A spherical grid hoisting construction control method and system based on overall positioning

Abstract

The present invention relates to a spherical grid hoisting construction control method and system based on overall positioning, which relates to the field of hoisting control. The method pre-collects a welding parameter array to perform welding deformation analysis, utilizes a hoisting equipment array to hoist according to preset parameters and performs overall positioning monitoring at a specific time, analyzes grid deformation in combination with welding deformation parameters, and then optimizes hoisting parameters to achieve precise hoisting of the spherical grid. The method solves the technical problems of difficult installation, difficult precision assurance, high safety risks of high-altitude operations, and long construction period in the hoisting construction of the spherical grid, thereby achieving the technical effects of improving hoisting precision, shortening construction period, reducing safety risks, and ensuring structural stability.

Description

Technical Field

[0001] The present invention relates to the field of hoisting control, and in particular to a spherical grid hoisting construction control method and system based on overall positioning. Background Art

[0002] In modern construction, especially for large public buildings like convention centers and stadiums, complex spatial grid systems are often used for roofing. Spherical grid systems are particularly popular for their stability and aesthetic appeal. However, the installation of spherical grid systems presents numerous challenges, including difficulty in installation, high precision requirements, and significant safety risks.

[0003] Among existing construction methods, spherical grids are often installed in blocks or in bulk at high altitudes. These methods not only have a long construction period, but also place high demands on high-altitude operations, posing significant safety risks. Furthermore, due to the complex high-altitude working environment, it is difficult to ensure precise alignment and overall stability during the installation process, often resulting in low installation accuracy and affecting the overall aesthetics and functionality of the building. With the advancement of science and technology, digital and intelligent technologies have been widely used in the field of construction engineering. Digital positioning technology uses high-precision measuring equipment, such as total stations and laser scanners, to accurately measure and locate building structures. Intelligent technologies, such as the Internet of Things and smart sensors, can monitor various parameters during the construction process in real time, providing data support for construction control. Summary of the Invention

[0004] The present invention aims to solve the technical problems in the existing technology of spherical grid hoisting construction, such as great installation difficulty, difficulty in ensuring accuracy, high safety risks of high-altitude operations and long construction period, and provides a spherical grid hoisting construction control method and system based on overall positioning to solve the problems.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] In a first aspect, the present invention provides a spherical grid hoisting construction control method based on overall positioning, the method comprising: in the pre-welding of the spherical grid, collecting welding parameter arrays of multiple welding positions, performing welding deformation analysis, and obtaining a welding deformation parameter array; hoisting the pre-welded spherical grid according to a preset hoisting parameter array through a hoisting equipment array, performing overall positioning monitoring processing on multiple positioning positions at a first moment, obtaining a first deviation information array, and performing grid deformation analysis in combination with the welding deformation parameter array to obtain a first grid deformation parameter; optimizing the hoisting parameters of the hoisting equipment array according to the first grid deformation parameter to obtain an optimized compensation hoisting parameter array, and continuing the hoisting and overall positioning monitoring analysis until the hoisting of the spherical grid is completed.

[0007] In the second aspect, the present invention provides a spherical grid hoisting construction control system based on overall positioning, the system comprising: a parameter acquisition module, used to collect welding parameter arrays of multiple welding positions during pre-welding of the spherical grid, perform welding deformation analysis, and obtain a welding deformation parameter array; a positioning monitoring module, used to hoist the pre-welded spherical grid according to a preset hoisting parameter array through a hoisting equipment array, perform overall positioning monitoring processing on multiple positioning positions at a first moment, obtain a first deviation information array, and perform grid deformation analysis in combination with the welding deformation parameter array to obtain a first grid deformation parameter; a parameter optimization module, used to optimize the hoisting parameters of the hoisting equipment array according to the first grid deformation parameter, obtain an optimized compensation hoisting parameter array, and continue hoisting and overall positioning monitoring analysis until the hoisting of the spherical grid is completed.

[0008] The beneficial effects of the present invention are: by pre-collecting the welding parameter array to perform welding deformation analysis, using the lifting equipment array to lift according to preset parameters and perform overall positioning monitoring at specific times, combining the welding deformation parameters to analyze the grid deformation, and then optimizing the lifting parameters to achieve precise lifting of the spherical grid, achieving the technical effects of improving lifting accuracy, shortening the construction period, reducing safety risks and ensuring structural stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 The present invention provides a schematic flow chart of a spherical grid hoisting construction control method based on overall positioning.

