A method and device for detecting the accuracy of a fully hydraulic segmental beam prefabricated template

Abstract

The present application discloses a method and device for detecting the accuracy of a fully hydraulic segmental beam prefabricated template, and relates to the field related to the detection of segmental beam accuracy. The method includes: constructing a three-dimensional structure of the fully hydraulic segmental prefabricated template for feature extraction, determining multiple key points based on the three-dimensional structure features to traverse the fully hydraulic segmental prefabricated template for detection, synchronizing multiple template single-point parameters of the fully hydraulic segmental prefabricated template to the balance identification channel, performing deviation calculation on the parameter balance result and multiple template single-point parameters, detecting the deviation calculation result for feedback adjustment, and intelligently detecting the accuracy of the threshold template of the fully hydraulic segmental beam in combination with the feedback optimization information. The method solves the technical problem that the traditional fully hydraulic segmental beam prefabricated template has minor defects, resulting in certain errors in the accuracy detection of the fully hydraulic segmental beam prefabricated template, and achieves the technical effect of adjusting the fully hydraulic segmental beam prefabricated template to achieve parameter balance at each point, thereby improving the detection accuracy.

Description

Technical Field

[0001] The present application relates to the field related to segmental beam precision detection, and in particular to a precision detection method and device for a fully hydraulic segmental beam prefabricated template. Background Art

[0002] With the continuous development of bridge construction technology, the accuracy requirements for prefabricated formwork are increasing day by day, and it is necessary to conduct comprehensive inspections of the internal structure and surface quality of the formwork from different angles. However, the existing technology still has some shortcomings in practical applications. On the one hand, some high-precision inspection equipment is expensive and complicated to operate, and requires high professional skills and experience from the inspectors, which to a certain extent limits its widespread application. On the other hand, since the prefabrication process of bridge beams and slabs involves a variety of materials and complex processes, there may be minor defects or structural changes inside the formwork, which are sometimes difficult to be accurately identified by existing technologies, resulting in technical problems such as certain errors in the accuracy inspection of the prefabricated formwork for fully hydraulic segmental beams. Summary of the invention

[0003] The present application provides a method and device for detecting the accuracy of a fully hydraulic segmental beam precast formwork, thereby solving the technical problem that the traditional fully hydraulic segmental beam precast formwork has tiny defects, resulting in certain errors in the accuracy detection of the fully hydraulic segmental beam precast formwork. The application achieves the technical effect of adjusting the fully hydraulic segmental beam precast formwork to achieve parameter balance at each point and improve the detection accuracy.

[0004] The present application provides a method for detecting the accuracy of a full-hydraulic segmental beam prefabricated template, and the method is applied to a device for detecting the accuracy of a full-hydraulic segmental beam prefabricated template, comprising: collecting three-dimensional data of the full-hydraulic segmental prefabricated template to obtain a three-dimensional point cloud data set, and constructing a three-dimensional structure of the full-hydraulic segmental prefabricated template based on the three-dimensional point cloud data set; traversing the three-dimensional structure of the full-hydraulic segmental prefabricated template to extract features, and determining a plurality of key points according to the three-dimensional structure features; traversing the full-hydraulic segmental prefabricated template based on the plurality of key points to perform detection, and determine a plurality of template single-point parameters; synchronizing the plurality of template single-point parameters of the full-hydraulic segmental prefabricated template to a balanced identification channel, and generating a parameter balanced identification result; performing deviation calculation based on the parameter balanced identification result and the plurality of template single-point parameters, detecting the deviation calculation result and performing feedback adjustment, and performing intelligent detection of the accuracy of the full-hydraulic segmental beam threshold template in combination with the feedback optimization information.

[0005] In a possible implementation, the plurality of template single-point parameters of the fully hydraulic segment prefabricated template are synchronized to the balanced identification channel, a parameter balanced identification result is generated, and the following processing is performed: a strategy space is defined based on the plurality of template single-point parameters, , is the kth strategy of the i-th template single point parameter; constructing the profit function and loss function of the multiple template single point parameters based on the strategy space; the profit function is: ; The loss function is: ;in, is the profit of the i-th template single-point function among multiple template single-point parameters, is the strategy of the single-point parameter of the i-th template, For multiple template single point parameters, except for the other strategies of the i-th template single point parameter, is the actual parameter value of the single-point parameter of the i-th template under its corresponding strategy, is the expected parameter value of the i-th template single point parameter, is the loss of the i-th template single-point function among multiple template single-point parameters, The actual parameter value of the i-th template single point parameter Expected value The absolute difference between is the weight coefficient of the i-th template single point parameter, For the i-th template single point parameter in the strategy The cost under the above-mentioned cost; the strategies of the multiple template single-point parameters are calculated by the benefit function to obtain the expected close value of each single-point parameter in the corresponding strategy; the strategies of the multiple template single-point parameters are calculated by the loss function to obtain the expected deviation value of each single-point parameter in the corresponding strategy; the Nash equilibrium condition is introduced, and based on the Nash equilibrium condition, the strategies corresponding to each template single-point parameter are traversed in combination with the expected close value and the expected deviation value of each single-point parameter in the corresponding strategy to perform optimal judgment, and the optimal equilibrium strategy of each template single-point parameter is determined; the optimal equilibrium strategy of each template single-point parameter is synchronized to the equilibrium identification channel to generate a parameter equilibrium identification result.

[0006] In a possible implementation, a Nash equilibrium condition is introduced, and based on the Nash equilibrium condition, the strategy corresponding to each template single point parameter is traversed in combination with the expected close value and the expected deviation value of each single point parameter in the corresponding strategy to perform optimal determination, and the optimal equilibrium strategy for each template single point parameter is determined, and the following processing is performed: The Nash equilibrium condition is: ;in, is the optimal strategy for the single-point parameter of the i-th template, is the optimal strategy among multiple template single point parameters except the i-th template single point parameter, is any strategy of the i-th template single-point parameter; based on the Nash equilibrium condition, traverse the strategies corresponding to each template single-point parameter, compare the expected close value and the expected deviation value of each single-point parameter in the corresponding strategy in turn, and obtain the to-be-verified equilibrium strategy of each template single-point parameter; judge whether the to-be-verified equilibrium strategy of each template single-point parameter satisfies the Nash equilibrium condition, and when the to-be-verified equilibrium strategy of each template single-point parameter satisfies the Nash equilibrium condition, determine the optimal equilibrium strategy of each template single-point parameter.

