Water conservancy facility damage assessment and maintenance system

Abstract

The invention relates to the technical field of water conservancy facilities, in particular to a water conservancy facility damage assessment and maintenance system which comprises a working condition fluctuation recognition module, a sudden change recognition module, a load judgment module, a response deviation module and a task sorting module. According to the method, through multi-period combined trend analysis combining pressure, strain and flow velocity, a change direction and synchronism comparison mechanism among multiple parameters is established, disturbance symptoms can be identified before the structural state is abruptly changed, the sensitivity of risk early-stage identification is improved, and through time coincidence judgment of a strain curve and a pressure abrupt change point, the accuracy of risk early-stage identification is improved. Multi-part response data is introduced for cross comparison, a cross-parameter linkage recognition mechanism is constructed, the recognition depth of structural response abnormity is enhanced, state evaluation of the operation load is based on the gradient fluctuation change trend between the average load and the peak load, single-point judgment errors are avoided, and operation limit judgment logic is refined.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water conservancy facilities, and particularly relates to a water conservancy facility damage assessment and maintenance system. BACKGROUND

[0002] Water conservancy facilities refer to a collection of various engineering facilities and related technologies for water resource development, utilization, management and protection, covering the design, construction, operation, detection, maintenance and management of structures such as dams, reservoirs, dikes, diversion channels, sluices, pumping stations and pipelines and their auxiliary systems. This field closely combines hydrology, hydraulics, civil engineering, structural mechanics, materials science and modern information technology, and is widely used in the fields of flood control, drainage, irrigation, water supply, hydropower generation and ecological environment protection.

[0003] Among them, the water conservancy facility damage assessment and maintenance system is a comprehensive platform integrating detection technology and intelligent analysis system, which is used for comprehensive identification, assessment and recording of the damage of various water conservancy engineering facilities during service, and provides scientific maintenance suggestions and management measures accordingly. Its main purpose is to improve the safety, reliability and maintenance efficiency of water conservancy facilities, and it is particularly suitable for real-time monitoring and risk warning of large or key facilities, realizing the transformation from traditional passive maintenance to active prevention and accurate management.

[0004] The prior art mainly relies on single parameter abnormal values for judgment in water conservancy facility monitoring, often triggers alarm with static threshold, lacks trend coordination judgment ability among multi-dimensional monitoring data, and cannot identify early signals of structural disturbance in time. In the assessment task response priority order, fixed rules or task classification results are often used for static sorting, without joint assessment of task time consumption and facility state change, which may cause mismatch between scheduling priority and actual risk level. Resource allocation is executed according to the established plan, without considering the real-time influence of facility operation state change on response resource scheduling, which may cause deviation in scheduling response, affect immediate processing of high-risk facilities, and cause disconnection between resource calling and health deviation state in scheduling process, so that task sorting cannot dynamically adapt to regional scheduling conditions, resulting in out-of-order task processing, affecting water conservancy facility operation safety and operation efficiency. SUMMARY

[0005] The present application aims to solve the problems in the prior art and provides a water conservancy facility damage assessment and maintenance system.

[0006] In order to achieve the above-mentioned purpose, the present application adopts the following technical scheme: a water conservancy facility damage assessment and maintenance system, the system comprises: The working condition fluctuation identification module is based on key components of the water conservancy facility, analyzes variation trends of pressure, strain and flow rate monitoring data, judges whether it is continuously increasing in multiple cycles, compares current and previous data synchronicity and variation direction, filters increasing trend cycles, identifies structure operation fluctuation state, and obtains a cycle linkage enhancement stage; The mutation identification module is based on the cycle linkage enhancement stage, judges whether the monitoring parameter curve has a mutation, compares time correspondence of strain and pressure mutation points, calculates offset rate difference in combination with structure component response data, identifies potential linkage abnormalities, and obtains an evolution intensity grade; The load determination module is based on the evolution intensity grade, analyzes changes of a load curve, compares average load and peak value difference of adjacent cycles, judges whether the load curve is close to a critical state, filters a load stage with a sudden change feature, and obtains an operation critical response section. The response deviation module is based on the operation critical response section, compares task response time consumption and health offset range, judges whether the response time matches, identifies scheduling time offset tasks in combination with historical scheduling records and resource response conditions, and obtains a deployment delay conflict identification quantity.

[0007] The application improves that the cycle linkage enhancement stage includes a trend joint growth segment, a monitoring data synchronization section and a structure response initial change interval, the evolution intensity grade includes a linkage mutation grade, an offset synchronization grade and a curve jump grade, the operation critical response section includes a load transition boundary section, an operation wave amplitude change section and a device load integration section, and the deployment delay conflict identification quantity includes a task response lag mark, a facility state offset level and a scheduling matching error parameter.

[0008] The application improves that the working condition fluctuation identification module includes: The cycle trend extraction submodule is based on key components of the water conservancy facility, analyzes variation trends of pressure, strain and flow rate in a key component operation cycle, judges whether consecutive cycles commonly present an upward trend, filters out data cycles with inconsistent variation directions, and obtains a trend growth cycle sequence. The data variation filtering submodule compares data variation directions of consecutive two cycles in the trend growth cycle sequence, filters cycles with consistent variation directions, judges whether there is a positive change of pressure, strain and flow rate at the same time, excludes cycles with mixed offset trends, and obtains a synchronous increasing cycle set. The structure attribution judgment submodule judges consecutive cycle combination conditions according to the synchronous increasing cycle set, analyzes growth consistency of monitoring data in consecutive cycles, identifies cycle combinations with stable linkage growth, and obtains a cycle linkage enhancement stage.

