Ship lock safe passage early warning system based on digital twinning

Abstract

The invention discloses a ship lock safe passage early warning system based on digital twinning, and belongs to the field of ship lock operation and maintenance. The invention discloses a ship lock safe passage early warning system based on digital twinning. The ship lock safe passage early warning system comprises a digital twinning modeling unit, a digital twinning modeling unit, a processing analysis unit, a risk early warning unit and a user interaction unit. The problem that the prior art depends on manual monitoring and simple sensor monitoring is solved, the digital twinning modeling unit accurately reflects the running state of the ship lock in real time through the digital twinning technology, key data are comprehensively collected through the multi-source sensing unit, potential safety hazards are deeply excavated through the processing and analyzing unit and evaluated in real time, and the real-time monitoring of the ship lock is achieved. The risk early warning unit is combined to timely send out an early warning signal, so that the operation safety of the ship lock is effectively improved, the safe passing early warning of the ship lock is realized, meanwhile, the visual display function of the user interaction unit enables managers to intuitively master the operation condition of the ship lock, the stable operation of the ship lock is ensured, and the navigation efficiency is improved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of ship lock operation and maintenance, in particular to a ship lock safe passing early warning system based on digital twinning. BACKGROUND

[0002] The ship lock is an important navigation facility in water transportation, and its safe passing is crucial for ensuring smooth water transportation and the safety of ships. The traditional ship lock safe passing early warning method mainly relies on manual monitoring and simple sensor monitoring, which has the problems of low monitoring accuracy, poor real-time performance, and inability to comprehensively perceive the ship lock operation state, and cannot effectively prevent safety hazards in the ship lock passing process. Therefore, the existing requirements are not met, and the ship lock safe passing early warning system based on digital twinning is proposed. SUMMARY

[0003] The application aims to provide a ship lock safe passing early warning system based on digital twinning. A digital twinning modeling unit is used to construct a ship lock digital twinning model to reflect the physical state in real time. A multi-source perception unit collects ship lock operation multi-dimensional data and transmits them to a processing and analysis unit. The data are preprocessed, fused, and key features are extracted. The ship lock operation state is evaluated in real time according to a safe operation model, and potential safety hazards are determined. A risk early warning unit sends an early warning signal and notifies the management personnel in a timely manner according to the evaluation results. In addition, a user interaction unit provides an operation interface to support system operation, parameter setting, early warning information viewing and processing, and digital twinning model visualization display, helping the management personnel to intuitively understand the ship lock operation state, and solving the problems raised in the above background technology.

[0004] To achieve the above-mentioned purpose, the application provides the following technical scheme: a ship lock safe passing early warning system based on digital twinning, which comprises:

[0005] A digital twinning modeling unit configured to construct a digital twinning model of the ship lock by digital twinning technology and reflect the physical state of the ship lock in real time;

[0006] A multi-source perception unit configured to collect ship lock operation data, including but not limited to ship position information, ship lock water level information, ship speed information, ship lock gate state information, and ship draft depth information, and transmit the collected data to a processing and analysis module;

[0007] A processing and analysis unit configured to preprocess, fuse, and extract key features of the ship lock safe operation of the collected data, evaluate the ship lock operation state in real time according to the ship lock safe operation model, and determine whether there is a potential safety hazard in the ship lock operation;

[0008] The risk early warning unit is configured to, according to the evaluation result of the processing analysis unit, timely issue a warning signal when it is detected that there is a safety hazard in the operation of the ship lock, and notify the management personnel through various ways;

[0009] The user interaction unit is configured to provide a user interface for the ship lock management personnel to perform system operation, parameter setting, early warning information viewing and processing, and simultaneously support visual display of the digital twin model, so that the management personnel can intuitively understand the operation state of the ship lock.

[0010] Further, the digital twin modeling unit comprises:

[0011] The digital twin modeling module is configured to construct a digital twin model of the ship lock through digital twin technology, specifically:

[0012] A three-dimensional geometric model of the ship lock is constructed using a three-dimensional modeling tool according to design drawings and actual measurement data of the ship lock, including the main structure, lock chamber, gate and approach channel of the ship lock;

[0013] Physical properties are added to the constructed three-dimensional geometric model in combination with the actual materials and structural parameters of the ship lock;

[0014] The dynamic behavior of the ship lock is simulated in combination with the operating conditions and control logic of the ship lock, including the opening and closing actions of the gate, the flow of water flow and the entry and exit of the ship;

[0015] The data integration module is configured to establish a data interface with the multi-source perception unit, and the data interface uses a standardized data communication protocol to receive real-time ship lock operation data;

[0016] The data synchronization module is configured to use a data synchronization algorithm to update the data in the digital twin model in real time, ensuring that the digital twin model and the physical state of the ship lock remain synchronized, wherein the data synchronization algorithm includes timestamp synchronization or event-driven synchronization.

