Intelligent alarm system for ship

Abstract

The invention discloses an intelligent alarm system for a ship, and aims to overcome the defects of an existing alarm system for the ship and improve the sailing safety of the ship. The system comprises modules of data acquisition, preprocessing, analysis, alarm decision, output, user interaction, storage and the like. The data acquisition module collects ship key parts and system operation data by means of various sensors, and after operations of filtering, amplification, analog-to-digital conversion and the like of the preprocessing module, the data analysis module performs real-time analysis by applying models such as machine learning fault diagnosis, statistical trend analysis, rule threshold judgment and the like, and the operation state and potential fault hidden danger are accurately identified. The alarm decision module gives an alarm according to an analysis result and a preset strategy decision, and gives an alarm in the modes of sound and light, display, short messages, satellite communication and the like through the output module. The user interaction module facilitates operation and information interaction of sailors, the data storage module stores data for subsequent maintenance management and the like, and all the modules work cooperatively to guarantee safe and efficient operation of the ship.

Description

Technical Field

[0001] The present invention relates to the field of ship safety, and specifically to a ship intelligent alarm system. Background Art

[0002] During the navigation of a ship, it will face various potential dangers and fault situations, such as fires, water leakage, mechanical failures, collision risks, etc. Traditional ship alarm systems often have a single function and can only perform simple threshold alarms for specific types of dangerous situations. They cannot monitor the operating status of the ship in real time and comprehensively, and there are deficiencies in the accuracy, timeliness, and intelligent processing of alarm information. For example, when a ship has a slight mechanical abnormal vibration, the traditional alarm system may not be able to detect it in time because it has not reached the preset fixed threshold, and an alarm is only issued when the fault becomes serious, at which time it may have had a greater impact on the safe navigation of the ship. In addition, different types of ships have differences in structure, equipment configuration, and operating environment, and there are also relatively high personalized requirements for the alarm system, but the existing alarm systems are difficult to meet such diverse needs. Therefore, it is of great practical significance to develop a system that can monitor various operating parameters of a ship in real time, perform intelligent analysis, and give accurate and timely alarms. Summary of the Invention

[0003] The purpose of the present invention is to provide a ship intelligent alarm system to solve the problems raised in the above background art.

[0004] To achieve the above purpose, the present invention provides the following technical solution: A ship intelligent alarm system includes a data acquisition module, a data preprocessing module, a data analysis module, an alarm decision module, an alarm output module, a user interaction module, and a data storage module. The data acquisition module is used to collect the operating data of various key parts and systems on the ship, including but not limited to temperature, pressure, liquid level, vibration, smoke concentration, gas concentration, ship position, speed, heading, and the working current and voltage parameters of each device. The data acquisition module is distributed in the engine room, cargo hold, cab, and living area of the ship through various types of sensors, and a wired or wireless communication method is used to connect the sensors to the data acquisition module to ensure the stable transmission of data;

[0005] The data preprocessing module preprocesses the data transmitted from the data acquisition module, including data filtering, amplification, and analog-to-digital conversion operations, removes noise interference, and converts analog signals into digital signals for subsequent analysis and processing; at the same time, a preliminary integrity and rationality check is performed on the data, and obviously abnormal or missing data is marked or repaired;

[0006] The data analysis module uses a preset intelligent algorithm to perform real-time analysis on the preprocessed data. The data analysis module is built-in with a variety of data analysis models, specifically a fault diagnosis model based on machine learning, a trend analysis model based on statistics, and a threshold judgment model based on rules. By learning historical data and dynamically monitoring real-time data, it accurately identifies the operating status of each ship system and discovers potential fault hazards and abnormal conditions in advance.

[0007] The alarm decision-making module makes an alarm decision based on the analysis results of the data analysis module, combined with the current operating status of the ship and the preset alarm strategy. The alarm strategy is personalized according to factors such as the type, use, and navigation area of the ship, including the alarm level, alarm method, and alarm receiving object corresponding to different fault types and danger levels.

