Bridge high pier multi-model equipment cooperative control method and system

Abstract

The invention relates to the technical field of intelligent cooperative control and automation, in particular to a bridge high pier multi-model equipment cooperative control method and system, and the method comprises the following steps: setting a data sampling time registration mechanism based on a construction monitoring system, and collecting a monitoring data set of multi-model equipment in combination with the registration mechanism; establishing a data fusion compensation model, and processing the monitoring data set to obtain a target monitoring information set of the construction monitoring system; constructing and utilizing a collaborative operation control framework of the multi-model equipment to analyze the collaborative control parameters so as to obtain an analysis result of the collaborative operation control framework; and combining an analysis result, a collaborative operation control framework and a target monitoring information set to coordinate and control the bridge high-pier multi-machine-type equipment. Based on a monitoring system, a time registration mechanism and a cooperative control framework, cooperative control of multiple types of equipment in bridge high pier construction is achieved, the construction risk and cost are reduced, and technical support is brought to linear operation of highway engineering.

Description

Technical Field

[0001] The present invention relates to the field of intelligent collaborative control and automation technology, and specifically to a collaborative control method and system for multiple types of equipment on high bridge piers. Background Art

[0002] Highway engineering linear operations, especially the construction of high-rise bridge piers, present high-risk challenges such as overhead work and heavy lifting. Accidents in any of these stages can have extremely serious consequences. Furthermore, high-rise pier construction involves multiple complex phases, each requiring planning and control based on actual site conditions while overcoming multiple unfavorable factors such as complex terrain and climate change. This, in turn, places extremely high demands on the coordinated control of construction equipment.

[0003] During construction, various types of construction machinery and equipment, such as cranes, excavators, and concrete pumps, are used. These devices must work together to ensure efficient and safe construction. However, traditional control methods present significant challenges: a lack of information sharing and communication mechanisms between devices leads to frequent information silos; and a lack of collaborative control mechanisms and equipment scheduling references results in low construction collaboration efficiency.

[0004] Therefore, it is necessary to optimize the existing collaborative control methods to achieve real-time sharing and unification of information among various equipment in highway projects, strengthen the coordination between equipment, improve construction efficiency, quality and accuracy, and provide guarantees for the efficient, safe and smooth construction of high piers of bridges. Summary of the Invention

[0005] In response to the shortcomings of existing methods and the demands of practical application, linear operations in highway engineering possess unique continuity and scalability, placing high demands on construction efficiency and quality control. To address these challenges and address issues such as inconsistent information sharing between system devices and inefficient collaborative operations, a registration mechanism, a fusion compensation model, and a collaborative operation control framework are introduced to improve construction efficiency, reduce economic costs, and ensure the scientific nature of collaborative control solutions, thereby ensuring smooth and safe construction of high-rise bridge piers. In the first aspect, the present invention provides a method for collaborative control of multiple types of equipment for high-rise bridge piers, the method comprising the following steps: setting a data sampling time alignment mechanism based on a construction monitoring system, collecting a monitoring data set of multiple types of equipment according to the data sampling time alignment mechanism and the construction monitoring system; establishing a data fusion compensation model, processing the monitoring data set through the data fusion compensation model to obtain a target monitoring information set of the construction monitoring system; constructing a collaborative operation control framework for multiple types of equipment, parsing collaborative control parameters according to the collaborative operation control framework and the target monitoring information set to obtain an analysis result of the collaborative operation control framework; and coordinating and controlling multiple types of equipment for high-rise bridge piers in combination with the analysis result, the collaborative operation control framework and the target monitoring information set. The present invention can improve data accuracy and timeliness, enhance collaborative operation efficiency, help ensure the smooth and safe construction process of high-rise bridge piers, adapt to the linear operation characteristics of highway engineering, improve construction efficiency and quality, and reduce the risk probability of construction.

[0006] Optionally, establishing a data sampling time alignment mechanism based on the construction monitoring system includes: analyzing a construction monitoring time period based on the construction monitoring system; and establishing a time correction analysis model and a time interval unified model in the data sampling time alignment mechanism based on the construction monitoring time period. The time correction analysis model and time interval unified model of the present invention can improve the synchronization and accuracy of monitoring data, thereby helping to ensure the accuracy and reliability of relevant data.

[0007] Optionally, the collection of monitoring data sets for multiple types of equipment based on the data sampling time alignment mechanism and the construction monitoring system includes: setting data sampling time intervals for multiple types of equipment based on the construction monitoring time period; analyzing the data sampling time intervals using the time correction analysis model to obtain a correction for the data sampling time interval; adjusting the data sampling time intervals in combination with the correction and the unified time interval model to obtain an optimized data sampling time interval; and collecting monitoring data sets for multiple types of equipment based on the optimized data sampling time intervals and the construction monitoring system. The model of the present invention can achieve consistent data sampling frequencies for each device, avoiding problems such as missing or overlapping data, thereby ensuring data integrity and continuity.

[0008] Optionally, setting a time correction value analysis model and a time interval unified model in a data sampling time alignment mechanism according to the construction monitoring time period includes: The time correction analysis model satisfies the following relationship:

[0009] in, Indicates the correction amount corresponding to the sampling time interval, express The reference time node, Indicates the Data sampling time nodes, express The reference time node, Indicates the Data sampling time nodes; The time interval unified model satisfies the following relationship:

[0010] in, Indicates the optimized data sampling time interval, Indicates the Data sampling time nodes, Indicates the Data sampling time nodes, Indicates the correction amount corresponding to the sampling time interval.

[0011] The present invention realizes time synchronization and unification of information of different devices based on an algorithm model, which is helpful for highway construction monitoring, timely discovery and early warning of potential safety hazards, and ensuring the safety of construction and the normal operation of system equipment.

[0012] Optionally, the establishing of a data fusion compensation model, and processing the monitoring data set by means of the data fusion compensation model to obtain a target monitoring information set of the construction monitoring system comprises: establishing a data fusion compensation model based on the monitoring data set; The data fusion compensation model satisfies the following relationship:

[0013] in, represents the deviation compensation amount of data fusion, represents the average value of the reference information matrix, represents the data fusion ratio coefficient, Indicates the compensation reference value of the monitoring data, Indicates the adjustment coefficient of the data sampling time interval, Indicates the deviation compensation coefficient of the data sampling time interval.

[0014] The data fusion compensation model of the present invention processes the monitoring data set, which can improve data accuracy, optimize data fusion effects, and enhance the performance of the construction monitoring system, helping to ensure the smooth progress of highway projects.

