

[0065] Embodiment 2

[0066] Based on the intelligent vibration control method of a shield concrete segment in the aforementioned embodiment, the present application also provides an intelligent vibration control system for a shield concrete segment, see the attached Figure 3 , the system comprising:

[0067] The information acquisition module 11 is used to obtain concrete property information, target vibration index and mold property information, wherein the concrete property information includes mix ratio and slump, the target vibration index includes density index, uniformity index and porosity index, and the mold property information includes mold shape, mold size and mold material.

[0068] The vibration process division module 12 is used to divide the target concrete vibration process through a vibration analysis model based on the concrete property information, the target vibration index and the mold property information, determine multiple vibration stages, and obtain multiple stage vibration indexes and multiple stage concrete proportions of the multiple vibration stages.

[0069] The mold damage analysis module 13 is used to perform stage mold damage analysis based on the concrete property information and the mold property information and according to the concrete proportions of the multiple stages, and determine the maximum flow rates of vibration in the multiple stages.

[0070] The vibration parameter optimization module 14 is used to optimize the vibration parameters based on the vibration indicators of the multiple stages and the maximum flow rate of the vibration in the multiple stages, and determine the optimized vibration scheme, wherein the optimized vibration scheme includes multiple optimized vibration parameters, the optimized vibration parameters correspond to the vibration stages one by one, and the vibration parameters are compressed air flow rates.

[0071] The pressure data feedback module 15 is used to perform the vibration operation in the multiple vibration stages according to the optimized vibration scheme, and during the vibration operation, collect real-time pressure data through the pressure sensor and feed it back to the control unit.

[0072] The opening optimization control module 16 is used to perform pressure deviation analysis based on the PID control algorithm in the control unit, generate feedback adjustment parameters, and perform opening optimization control on the electric control valve according to the feedback adjustment parameters until the vibration operation is completed.

[0073] Further, the vibration process division module 12 in the system is also used for:

[0074] The concrete property information is used as a material constraint, and the mold property information is used as an equipment constraint. Information retrieval is performed based on industrial big data networking to obtain a sample training data set, wherein the sample training data includes a sample vibration index and a sample vibration stage set; the sample training data set is divided into N equal parts, and is selected N times without replacement to generate a first training set, and iteratively selected N times to obtain N training sets; the BP neural network is supervised and trained using the N training sets to obtain N vibration analysis units that meet the expected convergence constraints, and the vibration analysis model is constructed based on the N vibration analysis units, wherein the output of the vibration analysis model is the mode of the output results of the N vibration analysis units; the target vibration index is input into the vibration analysis model for stage division, and multiple vibration stages are output.

[0075] Furthermore, the mold damage analysis module 13 in the system is also used for:

[0076] Based on the digital twin technology, vibration simulation modeling is performed according to the concrete property information and the mold property information to generate a vibration twin model; the first vibration stage is selected from the multiple vibration stages, and the first vibration duration and the first stage concrete ratio of the first vibration stage are obtained, wherein the first stage concrete ratio refers to the volume proportion of concrete in the mold at the end of the first vibration stage; with the purpose of being less than the upper limit of mold damage, based on the first vibration duration and the first stage concrete ratio, vibration simulation is performed through the vibration twin model to determine the first maximum vibration parameter, wherein the first maximum vibration parameter includes a first vibration frequency and a first vibration amplitude; the first stage vibration maximum flow rate is determined based on the first vibration frequency and the first vibration amplitude, and added to the multiple stage vibration maximum flows.

[0077] Furthermore, the mold damage analysis module 13 in the system is also used for:

[0078] Read the vibration control parameters of the pneumatic attached vibrator, and establish a first mapping relationship between the vibration control parameters and the compressed air flow rate; based on the first mapping relationship, determine the first compressed air flow rate according to the first vibration frequency and the first vibration amplitude, and set the first compressed air flow rate as the maximum flow rate of the first stage vibration.

