A ship lock fire emergency response and linkage control method

Abstract

This invention relates to the field of information technology and discloses a method for emergency response and linkage control in ship lock fires. The method involves real-time acquisition of environmental data through multi-source sensors, multi-layer analysis to generate precise fire early warning signals, and automatic activation of the emergency coordination module when the warning intensity exceeds a dynamic threshold. This module synchronously controls the channel devices and ship dispatching devices, generating an equipment linkage sequence. Based on this linkage sequence, the channel status is adjusted, and smoke extraction, ventilation, and emergency lighting equipment are simultaneously activated to optimize the evacuation environment and generate the optimal evacuation route. After evacuation, non-essential circuits are automatically cut off, prioritizing fire-fighting power supply, and finally, an emergency response assessment result is generated. This method achieves full-process automation of fire monitoring, early warning, linkage control, and evacuation guidance, significantly improving the efficiency and safety of ship lock fire response.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and particularly to a method for ship lock fire emergency response and linkage control. Background Art

[0002] As a key facility for water transportation, a ship lock bears the heavy responsibility of regulating water levels and ensuring the safe passage of ships. Its fire safety is directly related to the stable operation of the water transportation system and the safety of personnel and property. With the expansion of the scale of modern ship locks and the increase in ship traffic, fire prevention and control have become an important issue for ensuring the safe operation of ship locks. Once a fire occurs, it may cause ship congestion, equipment damage, and even casualties. The rapid response and efficient coordination of the fire protection system are crucial for reducing losses. Therefore, studying the emergency linkage control system of ship lock fire protection devices is of great significance for improving the overall safety and operation efficiency of ship locks.

[0003] Currently, the design of ship lock fire protection systems mostly relies on single fire detection and manual operation modes, which have obvious limitations. These systems often only focus on the detection and alarm of fire signals and lack deep integration with the ship lock operation control system. During a fire, it is difficult for fire protection devices to achieve real-time coordination with operation links such as gate control and ship scheduling.

[0004] For example, after a fire signal is triggered, the existing system may only activate the sprinkler device but cannot automatically adjust the gate state or guide ship evacuation, resulting in low emergency response efficiency and even potentially exacerbating chaos due to improper operation. This lack of systematic coordination makes it difficult to effectively integrate fire protection response and ship lock operation safety. A deeper technical difficulty lies in how to achieve real-time linkage control among multiple devices after a fire signal is triggered. Ship lock operation involves multiple subsystems such as gate control, smoke exhaust fans, power management, and emergency lighting. These subsystems need to be precisely coordinated in a fire scenario.

[0005] However, there are technical obstacles to the rapid transmission of fire signals and the synchronous response of each subsystem. The identification and processing of fire signals require extremely high real-time performance. If the signal processing is delayed, it may cause the gate to not be adjusted to a safe state in time, thereby affecting the efficiency of ship evacuation. In addition, the control logic among each subsystem is complex, and it is necessary to ensure that fire protection requirements are prioritized in a fire scenario while avoiding non-fire protection equipment from interfering with emergency operations. For example, if the timing of cutting off non-fire protection power is not accurate, it may cause the emergency lighting or smoke exhaust fans not to start properly, thereby affecting the visibility and air quality at the fire site.

[0006] Therefore, how to achieve rapid transmission of fire signals and precise coordinated control among multiple subsystems after a fire signal is triggered has become a key issue for the emergency linkage control system of lock fire-fighting devices. In actual business scenarios, such as when a fire occurs in a densely populated area of ​​the lock, signal delays may cause the gates to fail to open in time, preventing ships from evacuating quickly, and the spread of smoke may further exacerbate the difficulty of rescue. This problem of insufficient coordination among multiple systems directly affects the lock's emergency response capabilities in the event of a fire, and has become a critical issue that urgently needs to be addressed. Summary of the Invention

[0007] The purpose of this invention is to provide a method for emergency response and linkage control of ship lock fires, so as to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for emergency response and linkage control of a ship lock fire, comprising the following steps:

[0009] S1. Real-time acquisition of environmental parameters within the lock area through environmental data acquisition devices, extraction of abnormal fluctuation characteristics, and obtaining preliminary fire early warning signals; S2. Based on the initial fire warning signal, multi-source sensor data is fused, noise interference is filtered, the strength of the refined fire warning signal is determined, and the initial fire warning signal triggers the acquisition of multi-source sensor data. S3. If the intensity of the fire warning signal exceeds the preset threshold, the emergency coordination module will be activated to send alarm instructions to the channel control device and the ship dispatching device and obtain response confirmation feedback. The preset threshold will be dynamically adjusted according to the lock water level and ship density. S4. A system coordination mechanism is adopted to process response confirmation feedback, synchronize channel control devices and ship scheduling devices, determine the equipment linkage operation sequence, and realize the coordinated operation of multiple devices through real-time data interaction and instruction allocation. S5. Generate a control logic chain based on the equipment linkage operation sequence, issue adjustment instructions to the channel control device, and obtain the channel safe opening status; S6. Based on the safe opening status of the passage, simultaneously activate the smoke exhaust ventilation equipment and emergency lighting equipment to optimize air circulation and visibility, and determine the evacuation guidance plan; S7. If the evacuation guidance plan is completed, non-essential circuits will be cut off through the power distribution device to ensure power supply to fire-fighting equipment and obtain emergency response assessment results.

[0010] Preferably, the environmental parameters in step S1 include temperature, humidity, and smoke concentration; Step S1 further includes: S11. Data processing is performed based on the original environmental parameters. The sliding window algorithm is used to smooth the temperature parameters, humidity parameters and smoke concentration data to obtain smoothed environmental data. The sliding window algorithm performs local averaging on the time series data. S12, If any parameter in the smoothed environmental data exceeds the preset threshold, the abnormal fluctuation feature is calculated by the feature extraction method, and the abnormal fluctuation feature is classified by the K-means algorithm to obtain the abnormal fluctuation classification result. S13: Generate a preliminary fire warning signal based on the abnormal fluctuation classification results. If the classification result is abnormal, output a warning signal through logical judgment to obtain the fire warning signal.

[0011] Preferably, the multi-source sensor data in step S2 includes infrared thermal imaging and gas detection data. The infrared thermal imaging sensor is used to capture the temperature distribution in the lock area, and the gas detection sensor is used to monitor the concentration of combustible gas. Step S2 further includes: S21. The mean filtering method is used to filter noise from the original multi-source sensor data to obtain the first dataset after noise reduction. S22. Based on the first dataset, the temperature data of infrared thermal imaging and the concentration data of gas detection are standardized using a data calibration algorithm to obtain the calibrated second dataset. S23. Extract temperature distribution features and gas concentration features from the second dataset, and use a weighted average method to perform multi-source fusion of temperature distribution features and gas concentration features to obtain a comprehensive feature set; S24. If the feature values ​​of the comprehensive feature set exceed the preset threshold, the support vector machine algorithm is used to classify the feature values ​​and determine the strength of the refined fire warning signal.

[0012] Preferably, in step S3, the channel control device includes a lock gate control system and a water level regulation system, the ship scheduling device is responsible for coordinating the entry, exit and berthing of ships, and the alarm instruction includes the warning signal strength, trigger time and abnormal area location.

[0013] Preferably, step S3 further includes: S31. Obtain lock water level and ship density data from real-time monitoring, generate and refine fire early warning signal strength through signal processing, and obtain signal strength value; S32. Based on the lock water level and ship density data, the preset threshold is dynamically adjusted using a preset threshold adjustment algorithm to determine the adjusted threshold. S33. If the intensity of the refining fire warning signal exceeds the adjusted preset threshold, the emergency coordination module is activated to send alarm commands to the channel control device and the ship dispatching device and obtain the sending status. S34: Obtain response confirmation feedback from the channel control device and the ship scheduling device, determine whether the alarm command was successfully transmitted by comparing the response confirmation feedback content, and obtain the transmission result.

[0014] Preferably, the system coordination mechanism in step S4 includes data synchronization, instruction generation, and priority sorting; Step S4 further includes: S41. Obtain real-time ship location data and equipment operation status data from the status monitoring module, transmit them to the channel control device through a real-time communication protocol, and use a synchronization mechanism to timestamp the data to obtain the real-time status information required for ship scheduling. S42. Based on the real-time status information, the channel control device generates ship dispatch instructions through a preset dispatch instruction template. If the deviation between the instruction generation timestamp and the real-time status information timestamp exceeds a preset threshold, the status monitoring data is reacquired to determine the valid dispatch instruction set. S43. Transmit the scheduling instruction set to the device linkage module through the data interaction interface, and use the system coordination algorithm to prioritize the scheduling instruction set to obtain the operation sequence of device linkage. S44. According to the operation sequence, the equipment linkage module sends the execution instruction to the ship dispatching device through the real-time communication protocol, obtains the feedback processing data after execution, judges whether the execution status meets the requirements of the dispatching instruction, and obtains the final response confirmation result.

[0015] Preferably, the status monitoring module includes radar, cameras, and position sensors, deployed in the lock channel and ship berthing area to track the ship's position and equipment operating status in real time.