[0007] In a possible implementation, the optimal balancing strategy of each template single-point parameter is synchronized to the balancing identification channel to generate a parameter balancing identification result, and the following processing is performed: balancing calculation is performed based on the optimal balancing strategy of each template single-point parameter to obtain the balancing value of each template single-point parameter; the balancing value of each template single-point parameter is compared with a preset target value to extract the balancing value that does not meet the preset target value; the template single-point parameters corresponding to the balancing value that does not meet the preset target value are identified to obtain a parameter balancing abnormality label; and the parameter balancing abnormality label is added to the parameter balancing identification result.

[0008] In a possible implementation, a deviation calculation is performed based on the parameter equalization identification result and the multiple template single-point parameters, and the deviation calculation result is detected for feedback adjustment, and the following processing is performed: a deviation calculation is performed based on the parameter equalization identification result and the multiple template single-point parameters, and a deviation calculation result is determined, and the deviation calculation result includes deviation direction information and deviation size information; the deviation direction information is detected based on the deviation size information to obtain a deviation detection result, and it is determined whether the deviation detection result exceeds a preset deviation detection range; if the deviation detection result exceeds the preset deviation detection range, a feedback instruction is generated, and feedback is performed through the feedback instruction in combination with the deviation size information and the deviation direction information to generate feedback adjustment information; the feedback adjustment information is verified to generate a feedback verification token, and the feedback optimization information is determined according to the feedback verification token.

[0009] In a possible implementation, if the deviation detection result exceeds the preset deviation detection range, a feedback instruction is generated, and feedback is performed through the feedback instruction in combination with the deviation size information and the deviation direction information to generate feedback adjustment information, and the following processing is performed: the multiple template single-point parameters are traced according to the parameter balance exception label to determine multiple exception parameters; the feedback instruction is determined based on the multiple exception parameters; the feedback instruction is executed to perform dynamic adjustment in combination with the deviation size information to determine a first deviation adjustment parameter; the feedback instruction is executed to perform dynamic adjustment in combination with the deviation direction information to determine a second deviation adjustment parameter; the first deviation adjustment parameter and the second deviation adjustment parameter are added to the feedback adjustment information.

[0010] In a possible implementation, the feedback adjustment information is verified to generate a feedback verification token, feedback optimization information is determined based on the feedback verification token, and the following processing is performed: multi-dimensional verification is performed on the feedback adjustment information to generate a multi-dimensional verification result; the feedback verification token is constructed based on the multi-dimensional verification result; the feedback verification token is associated with the feedback adjustment information to determine an associated factor; the feedback verification token is parsed according to the associated factor, and an adjustment risk assessment is performed based on the feedback parsed information to generate a risk assessment result; the feedback adjustment information is integrated according to the risk assessment result to determine the feedback optimization information.

[0011] The present application also provides a precision detection device for a full-hydraulic segmental beam prefabricated template, including: a data acquisition module, the data acquisition module is used to perform three-dimensional data acquisition on the full-hydraulic segmental prefabricated template, obtain a three-dimensional point cloud data set, and construct a three-dimensional structure of the full-hydraulic segmental prefabricated template based on the three-dimensional point cloud data set; a feature extraction module, the feature extraction module is used to traverse the three-dimensional structure of the full-hydraulic segmental prefabricated template to extract features, and determine multiple key points according to the three-dimensional structure features; a data detection module, the data detection module is used to traverse the full-hydraulic segmental prefabricated template based on the multiple key points for detection, and determine multiple template single-point parameters; a balance identification module, the balance identification module is used to synchronize the multiple template single-point parameters of the full-hydraulic segmental prefabricated template to a balance identification channel, and generate a parameter balance identification result; a deviation calculation module, the deviation calculation module is used to perform deviation calculation based on the parameter balance identification result and the multiple template single-point parameters, detect the deviation calculation result for feedback adjustment, and intelligently detect the precision of the full-hydraulic segmental beam threshold template in combination with the feedback optimization information.

[0012] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0013] The present application provides a method and device for detecting the accuracy of a fully hydraulic segmental beam precast template, which relates to the technical field of segmental beam accuracy detection. It solves the technical problem that the traditional fully hydraulic segmental beam precast template has tiny defects, resulting in certain errors in the accuracy detection of the fully hydraulic segmental beam precast template, and achieves the technical effect of adjusting the fully hydraulic segmental beam precast template to achieve parameter balance at each point, thereby improving the detection accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present application, the accompanying drawings of the embodiment of the present application will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the device according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic flow chart of a method for detecting the accuracy of a fully hydraulic segmental beam prefabricated template provided in an embodiment of the present application;

[0016] Figure 2 A schematic structural diagram of a precision detection device for a fully hydraulic segmental beam precast formwork provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] 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 in accordance with the contents of the specification. 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 listed below.

[0018] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0019] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, device, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0020] The embodiment of the present application provides a method for detecting the accuracy of a fully hydraulic segmental beam prefabricated template, and the method is applied to a device for detecting the accuracy of a fully hydraulic segmental beam prefabricated template, such as Figure 1 As shown, the method includes:

[0021] Step A100, collect three-dimensional data of the full-hydraulic segment prefabricated template to obtain a three-dimensional point cloud data set, and construct the three-dimensional structure of the full-hydraulic segment prefabricated template based on the three-dimensional point cloud data set; first, a large amount of point data of the full-hydraulic segment prefabricated template can be captured by using a high-precision three-dimensional laser scanner or a structured light scanner, and then multiple point cloud data sets obtained from scanning at different angles are merged into a unified coordinate system to obtain a three-dimensional point cloud data set, and further, the three-dimensional point cloud data set is converted into a continuous surface model using algorithms such as Poisson surface reconstruction and moving least squares method, and a spatial geometry is created based on the surface model. At the same time, the three-dimensional model is used to perform structural analysis, fluid dynamics simulation, etc. to construct the three-dimensional structure of the full-hydraulic segment prefabricated template, providing strong support for subsequent manufacturing, analysis and maintenance.

