Sluice safe operation system based on state predictive maintenance

Abstract

The invention relates to the technical field of safety monitoring, in particular to a state predictive maintenance-based sluice safety operation system, which comprises a hydrological impact monitoring module, a gate attitude tracking module, an opening and closing energy consumption monitoring module, a structural rigidity evolution monitoring module and a maintenance trigger monitoring module. According to the method, the evolution characteristics of the water flow impact state are identified by constructing a direction difference value change sequence, the displacement direction included angle change is linked to analyze the door body posture deviation trend, and the abnormal signal of the opening and closing driving system is judged by combining the unit displacement energy consumption and the data consistency in the speed stable interval; and further extracting residual deformation vector direction change characteristics in a loading stage, continuously identifying a structural rigidity evolution form, and finally performing time sequence recombination and mark pushing on various types of abnormal data of associated numbers, thereby realizing active identification and multi-dimensional linkage early warning of operation abnormity, enhancing the perception capability of the system to a complex state evolution process, and improving the reliability of the system. And the timeliness of abnormity discovery and the identification precision of the structure risk are improved.

Description

Technical Field

[0001] This invention relates to the field of safety monitoring technology, and in particular to a sluice gate safety operation system based on condition-based predictive maintenance. Background Technology

[0002] The field of safety monitoring technology involves the continuous observation, analysis, and response to the status of specific areas, equipment, or systems. Its core aspects include real-time data acquisition, abnormal behavior identification, fault early warning mechanisms, and response strategy formulation. It is widely used in public safety, industrial operations, and infrastructure maintenance. This field relies on sensor data acquisition, supplemented by data processing and transmission methods, to achieve effective control over operational status, aiming to prevent safety risks, ensure normal equipment operation, and improve overall management efficiency. Traditional sluice gate safety operation systems refer to systems that monitor and manage the operational status of sluice gate structures in water conservancy projects. They typically employ on-site manual inspections, water level gauges, and displacement sensors for data acquisition. Logical judgment rules are used to analyze the gate's opening and closing status, stress conditions, and equipment wear to formulate maintenance plans and emergency response schemes. These systems primarily rely on periodic inspections and static data thresholds for maintenance decisions, making it difficult to accurately predict future changes in the status of key sluice gate components, resulting in low maintenance efficiency and delayed response times.

[0003] The existing sluice gate operation system relies on timed inspections and static monitoring data to judge the operational status. It can only identify obvious anomalies through preset thresholds and lacks a processing mechanism for the inherent correlation between multi-source data. It cannot capture the real-time dynamic changes between water flow impact and structural response. Faced with gate offset and structural stress deformation under complex coupling factors, it is difficult to identify the correlation and predict the trend. As a result, some potential faults are masked in seemingly normal data fluctuations. It fails to effectively identify energy consumption mutations and structural stiffness evolution in the drive system, resulting in a lag in the abnormal response mechanism, inaccurate judgment of maintenance timing, and increased operation and maintenance risks and management burden. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a sluice gate safe operation system based on condition-predictive maintenance. On one hand, a sluice gate safe operation system based on condition-predictive maintenance is provided, the system comprising:

[0005] The hydrological impact monitoring module acquires the impact direction and dynamic pressure changes of upstream and downstream water flow, and calculates the directional difference and extracts the change curve by combining the direction of the water-facing surface of the gate and the contact surface of the gate slot, thus generating abnormal water flow impact signals.

[0006] Based on the abnormal water flow impact signal, the gate attitude tracking module calls the gate's horizontal and vertical displacement records, calculates the angle between the synthetic displacement direction and the stationary reference direction, filters out consecutive offset numbers in the same direction, and generates a gate attitude offset signal.

[0007] The opening and closing energy consumption monitoring module extracts the opening and closing path energy consumption and speed data based on the gate posture offset signal, analyzes the unit displacement energy consumption and speed stability in segments, identifies energy consumption jump intervals in the speed stable area, and generates an abnormal opening and closing drive signal.

[0008] Based on the opening and closing drive anomaly signal, the structural stiffness evolution monitoring module extracts the structural deformation trajectory, calculates the direction of the residual deformation vector during the continuous loading stage, analyzes the consistency of change, determines whether there is continuous offset, and generates a structural stiffness early warning signal.

[0009] The maintenance trigger monitoring module integrates records such as water flow impact, gate offset, and energy consumption jumps based on the structural stiffness early warning signal, sorts them by time and marks their sources, and generates core instructions for the safe operation of the sluice gate.

[0010] As a further embodiment of the present invention, the abnormal water flow impact signal includes the critical interval of the impact direction difference, the sequence of structural pressure direction turning points, and abnormal fluctuation characteristic parameters; the gate attitude deviation signal includes the displacement synthesis direction angle sequence, the continuous offset azimuth of the included angle, and the duration of attitude deviation; the abnormal opening and closing drive signal includes the sudden change value of energy consumption per unit displacement, the identification number of the velocity stability zone, and the deviation degree of energy consumption and velocity change; the structural stiffness early warning signal includes the staged residual deformation direction, the continuous loading offset trend, and the structural stiffness change level; and the core instruction for safe operation of the sluice gate includes the abnormality type label, the associated structure number, and the time sequence integration information.

[0011] As a further aspect of the present invention, the continuous offset unidirectional number refers to the numbering sequence in which the gate body's attitude offsets in the same direction over a continuous period of time, indicating a continuous and consistent attitude offset trend.

[0012] As a further aspect of the present invention, the identification of energy consumption jump intervals in the speed stable region refers to the time interval during which energy consumption per unit displacement suddenly changes in the section where the speed remains stable during the opening and closing process.