[0016] Preferably, in step S5, the control logic chain integrates the equipment linkage operation sequence and the lock operation rules to generate precise instructions for the channel control device, ensuring the safe operation of the channel in fire emergency scenarios. Step S5 further includes: S51. Obtain the linkage triggering conditions and equipment status parameters from the equipment linkage operation sequence, match them using a preset logic rule base, and generate a control logic chain. The linkage triggering conditions include the fire warning signal strength, ship position, and water level status. S52. Based on the control logic chain, generate adjustment instructions for the channel control device and send the adjustment instructions to the channel control device through the instruction issuance mechanism. S53. If the channel control device returns equipment status parameters after receiving the adjustment command, the channel safety status is determined by comparing the real-time monitoring data with the preset safety status threshold. S54. When the channel safety status meets the preset channel operation mode, obtain the channel safety open status and determine the execution efficiency of the control logic chain.

[0017] Preferably, in step S6, the smoke exhaust ventilation equipment is used to reduce the smoke concentration, and the emergency lighting equipment is used to improve the visibility of the passageway; Step S6 further includes: S61. Obtain access control status data, extract the access control status and security detection trigger signal from the pre-established access control sensor database, determine whether the access control is in a secure open state, and obtain access control security status data; S62. Based on the safety status data of the passage, the equipment linkage control protocol is adopted, and the smoke exhaust ventilation equipment and emergency lighting equipment are started synchronously through real-time response speed detection to determine the equipment trigger time and operating status. S63. Obtain air quality parameters and smoke concentration data from the operation data of the smoke exhaust ventilation equipment, combine them with the ventilation direction optimization algorithm, adjust the operation parameters of the ventilation equipment, and obtain the air circulation optimization results; S64. Obtain the air circulation optimization results and light intensity adjustment data, and generate an evacuation guidance plan by using a path dynamic programming algorithm and combining it with dynamic guidance efficiency requirements, and determine the optimal evacuation path.

[0018] Preferably, the completion of the evacuation guidance plan in step S7 is determined by real-time monitoring data and the distribution status of personnel; Step S7 further includes: S71. Obtain evacuation guidance plan data from the emergency plan database, combine it with real-time monitoring data collected by status detection sensors, determine the distribution of people in the building and the fire alarm status, and generate the completion status of the evacuation guidance plan. S72. If the evacuation guidance plan is complete, then the circuit switching control is executed through the power distribution device to cut off the non-essential circuits and determine the completion status of the non-essential circuit cut-off. S73. Based on the completion status of non-essential circuit disconnection, load balancing is used to adjust the power supply priority of the power distribution device to ensure the power supply of fire-fighting equipment and obtain a stable power supply status for fire-fighting equipment. S74. By monitoring real-time data and the stable power supply status of fire-fighting equipment, and combining this with the emergency plan database, an emergency response assessment is conducted, and assessment results are generated.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention collects environmental data in real time through multi-source sensors (such as temperature, humidity, smoke concentration, infrared thermal imaging, and gas detection), and uses advanced data processing technologies such as sliding window algorithm, K-means classification, and support vector machine to perform noise filtering, feature extraction, and data fusion. This multi-level analysis can quickly identify abnormal fluctuations, generate refined fire early warning signals, and significantly reduce the risk of false alarms and missed alarms. Through a dynamic threshold adjustment mechanism, the system can adapt to changes in lock water level and ship density, ensuring that the early warning signal remains highly accurate in complex environments, thereby achieving early detection and rapid response to fires. 2. This invention uses a fire early warning signal to automatically activate subsystems such as channel control, ship scheduling, smoke extraction and ventilation, and emergency lighting through an emergency coordination module. It generates a sequence of linked operation operations for each device and employs a system coordination algorithm and real-time communication protocol to ensure rapid transmission of commands and feedback on execution status. In the event of a fire, the system can simultaneously close gates, guide ship evacuation, and activate smoke extraction equipment, avoiding confusion caused by manual operation or signal delays. This integrated linkage control solves the problem of insufficient integration in traditional systems, significantly improving emergency response efficiency and overall operational safety. 3. This invention generates the optimal evacuation guidance scheme through a path dynamic programming algorithm, combined with air circulation optimization and emergency lighting adjustment, to ensure that visibility and air quality in the passage meet evacuation requirements. At the same time, the power distribution device will cut off non-essential circuits, prioritize the power supply to fire-fighting equipment (such as smoke exhaust fans and emergency lights), and maintain power supply stability through load balancing. For example, after evacuation is completed, the system can automatically evaluate the response effect to ensure the continuous operation of fire-fighting equipment, thereby reducing the risk of casualties and equipment damage and improving the overall emergency response capability of the lock in a fire. Attached Figure Description