[0010] Figure 2 This is a structural schematic diagram of a spherical grid hoisting construction control system based on overall positioning provided by the present invention.

[0011] Description of the accompanying drawings: parameter acquisition module 11, positioning monitoring module 12, parameter optimization module 13. DETAILED DESCRIPTION

[0012] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0013] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the specified features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0014] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or illustration". Any embodiment of the present invention described as "for example" is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed herein. Example 1

[0015] like Figure 1 As shown, an embodiment of the present invention provides a spherical grid hoisting construction control method based on overall positioning, the method comprising:

[0016] S10: During the pre-welding of the spherical grid, welding parameter arrays of multiple welding positions are collected, welding deformation analysis is performed, and a welding deformation parameter array is obtained.

[0017] For example, during the pre-welding phase of the spherical truss, accurate prediction and control of deformation generated during the welding process are required to ensure the accuracy and safety of subsequent hoisting operations. Specifically, the construction team systematically collects welding parameter arrays for multiple key welding locations on the spherical truss. The parameters in the welding parameter arrays include, but are not limited to, welding current, voltage, welding speed, and heat input, which are directly related to the stress distribution and deformation trends during the welding process. By using welding deformation analysis technology, combined with the mechanical properties of the material and welding process parameters, the collected welding parameter arrays are deeply analyzed to accurately quantify the deformation of each location caused by welding stress. The welding deformation parameter arrays generated in this process not only reflect the deformation patterns of different welding locations under specific process conditions, but also provide a scientific basis for deformation compensation and structural adjustment during the subsequent hoisting process. For example, if the welding deformation parameters of a certain welding location indicate significant shrinkage deformation, possible installation deviations at that location can be foreseen before hoisting, and corresponding adjustment measures can be formulated in advance to ensure the accuracy and structural stability of the overall hoisting of the spherical truss.

[0018] S20: The pre-welded spherical truss is hoisted according to a preset hoisting parameter array through a hoisting equipment array. At a first moment, an overall positioning monitoring process is performed on multiple positioning positions to obtain a first deviation information array. Combined with the welding deformation parameter array, a truss deformation analysis is performed to obtain a first truss deformation parameter.

[0019] Preferably, during the hoisting operation of the spherical truss, the pre-welded spherical truss is first hoisted as a whole using an array of hoisting equipment (e.g., multiple synchronously lifting hydraulic jacks or electric hoists) according to a pre-set array of hoisting parameters, including key parameters such as hoisting speed, acceleration, hoisting point location, and hoisting sequence. During this process, although each hoisting equipment follows unified instructions, minor mechanical errors are unavoidable due to factors such as mechanical precision, equipment aging, and operational response speed. For example, under the same control instructions, the actual lifting speeds of different hoisting equipment may vary slightly. Such accumulated deviations will lead to overall or local positioning errors of the truss during the hoisting process. To accurately monitor the hoisting status, at a specific moment in the hoisting process, i.e., the first moment (e.g., 5 seconds after the start of hoisting), a high-precision positioning system (e.g., a total station equipped with laser tracking technology) is used to synchronously collect coordinates of multiple preset positioning positions on the truss. These actual positioning coordinates are then compared and analyzed with the pre-planned ideal hoisting position coordinates to calculate the actual deviation values ​​of each positioning point, which are then aggregated to form a first deviation information array. At the same time, considering the impact of residual stress and thermal deformation generated during the welding process on the grid structure, the obtained welding deformation parameter array is taken into consideration. By comprehensively analyzing the superimposed effect of welding deformation and hoisting position deviation, finite element analysis or machine learning algorithms are used to predict the deformation amplitude of the grid in the current hoisting state. The final determination of the first grid deformation parameter provides key data support for the subsequent optimization and adjustment of hoisting parameters and the safety verification of the grid structure. For example, if a certain hoisting point is hoisted too fast due to equipment errors, and this area happens to be an area with large welding deformation, the comprehensive analysis can accurately predict the grid deformation in this area, so that the hoisting strategy can be adjusted in time to ensure the safety and accuracy of the grid hoisting.

[0020] S30: Optimizing the hoisting parameters of the hoisting equipment array according to the first grid deformation parameters to obtain an optimized compensation hoisting parameter array, and continuing the hoisting and overall positioning monitoring and analysis until the hoisting of the spherical grid is completed.