[0022] Execute step A200, traverse the three-dimensional structure of the full-hydraulic segment prefabricated template to perform feature extraction, and determine multiple key points based on the three-dimensional structural features; first, comprehensively analyze the three-dimensional structure of the full-hydraulic segment prefabricated template to determine the overall shape, size, material distribution and relationship between the various components of the full-hydraulic segment prefabricated template; further, traverse the three-dimensional structure of the full-hydraulic segment prefabricated template to perform feature extraction, which means extracting the geometric features and topological features of the full-hydraulic segment prefabricated template; the geometric features of the full-hydraulic segment prefabricated template can be respectively detected by edge detection, i.e. identifying the outer contour of the template and the edges of the internal components; plane detection, i.e. identifying the plane areas in the template, such as panels, partitions, etc.; surface detection, i.e. identifying the curved parts in the template, such as arc edges, curved panels, etc.; hole detection, i.e. identifying the holes in the template, such as connecting holes, ventilation holes, etc.; and concave-convex features, i.e. identifying the convex and concave parts on the surface of the template. The topological features of the fully hydraulic segmented prefabricated template can be respectively determined through the connection relationship, that is, analyzing the connection mode and position relationship between the various components in the template, the supporting structure, that is, identifying the key supporting structures such as the supporting columns and beams in the template, and further determining multiple key points of the fully hydraulic segmented prefabricated template according to the geometric characteristics and topological characteristics of the fully hydraulic segmented prefabricated template. The multiple key points can be important reference points in the process of template design, manufacturing, installation and maintenance. The multiple key points can include the center point, that is, the geometric center point or center of gravity position of the template, the connection point, that is, the connection point between the components in the template, such as bolt holes, welding points, etc., the support point, that is, the key stress point of the supporting structure, such as the contact point between the support column and the ground, the connection point between the beam and the panel, etc., the key point, that is, the area on the template that may affect the overall performance or require special attention, such as stress concentration areas, vulnerable parts, etc., to provide strong support for the full life cycle management of the template.

[0023] Execute step A300, traverse the full hydraulic segment prefabricated template based on the multiple key points to perform inspection, and determine multiple template single point parameters; first, a detection plan can be formulated according to the design drawings of the full hydraulic segment prefabricated template and the multiple key points determined above, and the parameters that need to be measured at each key point are determined, which may include position coordinates, size, shape, stress, vibration, etc., and the detection sequence and path are arranged at the same time to ensure efficient and comprehensive coverage of all key points. Further, according to the detection plan, each of the multiple key points is visited one by one, and appropriate measuring equipment and sensors are used to accurately measure the multiple key points and record them. For parameters that need to be measured multiple times or under different conditions, ensure that they are carried out in accordance with the formulated detection plan, then clean and preprocess the detected data, remove noise and outliers, analyze the data results, determine the specific parameter values ​​of each key point, and evaluate the overall performance and quality of the template. According to the results of data processing and analysis, determine the specific single-point parameter values ​​for each key point. The single-point parameter values ​​can include position coordinates, dimensional deviation, shape error, stress level, vibration frequency and other data, so as to determine the single-point parameters of multiple templates of the full hydraulic segment prefabricated template, which will serve as a guarantee for the later precision detection of the full hydraulic segment prefabricated template.

[0024] Execute step A400, synchronize the multiple template single-point parameters of the full hydraulic segment prefabricated template to the balance identification channel, and generate a parameter balance identification result; in a possible implementation, step A400 further includes step A410, defining a strategy space based on the multiple template single-point parameters, , is the kth strategy of the ith template single point parameter; first, the strategy space is defined according to multiple template single point parameters. The strategy space refers to the set of all possible strategies. The strategy refers to the specific operations or parameter settings that the participants can take during the game. In this application, each template single point parameter is regarded as a game participant, and its strategy is all possible settings that it can choose. The strategy is used to guide how to adjust the single point parameters in the template to achieve a certain goal. The defined strategy space is , It is the kth strategy of the i-th template single-point parameter, and the strategy may include step size, direction or more complex strategy rules for later parameter adjustment.

[0025] Execute step A420 to construct a benefit function and a loss function of the multiple template single-point parameters based on the strategy space; the benefit function is used to quantify the benefit obtained from adjusting the single-point parameters under a given strategy, and the benefit is related to the degree of closeness to achieving the target state. For example, when the goal is to maximize a certain performance indicator, the benefit function is directly related to the performance indicator and is a function used to reflect the improvement of the performance indicator.

[0026] The loss function is used to quantify the deviation after executing an action under a given policy. The loss is related to the degree to which the goal state is not reached. In contrast to the gain function, the loss function is minimized during the optimization process.