[0015] Optionally, constructing a collaborative operation control framework for multiple types of equipment includes: determining collaborative control parameters based on the collaborative operation control requirements of multiple types of equipment on high bridge piers, the collaborative control parameters including device operating distance, device operating time difference, device force value, and foundation structure force value; and obtaining the collaborative operation control framework for multiple types of equipment by combining the device operating distance, the device operating time difference, the device force value, and the foundation structure force value. The collaborative operation control framework of the present invention can monitor the operating status of various types of equipment in real time and promptly identify potential safety hazards.

[0016] Optionally, the constructing of a collaborative operation control framework for multiple types of equipment includes: setting a collaborative control parameter calculation function in the collaborative operation control framework, the collaborative control parameter calculation function including a device running distance calculation function, a device operation time difference calculation function, a device force value calculation function, and a foundation structure force value calculation function; The device runs a distance calculation function that satisfies the following relationship:

[0017] in, Indicates the running distance between different devices, Indicates the coordinate position of a device. Indicates the coordinate position of another device; The device operation time difference calculation function satisfies the following relationship:

[0018] in, Indicates the operating time difference between different devices, Indicates the time when a device starts or ends operation. Indicates the time when another device starts or ends operation; The force value calculation function of the device satisfies the following relationship:

[0019] in, Indicates the stress values of different devices, represents the stiffness coefficient of different devices, Indicates the strain of different devices; The foundation structure force value calculation function satisfies the following relationship:

[0020] in, Represents the stress results of the foundation structure. It represents the vertical foundation reaction parameter of the foundation soil. It represents the vertical foundation reaction parameter of the pile foundation soil. represents the reaction force of the foundation soil, Indicates the total area of the platform. Indicates the cohesion of the foundation soil. represents the weight coefficient of the pile foundation axial force, It represents the internal friction coefficient of the base soil.

[0021] The present invention constructs a collaborative control parameter calculation function, which can improve construction accuracy, enhance construction safety, improve construction efficiency and promote the intelligent development of construction systems.

[0022] Optionally, parsing the collaborative control parameters based on the collaborative operation control framework and the target monitoring information set to obtain the analysis results of the collaborative operation control framework includes: obtaining the operating distance between different devices based on the device operating distance calculation function; obtaining the operating time difference between different devices through the device operating time difference calculation function; obtaining the stress values of different devices based on the device force value calculation function; and obtaining the force results of the foundation structure based on the foundation structure force value calculation function. The collaborative control parameters of the present invention help to more rationally allocate and utilize equipment resources, avoid idleness and waste of system devices, and improve the utilization rate of system equipment.

[0023] Optionally, the coordination and control of multiple types of equipment on high piers of bridges in combination with the analysis results, the collaborative operation control framework and the target monitoring information set includes: conducting a comprehensive analysis of multiple types of equipment on high piers of bridges in combination with the operating distance, the operation time difference, the stress value, the force result, the collaborative operation control framework and the target monitoring information set, and achieving coordination and control of multiple types of equipment on high piers of bridges based on the comprehensive analysis results. The present invention coordinates and controls multiple types of equipment on high piers of bridges in combination with the analysis results, the collaborative operation control framework and the target monitoring information set, which can improve the construction efficiency of the project, enhance construction safety, improve construction quality, reduce construction costs and promote intelligent construction, thereby improving the overall level of high pier construction of bridges and promoting the sustainable development of the construction industry.

[0024] On the second aspect, in order to be able to efficiently execute the method for collaborative control of multiple types of equipment on high-rise bridge piers provided by the present invention, the present invention also provides a collaborative control system for multiple types of equipment on high-rise bridge piers, comprising a processor, an input device, an output device, and a memory, wherein the processor, input device, output device, and memory are interconnected, wherein the memory is used to store a computer program, and the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method for collaborative control of multiple types of equipment on high-rise bridge piers as described in the first aspect of the present invention. The collaborative control system for multiple types of equipment on high-rise bridge piers of the present invention has a compact structure and stable performance, and can stably execute the method for collaborative control of multiple types of equipment on high-rise bridge piers provided by the present invention, thereby improving the overall applicability and practical application capabilities of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a flow chart of the collaborative control method for multiple types of equipment on high bridge piers of the present invention; Figure 2 Schematic diagram showing the comparison of sampling time intervals before and after optimization in the collaborative control method for multiple types of equipment on high bridge piers of the present invention; Figure 3 This is a structural diagram of the collaborative control system for multiple types of equipment on high bridge piers of the present invention. DETAILED DESCRIPTION

[0026] See also Figure 1 In order to adapt to the linear operation characteristics of highway engineering, realize information sharing and unification among multiple devices, improve the efficiency of device collaboration, and further ensure the scientificity and practicality of the collaborative control scheme, the present invention provides a collaborative control method for multiple types of equipment on high-rise bridge piers. The collaborative control method for multiple types of equipment on high-rise bridge piers includes the following steps: S1. A data sampling time alignment mechanism is set up based on the construction monitoring system. Monitoring data sets of multiple types of equipment are collected based on the data sampling time alignment mechanism and the construction monitoring system. The specific implementation steps and contents are as follows; Set up a data sampling time alignment mechanism based on the construction monitoring system.

[0027] In this embodiment, the construction monitoring time period is analyzed based on the relevant information of the construction monitoring system. First, a construction monitoring system is constructed, which can effectively monitor and monitor the operating conditions and working information of various types of equipment on high bridge piers. The main contents are as follows: 1. Architecture of the construction monitoring system The construction monitoring system primarily consists of two subsystems: the construction site control system and the construction control management system. The former is responsible for specific on-site monitoring and real-time feedback, while the latter is responsible for overall coordination and decision-making for high-pier bridge construction. Furthermore, the construction monitoring system includes multiple subsystems, including but not limited to wind speed monitoring, stress and strain monitoring, temperature monitoring, and dynamic observation systems. Each of these subsystems is responsible for collecting and analyzing various types of construction-related data. In this embodiment, the structure of the construction monitoring system is adjusted and optimized based on the unique characteristics of highway engineering, such as continuity and expansion.

[0028] 2. Hardware configuration of construction monitoring system To ensure the effective operation of the construction monitoring system, a variety of hardware devices are installed, including but not limited to wind speed sensors, temperature sensors, stress and strain sensors, and acceleration sensors. These intelligent monitoring devices can monitor various key parameters during the construction of high bridge piers in real time. In addition, communication equipment is configured to transmit information between various systems. Control equipment, including but not limited to computers and controllers, is responsible for collecting and analyzing monitoring data in real time, facilitating the subsequent issuance of corresponding control instructions.

