A risk intelligent monitoring method for the structural safety of outfitting wharves

Abstract

This invention discloses an intelligent risk monitoring method for the safety of outfitting wharf structures, specifically relating to the field of wharf structure risk monitoring and assessment. It addresses the problem that existing outfitting operations rely on static load verification and experience-based judgment, which are insufficient to reflect the time-varying characteristics of structural loads and the collaborative effects between structural units under conditions of multiple vessels berthing side-by-side and multiple parallel processes. This method analyzes the outfitting operation plan, constructs an operation load plan table and a time-varying load spectrum for the wharf area, and, combined with the wharf structure topology and load transfer mechanism, calculates the cumulative damage degree and cascading collaborative failure risk of structural units. The method then spatially expresses the risk results in a geographic information system, thereby implementing constraint adjustments and corrections to the original operation plan. This achieves dynamic monitoring and risk prevention of outfitting operations, improves the operational safety and operational organization rationality of outfitting wharf structures, and has good engineering application prospects.

Description

Technical Field

[0001] This invention relates to the field of terminal risk monitoring and assessment technology, and more specifically, to an intelligent risk monitoring method for the structural safety of outfitting terminals. Background Technology

[0002] With the expansion of large-scale shipbuilding and repair, the weight of large outfitting objects is constantly increasing, the lifting radius is continuously expanding, and the tension of mooring lines is changing frequently. This causes the wharf structure to bear significantly varying and highly superimposed operational loads in a short period of time. At the same time, the wharf structure is usually composed of multiple interconnected structural units. Local overload or long-term damage to a single structural unit may affect adjacent units through structural connections, thereby causing regional safety hazards.

[0003] However, in current engineering practice, outfitting operation safety management largely relies on empirical rules or static load verification, which fails to reflect the actual load changes over time during the operation and cannot characterize the load transfer and synergistic effects between multiple structural units. While some methods focus on structural inspection or single-point fatigue assessment, they are usually detached from the specific outfitting operation scenario and fail to systematically link the operation plan, hoisting conditions, and structural safety status. This results in delayed risk identification, reliance on manual judgment for operation adjustments, and difficulty in effectively constraining high-risk operations in a timely manner.

[0004] Therefore, there is a need for a risk intelligent monitoring method for actual outfitting wharf operations. This method should be able to comprehensively consider the lifting objects, operation sequence, and interactions between structural units during the execution of the operation plan, dynamically assess and visualize the structural safety risks of the wharf, and provide a reliable basis for the safety control of outfitting operations. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a risk intelligent monitoring method for the safety of outfitting wharf structures to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A risk intelligent monitoring method for the structural safety of outfitting wharves includes the following steps:

[0008] S1. Analyze the outfitting operation plan and generate dynamic risk assessment tasks for each ship and associated terminal structural unit based on the mapping relationship between ship berths and terminal structural units.

[0009] S2. Based on the list of work items in the risk assessment task, match the corresponding lifting object weight, lifting range and mooring cable standard configuration data from the preset standard operation process library, and combine the rated load data of the wharf structural unit to simulate and generate a load plan table for the operation period.

[0010] S3. Overlay the load schedules of all adjacent wharf structural units according to the operation time axis to construct the time-varying load spectrum of the entire wharf area. At the same time, construct the wharf structural topology network and calculate the load transfer matrix between adjacent wharf structural units.

[0011] S4. Based on the time-varying load spectrum, the rainflow counting method is applied to calculate the cumulative damage index of each wharf structural unit throughout the entire planning period;

[0012] S5. Based on the load transfer matrix, the load of adjacent wharf structural units is corrected along the structural topology path, and the risk value of cascaded collaborative failure between structural units is calculated based on the corrected load.

[0013] S6. Based on the cumulative damage index and the collaborative failure risk value, generate a hierarchical operation risk heat map in the terminal geographic information system, identify the structural risk level under different outfitting operations, and adjust the constraints of the outfitting operation plan by tracing back according to the structural risk level.

[0014] As a further aspect of the present invention, in step S1, generating the dynamic risk assessment task specifically includes:

[0015] Read the dock's outfitting operation plan, identify and extract the berth number corresponding to each outfitting vessel and the sequence of outfitting operation items represented by the operation code, and establish a mapping relationship between berth numbers and dock structural unit identifiers based on the preset dock zoning digital drawings.

[0016] Traverse the sequence of work items and create a dynamic risk assessment task record for each affected wharf structural unit in combination with the planned work time window. The record should include at least the associated vessel identifier, wharf structural unit identifier, work time window, and work item code list.

[0017] As a further aspect of the present invention, in step S2, simulating and generating a load schedule for the work period specifically includes:

[0018] Based on the load-bearing attributes of the wharf structural units corresponding to the dynamic risk assessment task, including vertical and lateral rated load data;

[0019] Within the operation time window, extract the static benchmark operation load that directly acts on the dock structural unit from the weight of the hoisting object.

