A control method and device for uniform feeding of steel fiber reinforced concrete for shield segments

Abstract

The application discloses a kind of shield segment steel fiber concrete uniform feeding control method and device, it is related to concrete feeding control technical field.The shield segment steel fiber concrete uniform feeding control method, the following steps are included: slurry fluidity quantification;Feeding mixing uniformity quantification;Feeding supplement uniformity quantification.The application is quantified by the slurry fluidity of the initial data of feeding obtained, to determine whether there is first viscidity optimization demand, then based on the distribution uniformity quantification of the feeding mixing data obtained, to determine whether there is second viscidity optimization demand, finally based on the supplement uniformity quantification of the feeding supplement data obtained, to determine whether there is third viscidity optimization demand, reach the effect of improving the interference control timeliness of corresponding steel fiber content in concrete feeding process, solve the problem that existing technology exists in the interference control timeliness of corresponding steel fiber content in shield segment concrete feeding process.

Description

Technical Field

[0001] This invention relates to the field of concrete feeding control technology, and in particular to a method and device for controlling the uniform feeding of steel fiber reinforced concrete for tunnel segments. Background Technology

[0002] The existing method for uniformly feeding steel fiber reinforced concrete (SFR) into tunnel segments comprises three stages: preparation, implementation, and finalization / optimization. Before feeding, initial values ​​for feeding parameters are preset for different areas based on the design dimensions and shape of the tunnel segment and historical production data. For example, in areas near the edges and corners of the mold, where concrete flow resistance is higher, the feeding speed is preset to be relatively slower, and the feeding amount is rationally allocated according to the area and expected filling difficulty. During feeding, laser displacement sensors are used to monitor the concrete filling status within the mold in real time, including filling height and density distribution. Based on changes in mold dimensions and the current filling status, the feeding amount in each area is dynamically adjusted using a preset dynamic adjustment model (such as a fuzzy logic model) to ensure uniform distribution of steel fibers in the concrete, thereby improving the strength and durability of the tunnel segment.

[0003] For example, the invention patent announcement CN109991945B discloses a combined control system for a batching plant and a concrete pump, comprising: a main controller; at least two secondary controllers connected to the main controller, each secondary controller including at least one batching plant controller and at least one concrete pump controller, each secondary controller being used to connect to and control a corresponding execution device, and also connected to and capable of controlling the execution device corresponding to at least one other secondary controller; if the main controller detects a fault in any secondary controller, the main controller designates at least one other secondary controller to control the execution device corresponding to the faulty secondary controller.

[0004] For example, the aggregate feeding control system, mixing plant, and control method announced in the invention patent announcement CN109407580B include: a data processing unit receiving the weight information of the intermediate silo storing aggregate collected by the sensor acquisition unit and transmitting it to the data analysis and management unit; the data analysis and management unit determining whether the weight of the intermediate silo has reached a preset value and whether the feeding time is within the preset feeding time range of the intermediate silo; transmitting the determination information to the silo door control module, and when the determination information is that the weight of the intermediate silo has reached the preset value and the feeding time is within the preset feeding time range of the intermediate silo, the silo door control module controls the intermediate silo door to close.

[0005] In existing technologies, monitoring of steel fiber content during material feeding is mostly done in stages or through sampling. For example, due to feeding issues, the actual content may be less than the set steel fiber content. Because the fixed-parameter control system has a slow adjustment response, it cannot detect and adjust in a timely manner. Assuming the control system is set to adjust the feeding amount by 0.1% each time, when it detects that the steel fiber content in a certain area is 0.3% lower, the control system needs to make three adjustments to reach the target, with time intervals between each adjustment. This results in the problem of insufficient steel fiber distribution in that area remaining unresolved for a considerable period. Furthermore, different filling stages and areas may... Different mixing modes may be required. In the edges and corners of the mold, a single mixing mode may not be able to disperse the steel fibers sufficiently, resulting in inconsistent steel fiber concentration in these areas compared to the central area. In addition, for small molds, a shorter feeding time and a smaller feeding amount may be sufficient to ensure uniform distribution of steel fibers. However, for large molds, if the feeding parameters are still used for small molds, it is obviously impossible to meet the requirement of uniform steel fiber distribution. If the feeding system continues to feed according to the parameters of small molds, it will lead to a decrease in steel fiber concentration and uneven distribution. There is a problem of low timeliness in controlling the interference of steel fiber content during the feeding of concrete for shield tunnel segments. Summary of the Invention

[0006] This application provides a method and apparatus for controlling the uniform feeding of steel fiber reinforced concrete for tunnel segments, which solves the problem of low timeliness in controlling interference with the steel fiber content during the concrete feeding process of tunnel segments in the prior art, and improves the timeliness of controlling interference with the steel fiber content during the concrete feeding process.

[0007] This application provides a method for controlling the uniform feeding of steel fiber reinforced concrete for tunnel lining segments, including the following steps: S1, in the initial feeding stage, the slurry fluidity of a specified batch of concrete is quantified based on the acquired initial feeding data, and it is determined whether there is a first viscosity optimization requirement. The initial feeding stage refers to the operation from the start of adding steel fibers to the specified batch of concrete until all steel fibers are added. The first viscosity optimization requirement means improving the uniformity of steel fiber distribution in the specified batch of concrete by optimizing the water-reducing agent content or the initial feeding speed; S2, in the feeding and mixing stage, the uniformity of the distribution of the specified batch of concrete is assessed based on the acquired feeding and mixing data. Quantification is performed, and it is determined whether there is a second viscosity optimization requirement. The feeding and mixing stage represents the operation step when the slurry fluidity meets the feeding and mixing requirements. The second viscosity optimization requirement means improving the distribution uniformity of steel fibers in the feeding and mixing stage through stacking optimization or sparse optimization. S3, in the feeding and replenishment stage, the replenishment uniformity of a specified batch of concrete is quantified based on the acquired feeding and replenishment data, and it is determined whether there is a third viscosity optimization requirement. The feeding and replenishment stage represents the operation step when the distribution uniformity meets the feeding and replenishment requirements. The third viscosity optimization requirement means improving the distribution uniformity of steel fibers in the feeding and replenishment stage through mixing paddle speed optimization and mixing time optimization.

[0008] This application provides a control device for uniformly feeding steel fiber reinforced concrete for tunnel segments, comprising: a laser rangefinder, a high-precision electromagnetic flowmeter, an electromagnetic induction sensor, a laser scanner, an encoder, a Hall sensor, and a PLC operating terminal; the laser rangefinder is used to monitor the concrete slump in real time; the high-precision electromagnetic flowmeter is used to measure the amount of water-reducing agent in real time; the electromagnetic induction sensor is used to monitor the steel fiber concentration in real time; the laser scanner is typically used to collect the area of ​​missing steel fibers and the steel fiber concentration deviation in real time; the encoder is used to monitor the feeding speed in real time; the Hall sensor is used to monitor the rotation speed of the mixing paddle in real time; and the PLC operating terminal is used to control the rotation speed of the mixing paddle, the feeding amount, the mixing time, and the feeding speed through a built-in PID control algorithm.