[0008] The alarm output module is responsible for outputting the alarm information generated by the alarm decision-making module in multiple ways, including audible and visual alarms, display screen prompts, SMS notifications, and satellite communication alarms. The alarm output module sets audible and visual alarms at key positions in the ship's cab, engine room, and crew living area. When an alarm information is generated, it emits a strong audible and visual signal to attract the attention of the crew. At the same time, it details the alarm location, type, severity, and relevant handling suggestion information on the ship's monitoring display screen, facilitating the crew to quickly understand the situation and take corresponding measures.

[0009] The user interaction module provides an interface for the crew to interact with the alarm system. The crew can view the real-time operating data of the ship, historical alarm records, and the setting parameter information of the alarm system through this module, and also perform manual tests, parameter adjustments, and operations to add or modify personalized alarm rules on the alarm system. The user interaction module has an alarm information confirmation and feedback function. After the crew processes an alarm event, they feedback the processing result to the alarm output module through the user interaction module, so that the system can record and analyze the alarm event, continuously optimize the alarm strategy, and improve the performance of the system.

[0010] The data storage module is used to store the collected ship operating data, alarm records, data analysis models, and various configuration parameter information of the system. The data storage module uses a large-capacity storage device and has data backup and recovery functions to ensure the security and integrity of the data. By storing and analyzing historical data for a long time, it provides data support for the maintenance, fault diagnosis, and performance optimization of the ship.

[0011] Preferably, the data acquisition module includes temperature sensors, pressure sensors, liquid level sensors, vibration sensors, smoke concentration sensors, gas concentration sensors, ship position, speed and heading sensors, and equipment working current and voltage sensors.

[0012] Preferably, the preprocessing of the data preprocessing module specifically includes the following:

[0013] Data filtering: Perform filtering operations on the data transmitted from the data acquisition module. For some physical quantities that change relatively slowly, low-pass filtering is used to remove high-frequency noise; for rapidly changing parameters, high-pass filtering is used to remove low-frequency interference signals; for specific noise frequency distributions and the data frequency ranges to be retained, band-pass filtering or band-stop filtering is used to remove interference signals.

[0014] Amplification operation: A preamplifier is set near the sensor in the data acquisition module to preliminarily amplify the weak signal output by the sensor; then, according to actual needs, a multi-stage amplification circuit is used to gradually amplify the signal; during each stage of amplification, the amplification factor and bandwidth are selected to avoid signal distortion and introduce too much noise. Among them, good shielding and grounding treatment should be carried out on the amplification circuit to prevent external interference from affecting the amplified signal.

[0015] Analog-to-digital conversion: Sample the analog signal collected by the data acquisition module, and discretely sample the analog signal at a certain time interval; the selection of the sampling frequency should follow the Nyquist sampling theorem, that is, the sampling frequency must be greater than twice the highest frequency of the analog signal to ensure that the original analog signal can be accurately restored; the amplitude of the sampled analog signal is quantized, that is, the continuous amplitude range is divided into several discrete quantization levels, and the number of quantization bits determines the amplitude accuracy that the digital signal can represent; finally, the quantized signal is converted into a digital coding form, usually using binary coding, for storage, transmission, and processing in a digital system.

[0016] Preferably, the data analysis module specifically includes the following steps:

[0017] Step 1, data collection and feature extraction: Obtain the historical data of the long-term operation of various equipment in the engine room from the data storage module, including vibration, temperature, pressure, current, and voltage parameters. For vibration data, the time-domain signal is converted into a frequency-domain signal through the fast Fourier transform method, and features such as the frequency and amplitude of vibration are extracted; for temperature data, in addition to recording the actual temperature value, the change rate and fluctuation range characteristics over time are also analyzed; for electrical parameters, the harmonic components and three-phase unbalance characteristics of current and voltage are extracted. The above features are used as the input of the machine learning model to comprehensively reflect the operating state of the equipment.

[0018] Step 2, Model Training: Using a supervised learning algorithm for model training. First, divide the historical data in the data storage module into two categories: normal operation data and fault data, and label them. Then use the normal operation data to train the model so that it learns the characteristic patterns during normal operation of the equipment. Next, use the fault data to verify and optimize the model, and adjust the model parameters to improve the model's ability to identify faults.

