Collaborative decision-making method and system for bridge pile foundation cluster construction

Abstract

The invention discloses a collaborative decision-making method and system for bridge pile foundation cluster construction, and relates to the technical field of bridges, and the technical scheme is characterized by comprising the following steps: constructing a collaborative decision-making database according to the relevance of an equipment collaborative scheduling rule, a risk response strategy and a construction progress of historical reference construction data; acquiring real-time construction state data of a bridge pile foundation cluster, operation parameters of construction equipment and dynamic risk factors of a construction area at the current construction stage; analyzing the real-time construction state data of the bridge pile foundation cluster to obtain progress deviation values and equipment load rates of construction of all pile foundations, comparing the progress deviation values and the equipment load rates with a collaborative decision database in combination with operation parameters of construction equipment and dynamic risk factors of a construction area, and judging whether the current construction collaborative state is in a reasonable interval or not; if the current construction coordination state is in the unreasonable interval, calculating an equipment coordination deviation coefficient and a risk response gap value; the management efficiency and the management and control capability are improved.

Description

Technical Field

[0001] This invention relates to the field of bridge technology, and more specifically, to a collaborative decision-making method and system for bridge pile foundation cluster construction. Background Technology

[0002] Equipment scheduling for bridge pile foundation construction relies on the experience of management personnel for cross-work allocation, lacking the summarization and reuse of historical efficient scheduling patterns. This leads to frequent equipment idleness or overload, thus affecting construction efficiency. Monitoring and handling of dynamic risk factors such as groundwater level changes and pipeline settlement are mostly reactive, lacking standardized risk response strategies based on historical success cases. This makes it difficult to predict and quickly address risks in advance, easily leading to quality and safety accidents and project delays. Control over the construction progress of each pile foundation is rather rough, making it difficult to calculate progress deviations and supplement resources accordingly, resulting in resource waste or insufficient supply. Furthermore, these aspects are fragmented, with a lack of coordination between equipment scheduling, risk control, and progress management, leading to poor construction synergy and making it difficult to guarantee overall construction efficiency, quality, and safety. Summary of the Invention

[0003] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a collaborative decision-making method and system for bridge pile foundation cluster construction.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A collaborative decision-making method for bridge pile foundation cluster construction, comprising the following steps:

[0006] A collaborative decision-making database is constructed by examining the correlation between equipment scheduling patterns, risk response strategies, and construction progress based on historical reference construction data.

[0007] To obtain real-time construction status data of bridge pile foundation clusters, operating parameters of construction equipment, and dynamic risk factors of the construction area during the current construction phase;

[0008] The real-time construction status data of the bridge pile foundation cluster is analyzed to obtain the progress deviation value and equipment load rate of each pile foundation construction. The operating parameters of the construction equipment, the dynamic risk factors of the construction area, and the collaborative decision database are compared to determine whether the current construction collaboration status is within a reasonable range.

[0009] If the current construction coordination status is in an unreasonable range, then calculate the equipment coordination deviation coefficient and the risk response gap value;

[0010] Based on the equipment coordination deviation coefficient and the risk response gap value, the priority of coordination adjustment is determined. The scheduling path of construction equipment, the resource replenishment plan for each pile foundation construction and the risk prevention and control measures are optimized and adjusted to generate multiple sets of coordination decision adjustment plans. The optimal coordination decision plan is output through equipment operation stability, construction progress recovery rate and risk control effect.

[0011] Preferably, a collaborative decision-making database is constructed by integrating the correlation between equipment collaborative scheduling patterns, risk response strategies, and construction progress from historical reference construction data. This specifically includes the following steps:

[0012] Bridge pile foundation cluster construction data with the same geological conditions as the current construction stage were selected from historical reference construction data;

[0013] Preset equipment failure rate thresholds and risk response time standards, and select reference construction data from bridge pile foundation cluster construction data that have equipment failure rates lower than the preset equipment failure rate thresholds and risk response times that meet the risk response time standards;

[0014] Extract equipment collaborative scheduling rules from reference construction data; wherein, the equipment collaborative scheduling rules include the cross-workstation scheduling frequency of construction equipment, the allocation of operation time, and the rules for allocating emergency backup equipment in case of failure;

[0015] Risk response strategies for risk events are extracted from reference construction data; wherein, the risk response strategies include handling procedures, resource allocation priorities, and schedule compensation measures;

[0016] Extract the construction progress achievement rate from the reference construction data;

[0017] After establishing the correspondence between equipment collaborative scheduling rules, risk response strategies and construction progress achievement rates, a collaborative decision-making database is constructed.

[0018] Preferably, the real-time construction status data includes real-time drilling speed, concrete pouring volume, and rebar cage installation progress;

[0019] The operating parameters of the construction equipment include operating power, fault records, and maintenance cycle;

[0020] The dynamic risk factors in the construction area include changes in groundwater level and settlement of surrounding pipelines.

[0021] Preferably, the real-time construction status data of the bridge pile foundation cluster is analyzed to obtain the progress deviation value and equipment load rate of each pile foundation construction, specifically including the following steps:

[0022] The construction progress data of each pile foundation in the bridge pile foundation cluster is collected in real time through IoT monitoring devices.

[0023] The progress data is compared with the preset construction plan data to obtain the progress deviation value of each pile foundation construction;

[0024] Real-time load data of construction equipment is obtained through equipment sensors, and the equipment load rate is obtained by combining the equipment's rated load parameters.

[0025] Preferably, the real-time load data of the construction equipment is obtained through equipment sensors, and the equipment load rate is obtained by combining the equipment's rated load parameters. Specifically, this includes the following steps:

[0026] The power output amplitude and frequency of the equipment during operation are collected in real time through the equipment's sensors.

[0027] The power output amplitude load ratio is obtained by taking the ratio of the difference between the real-time collected power output amplitude and the rated output amplitude.