[0013] As a further aspect of the present invention, the hydrological impact monitoring module includes:

[0014] The directional data acquisition submodule acquires records of the impact direction and dynamic pressure changes of upstream and downstream water flow, calls up the data of the direction of the gate's water-facing surface and the direction of the gate slot contact surface, calculates the directional difference according to the impact direction and pressure direction in the time series, and generates a directional difference sequence value.

[0015] The difference sequence construction submodule, based on the directional difference sequence value, establishes trend marker records according to the changing trend of adjacent differences, extracts continuous changing segments to form a trend change trajectory, and generates a directional difference trend trajectory.

[0016] The turning section identification submodule calls the direction difference trend trajectory, compares the trend marker direction change, identifies the time period number of continuous reversal, filters the sequence position that meets the conditions, and generates water flow impact abnormal signal identifier.

[0017] As a further aspect of the present invention, the door posture tracking module includes:

[0018] The attitude data retrieval submodule retrieves the lateral and longitudinal displacement records of the gate within the corresponding time period based on the time period number identified by the water flow impact anomaly signal. It extracts the lateral and longitudinal displacement components at the time point and calculates the synthetic displacement direction angle at each time point through the displacement components to obtain the synthetic direction angle sequence of the gate.

[0019] The included angle offset calculation submodule calls the gate body synthetic direction angle sequence, calculates the included angle value at the time point based on the gate body static reference direction angle, extracts the set of numbers whose offset angle is greater than the set offset threshold from the included angle value sequence, and obtains the included angle offset orientation sequence.

[0020] The continuous offset filtering submodule counts the time periods that continuously offset to the same position in the sequence based on the included angle offset azimuth sequence, filters the numbered segments with the same offset direction and the duration that meets the minimum duration condition, and generates the gate attitude offset signal.

[0021] As a further aspect of the present invention, the start-up and shutdown energy consumption monitoring module includes:

[0022] The energy consumption data extraction submodule, based on the gate number contained in the gate posture offset signal, calls the energy consumption data and displacement record of the corresponding gate opening and closing path, divides the opening and closing path into equidistant segments, extracts the energy consumption value per unit displacement of the segment, calculates the increase or decrease in energy consumption per unit displacement between consecutive segments, and generates a sequence of segment energy consumption change values.

[0023] Based on the gate attitude offset signal, the speed stability identification submodule calculates the speed change rate in each equidistant path segment, marks the segment with a speed change rate lower than the speed fluctuation benchmark value as a stable segment, and obtains a set of speed stable segment numbers.

[0024] The drive anomaly identification submodule filters the positions in the stable section where the energy consumption change value sequence exceeds the set energy consumption jump benchmark value based on the energy consumption change value sequence of the section and the set of speed stable section numbers. It then extracts the section numbers that meet the jump conditions as abnormal segment numbers and generates a start / stop drive anomaly signal.

[0025] As a further aspect of the present invention, the structural stiffness evolution monitoring module includes:

[0026] The loading segment extraction submodule, based on the interval number marked by the start-stop drive abnormal signal, calls the loading stage data corresponding to the number in the structural loading record, extracts the sequentially arranged continuous loading stages in each numbered segment, synchronously organizes the structural deformation trajectory in the stage, and generates a continuous loading stage trajectory sequence.

[0027] The residual vector calculation submodule calls the trajectory sequence of the continuous loading stage, extracts the end deformation position and the start position from each loading stage to construct the residual deformation vector, performs direction normalization processing on the vectors within the stage, calculates the vector angle value sequence between adjacent stages, and obtains the residual deformation vector angle value group.

[0028] The offset morphology discrimination submodule determines whether the vector angle between the three stages is continuously less than the set angle consistency threshold based on the residual deformation vector angle value group, filters out the structure numbers that meet the continuous direction consistency condition, marks the number as being in a continuous offset state, and generates a structural stiffness warning signal.

[0029] As a further aspect of the present invention, the maintenance trigger monitoring module includes:

[0030] The abnormal data integration submodule, based on the structure number in the structural stiffness warning signal, calls the water flow impact record, door offset direction record and drive energy consumption jump section number under the same structure number, classifies the data according to the number correspondence rule, extracts the key time tags in the record and unifies the time format, and generates a structural abnormal record dataset.

[0031] The time series indexing module calls the structural anomaly record dataset, constructs an ordered time series linked list according to the time labels in the records, marks the source field for each data item and establishes a time node index, locates overlapping and continuous anomaly segments in the sequence, and generates a multi-source anomaly time series index table.

[0032] The instruction generation and push submodule integrates multiple types of abnormal event numbers within the same time period under the same structure number according to the multi-source abnormal time series index table, constructs a corresponding mapping structure between structure number and abnormal type, encapsulates and outputs it to the scheduling terminal according to a unified data format, and generates the core instruction for safe operation of the sluice gate.

[0033] As a further aspect of the present invention, the location record overlap and continuous abnormal segment refers to the segment in which the time overlap of differential source records and the occurrence of abnormal events are identified in the multi-source abnormal time series, and the potential risk concentration period is marked.

[0034] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0035] By constructing a sequence of directional difference changes to identify the evolution characteristics of water flow impact state, analyzing the trend of gate attitude deviation by linking the changes in the included angle of displacement direction, judging abnormal signals of the opening and closing drive system by combining the energy consumption per unit displacement and the data consistency within the stable velocity range, further extracting the directional change characteristics of residual deformation vector during the loading stage, continuously identifying the evolution mode of structural stiffness, and finally performing time series recombination and labeling of multiple types of abnormal data with associated numbers, the system can achieve proactive identification of operational anomalies and multi-dimensional linkage early warning, enhance the system's ability to perceive complex state evolution processes, and improve the timeliness of anomaly detection and the accuracy of structural risk identification. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a schematic diagram of the system of the present invention;

[0038] Figure 2 This is a flowchart of the hydrological impact monitoring module in this invention;

[0039] Figure 3 This is a flowchart of the door posture tracking module in this invention;

[0040] Figure 4 This is a flowchart of the energy consumption monitoring module for starting and stopping in this invention;

[0041] Figure 5 This is a flowchart of the structural stiffness evolution monitoring module of the present invention;

[0042] Figure 6 This is a flowchart of the maintenance trigger monitoring module in this invention. Detailed Implementation

[0043] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0044] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0045] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent.