[0079] Furthermore, the vibration parameter optimization module 14 in the system is also used for:

[0080] A first vibration stage is selected from the multiple vibration stages, and a first-stage vibration maximum flow rate and a first-stage vibration index of the first vibration stage are obtained, wherein the first-stage vibration index includes a first density index, a first uniformity index, and a first porosity index; a flow adjustment threshold of the electric regulating valve is obtained, and a plurality of flow values ​​are randomly selected within the flow adjustment threshold with a constraint of being less than the first-stage vibration maximum flow rate, and a plurality of vibration control parameters of the plurality of flow values ​​are determined based on the first mapping relationship; vibration simulation is performed on the plurality of vibration control parameters respectively through the vibration twin model to determine a plurality of stage vibration simulation results, wherein each stage vibration simulation result includes a stage density, a stage uniformity, and a stage porosity; a fitness evaluation is performed on the plurality of stage vibration simulation results respectively using a vibration quality evaluation function to determine a plurality of fitnesses, and a plurality of flow values ​​are sorted from large to small according to the fitnesses, and the flow value is set as an initial solution to generate an initial solution sequence; The first M initial solutions in the initial solution sequence are set as optimal solutions, and the last N initial solutions are set as inferior solutions, wherein the sum of M and N is the number of initial solutions, and N is greater than M; the M optimal solutions are used to randomly cluster the N inferior solutions to generate M solution sets, and within the M solution sets, the superior solutions are used as the optimization direction, and the inferior solutions are updated according to a preset step size to obtain M updated solution sets, wherein the inferior solutions in the updated solution sets must be less than the maximum flow rate of the first stage vibration; M updated solution sets are identified, and if there is an inferior solution whose fitness is greater than or equal to the superior solution in the updated solution set, the superior solution is replaced by the inferior solution; iterative optimization is continued until the preset optimization number constraint is reached, and the current M updated solution sets are output, and the optimal solution of the optimal solution set in the current M updated solution sets is selected as the first optimized vibration parameter, wherein the optimal solution set is the updated solution set with the largest sum of fitness; the first optimized vibration parameter is added to the multiple optimized vibration parameters, and the optimized vibration scheme is composed according to the multiple optimized vibration parameters in the order of stages.

[0081] Furthermore, the vibration parameter optimization module 14 in the system is also used for: the vibration quality evaluation function expression is: ;in, is the fitness of the vibration simulation results of the i-th stage, is the first weight, is the second weight, is the third weight, is the stage density of the vibration simulation result of the i-th stage, is the first density index, is the stage uniformity of the vibration simulation results of the i-th stage, is the first uniformity index, is the porosity of the stage i vibration simulation result, It is the first porosity indicator.

[0082] Furthermore, the opening degree optimization control module 16 in the system is also used for:

[0083] At a preset node, real-time pressure data is collected through a pressure sensor, and the real-time pressure data is fed back to a control unit, wherein the pressure sensor is arranged in a compressed air output pipeline; the current optimized vibration parameters at the preset node are obtained, a target pressure value is determined based on the current optimized vibration parameters, and a deviation comparison is performed between the target pressure value and the real-time pressure data to determine a real-time pressure deviation value; based on a PID control algorithm, a compensation analysis is performed on the real-time pressure deviation value, and a feedback adjustment parameter is output, wherein the feedback adjustment parameter is a control parameter for adjusting the opening of an electric control valve.

[0084] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The intelligent vibration control method and specific examples of a shield concrete segment in the aforementioned embodiment 1 are also applicable to an intelligent vibration control system for a shield concrete segment in this embodiment. Through the aforementioned detailed description of the intelligent vibration control method for a shield concrete segment, those skilled in the art can clearly understand the intelligent vibration control system for a shield concrete segment in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method description.

[0085] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0086] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. An intelligent vibration control method for shield concrete segments, characterized in that: The method comprises: Acquire concrete property information, target vibration index and mold property information, wherein the concrete property information includes mix ratio and slump, the target vibration index includes density index, uniformity index and porosity index, and the mold property information includes mold shape, mold size and mold material; Based on the concrete property information, the target vibration index and the mold property information, the target concrete vibration process is divided through a vibration analysis model to determine multiple vibration stages, and multiple stage vibration indexes and multiple stage concrete proportions of the multiple vibration stages are obtained; Based on the concrete property information and the mold property information, performing a stage mold damage analysis according to the concrete proportions of the multiple stages, and determining the maximum flow rates of the multiple stage vibrations; Taking the maximum flow rate of the vibration in the multiple stages as a constraint, optimizing the vibration parameters based on the vibration indicators in the multiple stages, and determining an optimized vibration scheme, wherein the optimized vibration scheme includes multiple optimized vibration parameters, the optimized vibration parameters correspond to the vibration stages one by one, and the vibration parameter is the compressed air flow rate; Performing the vibration operation in the multiple vibration stages according to the optimized vibration scheme, and collecting real-time pressure data through a pressure sensor during the vibration operation and feeding it back to a control unit; In the control unit, pressure deviation analysis is performed based on the PID control algorithm to generate feedback adjustment parameters, and the opening of the electric control valve is optimized and controlled according to the feedback adjustment parameters until the vibration operation is completed.