[0028] The power output frequency load ratio is obtained by taking the ratio of the difference between the real-time collected power output frequency and the rated output frequency.

[0029] The power output amplitude load ratio and power output frequency load ratio are preset according to the equipment operation type;

[0030] The equipment load rate is obtained based on the power output amplitude load ratio, power output frequency load ratio, power output amplitude load ratio, and power output frequency load ratio.

[0031] Preferably, if the current construction coordination status is in an unreasonable range, the equipment coordination deviation coefficient and risk response gap value are calculated, specifically including the following steps:

[0032] If the current construction coordination status is in an unreasonable range, the equipment coordination deviation coefficient between the current equipment scheduling scheme and the baseline equipment coordination scheduling rule is calculated based on the equipment scheduling response speed deviation, cross-workstation collaboration efficiency deviation, and the timeliness of standby equipment activation.

[0033] The risk response gap between the current risk prevention and control measures and the baseline risk response strategy is calculated based on the scope of the risk impact, the amount of resources required for risk disposal, and the existing resource reserves.

[0034] Preferably, the priority of collaborative adjustment is determined based on the equipment coordination deviation coefficient and the risk response gap value. Multiple sets of collaborative decision-making adjustment schemes are generated by optimizing and adjusting the scheduling paths of construction equipment, resource replenishment plans for each pile foundation construction, and risk prevention and control measures. Specifically, this includes the following steps:

[0035] The priority of collaborative adjustments is determined based on the equipment coordination deviation coefficient and the risk response gap value.

[0036] If the priority of the equipment coordination deviation coefficient is higher than the risk response gap value, then the scheduling path of the construction equipment is optimized according to the equipment coordination scheduling rules of the coordination decision database and the current construction station distribution, and the equipment operation time allocation scheme is adjusted. Then, the corresponding resources are supplemented according to the progress deviation value of each pile foundation construction in the bridge pile foundation cluster, and the first set of coordination decision adjustment schemes is generated.

[0037] If the risk response gap value has a higher priority than the equipment coordination deviation coefficient, the risk response strategy of the coordination decision database will be prioritized. After the prevention and control measures are formulated for the risk factors, the response resource gap will be supplemented. A second set of coordination decision adjustment plans will be generated after avoiding the overlap between the equipment operation area and the risk impact area.

[0038] If the equipment coordination deviation coefficient is equal to the risk response gap value, then the equipment scheduling and risk prevention and control measures are optimized simultaneously, and a third set of collaborative decision adjustment schemes is generated in combination with the schedule deviation repair requirements.

[0039] Preferably, the optimal collaborative decision-making solution is output based on equipment operational stability, construction progress recovery rate, and risk management effectiveness, specifically including the following steps:

[0040] The equipment operation stability, construction progress recovery rate, and risk control effectiveness of the first, second, and third collaborative decision-making adjustment schemes were quantitatively evaluated to obtain evaluation values.

[0041] Select the optimal collaborative decision-making scheme based on the evaluation value.

[0042] A collaborative decision-making system for bridge pile foundation cluster construction includes:

[0043] Building module: Constructs a collaborative decision-making database by integrating the correlation between equipment collaborative scheduling patterns, risk response strategies, and construction progress based on historical reference construction data;

[0044] Acquisition module: Acquires real-time construction status data of bridge pile foundation clusters, operating parameters of construction equipment, and dynamic risk factors of the construction area during the current construction phase;

[0045] Judgment Module: Analyzes the real-time construction status data of the bridge pile foundation cluster to obtain the progress deviation value and equipment load rate of each pile foundation construction. Combines the operating parameters of the construction equipment, the dynamic risk factors of the construction area, and the collaborative decision database to determine whether the current construction collaboration status is within a reasonable range.

[0046] Calculation module: If the current construction coordination status is in an unreasonable range, calculate the equipment coordination deviation coefficient and the risk response gap value;

[0047] Output module: Based on the equipment coordination deviation coefficient and risk response gap value, determine the priority of coordination adjustment, optimize and adjust the scheduling path of construction equipment, resource replenishment plan for each pile foundation construction and risk prevention and control measures to generate multiple sets of coordination decision adjustment plans, and output the optimal coordination decision plan through equipment operation stability, construction progress recovery rate and risk control effect.

[0048] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the aforementioned collaborative decision-making method for bridge pile foundation cluster construction.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] This invention constructs a collaborative decision-making database by correlating historical equipment scheduling patterns, risk response strategies, and construction progress. This database provides a scientific basis for real-time decision-making, significantly improving the accuracy and reliability of decisions. The method achieves efficient collaboration in equipment scheduling and resource allocation. By analyzing real-time construction status data, it grasps the progress deviations of each pile foundation and the equipment load. Combined with the collaborative decision-making database, it optimizes equipment scheduling paths and work duration allocation, avoiding equipment idleness and resource waste, improving resource utilization efficiency. It also enables real-time monitoring of dynamic risk factors in the construction area, and, combined with the risk response strategies in the collaborative decision-making database, identifies and addresses risks in advance, reducing the probability and impact of risks, preventing equipment overload, and minimizing equipment failures. This ensures the stability of pile foundation construction quality and improves the overall quality level of the project. It achieves real-time perception and data-driven management of construction status, equipment operation, and risk factors, significantly improving management efficiency and control capabilities. Attached Figure Description

[0051] Figure 1 This is a schematic diagram illustrating the steps of a collaborative decision-making method for bridge pile foundation cluster construction proposed in this invention;

[0052] Figure 2 This invention presents a schematic diagram of a collaborative decision-making system for bridge pile foundation cluster construction.

[0053] Figure 3 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention.

[0054] 610. Processor; 620. Communication interface; 630. Memory; 640. Communication bus. Detailed Implementation

[0055] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0056] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0057] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0058] Reference Figures 1-3 As shown.