[0029] Through the working mechanism and operating rules of the hardware equipment of the above-mentioned system, it is possible to effectively control and understand the time cycle and detection time interval requirements of the construction monitoring system, that is, to effectively analyze the construction monitoring time cycle of the construction monitoring system. At the same time, it is possible to further understand the construction monitoring time cycle, and to efficiently collect and analyze key data of highway construction sites, thereby realizing real-time monitoring of the operating conditions of various types of equipment on high-rise bridge piers, which not only improves the monitoring efficiency, but also ensures the accuracy and timeliness of relevant monitoring data.

[0030] In this embodiment, a data sampling time alignment mechanism is introduced to ensure that different sensors can provide observation data of the same target device at the same time point. The above time alignment process involves adjusting the sensor observation time series and then synchronizing the time intervals of data sampling.

[0031] In the data sampling time alignment mechanism, the correction (adjustment value) required for the system's sampling interval is first calculated based on the data sampling time nodes and reference information of various monitoring devices in the construction monitoring system. This correction (adjustment value) is then used to standardize the sampling intervals of all sensors to a specific time interval, essentially setting them within the same time processing cycle, thereby achieving synchronized processing of the sampling intervals. This allows for scientific planning of the sensor acquisition cycles for various types of equipment on high-rise bridge piers. This unified time interval ensures data temporal and spatial consistency, providing a foundation for subsequent data fusion processing and device collaborative control.

[0032] According to the above construction monitoring time period, a time correction analysis model and a time interval unified model are set up in the data sampling time alignment mechanism.

[0033] Based on the above construction monitoring time period related information, in this embodiment, is the data sampling interval of various monitoring equipment, where Satisfies the following relationship:

[0034] in, Indicates the data sampling time interval, Indicates the Data sampling time nodes, Indicates the Data sampling time nodes.

[0035] In practical applications, due to the time error of data collection time (time node), it is necessary to calibrate the time nodes of different monitoring devices. The sampling time interval in various monitoring devices is not fixed. It is closely related to the target space state and the working state of the equipment at different times. Therefore, the time difference between adjacent moments cannot be directly used. As a basis for collecting data sets, this embodiment further performs detection and optimization on the data sampling time interval to ensure that the data sampling time interval can meet a specific time period relationship.

[0036] A time correction analysis model is set up in the data sampling time alignment mechanism. Based on this, the sampling time interval correction value (adjustment value) of the construction monitoring system is analyzed. The above time correction analysis model satisfies the following relationship:

[0037] in, Indicates the correction amount corresponding to the sampling time interval, express The reference time node, Indicates the Data sampling time nodes, express The reference time node, Indicates the Data sampling time nodes; The correction value corresponding to the sampling time interval can be used to adjust or correct the actual sampling time interval of various monitoring devices to make the time interval more consistent with theoretical or expected conditions.

[0038] The reference time node refers to the reference time node for data sampling. It is used as a reference or standard time point for different time nodes. By comparing the reference time node with the actual sampling time node, the error at different time points can be calculated.

[0039] Different data sampling time nodes refer to the actual time points at which data sampling is performed, which may deviate from the reference time nodes due to device delays, network delays, or other factors.

[0040] The parameter time correction analysis model mentioned above can be used to calculate the correction amount (adjustment value) of the system sampling time interval, and then adjust the actual sampling time interval of various monitoring devices in the system to ensure the consistency of data sampling time. The above adjustment plays an important role in application scenarios such as multi-sensor data fusion and collaborative control, and helps to improve the integrity and reliability of the database.

[0041] Then, a unified time interval model is set in the data sampling time alignment mechanism. The data sampling interval of the construction monitoring system is adjusted according to the above correction amount and the unified time interval model to achieve a unified setting of the data sampling interval.

[0042] The above time interval unified model satisfies the following relationship:

[0043] in, Indicates the optimized data sampling time interval, Indicates the Data sampling time nodes, Indicates the Data sampling time nodes, Indicates the correction amount corresponding to the sampling time interval.

[0044] The optimized data sampling time interval is the basis for setting the time interval for data sampling in the construction monitoring system. This embodiment optimizes the data sampling time interval based on the actual sampling time node, the reference time node, and the correction amount, thereby achieving the unification and standardization of the data sampling interval time.

[0045] The correction value corresponding to the sampling time interval represents the correction value (adjustment value) corresponding to the sampling time interval. This parameter is an important adjustment item for model operation. It can be used to correct the difference between the actual sampling time interval and the standard time interval, further improving the consistency of the data sampling interval.

[0046] The above-mentioned unified time interval model comprehensively considers multiple factors such as actual sampling time nodes, reference time nodes, and correction amounts, and realizes the optimization and adjustment of data sampling intervals. The above process is conducive to ensuring the validity and reliability of data in the construction monitoring system, and helps to improve the overall performance of the collaborative control method of multiple types of equipment on high piers of bridges.

[0047] At the same time, the time interval unification model takes into account the difference (correction amount) between the actual sampling time node and the reference time node, and adjusts the time interval between two adjacent sampling time nodes to obtain the optimized data sampling time interval, thereby ensuring the validity and uniformity of construction monitoring data.

[0048] Next, based on the optimized data sampling time interval, the monitoring data set of multiple types of equipment is collected. To express.

[0049] The data sampling time nodes of various equipment in the construction monitoring system meet the following relationship:

[0050] in, Represents the data sampling time node set of different devices, 1 represents the data sampling time node, 2 represents the data sampling time node, 3 represents the Data sampling time nodes, Indicates the Data sampling time nodes.

[0051] Therefore, the data sampling time intervals of various equipment in the construction monitoring system need to satisfy the following relationship:

[0052]

[0053]

[0054]

[0055]

[0056] in, represents the sampling time interval before optimization, Indicates the Data sampling time nodes, Indicates the initial time node, Indicates the Data sampling time nodes, Indicates the Data sampling time nodes, Indicates the Data sampling time nodes, Indicates the Data sampling time nodes, represents the set of sampling time intervals before optimization, Indicates the first Sampling time interval, Indicates the first Sampling time interval, Indicates the first Sampling interval.

[0057] The above data sampling time intervals are processed according to the time correction analysis model and the time interval unified model in the data sampling time alignment mechanism to obtain the optimized data sampling time intervals for various devices, and the following relationship is satisfied:

[0058] in, represents the optimized sampling time interval set, The optimized Sampling time interval, The optimized Sampling time interval, The optimized Sampling time interval, The optimized Sampling interval.