[0046] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0047] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0048] This invention provides a sluice gate safe operation system based on condition-predictive maintenance, such as... Figure 1 The diagram shown illustrates a sluice gate safety operation system based on condition-based predictive maintenance. This system includes:

[0049] The hydrological impact monitoring module acquires records of water flow impact direction and dynamic pressure changes in upstream and downstream areas, calls data on the direction of the gate's water-facing surface and the direction of the gate slot contact surface, performs time-by-time direction difference calculation on the water flow impact direction and the structural pressure direction, extracts the change curve based on the change trend of the direction difference, determines the time period number with continuous turning indicators in the change curve, and generates an abnormal water flow impact signal.

[0050] The gate attitude tracking module uses the time period number identified by the abnormal water flow impact signal to call the lateral and longitudinal displacement records of the gate within the time period, calculates the angle between the synthetic displacement direction and the stationary reference direction of the gate at each time point, filters the numbers of continuous angle shifts in the same direction, identifies the consistency between the shift duration and direction, and generates the gate attitude shift signal.

[0051] The opening and closing energy consumption monitoring module uses the gate number contained in the gate attitude offset signal to call the energy consumption data and displacement speed data on the opening and closing path, extracts the unit displacement energy consumption change value and speed stability indicator in the path interval in segments, compares the consistency of energy consumption and speed change, and determines the interval number where energy consumption jumps in the speed stable area, and generates an opening and closing drive abnormal signal.

[0052] The structural stiffness evolution monitoring module uses the interval number marked by the start-stop drive anomaly signal to call the deformation record trajectory of the corresponding segment in the structural loading record, calculates the residual deformation vector direction of the three consecutive loading stages, compares the consistency of the vector direction change in the stages, determines whether the structural number is in a continuous offset state, and generates a structural stiffness early warning signal.

[0053] The maintenance trigger monitoring module, based on the structural number in the structural stiffness early warning signal, calls the water flow impact record, gate offset direction record and drive energy consumption jump section number under the same number, integrates the three record sequences and marks the source number and sequence time order, pushes the abnormal type merging event to the dispatch terminal, and generates the core instruction for safe operation of the sluice gate.

[0054] The abnormal signals of water flow impact include the critical interval of impact direction difference, the sequence of structural pressure direction turning points, and abnormal fluctuation characteristic parameters. The gate attitude deviation signals include the displacement synthesis direction angle sequence, the continuous offset azimuth of the included angle, and the duration of attitude deviation. The abnormal signals of opening and closing drive include the sudden change value of energy consumption per unit displacement, the identification number of the velocity stability zone, and the deviation degree of energy consumption and velocity change. The structural stiffness early warning signals include the staged residual deformation direction, the continuous loading offset trend, and the structural stiffness change level. The core instructions for safe operation of the sluice gate include the abnormality type label, the associated structure number, and the time sequence integration information.

[0055] Specifically, such as Figure 2 As shown, the hydrological impact monitoring module includes:

[0056] The directional data acquisition submodule acquires records of the impact direction and dynamic pressure changes of upstream and downstream water flow, calls up the data of the direction of the gate's water-facing surface and the direction of the gate slot contact surface, calculates the directional difference according to the impact direction and pressure direction in the time series, and generates a directional difference sequence value.

[0057] First, several sets of direction recognition sensors and pressure sensing devices need to be installed on the upstream and downstream sides of the hydraulic structure. The direction recognition sensors are used to collect the impact direction; direction sensing components with three-axis sensing capabilities can be deployed. The pressure sensing devices are used to sense the instantaneous change in the impact force per unit area of ​​the water on the structural surface. All sensors are connected to the data acquisition system through a unified data interface. A unified time synchronization benchmark is set in the system, and a minimum sampling time interval, such as 0.1 seconds, is set as the time sequence division unit. The sampling data from all sensors is timestamped. The data for the upstream direction of the gate and the contact surface of the gate slot need to be pre-entered from the three-dimensional data of the gate model obtained during the structural design phase. The normal directions of each region on the water-facing surface and the normal direction of the gate slot contact area are extracted from the model and spatially bound to the sensor deployment location. The water flow impact direction at each moment is recorded. By finding the correspondence between the water flow direction and the normal direction of the structural surface at the corresponding timestamp, a set of one-to-one matching data pairs is formed. For each set of matching data, the deviation relationship between the impact direction and the pressure direction in space is identified, and the angle deviation value of each set is extracted as the basic building block of the direction difference sequence. Each set of direction difference consists of the angle difference between the upstream and downstream impact directions and the corresponding pressure surface direction of the structural surface. The collected data is continuously recorded and organized in chronological order to form a direction difference sequence value covering the entire sampling period.

[0058] The difference sequence construction submodule establishes trend marker records based on the directional difference sequence values, according to the changing trend of adjacent differences, extracts continuous changing segments to form a trend change trajectory, and generates a directional difference trend trajectory.