[0019] Step 3, Real-time Fault Diagnosis: During the operation of the ship, after collecting and preprocessing the data of the equipment in real time, input it into the trained machine learning model. The model calculates the probability that the equipment is in a normal or faulty state based on the characteristics of the input data. If the model determines that there is a risk of equipment failure, it will further analyze the type and severity of the fault.

[0020] Preferably, the user interaction module specifically includes the following:

[0021] Information Viewing Function: Real-time Operation Data Viewing: Crew members can directly view the real-time operation data of various key parts and systems of the ship through the display screen of the user interaction module. The above data is presented in a clear and easy-to-understand chart or digital form; Historical Alarm Record Query: Crew members can query all alarm records within a certain period of time in the past. The system displays the alarm events in a list in chronological order, and each record includes the time, location, type, severity of the alarm, and detailed information about the ship's operation status at that time; Alarm System Setting Parameter Viewing: The user interaction module allows crew members to view various setting parameters of the alarm system, including the acquisition frequency of each sensor, the filtering parameters for data preprocessing, the threshold settings of the data analysis model, the output method of the alarm, and the level definition.

[0022] System Operation Function: Manual Test Function: Crew members can manually test the alarm system through the user interaction module to check whether all components of the system are working properly; Parameter Adjustment Function: Crew members can adjust the parameters of the alarm system according to different operation stages of the ship, different navigation environments, and equipment aging factors; Personalized Alarm Rule Adding and Modifying Function: Different types of ships have different safety requirements and concerns during operation. The user interaction module allows crew members to add or modify personalized alarm rules according to the actual situation of the ship.

[0023] Alarm information confirmation and feedback function: Alarm information confirmation function: When the alarm system issues an alarm, the crew will receive prominent alarm prompt information on the display screen of the user interaction module, including the specific content of the alarm, the location where it occurred, and the severity, etc. After learning the alarm information, the crew needs to perform a confirmation operation to inform the system that the alarm has been received and corresponding measures are being taken for handling. This confirmation operation is completed by clicking the confirmation button on the display screen, entering a password, or fingerprint recognition to ensure that only authorized crew members can perform the confirmation operation and prevent misoperation or failure to confirm in a timely manner. Once the alarm information is confirmed, the system will record the confirmation time and the information of the confirming person, stop the continuous reminder of the audible and visual alarm, and at the same time feedback the confirmation information to the alarm decision-making module; Alarm handling result feedback function: After the crew has handled the alarm event, the handling result is fed back to the alarm system through the user interaction module. The feedback information includes the cause of the fault, the maintenance measures taken, the maintenance time, and the detailed content of whether the equipment has returned to normal operation.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows: The intelligent alarm system of the present invention can comprehensively and real-time monitor and collect various types of operating parameters on the ship. Through advanced data analysis technology and intelligent algorithms, it can discover potential fault hazards and abnormal situations in advance, improve the timeliness and accuracy of alarms, and provide a strong guarantee for the safe navigation of the ship.

[0025] The system has the characteristics of high intelligence and personalization. Through learning and analyzing historical data, the intelligent algorithm can continuously optimize itself to adapt to the changes of ship equipment and operating environment; at the same time, the alarm strategy can be personalized according to factors such as the specific type, use, and navigation area of the ship to meet the diverse needs of different ships.

[0026] The combination of multiple alarm output methods ensures that the crew can receive alarm information in a timely and accurate manner regardless of their location on the ship or their working state. Audible and visual alarms, display screen prompts, SMS notifications, and satellite communication alarms, etc., complement each other, effectively improving the transmission efficiency of alarm information and avoiding safety accidents caused by poor information transmission.

[0027] The user interaction module provides a convenient operation interface for the crew, enabling them to easily view ship operation data, alarm records, and set and manage the system. At the same time, the system has a permission management function, ensuring the safety and stability of operations and preventing misoperations from having an adverse impact on ship operation.