[0027] Execute step A430, the profit function is: ; Execute step A440, the loss function is: ;in, is the profit of the i-th template single-point function among multiple template single-point parameters, is the strategy of the single-point parameter of the i-th template, For multiple template single point parameters, except for the other strategies of the i-th template single point parameter, is the actual parameter value of the single-point parameter of the i-th template under its corresponding strategy, is the expected parameter value of the i-th template single point parameter, is the loss of the i-th template single-point function among multiple template single-point parameters, The actual parameter value of the i-th template single point parameter Expected value The absolute difference between is the weight coefficient of the i-th template single point parameter, For the i-th template single point parameter in the strategy The cost under the policy combination; executing step A450, calculating the policies of the plurality of template single-point parameters by the benefit function, and obtaining the expected approach value of each single-point parameter in the corresponding policy; executing step A460, calculating the policies of the plurality of template single-point parameters by the loss function, and obtaining the expected deviation value of each single-point parameter in the corresponding policy; the benefit function is used to reflect the degree of proximity of each single-point parameter to the target expected value under the policy combination, and the loss function is used to reflect the deviation of the target value under the policy combination and the resulting resource consumption, and the benefit function is: ; The loss function is: ;in, is the profit of the i-th template single-point function among multiple template single-point parameters, is the strategy of the single-point parameter of the i-th template, For multiple template single point parameters, except for the other strategies of the i-th template single point parameter, is the actual parameter value of the single-point parameter of the i-th template under its corresponding strategy, is the expected parameter value of the i-th template single point parameter, is the loss of the i-th template single-point function among multiple template single-point parameters, The actual parameter value of the i-th template single point parameter Expected value The absolute difference between is the weight coefficient of the i-th template single point parameter, For the i-th template single point parameter in the strategy The cost under the strategy; it means that for each single-point parameter, under a given strategy, by simulating or actually executing parameter adjustments, observing the changes in performance indicators, and calculating the cumulative value or average value of these changes using the benefit function, the expected approach value of the single-point parameter under the corresponding strategy is obtained. The expected approach value is used to characterize the expected effect of the strategy on improving the target performance indicator. The expected deviation value of the single-point parameter under the corresponding strategy is obtained by calculating the cumulative value or average value of these deviations using the loss function. The expected deviation value is used to characterize the negative effects or uncertainties that may be generated during the execution of the strategy. Similarly, for each single-point parameter, under a given strategy, by simulating or actually executing parameter adjustments, observing the deviation between the actual performance and the ideal performance, and by comparing the expected approach value and expected deviation value under different strategies, the effectiveness and risk of each strategy can be evaluated.

[0028] Execute step A470, introduce the Nash equilibrium condition, traverse the strategy corresponding to each template single point parameter based on the Nash equilibrium condition combined with the expected proximity value and the expected deviation value of each single point parameter in the corresponding strategy to perform optimization determination, and determine the optimal equilibrium strategy for each template single point parameter; in a possible implementation, step A470 further includes step A471, and the Nash equilibrium condition is: ;in, is the optimal strategy for the single-point parameter of the i-th template, is the optimal strategy among multiple template single point parameters except the i-th template single point parameter, is any strategy of the i-th template single-point parameter; execute step A472, based on the Nash equilibrium condition, traverse the strategies corresponding to each template single-point parameter, compare the expected close value and the expected deviation value of each single-point parameter in the corresponding strategy in turn, and obtain the to-be-verified equilibrium strategy of each template single-point parameter; execute step A473, determine whether the to-be-verified equilibrium strategy of each template single-point parameter satisfies the Nash equilibrium condition, and when the to-be-verified equilibrium strategy of each template single-point parameter satisfies the Nash equilibrium condition, determine the optimal equilibrium strategy of each template single-point parameter.

[0029] First, the Nash equilibrium condition is introduced. In the context of template single-point parameters, the Nash equilibrium condition can be defined as: for each single-point parameter in the template, its current strategy is the optimal choice given all other single-point parameter strategies. The Nash equilibrium condition is: ;in, is the optimal strategy for the single-point parameter of the i-th template, is the optimal strategy among multiple template single point parameters except the i-th template single point parameter, For any strategy of the i-th template single-point parameter, further, based on the Nash equilibrium condition, traverse the strategy corresponding to each template single-point parameter, and compare the expected close value and expected deviation value of each single-point parameter in the corresponding strategy in turn, which means that for each single-point parameter in the template, traverse its corresponding strategy space, and for each strategy of each single-point parameter, use the previously defined benefit function and loss function to calculate the expected close value and expected deviation value, which are used to reflect the performance of the strategy in improving the target performance index (expected close value) and the possible negative effects (expected deviation value). For each single-point parameter, compare the expected close value and expected deviation value of all its strategies. The purpose of the comparison is to determine the strategy with a higher expected close value and a lower expected deviation value as a candidate equilibrium strategy. For each candidate equilibrium strategy of each single-point parameter, it is necessary to verify whether it meets the Nash equilibrium condition, which is to check whether the strategy is still the optimal choice for the single-point parameter given that all other single-point parameter strategies remain unchanged.

[0030] Furthermore, for each participant (single-point parameter), verify whether the optimal strategy found meets the Nash equilibrium conditions. If a certain strategy combination does not meet the Nash equilibrium conditions, it is necessary to adjust the strategy combinations of other participants and recalculate the optimal strategy. Finally, through iterative optimization, the Nash equilibrium point of all participants' strategies is reached.

[0031] If and only if the candidate equilibrium strategies of all single-point parameters satisfy the Nash equilibrium conditions, the optimal equilibrium strategy combination of each single-point parameter is output, which means that under the current strategy combination, no single-point parameter has the motivation to change its strategy because doing so will not bring better results. The optimal equilibrium strategy of each template single-point parameter is determined, and these strategy combinations are synchronized to the equilibrium identification channel.

[0032] Execute step A480, synchronize the optimal balancing strategy of each template single-point parameter to the balancing identification channel, and generate a parameter balancing identification result. In a possible implementation, step A480 further includes step A481, performing balancing calculation based on the optimal balancing strategy of each template single-point parameter to obtain a balancing value of each template single-point parameter; executing step A482, comparing the balancing value of each template single-point parameter with a preset target value, and extracting a balancing value that does not meet the preset target value; executing step A483, marking the template single-point parameter corresponding to the balancing value that does not meet the preset target value, and obtaining a parameter balancing abnormality label; executing step A484, adding the parameter balancing abnormality label to the parameter balancing identification result.

[0033] First, for each template single-point parameter, the equilibrium calculation is performed according to its optimal equilibrium strategy, which means that the optimal strategy is applied to the single-point parameter and its corresponding equilibrium value is calculated. The calculation process can be based on the single-point parameters in the template, collect relevant historical data, experimental data, user feedback, etc. to build a mathematical model or simulation model to quantify the optimization objectives and constraints, and apply optimization algorithms such as gradient descent method, Newton method, genetic algorithm, simulated annealing algorithm, particle swarm optimization algorithm, etc. to the constructed mathematical model or simulation model for iterative calculation, and continuously adjust the value of the single-point parameter until the stopping criteria are met (such as reaching the preset number of iterations, the change in the optimization target value is less than a certain threshold, etc.). During the iteration process, the algorithm will calculate and compare the objective function values ​​under different parameter values ​​according to the optimization objectives and constraints, so as to gradually approach the optimal solution, and then output the equilibrium value of each template single-point parameter.