[0020] Based on the crane's working load curve, the rated lifting capacity under the current working conditions is queried using the lifting operation radius. The ratio of the weight of the object being lifted to the rated lifting capacity is used as the dynamic load coefficient to make an equivalent correction to the static reference working load.

[0021] Based on the spatial angle between the mooring lines and the ship at the dock mooring bollards, the standard tension configuration of each line is decomposed into lateral load components on the dock structural units.

[0022] The equivalent corrected static baseline operating load and each lateral load component are superimposed according to the time series to calculate the total load generated on the wharf structural unit, and a time-series load curve with time as the horizontal axis and load value as the vertical axis is generated as the load plan table of the wharf structural unit.

[0023] As a further aspect of the present invention, in step S3, constructing the time-varying load spectrum of the entire wharf area, simultaneously constructing the wharf structural topology network, and calculating the load transfer matrix between adjacent wharf structural units specifically includes:

[0024] Load the time-series load curves corresponding to the load plans of all wharf structural units, establish a two-dimensional matrix with the operation time points as rows and the wharf structural units as columns, fill the load values ​​corresponding to the structural units at each time point into the corresponding positions of the matrix, and form the time-varying load spectrum of the wharf area.

[0025] Extract the physical connections and support relationships between each structural unit, construct the wharf structure topology network with units as nodes and connections as edges, and assign a load transfer coefficient to each pair of adjacent units according to the connection direction of the edges in the topology network and the mechanical properties of the connecting components. All load transfer coefficients form the load transfer matrix between adjacent units.

[0026] As a further aspect of the present invention, in step S4, calculating the cumulative damage index of each wharf structural unit throughout the entire planning period using the rainflow counting method based on the time-varying load spectrum specifically includes:

[0027] The complete load time series of each wharf structural unit is extracted from the corresponding time-varying load spectrum, and the complete load time series is equivalently mapped to the stress response time series. All complete stress cycles in the series are counted by the rainflow counting algorithm, and the amplitude of each stress cycle is recorded.

[0028] Based on the preset standard stress fatigue curve of the wharf structure material, the allowable number of cycles is matched for each identified stress cycle amplitude, and the reciprocal of the allowable number of cycles is calculated as the damage degree of each stress cycle.

[0029] The cumulative damage index of each wharf structural unit is obtained by summing up the damage of all stress cycles during the planning period.

[0030] As a further aspect of the present invention, in S5, the load of adjacent wharf structural units is corrected along the structural topology path based on the load transfer matrix, and the risk value of cascaded collaborative failure between structural units is calculated based on the corrected load, specifically including:

[0031] Traverse and extract the maximum load value of each wharf structural unit in the time-varying load spectrum, compare the maximum load value with the rated load data of the wharf structural unit, and record the excess load part that exceeds the rated load data;

[0032] In the wharf structure topology network, based on the transmission coefficient between the wharf structure unit and each adjacent unit in the load transmission matrix, the excess load is proportionally distributed as additional load to each adjacent unit.

[0033] For each wharf structural unit, the number of times its total load exceeds the rated capacity after each adjacent unit receives additional load is counted. The number of times all adjacent units exceed the limit is accumulated, and the accumulated value is used as the cascade collaborative failure risk value of that unit.

[0034] As a further aspect of the present invention, in step S6, generating a layered operational risk heat map in the dock geographic information system to identify the structural risk level under different outfitting operations specifically includes:

[0035] The cumulative damage index of each wharf structural unit is weighted and fused with the cascaded collaborative failure risk value to obtain the comprehensive risk value of each structural unit and convert it into the corresponding structural risk level.

[0036] Based on the spatial coordinates and geometric shape data of each wharf structural unit stored in the wharf geographic information system, a spatial layer with structural units as basic graphic elements is generated. According to the structural risk level assigned to each structural unit, the corresponding color filling rules are called to color and render the geometry of each unit, generating a risk heat map of the outfitting wharf with color representing the risk level.

[0037] As a further aspect of the present invention, S6, specifically including the constraint adjustment of the outfitting operation plan based on the structural risk level, includes:

[0038] Locate all wharf structural units with identified risk levels in the operational risk heat map, query the corresponding outfitting operation plan based on the dynamic risk assessment task record, and adjust the tasks of the operation plan based on the cumulative damage index and cascade collaborative failure risk value.

[0039] The technical effects and advantages of the intelligent risk monitoring method for outfitting wharf structure safety of the present invention are as follows:

[0040] This invention achieves a dynamic mapping between work load and structural safety status by finely linking outfitting operation plans with the load-bearing characteristics of wharf structural units. Compared with traditional management methods based on static verification or experience-based judgment, it can truly reflect the comprehensive impact of load changes over time and the superposition of multiple processes on the wharf structure during outfitting operations.