[0028] The data storage module can not only store the ship operation data and alarm information for a long time, but also conduct data interaction and sharing with other ship information systems, realizing the integrated management of ship information, providing rich data support for ship maintenance, performance optimization and comprehensive decision-making, and helping to improve the overall operation efficiency and management level of the ship. Brief Description of the Drawings

[0029] Figure 1 It is a schematic diagram of the overall system structure of the present invention. Detailed Embodiments

[0030] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0031] Please refer to Figure 1 , the present invention provides a technical solution: an intelligent ship alarm system, including a data acquisition module, a data preprocessing module, a data analysis module, an alarm decision module, an alarm output module, a user interaction module and a data storage module. The data acquisition module is used to collect the operation data of various key parts and systems on the ship, including but not limited to temperature, pressure, liquid level, vibration, smoke concentration, gas concentration, ship position, speed, heading, and the working current and voltage parameters of each device. The data acquisition module is distributed in the engine room, cargo hold, cab, and living area of the ship through various types of sensors, and a wired or wireless communication method is used to connect the sensors and the data acquisition module to ensure stable data transmission; the data acquisition module includes a temperature sensor, a pressure sensor, a liquid level sensor, a vibration sensor, a smoke concentration sensor, a gas concentration sensor, a ship position, speed and heading sensor, and a device working current and voltage sensor;

[0032] The data preprocessing module preprocesses the data transmitted by the data acquisition module, including data filtering, amplification, and analog-to-digital conversion operations, removing noise interference, and converting analog signals into digital signals for subsequent analysis and processing; at the same time, a preliminary integrity and rationality check is performed on the data, and obvious abnormal or missing data is marked or repaired;

[0033] The preprocessing of the data preprocessing module specifically includes the following contents:

[0034] Data filtering: Filter the data transmitted from the data acquisition module. For some physical quantities that change relatively slowly, low-pass filtering is used to remove high-frequency noise; for rapidly changing parameters, high-pass filtering is used to remove low-frequency interference signals; for the specific noise frequency distribution and the data frequency range to be retained, band-pass filtering or band-stop filtering is used to remove interference signals;

[0035] Amplification operation: A preamplifier is set near the sensor in the data acquisition module to preliminarily amplify the weak signal output by the sensor; then, according to actual needs, a multi-stage amplification circuit is used to gradually amplify the signal; during each stage of amplification, the amplification factor and bandwidth are selected to avoid signal distortion and introduce too much noise. Among them, good shielding and grounding treatment should be carried out on the amplification circuit to prevent external interference from affecting the amplified signal;

[0036] Analog-to-digital conversion: Sample the analog signal collected by the data acquisition module, and discretely sample the analog signal at a certain time interval; the selection of the sampling frequency should follow the Nyquist sampling theorem, that is, the sampling frequency must be greater than twice the highest frequency of the analog signal to ensure that the original analog signal can be accurately restored; the amplitude of the sampled analog signal is quantized, that is, the continuous amplitude range is divided into several discrete quantization levels, and the number of quantization bits determines the amplitude accuracy that the digital signal can represent; finally, the quantized signal is converted into a digital coding form, usually using binary coding, for storage, transmission, and processing in a digital system

[0037] The data analysis module uses a preset intelligent algorithm to perform real-time analysis on the preprocessed data. The data analysis module is built-in with a variety of data analysis models, specifically a fault diagnosis model based on machine learning, a trend analysis model based on statistics, and a threshold judgment model based on rules; through the learning of historical data and the dynamic monitoring of real-time data, accurately identify the operating status of each system of the ship, and discover potential fault hazards and abnormal conditions in advance;

[0038] The data analysis module specifically includes the following steps:

[0039] Step 1, data collection and feature extraction: Obtain the historical data of the long-term operation of various equipment in the engine room from the data storage module, including vibration, temperature, pressure, current, and voltage parameters. For vibration data, the time-domain signal is converted into a frequency-domain signal by the fast Fourier transform method, and features such as vibration frequency and amplitude are extracted; for temperature data, in addition to recording the actual temperature value, its change rate and fluctuation range characteristics over time are also analyzed; for electrical parameters, the harmonic components and three-phase unbalance characteristics of current and voltage are extracted. The above features are used as the input of the machine learning model to comprehensively reflect the operating status of the equipment;

[0040] Step 2: Model Training: Using the supervised learning algorithm, conduct model training. First, divide the historical data in the data storage module into two categories: normal operation data and fault data, and perform annotation. Use the normal operation data to train the model so that it learns the characteristic patterns during normal operation of the equipment. Then, use the fault data to verify and optimize the model, and adjust the parameters of the model to improve the model's fault recognition ability.