[0059] First, the acquired directional differences are expanded into a time series, and the changes in the difference between adjacent points are read point by point. By judging the increase or decrease relationship between the previous and subsequent values, the trend of the difference change is marked. If the subsequent value is greater than the previous value, it is marked as rising; otherwise, it is marked as falling; if they are equal, it is marked as stable. After the above processing, the entire difference sequence forms a trend mark sequence. This trend mark record includes not only the direction of the trend itself, but also the time range of the trend and the corresponding start and end position indices. Then, the trend mark sequence is scanned, and the parts that continuously show the same trend direction are extracted as a trend segment record, and its start is marked. By combining the end time index with the trend segments in chronological order, a complete trend change trajectory is obtained. This trajectory can be represented as an ordered sequence of multiple trend segments. Each trend segment records its trend type, duration of change, range of direction values, and number of change points. If a set of differences gradually increases, it will be reflected as a continuous upward segment in the trend trajectory. If a downward segment is interspersed, it will be divided into two different trend segments. The trend trajectory constructed in this way can clearly reflect the dynamic change process of the entire direction difference over time, providing input data support for subsequent reversal trend identification and abnormal signal judgment.

[0060] The turning section identification submodule calls the direction difference trend trajectory, compares the trend marker direction change, identifies the time period number of continuous reversal, filters the sequence position that meets the conditions, and generates water flow impact abnormal signal identifier.

[0061] Each trend segment in the trend trajectory needs to be compared pairwise in sequence to determine whether the direction of change of the current trend segment is opposite to the direction of change of the next trend segment immediately following it. That is, determine whether one trend is rising and the next is falling, or the current trend is falling and the next is rising. If this reversal condition is met, it is temporarily recorded as a possible turning segment. Further, the duration of the two trend segments in the segment is calculated separately, and the time span of each trend segment is compared with the preset minimum effective time threshold. If the duration of any trend segment is less than the threshold, the segment is identified as a non-significant change and the turning mark is not adopted. Only the case that satisfies the reversal direction and the time of both trend segments is greater than or equal to the minimum threshold is retained. The retained effective reversal segments are numbered, and the start time of the starting trend segment and the end time of the ending trend segment of the reversal segment are extracted as the start and end range of the abnormal signal identification, forming the final result of the water flow impact abnormal signal identification. This result can be output by recording the abnormal identification number, the corresponding time segment position index, the direction of change and the statistical parameters of the corresponding difference interval, etc., to complete the identification and marking of abnormal segments.

[0062] Specifically, such as Figure 3 As shown, the door attitude tracking module includes:

[0063] The attitude data retrieval submodule retrieves the lateral and longitudinal displacement records of the gate within the corresponding time period based on the time period number identified by the abnormal water flow impact signal. It extracts the lateral and longitudinal displacement components at the time point and calculates the synthetic displacement direction angle at each time point through the displacement components to obtain the synthetic direction angle sequence of the gate.

[0064] Based on the start and end times of the abnormal signals, lateral and longitudinal displacement data for the corresponding time periods need to be extracted from the door motion monitoring system. The extracted lateral displacement data represents the horizontal displacement change of the door relative to its initial position, and the longitudinal displacement data represents the vertical displacement change of the door. Both sets of data are timestamped and paired according to chronological order to ensure that each sampling time point corresponds to a lateral and longitudinal displacement value. Subsequently, a direction combination calculation is performed on each pair of displacement components to identify the composite direction of the door's motion trajectory at that time point, where the lateral direction is represented by the x-axis and the longitudinal direction by the x-axis. The y-axis, the combined direction, is determined by the angle value calculated from the positive direction of the structural coordinate axis. This angle represents the current composite motion direction of the door. By traversing all time points within the entire time period, all composite direction angles are extracted and recorded sequentially to form a complete sequence of composite direction angles of the door. For example, if the sampling frequency is 10 times per second for 5 seconds within a certain time period, 50 sets of horizontal and vertical displacement data should be extracted, and 50 composite direction angle values ​​should be generated sequentially. Each angle value is recorded under the corresponding time point number to form a complete temporal direction change sequence, and finally, the sequence of composite direction angles of the door is obtained.

[0065] The included angle offset calculation submodule calls the gate body synthetic direction angle sequence, calculates the included angle value at the time point based on the gate body static reference direction angle, extracts the set of numbers whose offset angle is greater than the set offset threshold from the included angle value sequence, and obtains the included angle offset orientation sequence.

[0066] First, a reference direction angle is set when the door is stationary. This angle value can be given in the initial engineering settings, such as 0 degrees when the door has no vertical offset. Then, the difference between each angle value in the generated composite direction angle sequence of the door and the reference direction angle is calculated to obtain the included angle value at each time point. This included angle value represents the degree of offset of the door from the ideal stationary direction at that time point. All included angle values ​​are arranged in chronological order to form an included angle value sequence. Next, the subsequence is analyzed point by point to extract the numbered points where the included angle value is greater than the pre-set offset threshold. The offset threshold value is... The offset threshold is set based on the allowable range of actual engineering errors, generally between 5 and 15 degrees. If the offset threshold is set to 10 degrees, then when the included angle value at any time point is greater than 10 degrees, the number is regarded as an offset anomaly and included in the offset number set. For example, if the direction angle at the 20th time point is 13 degrees, and the included angle between the 20th time point and the reference direction of 0 degrees is 13 degrees, which exceeds the offset threshold of 10 degrees, then the number 20 of this point is included in the offset sequence. This process is repeated until all time points have been judged, and finally the included angle offset azimuth sequence is obtained. This sequence contains all time point numbers and offset angles that exceed the offset threshold.

[0067] The continuous offset filtering submodule counts the time period numbers of consecutive offsets to the same direction in the sequence based on the included angle offset azimuth sequence, filters the numbered segments with the same offset direction and the duration meeting the minimum duration condition, and generates the door attitude offset signal.