[0021] Specifically, after obtaining the first grid deformation parameters, the lifting parameters of each lifting device in the lifting device array will be optimized based on this data to generate an optimized compensation lifting parameter array. Specifically, for each lifting device, its contribution to grid deformation and positioning deviation during the current lifting phase is analyzed, and the required compensation amount is calculated accordingly. For example, if the grid is 30mm lower in the area responsible for a certain lifting device due to welding deformation and lifting errors, a compensation instruction of 30mm will be automatically generated for this device. This optimization process comprehensively considers multiple influences such as welding deformation, mechanical errors, and environmental factors (such as wind load and temperature changes) to ensure the accuracy and effectiveness of the compensation measures. Subsequently, the lifting device array will be adjusted in real time according to the optimized compensation lifting parameter array, executing compensation actions one by one to gradually eliminate the identified positioning deviation and grid deformation.

[0022] After the compensation action is implemented, the overall positioning monitoring and analysis of the spherical grid continues. The spatial position information of the grid is captured in real time by high-precision measuring equipment and compared with the ideal hoisting state to verify the compensation effect and monitor the occurrence of new deviations. If the monitoring results show that there are still deviations, the optimization and compensation process is repeated, that is, the grid deformation parameters are updated according to the new monitoring data, and the hoisting parameters are optimized again until all the positioning positions of the spherical grid meet the preset accuracy requirements and the hoisting operation is successfully completed. For example, during a hoisting process, if the deviation of a key positioning point still exceeds the allowable range after the first compensation, the system will immediately start a new round of optimization calculations to generate more accurate compensation instructions for the relevant hoisting equipment until the deviation at that point is effectively corrected, ensuring the high precision and safety of the entire hoisting process.

[0023] In a preferred embodiment, during the pre-welding of the spherical grid, welding parameter arrays of multiple welding positions are collected, welding deformation analysis is performed, and a welding deformation parameter array is obtained, including: during the pre-welding of the spherical grid, welding parameter arrays of multiple welding positions are collected; based on the welding parameter array, the spherical grid welding data in the historical time is used to predict the welding deformation of the spherical grid and obtain a welding deformation parameter array.

[0024] Specifically, during the pre-welding stage of the spherical grid, in order to accurately predict and control the deformation that may occur during the welding process, the construction team will systematically collect welding parameter arrays at multiple key welding positions. These parameters include but are not limited to welding current, voltage, welding speed, heat input, and welding sequence, which together constitute the basic data for the formation of the heat-affected zone and stress distribution during the welding process. Subsequently, relying on the spherical grid welding data accumulated over a long period of time, which covers the actual deformation of the grid under different welding parameter combinations, a welding deformation predictor is constructed through data mining and pattern recognition technology. The welding deformation predictor can simulate and predict the deformation that may occur in various parts of the spherical grid under the current welding conditions based on the currently collected welding parameter array, and then generate a welding deformation parameter array. For example, if historical data shows that a certain area of ​​the grid is prone to shrinkage deformation under a specific welding current and speed combination, then when the current welding parameter array matches it, the prediction model will accurately estimate the deformation trend and magnitude of this area, providing a scientific basis for deformation compensation and structural adjustment during the subsequent lifting process.

[0025] In a preferred embodiment, according to the welding parameter array, the spherical grid welding data in the historical time is used to predict the welding deformation of the spherical grid to obtain the welding deformation parameter array, including: collecting the spherical grid welding data in the historical time, and extracting a sample welding parameter array set and a sample welding deformation parameter array set; based on machine learning, using the welding parameter array as an input feature and the welding deformation parameter array as an output feature, constructing a welding deformation predictor; using the sample welding parameter array set and the sample welding deformation parameter array set to supervise the training of the welding deformation predictor until convergence; inputting the welding parameter array into the welding deformation predictor, and predicting the output to obtain the welding deformation parameter array set.

[0026] Specifically, the process of predicting the welding deformation of a spherical truss requires systematically collecting historical welding data. This data provides a detailed record of the actual deformation of the truss under different welding conditions. Furthermore, a set of sample welding parameter arrays and corresponding sample welding deformation parameter arrays are extracted from the historical data. The former covers key parameters such as welding current, voltage, and speed, while the latter reflects the deformation of various parts of the truss under specific welding parameters. Subsequently, a welding deformation predictor is constructed based on machine learning technology, using the welding parameter array as input features and the welding deformation parameter array as output features.