[0041] By constructing a time-varying load spectrum and structural topology network, and introducing a joint assessment mechanism of cumulative damage degree and cascading collaborative failure risk, this approach can not only identify the long-term fatigue risk of individual structural units but also reveal the regional risk diffusion characteristics caused by load transfer between adjacent structural units. This avoids the amplification of overall risk due to inaccurate local safety assessments. Furthermore, by spatially representing the risk results in a geographic information system and adjusting and correcting the outfitting operation plan based on the assessment results, the risk assessment results can directly serve the operation execution control, improving the foresight and pertinence of outfitting operation safety management, reducing the hidden dangers of structural overload and fatigue failure, and demonstrating good engineering applicability and promotional value. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of a risk intelligent monitoring method for the structural safety of outfitting docks according to the present invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0044] Example 1

[0045] Figure 1 This invention provides an intelligent risk monitoring method for the structural safety of outfitting wharves, comprising the following steps:

[0046] S1. Analyze the outfitting operation plan and generate dynamic risk assessment tasks for each ship and associated terminal structural unit based on the mapping relationship between ship berths and terminal structural units.

[0047] S2. Based on the list of work items in the risk assessment task, match the corresponding lifting object weight, lifting range and mooring cable standard configuration data from the preset standard operation process library, and combine the rated load data of the wharf structural unit to simulate and generate a load plan table for the operation period.

[0048] S3. Overlay the load schedules of all adjacent wharf structural units according to the operation time axis to construct the time-varying load spectrum of the entire wharf area. At the same time, construct the wharf structural topology network and calculate the load transfer matrix between adjacent wharf structural units.

[0049] S4. Based on the time-varying load spectrum, the rainflow counting method is applied to calculate the cumulative damage index of each wharf structural unit throughout the entire planning period;

[0050] S5. Based on the load transfer matrix, the load of adjacent wharf structural units is corrected along the structural topology path, and the risk value of cascaded collaborative failure between structural units is calculated based on the corrected load.

[0051] S6. Based on the cumulative damage index and the collaborative failure risk value, generate a hierarchical operation risk heat map in the terminal geographic information system, identify the structural risk level under different outfitting operations, and adjust the constraints of the outfitting operation plan by tracing back according to the structural risk level.

[0052] In step S1, a dynamic risk assessment task is generated.

[0053] The system retrieves information on all vessels participating in the outfitting operation during the current period from the established outfitting operation plan document of the wharf. This operation plan uses outfitting vessels as the basic organizational unit, clearly recording the berth number of each vessel and the corresponding outfitting operation content. During implementation, the operation plan is analyzed vessel by vessel. For each vessel, its berth number is extracted, and simultaneously, the sequence of outfitting operation items represented by operation codes is extracted. These operation codes identify specific outfitting operation types, such as codes for large equipment hoisting, code for segmented component installation, code for deck accessory installation, and code for mooring adjustment operations. This method transforms the complex outfitting operation content into a structured sequence of operation items. Subsequently, based on a pre-established digital map of the wharf's zoning, the berth numbers are spatially located and analyzed. The digital map has structurally divided the entire wharf area, and each wharf structural unit is assigned a unique structural unit identifier. By finding the spatial range corresponding to the berth number in the digital drawings, the set of wharf structural units covered or directly associated with the berth is determined, and a correspondence or one-to-many mapping relationship between the berth number and the wharf structural unit identifier is established accordingly.

[0054] After establishing the mapping relationship between berth numbers and wharf structural unit identifiers, for each outfitting vessel, the extracted sequence of work items is iterated item by item according to the order given in the work plan. During the iteration, the wharf structural units that may be affected by each work item are identified by combining the planned work time window corresponding to each work item in the work plan. The time window is used to specify the specific time range of the start and end of the work item. For each identified affected wharf structural unit, an independent dynamic risk assessment task record is created and associated with the specific vessel identifier and wharf structural unit identifier. Each dynamic risk assessment task record contains at least the following information: the corresponding vessel identifier, used to distinguish the operational impact brought by different outfitting vessels; the wharf structural unit identifier, used to identify the specific structural object of the risk assessment; the work time window, used to limit the time range of the risk assessment; and a list of work item codes, used to fully describe the types of outfitting operations that may affect the structural unit within the time window. If multiple work items operate on the same wharf structural unit within the same time window, the corresponding work item codes will be uniformly incorporated into the task record of that structural unit, thereby forming a dynamic risk assessment task that can truly reflect the concurrent state of multiple operations.

[0055] In step S2, a load schedule for the work period is generated by simulation.