[0017] Further, the digital twin modeling module comprises:

[0018] For data security, an encryption technology is used to protect the security of data during transmission and storage, and an access control mechanism is established to limit the access rights to the digital twin model and data;

[0019] For model maintenance, a model maintenance mechanism is established, including regularly checking the geometric accuracy of the model and the accuracy of the physical properties, and regularly calibrating and optimizing the digital twin model in combination with the actual operation data of the ship lock.

[0020] Further, the multi-source perception unit comprises:

[0021] The data collection module is configured to collect ship lock operation data by using various sensors and monitoring devices, including but not limited to ship position information, ship lock water level information, ship speed information, ship lock gate state information and ship draft depth information.

[0022] The data transmission module is configured to package the data collected by the data collection module into a unified data packet format, including a timestamp, a data type and a data value field, and then transmit the packaged data to the processing and analysis module, while monitoring the integrity and accuracy of the data transmission process in real time, discovering and processing data loss or errors in a timely manner, and automatically triggering retransmission and error correction mechanisms when detecting data loss or errors.

[0023] Further, the data transmission module comprises:

[0024] The transmission optimization module is configured to compress data using a data compression algorithm to reduce the amount of data transmitted, and to prioritize data packets according to the importance and timeliness of the data, with high-priority data being transmitted first.

[0025] The transmission monitoring module is configured to monitor the integrity and accuracy of the data transmission process in real time, specifically:

[0026] Data integrity check: Each data packet is assigned a unique sequence number, and the processing and analysis module checks the continuity of the data packets by sequence number to find missing data packets.

[0027] Data accuracy monitoring: Compare the same type of data collected by different sensors or monitoring devices, and detect abnormal data through a consistency algorithm.

[0028] The data retransmission module is configured to automatically trigger retransmission and error correction mechanisms when detecting data loss or errors, and the data transmission module re-sends the missing or erroneous data packets.

[0029] Further, in the transmission optimization module, the priority of the data packets is sorted as follows:

[0030] Ρ = ω1 × I + ω2 × T

[0031] Where P is the priority of the data packet, indicating the importance of the data packet in transmission; ω1 and ω2 are weight coefficients, representing the weight of data importance and timeliness in priority calculation, and ω1 + ω2 = 1; I is the importance of the data, with a value range of [0, 1], and the larger the value, the more important the data; T is the timeliness of the data, with a value range of [0, 1], and the larger the value, the more timely the data needs to be transmitted.

[0032] Further, the processing and analysis unit comprises:

[0033] The data processing module is configured to preprocess the collected raw data, specifically:

[0034] The sliding average filtering or low-pass filtering algorithm is adopted to remove high-frequency noise in the data.

[0035] Based on statistical method, abnormal data points are detected and removed;

[0036] For missing data, interpolation method is used to fill in;

[0037] The data fusion module is configured to convert the data collected by different sensors or monitoring devices into a unified format, including timestamp alignment and unit conversion, and then use Kalman filtering and Bayesian fusion algorithm to fuse the data;

[0038] The feature extraction module is configured to extract key features related to the safe operation of the ship lock from the fused data, including ship speed, channel width, ship spacing, water level change rate and gate opening and closing speed, calculate the specific values of the selected features, including statistical features, time series features and spatial features, and normalize the extracted features to ensure comparability between different features;

[0039] The model construction module is configured to analyze historical operation data, extract normal operation and abnormal operation feature patterns, train the features extracted from historical operation data using machine learning algorithms, construct a ship lock safety operation model, and verify the constructed model through cross-validation method;

[0040] The real-time evaluation module is configured to input the data processed by the feature extraction module into the ship lock safety operation model, evaluate the real-time operation state of the ship lock through the ship lock safety operation model, and judge whether there is potential safety risk;

[0041] The hidden danger judgment module is configured to set the threshold of safety index, judge whether there is potential safety hidden danger in the operation of the ship lock according to the real-time evaluation result of the real-time evaluation module.