[0009] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0010] 1. First, by acquiring initial feeding data and quantifying the slurry fluidity in the initial feeding stage, the system can automatically determine whether the first viscosity optimization is needed, achieving precise adjustment of the water-reducing agent, ensuring a smooth slurry, and avoiding problems such as uneven mixing and steel fiber agglomeration caused by excessively high initial feeding viscosity, thus improving the initial uniformity of concrete. Then, in the feeding and mixing stage, based on the quantified distribution uniformity of the mixing data, the system dynamically determines whether the second viscosity optimization is needed. By adjusting the mixing paddle speed and mixing time in real time, the system improves the dispersion uniformity of materials such as steel fibers in concrete, reducing strength fluctuations caused by fiber accumulation or sparseness. Finally, in the feeding and replenishment stage, by quantifying the replenishment uniformity, the system determines whether the third viscosity optimization is needed, automatically adjusting the mixing parameters to precisely control the dispersion degree of the replenishment materials, improving the consistency of material mixing in the replenishment stage, reducing local segregation problems caused by uneven feeding, and ultimately improving the overall quality stability and production efficiency of the shield tunnel segment concrete.

[0011] 2. By obtaining the slump of a specified batch of concrete at the end of the initial time period and comparing it with a preset value, a slump difference coefficient is calculated. Simultaneously, the amount of water-reducing agent used at this time is obtained and compared with a preset amount to obtain a relative difference coefficient. These two coefficients are then averaged to obtain a slurry uniformity index, thereby quantifying the impact of initial material input data on slurry flowability. By simultaneously considering these two key factors—slump and water-reducing agent usage—and averaging the difference coefficients, the effect of initial material input on slurry flowability can be assessed more comprehensively and accurately. This allows for the timely detection of flowability anomalies in the early stages of production, reducing quality fluctuations and thus minimizing production delays caused by flowability issues.

[0012] 3. By proportionally processing the steel fiber concentration deviation and missing steel fiber area in the mold feeding area with preset data in the database, the corresponding ratio values ​​are calculated. These two ratio results are then measured and finally harmonic averaged to obtain the replenishment uniformity interference value, reflecting the degree of interference in replenishment uniformity. By comprehensively considering multiple key factors such as steel fiber concentration deviation and missing area, and using calculation methods such as proportional processing, measurement factors, and harmonic averaging, the degree of interference in replenishment uniformity can be more accurately quantified. This helps production personnel to promptly detect problems in the replenishment process, quickly adjust replenishment strategies, avoid uneven distribution of steel fibers in concrete, and effectively improve the uniformity of steel fiber distribution in concrete. Attached Figure Description

[0013] Figure 1 A flowchart illustrating a method for controlling the uniform feeding of steel fiber reinforced concrete for tunnel segments, provided in this application embodiment;

[0014] Figure 2 A flowchart for quantifying slurry flowability and determining the first viscosity optimization provided in the embodiments of this application;

[0015] Figure 3 A flowchart for quantifying the uniformity of material feeding and mixing and determining the second viscosity optimization provided in the embodiments of this application;

[0016] Figure 4 The flowchart illustrates the process for quantifying the uniformity of material addition and determining the third viscosity optimization in the embodiments of this application. Detailed Implementation

[0017] This application provides a method and apparatus for controlling the uniform feeding of steel fiber reinforced concrete for tunnel lining segments. This solves the problem of low timeliness in controlling interference related to the steel fiber content during the concrete feeding process in existing technologies. By quantifying the slurry flowability of a specified batch of concrete based on the acquired initial feeding data in the initial feeding stage, and determining whether there is a first viscosity optimization requirement, and then quantifying the distribution uniformity of the specified batch of concrete based on the acquired feeding and mixing data in the feeding and mixing stage, and determining whether there is a second viscosity optimization requirement, and finally quantifying the uniformity of the supplementary feeding of a specified batch of concrete based on the acquired supplementary feeding data in the feeding and replenishing stage, and determining whether there is a third viscosity optimization requirement, the timeliness of interference control related to the steel fiber content during the concrete feeding process is improved.

[0018] The technical solution in this application is to solve the above problems, and the overall approach is as follows:

[0019] By quantifying the fluidity of the slurry at the initial feeding stage to determine whether there is a first viscosity optimization requirement, then quantifying the distribution uniformity during the feeding and mixing stage to determine whether there is a second viscosity optimization requirement, and finally quantifying the uniformity of the supplementary feeding stage to determine whether there is a third viscosity optimization requirement, the timeliness of interference control for the corresponding steel fiber content during concrete feeding is improved.

[0020] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0021] like Figure 1 The diagram shows a flowchart of a method for controlling the uniform feeding of steel fiber reinforced concrete for tunnel segments according to an embodiment of this application. The method includes the following steps:

[0022] S1, in the initial feeding stage, the slurry fluidity of the specified batch of concrete is quantified based on the acquired initial feeding data, and it is determined whether there is a first viscosity optimization requirement. The initial feeding stage refers to the operation link from the start of adding steel fibers to the specified batch of concrete until all steel fibers are added. The first viscosity optimization requirement means improving the uniformity of steel fiber distribution in the specified batch of concrete by optimizing the water-reducing agent content or the initial feeding speed. The initial feeding data includes concrete slump and water-reducing agent dosage.

[0023] S2, during the feeding and mixing stage, the uniformity of the distribution of a specified batch of concrete is quantified based on the acquired feeding and mixing data. At the same time, it is determined whether there is a second viscosity optimization requirement. The feeding and mixing stage refers to the operation step corresponding to when the slurry fluidity meets the feeding and mixing requirements. The second viscosity optimization requirement refers to improving the uniformity of steel fiber distribution during the feeding and mixing stage through stacking optimization or sparse optimization. The feeding and mixing data includes concrete consistency and steel fiber concentration.

[0024] S3, in the material feeding and replenishment stage, the uniformity of replenishment of a specified batch of concrete is quantified based on the acquired material feeding and replenishment data. At the same time, it is determined whether there is a third viscosity optimization requirement. The material feeding and replenishment stage represents the operation step corresponding to when the distribution uniformity meets the material feeding and replenishment requirements. The third viscosity optimization requirement means improving the distribution uniformity of steel fibers in the material feeding and replenishment stage by optimizing the mixing paddle speed and mixing time. The material feeding and replenishment data includes the steel fiber concentration deviation, which reflects the degree of difference between the steel fiber concentration at the end of the material feeding and replenishment period and the steel fiber missing area, which is obtained by converting the mold area area, pixels and actual size.

[0025] In this embodiment, the mold area is first selected in the image, and its pixel area is measured. The actual size of the mold area is then calculated by measuring the actual dimensions of the mold area. Next, the pixel area of ​​the steel fiber missing area is measured, and this area is multiplied by the actual size of the unit pixel to obtain the actual area of ​​the missing steel fiber. This example quantifies uniformity and determines optimization needs based on corresponding data in three key stages: initial feeding, mixing, and supplementary feeding. This phased, multi-method control approach can more accurately and comprehensively improve the uniformity of steel fiber distribution in concrete, effectively enhancing the uniformity of steel fiber distribution, thereby improving the quality and performance of steel fiber concrete for tunnel segments, strengthening the overall strength and stability of the tunnel segments, and effectively improving the timeliness of interference control regarding the steel fiber content during concrete feeding.