[0041] Step 3: Real-time Fault Diagnosis: During the operation of the ship, after collecting and preprocessing the data of the equipment in real time, input it into the trained machine learning model. The model calculates the probability that the equipment is in a normal or faulty state based on the characteristics of the input data. If the model determines that there is a fault risk in the equipment, it will further analyze the fault type and severity.

[0042] The alarm decision-making module makes an alarm decision based on the analysis results of the data analysis module, combined with the current operating state of the ship and the preset alarm strategy. The alarm strategy is customized according to factors such as the type, use, and navigation area of the ship, including the alarm levels, alarm methods, and alarm recipients corresponding to different fault types and danger levels.

[0043] The alarm output module is responsible for outputting the alarm information generated by the alarm decision-making module in various ways, including audible and visual alarms, display screen prompts, SMS notifications, and satellite communication alarms. The alarm output module sets audible and visual alarms at key positions in the ship's cab, engine room, and crew living area. When there is an alarm information, it emits a strong audible and visual signal to attract the attention of the crew. At the same time, it displays detailed information about the alarm location, type, severity, and relevant handling suggestions on the ship's monitoring display screen, facilitating the crew to quickly understand the situation and take corresponding measures.

[0044] The user interaction module provides an interface for the crew to interact with the alarm system. The crew can view the real-time operation data of the ship, historical alarm records, and setting parameter information of the alarm system through this module. They can also perform manual tests on the alarm system, parameter adjustments, and operations of adding or modifying personalized alarm rules. The user interaction module has the functions of alarm information confirmation and feedback. After the crew finishes handling the alarm event, they feedback the handling result to the alarm output module through the user interaction module, so that the system can record and analyze the alarm event, continuously optimize the alarm strategy, and improve the performance of the system.

[0045] The user interaction module specifically includes the following content:

[0046] Information viewing function: Real-time operation data viewing: Crew members can visually view the real-time operation data of various key parts and systems of the ship through the display screen of the user interaction module. The above data is presented in the form of clear and understandable charts or numbers; Historical alarm record query: Crew members can query all alarm records within a certain period in the past; The system displays the alarm events in a list according to the time sequence, and each record includes the time, location, type, severity of the alarm occurrence, and detailed information on the ship's operation status at that time; Viewing of alarm system setting parameters: The user interaction module allows crew members to view various setting parameters of the alarm system, including the acquisition frequency of each sensor, the filtering parameters for data preprocessing, the threshold settings of the data analysis model, the alarm output method, and level definition;

[0047] System operation function: Manual test function: Crew members can manually test the alarm system through the user interaction module to check whether all components of the system are working properly; Parameter adjustment function: Crew members can adjust the parameters of the alarm system according to the ship's different operation stages, different navigation environments, and equipment aging factors; Function of adding and modifying personalized alarm rules: Different types of ships have different safety requirements and concerns during operation. The user interaction module allows crew members to add or modify personalized alarm rules according to the actual situation of the ship;

[0048] Alarm information confirmation and feedback function: Alarm information confirmation function: When the alarm system issues an alarm, crew members will receive prominent alarm prompt information on the display screen of the user interaction module, including the specific content, occurrence location, and severity of the alarm, etc. After learning the alarm information, crew members need to perform a confirmation operation to inform the system that the alarm has been received and corresponding measures are being taken for processing. This confirmation operation is completed by clicking the confirmation button on the display screen, entering a password, or fingerprint recognition to ensure that only authorized crew members can perform the confirmation operation and prevent misoperation or failure to confirm in a timely manner. Once the alarm information is confirmed, the system will record the confirmation time and the information of the confirming person, stop the continuous reminder of the audible and visual alarm, and at the same time feedback the confirmation information to the alarm decision-making module; Alarm handling result feedback function: After crew members handle the alarm event, they feedback the handling result to the alarm system through the user interaction module. The feedback information includes the cause of the failure, the maintenance measures taken, the maintenance time, and detailed information on whether the equipment has returned to normal operation;

[0049] The data storage module is used to store the collected ship operation data, alarm records, data analysis models, and various configuration parameter information of the system. The data storage module uses a large-capacity storage device and has data backup and recovery functions to ensure the security and integrity of the data; Through long-term storage and analysis of historical data, it provides data support for ship maintenance, fault diagnosis, and performance optimization.