[0009] The application improves that the mutation identification module includes: The inflection detection submodule analyzes the slope change of the strain curve and the pressure curve in a period based on the period linkage enhancement stage, judges whether the direction reversal or mutation position appears in the same period, performs corresponding mapping by identifying the time sequence position of the transformation point, compares the mapping integrity, and obtains the period inflection correspondence proportion; The time correspondence comparison submodule calls the period inflection correspondence proportion, compares the sequence deviation of the strain mutation time and the pressure mutation time, screens the period segments whose time difference is within a range, and counts the coverage number of the period segments in all periods, to obtain the time synchronization distribution proportion; The rate difference calculation submodule calculates the displacement change rate of the structural response point in the inflection period according to the time synchronization distribution proportion, judges the response difference degree of the arch back plate and the pressure node in the same period, analyzes whether the change amplitude exists periodic divergence, calculates the period structural response difference amplitude, and combines the time synchronization distribution proportion to obtain the evolution intensity level.

[0010] The load determination module comprises: The load segment extraction submodule analyzes the load curve shape in the operation period of the water conservancy facility equipment based on the evolution intensity level, identifies the segment where the curve fluctuates, calculates the load variation frequency and continuous time span of the segment, discriminates the continuous change state, screens the key stage where the fluctuation state concentrates, and obtains the sudden load change segment. The load difference judgment submodule calls the sudden load change segment, compares the average load and peak load trend of the sudden segment in adjacent periods, analyzes the direction and degree of difference change, compares the curve shape evolution intensity according to the difference trend amplitude data, synchronously classifies the trend category, judges whether the curve trend has a mutation, and obtains the load difference mutation trend amplitude. The critical response screening submodule calculates the response fluctuation ratio sequence based on the load difference mutation trend amplitude, screens the operation stage in the response feature set, and obtains the operation critical response segment.

[0011] The response deviation module comprises: The response time consumption discrimination submodule compares the operation critical response segment with the health offset period in the facility monitoring record, determines the time deviation, judges whether the task response exceeds the period time structure corresponding to the normal operation of the facility, marks the task that has response lag, and obtains the response time offset amount. The offset period adaptation submodule judges whether the response offset performance of the task matches the current operation period based on the response time offset amount, determines the duration of the offset phenomenon in the period, identifies the period misalignment task, screens the task group that affects the scheduling rhythm, and obtains the period mismatch task amount. The conflict identification generation submodule identifies construction time conflicts and resource response overlap conditions according to the periodic mismatch task quantity, calculates the deployment conflict degree between tasks, judges the tasks with arrangement conflicts and response imbalance, and obtains the deployment delay conflict identification quantity.

[0012] The system further comprises: The task sequencing module converts the deployment delay conflict identification quantity into scoring data of the same scale, compares the resource matching relationship of the tasks within the current scheduling range, arranges the task order according to the scoring level, and obtains the maintenance scheduling priority classification result. The maintenance scheduling priority classification result comprises a task priority level label, a resource matching score, and a risk linkage scoring parameter.

[0013] The task sequencing module comprises: The scoring conversion submodule analyzes the deployment response delay and the conflict between tasks based on the deployment delay conflict identification quantity, judges the interference degree of the tasks on the scheduling plan according to the time difference and the conflict frequency of the tasks in the operation process, determines the influence degree between the tasks, adjusts the scoring range occupied by the tasks to a unified interval, and generates delay conflict scoring data. The priority sequencing submodule calls the delay conflict scoring data, compares the current availability of the resources and the required configuration conditions of the tasks, calculates the adaptation degree between the tasks and the resources, and sequentially arranges the tasks to obtain the maintenance scheduling priority classification result.

[0014] Compared with the prior art, the application has the following advantages and positive effects: In the application, the change direction and synchronization comparison mechanism between multiple parameters are established through the multi-period joint trend analysis of pressure, strain and flow rate, the disturbance signs can be identified before the structure state is severely mutated, the sensitivity of early risk identification is improved, the cross comparison of multi-site response data is introduced through the time coincidence of strain curve and pressure mutation point, the cross-parameter linkage identification mechanism is constructed, the identification depth of structure response anomaly is enhanced, the state evaluation of operating load is based on the gradient fluctuation trend between average load and peak load, the single-point judgment error is avoided, the operating limit judgment logic is refined, at the task level, the adaptation relationship between task response time and facility deviation state is identified and handled, the task sequencing is directly related to regional resources, risk degree and scheduling efficiency by combining historical resource arrangement information to form a dynamic scoring standard, the dynamic nature and response coordination of task priority sequencing are improved, and the operation safety and operation efficiency of water conservancy facilities are ensured. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1A system flow chart of the present application; Figure 2 A flow chart of the working condition fluctuation identification module in the present application; Figure 3 A flow chart of the mutation identification module in the present application; Figure 4 A flow chart of the load determination module in the present application; Figure 5 A flow chart of the response deviation module in the present application; Figure 6 A flow chart of the task sequencing module in the present application. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solutions and advantages of the present application clearer and more apparent, the present application will be further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0017] In the description of the present application, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, in the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise explicitly and specifically limited.

[0018] EMBODIMENT Please refer to Figure 1 The present application provides a technical solution: a water conservancy facility damage assessment and maintenance system comprising: The working condition fluctuation identification module analyzes the pressure, strain and flow rate monitoring data trend within the operation cycle based on the key components of the water conservancy facility, determines whether it is continuously increasing in the same direction in multiple cycles, compares the data synchronization and change direction of the current stage and the previous stage, filters the data cycle that simultaneously shows an increasing trend, determines the structure operation fluctuation state to which the cycle belongs, and obtains the cycle linkage enhancement stage; The mutation identification module judges whether the monitoring parameter curve has a turning point in the same cycle based on the cycle linkage enhancement stage, compares the time correspondence of the strain curve and the pressure mutation point, combines the structure response data of the arch gate back plate and the pressure dispersion node, calculates the key parameter combination of the deviation rate difference, identifies the abnormal position of potential linkage, and obtains the evolution intensity grade; The load determination module analyzes the change section of the load curve in the operation cycle of the water conservancy facility equipment based on the evolution intensity level, compares the difference degree of the average load and the peak load between adjacent cycles, judges whether the current load curve appears a fluctuation trend approaching the critical operation state, screens the load stage meeting the jump characteristics, and obtains the operation critical response section; The response deviation module compares the response time of the current task with the health offset range in the facility monitoring based on the operation critical response section, judges whether the response time matches the abnormal offset cycle, combines the historical records of the associated facilities in the maintenance construction arrangement and the regional material response queue, identifies the dispatching time offset task, and marks the emergency degree of the task processing, to obtain the deployment delay conflict identification quantity; The task sorting module converts the deployment delay conflict identification quantity into scoring data of the same scale, compares the resource matching relationship of the task in the current dispatching range, arranges the task order according to the score, and obtains the maintenance dispatching priority classification result.