[0068] First, all points exceeding the threshold in the azimuth offset sequence are scanned sequentially by time. The angle values ​​are then divided into quadrants according to the offset direction: 0 to 90 degrees is considered east-northeast, 90 to 180 degrees is east-southeast, 180 to 270 degrees is west-southwest, and 270 to 360 degrees is west-northwest. For each consecutive offset point sequence, it is determined whether they remain within the same quadrant of the offset direction. If the directions corresponding to consecutive points are all within the same quadrant, it is determined to be a segment with consistent offset directions. Next, the time span of this consecutive segment is calculated, which is the number of sampling intervals between the start and end time numbers of the segment multiplied by the sampling time interval. The actual offset duration is obtained by comparing it with the preset minimum duration condition. If the duration is not less than the minimum duration threshold, the segment is considered a valid continuous offset segment. The minimum duration condition can be set according to the structural response characteristics. For example, if it is set to 2.5 seconds and the sampling interval is 0.1 seconds, the segment must contain at least 25 consecutive time number points to meet the filtering condition. For example, if the points numbered 10 to 40 in the offset orientation sequence are consecutive points with the same offset direction, and there are 31 sampling points in a continuous period, the corresponding time is 3.1 seconds, which exceeds the minimum duration threshold of 2.5 seconds. This segment will be filtered and retained. Finally, all the offset segments that meet the requirements are recorded as the gate attitude offset signal.

[0069] Specifically, such as Figure 4 As shown, the energy consumption monitoring module includes:

[0070] The energy consumption data extraction submodule is based on the gate number contained in the gate attitude offset signal. It calls the energy consumption data and displacement record of the opening and closing path of the corresponding gate, divides the opening and closing path into equidistant segments, extracts the energy consumption value per unit displacement of the segment, calculates the increase or decrease in energy consumption per unit displacement between consecutive segments, and generates a sequence of segment energy consumption change values.

[0071] First, based on the identified door number, the system database retrieves the energy consumption and displacement records associated with the door's opening and closing operation. The energy consumption records are organized chronologically, and the displacement records are processed synchronously to ensure a one-to-one correspondence between energy consumption values ​​and displacement points. After data extraction, the door's opening and closing path needs to be divided using an equidistant principle. This involves dividing the total displacement length of the opening and closing path by a preset segment value. For example, if the total displacement of 1000mm is divided into 20 segments, each segment is 50mm. The cumulative energy consumption value corresponding to each equidistant point is then retrieved from the displacement records based on this distance. The energy consumption difference between two adjacent equidistant points is taken as the unit displacement energy consumption value for that segment. Subsequently... All equidistant segments are continuously compared, and the increase or decrease in energy consumption per unit displacement of the current segment is calculated compared to that of the previous segment. This change represents the degree of energy consumption change of the current segment relative to the previous segment. For example, if the energy consumption per unit displacement of a segment is 0.25 kJ / mm and the previous segment is 0.20 kJ / mm, then the energy consumption change of this segment is +0.05 kJ / mm. If it is 0.18 kJ / mm, then it is -0.02 kJ / mm. After traversing all segments in this way, a complete sequence of segment energy consumption change values ​​is formed. Each element in the sequence corresponds to the energy consumption change result of an equidistant segment. This sequence is used to reflect the staged changes in energy load during the opening and closing of the door.

[0072] Based on the gate attitude offset signal, the speed stability identification submodule calculates the speed change rate in each equidistant path segment, marks the segment with a speed change rate lower than the speed fluctuation benchmark value as a stable segment, and obtains a set of speed stable segment numbers.

[0073] First, within the equidistant segments of the opening and closing path, the corresponding time interval and displacement difference for each segment are read. The average velocity value for each segment is obtained by dividing the displacement difference by the corresponding time interval. Then, the average velocity values ​​of adjacent segments are compared to calculate the velocity change rate between adjacent segments. The velocity change rate is expressed as the ratio of the difference between the velocity of the later segment and the velocity of the earlier segment to the velocity of the earlier segment. For example, if the velocity of one segment is 12 mm / s and the previous segment was 10 mm / s, then the velocity change rate is 0.2. This velocity change rate is then compared with a preset velocity fluctuation benchmark value. The speed fluctuation benchmark value is determined by the operating characteristics of the structural equipment. For example, it is set to 0.15, which means that the speed change rate within ±0.15 is considered a speed stable section. If the change rate is 0.12 or −0.08, the condition is met. If it is 0.2 or −0.3, the condition is not met. The section that meets the condition is marked as a stable section. The numbers of all sections that meet the condition of speed change rate below the benchmark value are summarized to form a set of speed stable section numbers. This set is used to identify the stage intervals in which the speed performance of the equipment is relatively consistent during operation, and to provide a screening range for subsequent judgment of sudden changes in drive energy consumption.

[0074] The drive anomaly identification submodule filters the positions in the stable section where the energy consumption change exceeds the set energy consumption jump benchmark value based on the sequence of energy consumption change values ​​in the section and the set of stable section numbers. It then extracts the section numbers that meet the jump conditions as abnormal section numbers and generates start / stop drive anomaly signals.

[0075] First, the energy consumption change value corresponding to each stable segment number is compared item by item. The position of that segment in the energy consumption change sequence is extracted, and the energy consumption change value at that position is read. Then, it is compared with the set energy consumption jump benchmark value. The energy consumption jump benchmark value is a critical value set in advance based on the normal operating fluctuation range of the equipment. For example, it is set to ±0.05kJ / mm, which means that if the energy consumption change of a certain stable segment is greater than 0.05kJ / mm or less than −0.05kJ / mm, it is considered that there is a sudden change in energy consumption. This judgment action needs to be performed item by item. If segment number 3 in the stable segment set has a corresponding energy consumption change of +0.08 kJ / mm, it meets the abrupt change condition and is recorded as an abnormal segment number. If segment number 5 has a change of +0.03 kJ / mm, it does not meet the condition and is not recorded. Finally, all segment numbers that have experienced energy consumption abrupt changes in the stable speed state are extracted and summarized to generate an abrupt start-stop drive signal. This signal records the abrupt change segment number, the corresponding energy consumption change value, and the position of the segment in the start-stop path interval, which serves as the output basis for judging the abnormal operation of the drive system.