[0059] The embodiments further illustrate the collaborative decision-making method and system for bridge pile foundation cluster construction proposed in this invention.

[0060] A collaborative decision-making method for bridge pile foundation cluster construction, comprising the following steps:

[0061] A collaborative decision-making database is constructed by examining the correlation between equipment scheduling patterns, risk response strategies, and construction progress based on historical reference construction data.

[0062] To obtain real-time construction status data of bridge pile foundation clusters, operating parameters of construction equipment, and dynamic risk factors of the construction area during the current construction phase;

[0063] The real-time construction status data of the bridge pile foundation cluster is analyzed to obtain the progress deviation value and equipment load rate of each pile foundation construction. The operating parameters of the construction equipment, the dynamic risk factors of the construction area, and the collaborative decision database are compared to determine whether the current construction collaboration status is within a reasonable range.

[0064] The calculated construction progress deviations for each pile foundation, equipment load rates, operating parameters of construction equipment, and dynamic risk factors in the construction area are combined. This comprehensive data is then compared with a collaborative decision-making database. It is assumed that in historical data within the collaborative decision-making database, with the same geological conditions and equipment type as the current construction site, the reasonable range for progress deviations is -5% to 5%, the reasonable range for equipment load rates is 30% to 70%, the operating parameters of the construction equipment have no frequent failure records and the maintenance cycle is normal, and the dynamic risk factors in the construction area are within safe thresholds. If the progress deviation for a certain pile foundation is 10%, the equipment load rate is 20%, and the groundwater level in the construction area rises above the safe threshold, then by comparing with the baseline data in the database, the current construction coordination status is determined to be within an unreasonable range.

[0065] If the current construction coordination status is within a reasonable range, it indicates that the equipment scheduling, progress, and risk control of the bridge pile foundation cluster construction are in a relatively balanced state. At this time, real-time construction status data, construction equipment operating parameters, and dynamic risk factors in the construction area will be continuously monitored to ensure that all indicators remain stable within a reasonable range. Simultaneously, the construction process will be managed routinely based on the benchmark patterns in the collaborative decision-making database. For example, equipment operation will be scheduled according to the established equipment operation time allocation plan, concrete and rebar cage materials required for pile foundation construction will be replenished according to the preset resource supply rhythm, and risk assessment of the construction area will be conducted according to the routine risk inspection system.

[0066] If the current construction coordination status is in an unreasonable range, then calculate the equipment coordination deviation coefficient and the risk response gap value;

[0067] Based on the equipment coordination deviation coefficient and the risk response gap value, the priority of coordination adjustment is determined. The scheduling path of construction equipment, the resource replenishment plan for each pile foundation construction and the risk prevention and control measures are optimized and adjusted to generate multiple sets of coordination decision adjustment plans. The optimal coordination decision plan is output through equipment operation stability, construction progress recovery rate and risk control effect.

[0068] A collaborative decision-making database is constructed by establishing the correlation between equipment scheduling patterns, risk response strategies, and construction progress based on historical reference construction data. This includes the following steps:

[0069] Bridge pile foundation cluster construction data with the same geological conditions as the current construction stage were selected from historical reference construction data;

[0070] Preset equipment failure rate thresholds and risk response time standards, and select reference construction data from bridge pile foundation cluster construction data that have equipment failure rates lower than the preset equipment failure rate thresholds and risk response times that meet the risk response time standards;

[0071] Extract equipment coordination scheduling patterns from reference construction data; these patterns include cross-workstation scheduling frequency of construction equipment, allocation of work duration, and rules for allocating emergency backup equipment in case of failure.

[0072] Risk response strategies for risk events are extracted from reference construction data; these strategies include handling procedures, resource allocation priorities, and schedule compensation measures.

[0073] Extract the construction progress achievement rate from the reference construction data;

[0074] After establishing the correspondence between equipment collaborative scheduling rules, risk response strategies and construction progress achievement rates, a collaborative decision-making database is constructed.

[0075] We select bridge pile foundation cluster construction data from a large amount of historical reference construction data that have exactly the same geological conditions as the current construction stage. For example, if the current construction area is in sandy clay soil, we select bridge pile foundation construction case data in sandy clay soil from historical data to ensure the geological compatibility of the data.

[0076] It is necessary to pre-set equipment failure rate thresholds and risk response time standards. Construction data with equipment failure rates below the preset thresholds and risk response times meeting the time standards should be selected from the pre-screened construction data in the same geological conditions. For example, assuming a preset equipment failure rate threshold of 3% and a risk response time standard of 1.5 hours, reference construction data with equipment failure rates below 3% and response times within 1.5 hours after a risk event should be selected from the construction data in sandy clay soil conditions.

[0077] First, we collected a large amount of historical fault data of equipment operation in the construction of similar bridge pile foundations, statistically analyzed the fault rate distribution of different equipment under different working conditions, and determined the equipment fault rate threshold that can both ensure the safe and stable operation of equipment and take into account construction efficiency by referring to the industry standards for construction equipment management.

[0078] This study identifies common risk types in bridge pile foundation construction, assesses the consequences of each type of risk, and uses historical data on successful risk management to determine risk response timelines that effectively control risk escalation while minimizing impact on construction progress, taking into account current construction technology and resource allocation capabilities.

[0079] Extract the collaborative scheduling patterns of equipment from reference construction data. For example, a rotary drilling rig in sandy clay construction may have a cross-workstation scheduling frequency of twice a day, with the working time allocated as 6 hours of drilling and 1 hour of equipment maintenance. If the equipment fails, the backup equipment can be dispatched within 40 minutes. These are the collaborative scheduling patterns of the equipment.