[0026] Furthermore, based on the acquired initial feeding data, the slurry fluidity of a specified batch of concrete is quantified. Specifically, the slump of the specified batch of concrete at the end of the initial feeding period is obtained, and a preset concrete slump is simultaneously retrieved from the database. A difference comparison is then performed (i.e., the ratio of the acquired concrete slump to the preset concrete slump) to obtain the concrete slump difference coefficient. The preset concrete slump is represented by the summation and averaging of historical concrete slumps at the end of historical initial feeding periods in the database. The amount of water-reducing agent used in the specified batch of concrete at the end of the initial feeding period is also obtained, and simultaneously... The preset water-reducing agent dosage is obtained from the database, and a relative difference comparison is performed (i.e., the absolute value of the difference between the obtained water-reducing agent dosage and the preset water-reducing agent dosage is given by the preset water-reducing agent dosage). The preset water-reducing agent dosage is represented by the sum and average of the historical water-reducing agent dosages at the end of the historical material feeding period in the database. The obtained concrete slump difference coefficient and the relative difference coefficient of water-reducing agent dosage are harmonized and averaged to obtain the slurry uniformity index. The slurry uniformity index represents the quantitative data of the influence of the initial material feeding data on the slurry fluidity of a specified batch of concrete.

[0027] In this embodiment, the slump difference coefficient and the relative difference coefficient of water-reducing agent dosage are harmonized and averaged to take into account the synergistic effect of concrete workability (slump) and chemical regulation (water-reducing agent). This dual-parameter synergistic control avoids misjudgment caused by the distortion of a single parameter, that is, it balances the nonlinear influence of the two parameters and improves the accuracy of fluidity assessment. The preset value constructed based on the average of historical data can be automatically iterated with production accumulation to form a closed-loop optimization mechanism and continuously improve the mix design. The unified quantitative index provides a comparable benchmark for different batches and different production lines, which helps to improve the stability of concrete quality.

[0028] like Figure 2 The diagram shows a flowchart of the slurry fluidity quantification and first viscosity optimization determination provided in an embodiment of this application. The specific design logic is as follows: First, initial feeding data is obtained; then, the slurry uniformity index conditions are determined. If different conditions are met, different measures are taken: the first condition is to adjust the water-reducing agent content; the second condition is to adjust the water-reducing agent content and the initial feeding speed; the third condition is to conduct a first trial mixing test, and then determine whether the slurry uniformity index is qualified. If qualified, the feeding and mixing stage begins; if not qualified, an abnormal slurry uniformity warning is issued. This design, through step-by-step judgment and adjustment, ensures that the uniformity of steel fibers in the concrete meets the requirements in the initial feeding stage, guaranteeing the smooth progress of subsequent production stages.

[0029] Further understanding is needed regarding the determination of whether there is a first viscosity optimization requirement. Specifically, if the obtained slurry uniformity index meets the first difference condition, then the actual amount of water-reducing agent added is obtained based on the standard score of the deviation of the obtained first slurry uniformity index to reduce slurry viscosity and prevent steel fiber clumping. The first difference condition means that the minimum value of the historical slurry uniformity index in the database is greater than the obtained slurry uniformity index. The actual amount of water-reducing agent added represents the result output by inputting the standard score of the deviation of the first slurry uniformity index into the water-reducing agent adjustment linear regression model. The standard score of the deviation of the first slurry uniformity index represents the ratio of the difference between the obtained first slurry uniformity index deviation and the average value of the historical slurry uniformity index in the database to the standard deviation of the historical slurry uniformity index. The first slurry uniformity index deviation represents the difference between the minimum value of the historical slurry uniformity index and the obtained slurry uniformity index.

[0030] If the obtained slurry uniformity index meets the second difference condition, the actual reduction in water-reducing agent and the actual reduction in the initial feeding speed of steel fibers are obtained based on the standard score of the deviation of the obtained second slurry uniformity index. This is to increase the viscosity of the slurry and reduce the risk of steel fiber settling. The second difference condition indicates that the obtained slurry uniformity index is greater than the maximum value of the historical slurry uniformity index in the database. The actual reduction in water-reducing agent and the actual reduction in the initial feeding speed of steel fibers are the results output by inputting the distribution of the standard score of the deviation of the second slurry uniformity index into the linear regression model for water-reducing agent adjustment and the linear regression model for feeding speed adjustment. The standard score of the deviation of the second slurry uniformity index is the ratio of the difference between the obtained deviation of the second slurry uniformity index and the average value of the historical slurry uniformity index in the database to the standard deviation of the historical slurry uniformity index. The deviation of the second slurry uniformity index is the difference between the obtained slurry uniformity index and the maximum value of the historical slurry uniformity index.

[0031] After optimization to meet the difference conditions, a first concrete trial mixing test instruction is sent. If the slurry uniformity index re-acquired after the first concrete trial mixing test is within the allowable range of the slurry uniformity index in the database, the feeding and mixing stage is entered; otherwise, an abnormal steel fiber flow warning is issued. The first concrete trial mixing test instruction is used to prompt the preset personnel to conduct a concrete trial mixing test of a preset scale (set by the preset personnel) based on the optimized initial feeding data. The allowable range of the slurry uniformity index represents the closed interval corresponding to the maximum and minimum values ​​of the historical slurry uniformity index at the end of the historical initial feeding period in the database.

[0032] Specifically, the standard scores of flowability index deviations and the corresponding actual adjustments of water-reducing agent in historical batches are used as sample data and input into the univariate linear regression model in the linear regression model for training. The flowability-water-reducing agent adjustment linear regression model is obtained by training based on the least squares method. The standard scores of the first slurry uniformity index deviations of the current batch are input into the trained flowability-water-reducing agent adjustment linear regression model, and the actual increase in water-reducing agent is output. The amount of water-reducing agent used in the current batch is increased in real time based on the actual increase in water-reducing agent obtained by the dynamic feeding algorithm.

[0033] Similarly, the dynamic feeding algorithm reduces the amount of water-reducing agent used in the current batch in real time based on the actual reduction in water-reducing agent, thereby dynamically adjusting the viscosity of the slurry. Simultaneously, the standard score of the fluidity index deviation and the corresponding reduction in the actual initial feeding speed of steel fibers from historical batches are used as sample data and input into the multiple linear regression model for training. A fluidity-feeding speed adjustment linear regression model is obtained through training using the particle swarm optimization algorithm. The standard score of the second slurry uniformity index deviation of the current batch is input into the trained fluidity-feeding speed adjustment linear regression model, which outputs the reduction in the actual initial feeding speed of steel fibers. The dynamic feeding algorithm then reduces the initial feeding speed of steel fibers in the current batch in real time based on this reduction in the actual initial feeding speed of steel fibers.

[0034] It should be added that, assuming the initial concrete slump is 30mm, which is lower than the preset average concrete slump (e.g., 45mm), the slump difference coefficient is 0.67, indicating poor slurry fluidity. At the same time, the initial water-reducing agent dosage is 4.627kg, which is lower than the preset average water-reducing agent dosage (e.g., 5kg), and the relative difference coefficient of water-reducing agent dosage is 0.0754. Through blending and averaging, the slurry uniformity index is obtained, which reflects the influence of the initial material feeding data on the slurry fluidity.

[0035] If the slurry uniformity index meets the first variability condition (i.e., below the historical minimum), the system calculates the actual increase in water-reducing agent using a linear regression model. For example, an increase of 0.3 kg is used to reduce viscosity. After optimization, if the slurry uniformity index in the trial mixing test is within the allowable range, the system proceeds to the material feeding and mixing stage. Conversely, if the slurry uniformity index is abnormal, an early warning is issued, prompting further adjustments. This process, through quantitative indicators and dynamic adjustments, ensures the stability of concrete quality and optimizes the material feeding process.