[0034] Then, the equilibrium value of each template single-point parameter is compared with the preset target value. The preset target value can be set according to business needs, device performance requirements or other relevant standards, and is used to evaluate whether the equilibrium value meets expectations. Furthermore, if there is a equilibrium value of a template single-point parameter that does not meet the preset target value, the equilibrium value is extracted, and the extracted equilibrium value is used to characterize that the single-point parameter fails to achieve the expected performance or state under the current equilibrium state. Then, the template single-point parameter corresponding to the equilibrium value that does not meet the preset target value is identified. The identification can be to assign a specific label or mark to the single-point parameter to indicate that there is an abnormality in its equilibrium state. The identified label is a parameter equilibrium abnormality label. Finally, the parameter equilibrium abnormality label is added to the parameter equilibrium identification result. The parameter equilibrium identification result is the equilibrium identification result of multiple template single-point parameters, which is a collection of equilibrium state evaluation results of all template single-point parameters.

[0035] Next, execute step A500, perform deviation calculation based on the parameter balance identification result and the multiple template single-point parameters, detect the deviation calculation result for feedback adjustment, and intelligently detect the accuracy of the threshold template of the full hydraulic segment beam in combination with the feedback optimization information. In a possible implementation, step A500 further includes step A510, perform deviation calculation based on the parameter balance identification result and the multiple template single-point parameters, determine to obtain a deviation calculation result, and the deviation calculation result includes deviation direction information and deviation size information; execute step A520, detect the deviation direction information based on the deviation size information, obtain a deviation detection result, and determine whether the deviation detection result exceeds a preset deviation detection range;

[0036] In the process of performing deviation calculation based on parameter equalization identification results and multiple template single-point parameters, it is necessary to determine the deviation between the actual equalization value of each single-point parameter and its preset target value, and calculate the deviation between its equalization value and the preset target value based on each template single-point parameter. The deviation calculation result is divided into deviation direction and deviation size. The deviation direction is used to characterize whether the equalization value is higher or lower than the target value, and the deviation size is used to characterize the absolute difference between the equalization value and the target value. After obtaining the deviation direction and deviation size, it is necessary to detect whether the deviation exceeds the preset deviation detection range. The preset deviation detection range can be an absolute threshold based on business needs, or it can be set as a relative threshold of a percentage of the target value. If the deviation detection result exceeds the preset deviation detection range, a feedback instruction is generated.

[0037] Further execute step A530, if the deviation detection result exceeds the preset deviation detection range, generate a feedback instruction, and use the feedback instruction to perform feedback in combination with the deviation size information and the deviation direction information to generate feedback adjustment information; in one possible implementation, step A530 further includes step A531, tracing the abnormality of the multiple template single-point parameters according to the parameter balance abnormality label to determine multiple abnormal parameters; execute step A532, determine the feedback instruction based on the multiple abnormal parameters; execute step A533, execute the feedback instruction to perform dynamic adjustment in combination with the deviation size information to determine the first deviation adjustment parameter; execute step A534, execute the feedback instruction to perform dynamic adjustment in combination with the deviation direction information to determine the second deviation adjustment parameter; execute step A535, add the first deviation adjustment parameter and the second deviation adjustment parameter to the feedback adjustment information.

[0038] First, the anomaly traceability of multiple template single-point parameters is performed according to the parameter balance anomaly labels, which means determining which template single-point parameters have anomalies according to the parameter balance anomaly labels, and determining corresponding feedback instructions according to the characteristics of the abnormal parameters of the multiple abnormal parameters, system status or business requirements. The template library instructions may include adjustment strategies, adjustment amounts or other necessary operating instructions. Furthermore, executing the feedback instructions and dynamically adjusting them in combination with the deviation size information to determine the first deviation adjustment parameter means executing the adjustment strategy in the feedback instructions according to the deviation size to reduce or eliminate the deviation. At the same time, executing the feedback instructions and dynamically adjusting them in combination with the deviation direction information to determine the second deviation adjustment parameter means adjusting the parameter value to approach the target value based on the deviation direction (higher or lower than the target value), and the obtained first deviation adjustment parameter and second deviation adjustment parameter need to be adjusted under the condition of satisfying the Nash equilibrium condition. Finally, the first deviation adjustment parameter and the second deviation adjustment parameter are integrated and added to the feedback adjustment information.

[0039] Execute step A540, verify the feedback adjustment information, generate a feedback verification token, and determine the feedback optimization information according to the feedback verification token. In a possible implementation, step A540 further includes step A541, perform multi-dimensional verification on the feedback adjustment information, and generate a multi-dimensional verification result; execute step A542, construct the feedback verification token based on the multi-dimensional verification result; execute step A543, associate the feedback verification token with the feedback adjustment information, and determine the association factor; execute step A544, parse the feedback verification token according to the association factor, perform adjustment risk assessment according to the feedback parsing information, and generate a risk assessment result; execute step A545, integrate the feedback adjustment information according to the risk assessment result, and determine the feedback optimization information.

[0040] In order to ensure the accuracy, completeness and consistency of the feedback adjustment information, it is necessary to perform multi-dimensional verification on the feedback adjustment information, which means that the feedback adjustment information can be verified in dimensions such as data integrity, logical consistency, and business rules. The data integrity verification refers to checking whether all necessary fields are filled in, and the logical consistency verification refers to verifying whether the adjusted parameter values, such as parameter value ranges, relationships between parameters, etc., conform to logical rules. The business rule verification refers to checking whether the adjustment is reasonable according to business rules (such as cost-benefit analysis, performance impact assessment, etc.), and generating multi-dimensional verification results. The multi-dimensional verification results include specific items of passed and failed verification.

[0041] Furthermore, a hash function, digital signature or other encryption technology can be used to encapsulate all the data in the multi-dimensional verification result to generate a feedback verification token, which is unique and cannot be tampered with. In order to establish a clear connection between the token and the adjustment information so that it can be traced and verified when necessary, it is necessary to associate the feedback verification token with the feedback adjustment information. The correspondence between the token and the adjustment information can be recorded in a database and the association factor can be used to identify the relationship. The association factor can be a token ID, a timestamp, a serial number, etc.