[0080] The risk response strategy encompasses the handling process for risk events, resource allocation priorities, and schedule compensation measures. For example, when a pipeline settlement risk occurs in the construction area, the handling process is to first stop the surrounding pile foundation work, and then start the pipeline reinforcement equipment; the resource allocation priority is to prioritize ensuring the material supply for the reinforcement equipment; and the schedule compensation measures are to make up for time losses by optimizing other pile foundation construction procedures.

[0081] The construction progress achievement rate is the ratio of the actual construction progress to the planned progress. If a project plans to complete the pile foundation construction in 25 days and actually completes it in 23 days, the progress achievement rate is 23 / 25×100%=92%.

[0082] Establish information correlations and construct a collaborative decision-making database. Establish a correspondence between extracted equipment collaborative scheduling patterns, risk response strategies, and construction progress achievement rates. For example, establish a correlation record between the frequency of rotary drilling rig cross-workstation scheduling twice a day, the principle of stopping work before reinforcement when pipelines settle, and the progress achievement rate of 92%. After constructing a large number of such correlation records, a structured collaborative decision-making database is formed. In subsequent construction, whenever similar geological conditions, equipment scheduling, or risk scenarios are encountered, the corresponding progress achievement rate reference can be quickly retrieved from the database, providing a scientific basis for real-time collaborative decision-making.

[0083] Real-time construction status data includes real-time drilling speed, concrete pouring volume, and rebar cage installation progress.

[0084] The operating parameters of construction equipment include operating power, fault records, and maintenance cycles;

[0085] Dynamic risk factors in the construction area include changes in groundwater level and settlement of surrounding pipelines.

[0086] Real-time construction status data reflects the dynamic progress of pile foundation construction, specifically including real-time drilling speed, concrete pouring volume, and rebar cage installation progress. Taking a certain pile foundation construction as an example, the drilling speed of the drilling rig is monitored in real time through IoT sensors. If the designed pile length is 50 meters and the planned daily drilling is 10 meters, but the actual real-time drilling speed is 8 meters / day, then the progress deviation can be detected in time. The concrete pouring volume is collected through intelligent metering equipment. For example, if the designed pouring volume for a certain pile foundation is 200 cubic meters, but the actual pouring is 180 cubic meters, the time node can be combined to determine whether there is a pouring delay. The rebar cage installation progress is monitored through data such as installation time and number of sections. If the plan is to complete the installation of one rebar cage section in 4 hours, but it actually takes 5 hours, this can also reflect the progress difference.

[0087] Operating parameters of construction equipment are used to assess the equipment's health status and operational efficiency, covering operating power, fault records, and maintenance cycles. Taking a rotary drilling rig as an example, its operating power is collected through the equipment's built-in sensors. If the rated power is 200kW, but the actual operating power consistently exceeds 220kW, it indicates that the equipment is overloaded, and the risk of failure should be noted. Fault records should detail the types of past equipment failures, the time of occurrence, and the handling measures. If a drilling rig experiences three hydraulic system failures within six months, this system should be closely monitored in subsequent construction. Maintenance cycles are determined based on the equipment manual, industry maintenance standards, and actual usage. For example, the maintenance cycle for the drill rod is typically a comprehensive overhaul every 2000 meters of drilling, and maintenance plans should be arranged in advance based on the current drilling mileage.

[0088] The dynamic risk factors in the construction area focus on environmental changes that affect construction safety and quality, mainly including groundwater level changes and settlement of surrounding pipelines. Groundwater levels in the construction area are monitored in real time using water level monitoring instruments. If the designed anti-buoyancy water level is 10 meters underground, and the actual water level rises to 8 meters underground, the risk of water inrush during pile foundation construction increases. Settlement of surrounding pipelines is collected by displacement sensors at settlement monitoring points. If the settlement of a natural gas pipeline exceeds 5 mm / day, pile foundation construction in the surrounding area must be immediately suspended and protective measures implemented. Real-time monitoring of this dynamic risk data allows construction management to identify risks promptly and take preventative or simultaneous control measures, avoiding disruption of collaborative construction due to uncontrolled risks.

[0089] The real-time construction status data of the bridge pile foundation cluster is analyzed to obtain the progress deviation value and equipment load rate of each pile foundation construction. The specific steps include:

[0090] The construction progress data of each pile foundation in the bridge pile foundation cluster is collected in real time through IoT monitoring devices.

[0091] The progress data is compared with the preset construction plan data to obtain the progress deviation value of each pile foundation construction;

[0092] Real-time load data of construction equipment is obtained through equipment sensors, and the equipment load rate is obtained by combining the equipment's rated load parameters.

[0093] The construction progress data of each pile foundation in the bridge pile foundation cluster is collected in real time through IoT monitoring devices. For example, in the construction of a certain bridge pile foundation cluster, the IoT sensor equipped for each pile foundation will continuously monitor the real-time drilling speed, concrete pouring volume, and steel cage installation progress data. This data will be uploaded to the data management platform in real time via wireless transmission technology, realizing dynamic perception of the construction progress of each pile foundation.

[0094] The collected progress data is compared with the preset construction plan data. Taking one of the pile foundations as an example, the construction plan requires that 200 cubic meters of concrete be poured on the 5th day, while the actual pouring volume collected by the IoT monitoring device is 180 cubic meters. The progress deviation is calculated as (planned volume - actual volume) / planned volume × 100%, that is, (200-180) / 200 × 100% = 10%. This calculation can clearly show the degree of deviation between the construction progress of the pile foundation and the plan.

[0095] Real-time load data of construction equipment is obtained through equipment sensors. Taking a rotary drilling rig as an example, the equipment sensors collect the power output amplitude and frequency during operation. Assuming the rated power output amplitude of the rig is 100 units and the real-time collected power output amplitude is 80 units, the power output amplitude load ratio is (100-80) / 100×100%=20%. If the rated power output frequency is 50 times / minute and the real-time collected power output frequency is 40 times / minute, the power output frequency load ratio is (50-40) / 50×100%=20%. Based on the preset weighting of the power output amplitude load ratio as 0.6 and the power output frequency load ratio as 0.4 according to the operation type of the rotary drilling rig, the equipment load rate is 20%×0.6+20%×0.4=20%. This calculation can accurately grasp the operating load status of the equipment and avoid overload or idleness.