[0050] Specifically, when installing the intelligent alarm system of the present invention on a ship, first, according to the specific structure and equipment layout of the ship, various sensors in the data acquisition module are reasonably distributed to ensure that the operation data of each key part and system of the ship can be comprehensively and accurately collected. For example, temperature sensors, pressure sensors, vibration sensors, etc. are installed on equipment such as the main engine, auxiliary engine, and pumps in the engine room, smoke sensors, gas concentration sensors, and liquid level sensors are installed in the cargo hold, and ship position sensors, speed sensors, and heading sensors are installed in the cab, and these sensors are connected to the data acquisition module through a wired or wireless communication network.

[0051] The data collected by the data acquisition module is transmitted to the data preprocessing module in real time. The data preprocessing module performs preprocessing operations such as filtering, amplification, and analog-to-digital conversion on the data, removes noise interference, converts the analog signal into a digital signal, and conducts a preliminary integrity and rationality check on the data. The preprocessed data enters the data analysis module, and the data analysis module uses a preset intelligent algorithm to analyze the data in real time. For example, a fault diagnosis model based on machine learning is used to analyze the operation data of the engine room equipment. Through learning and training on a large amount of historical data, the model can identify the range of various characteristic parameters under the normal operation state of the equipment and the characteristic change patterns corresponding to different fault types. When the real-time monitored data exceeds the normal range or shows characteristic changes similar to the fault mode, the model judges that there may be a potential fault in the equipment and transmits the analysis result to the alarm decision-making module.

[0052] Based on the analysis result of the data analysis module and combined with the current operation state of the ship and the preset alarm strategy, the alarm decision-making module makes an alarm decision. For example, if it is judged that the temperature of a certain equipment in the engine room is rising significantly and is about to exceed the preset safety threshold but has not reached the severe fault level, the alarm decision-making module sends a secondary alarm to the handheld terminal of the engineer according to the preset alarm strategy, prompting him to check and maintain the equipment, and displays detailed alarm information and processing suggestions on the monitoring display screen of the ship. In case of an emergency such as a fire, the alarm decision-making module immediately sends the highest-level alarm to all crew members, simultaneously starts emergency equipment such as fire pumps and audible and visual alarms, and sends the alarm information to the rescue agency on shore through satellite communication.

[0053] The alarm information generated by the alarm decision-making module is output in various ways through the alarm output module. The audible and visual alarm emits strong audible and visual signals at key positions on the ship, and the detailed alarm information, including the alarm location, type, severity, and processing suggestions, is displayed on the display screen. For important alarm information, it can also be sent to the crew's mobile phones via text message notification to ensure that the crew can receive the alarm information in a timely manner regardless of their location.

[0054] Crew members can interact with the alarm system through the user interaction module to view information such as the real-time operation data of the ship, historical alarm records, and system setting parameters. After processing the alarm events, the crew members can feedback the processing results to the alarm system through the user interaction module, such as information that the equipment failure has been repaired, the fire has been extinguished, etc. The alarm system will record and analyze these feedback information for alarm events to continuously optimize the alarm strategy and improve the performance of the system.

[0055] The data storage module stores the ship operation data, alarm records, data analysis models, and various configuration parameters of the system collected for a long time, and has data backup and recovery functions. At the same time, the data storage module conducts data interaction and sharing with other information systems on the ship to realize the integrated management of ship information and provide more comprehensive data support for the comprehensive decision-making of the ship.