[0020] Figure 1 A flowchart of a preferred embodiment of the lock fire emergency response and linkage control method provided by the present invention; Figure 2 This is a flowchart of a method for processing raw environmental data provided by the present invention. Figure 3 This is a flowchart of a method for processing multi-source sensor data provided by the present invention; Figure 4 A flowchart of the method for dynamically adjusting a preset threshold provided by the present invention; Figure 5 A flowchart of the device linkage method provided by the present invention; Figure 6 This is a flowchart of a method for issuing adjustment commands to a channel control device provided by the present invention; Figure 7 A flowchart of the method for determining an evacuation guidance scheme provided by the present invention; Figure 8 The flowchart of the method for obtaining emergency response assessment results provided by the present invention is shown. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Please see Figures 1-8 As shown, a method for emergency response and linkage control in a ship lock fire includes the following steps: S1. Real-time acquisition of environmental parameters within the lock area through environmental data acquisition devices, extraction of abnormal fluctuation characteristics, and obtaining preliminary fire early warning signals; S2. Based on the initial fire warning signal, multi-source sensor data is fused, noise interference is filtered, the strength of the refined fire warning signal is determined, and the initial fire warning signal triggers the acquisition of multi-source sensor data. S3. If the intensity of the fire warning signal exceeds the preset threshold, the emergency coordination module will be activated to send alarm instructions to the channel control device and the ship dispatching device and obtain response confirmation feedback. The preset threshold will be dynamically adjusted according to the lock water level and ship density. S4. A system coordination mechanism is adopted to process response confirmation feedback, synchronize channel control devices and ship scheduling devices, determine the equipment linkage operation sequence, and realize the coordinated operation of multiple devices through real-time data interaction and instruction allocation. S5. Generate a control logic chain based on the equipment linkage operation sequence, issue adjustment instructions to the channel control device, and obtain the channel safe opening status; S6. Based on the safe opening status of the passage, simultaneously activate the smoke exhaust ventilation equipment and emergency lighting equipment to optimize air circulation and visibility, and determine the evacuation guidance plan; S7. If the evacuation guidance plan is completed, non-essential circuits will be cut off through the power distribution device to ensure power supply to fire-fighting equipment and obtain emergency response assessment results.

[0023] In step S1, environmental data acquisition devices are typically deployed in lock channels, control rooms, and ship berthing areas to ensure comprehensive coverage of the environmental monitoring range. The environmental data acquisition devices may include temperature sensors, humidity sensors, and smoke sensors. These sensors form an array and collect environmental parameters in real time through high-frequency sampling to generate raw environmental data. In step S11, data processing is performed based on the original environmental parameters. The sliding window algorithm is used to smooth the temperature parameters, humidity parameters, and smoke concentration data to obtain smoothed environmental data. The sliding window algorithm performs local averaging on the time series data.

[0024] Specifically, the size of the sliding window can be dynamically adjusted according to the rate of environmental change in the lock area; Step S12: If any parameter in the smoothed environmental data exceeds a preset threshold, abnormal fluctuation features are calculated using a feature extraction method. The K-means algorithm is then used to classify the abnormal fluctuation features to obtain the abnormal fluctuation classification result. The preset thresholds are determined based on the operating environment and historical data of the lock area. For example, the temperature threshold can be set to 50 degrees Celsius, the humidity threshold to 90% relative humidity, and the smoke concentration threshold to 200 micrograms per cubic meter. If any parameter exceeds the threshold, the system triggers the feature extraction process. The K-means algorithm is used to classify the abnormal fluctuation feature vector into two categories: normal and abnormal. In its implementation, the system pre-trains a K-means model based on historical environmental data to determine cluster centers for normal and abnormal states. During real-time detection, the distance between the current feature vector and the cluster center is compared, and the vector is assigned to the nearest category. For example, if a feature vector at a certain moment includes a temperature change rate of 0.5 degrees Celsius per second, a peak smoke concentration of 300 micrograms per cubic meter, and a fluctuation range of 20 micrograms per cubic meter, and is close to an abnormal cluster center, it is classified as abnormal. This classification method can quickly distinguish between normal environmental fluctuations and potential fire risks, improving the accuracy of early warnings. In one possible implementation, the K-means algorithm can introduce a dynamic cluster center update mechanism, periodically adjusting the cluster centers based on the latest collected environmental data to adapt to seasonal or long-term environmental changes in the lock area.