[0096] This technical solution uses IoT monitoring devices and sensors to collect real-time data on pile foundation construction progress and equipment load. Then, by comparing the data with the planned data and rated parameters, the progress deviation and equipment load rate of each pile foundation are calculated. This provides key quantitative indicators for judging whether the construction coordination status is reasonable and is an important data foundation for realizing collaborative decision-making in bridge pile foundation cluster construction.

[0097] The real-time load data of the construction equipment is obtained through the equipment's sensors, and the equipment load rate is calculated by combining the equipment's rated load parameters. This process includes the following steps:

[0098] The power output amplitude and frequency of the equipment during operation are collected in real time through the equipment's sensors.

[0099] The power output amplitude load ratio is obtained by taking the ratio of the difference between the real-time collected power output amplitude and the rated output amplitude.

[0100] The power output frequency load ratio is obtained by taking the ratio of the difference between the real-time collected power output frequency and the rated output frequency.

[0101] The power output amplitude load ratio and power output frequency load ratio are preset according to the equipment operation type;

[0102] The equipment load rate is obtained based on the power output amplitude load ratio, power output frequency load ratio, power output amplitude load ratio, and power output frequency load ratio.

[0103] Assuming a rotary drilling rig has a rated power output amplitude of 100 units and a real-time acquired power output amplitude of 80 units, the power output amplitude load ratio is calculated as (rated output amplitude - real-time output amplitude) / rated output amplitude × 100%, which is (100 - 80) / 100 × 100% = 20%. Further assuming the rig's rated power output frequency is 50 times / minute and the real-time acquired power output frequency is 40 times / minute, the power output frequency load ratio is (50 - 40) / 50 × 100% = 20%.

[0104] The weights of the power output amplitude load ratio and the power output frequency load ratio are preset according to the equipment's operating type. For equipment such as rotary drilling rigs, where power output amplitude is the main operating indicator, the preset weight of the power output amplitude load ratio is 0.6, and the weight of the power output frequency load ratio is 0.4.

[0105] The equipment load rate is calculated by the power output amplitude load ratio, the power output frequency load ratio, and their corresponding weights. Taking the rotary drilling rig mentioned above as an example, the equipment load rate is 20% × 0.6 + 20% × 0.4 = 20%. This allows for accurate monitoring of the equipment's operating load status, preventing equipment failure due to overload or resource idleness due to underload, and providing crucial information for the coordinated scheduling of subsequent construction equipment.

[0106] If the current construction coordination status is in an unreasonable range, calculate the equipment coordination deviation coefficient and the risk response gap value, specifically including the following steps:

[0107] If the current construction coordination status is in an unreasonable range, the equipment coordination deviation coefficient between the current equipment scheduling scheme and the baseline equipment coordination scheduling rule is calculated based on the equipment scheduling response speed deviation, cross-workstation collaboration efficiency deviation, and the timeliness of standby equipment activation.

[0108] The risk response gap between the current risk prevention and control measures and the baseline risk response strategy is calculated based on the scope of the risk impact, the amount of resources required for risk disposal, and the existing resource reserves.

[0109] When the construction coordination status is in an unreasonable range, it is necessary to quantify it from three dimensions: equipment scheduling response speed deviation, cross-workstation collaboration efficiency deviation, and the timeliness of backup equipment activation. Taking the construction of a bridge pile foundation cluster as an example, assuming that the response time for the drilling rig to be scheduled from workstation A to workstation B should be 30 minutes according to the benchmark equipment coordination scheduling rule, and the actual scheduling took 45 minutes, then the scheduling response speed deviation is (45-30) / 30×100%=50%; in the benchmark, the connection waiting time between two pieces of equipment during cross-workstation collaboration should be ≤10 minutes, and the actual waiting time was 20 minutes, so the cross-workstation collaboration efficiency deviation is (20-10) / 10×100%=100%; in the benchmark, backup equipment should be activated within 2 hours after the failure, and the actual timeliness deviation of backup equipment activation is 3 hours, so the timeliness deviation of backup equipment activation is (180-120) / 120×100%=50%. Weights are preset for these three dimensions based on equipment type and construction scenario. For example, the weight for scheduling response speed deviation is 0.4, the weight for cross-workstation collaboration efficiency deviation is 0.3, and the weight for standby equipment activation timeliness deviation is 0.3. Then the equipment collaboration deviation coefficient is 50%×0.4+100%×0.3+50%×0.3=65%. This coefficient reflects the degree of deviation between the current equipment scheduling scheme and the baseline equipment collaboration scheduling pattern.

[0110] The risk response gap is calculated by combining the scope of the risk impact, the amount of resources required for risk mitigation, and existing resource reserves. For example, if a groundwater level rise risk occurs in the construction area, and the baseline risk response strategy specifies an impact area of ​​500 square meters, but the actual impact area reaches 800 square meters, the deviation in the impact area is (800-500) / 500×100%=60%. The baseline mitigation of this risk requires 5 dewatering devices, but the existing reserves only have 3, resulting in a resource gap of 2 devices. The deviation in the amount of resources required for risk mitigation is 2 / 5×100%=40%. If the weight of the risk impact area deviation is 0.6 and the weight of the resource deviation is 0.4, and these weights are determined through historical data, then the risk response gap is 60%×0.6+40%×0.4=52%. This value quantifies the gap between the current risk prevention and control measures and the baseline risk response strategy.