[0036] In this embodiment, the flowability anomalies are accurately identified through the difference condition, avoiding the blindness of empirical adjustments and ensuring that the slurry viscosity always matches the steel fiber dispersion requirements. At the same time, the quantitative adjustment amount is output by combining the linear regression model, avoiding empirical and rough adjustment and significantly improving the stability of slurry performance. The trial mixing test and allowable range verification form a closed loop verification, which significantly reduces the risk of steel fiber clumping or settling due to flowability loss, and improves the stability of concrete quality. Automated deviation calculation and model prediction reduce manual calculation errors, shorten the adjustment cycle, and are suitable for industrial continuous production scenarios.

[0037] like Figure 3 The diagram shows a flowchart of the quantitative determination of material mixing uniformity and the second viscosity optimization judgment provided in an embodiment of this application. The specific design logic is as follows: First, the material mixing data is obtained, and the mixing speed of the mixing paddle is determined accordingly. If the speed needs to be increased, the viscosity can be reduced; if the speed is decreased, the viscosity will increase. If the mixing is uniform, the steel fiber concentration is checked. If the concentration is abnormal, accumulation is optimized and a second trial mixing test is conducted; if it is sparse, sparse optimization is conducted. Then, a third trial mixing test is conducted to check the steel fiber concentration again. If it is qualified, the material addition stage is entered; if it is not qualified, optimization continues. This logic ensures that the mixing quality meets the standards and guarantees the stability of concrete performance by dynamically adjusting the speed and optimizing the concentration.

[0038] Specifically, the uniformity of concrete distribution in a specified batch is quantified based on the acquired material feeding and mixing data. This involves: determining the rotation speed based on the concrete consistency in the mold feeding area and a preset concrete consistency in the database; if the rotation speed adjustment result is a first rotation speed adjustment result, the increase in mixing paddle speed is mapped in the database based on the acquired first concrete consistency deviation, which prompts the drive motor to increase the mixing paddle speed based on the acquired increase to reduce slurry resistance. The first rotation speed adjustment result indicates that the acquired maximum concrete consistency (i.e., the maximum value corresponding to the concrete consistency in the mold feeding area) is greater than the preset first concrete consistency, and the first concrete consistency deviation represents the difference between the acquired maximum concrete consistency and the preset first concrete consistency; if the rotation speed adjustment result is a second rotation speed adjustment result, the increase in mixing paddle speed is mapped in the database based on the acquired second concrete consistency deviation. The amount of reduction in the stirring paddle speed is used to prompt the drive motor to reduce the stirring paddle speed based on the obtained amount of reduction in stirring paddle speed to increase the consistency of the slurry. The second speed adjustment judgment result indicates that the obtained minimum concrete consistency (i.e., the minimum value corresponding to the concrete consistency in the mold feeding area) is less than the preset second concrete consistency. The second concrete consistency deviation indicates the difference between the preset second concrete consistency and the obtained minimum concrete consistency. If the speed adjustment judgment result is the third speed adjustment judgment result, it is recorded as uniform distribution and it is determined whether there is a second viscosity optimization requirement. The third speed adjustment judgment result indicates that the obtained concrete consistency is within the preset allowable range of concrete consistency. The preset concrete consistency includes the preset first concrete consistency (usually set to 15%), the preset second concrete consistency (usually set to 10%), and the preset allowable range of concrete consistency (usually set to 10%-15%).

[0039] The drive motor refers to the core power component in the mixing equipment that drives the mixing paddle to rotate, such as a three-phase asynchronous motor or a servo motor. It receives control signals and adjusts its output power through a frequency converter or servo driver. The acquired first concrete consistency deviation is converted into an increase in mixing paddle speed using a pre-stored mapping table in the database. The drive motor, through its built-in PID (Proportional-Integral-Derivative) control algorithm, calculates the corresponding mixing paddle speed control amount based on the PID formula to increase the frequency converter's output frequency or the motor current, thereby reducing the slurry resistance. Similarly, the drive motor, through its built-in PID control algorithm, calculates the corresponding mixing paddle speed control amount based on the PID formula to decrease the mixing paddle speed, thereby reducing the frequency converter's output frequency or the motor current, thus improving mixing uniformity and adapting to consistency fluctuation scenarios.

[0040] This example uses real-time consistency feedback and closed-loop speed control to precisely match the flowability requirements of different batches of concrete, avoiding the lag of manual parameter adjustment. This ensures uniform concrete distribution within the mold, reduces defects such as honeycomb and segregation caused by consistency fluctuations, and improves structural strength and durability. Automated adjustment shortens mixing time, reduces energy consumption, and is suitable for industrial continuous production scenarios. Allowable range verification and secondary optimization mechanisms ensure quality stability, are suitable for industrial continuous production scenarios, and shorten the commissioning cycle.

[0041] In addition, the determination of whether there is a second viscosity optimization requirement is as follows: If the steel fiber concentration in the mold feeding area is greater than the historical maximum steel fiber concentration in the database, the corresponding mold feeding area is marked as a local accumulation area and accumulation optimization is performed. Accumulation optimization includes feeding speed optimization to reduce the steel fiber feeding speed to reduce the accumulation of steel fibers in the local accumulation area, and first feeding amount optimization to reduce the steel fiber concentration in the local accumulation area; If the steel fiber concentration in the mold feeding area is within the allowable range of steel fiber concentration in the database, the corresponding mold feeding area is marked as a uniform feeding area and enters the feeding supplementation stage; If the steel fiber concentration in the mold feeding area is less than the historical minimum steel fiber concentration in the database, the corresponding mold feeding area is marked as a local sparse area and sparse optimization is performed. Sparse optimization includes stirring paddle speed optimization to enhance slurry flow to promote the diffusion of steel fibers to the local sparse area, and second feeding amount optimization to increase the feeding amount in the local sparse area to increase the steel fiber concentration.

[0042] The stacking optimization specifically involves: based on the mapping relationship between the obtained first standard score of steel fiber concentration deviation and the decrease values ​​of feeding speed and feeding amount in the database, the actual decrease values ​​of feeding speed and feeding amount are obtained. These values ​​are used to prompt the PLC (Programmable Logic Controller) to increase the steel fiber concentration based on the obtained actual decrease values ​​of feeding speed and feeding amount. The first standard score of steel fiber concentration deviation represents the ratio of the difference between the obtained first steel fiber concentration deviation and the historical average value of steel fiber concentration in the database to the standard deviation of historical steel fiber concentration. The first steel fiber concentration deviation represents the difference between the obtained steel fiber concentration and the historical maximum value of steel fiber concentration. After the stacking optimization is completed, a second concrete trial mixing test command is sent. If the steel fiber concentration re-obtained after the second concrete trial mixing test is within the allowable range of steel fiber concentration in the database, the stacking optimization is completed and the feeding supplementation stage begins. The allowable range of steel fiber concentration represents the closed interval corresponding to the maximum and minimum values ​​of historical steel fiber concentration in the mold feeding area at the end of the historical feeding and mixing period in the database.

[0043] The sparse optimization process involves: based on the mapping relationship between the obtained second steel fiber concentration deviation standard score and the increase values ​​of the agitator speed and the feed amount in the database, the actual increase values ​​of the agitator speed and the feed amount are obtained. These values ​​are used to prompt the PLC operator to reduce the steel fiber concentration based on the obtained actual increase values ​​of the agitator speed and the feed amount. The second steel fiber concentration deviation standard score represents the ratio of the difference between the obtained second steel fiber concentration deviation and the historical average steel fiber concentration in the database to the standard deviation of the historical steel fiber concentration. The second steel fiber concentration deviation represents the difference between the historical minimum steel fiber concentration and the obtained steel fiber concentration. After the sparse optimization is completed, a third concrete trial mixing test command is sent. If the steel fiber concentration obtained again after the third concrete trial mixing test is within the allowable range of the steel fiber concentration in the database, the sparse optimization is completed and the material feeding and replenishment stage begins.