2. The intelligent vibration control method for shield concrete segments according to claim 1 is characterized in that: The vibration analysis model is used to divide the target concrete vibration process and determine multiple vibration stages, including: Taking the concrete property information as a material constraint and the mold property information as an equipment constraint, information retrieval is performed based on industrial big data networking to obtain a sample training data set, wherein the sample training data includes a sample vibration index and a sample vibration stage set; Divide the sample training data set into N equal parts, select N times without replacement to generate a first training set, and iterate and select N times to obtain N training sets; Using the N training sets to perform supervised training on the BP neural network respectively, to obtain N vibration analysis units that meet the expected convergence constraints, and to establish the vibration analysis model based on the N vibration analysis units, wherein the output of the vibration analysis model is the mode of the output results of the N vibration analysis units; The target vibration index is input into the vibration analysis model for stage division, and a plurality of vibration stages are output.

3. The intelligent vibration control method for shield concrete segments according to claim 1 is characterized in that: Based on the concrete property information and the mold property information, performing a stage mold damage analysis according to the concrete proportions of the multiple stages, and determining the maximum flow rates of the multiple stage vibrations, including: Based on the digital twin technology, vibration simulation modeling is performed according to the concrete property information and the mold property information to generate a vibration twin model; Selecting a first vibration stage from the multiple vibration stages, and obtaining a first vibration duration and a first-stage concrete ratio of the first vibration stage, wherein the first-stage concrete ratio refers to a volume ratio of concrete in the mold at the end of the first vibration stage; For the purpose of being less than the upper limit of mold damage, based on the first vibration duration and the first stage concrete ratio, a vibration simulation is performed through the vibration twin model to determine a first maximum vibration parameter, wherein the first maximum vibration parameter includes a first vibration frequency and a first vibration amplitude; A first-stage vibration maximum flow rate is determined based on the first vibration frequency and the first vibration amplitude, and is added to multiple-stage vibration maximum flow rates.

4. The intelligent vibration control method for shield concrete segments according to claim 3 is characterized in that: Determining a maximum flow rate of vibration in the first stage based on the first vibration frequency and the first vibration amplitude includes: Reading vibration control parameters of the pneumatically attached vibrator, and establishing a first mapping relationship between the vibration control parameters and the compressed air flow rate; Based on the first mapping relationship, a first compressed air flow rate is determined according to the first vibration frequency and the first vibration amplitude, and the first compressed air flow rate is set as the maximum flow rate of the first stage vibration.