[0056] For wharf structural units clearly associated in the dynamic risk assessment task, the load-bearing attribute data calibrated during the design or operation and maintenance phase of these structural units is retrieved. This load-bearing attribute data includes at least the vertical rated load-bearing capacity and the lateral rated load-bearing capacity, used to define the range of operational loads that the structural unit can withstand under normal operating conditions. Based on this, and combined with the operational time windows recorded in the dynamic risk assessment task, the operational status of the hoisting object within that time window is analyzed to determine whether the hoisting object is in a suspended, moving, or temporarily stationary state during the corresponding period. During implementation, according to the actual execution method of the outfitting operation, the load-bearing path through which the weight of the hoisting object is transferred to the wharf structure via the crane support system is identified. Then, the weight share directly acting on the target wharf structural unit during the current operational period is extracted from the total weight of the hoisting object and used as the static baseline operational load corresponding to that structural unit. This load is not equivalent to the total weight of the object being lifted, but rather reflects the equivalent static load level actually felt by the structural unit at a specific berth location, under specific support conditions, and during a specific operating period. It transforms the abstract weight of the object being lifted into a load input that directly corresponds to the specific wharf structural unit, avoiding the evaluation bias caused by substituting the overall weight for the local force.

[0057] After obtaining the static baseline operating load corresponding to the wharf structural unit, the influence of crane operating conditions on the operating load level is further introduced. During implementation, based on the lifting operation radius specified in the outfitting operation plan, the rated lifting capacity corresponding to that radius is retrieved from the existing working load curve of the crane. This rated lifting capacity reflects the maximum lifting capacity that the crane can safely undertake under the current operating conditions. Subsequently, the ratio of the known weight of the object to be lifted to the retrieved rated lifting capacity is calculated to obtain a dynamic load coefficient reflecting the utilization level of the current lifting operation. This dynamic load coefficient is used to characterize the degree to which the lifting operation approaches the upper limit of the crane's capacity, rather than changing the physical weight of the object being lifted. In implementation, this dynamic load coefficient is used to equivalently correct the aforementioned static baseline operating load, so that the corrected load level can reflect the equivalent amplification of the operating load caused by increased structural flexibility, operational sensitivity, and additional effects under high operating conditions.

[0058] During outfitting operations, in addition to the vertical load generated by hoisting operations, the ship's mooring status also exerts significant lateral forces on the wharf structural units. Therefore, based on the ship mooring information associated with the dynamic risk assessment task, the corresponding mooring cable configuration schemes in the standard operating procedure library are retrieved to determine the standard tension level of each mooring cable under the current operating conditions. Based on this, and considering the spatial arrangement relationship between the wharf mooring bollards and the ship's mooring points, the spatial angular direction of each mooring cable relative to the wharf structural unit is determined. During implementation, based on the characteristics of cable tension along its spatial direction, the standard tension of each cable is decomposed into lateral load components acting on the structural unit according to its relative angle with the wharf structural unit, and these lateral load components are associated with the corresponding wharf structural unit.

[0059] After determining the equivalent corrected static baseline operating load and the lateral load components of each mooring cable, load superposition and load schedule generation are performed. Using the operating time window specified in the dynamic risk assessment task as a constraint, the application status of various loads on the structural unit is organized according to time sequence. The equivalent corrected operating load input is then superimposed hourly with the lateral load components existing within the corresponding time period to obtain the comprehensive load variation experienced by the wharf structural unit throughout the entire operating period. This superposition process is conducted in a time series format, ensuring that load changes under different operating stages and intensities are fully recorded. Finally, the calculated results are compiled into a time-series load curve with time as the horizontal axis and load value as the vertical axis, and this curve is stored as the load schedule for the corresponding wharf structural unit. This load schedule provides a clear visual representation of the load evolution characteristics of the structural unit throughout the outfitting operation.

[0060] In step S3, a time-varying load spectrum of the entire wharf area is constructed, and a wharf structural topology network is constructed to calculate the load transfer matrix between adjacent wharf structural units.

[0061] All generated load plans for wharf structural units are uniformly loaded. Each load plan records the load changes of the corresponding structural unit throughout the outfitting operation in time series form. Based on the complete operation time range covered by the outfitting operation plan, the time axis is uniformly discretized to form a continuous and ordered set of operation time points. Subsequently, using these operation time points as row indices and all structural units within the wharf as column indices, a two-dimensional data structure is constructed to carry the load distribution information of the entire wharf area at each time point. When filling this two-dimensional data structure, for each operation time point, the load value corresponding to each wharf structural unit at that time point is read one by one and filled into the corresponding row and column positions in the matrix. If a structural unit does not participate in outfitting operations or does not bear any new operation load at a specific time point, its corresponding position is filled with zero load or the load value maintaining its basic bearing state. Through the above method, the resulting two-dimensional matrix can completely reflect the load changes of different wharf structural units at different time points throughout the entire operation cycle. This two-dimensional matrix constitutes the time-varying load spectrum of the wharf area. This time-varying load spectrum integrates load information dispersed across various structural units using a unified time scale, enabling a clear expression of the load superposition effect under conditions of multiple ships berthing and multiple operations operating in parallel.