[0019] The cycle linkage enhancement stage includes the trend joint growth segment, the monitoring data synchronization section, and the structure response initial change interval. The evolution intensity level includes the linkage mutation level, the offset synchronization level, and the curve jump level. The operation critical response section includes the load transition boundary segment, the operation wave amplitude change segment, and the equipment load integration segment. The deployment delay conflict identification quantity includes the task response lag mark, the facility state offset level, and the dispatching matching error parameter. The maintenance dispatching priority classification result includes the task priority level label, the resource matching score, and the risk linkage score parameter.

[0020] Key components of water conservancy facilities refer to the parts that bear the main structural load or perform the core function in water conservancy facilities, usually including gate opening and closing mechanisms, spillway culverts, pressure well linings, intake and outlet walls, energy dissipaters, etc., whose operating state directly affects the overall safety and stability of the facility; data synchronization refers to whether the change trends of multiple monitoring parameters (such as pressure, strain, flow rate) in the time dimension are consistent, i.e., whether the parameters collectively show similar directional changes (e.g., rising or falling simultaneously) within the same monitoring period, for evaluating the coordination of structural response; change direction refers to whether the numerical trends of each monitoring parameter in consecutive periods show consistent directionality (e.g., increasing or decreasing), by comparing the change trends of the current period with the previous period to determine whether the fluctuations are continuous or reversed; structural operating fluctuation state refers to the dynamic stability performance of water conservancy facility structures within a certain period, if multiple key monitoring parameters show synchronous fluctuation intensification, it is considered to be in a fluctuation state, indicating that the structure is in a sensitive stage of disturbance or stress concentration; monitoring parameter curve refers to the time series curve drawn by a certain monitoring data (such as strain, pressure) within a continuous time period, for analyzing the trend, inflection point, mutation, etc. of the parameter on the time axis; time correspondence refers to whether the key change points (such as mutations or inflection points) on different parameter curves occur at the same or similar time nodes, for identifying whether there is a synchronous response behavior or potential linkage phenomenon; offset rate difference refers to the difference between the change rates of two parameters within the same time period, for measuring whether the response difference is abnormally increased, which is an important basis for judging stability and linkage relationship; abnormal position of potential linkage refers to the position area where different monitoring parameters mutate and interact within the same period, usually showing an abnormal coupling point of structural response, such as the coincidence of strain peak value and pressure sudden increase in the same section; water conservancy equipment refers to mechanical and electrical equipment that undertakes operational functions in water conservancy projects, typical examples include water pumps, electric hoists, hydraulic control systems, etc., which are different from structural components, focusing on operation and control, whose performance state directly affects project scheduling and water supply safety; critical operating state refers to the working state of equipment when it approaches the upper limit of safe operation or load limit, usually showing load soaring, operating efficiency decreasing or energy consumption increasing, etc., which is the operating node that needs early warning and intervention; sudden change feature refers to the rapid change of load curve within a short time, such as sudden rise or fall, caused by external intervention, internal failure or structural feedback, which is an important graphical feature for identifying equipment health abnormalities; maintenance construction arrangement refers to the construction organization arrangement of maintenance tasks in space and time dimensions, including work team distribution, construction schedule arrangement, work point setting, etc., affecting response timeliness and resource distribution; regional material response queue refers to the scheduling and calling sequence of materials (such as tools, spare parts, maintenance equipment) supporting maintenance tasks between regions, the rationality of the queue relates to the time matching and resource accessibility of task execution;The resource matching relationship of the task in the current scheduling range refers to the matching degree between the spatial region where the task is located and the currently available maintenance resources (manpower, materials, tools, and access paths), including whether the resources are sufficient, whether they are in the same region, and whether the response time is reasonable, which is the basis for determining the task ordering priority.

[0021] Referring to Figure 2 , the working condition fluctuation identification module includes: The periodic trend extraction submodule analyzes the pressure, strain, and flow rate variation trends within the operating period of the key component of the water conservancy facility, judges whether they collectively show an upward trend within consecutive periods, filters out data periods with inconsistent variation directions, and obtains a trend growth period sequence. Taking the arch gate backplate in water conservancy facilities as the key component, the continuous monitoring records of pressure, strain, and flow rate formed during daily operation are collected, the data is divided into a complete period every day, the monitoring data within a period is summarized by hour to form an average value sequence every hour, and then the average values of each period are compared item by item. For any two adjacent periods, it is judged whether the average values of pressure, strain, and flow rate are increased compared with the previous period. If the three data are all in a positive upward trend within the adjacent period, then mark this period as a growth period group. For example, within three consecutive days, the pressure of a gate backplate changes from 48.5 to 51.0 to 53.4, the strain changes from 21.2 to 23.5 to 25.6, and the flow rate increases from 3.8 to 4.2 to 4.6. Since each item shows an increasing trend, the three days corresponding to the periods are marked as trend growth periods. If the flow rate decreases from 4.2 to 3.7 on a certain day, then the period does not meet the condition and needs to be excluded. After completing the judgment of all periods in the entire time sequence, the period numbers of all periods that meet the condition of continuous upward trend of the three parameters are retained as the trend growth period sequence for further screening and judgment.