[0027] Furthermore, the extracted sample welding parameter arrays and sample welding deformation parameter arrays are used to conduct supervised training on the welding deformation predictor. During the training process, the welding deformation predictor parameters are continuously adjusted to minimize the error between the predicted and actual values. Cross-validation and other methods are used to evaluate performance and prevent overfitting until convergence and the prediction accuracy meet engineering requirements. Ultimately, a welding deformation predictor that can accurately predict welding deformation is obtained. Finally, the welding parameter arrays collected during the current welding operation are input into the trained welding deformation predictor. The deformation of each part of the spherical truss under the current welding conditions is calculated and predicted, forming a welding deformation parameter array set, which provides a scientific basis for subsequent construction control and deformation compensation. For example, if historical data shows that a certain area of ​​the truss is prone to large deformation under specific welding currents and speeds, then if similar parameters are used in the current operation, the predictor will accurately estimate the deformation trend of that area, thereby guiding the construction team to take appropriate preventive measures.

[0028] In a preferred embodiment, the pre-welded spherical grid is hoisted according to a preset hoisting parameter array through a hoisting equipment array, and at a first moment, overall positioning monitoring and processing are performed on multiple positioning positions to obtain a first deviation information array, including: constructing an ideal hoisting trajectory space of the spherical grid; hoisting the pre-welded spherical grid according to a preset hoisting parameter array through a hoisting equipment array; when the accumulated hoisting time reaches the first moment, collecting positioning information of multiple positioning positions in the spherical grid to obtain a first positioning information array; obtaining the first ideal positioning array in the ideal hoisting trajectory space at the first moment; and calculating and obtaining a first deviation information array based on the first positioning information array and the first ideal positioning array.

[0029] Furthermore, during the hoisting operation of the spherical truss, an ideal hoisting trajectory space must be constructed. This space, based on engineering design requirements, defines the ideal path and positional states that the truss should follow during the hoisting process. Using an array of hoisting equipment (such as multiple synchronously operated hydraulic lifting devices), the pre-welded spherical truss is hoisted as a whole according to a preset array of hoisting parameters (including hoisting speed, acceleration, and hoisting point positions). When the hoisting operation continues until a preset first moment (e.g., 10 seconds after the start of hoisting), a high-precision positioning system (such as a laser tracker or total station) collects real-time data from multiple preset positioning positions within the spherical truss, generating a first positioning information array. This array details the actual spatial coordinates of each positioning point at that moment. Simultaneously, a first ideal positioning array corresponding to the first moment is extracted from the pre-constructed ideal hoisting trajectory space. This array represents the precise position that each positioning point should theoretically achieve at that moment. By comparing the corresponding data points in the first positioning information array with those in the first ideal positioning array, the actual deviation values ​​of each positioning point are calculated and then summarized into the first deviation information array. This array intuitively reflects the hoisting deviation of the spherical grid at the first moment, providing a key basis for subsequent hoisting parameter adjustments and deformation compensation. For example, if the actual coordinates of a positioning point deviate by 5 mm in a certain direction compared to the ideal coordinates, this deviation value will be accurately recorded in the first deviation information array, allowing the construction team to take timely corrective measures.

[0030] In a preferred embodiment, the welding deformation parameter array is combined to perform a grid deformation analysis to obtain the first grid deformation parameter, including: collecting a sample welding deformation parameter array set and a sample deviation information array set based on the historical data of the spherical grid hoisting, and collecting the deformation amplitude of the spherical grid under different sample welding deformation parameter arrays and sample deviation information arrays, and marking to obtain the sample grid deformation parameter set; constructing a grid deformation analyzer based on machine learning; using the sample welding deformation parameter array set, sample deviation information array set and sample grid deformation parameter set, the grid deformation analyzer is supervised trained until convergence; the welding deformation parameter array and the first deviation information array are input into the grid deformation analyzer, and the first grid deformation parameter is obtained as output.

[0031] Optionally, to accurately analyze truss deformation, based on historical data from spherical truss installations, a set of sample welding deformation parameter arrays and a set of sample deviation information arrays are systematically collected. The former records the deformation characteristics of the truss under different welding conditions, while the latter reflects the actual deviations of each positioning point during the installation process. At the same time, for each sample combination (i.e., a specific welding deformation parameter array and deviation information array), the deformation amplitude data of the spherical truss is collected and annotated to form a sample truss deformation parameter set, which details the degree of truss deformation under different working conditions.