[0062] After generating the time-varying load spectrum for the wharf area, the physical connections between the wharf structural units are further modeled. During implementation, based on the structural design data and digitized drawings of the wharf project, the physical connections and support relationships between each wharf structural unit are systematically extracted. These connections include, but are not limited to, direct structural connections formed through beams, slabs, pile caps, or other load-bearing components, as well as indirect support relationships formed through continuous foundations or the overall structural system. Based on this, a wharf structural topology network is constructed, with each wharf structural unit as an independent node and the physical connections between structural units as the connecting edges between nodes. For each connecting edge in the topology network, a load transfer coefficient is determined based on the mechanical properties of the corresponding connecting component. These mechanical properties include at least the structural form, stiffness level, and force direction characteristics of the connecting component within the overall wharf structural system. During implementation, corresponding load transfer ratios are assigned to different types of connecting components through pre-calibration or engineering experience. For example, a higher load transfer ratio is assigned to structural connections with a high degree of rigidity, while a relatively lower load transfer ratio is assigned to flexible connections or indirect support relationships. The aforementioned load transfer coefficients characterize the extent to which a change in load on a structural unit is transmitted to adjacent structural units through structural connections. By assigning load transfer coefficients to each pair of adjacent structural units in the topology network, a load transfer matrix describing the load transfer relationship between adjacent structural units is ultimately formed. This matrix defines the propagation path and intensity of loads within the structural system based on clear engineering principles.

[0063] In S4, based on the time-varying load spectrum, the rainflow counting method is used to calculate the cumulative damage index of each wharf structural unit throughout the entire planning period.

[0064] For the time-varying load spectrum already constructed in the wharf area, the data is analyzed one by one according to the structural unit dimension. Taking the wharf structural unit as the analysis object, the load time series corresponding to the structural unit during the entire outfitting operation plan period is completely extracted from the time-varying load spectrum. This load time series is arranged continuously according to the operation time axis, which truly reflects the comprehensive load changes borne by the structural unit in different operation stages. After the load time series is extracted, combined with the mechanical response characteristics of the wharf structural unit that have been determined in the design or operation stage, the load time series is equivalently mapped to convert it into the corresponding stress response time series. The equivalent mapping process is based on the structural unit's construction form, stress mode, and material properties, transforming external load changes into internal stress change levels. In this application, a pre-mapping calibration method based on engineering measurement is adopted, so that the subsequent fatigue analysis is based on the actual structural response. After obtaining the stress response time series, the rainflow counting algorithm is used to perform cyclic identification processing on the stress response time series, and the complete stress cycle formed throughout the entire planning period is identified one by one according to the peak-valley relationship of stress changes. For each identified stress cycle, its corresponding stress amplitude information is recorded, so that the various stress fluctuations experienced by the structural unit during the entire outfitting process can be systematically organized and quantitatively described.

[0065] After identifying and recording the stress cycle amplitude of each wharf structural unit, the damage contribution of each stress cycle is further quantitatively evaluated based on the fatigue performance of the structural materials. A standard stress-fatigue curve corresponding to the material used in the wharf structural unit is retrieved. This fatigue curve, used in engineering practice to describe the range of cycles a material can withstand under different stress amplitudes, is set based on engineering experience. For each identified stress cycle amplitude, the allowable number of cycles under that stress amplitude is determined according to the standard stress-fatigue curve. This allowable number of cycles characterizes the upper limit of cycles the material can safely withstand at that stress level. Based on this, for each stress cycle, the reciprocal of the allowable number of cycles is calculated, and this value is used as the damage degree corresponding to that stress cycle, quantifying the relative consumption degree of the structural fatigue state caused by that single stress cycle. Subsequently, throughout the entire outfitting operation planning period, the damage degrees of all stress cycles belonging to the same wharf structural unit are cumulatively summed, and the cumulative result is used as the cumulative damage degree index of that structural unit during the planning period. This cumulative damage index comprehensively reflects the fatigue accumulation state of structural units under repeated operational loads, enabling the fatigue risk levels of different structural units under different outfitting conditions to be compared and analyzed on a unified scale.

[0066] In step S5, the load of adjacent wharf structural units is corrected along the structural topology path based on the load transfer matrix, and the risk value of cascaded collaborative failure between structural units is calculated based on the corrected load.

[0067] For the established time-varying load spectrum of the wharf area, the load data is traversed one by one according to the wharf structural unit dimension. The load time series corresponding to each wharf structural unit during the entire outfitting operation plan period is extracted from the time-varying load spectrum, and the maximum load value experienced by the structural unit is identified in this load time series. This maximum load value reflects the actual load level borne by the structural unit at the most unfavorable operating moment under conditions of multiple vessels berthing and multiple operations operating in parallel. After obtaining the maximum load value, it is compared and analyzed with the rated load capacity data determined during the calibration phase of the wharf structural unit. The rated load capacity data is used to limit the upper limit of the safe load that the structural unit can withstand under normal operating conditions. When the maximum load value does not exceed the rated load capacity data, it is recorded that the structural unit has not generated excess load during the planning period; when the maximum load value exceeds the rated load capacity data, the excess portion is recorded separately, forming the excess load amount generated by the structural unit under the corresponding operating conditions. This excess load amount is used to characterize the local bearing pressure generated by the structural unit at extreme operating moments, providing a clear quantitative input for subsequent load propagation analysis within the structural system. By using the above methods, potential load-bearing risk points can be identified without relying on complex structural calculations, ensuring that cascaded collaborative failure analysis is based on real and traceable abnormal load conditions.