[0059] Finally, based on the optimized data sampling time interval and the construction monitoring system, a monitoring data set of multiple types of equipment is collected. The above data set satisfies the following relationship:

[0060] in, Indicates the monitoring information set corresponding to different devices. express The corresponding monitoring information, express The corresponding monitoring information, express The corresponding monitoring information, express Corresponding monitoring information.

[0061] Based on the above implementation steps and related content, it can be seen that in this embodiment, the data sampling time intervals of multiple types of equipment are set based on the construction monitoring time period; at the same time, the data sampling time intervals are analyzed using the time correction analysis model to obtain the correction amount of the data sampling time interval; and then the data sampling time intervals are adjusted in combination with the correction amount and the unified time interval model to obtain the optimized data sampling time interval; finally, based on the optimized data sampling time interval and the construction monitoring system, a set of monitoring data of multiple types of equipment is collected.

[0062] In this implementation case, a comparative analysis of the sampling time intervals before and after optimization was conducted in the system. In order to intuitively demonstrate the optimization effect of the time interval, a comparative diagram of the sampling time intervals before and after optimization was drawn. For details, please refer to Figure 2 , where A represents the sampling time interval before the optimization of multiple equipment types, and B represents the sampling time interval after the optimization of multiple equipment types.

[0063] Furthermore, the method for obtaining monitoring data of multiple types of equipment in this embodiment is only an optional condition of the present invention. In other embodiments, the method for obtaining monitoring data of multiple types of equipment can be optimized and replaced according to the actual data collection requirements and sampling time of multiple types of equipment. The actual data collection requirements and sampling time of different equipment will be different. Selecting a method that is more suitable for the current scenario can improve the accuracy of monitoring data and provide more powerful data support for collaborative control and decision analysis of highway projects.

[0064] S2. Establish a data fusion compensation model. Use the data fusion compensation model to process the monitoring data set to obtain the target monitoring information set of the construction monitoring system. The specific implementation steps and contents are as follows: In order to integrate the monitoring information of different monitoring devices in the system, it is necessary to normalize the monitoring information set and convert the diverse monitoring data into a unified standard to generate the system target monitoring information set, that is, to transform and map the monitoring data set from the original state space to the integrated state space, and then obtain the target monitoring information set required by the system.

[0065] In order to achieve unified management and collaborative optimization of system monitoring information and meet the collaborative control requirements among multiple devices, a data fusion compensation model is established in the embodiment based on the characteristics of highway engineering operations, distributed consistency algorithms and equipment interaction requirements. The model can analyze the data deviation compensation amount of different monitoring devices, and then dynamically adjust and optimize the monitoring information of different devices, which is conducive to information sharing and interactive cooperation among different devices in the system.

[0066] First, the deviation compensation amount of data fusion is analyzed based on the monitoring data set S[h(T)] of multiple types of equipment. The sampling interval time sets of different equipment are analyzed to evaluate the deviation compensation amount in the data fusion process. This helps to understand the errors in the data fusion process and take corresponding measures to correct them, thereby ensuring the accuracy of the system target monitoring information.

[0067] A data fusion compensation model was established based on the above monitoring data set, which satisfies the following relationship:

[0068] in, represents the deviation compensation amount of data fusion, represents the average value of the reference information matrix, represents the data fusion ratio coefficient, Indicates the compensation reference value of the monitoring data, Indicates the adjustment coefficient of the data sampling time interval, Indicates the deviation compensation coefficient of the data sampling time interval.

[0069] Bias compensation refers to the difference or deviation between the data fusion result and the actual value during the data fusion process due to factors such as data source inconsistency, sensor errors, data transmission delays or loss, and limitations of the fusion algorithm. The data fusion compensation model analyzes the bias compensation using parameters such as the reference information matrix, data fusion ratio, time interval adjustment coefficient, and compensation coefficient, effectively reflecting the actual deviation.

[0070] The average value of the reference information matrix can be used to reflect the overall level and trend of the reference information. In the embodiment, the average value of the reference information matrix can be obtained by averaging the reference information matrix, which helps to eliminate abnormal fluctuations in individual data and improve the stability and accuracy of the data fusion compensation model.

[0071] The data fusion ratio coefficient is mainly used to adjust the weights and contributions of different data sources during the data fusion process. It is an adjustable parameter. By adjusting its ratio coefficient value, the effect of data fusion can be optimized to make the fused data more in line with actual needs.

[0072] The compensation reference value of the monitoring data can be used to determine the starting point and range of data compensation. In the embodiment, it is mainly set based on historical data of the highway project or system structure status, which helps to ensure the validity of the data compensation result.

[0073] The adjustment coefficient of the data sampling time interval can be used to adjust the impact of the data sampling time interval on the data fusion effect. The above adjustment coefficient can be used to optimize the data sampling strategy and improve the real-time performance and accuracy of the data fusion results.

[0074] The deviation compensation coefficient of the data sampling time interval is mainly used to measure and compensate for the deviation caused by the data sampling time interval. It is calculated based on the difference between the actual sampling situation and the reference sampling situation, which helps to ensure the consistency of the data sampling results.

[0075] The above-mentioned data fusion compensation model comprehensively considers multiple factors such as the reference information matrix, data fusion ratio, monitoring data reference value, time interval adjustment coefficient, etc., and realizes effective compensation of deviations in the data fusion process. The above-mentioned process helps to improve the accuracy of data fusion results and provides support for the practical application of the collaborative control method of multiple equipment types on high-rise bridge piers.

[0076] Then, the monitoring data set is processed by the above-mentioned data fusion compensation model to obtain the target monitoring information set of the construction monitoring system.

[0077] Based on the above embodiments, it can be seen that the monitoring data set of multiple types of equipment satisfies the following relationship:

[0078] in, Indicates the monitoring information set corresponding to different devices. express The corresponding monitoring information, express The corresponding monitoring information, express The corresponding monitoring information, express Corresponding monitoring information.

[0079] The monitoring data set is processed according to the above data fusion compensation model, and then the target monitoring information set of the construction monitoring system is obtained, which satisfies the following relationship:

[0080]

[0081] in, Represents the target monitoring information set of the construction monitoring system, represents the deviation compensation amount of data fusion, express The corresponding monitoring information, express The corresponding monitoring information, express The corresponding monitoring information, express The corresponding monitoring information, Indicates the deviation after compensation , Indicates the deviation after compensation , Indicates the deviation after compensation , Indicates the deviation after compensation .