[0032] Subsequently, a truss deformation analyzer was constructed based on machine learning techniques. By learning the inherent patterns in sample data, the analyzer was able to establish a complex mapping relationship between welding deformation parameters, deviation information, and truss deformation amplitude. Furthermore, the truss deformation analyzer was supervised and trained using a collection of sample welding deformation parameter arrays, sample deviation information arrays, and sample truss deformation parameter arrays. During training, the analyzer continuously adjusted its internal parameters to minimize the error between the predicted and actual deformation amplitudes until the model converged and the prediction accuracy met the engineering requirements. Finally, the welding deformation parameter array and the first deviation information array obtained from the current welding operation were input into the trained truss deformation analyzer. The model then calculated and predicted the deformation amplitude of the spherical truss under the current working conditions, i.e., the first truss deformation parameter. For example, if historical data shows that the truss is prone to large deformation under a specific welding deformation and deviation combination, the analyzer will accurately estimate the truss deformation extent if a similar working condition occurs in the current operation, providing a scientific basis for subsequent construction control and structural adjustments.

[0033] In a preferred embodiment, the lifting parameters of the lifting equipment array are optimized according to the first grid deformation parameter array to obtain an optimized compensation lifting parameter array, and the lifting and overall positioning monitoring and analysis are continued, including: using the first grid deformation parameter as the lifting parameter adjustment step; randomly setting the compensation lifting parameters of multiple lifting equipment in the lifting equipment array to obtain a first compensation lifting parameter array; calculating and obtaining a first compensation deviation array according to the first compensation lifting parameter array and the first deviation information array, and calculating and obtaining a first average compensation deviation; using the lifting parameter adjustment step to adjust and optimize the first compensation lifting parameter array until convergence, and obtaining an optimized compensation lifting parameter array with the minimum average compensation deviation; using the optimized compensation lifting parameter array to perform compensation control on the lifting equipment array, and continuing the lifting and overall positioning monitoring and analysis.

[0034] Exemplarily, after obtaining a first grid deformation parameter array, to optimize the hoisting parameters of the hoisting device array to reduce grid deformation, the first grid deformation parameter is used as the hoisting parameter adjustment step size. For example, the adjustment step size is set to 2% of the grid deformation parameter, which serves as a benchmark for subsequent parameter adjustments. Next, compensatory hoisting parameters are randomly set for multiple hoisting devices within the hoisting device array to generate a first compensatory hoisting parameter array. This array contains the parameter values ​​required to adjust each hoisting device to compensate for grid deformation, such as lift height and rotation angle. A first compensation deviation array is calculated based on the first compensation hoisting parameter array and the obtained first deviation information array. Specifically, if the compensatory hoisting parameter of a certain hoisting device is a 30mm lift, and the first deviation information at the corresponding positioning position indicates a height that is 25mm low, the calculated first compensation deviation is 5mm, indicating the deviation that still exists at that point after compensation. By summing up the first compensation deviations of all positioning positions and calculating their average, a first average compensation deviation is obtained, which is used to evaluate the overall effectiveness of the current compensation scheme.

[0035] To further optimize the compensation effect, the first compensation hoisting parameter array is iteratively adjusted using the set hoisting parameter adjustment step size. The average compensation deviation is recalculated after each adjustment until the adjustment process converges, that is, the average compensation deviation reaches the minimum value. The array obtained at this time is the optimized compensation hoisting parameter array. Finally, the optimized compensation hoisting parameter array is used to accurately compensate and control the hoisting equipment array, and the hoisting operation is continued. At the same time, overall positioning monitoring and analysis are performed to ensure that the deformation of the grid hoisting process is effectively controlled until the hoisting task is successfully completed. For example, if the average compensation deviation of a certain hoisting area is still large after the initial compensation, the compensation parameters are adjusted iteratively multiple times to gradually reduce the deviation until satisfactory hoisting accuracy is achieved.

[0036] In a preferred embodiment, a first compensation deviation array is calculated based on the first compensation hoisting parameter array and the first deviation information array, and a first average compensation deviation is calculated, including: obtaining the error amplitude of the compensation control of the hoisting equipment array according to the first compensation hoisting parameter array to obtain a compensation control error amplitude array; calculating a first basic compensation deviation array based on the first compensation hoisting parameter array and the first deviation information array; using the compensation control error amplitude array, performing error adjustment calculation on the first basic compensation deviation array to obtain a first compensation deviation array, and calculating the mean to obtain a first average compensation deviation.

[0037] Specifically, in order to accurately evaluate the compensation control effect of the hoisting equipment array, it is necessary to obtain the error amplitude generated when the hoisting equipment array performs compensation control according to the first compensation hoisting parameter array to form a compensation control error amplitude array. The compensation control error amplitude array reflects the degree of deviation between the actual compensation amount and the set compensation amount caused by factors such as mechanical accuracy and control response delay when each hoisting equipment performs the compensation action. Subsequently, based on the first compensation hoisting parameter array (such as the height to be lifted by each hoisting equipment) and the first deviation information array (such as the current height deviation of each positioning position), the first basic compensation deviation array is calculated. The first basic compensation deviation array represents the theoretical compensation effect that each positioning position should achieve through the compensation hoisting parameters without considering the compensation control error.