[0044] It should be added that, assuming that during the feeding and mixing process, if the maximum concrete consistency in the mold feeding area is monitored to be 18%, which is higher than the preset first concrete consistency of 15%, it is determined as the first speed adjustment judgment result. The system uses a mapping table to convert the first concrete consistency deviation of 3% (18%-15%) into an increase of 5 revolutions / minute in the mixing paddle speed. The drive motor increases its speed accordingly to reduce the slurry resistance. After optimization, if the trial mixing test shows that the steel fiber concentration is within the allowable range (e.g., 10%-15%), the stacking optimization is completed and the feeding and replenishment stage begins.

[0045] Conversely, if the minimum concrete consistency is detected to be 8%, which is lower than the preset second concrete consistency of 10%, it is determined as the second speed adjustment result. The system converts the second concrete consistency deviation of 2% (10%-8%) into a reduction of 3 revolutions per minute in the mixing paddle speed, and the drive motor accordingly reduces its speed to increase the consistency of the slurry. If the concrete consistency is within the range of 10%-15%, it is determined as the third speed adjustment result, and the steel fiber concentration is further checked. If the steel fiber concentration in a certain area is higher than the historical maximum value, the system performs stacking optimization, reducing the feeding speed and amount; if it is lower than the historical minimum value, it performs sparse optimization, increasing the mixing speed and feeding amount until the steel fiber concentration meets the requirements.

[0046] In this embodiment, the PLC operating terminal refers to the control terminal of the mixing equipment based on a programmable logic controller (PLC). It is responsible for receiving the first and second standard scores of steel fiber concentration deviation, executing the PID control algorithm, and outputting control signals to the feeding equipment (such as a screw conveyor or vibrating feeder) to achieve automated adjustment of the feeding speed and quantity. Specifically:

[0047] The first standard score of steel fiber concentration deviation is converted into a decrease in feeding speed and a decrease in feeding amount using a database mapping table. The PLC terminal executes a preset PID control algorithm to reduce the speed of the feeding equipment (e.g., by reducing the inverter frequency by 10%), thereby reducing the amount of material fed per unit time. Similarly, the second standard score of steel fiber concentration deviation is converted into an increase in agitator speed and an increase in feeding amount using the database mapping table. The PLC terminal executes a preset PID control algorithm to increase the agitator speed, thereby reducing the amount of material fed per unit time. Through coordinated control of "deceleration + reduction," the concentration of steel fibers in the slurry is rapidly increased, preventing local aggregation or sedimentation.

[0048] like Figure 4 The diagram shows a flowchart of the quantitative analysis of the uniformity of material addition and the third viscosity optimization judgment provided in this application embodiment. The specific design logic is as follows: First, calculate the difference in uniformity of material addition; then, determine whether the uniformity of material addition is qualified. If qualified, the uniformity of material addition is directly confirmed to be qualified; if not qualified, adjust the mixing speed and mixing time, and then conduct a fourth trial mixing test. After that, determine whether the difference in uniformity of material addition is qualified again. If qualified, the optimization of uniformity of material addition is completed; if not qualified, the parameters need to be readjusted or the cause needs to be further analyzed. This logic, through repeated verification and adjustment, ensures that the uniformity of the material addition stage meets the requirements, thus guaranteeing the stability and reliability of the final concrete quality.

[0049] The method involves quantifying the uniformity of concrete replenishment for a specified batch based on the acquired replenishment data. Specifically, at the end of the replenishment period, the replenishment data in the mold replenishment area is proportionally processed against the maximum allowable replenishment data in the database to obtain the proportional processing results. Simultaneously, the replenishment data measurement factors are used to measure each proportional processing result, followed by harmonic averaging to obtain the replenishment uniformity interference value. The maximum allowable replenishment data includes the maximum allowable steel fiber concentration deviation and the maximum allowable steel fiber missing area. The proportional processing results include the steel fiber concentration deviation ratio and the steel fiber missing area ratio. The steel fiber concentration deviation ratio indicates the steel fiber concentration deviation in the mold replenishment area. The steel fiber concentration deviation at the end of the replenishment period is the ratio of the maximum allowable steel fiber concentration deviation in the database. The steel fiber concentration deviation represents the absolute value of the difference between the steel fiber concentration at the end of the replenishment period and the steel fiber concentration at the beginning of the replenishment period (i.e., the steel fiber concentration at the end of the feeding and mixing period). The steel fiber missing area ratio represents the ratio of the steel fiber missing area in the corresponding mold feeding area at the end of the replenishment period to the maximum allowable steel fiber missing area in the database. The replenishment data measurement factors include the steel fiber concentration deviation measurement factor and the steel fiber missing area measurement factor. The replenishment uniformity interference value represents the quantitative data of the degree of interference of the replenishment data on the uniformity of the corresponding steel fiber distribution during the replenishment process.

[0050] The specific constraint expression for the uniformity interference value Y of the supplementary injection is as follows: in, In the formula, Y represents the uniformity interference value of the specified batch of concrete in the mold feeding area at the end of the feeding and replenishment period; Y1 represents the steel fiber concentration deviation ratio of the steel fiber in the mold feeding area at the end of the feeding and replenishment period; Y2 represents the steel fiber missing area ratio of the specified batch of concrete in the corresponding mold feeding area at the end of the feeding and replenishment period; a represents the steel fiber concentration deviation measurement factor; N represents the steel fiber concentration deviation in the mold feeding area at the end of the feeding and replenishment period; DN represents the maximum allowable steel fiber concentration deviation; b represents the steel fiber missing area measurement factor; M represents the steel fiber missing area in the corresponding mold feeding area at the end of the feeding and replenishment period; DM represents the maximum allowable steel fiber missing area. The units for the steel fiber missing area and the maximum allowable steel fiber missing area are the same, both in meters (m). 2 The units for the steel fiber concentration deviation and the maximum permissible steel fiber concentration deviation are the same, both being kg / m³. 3 The maximum permissible steel fiber concentration deviation is represented by the sum of the average values ​​of the historical steel fiber concentration deviations at the end of each historical feeding and replenishment period in the database. The maximum permissible steel fiber missing area is represented by the sum of the average values ​​of the historical steel fiber missing areas at the end of each historical feeding and replenishment period in the database.

[0051] The database stores preset measurement factors closely related to the interference value of the replenishment uniformity. These measurement factors establish a predefined mapping relationship with the corresponding steel fiber concentration deviation and steel fiber missing area. It is worth noting that this mapping is not arbitrarily set; it can be a one-to-one correspondence or a many-to-one relationship. For example, in practical applications, when it is necessary to evaluate the replenishment uniformity corresponding to the replenishment stage of a specified batch of concrete, the real-time acquired steel fiber concentration deviation and steel fiber missing area can be directly input into this preset mapping relationship. This allows for the rapid and accurate acquisition of steel fiber concentration deviation measurement factors and steel fiber missing area measurement factors that match the steel fiber concentration deviation and steel fiber missing area.

