Remote monitoring and diagnosing method and system for key equipment of intelligent ship
Through the analysis and correlation of parameter data of multiple monitoring points of intelligent ship key equipment and combined with the decision-making guidance of deep learning models, the problem of insufficient detection of single-point abnormalities in intelligent ships is solved, and timely fault diagnosis and safety improvement of key equipment is achieved.
Patent Information
- Application Number
- CN202510028481.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-07
- Publication Date
- 2025-04-18
AI Technical Summary
During long-distance navigation, smart ships rely solely on parameter abnormalities at a single monitoring point, and the ship's staff lack the ability to resolve equipment abnormalities, resulting in safety failures.
By obtaining parameter data of multiple monitoring points of intelligent ship key equipment, analyzing data changes trends, and performing correlation analysis based on historical abnormalities and fault data, outputting key equipment failures and abnormalities corresponding to parameter data abnormalities of the correlation monitoring point of different combinations. At the same time, through historical alarms and processing results, a deep learning model is designed, decision-making guidance is proposed and sent to the ship.
It realizes timely abnormal detection and fault diagnosis of key equipment in smart ships, reduces safety hazards, and improves the safety and reliability of ship operations.
Smart Images
Figure CN119840803A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of intelligent ship monitoring, and in particular relates to a remote monitoring and diagnosis method and system for key equipment of an intelligent ship. Background Art
[0002] During the navigation of smart ships, due to the harsh working environment and complex and changeable working conditions, the parts of ship equipment will inevitably deteriorate to varying degrees, resulting in different degrees of failure. In order to improve the safety and stability of ship operation, the existing smart ship equipment is equipped with sensors and detectors for detecting different operating parameters of ship equipment at multiple points for monitoring different parameter data of ship equipment. These detection devices monitor different points of key ship equipment online in real time, and transmit signals to the control room of the ship for staff to view in real time, so as to grasp the operating status of ship equipment in real time. In addition, when smart ships are sailing in the ocean, they will transmit the equipment operating status information to the shore in real time, which is convenient for shore management personnel to monitor and manage the ship-side equipment information. However, in the actual operation of smart ships, there may be hundreds of monitoring points for large equipment on the ship. It is impossible to determine whether the key equipment is abnormal by simply relying on the abnormal parameters of a certain monitoring point on the equipment; in addition, after the equipment abnormality is confirmed, the ship-side staff often lacks the ability to solve the abnormality of the ship-side equipment, which leads to the occurrence of ship safety failures, seriously affecting the operation safety of smart ships. Summary of the invention
[0003] The present invention solves the problem that currently smart ships only rely on the abnormal parameters of a certain monitoring point on the equipment and cannot determine whether key equipment is abnormal, and the ship-side staff often lacks the ability to solve the abnormalities of the ship-side equipment, which leads to ship safety failures. A remote monitoring and diagnosis method and system for key equipment of smart ships are provided to timely discover the abnormalities or failures of key equipment of smart ships, and guide the ship to take certain processing measures to deal with the abnormalities or failures.
[0004] The technical solution claimed in the present invention is as follows:
[0005] A remote monitoring and diagnosis method for key equipment of an intelligent ship comprises the following steps:
[0006] S1: Obtain parameter data of different monitoring points of key equipment of smart ships and basic data of ships;
[0007] S2: Set access permissions for parameter data and basic ship data obtained by S1 and store them;
[0008] S3: Analyze the change trends of parameter data of different monitoring points of key equipment of intelligent ships stored in S2 respectively, and associate parameter data of different monitoring points based on historical anomalies and failures of key equipment combined with guidance and suggestions from professionals, and output failures and anomalies of key equipment corresponding to abnormal parameter data of associated monitoring points of different combinations;
[0009] S4: For smart ships in operation, the abnormalities and failures of key equipment can be diagnosed and predicted by combining the changing trends of parameter data at different monitoring points of key equipment with the results output by S3;
[0010] S5: Provide decision-making guidance for the abnormalities and failures of key equipment diagnosed and predicted in S4 through historical alarms and processing results, and send the decision-making guidance to the ship side.