[0042] Further, the risk warning unit comprises:

[0043] The warning generation module is configured to generate corresponding warning signals according to the evaluation results of the processing and analysis unit, including warning level, warning reason and recommended measures;

[0044] The warning notification module is configured to select the corresponding notification mode according to the warning level and the preset notification strategy, including but not limited to sound and light alarm, SMS notification, email notification and system prompt;

[0045] The early warning record module is configured to record and store each early warning event after the early warning notification is sent, and provide a query interface for the management personnel to query historical early warning records and perform auditing and analysis.

[0046] Further, the early warning notification module comprises:

[0047] The response record module is configured to monitor the response time and response content of the management personnel in real time after the early warning notification is sent.

[0048] For the response time: record the time stamp of sending the early warning information and the time stamp of the response of the management personnel, calculate the response delay, and according to the preset delay threshold, divide the response delay into three categories of timely, delayed and seriously delayed;

[0049] For the response content: compare the response content of the management personnel with the recommended response measures of the system, and calculate the similarity of the response content and the recommended content by using the cosine similarity algorithm.

[0050] The response optimization module is configured to identify the training needs of the management personnel according to the response monitoring results, including but not limited to the improvement of response speed and operation skills, and provide targeted improvement suggestions, including but not limited to optimizing the early warning notification method and adjusting the response strategy.

[0051] Further, for the response time, specifically:

[0052] The response delay calculation formula is:

[0053] ΔT = T 预警 -T 响应

[0054] Wherein, ΔT represents the response delay; T 预警 represents the time stamp of sending the early warning information; T 响应 represents the time stamp of the response of the management personnel.

[0055] Suppose the preset delay threshold is T 阈值1 and T 阈值2 , and T 阈值1 is less than T 阈值2 , and the response delay is classified as follows:

[0056] If ΔT≤T 阈值1 , the response is timely.

[0057] If T 阈值1 <ΔT<T 阈值2 , the response is delayed.

[0058] If ΔT≥T 阈值2 , the response is seriously delayed.

[0059] Compared with the prior art, the application has the beneficial effects that:

[0060] The digital twin modeling unit of the application reflects the ship lock operation state in real time and accurately through digital twin technology, comprehensively collects key data by using a multi-source perception unit, deeply mines potential safety hazards and performs real-time evaluation through a processing and analysis unit, timely issues early warning signals in combination with a risk early warning unit, effectively improves the ship lock operation safety, and thus realizes ship lock safety passing early warning. BRIEF DESCRIPTION OF DRAWINGS

[0061] Figure 1 The figure is a structural schematic diagram of the ship lock safety passing early warning system based on digital twin of the application. DETAILED DESCRIPTION

[0062] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0063] To solve the technical problem that the existing ship lock safety passing early warning method mainly relies on manual monitoring and simple sensor monitoring, has low monitoring accuracy, poor real-time performance, cannot comprehensively perceive the ship lock operation state, and cannot effectively prevent safety hazards in the ship lock passing process, please refer to Figure 1 The embodiment provides the following technical solutions:

[0064] The ship lock safety passing early warning system based on digital twin comprises:

[0065] A digital twin modeling unit is configured to construct a digital twin model of the ship lock by using digital twin technology, and reflect the physical state of the ship lock in real time.

[0066] A multi-source perception unit is configured to collect ship lock operation data, including but not limited to ship position information, ship lock water level information, ship speed information, ship lock gate state information, and ship draft depth information, and transmit the collected data to a processing and analysis module.

[0067] A processing and analysis unit is configured to pre-process, fuse, and extract key features of the safe operation of the ship lock, perform real-time evaluation on the ship lock operation state according to a ship lock safe operation model, and determine whether there is a potential safety hazard in the operation of the ship lock.

[0068] The risk early warning unit is configured to, according to the evaluation result of the processing analysis unit, timely issue a warning signal when it is detected that there is a safety hazard in the operation of the ship lock, and notify the management personnel through various ways;

[0069] The user interaction unit is configured to provide a user interface for the ship lock management personnel to perform system operation, parameter setting, early warning information viewing and processing, and simultaneously support visual display of the digital twin model, so that the management personnel can intuitively understand the operation state of the ship lock.