[0052] Importantly, to ensure consistency and comparability of the assessments, the values ​​of the steel fiber concentration deviation metric and the steel fiber missing area metric in this example are limited to between 0 and 1, and their sum is 1.

[0053] In this embodiment, the interference value of the uniformity of the supplementation changes inversely with the increase of the steel fiber concentration deviation and the area of ​​missing steel fibers. Their mutual influence is as follows: the increase of the steel fiber concentration deviation will aggravate the local concentration unevenness, causing the distribution density of steel fibers in concrete to fluctuate, thereby expanding the sparse area; while the expansion of the area of ​​missing steel fibers will in turn amplify the negative impact of the concentration deviation, forming a "concentration-sparseness" cycle.

[0054] By dynamically adjusting the steel fiber concentration deviation measurement factor and the steel fiber missing area measurement factor through a preset mapping relationship, the system can quantify and suppress this collaborative interference in real time. This helps to quickly identify and correct abnormal fluctuations in steel fiber content during the material feeding and replenishment stage, ensuring that the uniformity of concrete in the mold meets the dynamic standard. This effectively solves the problem of low timeliness in controlling steel fiber content interference during the concrete feeding process of shield tunnel segments in the existing technology, and realizes fully automated closed-loop control.

[0055] Furthermore, to determine if a third viscosity optimization requirement exists, the following steps are taken: the degree of difference between the obtained replenishment uniformity interference value and the preset replenishment uniformity interference value in the database is recorded as the replenishment uniformity difference degree; if the obtained replenishment uniformity difference degree meets the replenishment uniformity optimization conditions, it is determined that the replenishment uniformity is unqualified and replenishment uniformity optimization is performed. Meeting the replenishment uniformity optimization conditions means that the obtained replenishment uniformity interference value is greater than the preset replenishment uniformity interference value. Replenishment uniformity optimization includes impeller speed optimization and stirring time optimization. Optimization means increasing the speed of the mixing paddle to enhance the turbulence intensity inside the slurry. Optimization of the mixing time is used to extend the mixing duration so that the steel fibers can fully migrate and mix in the slurry. If the obtained uniformity difference of the supplementary feeding does not meet the optimization conditions for uniformity of supplementary feeding, it is determined that the uniformity of supplementary feeding is qualified and the uniform feeding control of steel fiber concrete during the uniform feeding period is completed. Not meeting the optimization conditions for uniformity of supplementary feeding means that the obtained interference value of uniformity of supplementary feeding is not greater than the preset interference value of uniformity of supplementary feeding. The uniform feeding period includes the initial feeding period, the feeding and mixing period, and the feeding and supplementary feeding period.

[0056] Specifically, the optimization of replenishment uniformity involves: based on the mapping relationship between the obtained standard score of the replenishment uniformity interference value deviation and the amount of reduction in stirring speed in the database, obtaining the actual reduction in stirring speed, which prompts the PLC operator to reduce the stirring paddle speed based on the obtained actual reduction in stirring speed; and simultaneously, based on the mapping relationship between the obtained standard score of the replenishment uniformity interference value deviation and the amount of increase in stirring time in the database, obtaining the actual increase in stirring time, which prompts the PLC operator to increase the stirring time based on the obtained actual increase in stirring time. The standard score of the replenishment uniformity interference value deviation represents the relationship between the obtained replenishment uniformity interference value deviation and the amount of increase in stirring time in the database. The ratio of the difference between the average value of historical replenishment uniformity interference values ​​and the standard deviation of historical replenishment uniformity interference values ​​is used. The replenishment uniformity interference value deviation represents the difference between the obtained replenishment uniformity interference value and the preset replenishment uniformity interference value. The preset replenishment uniformity interference value is represented by the sum and average of the historical replenishment uniformity interference values ​​at the end of the historical feeding period in the database. After the replenishment uniformity optimization is completed, a fourth concrete trial mixing test instruction is sent. If the replenishment uniformity difference obtained again after the fourth concrete trial mixing test does not meet the replenishment uniformity optimization conditions, then the replenishment uniformity optimization is completed and the uniform feeding control of steel fiber reinforced concrete during the uniform feeding period is completed.

[0057] It should be added that if the steel fiber concentration deviation in the mold feeding area is 5 kg / m² at the end of the feeding and replenishment period. 3 The area of ​​missing steel fibers is 0.2m². 2 The maximum allowable deviation in steel fiber concentration in the database is 4 kg / m³. 3 The maximum permissible area of ​​missing steel fibers is 0.15m². 2 Through proportional processing, the steel fiber concentration deviation ratio is 1.25 and the steel fiber missing area ratio is 1.33. Assuming the steel fiber concentration deviation measurement factor is 0.6 and the steel fiber missing area measurement factor is 0.4, the replenishment uniformity interference value is 1.282. If the preset replenishment uniformity interference value is 1, the replenishment uniformity difference is 0.282, which meets the replenishment uniformity optimization conditions.

[0058] Based on the mapping relationship, the system obtains the actual reduction in mixing speed and the actual extension of mixing time, prompting the PLC operator to adjust the mixing parameters. After optimization, a fourth concrete trial mixing test is conducted. If the newly acquired difference in the uniformity of the added material is not greater than the preset value, the optimization of the uniformity of the added material is completed, and the control of the steel fiber reinforced concrete addition during the uniform addition period is confirmed to be qualified. This process ensures the uniformity of steel fiber distribution in the concrete through real-time quantification and control.

[0059] In this embodiment, the PLC terminal dynamically adjusts the stirring parameters through closed-loop control and parameter mapping. Specifically, the PLC terminal receives the standard score of the deviation of the uniformity interference value of the supplementary feeding, converts it into the actual reduction in stirring speed through a database mapping table, and sends an analog signal to the frequency converter to reduce the motor frequency and simultaneously reduce the stirring paddle speed. Simultaneously, it uses a PID algorithm for fine-tuning to avoid overshoot and ensure a smooth decrease in the turbulence intensity of the slurry. Similarly, the PLC terminal maps the stirring time extension based on the standard score of the deviation of the uniformity interference value of the supplementary feeding, triggering automatic accumulation of the stirring time. It controls the start and stop of the stirring equipment through the I / O interface to ensure the total stirring time meets the target, while simultaneously pausing the supplementary feeding system to avoid over-mixing.

[0060] This example demonstrates a significant improvement in the quality stability of steel fiber reinforced concrete through the quantification and dynamic optimization of uniformity differences in supplementary addition. On one hand, the reduction in mixing speed and the extension of mixing time are automatically mapped based on the standard score of the deviation of the uniformity interference value of supplementary addition, achieving precise adjustment and effectively eliminating the problem of local agglomeration or uneven distribution of steel fibers. This improves the uniformity of the density of the tunnel segments and reduces defects such as honeycomb and cracks. On the other hand, the optimization effect is verified through a fourth concrete trial mixing test, ensuring that the process automatically ends after the viscosity reaches the standard during the supplementary addition stage, avoiding excessive adjustments that lead to energy waste. At the same time, a data closed loop is formed to support iterative optimization of process parameters, ultimately achieving efficient, low-consumption, and high-quality continuous production, adapting to the concrete performance requirements of high-precision shield tunnel segments.