[0022] The data variation screening submodule compares the data variation directions of two consecutive periods in the trend growth period sequence, screens the periods with consistent variation directions, and judges whether there is a positive change in pressure, strain, and flow rate at the same time. The periods with mixed offset trends are excluded, and a synchronous increasing period set is obtained. Extracting the continuous period pairs in each group, comparing the change direction of pressure, strain and flow rate respectively, in each period group, the difference between the monitoring values of the previous and the next period is judged to be positive or negative, if all three parameters are positive, it means that the period group belongs to the positive growth period, if any one is negative or zero, the group period is excluded; Taking two days as an example, the pressure of the previous day is 54.0, and the pressure of the next day is 56.8, the strain rises from 26.4 to 27.9, and the flow rate rises from 4.7 to 5.1, so it is considered that this period pair belongs to the positive growth period; If the flow rate is 4.3, i.e. from 4.7 to 4.3, the period group is excluded; In order to further improve the identification accuracy, the fluctuation of the data in the period is also checked, the change amplitude of each parameter is calculated, if the fluctuation of a certain parameter is large, the data is unstable, and whether the fluctuation range is less than the specified judgment value is judged, if not, the period is excluded; For example, the hourly pressure fluctuation in a certain period is greater than 2.5, if it exceeds the preset stable interval, although the trend is rising, the period combination also needs to be excluded. After excluding all the periods that do not meet the conditions, the remaining periods are the synchronous incremental period set, which provides basic data support for subsequent stability judgment.

[0023] The structure attribution judgment submodule judges the continuous period combination according to the synchronous incremental period set, analyzes the consistency of the growth of the monitoring data in the continuous period, identifies the period combination with stable linkage growth, and obtains the period linkage enhancement stage. After obtaining the synchronous incremental period set, the continuous numbered periods in the set are combined in turn, whether there are more than three periods that continuously keep synchronous increment is identified, the growth amplitude of pressure, strain and flow rate in each continuous period segment is checked, whether the growth keeps small fluctuation amplitude and is consistent in direction is analyzed, if the pressure growth amplitudes of three periods are 1.6, 1.5 and 1.7 respectively, the strain growth is 1.2, 1.1 and 1.3, and the flow rate growth is 0.3, 0.3 and 0.4, it is considered that the growth behavior of the period is consistent and stable, the combination is marked as a stable growth sequence, the start and end period numbers are recorded, and the number of days, the total change value and the daily average change value of the three data in this period are also counted, and the linkage state identification value is assigned to each stable period, which is used as the period linkage enhancement stage. In practical application, when the monitoring values of a certain facility on the 5th, 6th and 7th day continuously meet the above stable growth characteristics, the 5th to 7th period can be defined as a linkage enhancement stage, which is used by the next mutation identification module. The data growth degree and duration of the stage also need to be marked synchronously, which provides basic data support for subsequent identification of abnormal trend evolution level.

[0024] Please refer to Figure 3 , the mutation identification module comprises: The inflection detection submodule is based on the periodic linkage enhancement stage, analyzes the slope changes of the strain curve and the pressure curve in the period, judges whether there is a direction reversal or a mutation position in the same period, maps the time sequence position of the transformation point, compares the mapping integrity, and obtains the periodic inflection correspondence proportion; All data points of the strain curve and the pressure curve in the period are extracted, the data is discretized into equally spaced points in time sequence, the slope value is calculated using the change amplitude between each adjacent point pair, the slope direction of the continuous time points is judged, whether there is a change phenomenon from positive to negative or from negative to positive is identified, the time point of the slope direction reversal is recorded as a candidate inflection point, for example, the strain curve in a certain period shows positive growth from time t1 to t5, and decreases from t5 to t8, then it is judged that there is a direction inflection at time t5, the pressure curve also repeats the above operation, and the complete inflection point time set is obtained, then for each strain curve inflection point, whether there is a time close pressure curve inflection point is found, the maximum time error threshold is set to 2 minutes, if the corresponding pressure change inflection point can be found within 2 minutes, it is judged as an effective inflection pair, the strain inflection points are continuously traversed, and the ratio of the number of successfully matched points to the total number of inflection points is accumulated, the complete mapping proportion is obtained, for example, 5 strain inflection points are identified in a period, 4 of which can be matched to inflection points in the pressure curve within the error tolerance, then the periodic inflection correspondence proportion is 80%, if the proportion is lower than the set threshold 60%, the period is judged as a weak inflection correspondence period, and is not included in the subsequent analysis, otherwise it is retained as a candidate period.

[0025] The time correspondence comparison submodule calls the periodic inflection correspondence proportion, compares the sequence deviation of the strain mutation time and the pressure mutation time, selects the period segment with the time difference within the range, and counts the coverage number in all periods to obtain the time synchronization distribution proportion. In the period with a ratio higher than the set threshold, the time difference of each corresponding inflection point is further extracted to form a mutation time comparison sequence. It is judged whether the time difference of each inflection point in each period falls within the set maximum synchronization time deviation interval, which is set to 1 minute to 3 minutes, and is selected according to the response time accuracy requirement of the hydraulic facility. For example, in period 8, 3 groups of inflection point pairs are detected, and the time differences are 1.1 minutes, 2.8 minutes and 3.5 minutes respectively. Only the first two groups belong to the matching group that meets the deviation requirement. Period 8 is marked as a partial time synchronization period. If all the time differences of the inflection points in a period are within 3 minutes, the period is marked as a complete time synchronization period. Meanwhile, the number of such periods in all periods is accumulated to calculate the coverage ratio. Assuming that the total number of analysis periods is 20, and the number of periods that meet the condition that all the time differences of the inflection points are within the set range is 14, the output time synchronization distribution ratio is 70%, and the period number is output as the basis for subsequent mutation intensity determination.