[0111] Based on the equipment coordination deviation coefficient and risk response gap value, the priority of coordination adjustment is determined. The scheduling path of construction equipment, the resource replenishment plan for each pile foundation construction, and the risk prevention and control measures are optimized and adjusted to generate multiple sets of coordination decision adjustment plans. The specific steps include:

[0112] The priority of collaborative adjustments is determined based on the equipment coordination deviation coefficient and the risk response gap value.

[0113] If the priority of the equipment coordination deviation coefficient is higher than the risk response gap value, then the scheduling path of the construction equipment is optimized according to the equipment coordination scheduling rules of the coordination decision database and the current construction station distribution, and the equipment operation time allocation scheme is adjusted. Then, the corresponding resources are supplemented according to the progress deviation value of each pile foundation construction in the bridge pile foundation cluster, and the first set of coordination decision adjustment schemes is generated.

[0114] If the risk response gap value has a higher priority than the equipment coordination deviation coefficient, the risk response strategy of the coordination decision database will be prioritized. After the prevention and control measures are formulated for the risk factors, the response resource gap will be supplemented. A second set of coordination decision adjustment plans will be generated after avoiding the overlap between the equipment operation area and the risk impact area.

[0115] If the equipment coordination deviation coefficient is equal to the risk response gap value, then the equipment scheduling and risk prevention and control measures are optimized simultaneously, and a third set of collaborative decision adjustment schemes is generated in combination with the schedule deviation repair requirements.

[0116] The priority of coordination adjustments is determined by comparing the equipment coordination deviation coefficient and the risk response gap value. For example, in the construction of a bridge pile foundation, if the equipment coordination deviation coefficient is 65% and the risk response gap value is 52%, then the equipment coordination deviation coefficient has a higher priority than the risk response gap value. If the equipment coordination deviation coefficient is 50% and the risk response gap value is 60%, then the risk response gap value has a higher priority. If both are 55%, then they have the same priority.

[0117] The first set of collaborative decision adjustment schemes is generated when the equipment coordination deviation coefficient has a higher priority. Taking a case with an equipment coordination deviation coefficient of 65% as an example, the scheduling rules of equipment coordination under sandy clay soil in the collaborative decision database are referenced, and the scheduling path of construction equipment is optimized in combination with the current distribution of construction positions. For example, if the drilling rig originally had to take a detour from position A to position B, a straight path is now planned to shorten the scheduling time. At the same time, the equipment operation time allocation scheme is adjusted. If the original operation time of a drilling rig was 8 hours of drilling and 2 hours of maintenance, it is now adjusted to 9 hours of drilling and 1 hour of maintenance based on the progress deviation. Corresponding resources are supplemented according to the progress deviation value of each pile foundation construction. For example, if the progress deviation value of a certain pile foundation is 10% and 10 cubic meters of concrete is lacking, then 10 cubic meters of concrete are supplemented, and finally the first set of collaborative decision adjustment schemes is generated.

[0118] If the risk response gap value has a higher priority, a second set of collaborative decision-making adjustment plans is generated. Taking a case with a risk response gap value of 60% as an example, the risk response strategies for rising groundwater levels in the collaborative decision-making database are referenced first, and prevention and control measures are formulated for this risk factor, such as adding two dewatering devices. Then, the resource gap is addressed by allocating corresponding power and spare parts to support the operation of the dewatering devices. At the same time, overlap between the equipment operation area and the risk-affected area is avoided. For example, drilling rigs that were originally operating in the risk-affected area are adjusted to a safe area, thus generating a second set of collaborative decision-making adjustment plans.

[0119] When the equipment coordination deviation coefficient equals the risk response gap value, a third set of collaborative decision-making adjustment schemes is generated. This involves simultaneously optimizing equipment scheduling and risk control measures. On one hand, the drilling rig's scheduling path and operation time are optimized; on the other hand, reinforcement measures are developed to address risk factors such as settlement of surrounding pipelines. Simultaneously, considering the need to correct progress deviations, such as an 8% progress deviation for a certain pile foundation, progress is compensated for by increasing worker shifts while optimizing equipment and controlling risks, ultimately generating the third set of collaborative decision-making adjustment schemes.

[0120] The optimal collaborative decision-making solution is derived by considering equipment operational stability, construction progress recovery rate, and risk management effectiveness. This process includes the following steps:

[0121] The equipment operation stability, construction progress recovery rate, and risk control effectiveness of the first, second, and third collaborative decision-making adjustment schemes were quantitatively evaluated to obtain evaluation values.

[0122] Select the optimal collaborative decision-making scheme based on the evaluation value.

[0123] Taking three sets of plans for the construction of a bridge pile foundation as an example, the stability of equipment operation is evaluated by statistically analyzing the number of equipment failures and the repair time after the implementation of each plan. Assume that after the implementation of the first collaborative decision-making adjustment plan, the equipment failure rate decreased from 5% to 3%; after the implementation of the second collaborative decision-making adjustment plan, the equipment failure rate decreased from 5% to 4%; and after the implementation of the third collaborative decision-making adjustment plan, the equipment failure rate decreased from 5% to 3.5%. The degree of recovery of the construction progress is calculated to determine the extent of the progress deviation. If the original progress deviation of a certain pile foundation is 10%, after the implementation of the first collaborative decision-making adjustment plan... The deviation value became 3%, and the progress recovery rate was (10-3) / 10×100%=70%. After the implementation of the second group of collaborative decision-making adjustment plans, the deviation value became 4%, and the progress recovery rate was 60%. After the implementation of the third group of collaborative decision-making adjustment plans, the deviation value became 3.5%, and the progress recovery rate was 65%. The risk control effect was assessed by the degree of reduction in the probability of risk occurrence. For example, the original probability of groundwater level rise risk was 20%. After the implementation of the first group of collaborative decision-making adjustment plans, it was reduced to 10%. After the implementation of the second group of collaborative decision-making adjustment plans, it was reduced to 5%. After the implementation of the third group of collaborative decision-making adjustment plans, it was reduced to 8%. Weights were preset for these three evaluation dimensions, such as equipment operation stability (0.3), construction progress recovery rate (0.4), and risk management effectiveness (0.3). The evaluation values ​​for the three sets of schemes were calculated as follows: Set 1: 3%×0.3 + 70%×0.4 + 10%×0.3 = 32.9%; Set 2: 4%×0.3 + 60%×0.4 + 5%×0.3 = 27.7%; Set 3: 3.5%×0.3 + 65%×0.4 + 8%×0.3 = 31.25%. The weights for equipment operation stability, construction progress recovery rate, and risk management effectiveness were obtained by analyzing historical data.