[0042] Finally, the feedback verification token is parsed according to the associated factors. The token can be parsed by using the same decryption or verification technology as when building the token, and the multi-dimensional verification results and other key information in the token can be extracted to further adjust the risk assessment based on the feedback parsed information. The positive and / or negative impact can be evaluated through system stability, performance impact, etc., and the risk assessment results are generated. At the same time, the feedback adjustment information is integrated according to the risk assessment results, which means determining which adjustments should be adopted based on the risk assessment results, and then integrating the verified and adjusted feedback information into the system to reflect these adjustments, thereby determining the feedback optimization information.

[0043] The embodiments of the present application solve the technical problem that the traditional fully hydraulic segmental beam precast formwork has minor defects, which leads to certain errors in the accuracy detection of the fully hydraulic segmental beam precast formwork, and achieves the technical effect of adjusting the fully hydraulic segmental beam precast formwork to achieve parameter balance at each point and improve the detection accuracy.

[0044] In the above, refer to Figure 1 A method for detecting the accuracy of a fully hydraulic segmental beam prefabricated template according to an embodiment of the present application is described in detail. Figure 2 A precision detection device for a fully hydraulic segmental beam precast formwork according to an embodiment of the present application is described.

[0045] According to the embodiment of the present application, a precision detection device for a fully hydraulic segmental beam prefabricated template is used to solve the technical problem that the traditional fully hydraulic segmental beam prefabricated template has tiny defects, resulting in a certain error in the precision detection of the fully hydraulic segmental beam prefabricated template, and achieves the technical effect of adjusting the fully hydraulic segmental beam prefabricated template to achieve parameter balance at each point to improve the detection accuracy. A precision detection device for a fully hydraulic segmental beam prefabricated template includes: a data acquisition module 10, a feature extraction module 20, a data detection module 30, a balance identification module 40, and a deviation calculation module 50.

[0046] A data acquisition module 10, wherein the data acquisition module 10 is used to perform three-dimensional data acquisition on the full hydraulic segment prefabricated template to obtain a three-dimensional point cloud data set, and to construct a three-dimensional structure of the full hydraulic segment prefabricated template based on the three-dimensional point cloud data set;

[0047] A feature extraction module 20, the feature extraction module 20 is used to traverse the three-dimensional structure of the full hydraulic segment prefabricated template to extract features, and determine a plurality of key points according to the three-dimensional structure features;

[0048] A data detection module 30, wherein the data detection module 30 is used to traverse the full hydraulic segment prefabricated template for detection based on the multiple key points to determine multiple template single point parameters;

[0049] A balanced identification module 40, the balanced identification module 40 is used to synchronize the plurality of template single-point parameters of the full hydraulic segment prefabricated template to a balanced identification channel to generate a parameter balanced identification result;

[0050] The deviation calculation module 50 is used to perform deviation calculation based on the parameter balance identification result and the multiple template single-point parameters, detect the deviation calculation result for feedback adjustment, and intelligently detect the accuracy of the full hydraulic segment beam threshold template in combination with the feedback optimization information.

[0051] The specific configuration of the balance identification module 40 will be described in detail below. As described above, the multiple template single-point parameters of the full hydraulic segment prefabricated template are synchronized to the balance identification channel to generate a parameter balance identification result. The balance identification module 40 may further include: a space definition unit for defining a strategy space based on the multiple template single-point parameters, , is the kth strategy of the i-th template single point parameter; the function definition unit is used to construct the profit function and loss function of the multiple template single point parameters based on the strategy space; the first function unit is used for the profit function: ; The second function unit is used for the loss function: ;in, is the profit of the i-th template single-point function among multiple template single-point parameters, is the strategy of the single-point parameter of the i-th template, For multiple template single point parameters, except for the other strategies of the i-th template single point parameter, is the actual parameter value of the single-point parameter of the i-th template under its corresponding strategy, is the expected parameter value of the i-th template single point parameter, is the loss of the i-th template single-point function among multiple template single-point parameters, The actual parameter value of the i-th template single point parameter Expected value The absolute difference between is the weight coefficient of the i-th template single point parameter, For the i-th template single point parameter in the strategy The cost under the condition; the first calculation unit is used to calculate the strategies of the multiple template single-point parameters through the benefit function to obtain the expected close value of each single-point parameter in the corresponding strategy; the second calculation unit is used to calculate the strategies of the multiple template single-point parameters through the loss function to obtain the expected deviation value of each single-point parameter in the corresponding strategy; the judgment unit is used to introduce the Nash equilibrium condition, and based on the Nash equilibrium condition, traverse the strategies corresponding to each template single-point parameter in combination with the expected close value and the expected deviation value of each single-point parameter in the corresponding strategy to perform optimal judgment, and determine the optimal equilibrium strategy for each template single-point parameter; the data synchronization unit is used to synchronize the optimal equilibrium strategy of each template single-point parameter to the equilibrium identification channel to generate a parameter equilibrium identification result.

[0052] The specific configuration of the equilibrium identification module 40 will be described in detail below. As described above, the Nash equilibrium condition is introduced, and based on the Nash equilibrium condition, the strategy corresponding to each template single point parameter is traversed in combination with the expected close value and the expected deviation value of each single point parameter in the corresponding strategy to perform optimal determination, and the optimal equilibrium strategy for each template single point parameter is determined. The equilibrium identification module 40 may further include: a condition definition unit for the Nash equilibrium condition is: ;in, is the optimal strategy for the single-point parameter of the i-th template, is the optimal strategy among multiple template single point parameters except the i-th template single point parameter, is any strategy of the i-th template single-point parameter; the first traversal unit is used to traverse the strategies corresponding to each template single-point parameter based on the Nash equilibrium condition, and compare the expected close value and the expected deviation value of each single-point parameter in the corresponding strategy in turn to obtain the to-be-verified equilibrium strategy of each template single-point parameter; the first judgment unit is used to judge whether the to-be-verified equilibrium strategy of each template single-point parameter satisfies the Nash equilibrium condition, and when the to-be-verified equilibrium strategy of each template single-point parameter satisfies the Nash equilibrium condition, determine the optimal equilibrium strategy of each template single-point parameter.