[0025] Step S13: Generate a preliminary fire warning signal based on the abnormal fluctuation classification results. If the classification result is abnormal, output a warning signal through logical judgment to obtain a fire warning signal. The logical judgment is based on the classification results and preset rules. If the K-means algorithm outputs an abnormality, generate a warning signal containing a timestamp, abnormal parameter type, and abnormality degree. The warning signal is transmitted to the subsequent processing module through an internal communication protocol to ensure rapid response.

[0026] In step S2, the sensor data is transmitted to the processing unit in real time via a high-speed data bus. The acquisition frequency is usually twice per second to ensure the timeliness of the data.

[0027] Step S21: The original multi-source sensor data is filtered for noise using the mean filtering method to obtain the first dataset after noise reduction. The mean filtering eliminates noise caused by environmental interference or sensor jitter by calculating the average value of the data within the time window.

[0028] Step S22: Based on the first dataset, the temperature data from infrared thermal imaging and the concentration data from gas detection are standardized using a data calibration algorithm to obtain a calibrated second dataset. The data calibration algorithm eliminates dimensional differences between different sensors through normalization processing, ensuring that the temperature and gas concentration data are fused on a unified scale in subsequent steps.

[0029] Step S23: Extract temperature distribution features and gas concentration features from the second dataset, and use a weighted average method to perform multi-source fusion of temperature distribution features and gas concentration features to obtain a comprehensive feature set; temperature distribution features include the area of ​​the heat source region, the highest temperature, and the temperature gradient; gas concentration features include the concentration peak, the rate of change, and the uniformity of distribution.

[0030] Step S24: If the feature value of the comprehensive feature set exceeds the preset threshold, the support vector machine algorithm is used to classify the feature value and determine the intensity of the refined fire warning signal; the preset threshold is determined based on historical fire data and the lock operation environment.

[0031] The implementation methods of steps S1 to S2 have been described in detail, covering environmental data collection, abnormal fluctuation feature extraction, multi-source data fusion, and determination of the intensity of refined fire early warning signals. These steps, through multi-level data processing and analysis, have enabled accurate monitoring of fire risks in the lock area, providing a reliable basis for subsequent emergency response.

[0032] In step S3, the channel control device typically includes a lock gate control system and a water level regulation system, while the ship scheduling device is responsible for coordinating the entry, exit, and berthing of ships; the alarm instruction includes the warning signal strength, trigger time, and location of the abnormal area.

[0033] Step S31: Obtain lock water level and ship density data from real-time monitoring, generate refined fire warning signal strength through signal processing, and obtain signal strength value; lock water level data is collected by water level sensors installed on both sides of the lock. The sensors usually adopt the ultrasonic ranging principle, with a measurement accuracy of 0.01 meters, which can reflect water level changes in real time.

[0034] Step S32: Based on the lock water level and ship density data, a preset threshold is dynamically adjusted using a preset threshold adjustment algorithm to determine the adjusted threshold. The preset threshold adjustment algorithm is designed based on the dynamic characteristics of the lock operating environment.

[0035] Step S33: If the intensity of the fire warning signal exceeds the adjusted preset threshold, the emergency coordination module is activated to send an alarm command to the channel control device and the ship dispatching device and obtain the sending status; the signal intensity is compared with the adjusted threshold, and if it exceeds the threshold, the emergency coordination module immediately generates an alarm command.

[0036] Step S34: Obtain response confirmation feedback from the channel control device and the ship scheduling device, and determine whether the alarm command was successfully transmitted by comparing the content of the response confirmation feedback to obtain the transmission result; the response confirmation feedback includes the device execution status and the command reception timestamp.

[0037] In step S4, a system coordination mechanism is used to process response confirmation feedback, synchronize the channel control device and the ship scheduling device, and determine the equipment linkage operation sequence; the system coordination mechanism realizes coordinated operation among multiple devices through real-time data interaction and instruction allocation.

[0038] Step S41: Obtain real-time ship position data and equipment operation status data from the status monitoring module, transmit them to the channel control device through a real-time communication protocol, and use a synchronization mechanism to timestamp the data to obtain the real-time status information required for ship scheduling; the status monitoring module includes radar, camera and position sensor, which are deployed in the lock channel and ship berthing area to track ship position and equipment operation status in real time.

[0039] Step S42: Based on the real-time status information, the channel control device generates ship scheduling instructions through a preset scheduling instruction template. If the deviation between the instruction generation timestamp and the real-time status information timestamp exceeds a preset threshold, the status monitoring data is reacquired to determine the valid scheduling instruction set. The scheduling instruction template is designed based on the lock operation rules.

[0040] Step S43: The scheduling instruction set is transmitted to the device linkage module through the data interaction interface. The scheduling instruction set is prioritized using a system collaborative algorithm to obtain the operation sequence of device linkage. The data interaction interface adopts a standardized communication protocol.