[0124] The optimal collaborative decision-making scheme is selected based on the evaluation values. Comparing the evaluation values ​​of the three schemes, the first group has the highest evaluation value, indicating that it has the best overall performance in terms of equipment operation stability, construction progress recovery rate, and risk control effectiveness. Therefore, the first group is selected as the optimal collaborative decision-making scheme.

[0125] In summary, this technical solution quantifies and calculates the evaluation values ​​of three sets of collaborative decision-making adjustment schemes from three dimensions: equipment operation stability, construction progress recovery rate, and risk control effectiveness. Finally, the optimal scheme is selected based on the evaluation value, ensuring the scientificity and effectiveness of collaborative decision-making in bridge pile foundation cluster construction and achieving the optimal balance between construction efficiency, equipment stability, and risk control.

[0126] A collaborative decision-making system for bridge pile foundation cluster construction includes:

[0127] Building module: Constructs a collaborative decision-making database by integrating the correlation between equipment collaborative scheduling patterns, risk response strategies, and construction progress based on historical reference construction data;

[0128] Acquisition module: Acquires real-time construction status data of bridge pile foundation clusters, operating parameters of construction equipment, and dynamic risk factors of the construction area during the current construction phase;

[0129] Judgment Module: Analyzes the real-time construction status data of the bridge pile foundation cluster to obtain the progress deviation value and equipment load rate of each pile foundation construction. Combines the operating parameters of the construction equipment, the dynamic risk factors of the construction area, and the collaborative decision database to determine whether the current construction collaboration status is within a reasonable range.

[0130] Calculation module: If the current construction coordination status is in an unreasonable range, calculate the equipment coordination deviation coefficient and the risk response gap value;

[0131] Output module: Based on the equipment coordination deviation coefficient and risk response gap value, determine the priority of coordination adjustment, optimize and adjust the scheduling path of construction equipment, resource replenishment plan for each pile foundation construction and risk prevention and control measures to generate multiple sets of coordination decision adjustment plans, and output the optimal coordination decision plan through equipment operation stability, construction progress recovery rate and risk control effect.

[0132] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a collaborative decision-making method for bridge pile foundation cluster construction.

[0133] like Figure 3 As shown, the electronic device may include a processor 610, a communication interface 620, a memory 630, and a communication bus 640, wherein the processor 610, the communication interface 620, and the memory 630 communicate with each other through the communication bus 640. The processor 610 can call logical instructions in the memory 630 to execute a collaborative decision-making method for bridge pile foundation cluster construction.

[0134] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0135] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute a collaborative decision-making method for bridge pile foundation cluster construction.

[0136] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform a collaborative decision-making method for bridge pile foundation cluster construction.

[0137] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0138] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0139] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A collaborative decision-making method for bridge pile foundation cluster construction, characterized in that, The method includes the following steps: A collaborative decision-making database is constructed by examining the correlation between equipment scheduling patterns, risk response strategies, and construction progress based on historical reference construction data. To obtain real-time construction status data of bridge pile foundation clusters, operating parameters of construction equipment, and dynamic risk factors of the construction area during the current construction phase; The real-time construction status data of the bridge pile foundation cluster is analyzed to obtain the progress deviation value and equipment load rate of each pile foundation construction. The operating parameters of the construction equipment, the dynamic risk factors of the construction area, and the collaborative decision database are compared to determine whether the current construction collaboration status is within a reasonable range. If the current construction coordination status is in an unreasonable range, then calculate the equipment coordination deviation coefficient and the risk response gap value; Based on the equipment coordination deviation coefficient and the risk response gap value, the priority of coordination adjustment is determined. The scheduling path of construction equipment, the resource replenishment plan for each pile foundation construction and the risk prevention and control measures are optimized and adjusted to generate multiple sets of coordination decision adjustment plans. The optimal coordination decision plan is output through equipment operation stability, construction progress recovery rate and risk control effect.

2. The collaborative decision-making method for bridge pile foundation cluster construction according to claim 1, characterized in that, A collaborative decision-making database is constructed by establishing the correlation between equipment scheduling patterns, risk response strategies, and construction progress based on historical reference construction data. This includes the following steps: Bridge pile foundation cluster construction data with the same geological conditions as the current construction stage were selected from historical reference construction data; Preset equipment failure rate thresholds and risk response time standards, and select reference construction data from bridge pile foundation cluster construction data that have equipment failure rates lower than the preset equipment failure rate thresholds and risk response times that meet the risk response time standards; Extract equipment collaborative scheduling rules from reference construction data; wherein, the equipment collaborative scheduling rules include the cross-workstation scheduling frequency of construction equipment, the allocation of operation time, and the rules for allocating emergency backup equipment in case of failure; Risk response strategies for risk events are extracted from reference construction data; wherein, the risk response strategies include handling procedures, resource allocation priorities, and schedule compensation measures; Extract the construction progress achievement rate from the reference construction data; After establishing the correspondence between equipment collaborative scheduling rules, risk response strategies and construction progress achievement rates, a collaborative decision-making database is constructed.