[0053] The specific configuration of the balance identification module 40 will be described in detail below. As described above, the optimal balance strategy of each template single-point parameter is synchronized to the balance identification channel to generate a parameter balance identification result. The balance identification module 40 may further include: a third calculation unit for performing a balance calculation based on the optimal balance strategy of each template single-point parameter to obtain a balance value of each template single-point parameter; a data comparison unit for comparing the balance value of each template single-point parameter with a preset target value to extract a balance value that does not meet the preset target value; a first identification unit for identifying the template single-point parameter corresponding to the balance value that does not meet the preset target value to obtain a parameter balance abnormality label; and a first adding unit for adding the parameter balance abnormality label to the parameter balance identification result.

[0054] The specific configuration of the deviation calculation module 50 will be described in detail below. As described above, the deviation calculation is performed based on the parameter equalization recognition result and the multiple template single-point parameters, and the deviation calculation result is detected for feedback adjustment. The deviation calculation module 50 may further include: a fourth calculation unit is used to perform deviation calculation based on the parameter equalization recognition result and the multiple template single-point parameters to determine the deviation calculation result, and the deviation calculation result includes deviation direction information and deviation size information; a data detection unit is used to detect the deviation direction information based on the deviation size information, obtain the deviation detection result, and determine whether the deviation detection result exceeds the preset deviation detection range; a second judgment unit is used to generate a feedback instruction if the deviation detection result exceeds the preset deviation detection range, and feedback is generated through the feedback instruction combined with the deviation size information and the deviation direction information to generate feedback adjustment information; a data verification unit is used to verify the feedback adjustment information, generate a feedback verification token, and determine the feedback optimization information according to the feedback verification token.

[0055] The specific configuration of the deviation calculation module 50 will be described in detail below. As described above, if the deviation detection result exceeds the preset deviation detection range, a feedback instruction is generated, and the feedback instruction is combined with the deviation size information and the deviation direction information for feedback to generate feedback adjustment information. The deviation calculation module 50 may further include: a data tracing unit for tracing the abnormality of the multiple template single-point parameters according to the parameter balance abnormality label to determine multiple abnormal parameters; an instruction generation unit for determining the feedback instruction based on the multiple abnormal parameters; a first dynamic adjustment unit for executing the feedback instruction for dynamic adjustment in combination with the deviation size information to determine the first deviation adjustment parameter; a second dynamic adjustment unit for executing the feedback instruction for dynamic adjustment in combination with the deviation direction information to determine the second deviation adjustment parameter; a second adding unit for adding the first deviation adjustment parameter and the second deviation adjustment parameter to the feedback adjustment information.

[0056] The specific configuration of the deviation calculation module 50 will be described in detail below. As described above, the feedback adjustment information is verified, a feedback verification token is generated, and the feedback optimization information is determined according to the feedback verification token. The deviation calculation module 50 may further include: a multi-dimensional verification unit for performing multi-dimensional verification on the feedback adjustment information and generating a multi-dimensional verification result; a token construction unit for constructing the feedback verification token based on the multi-dimensional verification result; an association unit for associating the feedback verification token with the feedback adjustment information and determining an association factor; a parsing unit for parsing the feedback verification token according to the association factor, adjusting the risk assessment according to the feedback parsing information, and generating a risk assessment result; and an integration unit for integrating the feedback adjustment information according to the risk assessment result and determining the feedback optimization information.

[0057] An accuracy detection device for a fully hydraulic segmented beam prefabricated formwork provided in an embodiment of the present application can execute an accuracy detection method for a fully hydraulic segmented beam prefabricated formwork provided in any embodiment of the present application, and has functional modules and beneficial effects corresponding to the execution method.

[0058] Although the present application makes various references to certain modules in the device according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present application.

[0059] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for detecting the accuracy of a fully hydraulic segmental beam prefabricated formwork, characterized in that: The method comprises: Performing three-dimensional data acquisition on the fully hydraulic segment prefabricated template to obtain a three-dimensional point cloud data set, and constructing a three-dimensional structure of the fully hydraulic segment prefabricated template based on the three-dimensional point cloud data set; Traversing the three-dimensional structure of the fully hydraulic segment prefabricated template, performing feature extraction, and determining a plurality of key points according to the three-dimensional structure features; Traversing the fully hydraulic segment prefabricated template based on the multiple key points, and performing detection to determine multiple template single point parameters; Synchronize the multiple template single-point parameters of the full hydraulic segment prefabricated template to the balance identification channel to generate a parameter balance identification result; Based on the parameter balance identification result and the multiple template single point parameters, deviation calculation is performed, the deviation calculation result is detected for feedback adjustment, and the accuracy of the full hydraulic segmental beam threshold template is intelligently detected in combination with the feedback optimization information; The method of synchronizing the plurality of template single-point parameters of the fully hydraulic segment prefabricated template to the balanced identification channel to generate a parameter balanced identification result includes: Defining a policy space based on the plurality of template single point parameters, , is the kth strategy for the i-th template single point parameter; Constructing a profit function and a loss function of the plurality of template single-point parameters based on the strategy space; The profit function is: ； The loss function is: ； in, is the profit of the i-th template single-point function among multiple template single-point parameters, is the strategy of the single-point parameter of the i-th template, For multiple template single point parameters, except for the other strategies of the i-th template single point parameter, is the actual parameter value of the single-point parameter of the i-th template under its corresponding strategy, is the expected parameter value of the i-th template single point parameter, is the loss of the i-th template single-point function among multiple template single-point parameters, The actual parameter value of the i-th template single point parameter Expected value The absolute difference between is the weight coefficient of the i-th template single point parameter, For the i-th template single point parameter in the strategy The cost of Calculating the strategies of the plurality of template single-point parameters through the profit function to obtain the expected approximate value of each single-point parameter in the corresponding strategy; The strategies of multiple template single-point parameters are calculated by the loss function to obtain the expected deviation value of each single-point parameter in the corresponding strategy; Introducing Nash equilibrium conditions, based on the Nash equilibrium conditions combined with the expected proximity value and the expected deviation value of each single point parameter in the corresponding strategy, traversing the strategy corresponding to each template single point parameter to perform optimal determination, and determining the optimal equilibrium strategy for each template single point parameter; The optimal equalization strategy of each template single-point parameter is synchronized to the equalization identification channel to generate a parameter equalization identification result.