[0026] The rate difference calculation submodule calculates the displacement change rate of the structural response point in the inflection period according to the time synchronization distribution ratio, judges the response difference degree of the arch back plate and the pressure node in the same period, analyzes whether the change amplitude exists periodic divergence, and uses the formula: ; Obtain the amplitude of the structural response difference , which is used to measure the change degree of the structural behavior of the arch back plate and the pressure node in the synchronization period, and obtain the evolution intensity level in combination with the time synchronization distribution ratio, wherein, represents the response change amount of the arch back plate in the period, which refers to the displacement difference between the start and end times of the arch back plate in the period, represents the response change amount of the pressure node in the period, which refers to the displacement difference between the start and end times of the pressure dispersion node in the period, represents the span of the period, i.e. the total length of the structural response period in the inflection period, represents the average term of the structural point acceleration in the period, which is derived from the average calculation of the acceleration change of the arch back plate and the pressure node sampling point, represents the average term of the structural point displacement in the period, which is the average value of the displacement amplitude of the sampling point in the period, represents the response process duration in the period, which corresponds to the total time of the structural response from the start to the end in the period, and is used for uniform adjustment of the response process timeliness, represents the number of synchronization periods, i.e. the number of periods determined as inflection synchronization in the time synchronization distribution ratio screening; The displacement rate of each cycle is estimated by the displacement change of the structural response point in each cycle. The calculation formula of displacement change rate is the difference value of displacement in each cycle divided by the time span. For example, in a certain cycle, the displacement of the strain curve and the pressure node is 0.08 m and 0.12 m respectively, and the cycle time span is 4 seconds. Then the displacement change rate of the cycle is calculated as: ; The response rate difference in each cycle is compared to observe whether there is a periodic divergence. Specifically, the displacement change rates in all cycles are compared to analyze the differences. If the difference is large, it means that the dynamic response of the structure changes dramatically between different cycles, indicating potential structural abnormalities.

[0027] The formula is used to calculate the amplitude of the periodic structural response difference . By substituting the numerical values, if the displacement difference of the arch back plate in the first cycle is 0.08 m, the displacement difference of the pressure node is 0.12 m, the cycle time span is 4 seconds, the average acceleration is 0.2 m / s2, the average displacement is 0.1 m, and the reaction time is 6 seconds, the formula is used to calculate: ; The square of the displacement difference is calculated and divided by the square of the time span: ; The product of acceleration and displacement is calculated and divided by the reaction time: ; The sum of the two is: ; If the number of cycles (i.e. only one cycle result), then: ; Therefore, the amplitude of the periodic structural response difference . The result shows that the response difference between the arch back plate and the pressure node is small in the given cycle, and the dynamic behavior of the structure changes smoothly. The formula aims to comprehensively evaluate the response difference between the arch back plate and the pressure node in the periodic change, and analyze the potential structural abnormalities or dramatic evolution by calculating the degree of structural behavior change in different cycles.

[0028] Please refer to Figure 4 , the load determination module includes: The load section extraction submodule analyzes the load curve shape in the operation period of the water conservancy facility equipment based on the evolution intensity level, identifies the section where the curve fluctuates, calculates the load variation frequency and continuous time span of the section, discriminates the continuous change state, screens the key stage where the fluctuation state concentrates, and obtains the sudden load change section; Based on the determination result of the evolution intensity level, the point-by-point extraction of the load curve data is performed for each operation period corresponding thereto, the complete time sequence is generated by sampling every hour, in each period, the curve data is traversed, the change amplitude between adjacent points is calculated, it is judged whether the load continuously presents an upward or downward trend, when two or more positive and negative alternating fluctuations continuously occur, and the fluctuation amplitude is greater than the set fluctuation reference value, the continuous section is marked as a fluctuation section, after all the fluctuation sections are identified, the duration length of each section is counted, the number of fluctuation sections that occur in a period is counted, if the number of fluctuation sections in a section is more than 3 and the total duration time accounts for more than 30% of the whole period, the section is marked as a fluctuation concentrated section, which is taken as a candidate sudden load stage; for example, in the 12th period of operation of a certain water conservancy hub, the hourly load is 72, 75, 73, 78, 74, 79, 77, and 82, the fluctuation amplitude continuously exceeds 3 units, forms 3 fluctuation peaks, and concentrates between the 3rd hour and the 8th hour, the total fluctuation time is 6 hours, accounting for 75% of the period length, and the fluctuation frequency is 4 times, which meets the preset fluctuation concentration identification standard, the section is marked as a sudden load change section, and its starting time, ending time, average load and maximum load value and other attributes are recorded.

[0029] The load difference judgment submodule calls the sudden load change section, compares the average load and peak load trend of the sudden section in adjacent periods, analyzes the direction and degree of difference change, compares the curve shape evolution intensity according to the difference trend amplitude data, synchronously classifies the trend category, judges whether the curve trend has mutated, and obtains the load difference mutation trend amplitude; The identified sudden jump load change section is called, the average load and peak load of the section in the same period of the adjacent two cycles are extracted, the average load values in the previous cycle and the next cycle are compared in sequence, if the average load of the next cycle is higher than that of the previous cycle and the difference between them exceeds the set difference reference value 3 units, it is determined that the average load rises significantly, the peak loads in the two cycles are compared in the same way, when the peak value of the next cycle is higher than that of the previous cycle and exceeds 5 units, it is considered that there is a peak value jump trend, the average load change direction and the peak load change direction are combined to judge, if the two directions are consistent, it means that the overall trend of load change rises, otherwise it is inconsistent; then analyze whether the difference between the two is synchronous growth, if the average value grows by 4 and the peak value grows by 6, both of which exceed the reference value and are consistent in direction, it is determined that it is a trend evolution intensity enhancement stage, otherwise if one of them grows less than the reference value, it is determined to be a weak mutation; for example, in the 15th cycle and the 16th cycle, the average load of the sudden jump section is 72 and 78 respectively, the difference is 6, the peak load is 83 and 89 respectively, the difference is 6, both of which are positive changes and higher than the reference value, the trend is classified as a synchronous enhancement type, after summarizing all cycles, each type of trend is classified according to the frequency, and the curve shape is compared to judge whether it suddenly enters the high-frequency fluctuation section from the smooth change, and whether there is a curve trend mutation behavior is judged, and the load difference mutation trend amplitude of this stage is output.