[0070] The technical effects of the above technical solutions are as follows: through the cooperative work of the digital twin modeling unit and the multi-source perception unit, the system can obtain multi-dimensional data of the operation of the ship lock in real time, and with the help of the processing analysis unit, the data is deeply processed and analyzed, the operation state of the ship lock is accurately evaluated, potential safety hazards are timely discovered, the safety and reliability of the operation of the ship lock are ensured, the risk early warning unit can quickly and accurately issue a warning signal based on the evaluation result of the processing analysis unit, and notify the management personnel through various ways, so that the management personnel can take timely response measures to avoid accidents, reduce safety risks, and improve the safety management level of the operation of the ship lock, and the user interaction unit provides an intuitive user interface and supports visual display of the digital twin model, so that the management personnel can clearly understand the operation state and safety condition of the ship lock, and the unit also has functions of system operation, parameter setting, early warning information viewing and processing, which greatly improves the management efficiency and the scientific nature of decision-making, and reduces the management difficulty.

[0071] The digital twin modeling unit comprises:

[0072] The digital twin modeling module is configured to construct a digital twin model of the ship lock through digital twin technology, specifically:

[0073] A three-dimensional geometric model of the ship lock is constructed by using a three-dimensional modeling tool according to design drawings and actual measurement data of the ship lock, including the main structure, the lock chamber, the lock gate and the approach channel of the ship lock;

[0074] Physical properties are added to the constructed three-dimensional geometric model in combination with the actual materials and structural parameters of the ship lock;

[0075] Dynamic behaviors of the ship lock are simulated in combination with the operation conditions and control logic of the ship lock, including the opening and closing actions of the lock gate, the flow of water flow and the entry and exit of the ship;

[0076] The data integration module is configured to establish a data interface with the multi-source perception unit, the data interface adopts a standardized data communication protocol (such as MQTT, OPC UA, etc.), and real-time ship lock operation data is received;

[0077] The data synchronization module is configured to update data in the digital twin model in real time by using a data synchronization algorithm to ensure that the digital twin model is synchronized with the physical state of the ship lock, wherein the data synchronization algorithm includes timestamp synchronization or event-driven synchronization.

[0078] The technical effects of the above technical solution are: the digital twin modeling module uses a three-dimensional modeling tool to construct a three-dimensional geometric model of the ship lock in combination with design drawings and actual data, and adds physical properties and dynamic behavior simulation, which can accurately restore the structure and operating conditions of the ship lock, and provide an intuitive digital display for the operation and management of the ship lock. The data integration module establishes a data interface through a standardized data communication protocol, and receives ship lock operation data collected by the multi-source perception unit in real time, realizes efficient integration of multi-source perception data, and provides comprehensive data support for the digital twin model. The data synchronization module uses data synchronization algorithms such as timestamp synchronization or event-driven synchronization to ensure that the data in the digital twin model is consistent with the physical state of the ship lock in real time, improving the real-time and accuracy of the digital twin model, and providing a reliable basis for the operation monitoring, fault diagnosis and optimal scheduling of the ship lock.

[0079] The digital twin modeling module comprises:

[0080] For data security, encryption technology (such as SSL / TLS encrypted transmission, data encryption storage, etc.) is configured to protect data security during transmission and storage, and an access control mechanism is established to limit access rights to the digital twin model and data.

[0081] For model maintenance, a model maintenance mechanism is established, including regularly checking the geometric accuracy of the model and the accuracy of the physical properties, and regularly calibrating and optimizing the digital twin model in combination with the actual operation data of the ship lock.

[0082] The technical effects of the above technical solution are: for data security, encryption and establishment of an access control mechanism can enhance the security of the system, and for model maintenance, a model maintenance mechanism is established and the digital twin model is regularly calibrated and optimized, which can improve the reliability and practicality of the model. The combination of the above data security and model maintenance mechanism not only ensures the data security of the digital twin system, but also improves the accuracy and reliability of the model, providing solid technical support for the digital management and decision-making of the ship lock.

[0083] The multi-source perception unit comprises:

[0084] The data acquisition module is configured to collect ship lock operation data using various sensors and monitoring devices, including but not limited to ship position information, ship lock water level information, ship speed information, ship lock gate state information and ship draft depth information.

[0085] The data transmission module is configured to encapsulate the data collected by the data collection module into a unified data packet format, including a timestamp, a data type and a data value field, and then transmit the encapsulated data to the processing and analysis module, while monitoring the integrity and accuracy of the data transmission process in real time, discovering and processing data loss or errors in a timely manner, and automatically triggering a retransmission and error correction mechanism when detecting data loss or errors.