[0038] Furthermore, the compensation control error amplitude array is used to perform error adjustment calculations on the first basic compensation deviation array. Specifically, if a certain lifting equipment is controlled according to a 30mm lifting instruction, but there is a 5% error margin, its actual compensation effect will deviate from the theoretical value. For example, if the first basic compensation deviation at a certain point is 5mm, then after considering the 5% error margin, the first compensation deviation is calculated as 5mm multiplied by (1+5%), that is, 5.25mm. By traversing all positioning positions, the error adjustment calculation of the entire first basic compensation deviation array is completed to obtain the first compensation deviation array. Finally, the mean of all deviation values ​​in the first compensation deviation array is calculated to obtain the first average compensation deviation. This value serves as a quantitative indicator for evaluating the overall effect of the current compensation control scheme and is used to guide subsequent optimization and adjustment of lifting parameters. For example, if the first average compensation deviation is large, it indicates that the current compensation control scheme still needs to be improved. It may be necessary to reduce the deviation and improve the lifting accuracy by adjusting the lifting parameters, optimizing the control algorithm, etc.

[0039] The embodiment of the present invention provides a spherical grid hoisting construction control method based on overall positioning, which has at least the following technical effects:

[0040] 1. By collecting historical welding data and using machine learning technology to build a welding deformation predictor, the deformation of the spherical truss during the welding process can be accurately predicted, and then a welding deformation parameter array can be obtained. This allows the potential deformation of the truss to be predicted before lifting and compensated through subsequent lifting parameter optimization, effectively reducing the deformation risk during the lifting process and improving lifting accuracy.

[0041] 2. During the hoisting process, by constructing an ideal hoisting trajectory space and performing overall positioning monitoring and processing on multiple positioning positions at specific times, the deviation information array between the actual position information of the grid and the ideal position can be obtained in real time. Combined with the welding deformation parameter array, the grid deformation analysis is further performed to obtain the first grid deformation parameter, realizing real-time monitoring and deviation analysis of the hoisting process, and providing accurate data support for subsequent hoisting parameter optimization.

[0042] 3. Based on the deformation parameters of the first truss, the lifting parameters of the lifting equipment array are dynamically optimized to obtain the optimized compensation lifting parameter array, and the lifting and overall positioning monitoring and analysis are continued. During this process, by continuously adjusting the lifting parameters to reduce the compensation deviation, closed-loop control of the lifting process is achieved. This not only improves the adaptability and robustness of the lifting process, but also ensures that the spherical truss can be accurately lifted into place according to the predetermined trajectory, significantly improving the overall efficiency and quality of the lifting construction. Example 2

[0043] like Figure 2 As shown, based on the same inventive concept as the spherical grid hoisting construction control method based on overall positioning provided in the first embodiment, the embodiment of the present invention further provides a spherical grid hoisting construction control system based on overall positioning, the system comprising:

[0044] The parameter acquisition module 11 is used to acquire welding parameter arrays of multiple welding positions during the pre-welding of the spherical grid, perform welding deformation analysis, and obtain a welding deformation parameter array.

[0045] The positioning monitoring module 12 is used to hoist the pre-welded spherical grid through a hoisting equipment array according to a preset hoisting parameter array. At the first moment, the module performs overall positioning monitoring processing on multiple positioning positions to obtain a first deviation information array. Combined with the welding deformation parameter array, the module performs grid deformation analysis to obtain the first grid deformation parameter.

[0046] The parameter optimization module 13 is used to optimize the hoisting parameters of the hoisting equipment array according to the first grid deformation parameters, obtain an optimized compensation hoisting parameter array, and continue hoisting and overall positioning monitoring and analysis until the spherical grid is hoisted.

[0047] Furthermore, the parameter acquisition module 11 is further configured to perform the following steps:

[0048] During the pre-welding of the spherical grid, welding parameter arrays of multiple welding positions are collected; based on the welding parameter arrays, the welding deformation of the spherical grid is predicted using the spherical grid welding data in historical time to obtain the welding deformation parameter array.