[0082] The data fusion compensation model is used to analyze and compensate for deviations in the system monitoring data, thereby improving the accuracy of the fused data set and enhancing the reliability of the entire construction monitoring system. This allows the collaborative control method for multiple types of equipment on high-rise bridge piers to adapt to complex and changing construction environments and highway operating conditions.

[0083] Furthermore, the optimization method and specific analysis model for the target monitoring information set in this embodiment are merely optional conditions of the present invention. In one or more other embodiments, the optimization method for target monitoring information can be modified based on the fusion characteristics of system data and the actual application of the construction monitoring system. Different construction environments and monitoring needs have different requirements for data fusion and monitoring information. Replacing and adjusting the optimization method allows the present invention to flexibly adapt to different highway projects, thereby ensuring the feasibility of the collaborative control method.

[0084] S3. Construct a collaborative operation control framework for multiple types of equipment. Analyze collaborative control parameters based on the collaborative operation control framework and target monitoring information set to obtain analysis results of the collaborative operation control framework. The specific implementation steps and content are as follows: The collaborative control parameters are determined based on the collaborative operation control requirements of multiple types of equipment on high piers of bridges. The above collaborative control parameters mainly include the device operation distance, device operation time difference, device force value and foundation structure force value; then, the collaborative operation control framework of multiple types of equipment can be obtained by combining the device operation distance, device operation time difference, device force value and foundation structure force value.

[0085] In order to meet the collaborative operation control requirements of multiple types of equipment in the construction of high bridge piers, it is first necessary to determine the key collaborative control parameters in highway engineering. The relevant parameters reflect the interaction and coordination relationship between system equipment.

[0086] The device operating distance measures the relative position relationship of different equipment during the construction process, which is crucial for avoiding collisions and ensuring the effective use of construction space. By calculating and controlling the operating distance of each equipment, orderly scheduling and collaborative operation of system equipment can be achieved.

[0087] The device operation time difference reflects the difference in time points when different equipment starts or ends operations. By reasonably adjusting the operation time difference, the construction process can be optimized, waiting time can be reduced, and the overall construction efficiency of the project can be improved.

[0088] The stress value of the device is directly related to the construction capacity and safety of each equipment. By real-time monitoring, analysis and control of the stress conditions of the equipment, it can ensure that all types of equipment can operate stably under reasonable loads and avoid damage or safety accidents caused by overload.

[0089] The foundation serves as the basis for supporting the construction of the entire bridge pier. The stress value of the foundation structure can ensure the stability of the construction process and the bearing capacity to meet the construction requirements of different highway projects.

[0090] After determining the above-mentioned collaborative control parameters, a collaborative operation control framework for multiple types of equipment was constructed by combining the collaborative control parameters with the characteristics of highway projects. This framework not only includes real-time monitoring and control mechanisms for parameters, but also can realize information integration and sharing. Through efficient information integration and sharing mechanisms, data exchange and synchronization of different equipment can be achieved, providing a basis for engineering collaborative control methods; at the same time, system safety monitoring and early warning can be realized. By establishing a safety monitoring and early warning system, potential safety hazards can be discovered and responded to in a timely manner, ensuring the safety and stability of different highway projects.

[0091] In summary, by collaboratively controlling parameters and combining key elements such as information integration, intelligent decision-making, safety monitoring, and dynamic adjustment, a comprehensive, efficient, and safe collaborative operation control framework for multiple equipment types was constructed, providing information support for high-pier bridge construction.

[0092] Furthermore, a collaborative control parameter calculation function is set up in the collaborative operation control framework, and the above-mentioned collaborative control parameter calculation function mainly includes: device operation distance calculation function, device operation time difference calculation function, device force value calculation function and foundation structure force value calculation function.

[0093] In the collaborative operation control framework, in order to quickly and accurately capture the numerical information and changing trends of different collaborative control parameters, a collaborative control parameter calculation function was designed. This not only improves the timeliness of parameter acquisition, but also ensures the accuracy of the data, providing a solid basis for engineering decision-making and scheme adjustment.

[0094] The device operation distance calculation function in the collaborative operation control framework satisfies the following relationship:

[0095] in, Indicates the running distance between different devices, Indicates the coordinate position of a device. Indicates the coordinate position of another device; The operating distance between different devices refers to the straight-line distance between two devices in space. It can be used to measure the relative position relationship between the two devices and is an important reference indicator in collaborative operation control.

[0096] In the coordinate position of any device, Indicates the position of the device in the horizontal direction (x-axis), Indicates the position of the device in the vertical direction (y-axis). Based on this, the specific position of different devices in space can be determined. It is the basis for calculating the running distance between different devices. and Necessary parameters to calculate the running distance between devices.

[0097] Furthermore, the embodiment sets a safe operation distance threshold and its early warning mechanism.

[0098] To ensure safety during highway construction, a safe operating distance threshold is also set. This threshold is used to assess whether the relative distance between different devices is within a safe range. When the actual distance between different devices is less than or equal to the safe operating distance threshold, the safety warning device in the system will be triggered to remind relevant operators to take necessary preventive measures in a timely manner.

[0099] In the embodiment, the above-mentioned safe operation distance threshold ( ) is set in advance to a constant ( ), this constant represents the minimum safe distance allowed under different equipment types, sizes and safety standards, The determination of the threshold value needs to comprehensively consider the physical characteristics of various types of equipment on high piers of bridges, the highway operating environment and the engineering safety risks to ensure the rationality and effectiveness of the threshold value.

[0100] The above-mentioned safe operating distance threshold satisfies the following relationship:

[0101] in, Indicates the device safety distance threshold. Indicates the constant corresponding to the safety distance threshold.

[0102] Therefore, when the actual running distance between different equipment Less than or equal to ,Right now When the vehicle is in collision, the system will immediately trigger the safety warning device and send out a safety warning signal, prompting the operator to pay attention to the distance between the system equipment to avoid potential collisions or safety accidents, thereby improving the safety of the construction process and further ensuring the smooth implementation of the collaborative control method of multiple types of equipment on high piers of bridges.

[0103] The device operation time difference calculation function in the collaborative operation control framework satisfies the following relationship:

[0104] in, Indicates the operating time difference between different devices, Indicates the time when a device starts or ends operation. Indicates the time when another device starts or ends operation; In the collaborative control method for multiple types of equipment on high bridge piers, in order to maximize operational efficiency and avoid resource conflicts, the time window overlap of different devices within the same operating area is calculated, and the operation time difference analysis is achieved by comparing the start or end time of each device.