[0086] The technical effects of the above technical solution are as follows: The data collection module uses various sensors and monitoring devices to collect key data during the operation of the ship lock, providing comprehensive data support for the operation monitoring and management of the ship lock. The data transmission module encapsulates the collected data into a unified format data packet to ensure the standardization and readability of the data, and monitors the integrity and accuracy of the data transmission process in real time, so that data loss or errors can be discovered and processed in a timely manner. When detecting data loss or errors, a retransmission and error correction mechanism is automatically triggered, thereby ensuring the reliability and integrity of data transmission.

[0087] The data transmission module comprises:

[0088] The transmission optimization module is configured to compress data using a data compression algorithm to reduce the amount of data transmitted, and to prioritize data packets according to the importance and timeliness of the data, with high-priority data being transmitted first, as shown in the following formula:

[0089] P = ω1 x I + ω2 x T

[0090] where P is the priority of the data packet, indicating the importance of the data packet in transmission; ω1 and ω2 are weight coefficients, representing the weight of data importance and timeliness in priority calculation, and ω1 + ω2 = 1; I is the importance of the data, with a value range of [0, 1], and a larger value indicating more important data; T is the timeliness of the data, with a value range of [0, 1], and a larger value indicating the need for timely transmission of data;

[0091] The transmission monitoring module is configured to monitor the integrity and accuracy of the data transmission process in real time, specifically:

[0092] Data integrity check: Each data packet is assigned a unique sequence number, and the processing and analysis module checks the continuity of the data packet through the sequence number to find missing data packets;

[0093] Data accuracy monitoring: Compare the same type of data collected by different sensors or monitoring devices, and detect abnormal data through a consistency algorithm (such as median filtering);

[0094] The data retransmission module is configured to automatically trigger a retransmission and error correction mechanism when detecting data loss or errors, and the data transmission module re-sends the lost or erroneous data packets.

[0095] The technical effects of the above solution are as follows: The transmission optimization module compresses data, reducing the amount of data transmitted, lowering transmission costs, and improving transmission efficiency. It then prioritizes data packets according to their importance and timeliness, ensuring that critical data arrives at the processing and analysis module in a timely manner, thereby optimizing resource allocation and improving the overall performance of the system. The transmission monitoring module checks the continuity of data packets by sequence number, quickly identifying lost data packets and ensuring data integrity. It also detects abnormal data through a consistency algorithm, ensuring data accuracy. Finally, the data retransmission module automatically triggers retransmission and error correction mechanisms when it detects data loss or errors, thereby ensuring the reliability and integrity of data transmission.

[0096] In summary, through mechanisms such as data compression, priority sorting, integrity checks, accuracy monitoring, and automatic retransmission, this data transmission module not only improves data transmission efficiency but also ensures data integrity and accuracy, providing high-quality real-time data support for the digital management and decision-making of the lock, and enhancing the overall reliability and stability of the system.

[0097] The processing and analysis unit includes:

[0098] The data processing module is configured to preprocess the collected raw data, specifically as follows:

[0099] High-frequency noise in the data can be removed by using moving average filtering or low-pass filtering algorithms.

[0100] Detect and remove outlier data points based on statistical methods (such as the 3σ rule);

[0101] For missing data, interpolation methods (such as linear interpolation or spline interpolation) are used to fill in the missing data;

[0102] The data fusion module is configured to convert data collected by different sensors or monitoring devices into a unified format, including timestamp alignment and unit conversion, and then use Kalman filtering and Bayesian fusion algorithms to fuse the data.

[0103] The feature extraction module is configured to extract key features related to the safe operation of the lock from the fused data, including ship speed, channel width, ship spacing, water level change rate and gate opening and closing speed. It calculates the specific values ​​of the selected features, including statistical features (such as mean and variance), time series features (such as trend and periodicity) and spatial features (such as ship position and channel width). It normalizes the extracted features to ensure comparability between different features.

[0104] The model building module is configured to analyze historical operation data, extract feature patterns of normal and abnormal operation, use machine learning algorithms (such as support vector machine, random forest, deep learning algorithm) to train the features extracted from historical operation data, build a safe operation model of the lock, and verify the built model through cross-validation.

[0105] The real-time evaluation module is configured to input the data processed by the feature extraction module into the lock safety operation model, and evaluate the real-time operation status of the lock through the lock safety operation model to determine whether there are potential safety risks.

[0106] The hazard assessment module is configured to set thresholds for safety indicators and, based on the real-time assessment results from the real-time evaluation module, determines whether there are potential safety hazards in the operation of the lock.