[0049] Furthermore, the parameter acquisition module 11 is further configured to perform the following steps:

[0050] Spherical grid welding data within a historical period is collected, and a sample welding parameter array set and a sample welding deformation parameter array set are extracted; based on machine learning, a welding deformation predictor is constructed with the welding parameter array as an input feature and the welding deformation parameter array as an output feature; the sample welding parameter array set and the sample welding deformation parameter array set are used to perform supervised training on the welding deformation predictor until convergence; the welding parameter array is input into the welding deformation predictor, and the welding deformation parameter array set is obtained as a prediction output.

[0051] Furthermore, the positioning monitoring module 12 is further configured to perform the following steps:

[0052] Construct an ideal hoisting trajectory space for the spherical truss; hoist the pre-welded spherical truss according to a preset hoisting parameter array using a hoisting equipment array; when the accumulated hoisting time reaches a first moment, collect positioning information of multiple positioning positions in the spherical truss to obtain a first positioning information array; obtain a first ideal positioning array in the ideal hoisting trajectory space at the first moment; and calculate a first deviation information array based on the first positioning information array and the first ideal positioning array.

[0053] Furthermore, the positioning monitoring module 12 is further configured to perform the following steps:

[0054] Based on the historical data of spherical grid hoisting, a sample welding deformation parameter array set and a sample deviation information array set are collected, and the deformation amplitude of the spherical grid under different sample welding deformation parameter arrays and sample deviation information arrays are collected, and the sample grid deformation parameter set is obtained by annotation; based on machine learning, a grid deformation analyzer is constructed; the sample welding deformation parameter array set, the sample deviation information array set and the sample grid deformation parameter set are used to supervise the grid deformation analyzer until convergence; the welding deformation parameter array and the first deviation information array are input into the grid deformation analyzer, and the first grid deformation parameter is obtained as output.

[0055] Furthermore, the parameter optimization module 13 is further configured to perform the following steps:

[0056] The first truss deformation parameter is used as the lifting parameter adjustment step; the compensation lifting parameters of multiple lifting devices in the lifting device array are randomly set to obtain a first compensation lifting parameter array; based on the first compensation lifting parameter array and the first deviation information array, a first compensation deviation array is calculated and a first average compensation deviation is calculated; the first compensation lifting parameter array is adjusted and optimized using the lifting parameter adjustment step until convergence, and an optimized compensation lifting parameter array with the minimum average compensation deviation is obtained; the optimized compensation lifting parameter array is used to perform compensation control on the lifting equipment array, and the lifting and overall positioning monitoring and analysis are continued.

[0057] Furthermore, the parameter optimization module 13 is further configured to perform the following steps:

[0058] Obtain the error amplitude of the compensation control of the hoisting equipment array according to the first compensation hoisting parameter array to obtain a compensation control error amplitude array; calculate and obtain a first basic compensation deviation array based on the first compensation hoisting parameter array and the first deviation information array; use the compensation control error amplitude array to perform error adjustment calculation on the first basic compensation deviation array to obtain a first compensation deviation array, and calculate the mean to obtain a first average compensation deviation.

[0059] Through the above detailed description of a spherical grid hoisting construction control method based on overall positioning in this specification, those skilled in the art can clearly understand a spherical grid hoisting construction control system based on overall positioning in this embodiment. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0060] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A spherical grid hoisting construction control method based on overall positioning, characterized in that: The method comprises: In the pre-welding of the spherical grid, welding parameter arrays of multiple welding positions are collected, welding deformation analysis is performed, and a welding deformation parameter array is obtained; The pre-welded spherical grid is hoisted by a hoisting equipment array according to a preset hoisting parameter array. At a first moment, an overall positioning monitoring process is performed on multiple positioning positions to obtain a first deviation information array. Combined with the welding deformation parameter array, the grid deformation analysis is performed to obtain a first grid deformation parameter. Optimizing the hoisting parameters of the hoisting equipment array according to the first grid deformation parameters to obtain an optimized compensation hoisting parameter array, and continuing hoisting and overall positioning monitoring and analysis, including: Using the first grid deformation parameter as the lifting parameter adjustment step; Randomly setting compensation hoisting parameters for a plurality of hoisting devices in the hoisting device array to obtain a first compensation hoisting parameter array; Calculating a first compensation deviation array and a first average compensation deviation based on the first compensation hoisting parameter array and the first deviation information array; Using the hoisting parameter adjustment step size, the first compensation hoisting parameter array is adjusted and optimized until convergence, thereby obtaining an optimized compensation hoisting parameter array with the minimum average compensation deviation; The optimized compensation hoisting parameter array is used to perform compensation control on the hoisting equipment array, and hoisting and overall positioning monitoring and analysis are continued until the hoisting of the spherical grid is completed.