[0061] This application provides a control device for uniformly feeding steel fiber reinforced concrete for tunnel segments, comprising: a laser rangefinder, a high-precision electromagnetic flowmeter, an electromagnetic induction sensor, a laser scanner, an encoder, and a Hall effect sensor. The laser rangefinder is typically installed below the mixer outlet (or at the location of the standard slump test mold) for real-time monitoring of concrete slump. The high-precision electromagnetic flowmeter is typically installed on the outlet pipeline of the water-reducing agent storage tank for real-time metering of the water-reducing agent dosage. The electromagnetic induction sensor is typically installed in the middle section of the mixing paddle axial direction for real-time monitoring of steel fiber concentration. The laser scanner is typically installed at the top of the mold feeding area for real-time acquisition of the steel fiber missing area and steel fiber concentration deviation. The encoder is typically installed at the feeding port for real-time monitoring of the feeding speed. The Hall effect sensor is typically installed on the mixing paddle drive shaft for real-time monitoring of the mixing paddle rotation speed. The PLC operating terminal is used to control the mixing paddle rotation speed, feeding amount, mixing time, and feeding speed through a built-in PID control algorithm.

[0062] In summary, the embodiments of this application first acquire initial feeding data and quantify the fluidity of the slurry in the initial feeding stage. The system can automatically determine whether a first viscosity optimization is needed, achieving precise adjustment of the water-reducing agent, ensuring a smooth slurry, and avoiding problems such as uneven mixing and steel fiber agglomeration caused by excessively high initial feeding viscosity, thereby improving the initial uniformity of concrete. Then, in the feeding and mixing stage, based on the quantification of distribution uniformity of mixing data, the system dynamically determines whether a second viscosity optimization is needed. By adjusting the mixing paddle speed and mixing time in real time, the system improves the dispersion uniformity of materials such as steel fibers in concrete, reducing strength fluctuations caused by fiber accumulation or sparseness. Finally, in the feeding and replenishment stage, by quantifying the replenishment uniformity, the system determines whether a third viscosity optimization is needed, automatically adjusting the mixing parameters to precisely control the dispersion degree of the replenishment materials, improving the consistency of material mixing in the replenishment stage, reducing local segregation problems caused by uneven feeding, and ultimately improving the overall quality stability and production efficiency of the shield tunnel segment concrete.

[0063] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0064] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0065] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0066] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0067] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0068] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method of controlling uniform feeding of steel fiber reinforced concrete for a shield segment, characterized by, Includes the following steps: S1, in the initial feeding stage, the slurry flowability of a specified batch of concrete is quantified based on the acquired initial feeding data, and it is determined whether there is a first viscosity optimization requirement. The initial feeding stage refers to the operation from the start of adding steel fibers to the specified batch of concrete until all steel fibers have been added. The first viscosity optimization requirement means improving the uniformity of steel fiber distribution in the specified batch of concrete by optimizing the water-reducing agent content or the initial feeding speed. The quantification of the slurry flowability of the specified batch of concrete based on the acquired initial feeding data specifically involves: obtaining the concrete slump of the specified batch of concrete at the end of the initial feeding period. The system simultaneously retrieves the preset concrete slump from the database and compares the differences to obtain the concrete slump difference coefficient; it also retrieves the water-reducing agent dosage of a specified batch of concrete at the end of the initial feeding period, retrieves the preset water-reducing agent dosage from the database, and compares the relative differences to obtain the relative difference coefficient of water-reducing agent dosage; and it harmonizes and averages the obtained concrete slump difference coefficient and the relative difference coefficient of water-reducing agent dosage to obtain the slurry uniformity index. The slurry uniformity index represents the quantitative data on the influence of the initial feeding data on the slurry fluidity of the specified batch of concrete. The initial feeding data includes the concrete slump and the water-reducing agent dosage. S2, In the feeding and mixing stage, the uniformity of the distribution of a specified batch of concrete is quantified based on the acquired feeding and mixing data, and at the same time it is determined whether there is a second viscosity optimization requirement. The feeding and mixing stage refers to the operation step corresponding to when the fluidity of the slurry meets the feeding and mixing requirements. The second viscosity optimization requirement refers to improving the uniformity of steel fiber distribution in the feeding and mixing stage through stacking optimization or sparse optimization. S3, in the material feeding and replenishment stage, the uniformity of replenishment of a specified batch of concrete is quantified based on the acquired material feeding and replenishment data, and at the same time it is determined whether there is a third viscosity optimization requirement. The material feeding and replenishment stage refers to the operation step corresponding to when the distribution uniformity meets the material feeding and replenishment requirement. The third viscosity optimization requirement means improving the distribution uniformity of steel fibers in the material feeding and replenishment stage by optimizing the mixing paddle speed and mixing time.

2. The method for controlling the uniform feeding of steel fiber reinforced concrete for tunnel segments as described in claim 1, characterized in that, The determination of whether there is a need for first viscosity optimization is as follows: If the obtained slurry uniformity index meets the first difference condition, the actual amount of water-reducing agent added is obtained based on the standard score of the deviation of the first slurry uniformity index to reduce the viscosity of the slurry. The first difference condition means that the minimum value of the historical slurry uniformity index in the database is greater than the obtained slurry uniformity index. The actual amount of water-reducing agent added means the result output by inputting the standard score of the deviation of the first slurry uniformity index into the water-reducing agent adjustment linear regression model. If the obtained slurry uniformity index meets the second difference condition, the actual reduction in water-reducing agent and the actual reduction in the initial feeding speed of steel fibers are obtained based on the standard score of the deviation of the obtained second slurry uniformity index, so as to increase the viscosity of the slurry. The second difference condition means that the obtained slurry uniformity index is greater than the maximum value of the historical slurry uniformity index in the database. The actual reduction in water-reducing agent and the actual reduction in the initial feeding speed of steel fibers represent the results output by inputting the distribution of the standard score of the deviation of the second slurry uniformity index into the linear regression model for water-reducing agent adjustment and the linear regression model for feeding speed adjustment. After optimization to meet the difference conditions, a first concrete trial mixing test instruction is sent. If the slurry uniformity index re-acquired after the first concrete trial mixing test is within the allowable range of the slurry uniformity index in the database, the feeding and mixing stage is entered; otherwise, an abnormal steel fiber flow warning is issued. The first concrete trial mixing test instruction is used to prompt the preset personnel to conduct a pre-set concrete trial mixing test based on the optimized initial feeding data.

3. The method for controlling the uniform feeding of steel fiber reinforced concrete for tunnel segments as described in claim 1, characterized in that, The quantification of the uniformity of concrete distribution in a specified batch based on the acquired material feeding and mixing data is specifically as follows: The rotation speed adjustment is determined based on the concrete consistency in the mold feeding area and the preset concrete consistency in the database. If the speed adjustment determination result is the first speed adjustment determination result, the increase in stirring paddle speed is mapped in the database based on the obtained first concrete consistency deviation. This is used to prompt the drive motor to increase the stirring paddle speed based on the obtained increase in stirring paddle speed to reduce the slurry resistance. The first speed adjustment determination result indicates that the maximum value corresponding to the concrete consistency in the mold feeding area is greater than the preset first concrete consistency. If the speed adjustment determination result is the second speed adjustment determination result, the amount of reduction in the stirring paddle speed is mapped in the database based on the obtained second concrete consistency deviation. This is used to prompt the drive motor to reduce the stirring paddle speed based on the obtained amount of reduction in the stirring paddle speed in order to increase the consistency of the slurry. The second speed adjustment determination result indicates that the minimum value of the concrete consistency in the mold feeding area is less than the preset second concrete consistency. If the speed adjustment determination result is the third speed adjustment determination result, it is recorded as uniform distribution and it is determined whether there is a second viscosity optimization requirement. The third speed adjustment determination result indicates that the obtained concrete consistency is within the preset allowable range of concrete consistency.