[0107] The technical effects of the above solution are as follows: The data processing module ensures the reliability and integrity of the data by performing a series of preprocessing operations; the data fusion module further improves the accuracy and reliability of the data by unifying and fusing the data format; the feature extraction module extracts key features related to the safe operation of the lock from the fused data, calculates the specific values ​​of the selected features, and normalizes the extracted features to ensure comparability between different features; the real-time evaluation module inputs the data processed by the feature extraction module into the lock safety operation model constructed by the model building module to evaluate the real-time operation status of the lock; and the hazard judgment module, by setting thresholds for safety indicators and based on the real-time evaluation results, can determine whether there are potential safety hazards in the lock operation, so as to issue timely warnings. Based on the above design, through efficient data preprocessing, data fusion, key feature extraction, accurate model building, real-time operation status evaluation, and hazard judgment, this processing and analysis unit can comprehensively analyze the lock's operation data, promptly discover potential safety hazards, provide scientific basis and technical support for the safe operation of the lock, and significantly improve the safety and reliability of the lock operation.

[0108] The risk warning unit includes:

[0109] The early warning generation module is configured to generate corresponding early warning signals based on the evaluation results of the processing and analysis unit, including the early warning level (such as low, medium, and high), the cause of the early warning (such as insufficient ship spacing, abnormal water level changes, etc.), and recommended measures.

[0110] The early warning notification module is configured to select the appropriate notification method based on the early warning level and the preset notification strategy, including but not limited to audible and visual alarms, SMS notifications, email notifications, and system prompts.

[0111] The early warning record module is configured to record and store each early warning event (such as early warning time, early warning level, early warning reason, notification method, response time, etc.) after an early warning notification is issued. It provides a query interface for managers to query historical early warning records and perform auditing and analysis.

[0112] The technical effects of the above-mentioned technical solution are as follows: through accurate early warning generation, flexible early warning notification, and comprehensive early warning recording and auditing functions, the risk early warning unit can promptly detect and notify potential risks in the operation of the lock, ensuring that managers can take measures quickly to reduce the probability of accidents and ensure the safe operation of the lock. At the same time, the storage and query functions of early warning records provide strong support for the continuous optimization and management of the system, significantly improving the level of intelligence in lock operation management.

[0113] The early warning notification module includes:

[0114] The response logging module is configured to monitor the response time and content of administrators in real time after an alert notification is issued.

[0115] Regarding response time: Record the timestamps of the warning information sending and the management personnel's response, calculate the response delay, and categorize the response delay into three types based on a preset delay threshold: timely, delayed, and severely delayed.

[0116] The formula for calculating response delay is:

[0117] ΔT=T 预警 -T 响应

[0118] Where ΔT represents the response delay; T 预警 Indicates the timestamp of the warning message being sent; T 响应 The timestamp indicating the administrator's response;

[0119] Assume the preset delay threshold is T. 阈值1 and T 阈值2 And T 阈值1 Less than T 阈值2 The response latency is classified as follows:

[0120] If ΔT≤T 阈值1 If so, the response is timely;

[0121] If T 阈值1 <ΔT<T 阈值2 The response will be delayed.

[0122] If ΔT≥T 阈值2 The response will be severely delayed.

[0123] Regarding the response content: The response content of the managers is compared with the response measures suggested by the system, and the cosine similarity algorithm is used to calculate the similarity between the response content and the suggested content;

[0124] The response optimization module is configured to identify the training needs of managers based on response monitoring results, including but not limited to improving response speed and operational skills, and to provide targeted improvement suggestions, including but not limited to optimizing early warning notification methods and adjusting response strategies.

[0125] The technical effects of the above-mentioned technical solution are as follows: By monitoring the response time and content of management personnel in real time and providing targeted improvement suggestions based on the monitoring results, the early warning notification module can effectively improve the response speed and accuracy of management personnel to early warning information. At the same time, by identifying training needs and optimizing the early warning notification method, the module further improves the intelligence level of the early warning system, ensuring that the risks of lock operation can be dealt with in a timely and effective manner, and significantly improving the efficiency and safety of lock operation management.