[0011] Preferably, the key equipment in S1 refers to equipment running on a smart ship related to safe navigation of the smart ship, and the basic ship data includes a unique identification code of the smart ship and the shipowner to which the smart ship belongs.
[0012] Preferably, the data access rights in S2 are set so that only the ship owner to whom the smart ship in the ship basic data belongs can access the parameter data of different monitoring points of key equipment of the smart ship and the ship basic data.
[0013] In a specific embodiment of the present invention, the fault in S3 refers to a specific fault point of a key device.
[0014] In some embodiments of the present invention, S5 specifically includes: designing and training a deep learning model by collecting historical alarms and processing results, and outputting the most commonly used solutions, which are decision-making guidelines.
[0015] Preferably, the method also includes: providing a user interaction interface, which visualizes the parameter data of different monitoring points of key equipment of the smart ship in a certain date interval, and the date interval supports free configuration; the user interaction interface supports user configuration to associate and display parameter data of key equipment monitoring points in different combinations.
[0016] The present invention also provides a remote monitoring and diagnosis system for key equipment of an intelligent ship based on the method, comprising a data acquisition module connected in sequence for acquiring parameter data of different monitoring points of key equipment of an intelligent ship and basic data of a ship, a data storage module for setting data access permissions for the parameter data obtained by the data acquisition module and storing the same, a data association analysis module for analyzing the change trends of the parameter data of different monitoring points of key equipment of an intelligent ship stored in the data storage module, and correlating the parameter data of different monitoring points based on historical abnormalities and failures of the key equipment in combination with the guidance and suggestions of professionals, and finally outputting abnormalities and failures of key equipment corresponding to abnormal parameter data of associated monitoring points in different combinations, a ship equipment diagnosis and prediction module for diagnosing and predicting abnormalities and failures of key equipment by combining the change trends of the parameter data of different monitoring points of key equipment of an on-board intelligent ship with the results output by the data association analysis module, and a ship-end equipment abnormality guidance module for collecting historical alarms and processing results to establish a model, proposing decision-making guidance opinions for the abnormalities and failures of key equipment diagnosed and predicted by the ship equipment diagnosis and prediction module, and sending the decision-making guidance opinions to the ship-end.
[0017] Preferably, in the above system, the key equipment refers to equipment running on the smart ship related to the safe navigation of the smart ship; the basic ship data includes the unique identification code of the smart ship and the owner of the smart ship.
[0018] Preferably, in the above system, the data access rights are set so that only the ship owner to whom the smart ship in the ship basic data belongs can access the parameter data of different monitoring points of key equipment of the smart ship and the ship basic data.
[0019] Preferably, the system also includes a user interaction module connected to the data storage module for providing a user interaction interface. The user interaction module can visualize the parameter data of different monitoring points of key equipment of the smart ship in a certain date range according to the configuration, and support the user configuration to associate and display the parameter data of different combinations of key equipment monitoring points.
[0020] Beneficial effects:
[0021] The present invention provides a remote monitoring and diagnosis method and system for key equipment of an intelligent ship. During the actual operation of an intelligent ship, multiple monitoring points are set on the key equipment of the ship. Workers often cannot judge whether the equipment is abnormal only through the abnormality of a single monitoring point or several monitoring points. The method analyzes the change trends of parameter data of different monitoring points of key equipment of the stored intelligent ship respectively, and associates the parameter data of different monitoring points based on the historical abnormalities and failures of the key equipment combined with the guidance and suggestions of professionals, outputs the failures and abnormalities of the key equipment corresponding to the abnormalities of the parameter data of the associated monitoring points in different combinations, associates and combines multiple monitoring points through historical experience, and if the parameter data of the associated multiple monitoring points are abnormal, it can be directly judged that the key equipment is abnormal, thereby solving the problem that the current intelligent ship only relies on the parameter abnormality of a certain point on the equipment and cannot determine whether the key equipment is abnormal. The method diagnoses and predicts abnormalities and failures of key equipment for an intelligent ship on the water by combining the change trends of parameter data at different monitoring points of key equipment with associated monitoring points, which helps to timely discover abnormalities of key equipment on the ship and warn of potential safety hazards. It also provides decision-making guidance opinions on the abnormalities and failures of the diagnosed and predicted key equipment through historical alarms and processing results, and sends the decision-making guidance opinions to the ship side, thereby solving the problem that the ship side staff often lack the ability to solve the abnormalities of the ship side equipment, which leads to safety failures of the ship, and improving the safety and reliability of the ship.