[0068] After identifying the excess load components of each wharf structural unit, the structural propagation process of the excess load is further analyzed within the wharf structural topology network. Based on the constructed wharf structural topology network, for each structural unit generating excess load, its directly adjacent structural units in the topology network are identified, and the corresponding load transfer coefficients in the load transfer matrix are retrieved. These load transfer coefficients have been calibrated based on the mechanical properties of the structural connection components. The identified excess load is distributed as additional load to each adjacent wharf structural unit according to the proportional relationship specified in the load transfer matrix, so that adjacent units receive additional load from the loaded unit on top of their original load. This distribution process strictly follows the structural connection direction and transfer intensity defined in the topology network, ensuring that the propagation path of the additional load is consistent with the actual stress relationship of the wharf structure.

[0069] After the additional load is distributed to adjacent structural units, a statistical analysis is conducted on the structural overload caused by the additional load. During implementation, for each wharf structural unit, its total load after receiving additional loads from adjacent structural units is statistically analyzed to determine whether it exceeds its corresponding rated load capacity. If, at any given moment, the total load of the structural unit exceeds its rated load capacity due to the cumulative effect of the additional load, an overload event is recorded; otherwise, it is not counted. This statistical process continues throughout the entire outfitting operation plan, ensuring that the overload situation of each structural unit at different times and under different load propagation conditions is fully recorded. Subsequently, for each wharf structural unit, the number of all overload events caused by the propagation of excess loads from adjacent units is accumulated to obtain the corresponding cumulative overload count. This cumulative value characterizes the frequency with which the structural unit is affected by abnormal loads from adjacent units within the structural system; the larger the cumulative value, the more significant the cascading impact on the structural unit within the structural coordination relationship. Finally, the accumulated number of times exceeding the limit is used as the cascaded collaborative failure risk value of the structural unit, which is used to characterize the collaborative risk level of the structural unit in the overall wharf structural system, so that the structural safety assessment can simultaneously reflect the comprehensive risk characteristics brought about by local load-bearing anomalies and the interaction between structures.

[0070] In step S6, a hierarchical operational risk heat map is generated in the terminal geographic information system to identify the structural risk level under different outfitting operations, and the outfitting operation plan is traced back and adjusted according to the structural risk level.

[0071] For each wharf structural unit, the cumulative damage index and cascaded collaborative failure risk value, calculated in previous steps, are first retrieved. These reflect the fatigue accumulation state of the structural unit over time and its sensitivity to collaborative stress within the spatial structural system, respectively. To ensure a reasonable proportion of different types of risk factors in the comprehensive assessment, a weighted fusion mechanism is introduced for these two indicators. The weights are determined based on established safety control principles in wharf structure operation and management, prioritizing fatigue safety during long-term operation while considering collaborative failure risks caused by sudden or regional load propagation. For wharf areas that are under frequent outfitting operations and have high structural aging, a relatively high weight is assigned to the cumulative damage index, for example, making it a major part of the comprehensive risk assessment. For newly built or recently reinforced wharf areas with multiple units operating concurrently, the weight of the cascaded collaborative failure risk value in the comprehensive assessment is appropriately increased. These weights are determined based on the wharf structure's service life, historical operation density, and the criticality of the structural unit in the topology network, and remain consistent within the same evaluation period. By fusing the weighted cumulative damage index with the cascaded collaborative failure risk value, a comprehensive risk value reflecting the overall risk level of the structural unit under the current outfitting operation conditions is obtained. Subsequently, according to the risk classification rules already adopted in port safety management, the continuous comprehensive risk value is mapped and converted into the corresponding structural risk level, so that different structural units can be clearly distinguished in terms of risk level, and a structured expression of risk status can be achieved.

[0072] After obtaining the structural risk level corresponding to each wharf structural unit, the risk results are further spatialized by combining wharf geographic information data. Spatial coordinate information and geometric shape data of each wharf structural unit are retrieved from the wharf geographic information system. The geometric shape data is used to accurately describe the location range and boundary shape of the structural unit in the wharf plane. Based on this, a spatial layer covering the entire outfitting wharf area is constructed, using the wharf structural unit as the smallest spatial expression unit, where each element corresponds to a specific structural unit. Subsequently, based on the determined structural risk level, clear color filling rules are pre-defined for different risk levels. For example, a gradient from cool to warm colors is used to distinguish risk levels, with each level corresponding to a unique and fixed color representation. During implementation, according to the structural risk level assigned to each structural unit, the corresponding color filling rule is invoked to colorize and render the geometry of the structural unit, presenting it in a visually intuitive color form in the spatial layer. By performing the above color rendering operation on all wharf structural units, a risk heat map covering the entire outfitting wharf area is finally generated. This heat map reflects the risk status of each structural unit under different outfitting operation conditions in a color distribution format. This spatial representation method allows managers to quickly identify areas of concentrated risk and structurally sensitive locations without having to examine numerical results one by one, thereby enabling intuitive perception and precise positioning of structural risks in actual outfitting operations and safety management.