[0041] In step S44, according to the operation sequence, the equipment linkage module sends an execution command to the ship dispatching device through a real-time communication protocol, obtains feedback processing data after execution, determines whether the execution status meets the requirements of the dispatching command, and obtains the final response confirmation result. The equipment linkage module sends the execution command through a high-speed communication link.

[0042] Step S5 also includes step S51, which involves obtaining the linkage triggering conditions and equipment status parameters from the equipment linkage operation sequence, matching them using a preset logic rule base, and generating a control logic chain; the linkage triggering conditions include the fire warning signal strength, the ship's position, and the water level status.

[0043] Step S52: Based on the control logic chain, an adjustment command is generated for the channel control device, and the adjustment command is sent to the channel control device through the command issuance mechanism.

[0044] Step S53: If the channel control device returns equipment status parameters after receiving the adjustment command, the channel safety status is determined by comparing the real-time monitoring data with the preset safety status threshold. The equipment status parameters include the actual opening and closing status of the lock gate, the real-time value of the water level adjustment, etc.

[0045] Step S54: When the channel safety status meets the preset channel operation mode, obtain the channel safety open status and determine the execution efficiency of the control logic chain; the channel operation mode includes normal operation, emergency isolation and backup channel mode.

[0046] In step S6, the safe opening status of the passage triggers the coordinated operation of the smoke exhaust ventilation equipment and emergency lighting equipment to improve air quality and visibility in the fire area and provide support for personnel evacuation. It also includes step S61, which obtains passage access control status data, extracts passage opening status and safety detection trigger signals from a pre-established access control sensor database, determines whether the passage is in a safe opening state, and obtains passage safety status data; the access control sensors are deployed at key nodes of the lock passage.

[0047] Step S62: Based on the channel safety status data, the equipment linkage control protocol is adopted to synchronously start the smoke exhaust ventilation equipment and emergency lighting equipment through real-time response speed detection, and the equipment trigger time and operating status are determined; the equipment linkage control protocol defines the start-up sequence and parameters of the smoke exhaust ventilation equipment and emergency lighting equipment.

[0048] Step S63: Obtain air quality parameters and smoke concentration data from the smoke exhaust ventilation equipment's operating data. Combine this with the ventilation direction optimization algorithm to adjust the ventilation equipment's operating parameters and obtain optimized airflow results. Air quality parameters include PM2.5 concentration and carbon monoxide concentration, while smoke concentration data is obtained through the aforementioned smoke sensor. The ventilation direction optimization algorithm determines the optimal smoke exhaust direction based on the channel structure and fire location.

[0049] Step S64: Obtain the air circulation optimization results and light intensity adjustment data. Using the path dynamic planning algorithm and combined with the dynamic guidance efficiency requirements, generate an evacuation guidance plan and determine the optimal evacuation path. The path dynamic planning algorithm calculates the shortest path from the fire area to the safety exit based on the channel structure diagram and real-time environmental data. The light intensity adjustment data is collected through emergency lighting equipment.

[0050] In step S7, the completion of the evacuation guidance plan is determined by real-time monitoring data and the distribution status of personnel. It also includes step S71, which retrieves evacuation guidance plan data from the emergency plan database, combines it with real-time monitoring data collected by status detection sensors, determines the distribution of personnel and fire alarm status within the building, and generates the completion status of the evacuation guidance plan; the emergency plan database stores predefined evacuation routes and rules.

[0051] Step S72: If the evacuation guidance plan is complete, then the circuit switching control is executed through the power distribution device to cut off the non-essential circuits and determine the completion status of the non-essential circuit cut-off; the circuit switching control is implemented through the relay module.

[0052] Step S73: Based on the completion status of non-essential circuit disconnection, load balancing is used to adjust the power supply priority of the power distribution device to ensure the power supply of fire-fighting equipment and obtain a stable power supply status for the fire-fighting equipment; load balancing optimizes power distribution by analyzing equipment power consumption and power supply capacity.

[0053] Step S74 involves performing an emergency response assessment by real-time monitoring data and the stable power supply status of fire-fighting equipment, combined with the emergency plan database, and generating assessment results. The emergency response assessment is based on evacuation completion time, fire control effectiveness, and equipment operational stability. For example, if evacuation takes 5 minutes, the smoke concentration in the fire area drops to a safe level, and the fire-fighting equipment operates normally, the assessment result is excellent. For instance, in a lock fire emergency scenario, the system generates an assessment report including evacuation efficiency, equipment response time, and fire control effectiveness, providing data support for subsequent optimization. In one possible implementation, the assessment results can also be compared with historical data to identify potential areas for improvement in the emergency response, such as shortening equipment response time or optimizing evacuation routes. Thus, the implementation methods of steps S3 to S7 have been described in detail, covering fire warning signal processing, equipment linkage, channel control, environmental optimization, and emergency response assessment. These steps, through multi-level collaboration and data processing, achieve rapid response and effective control of lock fires, ensuring personnel safety and stable equipment operation.