[0126] Working Principle: Through the collaborative work of the digital twin modeling unit and the multi-source sensing unit, the system can acquire multi-dimensional data on the operation of the lock in real time. The processing and analysis unit then performs in-depth processing and analysis on the data to accurately assess the lock's operational status, thereby promptly identifying potential safety hazards and ensuring the safety and reliability of the lock's operation. Based on the assessment results from the processing and analysis unit, the risk warning unit can quickly and accurately issue warning signals and notify management personnel through various means, enabling them to take timely countermeasures to prevent accidents, reduce safety risks, and improve the safety management level of the lock's operation. The user interaction unit provides an intuitive user interface that supports the visualization of the digital twin model, allowing management personnel to clearly understand the lock's operational status and safety conditions. This unit also has functions such as system operation, parameter setting, and viewing and processing of warning information, greatly improving management efficiency and the scientific nature of decision-making while reducing management difficulty.

[0127] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0128] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A lock safety passage early warning system based on digital twins, characterized in that, The system includes: The digital twin modeling unit is configured to construct a digital twin model of the lock using digital twin technology and reflect the physical state of the lock in real time. The multi-source sensing unit is configured to collect lock operation data, including but not limited to ship position information, lock water level information, ship speed information, lock gate status information and ship draft information, and transmit the collected data to the processing and analysis module. The processing and analysis unit is configured to preprocess, fuse, and extract key features for safe operation of the lock from the collected data, and to evaluate the lock's operating status in real time based on the lock's safe operation model to determine whether there are potential safety hazards in the lock's operation. The risk warning unit is configured to issue a warning signal in a timely manner when a safety hazard is detected in the operation of the lock, based on the evaluation results of the processing and analysis unit, and notify the management personnel through various means. The user interaction unit is configured to provide a user interface for lock management personnel to operate the system, set parameters, view and process early warning information, and also supports the visualization of the digital twin model, enabling management personnel to intuitively understand the lock's operating status.

2. The lock safety passage early warning system based on digital twin as described in claim 1, characterized in that, The digital twin modeling unit includes: The digital twin modeling module is configured to construct a digital twin model of the lock using digital twin technology, specifically: Using 3D modeling tools, a 3D geometric model of the lock is constructed based on the lock's design drawings and actual measurement data, including the lock's main structure, lock chamber, lock gate, and navigation channel. Based on the actual materials and structural parameters of the lock, physical properties are added to the constructed three-dimensional geometric model; Based on the operating conditions and control logic of the lock, the dynamic behavior of the lock is simulated, including the opening and closing of the gates, the flow of water, and the entry and exit of ships. The data integration module is configured to establish a data interface with the multi-source sensing unit. The data interface adopts a standardized data communication protocol to receive lock operation data in real time. The data synchronization module is configured to use a data synchronization algorithm to update the data in the digital twin model in real time, ensuring that the digital twin model remains synchronized with the physical state of the lock. The data synchronization algorithm includes timestamp synchronization or event-driven synchronization.

3. The lock safety passage early warning system based on digital twin as described in claim 2, characterized in that, The digital twin modeling module includes: For data security, the configuration uses encryption technology to protect the data during transmission and storage. At the same time, an access control mechanism is established to restrict access to the digital twin model and data. For model maintenance, a model maintenance mechanism is configured to be established, including regularly checking the geometric accuracy and physical property accuracy of the model, and periodically calibrating and optimizing the digital twin model based on the actual operation data of the lock.

4. The lock safety passage early warning system based on digital twin as described in claim 1, characterized in that, The multi-source sensing unit includes: The data acquisition module is configured to collect lock operation data using various sensors and monitoring equipment, including but not limited to ship position information, lock water level information, ship speed information, lock gate status information, and ship draft information. The data transmission module is configured to encapsulate the data collected by the data acquisition module into a unified data packet format, including timestamp, data type, and data value fields, and then transmit the encapsulated data to the processing and analysis module. At the same time, it monitors the integrity and accuracy of the data transmission process in real time, promptly detects and handles data loss or errors, and automatically triggers retransmission and error correction mechanisms when data loss or errors are detected.

5. The lock safety passage early warning system based on digital twin as described in claim 4, characterized in that, The data transmission module includes: The transmission optimization module is configured to compress data using a data compression algorithm and prioritize data packets based on their importance and timeliness, transmitting high-priority data first. The transmission monitoring module is configured to monitor the integrity and accuracy of data transmission in real time, specifically as follows: Data integrity check: Each data packet is assigned a unique sequence number. The processing and analysis module checks the continuity of data packets by sequence number and finds missing data packets. Data accuracy monitoring: Compare the same type of data collected by different sensors or monitoring devices, and detect abnormal data through a consistency algorithm; The data retransmission module is configured to automatically trigger a retransmission and error correction mechanism when data loss or errors are detected, and the data transmission module retransmits the lost or erroneous data packets.