[0105] In practical applications, other time difference calculation methods need to be considered, such as calculating the difference between the start time of two devices, the difference between the end time, or the difference between the start time of one device and the end time of another device, so as to more accurately analyze the operation time difference between different devices. The operating time difference between different devices can be a positive value (indicating a time gap), zero (indicating complete time overlap) or a negative value (indicating partial time overlap). In this case, its absolute value needs to be taken to indicate the actual time interval or degree of overlap.

[0106] When using the device operation time difference calculation function, it is necessary to clarify and The specific time points represented by them, that is, they should uniformly represent the start time or end time of operation of different devices.

[0107] When calculating the operating time difference between devices, set and As a key time parameter, the time nodes expressed by the above two parameters must be consistent, that is, they represent the start time of operation of different devices at the same time, or represent the end time of operation of different devices at the same time.

[0108] In an alternative embodiment, and Both represent the start time of the operation, so they correspond to the start instants of two different devices. By calculating and The difference between them can be used to analyze the time interval between the two devices starting operations.

[0109] In another optional embodiment, and Both represent the end of the operation time, then they correspond to the completion instants of two different devices, and then calculate and The difference between the two devices can reveal the time interval between the completion of the operation.

[0110] By calculating the time difference between operations, we can evaluate the degree of time overlap between different devices in the same operation area, and then optimize the operation schedule, reduce waiting time, and improve overall operation efficiency. If the time difference between different devices is small or zero, the operation plan can be adjusted to avoid conflicts between equipment and waste of resources.

[0111] The device force calculation function in the collaborative operation control framework satisfies the following relationship:

[0112] in, Indicates the stress values of different devices, represents the stiffness coefficient of different devices, Indicates the strain of different devices; In the collaborative operation control framework, the device force value calculation function is used to evaluate the stress conditions borne by different devices during the operation process.

[0113] Stress values represent the amount of stress experienced by different devices under specific operating conditions. These values measure the material's ability to resist deformation under load. Understanding the stress profile of each device during collaborative operations helps prevent overloads, ensure operational safety, and optimize overall efficiency.

[0114] The stiffness coefficient indicates the stiffness of different devices, specifically their ability to resist deformation when subjected to force. The stiffness coefficient is an inherent property of the device material and is related to factors such as the material's elastic modulus and cross-sectional dimensions. A higher stiffness coefficient indicates a device's resistance to deformation under load, thereby maintaining better stability. During collaborative operations, device stiffness contributes to ensuring both quality and safety.

[0115] Strain refers to the relative deformation of a device when it is subjected to force. The strain value reflects the actual deformation of different devices under force. By monitoring the strain value, potential problems of the device, such as overload and fatigue, can be discovered in a timely manner, so that corresponding control measures can be taken.

[0116] The device force calculation function evaluates the stress condition of the device through stiffness coefficient and strain, providing a reference basis for the effective analysis and scientific control of the collaborative control method. By calculating and analyzing the stress values of each device, we can better understand the stress state of the device during operation, thereby optimizing the operation plan of different highway projects, improving operation efficiency, and ensuring construction safety.

[0117] Construction projects interact with the foundation. In practical applications, an interaction mechanism exists between track beams and the foundation. This mechanism involves the deformation of the track beams under load and the foundation's response to this deformation. To better understand this interaction, this embodiment establishes a foundation structure force calculation function within the collaborative operation control framework based on the elastic foundation beam calculation method.

[0118] In the embodiment, a device force value calculation function is established based on the assumption of a Winkler elastic foundation beam to predict the stress conditions of the foundation structure. Since the pressure per unit area of the foundation is proportional to the foundation settlement at that location, it further reflects the elastic characteristics of the soil. The device force value calculation function can quantitatively describe the stress conditions of the foundation during the construction process, thereby analyzing and predicting the stress conditions of the engineering foundation.

[0119] The calculation function of the foundation structure force value in the collaborative operation control framework satisfies the following relationship:

[0120] in, Represents the stress results of the foundation structure. It represents the vertical foundation reaction parameter of the foundation soil. It represents the vertical foundation reaction parameter of the pile foundation soil. represents the reaction force of the foundation soil, Indicates the total area of the platform. Indicates the cohesion of the foundation soil. represents the weight coefficient of the pile foundation axial force, It represents the internal friction coefficient of the base soil.

[0121] The aforementioned foundation structure force calculation function is primarily used to assess the stress response of a foundation structure under specific operating conditions. The foundation structure force result, representing the stress response to external loads, is a comprehensive evaluation indicator. By calculating these force results, we can understand the stress state of the foundation structure for various highway projects, providing a reference for foundation design, construction, and maintenance.

[0122] The vertical foundation reaction parameter of the cap foundation soil refers to the reaction characteristic parameter of the foundation soil under the cap under the vertical load. This parameter reflects the stiffness and bearing capacity of the cap foundation soil.

[0123] The vertical foundation reaction parameter of the pile foundation soil refers to the reaction characteristic parameter of the foundation soil under the pile foundation under the action of vertical load. This parameter reflects the bearing capacity and deformation characteristics of the pile foundation soil, and is of great significance for ensuring the stability and bearing capacity of the pile foundation.

[0124] The foundation soil reaction force is an important parameter in the stress analysis of foundation structure. The above-mentioned foundation soil reaction force refers to the reaction force generated by the foundation soil when it is subjected to external loads, which reflects the response ability of the foundation soil to external loads.

[0125] The above foundation soil reaction force needs to satisfy the following relationship:

[0126] in, represents the reaction force of the foundation soil, represents the elastic coefficient of soil, Indicates the foundation settlement value.

[0127] The elastic modulus of soil refers to its elastic properties, or its ability to return to its original shape after being subjected to stress. It is a physical quantity that measures the soil's elasticity. The elastic modulus of soil determines the degree of deformation and recovery of the foundation soil under external loads. A higher elastic modulus indicates less deformation and greater recovery, which helps improve the stability and bearing capacity of the foundation structure.

[0128] The foundation settlement value refers to the amount of settlement that occurs when the foundation is subjected to external loads. It can measure the degree of deformation of the foundation and evaluate the stability of the engineering foundation structure. During the coordinated control and construction process of multiple types of equipment, effective analysis of the foundation settlement value can ensure the stability and safety of highway projects.

[0129] The total area of the foundation refers to the ground area occupied by the engineering foundation. The area of the foundation determines the force distribution range of the foundation structure and plays an important role in evaluating the overall force state of the foundation structure.