3. The collaborative decision-making method for bridge pile foundation cluster construction according to claim 1, characterized in that, The real-time construction status data includes real-time drilling speed, concrete pouring volume, and steel cage installation progress. The operating parameters of the construction equipment include operating power, fault records, and maintenance cycle; The dynamic risk factors in the construction area include changes in groundwater level and settlement of surrounding pipelines.

4. The collaborative decision-making method for bridge pile foundation cluster construction according to claim 3, characterized in that, The real-time construction status data of the bridge pile foundation cluster is analyzed to obtain the progress deviation value and equipment load rate of each pile foundation construction. The specific steps include: The construction progress data of each pile foundation in the bridge pile foundation cluster is collected in real time through IoT monitoring devices. The progress data is compared with the preset construction plan data to obtain the progress deviation value of each pile foundation construction; Real-time load data of construction equipment is obtained through equipment sensors, and the equipment load rate is obtained by combining the equipment's rated load parameters.

5. The collaborative decision-making method for bridge pile foundation cluster construction according to claim 4, characterized in that, The real-time load data of the construction equipment is obtained through the equipment's sensors, and the equipment load rate is calculated by combining the equipment's rated load parameters. This process includes the following steps: The power output amplitude and frequency of the equipment during operation are collected in real time through the equipment's sensors. The power output amplitude load ratio is obtained by taking the ratio of the difference between the real-time collected power output amplitude and the rated output amplitude. The power output frequency load ratio is obtained by taking the ratio of the difference between the real-time collected power output frequency and the rated output frequency. The power output amplitude load ratio and power output frequency load ratio are preset according to the equipment operation type; The equipment load rate is obtained based on the power output amplitude load ratio, power output frequency load ratio, power output amplitude load ratio, and power output frequency load ratio.

6. The collaborative decision-making method for bridge pile foundation cluster construction according to claim 4, characterized in that, If the current construction coordination status is in an unreasonable range, calculate the equipment coordination deviation coefficient and the risk response gap value, specifically including the following steps: If the current construction coordination status is in an unreasonable range, the equipment coordination deviation coefficient between the current equipment scheduling scheme and the baseline equipment coordination scheduling rule is calculated based on the equipment scheduling response speed deviation, cross-workstation collaboration efficiency deviation, and the timeliness of standby equipment activation. The risk response gap between the current risk prevention and control measures and the baseline risk response strategy is calculated based on the scope of the risk impact, the amount of resources required for risk disposal, and the existing resource reserves.

7. The collaborative decision-making method for bridge pile foundation cluster construction according to claim 6, characterized in that, Based on the equipment coordination deviation coefficient and risk response gap value, the priority of coordination adjustment is determined. The scheduling path of construction equipment, the resource replenishment plan for each pile foundation construction, and the risk prevention and control measures are optimized and adjusted to generate multiple sets of coordination decision adjustment plans. The specific steps include: The priority of collaborative adjustments is determined based on the equipment coordination deviation coefficient and the risk response gap value. If the priority of the equipment coordination deviation coefficient is higher than the risk response gap value, then the scheduling path of the construction equipment is optimized according to the equipment coordination scheduling rules of the coordination decision database and the current construction station distribution, and the equipment operation time allocation scheme is adjusted. Then, the corresponding resources are supplemented according to the progress deviation value of each pile foundation construction in the bridge pile foundation cluster, and the first set of coordination decision adjustment schemes is generated. If the risk response gap value has a higher priority than the equipment coordination deviation coefficient, the risk response strategy of the coordination decision database will be prioritized. After the prevention and control measures are formulated for the risk factors, the response resource gap will be supplemented. A second set of coordination decision adjustment plans will be generated after avoiding the overlap between the equipment operation area and the risk impact area. If the equipment coordination deviation coefficient is equal to the risk response gap value, then the equipment scheduling and risk prevention and control measures are optimized simultaneously, and a third set of collaborative decision adjustment schemes is generated in combination with the schedule deviation repair requirements.

8. The collaborative decision-making method for bridge pile foundation cluster construction according to claim 7, characterized in that, The optimal collaborative decision-making solution is derived by considering equipment operational stability, construction progress recovery rate, and risk management effectiveness. This process includes the following steps: The equipment operation stability, construction progress recovery rate, and risk control effectiveness of the first, second, and third collaborative decision-making adjustment schemes were quantitatively evaluated to obtain evaluation values. Select the optimal collaborative decision-making scheme based on the evaluation value.

9. A collaborative decision-making system for bridge pile foundation cluster construction, applied to the collaborative decision-making method for bridge pile foundation cluster construction as described in any one of claims 1 to 8, characterized in that, include: Building module: Constructs a collaborative decision-making database by integrating the correlation between equipment collaborative scheduling patterns, risk response strategies, and construction progress based on historical reference construction data; Acquisition module: Acquires real-time construction status data of bridge pile foundation clusters, operating parameters of construction equipment, and dynamic risk factors of the construction area during the current construction phase; Judgment Module: Analyzes the real-time construction status data of the bridge pile foundation cluster to obtain the progress deviation value and equipment load rate of each pile foundation construction. Combines the operating parameters of the construction equipment, the dynamic risk factors of the construction area, and the collaborative decision database to determine whether the current construction collaboration status is within a reasonable range. Calculation module: If the current construction coordination status is in an unreasonable range, calculate the equipment coordination deviation coefficient and the risk response gap value; Output module: Based on the equipment coordination deviation coefficient and risk response gap value, determine the priority of coordination adjustment, optimize and adjust the scheduling path of construction equipment, resource replenishment plan for each pile foundation construction and risk prevention and control measures to generate multiple sets of coordination decision adjustment plans, and output the optimal coordination decision plan through equipment operation stability, construction progress recovery rate and risk control effect.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the collaborative decision-making method for bridge pile foundation cluster construction as described in any one of claims 1 to 8.

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