[0054] 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 a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0055] 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, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for emergency response and linkage control in a ship lock fire, characterized in that, Includes the following steps: S1. Real-time acquisition of environmental parameters within the lock area through environmental data acquisition devices, extraction of abnormal fluctuation characteristics, and obtaining preliminary fire early warning signals; S2. Based on the initial fire warning signal, multi-source sensor data is fused, noise interference is filtered, the strength of the refined fire warning signal is determined, and the initial fire warning signal triggers the acquisition of multi-source sensor data. S3. If the intensity of the fire warning signal exceeds the preset threshold, the emergency coordination module will be activated to send alarm instructions to the channel control device and the ship dispatching device and obtain response confirmation feedback. The preset threshold will be dynamically adjusted according to the lock water level and ship density. S4. A system coordination mechanism is adopted to process response confirmation feedback, synchronize channel control devices and ship scheduling devices, determine the equipment linkage operation sequence, and realize the coordinated operation of multiple devices through real-time data interaction and instruction allocation. S5. Generate a control logic chain based on the equipment linkage operation sequence, issue adjustment instructions to the channel control device, and obtain the channel safe opening status; S6. Based on the safe opening status of the passage, simultaneously activate the smoke exhaust ventilation equipment and emergency lighting equipment to optimize air circulation and visibility, and determine the evacuation guidance plan; S7. If the evacuation guidance plan is completed, non-essential circuits will be cut off through the power distribution device to ensure power supply to fire-fighting equipment and obtain emergency response assessment results.

2. The emergency response and linkage control method for a ship lock fire according to claim 1, characterized in that: The environmental parameters in step S1 include temperature, humidity, and smoke concentration; Step S1 further includes: S11. Data processing is performed based on the original environmental parameters. The sliding window algorithm is used to smooth the temperature parameters, humidity parameters and smoke concentration data to obtain smoothed environmental data. The sliding window algorithm performs local averaging on the time series data. S12, If any parameter in the smoothed environmental data exceeds the preset threshold, the abnormal fluctuation feature is calculated by the feature extraction method, and the abnormal fluctuation feature is classified by the K-means algorithm to obtain the abnormal fluctuation classification result. S13: Generate a preliminary fire warning signal based on the abnormal fluctuation classification results. If the classification result is abnormal, output a warning signal through logical judgment to obtain the fire warning signal.

3. The emergency response and linkage control method for a ship lock fire according to claim 1, characterized in that: The multi-source sensor data in step S2 includes infrared thermal imaging and gas detection data. The infrared thermal imaging sensor is used to capture the temperature distribution in the lock area, and the gas detection sensor is used to monitor the concentration of combustible gas. Step S2 further includes: S21. The mean filtering method is used to filter noise from the original multi-source sensor data to obtain the first dataset after noise reduction. S22. Based on the first dataset, the temperature data of infrared thermal imaging and the concentration data of gas detection are standardized using a data calibration algorithm to obtain the calibrated second dataset. S23. Extract temperature distribution features and gas concentration features from the second dataset, and use a weighted average method to perform multi-source fusion of temperature distribution features and gas concentration features to obtain a comprehensive feature set; S24. If the feature values ​​of the comprehensive feature set exceed the preset threshold, the support vector machine algorithm is used to classify the feature values ​​and determine the strength of the refined fire warning signal.

4. The emergency response and linkage control method for a ship lock fire according to claim 1, characterized in that: In step S3, the channel control device includes a lock gate control system and a water level regulation system. The ship scheduling device is responsible for coordinating the entry, exit, and berthing of ships. The alarm command includes the warning signal strength, trigger time, and location of the abnormal area.

5. The emergency response and linkage control method for a ship lock fire according to claim 1, characterized in that: Step S3 further includes: S31. Obtain lock water level and ship density data from real-time monitoring, generate and refine fire early warning signal strength through signal processing, and obtain signal strength value; S32. Based on the lock water level and ship density data, the preset threshold is dynamically adjusted using a preset threshold adjustment algorithm to determine the adjusted threshold. S33. If the intensity of the refining fire warning signal exceeds the adjusted preset threshold, the emergency coordination module is activated to send alarm commands to the channel control device and the ship dispatching device and obtain the sending status. S34: Obtain response confirmation feedback from the channel control device and the ship scheduling device, determine whether the alarm command was successfully transmitted by comparing the response confirmation feedback content, and obtain the transmission result.