[0130] Foundation soil cohesion refers to the cohesive force between foundation soil particles, that is, the force of mutual attraction between soil particles. Foundation soil cohesion is one of the important factors affecting the stability of foundation structure, which determines the deformation and destruction characteristics of foundation soil under external loads.

[0131] The pile foundation axial force weight coefficient refers to the weight of the pile foundation axial force in the foundation force analysis. The pile foundation axial force is an important component in the foundation structure force analysis. The weight coefficient can reflect the degree of influence of the pile foundation axial force on the foundation structure.

[0132] The internal friction angle coefficient of the foundation soil refers to the friction angle between the foundation soil particles under shear action. The above internal friction angle coefficient is a key factor affecting the shear stability and bearing capacity of the foundation structure, which determines the deformation characteristics of the foundation soil under shear load.

[0133] The various parameters in the foundation structure force calculation function together constitute the basis for foundation structure force analysis. By comprehensively considering the influence of relevant parameters, the stress state of the foundation structure under specific conditions can be evaluated more accurately, providing a scientific basis for the foundation design, construction and maintenance of highway projects.

[0134] Finally, the analysis results of the collaborative operation control framework are obtained according to the collaborative control parameter calculation function in the collaborative operation control framework.

[0135] In this embodiment, the running distance between different devices is obtained based on the device running distance calculation function; the operation time difference between different devices is obtained through the device operation time difference calculation function; the stress values of different devices are obtained based on the device force value calculation function; and the force result of the foundation structure is obtained according to the foundation structure force value calculation function.

[0136] The collaborative control parameter calculation function in the collaborative operation control framework is used to obtain comprehensive analysis results.

[0137] First, the relative operating distances between devices were obtained through the device operating distance calculation function. This data provides an intuitive understanding of the spatial layout and relative positions between devices.

[0138] Next, the device operation time difference calculation function is used to calculate the operation time differences between different devices, which helps to understand the operation timing and collaborative efficiency between devices.

[0139] Then, the stress values borne by each device during operation were evaluated based on the device force value calculation function. The above information helps to ensure the safe operation of various types of equipment and prevent potential operational failures.

[0140] Finally, the foundation structure force calculation function was used to analyze the stress conditions of the foundation structure under operating conditions, providing key data on foundation stability and bearing capacity during the construction of high bridge piers.

[0141] In summary, through the above calculation functions, the collaborative operation control framework was gradually analyzed from multiple dimensions, such as the device operating distance, operation time difference, device force value, and foundation structure force results, thereby obtaining comprehensive and accurate analysis results, which is conducive to the effective implementation and scientific application of the collaborative control method for multi-type equipment of high-rise bridge piers.

[0142] Furthermore, in this embodiment, the acquisition and analysis method of the analysis results of the collaborative operation control framework is only an optional condition of this embodiment. In one or some other embodiments, the analysis method of the collaborative operation control framework can be optimized according to the collaborative control objectives of multiple types of equipment and the actual situation of high piers of bridges, which can improve the efficiency of collaborative operations and thus enhance the feasibility of the control method.

[0143] S4. Combine the analysis results, collaborative operation control framework, and target monitoring information collection to coordinate and control multiple types of equipment on bridge piers. The specific implementation steps and contents are as follows: In this embodiment, a comprehensive analysis is performed on various types of equipment on high bridge piers based on the operating distance, operation time difference, stress value, force results, collaborative operation control framework and target monitoring information set, and coordination and control of various types of equipment on high bridge piers are achieved based on the comprehensive analysis results.

[0144] Finally, based on the above collaborative control parameter analysis results, collaborative operation control framework, and target monitoring information collection, coordination and control of multiple types of equipment in bridge high pier construction was implemented. The specific implementation process and content are as follows: First, a comprehensive evaluation of various types of equipment used in bridge high pier construction was conducted based on the collaborative operation control framework and target monitoring information set. The above evaluation content mainly included the operating distance, operation time difference, stress distribution, and force conditions between different types of equipment. At the same time, it was closely combined with the target monitoring information of collaborative control, which is conducive to achieving effective coordination and accurate control among multiple types of equipment.

[0145] In an optional embodiment, for the collaborative operation of multiple types of equipment on high bridge piers, the operation paths and schedules of the multiple types of equipment are optimized according to the actual progress of the highway project and the actual conditions of the site, effectively avoiding the mutual interference or collision risks between different devices, and ensuring the construction safety of different highway projects while maximizing construction efficiency.

[0146] Furthermore, a safety warning and emergency response mechanism has been established within a collaborative control method for multiple types of equipment on high-rise bridge piers. This mechanism collects and backs up the analysis results of the collaborative operation control framework in real time. Based on the relevant analysis results, monitoring data, and the collaborative control framework, it can issue timely safety warning signals, alerting relevant personnel to pay close attention and address potential operational risks. Furthermore, emergency response plans have been developed for various highway projects to ensure swift and effective action in the event of an accident or emergency, minimizing losses to the highway project.

[0147] This embodiment of the collaborative control method for multiple equipment types on high bridge piers comprehensively evaluates the travel distances, operating time differences, stress distribution, and load conditions between equipment types. Combined with the target monitoring information for collaborative control, this method achieves effective coordination and accurate control of multiple equipment types, improving highway construction efficiency. Furthermore, based on the actual progress of the highway project and site conditions, the operating paths and schedules of multiple equipment types are optimized and adjusted, effectively avoiding the risk of interference or collision between the multiple equipment types and further ensuring the smooth progress of the highway project.

[0148] At the same time, the collaborative control method for multiple types of equipment on high-rise bridge piers also establishes a safety warning and emergency response mechanism, which can collect and analyze the analysis results of the collaborative operation control framework in real time, and issue safety warning signals in a timely manner to ensure that actions can be taken quickly and effectively in emergency situations, thereby minimizing losses to highway projects.

[0149] The collaborative control method for multiple types of equipment on high bridge piers provides comprehensive and accurate data support for highway projects through comprehensive analysis and real-time monitoring, which helps to make more scientific collaborative control decisions, further optimize the construction plan of highway projects, and improve project quality and efficiency.