[0022] Provides a user interaction interface, where users can view the changing trends of parameter data of different monitoring points of key equipment within a certain time interval according to actual needs, so that users can intuitively view the operating conditions of the equipment within a certain period of time. Users can combine and display parameter data of multiple related monitoring points together, so that users can find possible abnormalities of key equipment in a timely and intuitive manner, and ensure the safety of ship operation. BRIEF DESCRIPTION OF THE DRAWINGS
[0023] Figure 1 Flow chart of the method of the present invention.
[0024] Figure 2 Schematic diagram of the system of the present invention. DETAILED DESCRIPTION
[0025] The present invention is described in detail below in conjunction with the accompanying drawings:
[0026] The present invention provides a remote monitoring and diagnosis method for key equipment of an intelligent ship, which is characterized by comprising the following steps:
[0027] S1: Obtain parameter data of different monitoring points of key equipment of smart ships and basic ship data; the key equipment refers to equipment running on smart ships related to safe navigation of smart ships; the basic ship data includes the unique identification code of the smart ship and the shipowner to which the smart ship belongs.
[0028] S2: Set access permissions for the parameter data and ship basic data obtained in S1 and store them; the data access permissions are set so that only the ship owner to whom the smart ship in the ship basic data belongs can access the parameter data and ship basic data of different monitoring points of key equipment of the smart ship.
[0029] S3: Analyze the changing trends of parameter data of different monitoring points of key equipment of intelligent ships stored in S2 respectively, and associate parameter data of different monitoring points based on historical anomalies and failures of key equipment combined with guidance and suggestions of professionals, and output failures and anomalies of key equipment corresponding to abnormalities of parameter data of associated monitoring points in different combinations; for example: assuming that there are A1-A100, 100 monitoring points on equipment A, among which A5-A10 are associated, and A25-A28 are associated, then A5-A10 abnormality or A25-A28 abnormality both indicate equipment abnormality, among which A25-A28 abnormality represents a failure of a certain part of the key equipment, and A5-A10 abnormality represents a failure of another part of the key equipment. The specific failure point of the key equipment can be determined by associating monitoring points; the failure refers to the specific failure point of the key equipment.
[0030] In a specific embodiment of the present invention, for example, the Exhaust Valve Closing Too Slow CCU8-03023315 alarm (abnormal) is triggered. The Exhaust Valve Closing Too Slow CCU8-03023315 is a monitoring point on the exhaust valve of a key device. The possible reasons for the alarm at this monitoring point are as follows:
[0031] ① The exhaust valve sensor is faulty, such as the sensor probe is dirty, the wiring is loose, the cable connected to the sensor is short-circuited, etc.;
[0032] ② Exhaust valve driver failure, such as internal plunger wear and blocking, driver upper low-pressure lubricating oil inlet check valve failure;
[0033] ③ FIVA valve and pilot valve failure, MPC board failure, slow exhaust valve driver hydraulic oil leakage, resulting in large exhaust valve closing resistance, accumulator diaphragm damage, insufficient pressure, and the FIVA feedback curve of this fault will also be abnormal;
[0034] ④ Fault in the hydraulic oil pipe between the exhaust valve and the drive, such as oil leakage from the oil pipe contact surface, oil leakage from cracks at the oil pipe elbow, etc.;
[0035] ⑤ Exhaust valve body failure, such as exhaust valve body throttle plug blockage, safety valve spring breakage and seal failure and oil leakage, exhaust valve air check valve damage, exhaust valve air cavity internal seal wear and tear resulting in air pressure unable to meet valve closing requirements, etc. Therefore, only through one monitoring point alarm, it is impossible to determine the specific fault location, so it is necessary to determine the specific fault location based on the associated monitoring points. For example: When the FIVA valve fails, the key monitoring points are: Exhaust Valve Closing TooSlow CCU8-03023315, Exhaust Valve open stroke low, Exhaust Temperature OuterHigh, Exhaust Temperature Deviation High. When the above monitoring points alarm together, it is judged as a FIVA valve failure.