[0056] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A ship intelligent alarm system, comprising a data acquisition module, a data preprocessing module, a data analysis module, an alarm decision module, an alarm output module, a user interaction module and a data storage module, characterized in that: The data acquisition module is used to collect operating data of various key parts and systems on the ship, including but not limited to temperature, pressure, liquid level, vibration, smoke concentration, gas concentration, ship position, speed, heading, and working current and voltage parameters of various equipment. The data acquisition module is distributed in the ship's cabin, cargo hold, cab, and living area through various types of sensors. The sensors and data acquisition modules are connected by wired or wireless communication to ensure stable data transmission; The data preprocessing module preprocesses the data received from the data acquisition module, including data filtering, amplification, analog-to-digital conversion, noise removal, and conversion of analog signals into digital signals for subsequent analysis and processing; at the same time, it performs a preliminary integrity and rationality check on the data, and marks or repairs data that is obviously abnormal or missing; The data analysis module uses a preset intelligent algorithm to perform real-time analysis on the pre-processed data. The data analysis module has multiple built-in data analysis models, including a machine learning-based fault diagnosis model, a statistical-based trend analysis model, and a rule-based threshold judgment model. Through the learning of historical data and the dynamic monitoring of real-time data, the operating status of each system of the ship can be accurately identified, and potential fault hazards and abnormal conditions can be discovered in advance. The alarm decision module makes an alarm decision based on the analysis results of the data analysis module, combined with the current operating status of the ship and the preset alarm strategy. The alarm strategy is personalized according to the type, purpose and navigation area of ​​the ship, including the alarm level, alarm mode and alarm recipient corresponding to different fault types and danger levels; The alarm output module is responsible for outputting the alarm information generated by the alarm decision module in a variety of ways, including sound and light alarms, display screen prompts, SMS notifications, and satellite communication alarms; the alarm output module sets sound and light alarms at key locations in the ship's wheelhouse, engine room, and crew living area. When an alarm message is generated, a strong sound and light signal is emitted to attract the attention of the crew; at the same time, the location, type, severity, and related processing suggestions of the alarm are displayed in detail on the ship's monitoring display screen, so that the crew can quickly understand the situation and take corresponding measures; The user interaction module provides an interface for the crew to interact with the alarm system. The crew can view the real-time operation data of the ship, historical alarm records, and setting parameter information of the alarm system through the module, and can also manually test the alarm system, adjust parameters, and add or modify personalized alarm rules. The user interaction module has the function of confirming and feedback of alarm information. After handling the alarm event, the crew can feedback the processing result to the alarm output module through the user interaction module, so that the system can record and analyze the alarm event, continuously optimize the alarm strategy and improve the performance of the system. The data storage module is used to store the collected ship operation data, alarm records, data analysis models and various configuration parameter information of the system. The data storage module adopts a large-capacity storage device and has data backup and recovery functions to ensure the security and integrity of the data; through the long-term storage and analysis of historical data, it provides data support for ship maintenance, fault diagnosis and performance optimization.

2. A ship intelligent alarm system according to claim 1, characterized in that: The data acquisition module includes a temperature sensor, a pressure sensor, a liquid level sensor, a vibration sensor, a smoke concentration sensor, a gas concentration sensor, a ship position, speed and heading sensor, and an equipment working current and voltage sensor.

3. A ship intelligent alarm system according to claim 1, characterized in that: The preprocessing of the data preprocessing module specifically includes the following contents: Data filtering: Filter the data received from the data acquisition module. For some relatively slow-changing physical quantities, low-pass filtering is used to remove high-frequency noise; for rapidly changing parameters, high-pass filtering is used to remove low-frequency interference signals; for specific noise frequency distribution and the frequency range of data that needs to be retained, band-pass filtering or band-stop filtering is used to remove interference signals; Amplification operation: a preamplifier is set near the sensor in the data acquisition module to preliminarily amplify the weak signal output by the sensor; then, according to actual needs, a multi-stage amplification circuit is used to gradually amplify the signal; in each stage of amplification, the amplification factor and bandwidth are selected to avoid signal distortion and the introduction of excessive noise. The amplification circuit must be well shielded and grounded to prevent external interference from affecting the amplified signal; Digital-to-analog conversion: The analog signal collected by the data acquisition module is sampled, and the analog signal is discretized and taken at certain time intervals; the selection of the sampling frequency must follow the Nyquist sampling theorem, that is, the sampling frequency must be greater than twice the highest frequency of the analog signal to ensure that the original analog signal can be accurately restored; the amplitude of the sampled analog signal is quantized, that is, the continuous amplitude range is divided into several discrete quantization levels, and the number of quantization bits determines the amplitude accuracy that the digital signal can represent; finally, the quantized signal is converted into a digital coding form, usually binary coding, so that it can be stored, transmitted and processed in the digital system.