6. The lock safety passage early warning system based on digital twin as described in claim 5, characterized in that, In the transmission optimization module, data packets are prioritized as shown in the following formula: P = ω1 × I + ω2 × T In the formula, P is the priority of the data packet, representing the importance of the data packet in the transmission; ω1 and ω2 are weighting coefficients, representing the weight of data importance and timeliness in the priority calculation, respectively, and ω1+ω2=1; I is the importance of the data, with a value range of [0,1], and the larger the value, the more important the data; T is the timeliness of the data, with a value range of [0,1], and the larger the value, the more timely the data needs to be transmitted. The result of P is a value between [0,1]. P close to 1 indicates that the data packet is very important and needs to be transmitted as soon as possible, while P close to 0 indicates that the data packet is relatively unimportant and will be transmitted later.

7. The lock safety passage early warning system based on digital twin as described in claim 1, characterized in that, The processing and analysis unit includes: The data processing module is configured to preprocess the collected raw data, specifically as follows: High-frequency noise in the data can be removed by using moving average filtering or low-pass filtering algorithms. Statistical methods were used to detect and remove outlier data points. For missing data, interpolation methods are used to fill in the missing data; The data fusion module is configured to convert data collected by different sensors or monitoring devices into a unified format, including timestamp alignment and unit conversion, and then use Kalman filtering and Bayesian fusion algorithms to fuse the data. The feature extraction module is configured to extract key features related to the safe operation of the lock from the fused data, including ship speed, channel width, ship spacing, water level change rate and gate opening and closing speed, calculate the specific values ​​of the selected features, including statistical features, time series features and spatial features, and normalize the extracted features to ensure comparability between different features. The model building module is configured to analyze historical operating data, extract feature patterns of normal and abnormal operation, use machine learning algorithms to train the features extracted from historical operating data, build a safe operation model for the lock, and verify the built model through cross-validation. The real-time evaluation module is configured to input the data processed by the feature extraction module into the lock safety operation model, and evaluate the real-time operation status of the lock through the lock safety operation model to determine whether there are potential safety risks. The hazard assessment module is configured to set thresholds for safety indicators and, based on the real-time assessment results from the real-time evaluation module, determines whether there are potential safety hazards in the operation of the lock.

8. The lock safety passage early warning system based on digital twin as described in claim 1, characterized in that, The risk warning unit includes: The early warning generation module is configured to generate corresponding early warning signals based on the evaluation results of the processing and analysis unit, including the early warning level, the cause of the early warning, and recommended measures. The early warning notification module is configured to select the appropriate notification method based on the early warning level and the preset notification strategy, including but not limited to audible and visual alarms, SMS notifications, email notifications, and system prompts. The early warning record module is configured to record and store each early warning event after an early warning notification is issued, and provides a query interface for managers to query historical early warning records and perform auditing and analysis.

9. The lock safety passage early warning system based on digital twin as described in claim 8, characterized in that, The early warning notification module includes: The response logging module is configured to monitor the response time and content of administrators in real time after an alert notification is issued. Regarding response time, the timestamps of the warning information being sent and the timestamps of the management personnel's response are recorded. The response delay is calculated, and based on a preset delay threshold, the response delay is categorized into three types: timely, delayed, and severely delayed. For the response content, the management personnel's response content is compared with the system's suggested response measures, and the cosine similarity algorithm is used to calculate the similarity between the response content and the suggested content; The response optimization module is configured to identify the training needs of managers based on response monitoring results, including but not limited to improving response speed and operational skills, and to provide targeted improvement suggestions, including but not limited to optimizing early warning notification methods and adjusting response strategies.

10. The lock safety passage early warning system based on digital twin according to claim 9, characterized in that, Regarding response time, specifically: The formula for calculating response delay is: ΔT=T 预警 -T 响应 Where ΔT represents the response delay; T 预警 Indicates the timestamp of the warning message being sent; T 响应 The timestamp indicating the administrator's response; Assume the preset delay threshold is T. 阈值1 and T 阈值2 And T 阈值1 Less than T 阈值2 The response latency is classified as follows: If ΔT≤T 阈值1 If so, the response is timely; If T 阈值1 <ΔT<T 阈值2 The response will be delayed. If ΔT≥T 阈值2 If so, the response will be severely delayed.

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