[0030] The critical response screening submodule is based on the load difference mutation trend amplitude, and uses the formula: ; Obtain the response fluctuation ratio sequence , screen the running stage in the response feature set, and obtain the running critical response section, wherein, represents the change amplitude between the average loads of the adjacent two running cycles in the i-th load section, represents the change amplitude between the peak loads of the adjacent two running cycles in the i-th load section, represents the load fluctuation density of the i-th load section, which is calculated by the frequency and continuity of the load fluctuation in the section, represents the maximum load of the i-th load section in the current running cycle, represents the average load of the i-th load section in the current running cycle, represents the actual fluctuation amplitude of the load curve of the i-th stage, which is derived from the screened stage fluctuation trend change sequence, represents the actual fluctuation amplitude of the load curve of the i-th stage, which is derived from the screened stage fluctuation trend change sequence, represents the actual fluctuation amplitude of the load curve of the i-th stage, which is derived from the screened stage fluctuation trend change sequence, represents the actual fluctuation amplitude of the load curve of the i-th stage, which is derived from the screened stage fluctuation trend change sequence, represents the actual fluctuation amplitude of the load curve of the i-th stage, which is derived from the screened stage fluctuation trend change sequence, represents the actual fluctuation amplitude of the load curve of the i-th stage, which is derived from the screened stage fluctuation trend change sequence, represents the actual fluctuation amplitude of the load curve of the i-th stage, which is derived from the screened stage fluctuation trend change sequence, represents the actual fluctuation amplitude of the load curve of the i-th stage, which is derived from the screened stage fluctuation trend change sequence, The critical reference fluctuation amplitude of the operating state of the stage, used to measure the relative fluctuation standard of the operating state approaching the sensitive point, The number of segments, The number of stages; The difference between the average load and the peak load of each load segment is calculated, squared, and then weighted by the load fluctuation intensity of the segment to calculate the fluctuation difference value of each segment, and the response fluctuation ratio is calculated by aggregating the results of all segments .

[0031] If the data of the first segment and the second segment are as follows: For the first segment, the average load change amplitude is , the peak load change amplitude is , and the load fluctuation intensity is ; For the second segment, the average load change amplitude is , the peak load change amplitude is , and the load fluctuation intensity is ; Calculate the square of the load difference of each segment: For the first segment, ; For the second segment, ; Weight the difference of each segment by the fluctuation intensity: For the first segment, ; For the second segment, ; Aggregate the weighted difference value with other items: For the first segment, , its square is ; For the second segment, , its square is also ; If the stage fluctuation amplitude and the critical reference fluctuation amplitude , the difference square is: ; Substitute the result into the formula to calculate the response fluctuation ratio : ; The response fluctuation ratio obtained is 0.814, indicating that the load fluctuation of the section is close to the critical response state. According to the result, the module can continue to screen to determine which sections enter the critical response section. The formula is to evaluate whether each load section is close to the critical response state by comprehensively considering the fluctuation difference, fluctuation intensity and response fluctuation amplitude of each load section, and then screen the critical response section.

[0032] Please refer to Figure 5 , the response deviation module includes: The response time-consuming discrimination sub-module compares the running critical response section with the health offset period in the facility monitoring record to determine the time deviation and judge whether the task response exceeds the corresponding period time structure of the normal operation of the facility, mark the tasks with response lag, and obtain the response time offset; Record the start time and completion time of each task response bound in each section, calculate the time length consumed by the task execution, obtain the response time-consuming data of the task, and extract the preset health offset period in the monitoring record in the running section. The health operation benchmark period length set in the monitoring system is called as a comparison basis, for example, for the water pump pressure regulating device, the period structure of its health operation is defined as 8-12 hours interval, if a task takes 14 hours from start to completion, it has 2 hours deviation compared with the upper limit value 12 hours, compare the response time of all tasks with the normal operation time structure of the section, if it exceeds the upper limit of the structure, record the task number and time difference, mark it as a response lag task, and record the deviation as the response time offset. Take the reservoir automatic drainage valve maintenance task as an example, it is scheduled to execute in the 7th running period, the start time is 08:00, the completion time is 23:00, the total time consumption is 15 hours, and the period operation structure of the facility is within 10 hours, which exceeds the preset upper limit of 5 hours, so it is recorded as a lag task, and the response time offset is 5 hours. Through the summary and comparison of such offset, the time deviation record table of task response is constructed.

[0033] The offset period adaptation sub-module determines whether the response offset performance of the task matches the regularity of the current running period based on the response time offset, determines the duration of the offset phenomenon in the period, identifies the period misalignment task, and screens the task group affecting the scheduling rhythm, and obtains the period misalignment task quantity. The offsets of each task are compared with the time structure of the corresponding running cycle to determine whether the offset behavior has repeated characteristics in multiple cycles. If the same task type or similar equipment type has similar offset trends in multiple cycles, the task is classified as a cycle offset matching type task. By scanning the offset length and frequency of each type of task in adjacent cycles, it is possible to identify whether there are task groups with time misalignment patterns. For example, in cycles 5, 6, and 8, the average offset of the gate opening and closing control task is more than 2 hours, and the offset direction is that the task completion time is later than the cycle end time, indicating that it has a cycle mismatch trend. Based on this, it is screened whether the task occupies the peak segment of scheduling resources. If multiple tasks are concentrated and delayed in the same period, resulting in increased resource competition, the task is identified as a scheduling rhythm conflict task. The total number of such tasks is counted. If the total number exceeds 25% of the number of tasks in the current cycle, it is recorded as a cycle mismatch task group. The task number and its cycle number are output, and the cycle mismatch task quantity is generated as an input parameter for scheduling optimization.