[0036] S4: For smart ships in motion, the change trend of parameter data at different monitoring points of key equipment is combined with the results of S3 output to diagnose and predict abnormalities and failures of key equipment; in a specific embodiment of the present invention, for example, according to the trend of the main engine NO.1 cylinder exhaust temperature parameter point is slowly rising, and at the same time, the explosion pressure of the main engine NO.1 cylinder at the monitoring point is low, based on the situation of different monitoring points, it is predicted that the combustion state of the main engine NO.1 cylinder is about to become abnormal, and combined with expert opinions, it is diagnosed that the main engine NO.1 cylinder injector spring is broken.
[0037] S5: Propose decision-making guidance opinions on the abnormalities and failures of key equipment diagnosed and predicted in S4 through historical alarms and processing results, and send the decision-making guidance opinions to the ship side; in a specific embodiment of the present invention, a deep learning model is designed and trained by collecting historical alarms and processing results, and the most commonly used solutions are output. The most commonly used solutions are decision-making guidance opinions.
[0038] The method also includes: providing a user interaction interface, which visualizes the parameter data of different monitoring points of key equipment of the smart ship in a certain date range, and the date range supports free configuration; the user interaction interface supports user configuration to associate and display parameter data of key equipment monitoring points of different combinations.
[0039] The present invention provides a remote monitoring and diagnosis system for key equipment of an intelligent ship based on the method, comprising a data acquisition module connected in sequence for acquiring parameter data of different monitoring points of key equipment of an intelligent ship and basic data of a ship, a data storage module for setting data access rights for parameter data obtained by the data acquisition module and storing the same, a data association analysis module for analyzing the change trends of parameter data of different monitoring points of key equipment of an intelligent ship stored in the data storage module, and correlating parameter data of different monitoring points based on historical abnormalities and failures of key equipment combined with guidance and suggestions of professionals, and finally outputting abnormalities and failures of key equipment corresponding to abnormal parameter data of associated monitoring points of different combinations, a ship equipment diagnosis and prediction module for diagnosing and predicting abnormalities and failures of key equipment through the change trends of parameter data of different monitoring points of key equipment of an on-board intelligent ship combined with the results output by the data association analysis module, a ship equipment abnormality guidance module for collecting historical alarms and processing results to establish a model, and providing decision-making guidance opinions for abnormalities and failures of key equipment diagnosed and predicted by the ship equipment diagnosis and prediction module, and sending the decision-making guidance opinions to the ship end, and a user interaction module connected to the data storage module for providing a user interaction interface. The key equipment refers to equipment running on an intelligent ship related to the safe navigation of an intelligent ship; the ship basic data includes a unique identification code of the intelligent ship and the ship owner to which the intelligent ship belongs. The data access permission is set so that only the shipowner of the smart ship in the ship basic data can access the parameter data of different monitoring points of key equipment of the smart ship and the ship basic data. The user interaction module can visualize the parameter data of different monitoring points of key equipment of the smart ship in a certain date range according to the configuration, and support the user configuration to associate and display the parameter data of key equipment monitoring points of different combinations.
[0040] It should be noted that the above-described specific implementations can enable those skilled in the art to more fully understand the invention, but do not limit the invention in any way. Therefore, although this specification has described the invention in detail with reference to the drawings and embodiments, those skilled in the art should understand that the invention can still be modified or replaced by equivalents. In short, all technical solutions and improvements that do not deviate from the spirit and scope of the invention should be included in the protection scope of the patent for the invention.