[0076] Specifically, such as Figure 5 As shown, the structural stiffness evolution monitoring module includes:

[0077] The loading segment extraction submodule uses the interval number marked by the start-stop drive abnormal signal to call the loading stage data corresponding to the number in the structural loading record, extracts the sequentially arranged continuous loading stages in each numbered segment, and synchronously organizes the structural deformation trajectory in the stage to generate a continuous loading stage trajectory sequence.

[0078] First, the loading stage data table recorded in the structural monitoring system is read. The table is then matched with the structural loading records associated with each number's start and end time period. For each abnormal segment number, all loading stage entries within its start and end time range are extracted. The loading stages are arranged chronologically and typically record the loading state data after each drive generates a displacement response, such as displacement, force, and deformation at the start of loading. After confirming the correct chronological order, structural deformation information is extracted from the loading data of each stage. This structural deformation information originates from strain gauges, displacement sensors, or three-dimensional measurement devices deployed at key nodes. The collected structural response data is processed by extracting the changes in node positions for each loading stage according to node number and arranging them in chronological order. These data are then processed synchronously to form the structural deformation trajectory within each stage. This trajectory is a set of multi-node displacement data, reflecting the actual deformation path of the structure from the initial state to the final state within that loading stage. After all stage trajectory data are processed, the extracted deformation trajectories of multiple loading stages are concatenated and combined according to the loading stage order to generate a continuous loading stage trajectory sequence. For example, if there are five continuous loading stages within the anomaly number segment, five sets of structural deformation trajectories are generated. Finally, these are combined to form a trajectory sequence for subsequent residual vector calculation.

[0079] The residual vector calculation submodule calls the trajectory sequence of the continuous loading stage, extracts the end deformation position and the start position from each loading stage to construct the residual deformation vector, performs direction normalization on the vectors within the stage, calculates the vector angle value sequence between adjacent stages, and obtains the residual deformation vector angle value group.

[0080] For each loading stage, the difference between the beginning and end points of the structural deformation trajectory needs to be extracted. The initial and ending positions of that stage are identified from the deformation trajectory, and the coordinate difference between these two positions is calculated to obtain the overall deformation vector of the structural end relative to the starting point. This deformation vector represents the direction and magnitude of the residual deformation of the structure after loading for that stage. This extraction process is repeated for all loading stages to obtain a set of residual deformation vectors for all stages. Next, each residual vector undergoes direction normalization, converting each deformation vector into a direction vector and standardizing its magnitude to a unit length to ensure that subsequent adjustments are based solely on the direction. After normalization, the included angle is calculated by selecting any two adjacent loading stages' direction vectors and calculating their included angle value. This included angle value represents the degree of change between the residual deformation directions of adjacent stages. The included angle calculation results between all adjacent stages are combined into a sequence. This sequence records the changes in the residual direction of the structure at each stage during loading. If the trajectory sequence contains six stages, five included angle values ​​will be obtained. For example, five sets of residual vectors between adjacent stages are constructed between stages 1 and 6. The included angles between stages 1 and 2, 2 and 3, etc., are calculated respectively and organized into a group of included angle values ​​of residual deformation vectors for use by the offset morphology judgment module.

[0081] The offset morphology discrimination submodule determines whether the vector angle between the three stages is continuously less than the set angle consistency threshold based on the residual deformation vector angle value group, filters the structure numbers that meet the continuous direction consistency condition, marks the number as being in a continuous offset state, and generates a structural stiffness warning signal.

[0082] First, the angle value groups are scanned sequentially, and all consecutive angle subgroups of length three are extracted for judgment. In each three-stage angle subgroup, angle value 1, angle value 2, and angle value 3 are taken in sequence and compared with a pre-set angle consistency threshold. This threshold is determined by the allowable direction difference range of structural deformation and is usually set between 5 and 10 degrees. For example, if it is set to 7 degrees, then when a group of three adjacent angle values ​​are all less than or equal to 7 degrees, it indicates that the residual deformation direction between the three stages is highly consistent. The corresponding structure number is judged to have a continuous direction consistency offset phenomenon. All numbers that meet the condition that the angle values ​​of three consecutive stages are all below the threshold are filtered and summarized. These numbers are marked as the identification results of the structure being in a continuous offset state. Finally, the results are output in the form of a list of structure numbers, forming a structural stiffness warning signal. This signal contains information such as the structure number, the angle value group used for judgment, the angle consistency threshold setting, and the loading stage range in which the judgment is valid.

[0083] Specifically, such as Figure 6 As shown, the maintenance trigger monitoring module includes:

[0084] The abnormal data integration submodule, based on the structure number in the structural stiffness warning signal, calls the water flow impact record, door offset direction record and drive energy consumption jump section number under the same structure number, classifies the data according to the number correspondence rules, extracts the key time tags in the records and unifies the time format, and generates a structural abnormal record dataset.