[0034] The conflict identification generation submodule analyzes the task's construction schedule, material response time, and historical facility records based on the periodically mismatched task volume to identify construction time conflicts and resource response overlaps, using the following formula: ; Calculate the degree of allocation conflict between tasks, identify tasks with scheduling conflicts and response imbalances, and obtain the allocation delay conflict indicator. ,in, It is the first The response time of a task refers to the time consumed from receiving the scheduling instruction to completing the response when the task is actually triggered. It is the first The offset cycle time of a task refers to the normal cycle response time structure of the segment where the task is located, as recorded in the facility monitoring system. It is the first The historical construction cycle difference associated with each task indicates the historical delays in the scheduling cycle related to that task during the historical construction process. It is the first The material response interval in a task refers to the interval between the actual response time and the planned response time of the materials required for that task during the allocation process. It is the first The historical response frequency of the facilities associated with a task reflects how frequently that facility has been invoked and responded to in past scheduling cycles. It is the first The number of past tasks associated with a task refers to the total number of tasks that the facility has been assigned to participate in during the recorded period. Total number of tasks; If the response time of task 1 is 10 minutes, the offset period is 8 minutes, the historical construction period difference is 5 minutes, the material response interval is 2 minutes, the historical response frequency is 3 times, and the historical task quantity is 20 times. According to the parameters, there will be a certain scheduling conflict for the task, because the response time deviation is large, and the historical construction period difference and the material response interval are also long, which will affect the subsequent task allocation. By using the formula to calculate the allocation conflict degree, the conflict situation of the task can be further clarified. If only one task (i.e. ), the parameter values are: (The response time: the actual response time of task 1 is 10 minutes); (The offset period time: the normal offset period time in the monitoring system of task 1 is 8 minutes); (The historical construction period difference: the historical construction period delay related to task 1 is 5 minutes); (The material response interval: the interval between the actual response time and the planned time of the material required by task 1 is 2 minutes); (The historical response frequency: the historical response frequency of the facility associated with task 1 is 3 times); (The historical task quantity: the total number of tasks in which the facility associated with task 1 participates in the historical tasks is 20); Substitute the parameters into the formula to calculate: ; Calculate: ; The result is: ; The calculation result is 4.6, which indicates that there is a certain gap between the response time and the offset period of task 1, and the historical construction period and the material response time are long, resulting in an increase in the allocation delay conflict identification quantity, which further affects the scheduling and resource allocation of the task. Therefore, it is necessary to further optimize the allocation strategy to ensure the smooth execution of subsequent tasks. This formula is used to calculate the degree of task allocation conflict. By calculating the difference between the actual response time and the predetermined offset period time of each task, it is evaluated whether the task exceeds the normal time range, and then the historical construction delay and the time difference of the material response are combined to evaluate the impact on the completion of the task. Then consider the historical response frequency and the number of tasks of the facility to adjust the conflict calculation to reflect the impact of facility load on allocation. Finally, by comprehensively considering the parameters and combining the weight coefficient, the degree of allocation conflict between tasks is calculated.

[0035] Please refer to Figure 6The task sequencing module comprises: The score conversion submodule analyzes the conflict between the scheduling response delay and the tasks based on the deployment delay conflict identification quantity, determines the interference degree of the tasks on the scheduling plan according to the time difference and the conflict frequency of the tasks in the operation process, determines the influence degree between the tasks, adjusts the score range occupied by the tasks to a unified interval, and generates delay conflict score data; The scheduling response delay time length of each task and the time overlap between the associated tasks are extracted one by one, the delay time is counted in hours in the task record, and the frequency of the task coinciding with other tasks in the same time period in the entire scheduling window is counted. It is judged whether the task interferes with the start of other tasks at multiple time nodes. If a task coincides with the response time of other tasks in three independent time periods, and the scheduling delay of the task itself exceeds 2 hours, it is determined that the scheduling conflict intensity of the task is high. The task is marked as an interference task, and a conflict interference degree index is constructed according to the conflict frequency and the delay time. The conflict intensity data of each task is uniformly normalized, all interference indexes are linearly compressed to the interval of 0 to 100, the task with the most serious interference gets a score of 100, the task with the lightest interference gets a score of 0, and the scores of the remaining tasks are calculated according to the linear proportion. For example, task A delays for 3 hours and overlaps with 5 tasks, and task B delays for 1 hour and overlaps with only 1 task. The score of task A is much higher than that of task B. Then, the scores of all tasks are indexed by task number to generate a score list. The score value is the delay conflict score data, which reflects the interference level and scheduling difficulty of the task in the current scheduling.

[0036] The priority sorting submodule calls the delay conflict score data, compares it with the current availability of resources and the configuration conditions required by the tasks, calculates the adaptation degree between the tasks and the resources, and sorts the tasks one by one to obtain the maintenance scheduling priority classification result. After obtaining the delay conflict score data, the score value of each task is called in turn, and the available resources recorded in the current system are compared with the required resource configuration conditions of the task to extract the three elements of equipment, manpower and materials required by each task. The number of idle resources in the scheduling system is matched item by item, and the satisfaction degree of each type of resource is calculated. For example, task C requires two professional hydraulic equipment maintenance personnel, one hydraulic lifting device and 10 standard sealing ring spare parts, while the corresponding resources in the current system can provide 2 people, 2 devices and 20 spare parts. The resource adaptation degree of task C is 100%, and if task D can only satisfy half of the required personnel, its adaptation degree is only 50%. The scheduling adaptation level of each task is calculated by combining the resource adaptation degree and the conflict score, and the higher the score and the lower the resource adaptation degree, the lower the scheduling priority. The tasks are arranged in order from high to low according to the comprehensive scheduling adaptation level, and a task ordering list is generated. For example, task E has a score of 85 and a resource adaptation degree of 100%, and the comprehensive order is higher than that of task F, which has a score of 60 and a resource adaptation degree of 70%. The final output is the priority level corresponding to each task number, and the maintenance scheduling priority classification result is formed from high to low.

[0037] The above is only a preferred embodiment of the present application, and does not limit the form of the present application. Any skilled person in the art can use the disclosed technical content to make changes or modifications to equivalent embodiments applied to other fields, but any simple modification, equivalent change and modification made according to the technical essence of the present application to the above embodiments without departing from the technical solution content of the present application still belongs to the protection scope of the present application.