5. The intelligent vibration control method for shield concrete segments according to claim 4 is characterized in that: Taking the maximum flow rate of the vibration in the multiple stages as a constraint, optimizing the vibration parameters based on the vibration indicators in the multiple stages, and determining an optimized vibration scheme include: Selecting a first vibration stage from the multiple vibration stages, obtaining a first-stage vibration maximum flow rate and a first-stage vibration index of the first vibration stage, wherein the first-stage vibration index includes a first density index, a first uniformity index, and a first porosity index; Obtaining a flow rate regulation threshold of the electric regulating valve, with the constraint that the flow rate is less than the maximum flow rate of the first stage of vibration, randomly selecting multiple flow rates within the flow rate regulation threshold, and determining multiple vibration control parameters for the multiple flow rates based on the first mapping relationship; The vibration twin model is used to respectively perform vibration simulation on the multiple vibration control parameters to determine multiple stage vibration simulation results, wherein each stage vibration simulation result includes stage density, stage uniformity and stage porosity; Using a vibration quality evaluation function, respectively evaluating the fitness of the vibration simulation results of the multiple stages, determining multiple fitnesses, and sorting the multiple flow values ​​from large to small according to the fitnesses, setting the flow value as an initial solution, and generating an initial solution sequence; The first M initial solutions in the initial solution sequence are set as optimal solutions, and the last N initial solutions are set as inferior solutions, wherein the sum of M and N is the number of initial solutions, and N is greater than M; Use M optimal solutions to randomly cluster N inferior solutions to generate M solution sets, and within the M solution sets, take the optimal solution as the optimization direction, update the inferior solution according to the preset step size, and obtain M updated solution sets, where the inferior solution in the updated solution set must be smaller than the maximum flow rate of the first stage of vibration; Identify M updated solution sets. If there is an inferior solution whose fitness is greater than or equal to the superior solution in the updated solution set, then use the inferior solution to replace the superior solution. Continue to iterate and optimize until the preset optimization number constraint is reached, then output the current M updated solution sets, and select the optimal solution of the optimal solution set among the current M updated solution sets to set as the first optimized vibration parameter, where the optimal solution set is the updated solution set with the largest sum of fitness; The first optimized vibration parameter is added to a plurality of optimized vibration parameters, and the optimized vibration scheme is composed according to the plurality of optimized vibration parameters in a stage order.

6. The intelligent vibration control method for shield concrete segments according to claim 5 is characterized in that: The method further comprises: The vibration quality evaluation function expression is: ； in, is the fitness of the vibration simulation results of the i-th stage, is the first weight, is the second weight, is the third weight, is the stage density of the vibration simulation result of the i-th stage, is the first density index, is the stage uniformity of the vibration simulation results of the i-th stage, is the first uniformity index, is the porosity of the stage i vibration simulation result, It is the first porosity indicator.

7. The intelligent vibration control method for shield concrete segments according to claim 1 is characterized in that: Based on the PID control algorithm, pressure deviation analysis is performed to generate feedback adjustment parameters, including: At a preset node, real-time pressure data is collected through a pressure sensor, and the real-time pressure data is fed back to a control unit, wherein the pressure sensor is arranged in a compressed air output pipeline; Acquire the current optimized vibration parameters under the preset node, determine the target pressure value based on the current optimized vibration parameters, and compare the target pressure value with the real-time pressure data to determine the real-time pressure deviation value; Based on the PID control algorithm, the real-time pressure deviation value is compensated and analyzed, and a feedback adjustment parameter is output, wherein the feedback adjustment parameter is a control parameter for adjusting the opening of the electric control valve.

8. An intelligent vibration control system for shield concrete segments, characterized in that: For implementing the steps of the method according to any one of claims 1 to 7, the system comprises: An information acquisition module, used to acquire concrete property information, target vibration index and mold property information, wherein the concrete property information includes mix ratio and slump, the target vibration index includes density index, uniformity index and porosity index, and the mold property information includes mold shape, mold size and mold material; A vibration process division module is used to divide the target concrete vibration process through a vibration analysis model based on the concrete property information, the target vibration index and the mold property information, determine multiple vibration stages, and obtain multiple stage vibration indexes and multiple stage concrete proportions of the multiple vibration stages; A mold damage analysis module, configured to perform a stage mold damage analysis based on the concrete property information and the mold property information and according to the concrete proportions of the multiple stages, and determine the maximum flow rates of vibration in the multiple stages; A vibration parameter optimization module is used to optimize the vibration parameters based on the vibration indicators of the multiple stages with the maximum flow rate of the vibration in the multiple stages as a constraint, and determine an optimized vibration scheme, wherein the optimized vibration scheme includes multiple optimized vibration parameters, the optimized vibration parameters correspond to the vibration stages one by one, and the vibration parameter is a compressed air flow rate; A pressure data feedback module is used to perform the vibration operation in the multiple vibration stages according to the optimized vibration scheme, and during the vibration operation, collect real-time pressure data through a pressure sensor and feed it back to the control unit; The opening optimization control module is used to perform pressure deviation analysis based on the PID control algorithm in the control unit, generate feedback adjustment parameters, and optimize the opening of the electric control valve according to the feedback adjustment parameters until the vibration operation is completed.

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