[0073] The generated outfitting wharf operation risk heat map is analyzed. This heat map uses wharf structural units as the basic spatial representation unit, and each structural unit is assigned a clear structural risk level identifier. During implementation, by reading the spatial identifier information of each structural unit in the heat map, all wharf structural units with identified risk levels are located one by one, forming a structural unit risk list. Subsequently, for each located structural unit, a reverse query operation is performed in the dynamic risk assessment task record based on its unique structural unit identifier. This dynamic risk assessment task record completely preserves the association between structural units and outfitting operation tasks. Through this reverse query process, all outfitting operation task information affecting the structural unit within the current planning period can be accurately extracted. This task information includes at least the corresponding vessel identifier, operation project code, operation time window, and operation sequence. In this embodiment, when the same structural unit is affected by multiple outfitting operation tasks in different time windows, all related operation tasks are uniformly aggregated into the operation task set corresponding to that structural unit, thereby forming a clear mapping relationship between structural units and outfitting operations.

[0074] After establishing the reverse correlation between structural units and their corresponding outfitting tasks, targeted constraints are further implemented on the associated outfitting operation plans based on the cumulative damage index and cascaded collaborative failure risk value of the structural unit. During implementation, for each associated outfitting task, the contribution characteristics of the task to the cumulative damage and collaborative failure risk of the structural unit are analyzed, taking into account its corresponding operation time window and operation type. When the cumulative damage index of a structural unit is continuously increasing, time constraints are implemented for outfitting tasks with long operation durations or repetitive operation characteristics on that structural unit. By adjusting their operation time window positions, high-frequency continuous loads are avoided on the same structural unit. When the cascaded collaborative failure risk value of a structural unit is prominent, concurrent constraints are implemented for outfitting tasks involving large-scale hoisting or potentially causing load propagation to adjacent structural units, restricting them from being executed simultaneously with other high-load operations within the same time period. The aforementioned constraints directly apply to specific task items in the outfitting operation plan. By adjusting the order of operations, the concurrency of operations, and the distribution of operations, proactive control of structural unit risks is achieved. In this embodiment, the outfitting operation plan, after being constrained, will be reorganized and recorded to ensure that the operation plan meets structural safety constraints while maintaining the original operational objectives. In this way, the structural risk assessment results are directly transformed into executable adjustment rules for the outfitting operation plan, realizing closed-loop management from risk identification to operation control, and ensuring that the wharf structure remains in a controllable and safe operating state under complex outfitting operation conditions.

[0075] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0076] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0077] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0078] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0079] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0080] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0081] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion 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 this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0082] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0083] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A risk intelligent monitoring method for the structural safety of outfitting wharves, characterized in that, Includes the following steps: S1. Analyze the outfitting operation plan and generate dynamic risk assessment tasks for each ship and associated terminal structural unit based on the mapping relationship between ship berths and terminal structural units. S2. Based on the list of work items in the risk assessment task, match the corresponding lifting object weight, lifting range and mooring cable standard configuration data from the preset standard operation process library, and combine the rated load data of the wharf structural unit to simulate and generate a load plan table for the operation period. S3. Overlay the load schedules of all adjacent wharf structural units according to the operation time axis to construct the time-varying load spectrum of the entire wharf area. At the same time, construct the wharf structural topology network and calculate the load transfer matrix between adjacent wharf structural units. S4. Based on the time-varying load spectrum, the rainflow counting method is applied to calculate the cumulative damage index of each wharf structural unit throughout the entire planning period; S5. Based on the load transfer matrix, the load of adjacent wharf structural units is corrected along the structural topology path, and the risk value of cascaded collaborative failure between structural units is calculated based on the corrected load. S6. Based on the cumulative damage index and the collaborative failure risk value, generate a hierarchical operation risk heat map in the terminal geographic information system, identify the structural risk level under different outfitting operations, and adjust the constraints of the outfitting operation plan by tracing back according to the structural risk level.

2. The intelligent risk monitoring method for the structural safety of outfitting wharves according to claim 1, characterized in that, In step S1, generating the dynamic risk assessment task specifically includes: Read the dock's outfitting operation plan, identify and extract the berth number corresponding to each outfitting vessel and the sequence of outfitting operation items represented by the operation code, and establish a mapping relationship between berth numbers and dock structural unit identifiers based on the preset dock zoning digital drawings. Traverse the sequence of work items and create a dynamic risk assessment task record for each affected wharf structural unit in combination with the planned work time window. The record should include at least the associated vessel identifier, wharf structural unit identifier, work time window, and work item code list.