Claims
1. A remote monitoring and diagnosis method for key equipment of an intelligent ship, characterized in that: The steps include: S1: Obtain parameter data of different monitoring points of key equipment of smart ships and basic data of ships; S2: Set access permissions for parameter data and basic ship data obtained by S1 and store them; S3: Analyze the change trends of parameter data of different monitoring points of key equipment of intelligent ships stored in S2 respectively, and associate parameter data of different monitoring points based on historical anomalies and failures of key equipment combined with guidance and suggestions from professionals, and output failures and anomalies of key equipment corresponding to abnormal parameter data of associated monitoring points of different combinations; S4: For smart ships in operation, the abnormalities and failures of key equipment can be diagnosed and predicted by combining the changing trends of parameter data at different monitoring points of key equipment with the results output by S3; S5: Provide decision-making guidance for the abnormalities and failures of key equipment diagnosed and predicted in S4 through historical alarms and processing results, and send the decision-making guidance to the ship side.
2. The remote monitoring and diagnosis method for key equipment of intelligent ships according to claim 1 is characterized in that: The key equipment mentioned in S1 refers to the equipment running on the smart ship related to the safe navigation of the smart ship, and the basic ship data includes the unique identification code of the smart ship and the shipowner to which the smart ship belongs.
3. The remote monitoring and diagnosis method for key equipment of intelligent ships according to claim 1 is characterized in that: The data access permission in S2 is set so that only the ship owner to whom the smart ship in the ship basic data belongs can access the parameter data of different monitoring points of the key equipment of the smart ship and the ship basic data.
4. The remote monitoring and diagnosis method for key equipment of an intelligent ship according to claim 1 is characterized in that: The failure described in S3 refers to the specific failure point of the key equipment.
5. The remote monitoring and diagnosis method for key equipment of intelligent ships according to claim 1 is characterized in that: The details of S5 are: designing and training a deep learning model by collecting historical alarms and processing results, and outputting the most commonly used solutions, which are decision-making guidelines.
6. The remote monitoring and diagnosis method for key equipment of an intelligent ship according to claim 1 is characterized in that: The method also includes: providing a user interaction interface, which visualizes the parameter data of different monitoring points of key equipment of the smart ship in a certain date range, and the date range supports free configuration; the user interaction interface supports user configuration to associate and display parameter data of key equipment monitoring points of different combinations.
7. A remote monitoring and diagnosis system for key equipment of an intelligent ship based on the method of claim 1, characterized in that: It includes a data acquisition module connected in sequence for acquiring parameter data of different monitoring points of key equipment of intelligent ships and basic data of ships, a data storage module for setting data access permissions for parameter data obtained by the data acquisition module and storing it, a data association analysis module for analyzing the change trends of parameter data of different monitoring points of key equipment of intelligent ships stored in the data storage module, and correlating parameter data of different monitoring points based on historical anomalies and failures of key equipment in combination with guidance and suggestions from professionals, and finally outputting anomalies and failures of key equipment corresponding to abnormal parameter data of associated monitoring points in different combinations, a ship equipment diagnosis and prediction module for diagnosing and predicting anomalies and failures of key equipment through the change trends of parameter data of different monitoring points of key equipment of sailing intelligent ships in combination with the results output by the data association analysis module, and a ship-end equipment abnormality guidance module for collecting historical alarms and processing results to establish a model, proposing decision-making guidance opinions for the anomalies and failures of key equipment diagnosed and predicted by the ship equipment diagnosis and prediction module, and sending the decision-making guidance opinions to the ship end.
8. The remote monitoring and diagnosis system for key equipment of intelligent ships according to claim 7 is characterized in that: The key equipment refers to the equipment running on the smart ship related to the safe navigation of the smart ship; the basic ship data includes the unique identification code of the smart ship and the shipowner to which the smart ship belongs.
9. The remote monitoring and diagnosis system for key equipment of intelligent ships according to claim 8 is characterized in that: The data access permission is set so that only the ship owner to whom the smart ship in the ship basic data belongs can access the parameter data of different monitoring points of key equipment of the smart ship and the ship basic data.
10. The remote monitoring and diagnosis system for key equipment of intelligent ships according to claim 7, characterized in that: The system also includes a user interaction module connected to the data storage module for providing a user interaction interface. The user interaction module can visualize the parameter data of different monitoring points of key equipment of the smart ship in a certain date range according to the configuration, and support the user configuration to associate and display the parameter data of key equipment monitoring points of different combinations.