[0085] First, a list of structure numbers is obtained, and each number is processed individually. Three types of data records related to each structure number are extracted from the system database: water flow impact records, gate offset direction records, and drive energy consumption jump section numbers. Water flow impact records need to match the velocity, direction, and dynamic pressure changes at the structure's location, and are categorized by timestamp. Gate offset direction records retrieve the identified attitude offset angle sequence under that structure number and extract the corresponding offset angle direction data. Drive energy consumption jump section numbers require finding the abnormal energy consumption section corresponding to that number from the energy consumption records. After extracting the three types of data, the structure number field in all records is uniformly confirmed to ensure that the data belongs to the same structure number. Then, the timestamp fields in each type of record are standardized, converting all time fields to a unified format, such as "yyyy-mm-dd". The data is formatted in 24-hour time format ("hh:mm:ss"). Records from different sources are then categorized chronologically. A data mapping relationship is established using the structure number and timestamp as the key to ensure that the three types of data can be aligned and compared in the time dimension. Key time tags corresponding to each record are then extracted, such as the impact start time, the first occurrence time of the offset, and the time of energy consumption mutation. The event type, source module, occurrence time, and structure number are recorded in the organized dataset, ultimately forming a structural anomaly record dataset.

[0086] The time series indexing module calls the structural anomaly record dataset, constructs an ordered time series linked list according to the time labels in the records, marks the source field for each data item and establishes a time node index, locates overlapping and continuous anomaly segments in the sequence, and generates a multi-source anomaly time series index table.

[0087] First, all records in the dataset are sorted in ascending order by the timestamp field, constructing a time-based main linked list. Each node in the linked list corresponds to a record, and these records are connected sequentially in chronological order to form a complete sequence. A source field identifier is added to each node, such as "impact record," "offset record," or "energy consumption record," and its original sub-module source identifier is recorded. Next, a time node index is generated for each node, recording its time value and position index number for each node in the sequence. By traversing the entire linked list, time overlap segments and consecutive abnormal segments of all records are identified. The logic for determining time overlap segments is that records from different sources occur within similar time periods. If the time interval between two records is less than the set judgment threshold (e.g., 30 seconds), they are considered to overlap. The logic for judging continuous abnormal segments is that multiple records from the same or different sources appear without interruption in duration. For example, if the offset record is from 10:00 to 10:05 and the impact record is from 10:03 to 10:06, they are considered to constitute an overlapping segment and are marked as a period of concentrated abnormality. After the analysis is completed, all records in the linked list structure are marked with an overlap mark field and an abnormal continuous number field. Finally, the information containing fields such as source identifier, time index, overlap mark and continuous segment number is output as a multi-source abnormal time series index table.

[0088] The instruction generation and push submodule integrates multiple types of abnormal event numbers within the same time period under the same structure number based on the multi-source abnormal time series index table, constructs a corresponding mapping structure between structure number and abnormal type, encapsulates and outputs it to the scheduling end in a unified data format, and generates the core instruction for safe operation of the sluice gate.

[0089] The system reads the abnormal records under each structure number one by one. By identifying multiple types of abnormal event numbers that occur within the same time period under the same structure number, it extracts the event type set that constitutes the abnormal combination within that time period. For example, if structure number A experiences impact abnormality, offset abnormality, and energy consumption abnormality simultaneously between 10:00 and 10:05, then the three types of abnormal numbers within that period are extracted and classified into the abnormal combination event under number A. By traversing the entire index table, the system integrates and classifies the abnormal events within each time period under all structure numbers. Subsequently, it constructs a corresponding mapping structure between structure numbers and abnormal type combinations. This structure contains a structure number field, a start and end time field, an abnormal type set field, and an abnormal combination number field. The information in the structure is further standardized by encapsulating the field content according to a unified message format. For example, the unified field order is "structure ID, start time, end time, abnormal type combination code, abnormal type list". The encapsulated data is generated into a data message according to the communication protocol requirements and pushed to the sluice gate scheduling terminal through the system's scheduling interface module as input for triggering feedback control logic in the scheduling system. Finally, it generates the core instruction for the safe operation of the sluice gate.

[0090] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A sluice gate safe operation system based on condition-predictive maintenance, characterized in that, The system includes: The hydrological impact monitoring module acquires the impact direction and dynamic pressure changes of upstream and downstream water flow, and calculates the directional difference and extracts the change curve by combining the direction of the water-facing surface of the gate and the contact surface of the gate slot, thus generating abnormal water flow impact signals. Based on the abnormal water flow impact signal, the gate attitude tracking module calls the gate's horizontal and vertical displacement records, calculates the angle between the synthetic displacement direction and the stationary reference direction, filters the consecutive offset numbers in the same direction, and generates the gate attitude offset signal. The opening and closing energy consumption monitoring module extracts the opening and closing path energy consumption and speed data based on the gate posture offset signal, analyzes the unit displacement energy consumption and speed stability in segments, identifies energy consumption jump intervals in the speed stable region, and generates an abnormal opening and closing drive signal. Based on the opening and closing drive anomaly signal, the structural stiffness evolution monitoring module extracts the structural deformation trajectory, calculates the direction of the residual deformation vector during the continuous loading stage, analyzes the consistency of change, determines whether there is continuous offset, and generates a structural stiffness early warning signal. The maintenance trigger monitoring module integrates records such as water flow impact, gate offset, and energy consumption jumps based on the structural stiffness early warning signal, sorts them by time and marks their sources, and generates core instructions for the safe operation of the sluice gate.

2. The sluice gate safe operation system based on condition-predictive maintenance according to claim 1, characterized in that: The abnormal water flow impact signal includes the critical interval of the impact direction difference, the sequence of structural pressure direction turning points, and abnormal fluctuation characteristic parameters. The gate attitude deviation signal includes the displacement synthesis direction angle sequence, the continuous offset azimuth of the included angle, and the duration of attitude deviation. The abnormal opening and closing drive signal includes the sudden change value of energy consumption per unit displacement, the identification number of the velocity stability zone, and the deviation degree of energy consumption and velocity change. The structural stiffness early warning signal includes the staged residual deformation direction, the continuous loading offset trend, and the structural stiffness change level. The core instructions for safe operation of the sluice gate include the abnormality type label, the associated structure number, and the time sequence integration information.