4. The method for controlling the uniform feeding of steel fiber reinforced concrete for tunnel segments as described in claim 3, characterized in that, The determination of whether there is a second viscosity optimization requirement specifically involves: If the steel fiber concentration in the mold feeding area is greater than the historical maximum steel fiber concentration in the database, the corresponding mold feeding area is recorded as a local accumulation area and accumulation optimization is performed. The accumulation optimization includes feeding speed optimization to reduce the feeding speed of steel fibers to reduce the accumulation of steel fibers in the local accumulation area, and first feeding amount optimization to reduce the steel fiber concentration in the local accumulation area. If the steel fiber concentration in the mold feeding area is within the allowable range of steel fiber concentration in the database, the corresponding mold feeding area will be recorded as a uniform feeding area and will enter the feeding and replenishment stage. If the steel fiber concentration in the mold feeding area is less than the historical minimum steel fiber concentration in the database, the corresponding mold feeding area is recorded as a local sparse area and sparse optimization is performed. The sparse optimization includes the optimization of the stirring paddle speed to enhance the slurry flow and promote the diffusion of steel fibers to the local sparse area, and the second feeding amount optimization to increase the feeding amount in the local sparse area to improve the steel fiber concentration.

5. The method for controlling the uniform feeding of steel fiber reinforced concrete for tunnel segments as described in claim 4, characterized in that, The stacking optimization specifically includes: Based on the mapping relationship between the obtained first standard score of steel fiber concentration deviation and the decrease value of feeding speed and decrease value of feeding amount in the database, the actual decrease value of feeding speed and decrease value of feeding amount are obtained, which are used to prompt the PLC operation terminal based on the obtained actual decrease value of feeding speed and decrease value of feeding amount. After the stacking optimization is completed, a second concrete trial mixing test instruction is sent. If the steel fiber concentration obtained again after the second concrete trial mixing test is within the allowable range of steel fiber concentration in the database, the stacking optimization is completed and the material feeding and replenishment stage begins. The sparse optimization specifically involves: based on the mapping relationship between the obtained second standard score of steel fiber concentration deviation and the increase values ​​of agitator speed and feed amount in the database, obtaining the actual increase values ​​of agitator speed and feed amount. This is used to prompt the PLC operator to send a third concrete trial mixing test command after the sparse optimization is completed, based on the obtained actual increase values ​​of agitator speed and feed amount. If the steel fiber concentration obtained again after the third concrete trial mixing test is within the allowable range of steel fiber concentration in the database, then the sparse optimization is completed and the material feeding and replenishment stage begins.

6. The method for controlling the uniform feeding of steel fiber reinforced concrete for tunnel segments as described in claim 1, characterized in that, The quantification of the uniformity of the replenishment of a specified batch of concrete based on the acquired material replenishment data is as follows: At the end of the feeding and replenishment period, the feeding and replenishment data in the mold feeding area and the maximum allowable feeding and replenishment data in the database are proportionally processed to obtain the proportional processing results. At the same time, the feeding and replenishment data measurement factors are combined to measure the results of each proportional processing and perform harmonic averaging to obtain the replenishment uniformity interference value. The material feeding and replenishment data includes a steel fiber concentration deviation, which reflects the difference between the steel fiber concentration at the end of the material feeding and replenishment period and the steel fiber concentration at the beginning of the material feeding and replenishment period, and a steel fiber missing area calculated by converting the mold area area, pixels and actual size. The replenishment uniformity interference value represents the quantitative data of the degree of interference of the material feeding and replenishment data on the uniformity of the corresponding steel fiber distribution during the material feeding and replenishment process.

7. The method for controlling the uniform feeding of steel fiber reinforced concrete for tunnel segments as described in claim 6, characterized in that, The determination of whether there is a need for a third viscosity optimization is as follows: The degree of difference between the obtained uniformity interference value of the supplementary injection and the preset uniformity interference value of the supplementary injection in the database is denoted as the uniformity difference degree of the supplementary injection. If the obtained uniformity difference of the supplementary feeding meets the optimization conditions of the supplementary feeding uniformity, it is determined that the supplementary feeding uniformity is unqualified and the supplementary feeding uniformity is optimized. The condition of meeting the optimization conditions of the supplementary feeding uniformity means that the obtained interference value of the supplementary feeding uniformity is greater than the preset interference value of the supplementary feeding uniformity. The optimization of the supplementary feeding uniformity includes the optimization of the stirring speed and the optimization of the stirring time. The optimization of the stirring speed means to enhance the turbulence intensity inside the slurry by increasing the stirring speed. The optimization of the stirring time is used to extend the stirring time so that the steel fibers can fully migrate and mix in the slurry. If the obtained uniformity difference of the supplementary feeding does not meet the optimization conditions for uniformity of supplementary feeding, it is determined that the uniformity of supplementary feeding is qualified and the uniform feeding control of steel fiber concrete during the uniform feeding period is completed. The condition that it does not meet the optimization conditions for uniformity of supplementary feeding means that the obtained interference value of uniformity of supplementary feeding is not greater than the preset interference value of uniformity of supplementary feeding. The uniform feeding period includes the initial feeding period, the feeding and mixing period, and the feeding and supplementary feeding period.

8. The method for controlling the uniform feeding of steel fiber reinforced concrete for tunnel segments as described in claim 7, characterized in that, The optimization of the uniformity of replenishment is specifically as follows: Based on the mapping relationship between the standard score of the deviation of the uniformity of the supplementary feeding and the amount of reduction in stirring speed in the database, the actual amount of reduction in stirring speed is obtained, which is used to prompt the PLC operator to reduce the stirring speed based on the actual amount of reduction in stirring speed. At the same time, based on the mapping relationship between the standard score of the deviation of the uniformity of the supplementary feeding and the amount of extension of stirring time in the database, the actual amount of extension of stirring time is obtained, which is used to prompt the PLC operator to increase the stirring time based on the actual amount of extension of stirring time. After the optimization of the uniformity of the supplementary feeding is completed, the fourth concrete trial mixing test instruction is sent. If the difference in the uniformity of the supplementary feeding obtained after the fourth concrete trial mixing test does not meet the optimization conditions for the uniformity of the supplementary feeding, then the optimization of the uniformity of the supplementary feeding is completed and the uniform feeding control of steel fiber concrete during the uniform feeding period is completed.

9. A control device for uniform feeding of steel fiber reinforced concrete for tunnel segments, employing the control method for uniform feeding of steel fiber reinforced concrete for tunnel segments as described in any one of claims 1-8, characterized in that, include: Laser rangefinder, high-precision electromagnetic flowmeter, electromagnetic induction sensor, laser scanner, encoder, Hall sensor and PLC operator terminal; The laser rangefinder sensor is used to monitor the concrete slump in real time. The high-precision electromagnetic flowmeter is used to measure the amount of water-reducing agent used in real time. The electromagnetic induction sensor is used to monitor the steel fiber concentration in real time. The laser scanner is used to collect data on the area of ​​missing steel fibers and the deviation in steel fiber concentration in real time. The encoder is used to monitor the feeding speed in real time; The Hall sensor is used to monitor the stirring paddle speed in real time. The PLC operating terminal is used to control the stirring paddle speed, feeding amount, stirring time and feeding speed through the built-in PID control algorithm.

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