3. The intelligent risk monitoring method for the structural safety of outfitting wharves according to claim 1, characterized in that, In step S2, the simulation of generating a load schedule for the work period specifically includes: Based on the load-bearing attributes of the wharf structural units corresponding to the dynamic risk assessment task, including vertical and lateral rated load data; Within the operation time window, extract the static benchmark operation load that directly acts on the dock structural unit from the weight of the hoisting object. Based on the crane's working load curve, the rated lifting capacity under the current working conditions is queried using the lifting operation radius. The ratio of the weight of the object being lifted to the rated lifting capacity is used as the dynamic load coefficient to make an equivalent correction to the static reference working load. Based on the spatial angle between the mooring lines and the ship at the dock mooring bollards, the standard tension configuration of each line is decomposed into lateral load components on the dock structural units. The equivalent corrected static baseline operating load and each lateral load component are superimposed according to the time series to calculate the total load generated on the wharf structural unit, and a time-series load curve with time as the horizontal axis and load value as the vertical axis is generated as the load plan table of the wharf structural unit.

4. The intelligent risk monitoring method for the structural safety of outfitting wharves according to claim 1, characterized in that, In step S3, the time-varying load spectrum of the entire wharf area is constructed, and the wharf structural topology network is constructed simultaneously. The calculation of the load transfer matrix between adjacent wharf structural units specifically includes: Load the time-series load curves corresponding to the load plans of all wharf structural units, establish a two-dimensional matrix with the operation time points as rows and the wharf structural units as columns, fill the load values ​​corresponding to the structural units at each time point into the corresponding positions of the matrix, and form the time-varying load spectrum of the wharf area. Extract the physical connections and support relationships between each structural unit, construct the wharf structure topology network with units as nodes and connections as edges, and assign a load transfer coefficient to each pair of adjacent units according to the connection direction of the edges in the topology network and the mechanical properties of the connecting components. All load transfer coefficients form the load transfer matrix between adjacent units.

5. The intelligent risk monitoring method for the structural safety of outfitting wharves according to claim 1, characterized in that, In step S4, the calculation of the cumulative damage index of each wharf structural unit throughout the entire planning period using the rainflow counting method, based on the time-varying load spectrum, specifically includes: The complete load time series of each wharf structural unit is extracted from the corresponding time-varying load spectrum, and the complete load time series is equivalently mapped to the stress response time series. All complete stress cycles in the series are counted by the rainflow counting algorithm, and the amplitude of each stress cycle is recorded. Based on the preset standard stress fatigue curve of the wharf structure material, the allowable number of cycles is matched for each identified stress cycle amplitude, and the reciprocal of the allowable number of cycles is calculated as the damage degree of each stress cycle. The cumulative damage index of each wharf structural unit is obtained by summing up the damage of all stress cycles during the planning period.

6. The intelligent risk monitoring method for the structural safety of outfitting wharves according to claim 1, characterized in that, In step S5, the load of adjacent wharf structural units is corrected based on the load transfer matrix along the structural topology path, and the risk value of cascaded collaborative failure between structural units is calculated based on the corrected load, specifically including: Traverse and extract the maximum load value of each wharf structural unit in the time-varying load spectrum, compare the maximum load value with the rated load data of the wharf structural unit, and record the excess load part that exceeds the rated load data; In the wharf structure topology network, based on the transmission coefficient between the wharf structure unit and each adjacent unit in the load transmission matrix, the excess load is proportionally distributed as additional load to each adjacent unit. For each wharf structural unit, the number of times its total load exceeds the rated capacity after each adjacent unit receives additional load is counted. The number of times all adjacent units exceed the limit is accumulated, and the accumulated value is used as the cascade collaborative failure risk value of that unit.

7. The intelligent risk monitoring method for the structural safety of outfitting wharves according to claim 1, characterized in that, In step S6, generating a layered operational risk heatmap in the terminal geographic information system to identify the structural risk level under different outfitting operations specifically includes: The cumulative damage index of each wharf structural unit is weighted and fused with the cascaded collaborative failure risk value to obtain the comprehensive risk value of each structural unit and convert it into the corresponding structural risk level. Based on the spatial coordinates and geometric shape data of each wharf structural unit stored in the wharf geographic information system, a spatial layer with structural units as basic graphic elements is generated. According to the structural risk level assigned to each structural unit, the corresponding color filling rules are called to color and render the geometry of each unit, generating an operational risk heat map with color representing the risk level.

8. The intelligent risk monitoring method for the structural safety of outfitting wharves according to claim 1, characterized in that, In S6, the constraint adjustment of the outfitting operation plan based on the structural risk level includes: Locate all wharf structural units with identified risk levels in the operational risk heat map, query the corresponding outfitting operation plan based on the dynamic risk assessment task record, and adjust the tasks of the outfitting operation plan based on the cumulative damage index and cascade collaborative failure risk value.

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