2. The spherical grid hoisting construction control method based on overall positioning according to claim 1 is characterized in that: During the pre-welding of the spherical grid, the welding parameter arrays of multiple welding positions are collected to perform welding deformation analysis and obtain the welding deformation parameter array, including: In the pre-welding of the spherical grid, the welding parameter arrays of multiple welding positions are collected; According to the welding parameter array, the welding deformation of the spherical grid is predicted by using the welding data of the spherical grid in the historical time, and the welding deformation parameter array is obtained.

3. The spherical grid hoisting construction control method based on overall positioning according to claim 2 is characterized in that: According to the welding parameter array, the welding deformation of the spherical grid is predicted using the historical spherical grid welding data to obtain the welding deformation parameter array, including: Collecting spherical grid welding data in historical time, and extracting sample welding parameter array sets and sample welding deformation parameter array sets; Based on machine learning, a welding deformation predictor is constructed with welding parameter array as input feature and welding deformation parameter array as output feature; Using the sample welding parameter array set and the sample welding deformation parameter array set, the welding deformation predictor is supervised trained until convergence; The welding parameter array is input into the welding deformation predictor, and a welding deformation parameter array set is obtained as a prediction output.

4. The spherical grid hoisting construction control method based on overall positioning according to claim 1 is characterized in that: The pre-welded spherical grid is hoisted by a hoisting equipment array according to a preset hoisting parameter array. At a first moment, an overall positioning monitoring process is performed on multiple positioning positions to obtain a first deviation information array, including: Constructing an ideal hoisting trajectory space for the spherical grid; The pre-welded spherical grid is hoisted by means of a hoisting equipment array according to a preset hoisting parameter array; When the accumulated hoisting time reaches a first moment, the positioning information of multiple positioning positions in the spherical grid is collected to obtain a first positioning information array; Acquire a first ideal positioning array in the ideal hoisting trajectory space at the first moment; A first deviation information array is obtained by calculation based on the first positioning information array and the first ideal positioning array.

5. The spherical grid hoisting construction control method based on overall positioning according to claim 1 is characterized in that: Combined with the welding deformation parameter array, a grid deformation analysis is performed to obtain the first grid deformation parameter, including: According to the historical data of the spherical grid hoisting, a sample welding deformation parameter array set and a sample deviation information array set are collected, and the deformation amplitude of the spherical grid under different sample welding deformation parameter arrays and sample deviation information arrays are collected, and the sample grid deformation parameter set is obtained by annotation; Build a grid deformation analyzer based on machine learning; Using the sample welding deformation parameter array set, the sample deviation information array set, and the sample grid deformation parameter set, supervised training is performed on the grid deformation analyzer until convergence; The welding deformation parameter array and the first deviation information array are input into the grid deformation analyzer, and the first grid deformation parameter is obtained as an output.

6. The spherical grid hoisting construction control method based on overall positioning according to claim 1 is characterized in that: Calculating a first compensation deviation array and a first average compensation deviation according to the first compensation hoisting parameter array and the first deviation information array includes: Obtaining an error amplitude of compensation control performed on the hoisting equipment array according to the first compensation hoisting parameter array to obtain a compensation control error amplitude array; Calculating and obtaining a first basic compensation deviation array according to the first compensation hoisting parameter array and the first deviation information array; The compensation control error amplitude array is used to perform error adjustment calculation on the first basic compensation deviation array to obtain a first compensation deviation array, and the mean is calculated to obtain a first average compensation deviation.

7. A spherical grid hoisting construction control system based on overall positioning, characterized in that: A system for implementing a spherical grid hoisting construction control method based on overall positioning according to any one of claims 1 to 6, comprising: The parameter acquisition module is used to collect welding parameter arrays of multiple welding positions during the pre-welding of the spherical grid, perform welding deformation analysis, and obtain welding deformation parameter arrays; a positioning monitoring module for hoisting the pre-welded spherical truss using a hoisting equipment array according to a preset hoisting parameter array, performing overall positioning monitoring processing on multiple positioning positions at a first moment, obtaining a first deviation information array, and performing truss deformation analysis in combination with the welding deformation parameter array to obtain first truss deformation parameters; A parameter optimization module is used to optimize the hoisting parameters of the hoisting equipment array according to the first grid deformation parameters, obtain an optimized compensation hoisting parameter array, and continue hoisting and overall positioning monitoring and analysis until the spherical grid is hoisted.

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