Claims

1. A system for assessing and repairing damage to water conservancy facilities, characterized in that, The system includes: The operating condition fluctuation identification module is based on key components of water conservancy facilities. It analyzes the changing trends of pressure, strain and flow velocity monitoring data, determines whether they continue to increase in the same direction in multiple cycles, compares the synchronicity and changing direction of current data with previous data, filters the increasing trend cycle, identifies the structural operation fluctuation state, and obtains the cycle linkage enhancement stage. Based on the aforementioned periodic linkage enhancement stage, the mutation identification module determines whether abrupt changes occur in the monitoring parameter curve, compares the time correspondence between strain and pressure mutation points, calculates the offset rate difference by combining structural component response data, identifies potential linkage anomalies, and obtains the evolution severity level. Based on the level of evolution severity, the load determination module analyzes the changes in the load curve, compares the difference between the average load and the peak load in adjacent periods, determines whether the load curve is close to the critical state, filters the load stage with sudden jump characteristics, and obtains the critical response section of operation. The response deviation module compares the task response time with the health offset range based on the critical response segment of operation, determines whether the response time matches, and identifies the scheduling time offset task by combining historical scheduling records and resource response status, and obtains the allocation delay conflict identifier.

2. The water conservancy facility damage assessment and repair system according to claim 1, characterized in that, The periodic linkage enhancement phase includes trend joint growth segments, monitoring data synchronization segments, and structural response initial change intervals. The evolution intensity levels include linkage mutation levels, offset synchronization levels, and curve jump levels. The operational critical response segments include load transition boundary segments, operational amplitude change segments, and equipment load integration segments. The allocation delay conflict identification quantity includes task response lag markers, facility status offset levels, and scheduling matching error parameters.

3. The water conservancy facility damage assessment and repair system according to claim 1, characterized in that, The operating condition fluctuation identification module includes: The cycle trend extraction submodule is based on key components of water conservancy facilities. It analyzes the pressure, strain and flow velocity change trends of key components during the operating cycle, determines whether they all show an upward trend in continuous cycles, filters out data cycles with inconsistent change directions, and obtains a trend growth cycle sequence. The data change filtering submodule compares the data change directions of two consecutive cycles in the trend growth cycle sequence, filters the cycles with consistent change directions, and determines whether there are positive changes in pressure, strain and flow rate at the same time. It excludes cycles with mixed offset trends and obtains a set of synchronously increasing cycles. The structure attribution determination submodule determines the continuous cycle combination based on the synchronous incremental cycle set, analyzes the consistency of the growth of monitoring data within the continuous cycle, identifies cycle combinations with stable linkage growth, and obtains the cycle linkage enhancement stage.

4. The water conservancy facility damage assessment and repair system according to claim 1, characterized in that, The mutation identification module includes: The inflection detection submodule, based on the aforementioned periodic linkage enhancement stage, analyzes the slope changes of the strain curve and pressure curve within the period, determines whether there is a direction reversal or abrupt change in the same period, identifies the temporal position of the transformation point for corresponding mapping, compares the mapping integrity, and obtains the periodic inflection correspondence ratio. The time correspondence comparison submodule calls the cycle inflection correspondence ratio, compares the sequence deviation between strain change time and pressure change time, filters cycle segments with time differences within the range, and counts their coverage in the whole cycle to obtain the time synchronization distribution ratio. The rate difference calculation submodule calculates the displacement change rate of the structural response point in the inflection period based on the time synchronization distribution ratio, judges the degree of response difference between the arch back plate and the pressure node in the same period, analyzes whether there is a periodic divergence in their change amplitude, calculates the periodic structural response difference amplitude, and obtains the evolution intensity level by combining the time synchronization distribution ratio.

5. The water conservancy facility damage assessment and repair system according to claim 1, characterized in that, The load determination module includes: The load segment extraction submodule analyzes the load curve shape in the operation cycle of water conservancy facilities and equipment based on the aforementioned evolution intensity level, identifies segments where curve fluctuations are concentrated, calculates the load change frequency and continuous time span of the segment, judges the continuous change state, and screens the key stages where fluctuation states occur in a concentrated manner to obtain the sudden load change segment. The load difference judgment submodule calls the sudden load change segment, compares the average load and peak load trend of the sudden segment in adjacent cycles, analyzes the direction and degree of its difference change, compares the curve shape evolution intensity based on the difference trend amplitude data, and simultaneously sorts the trend category to determine whether the curve trend has changed abruptly, and obtains the load difference change trend amplitude. The critical response screening submodule calculates the response fluctuation ratio sequence based on the magnitude of the load difference abrupt change trend, and filters the operating stages in the response feature set to obtain the critical response segment.

6. The water conservancy facility damage assessment and repair system according to claim 1, characterized in that, The response deviation module includes: The response time determination submodule compares the critical response segment with the health offset cycle in the facility monitoring record to determine the time deviation and whether the task response exceeds the cycle time structure corresponding to the normal operation of the facility. It then marks the task with response lag and obtains the response time offset. The offset cycle adaptation submodule determines whether the response offset of the task matches the current running cycle based on the response time offset, determines the duration of the offset phenomenon within the cycle, identifies the cycle misaligned tasks, filters the task group that affects the scheduling rhythm, and obtains the number of cycle misaligned tasks. The conflict identifier generation submodule analyzes the construction schedule, material response time and historical facility records of the tasks based on the periodic mismatch task volume, identifies the construction time conflict and resource response overlap, calculates the degree of allocation conflict between tasks, judges the tasks with arrangement conflict and response imbalance, and obtains the allocation delay conflict identifier quantity.

7. The water conservancy facility damage assessment and repair system according to claim 1, characterized in that, The system also includes: The task sorting module converts the allocation delay conflict identifier into score data of the same scale, compares the resource matching relationship of tasks within the current scheduling range, and arranges the task order according to the score to obtain the maintenance scheduling priority classification result. The maintenance scheduling priority classification results include task priority level labels, resource matching scores, and risk linkage scoring parameters.

8. The water conservancy facility damage assessment and repair system according to claim 7, characterized in that, The task sorting module includes: The scoring conversion submodule analyzes the scheduling response delay and the conflict between tasks based on the scheduling delay conflict identifier. According to the time difference of tasks in the operation process and their conflict frequency, it judges the degree of interference to the scheduling plan, determines the degree of influence between tasks, adjusts the scoring range of each task to a unified range, and generates delay conflict scoring data. The priority ranking submodule calls the latency conflict score data, compares it with the current availability of resources and the configuration conditions required by the task, calculates the compatibility between the task and the resource, and ranks the tasks one by one to obtain the maintenance scheduling priority ranking result.

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