6. The emergency response and linkage control method for a ship lock fire according to claim 1, characterized in that: The system coordination mechanism in step S4 includes data synchronization, instruction generation, and priority sorting. Step S4 further includes: S41. Obtain real-time ship location data and equipment operation status data from the status monitoring module, transmit them to the channel control device through a real-time communication protocol, and use a synchronization mechanism to timestamp the data to obtain the real-time status information required for ship scheduling. S42. Based on the real-time status information, the channel control device generates ship dispatch instructions through a preset dispatch instruction template. If the deviation between the instruction generation timestamp and the real-time status information timestamp exceeds a preset threshold, the status monitoring data is reacquired to determine the valid dispatch instruction set. S43. Transmit the scheduling instruction set to the device linkage module through the data interaction interface, and use the system coordination algorithm to prioritize the scheduling instruction set to obtain the operation sequence of device linkage. S44. According to the operation sequence, the equipment linkage module sends the execution instruction to the ship dispatching device through the real-time communication protocol, obtains the feedback processing data after execution, judges whether the execution status meets the requirements of the dispatching instruction, and obtains the final response confirmation result.

7. The emergency response and linkage control method for a ship lock fire according to claim 6, characterized in that: The status monitoring module includes radar, cameras, and position sensors, and is deployed in the lock channel and ship berthing area to track the ship's position and equipment operating status in real time.

8. The emergency response and linkage control method for a ship lock fire according to claim 1, characterized in that: In step S5, the control logic chain integrates the equipment linkage operation sequence and the lock operation rules to generate precise instructions for the channel control device, ensuring the safe operation of the channel in fire emergency scenarios. Step S5 further includes: S51. Obtain the linkage triggering conditions and equipment status parameters from the equipment linkage operation sequence, match them using a preset logic rule base, and generate a control logic chain. The linkage triggering conditions include the fire warning signal strength, ship position, and water level status. S52. Based on the control logic chain, generate adjustment instructions for the channel control device and send the adjustment instructions to the channel control device through the instruction issuance mechanism. S53. If the channel control device returns equipment status parameters after receiving the adjustment command, the channel safety status is determined by comparing the real-time monitoring data with the preset safety status threshold. S54. When the channel safety status meets the preset channel operation mode, obtain the channel safety open status and determine the execution efficiency of the control logic chain.

9. The emergency response and linkage control method for a ship lock fire according to claim 1, characterized in that: In step S6, the smoke exhaust ventilation equipment is used to reduce the smoke concentration, and the emergency lighting equipment is used to improve the visibility of the passage. Step S6 further includes: S61. Obtain access control status data, extract the access control status and security detection trigger signal from the pre-established access control sensor database, determine whether the access control is in a secure open state, and obtain access control security status data; S62. Based on the safety status data of the passage, the equipment linkage control protocol is adopted, and the smoke exhaust ventilation equipment and emergency lighting equipment are started synchronously through real-time response speed detection to determine the equipment trigger time and operating status. S63. Obtain air quality parameters and smoke concentration data from the operation data of the smoke exhaust ventilation equipment, combine them with the ventilation direction optimization algorithm, adjust the operation parameters of the ventilation equipment, and obtain the air circulation optimization results; S64. Obtain the air circulation optimization results and light intensity adjustment data, and generate an evacuation guidance plan by using a path dynamic programming algorithm and combining it with dynamic guidance efficiency requirements, and determine the optimal evacuation path.

10. The emergency response and linkage control method for a ship lock fire according to claim 1, characterized in that: The completion of the evacuation guidance plan in step S7 is determined by real-time monitoring data and the distribution status of personnel. Step S7 further includes: S71. Obtain evacuation guidance plan data from the emergency plan database, combine it with real-time monitoring data collected by status detection sensors, determine the distribution of people in the building and the fire alarm status, and generate the completion status of the evacuation guidance plan. S72. If the evacuation guidance plan is complete, then the circuit switching control is executed through the power distribution device to cut off the non-essential circuits and determine the completion status of the non-essential circuit cut-off. S73. Based on the completion status of non-essential circuit disconnection, load balancing is used to adjust the power supply priority of the power distribution device to ensure the power supply of fire-fighting equipment and obtain a stable power supply status for fire-fighting equipment. S74. By monitoring real-time data and the stable power supply status of fire-fighting equipment, and combining this with the emergency plan database, an emergency response assessment is conducted, and assessment results are generated.

Images