2. The method for detecting the accuracy of a fully hydraulic segmental beam prefabricated template according to claim 1, characterized in that: Introducing a Nash equilibrium condition, based on the Nash equilibrium condition, combining the expected proximity value and the expected deviation value of each single point parameter in the corresponding strategy, traversing the strategy corresponding to each template single point parameter to perform optimal determination, and determining the optimal equilibrium strategy for each template single point parameter, the method includes: The Nash equilibrium condition is: ； in, is the optimal strategy for the single-point parameter of the i-th template, is the optimal strategy among multiple template single point parameters except the i-th template single point parameter, Any strategy for the single-point parameter of the i-th template; Based on the Nash equilibrium condition, traverse the strategies corresponding to each template single-point parameter, compare the expected approach value and the expected deviation value of each single-point parameter in the corresponding strategy in turn, and obtain the equilibrium strategy to be verified for each template single-point parameter; It is judged whether the to-be-verified balancing strategy of each template single-point parameter satisfies the Nash equilibrium condition, and when the to-be-verified balancing strategy of each template single-point parameter satisfies the Nash equilibrium condition, an optimal balancing strategy of each template single-point parameter is determined.

3. The method for detecting the accuracy of a fully hydraulic segmental beam prefabricated template according to claim 1, characterized in that: The optimal equalization strategy of each template single-point parameter is synchronized to the equalization identification channel to generate a parameter equalization identification result, the method comprising: Performing a balancing calculation based on the optimal balancing strategy of each template single point parameter to obtain a balancing value of each template single point parameter; Comparing the equilibrium value of each template single point parameter with a preset target value, and extracting the equilibrium value that does not meet the preset target value; Marking the template single-point parameter corresponding to the equalization value that does not meet the preset target value to obtain a parameter equalization abnormality label; The parameter equalization abnormality label is added to the parameter equalization identification result.

4. A method for detecting the accuracy of a fully hydraulic segmental beam prefabricated formwork according to claim 3, characterized in that: Based on the parameter equalization recognition result and the multiple template single-point parameters, deviation calculation is performed, and the deviation calculation result is detected for feedback adjustment, the method includes: Perform deviation calculation based on the parameter equalization recognition result and the multiple template single-point parameters to determine and obtain a deviation calculation result, wherein the deviation calculation result includes deviation direction information and deviation size information; Detecting the deviation direction information based on the deviation magnitude information to obtain a deviation detection result, and determining whether the deviation detection result exceeds a preset deviation detection range; If the deviation detection result exceeds the preset deviation detection range, a feedback instruction is generated, and feedback is performed by combining the deviation size information and the deviation direction information through the feedback instruction to generate feedback adjustment information; The feedback adjustment information is verified to generate a feedback verification token, and the feedback optimization information is determined according to the feedback verification token.

5. The method for detecting the accuracy of a fully hydraulic segmental beam prefabricated formwork according to claim 4, characterized in that: If the deviation detection result exceeds the preset deviation detection range, a feedback instruction is generated, and feedback is performed by combining the deviation size information and the deviation direction information through the feedback instruction to generate feedback adjustment information, and the method includes: According to the parameter balancing abnormality labels, the abnormality of the multiple template single-point parameters is traced to the source, and multiple abnormal parameters are determined; determining the feedback instruction based on the plurality of abnormal parameters; Execute the feedback instruction and perform dynamic adjustment in combination with the deviation size information to determine a first deviation adjustment parameter; Executing the feedback instruction and combining the deviation direction information to perform dynamic adjustment to determine a second deviation adjustment parameter; The first deviation adjustment parameter and the second deviation adjustment parameter are added to the feedback adjustment information.

6. The method for detecting the accuracy of a fully hydraulic segmental beam prefabricated template according to claim 4, characterized in that: The feedback adjustment information is verified to generate a feedback verification token, and feedback optimization information is determined according to the feedback verification token. The method includes: Performing multi-dimensional verification on the feedback adjustment information to generate a multi-dimensional verification result; Constructing the feedback verification token based on the multi-dimensional verification result; Associating the feedback verification token with the feedback adjustment information to determine an association factor; Parsing the feedback verification token according to the correlation factor, adjusting the risk assessment according to the feedback parsing information, and generating a risk assessment result; The feedback adjustment information is integrated according to the risk assessment result to determine the feedback optimization information.

7. A precision detection device for a fully hydraulic segmental beam prefabricated template, characterized in that: The device is used to implement the accuracy detection method of a fully hydraulic segmental beam prefabricated template according to any one of claims 1 to 6, and the device comprises: A data acquisition module, wherein the data acquisition module is used to perform three-dimensional data acquisition on the full hydraulic segment prefabricated template to obtain a three-dimensional point cloud data set, and construct a three-dimensional structure of the full hydraulic segment prefabricated template based on the three-dimensional point cloud data set; A feature extraction module, the feature extraction module is used to traverse the three-dimensional structure of the full hydraulic segment prefabricated template, and perform feature extraction, and determine a plurality of key points according to the three-dimensional structure features; A data detection module, the data detection module is used to traverse the full hydraulic segment prefabricated template based on the multiple key points, and perform detection to determine multiple template single point parameters; A balanced identification module, the balanced identification module is used to synchronize the multiple template single-point parameters of the full hydraulic segment prefabricated template to the balanced identification channel to generate a parameter balanced identification result; The deviation calculation module is used to perform deviation calculation based on the parameter balance identification result and the multiple template single-point parameters, detect the deviation calculation result for feedback adjustment, and intelligently detect the accuracy of the full hydraulic segment beam threshold template in combination with the feedback optimization information.

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