4. A ship intelligent alarm system according to claim 1, characterized in that: The data analysis module specifically includes the following steps: Step 1: Data collection and feature extraction: Obtain the long-term operation history data of various equipment in the cabin from the data storage module, including vibration, temperature, pressure, current, and voltage parameters. For vibration data, convert the time domain signal into a frequency domain signal through the fast Fourier transform method to extract the frequency, amplitude and other characteristics of the vibration; for temperature data, in addition to recording the actual temperature value, analyze its rate of change over time and fluctuation range characteristics; for electrical parameters, extract the harmonic components of current and voltage and the three-phase imbalance characteristics. The above features are used as the input of the machine learning model to fully reflect the operating status of the equipment; Step 2: Model training: Use supervised learning algorithm to train the model. First, divide the historical data in the data storage module into two categories: normal operation data and fault data, and mark them. Use the normal operation data to train the model so that it can learn the characteristic patterns of normal operation of the equipment. Then, use the fault data to verify and optimize the model, and adjust the model parameters to improve the model's ability to identify faults. Step 3: Real-time fault diagnosis: During the operation of the ship, the data of the equipment is collected in real time and preprocessed, and then input into the trained machine learning model; the model calculates the probability of the equipment being in a normal or faulty state based on the characteristics of the input data. If the model determines that the equipment has a fault risk, it will further analyze the fault type and severity.

5. A ship intelligent alarm system according to claim 1, characterized in that: The user interaction module specifically includes the following contents: Information viewing function: Real-time operation data viewing: The crew can intuitively see the real-time operation data of each key part and system of the ship through the display screen of the user interaction module. The above data is presented in clear and easy-to-understand charts or digital forms; Historical alarm record query: The crew can query all alarm records in the past period of time; The system lists the alarm events in chronological order, and each record contains the time, location, type, severity of the alarm, and detailed information on the ship's operating status at that time; Alarm system setting parameter viewing: The user interaction module allows the crew to view various setting parameters of the alarm system, including the acquisition frequency of each sensor, the filtering parameters of data preprocessing, the threshold setting of the data analysis model, and the alarm output method and level definition; System operation functions: Manual test function: The crew can manually test the alarm system through the user interaction module to check whether the various components of the system are working properly; Parameter adjustment function: The crew can adjust the parameters of the alarm system according to the ship's different operating stages, different navigation environments and equipment aging factors; Personalized alarm rule addition and modification function: Different types of ships have different safety requirements and concerns during operation. The user interaction module allows the crew to add or modify personalized alarm rules according to the actual situation of the ship; Alarm information confirmation and feedback function: Alarm information confirmation function: When the alarm system sounds an alarm, the crew will receive a striking alarm prompt message on the display screen of the user interaction module, including the specific content of the alarm, the location and severity of the alarm, etc. After learning the alarm information, the crew needs to confirm it to inform the system that the alarm has been received and appropriate measures are being taken to deal with it. This confirmation operation is completed by clicking the confirmation button on the display screen, entering a password or fingerprint recognition to ensure that only authorized crew members can perform the confirmation operation to prevent misoperation or untimely confirmation. Once the alarm information is confirmed, the system will record the confirmation time and the information of the confirming person, and stop the continuous reminder of the sound and light alarm, and at the same time feedback the confirmation information to the alarm decision module; Alarm processing result feedback function: After the crew has handled the alarm event, the processing result is fed back to the alarm system through the user interaction module. The feedback information includes the cause of the fault, the maintenance measures taken, the maintenance time, and the details of whether the equipment has resumed normal operation.

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