[0150] See Figure 3 In an optional embodiment, in order to be able to efficiently execute the method for collaborative control of multiple types of equipment on high-rise bridge piers provided by the present invention, the present invention also provides a collaborative control system for multiple types of equipment on high-rise bridge piers, in which the input device, processor, output device and memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the specific steps of the relevant embodiments of the method for collaborative control of multiple types of equipment on high-rise bridge piers provided by the present invention. The collaborative control system for multiple types of equipment on high-rise bridge piers of the present invention has a complete structure, is objective and stable, and can efficiently execute the method for collaborative control of multiple types of equipment on high-rise bridge piers of the present invention, thereby improving the overall applicability and practical application capabilities of the present invention.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. A method for collaborative control of multiple equipment types on high bridge piers, characterized in that: The steps include: Setting a data sampling time alignment mechanism based on the construction monitoring system, and collecting monitoring data sets of multiple types of equipment according to the data sampling time alignment mechanism and the construction monitoring system; Establishing a data fusion compensation model, and processing the monitoring data set through the data fusion compensation model to obtain a target monitoring information set of the construction monitoring system; Constructing a collaborative operation control framework for multiple types of equipment, parsing collaborative control parameters based on the collaborative operation control framework and target monitoring information sets to obtain analysis results of the collaborative operation control framework; The analysis results, the collaborative operation control framework and the target monitoring information set are combined to coordinate and control various types of equipment on high piers of bridges.

2. The method for coordinated control of multiple equipment types on high bridge piers according to claim 1 is characterized in that: The data sampling time alignment mechanism based on the construction monitoring system includes: Analyze the construction monitoring time cycle based on the construction monitoring system; A time correction analysis model and a time interval unified model are set in the data sampling time alignment mechanism according to the construction monitoring time period.

3. The method for coordinated control of multiple equipment types on high bridge piers according to claim 2 is characterized in that: The monitoring data set of multiple types of equipment collected according to the data sampling time alignment mechanism and the construction monitoring system includes: Setting data sampling time intervals for multiple types of equipment based on the construction monitoring time period; Analyzing the data sampling time interval using the time correction analysis model to obtain a correction value for the data sampling time interval; Adjusting the data sampling time interval in combination with the correction amount and the time interval unified model to obtain an optimized data sampling time interval; Based on the optimized data sampling time interval and the construction monitoring system, a monitoring data set of multiple types of equipment is collected.

4. The method for coordinated control of multiple equipment types on high bridge piers according to claim 2 is characterized in that: The setting of the time correction analysis model and the time interval unified model in the data sampling time alignment mechanism according to the construction monitoring time period includes: The time correction analysis model satisfies the following relationship: ， in, Indicates the correction amount corresponding to the sampling time interval, express The reference time node, Indicates the Data sampling time nodes, express The reference time node, Indicates the Data sampling time nodes; The time interval unified model satisfies the following relationship: ， in, Indicates the optimized data sampling time interval, Indicates the Data sampling time nodes, Indicates the Data sampling time nodes, Indicates the correction amount corresponding to the sampling time interval.

5. The method for coordinated control of multiple equipment types on high bridge piers according to claim 1 is characterized in that: The establishing of the data fusion compensation model and processing the monitoring data set by the data fusion compensation model to obtain the target monitoring information set of the construction monitoring system includes: establishing a data fusion compensation model based on the monitoring data set; The data fusion compensation model satisfies the following relationship: ， in, represents the deviation compensation amount of data fusion, represents the average value of the reference information matrix, represents the data fusion ratio coefficient, Indicates the compensation reference value of the monitoring data, Indicates the adjustment coefficient of the data sampling time interval, Indicates the deviation compensation coefficient of the data sampling time interval.

6. The method for coordinated control of multiple equipment types on high bridge piers according to claim 1 is characterized in that: The collaborative operation control framework for building multiple types of equipment includes: Determine collaborative control parameters based on the collaborative operation control requirements of multiple types of equipment on high-rise bridge piers. The collaborative control parameters include device operation distance, device operation time difference, device force value, and foundation structure force value. A collaborative operation control framework for multiple types of equipment is obtained by combining the device running distance, the device operation time difference, the device force value and the foundation structure force value.

7. The method for coordinated control of multiple types of equipment on high bridge piers according to claim 6 is characterized in that: The collaborative operation control framework for building multiple types of equipment includes: A collaborative control parameter calculation function is set in the collaborative operation control framework, wherein the collaborative control parameter calculation function includes a device operation distance calculation function, a device operation time difference calculation function, a device force value calculation function, and a foundation structure force value calculation function; The device runs a distance calculation function that satisfies the following relationship: ， in, Indicates the running distance between different devices, Indicates the coordinate position of a device. Indicates the coordinate position of another device; The device operation time difference calculation function satisfies the following relationship: ， in, Indicates the operating time difference between different devices, Indicates the time when a device starts or ends operation. Indicates the time when another device starts or ends operation; The force value calculation function of the device satisfies the following relationship: ， in, Indicates the stress values of different devices, represents the stiffness coefficient of different devices, Indicates the strain of different devices; The foundation structure force value calculation function satisfies the following relationship: ， in, Represents the stress results of the foundation structure. It represents the vertical foundation reaction parameter of the foundation soil. It represents the vertical foundation reaction parameter of the pile foundation soil. represents the reaction force of the foundation soil, Indicates the total area of the platform. Indicates the cohesion of the foundation soil. represents the weight coefficient of the pile foundation axial force, It represents the internal friction coefficient of the base soil.

8. The method for coordinated control of multiple types of equipment on high bridge piers according to claim 7 is characterized in that: The step of parsing the collaborative control parameters based on the collaborative operation control framework and the target monitoring information set to obtain the analysis result of the collaborative operation control framework includes: Obtaining the running distances between different devices according to the device running distance calculation function; Obtaining the operation time difference between different devices through the device operation time difference calculation function; Obtaining stress values of different devices based on the device force value calculation function; The force result of the foundation structure is obtained according to the foundation structure force value calculation function.

9. The method for coordinated control of multiple equipment types on high bridge piers according to claim 8, characterized in that: The coordination and control of multiple types of equipment on bridge high piers by combining the analysis results, the collaborative operation control framework and the target monitoring information set includes: A comprehensive analysis is performed on various types of equipment on high bridge piers based on the running distance, the operation time difference, the stress value, the force result, the collaborative operation control framework and the target monitoring information set, and coordination and control of various types of equipment on high bridge piers are achieved based on the comprehensive analysis results.

10. A coordinated control system for multiple equipment types on high bridge piers, characterized in that: The system includes a processor, an input device, an output device and a memory, which are interconnected. The memory is used to store a computer program, and the computer program includes program instructions. The processor is configured to call the program instructions to execute the collaborative control method for multiple types of equipment on high-rise bridges as described in any one of claims 1 to 9.

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