3. The sluice gate safe operation system based on condition-predictive maintenance according to claim 1, characterized in that: The continuous offset in the same direction number refers to the number sequence in which the gate body's attitude offsets in the same direction within a continuous time period, indicating a continuous and consistent attitude offset trend.

4. The sluice gate safe operation system based on condition-predictive maintenance according to claim 1, characterized in that: The identification of energy consumption jump intervals in the speed stable region refers to the time interval during which energy consumption per unit displacement suddenly changes within the section where the speed remains stable during the opening and closing process.

5. The sluice gate safe operation system based on condition-predictive maintenance according to claim 1, characterized in that, The hydrological impact monitoring module includes: The directional data acquisition submodule acquires records of the impact direction and dynamic pressure changes of upstream and downstream water flow, calls up the data of the direction of the gate's water-facing surface and the direction of the gate slot contact surface, calculates the directional difference according to the impact direction and pressure direction in the time series, and generates a directional difference sequence value. The difference sequence construction submodule, based on the directional difference sequence value, establishes trend marker records according to the changing trend of adjacent differences, extracts continuous changing segments to form a trend change trajectory, and generates a directional difference trend trajectory. The turning section identification submodule calls the direction difference trend trajectory, compares the trend marker direction change, identifies the time period number of continuous reversal, filters the sequence position that meets the conditions, and generates water flow impact abnormal signal identifier.

6. The sluice gate safe operation system based on condition-predictive maintenance according to claim 1, characterized in that, The door posture tracking module includes: The attitude data retrieval submodule retrieves the lateral and longitudinal displacement records of the gate within the corresponding time period based on the time period number identified by the water flow impact anomaly signal. It extracts the lateral and longitudinal displacement components at the time point and calculates the synthetic displacement direction angle at each time point through the displacement components to obtain the synthetic direction angle sequence of the gate. The included angle offset calculation submodule calls the gate body synthetic direction angle sequence, calculates the included angle value at the time point based on the gate body static reference direction angle, extracts the set of numbers whose offset angle is greater than the set offset threshold from the included angle value sequence, and obtains the included angle offset orientation sequence. The continuous offset filtering submodule counts the time periods that continuously offset to the same position in the sequence based on the included angle offset azimuth sequence, filters the numbered segments with the same offset direction and the duration that meets the minimum duration condition, and generates the gate attitude offset signal.

7. The sluice gate safe operation system based on condition-predictive maintenance according to claim 1, characterized in that, The start-up and shutdown energy consumption monitoring module includes: The energy consumption data extraction submodule, based on the gate number contained in the gate posture offset signal, calls the energy consumption data and displacement record of the corresponding gate opening and closing path, divides the opening and closing path into equidistant segments, extracts the energy consumption value per unit displacement of the segment, calculates the increase or decrease in energy consumption per unit displacement between consecutive segments, and generates a sequence of segment energy consumption change values. Based on the gate attitude offset signal, the speed stability identification submodule calculates the speed change rate in each equidistant path segment, marks the segment with a speed change rate lower than the speed fluctuation benchmark value as a stable segment, and obtains a set of speed stable segment numbers. The drive anomaly identification submodule filters the positions in the stable section where the energy consumption change value sequence exceeds the set energy consumption jump benchmark value based on the energy consumption change value sequence of the section and the set of speed stable section numbers. It then extracts the section numbers that meet the jump conditions as abnormal segment numbers and generates a start / stop drive anomaly signal.

8. The sluice gate safe operation system based on condition-predictive maintenance according to claim 1, characterized in that, The structural stiffness evolution monitoring module includes: The loading segment extraction submodule, based on the interval number marked by the start-stop drive abnormal signal, calls the loading stage data corresponding to the number in the structural loading record, extracts the sequentially arranged continuous loading stages in each numbered segment, synchronously organizes the structural deformation trajectory in the stage, and generates a continuous loading stage trajectory sequence. The residual vector calculation submodule calls the trajectory sequence of the continuous loading stage, extracts the end deformation position and the start position from each loading stage to construct the residual deformation vector, performs direction normalization processing on the vectors within the stage, calculates the vector angle value sequence between adjacent stages, and obtains the residual deformation vector angle value group. The offset morphology discrimination submodule determines whether the vector angle between the three stages is continuously less than the set angle consistency threshold based on the residual deformation vector angle value group, filters out the structure numbers that meet the continuous direction consistency condition, marks the number as being in a continuous offset state, and generates a structural stiffness warning signal.

9. The sluice gate safe operation system based on condition-predictive maintenance according to claim 1, characterized in that, The maintenance trigger monitoring module includes: The abnormal data integration submodule, based on the structure number in the structural stiffness warning signal, calls the water flow impact record, door offset direction record and drive energy consumption jump section number under the same structure number, classifies the data according to the number correspondence rule, extracts the key time tags in the record and unifies the time format, and generates a structural abnormal record dataset. The time series indexing module calls the structural anomaly record dataset, constructs an ordered time series linked list according to the time labels in the records, marks the source field for each data item and establishes a time node index, locates overlapping and continuous anomaly segments in the sequence, and generates a multi-source anomaly time series index table. The instruction generation and push submodule integrates multiple types of abnormal event numbers within the same time period under the same structure number according to the multi-source abnormal time series index table, constructs a corresponding mapping structure between structure number and abnormal type, encapsulates and outputs it to the scheduling terminal according to a unified data format, and generates the core instruction for safe operation of the sluice gate.

10. The sluice gate safe operation system based on condition-predictive maintenance according to claim 9, characterized in that: The aforementioned location record overlap and continuous abnormal segments refer to the segments in multi-source abnormal time series that identify time overlap of differential source records and occurrence of abnormal events, and mark potential risk concentration periods.

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