CN116773169A - Method and system for health management of propeller shaft - Google Patents
Method and system for health management of propeller shaft Download PDFInfo
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Abstract
The application provides a propulsion shaft health management method and system, which are particularly applied to the field of propulsion shaft management and comprise the steps of collecting operation data of a target propulsion shaft in a current period; detecting abnormal data in any one of the operation data; correcting the operation data containing the abnormal data to obtain reconstruction data; and determining the health state of the target propulsion shaft according to the reconstruction data. Therefore, the accurate identification of the health state of the ship propulsion shaft is realized, and the sailing safety is improved.
Description
Technical Field
The application relates to the field of propeller shaft management, in particular to a propeller shaft health management method and system.
Background
In recent years, with rapid development of computer technologies such as cloud computing, big data, internet of things and the like, various institutions are actively pushing research on intelligent ships. The ship propulsion shafting is used as a large-scale rotating machine, and the health state of the ship propulsion shafting is one of important guarantees of safe and stable operation of the ship. However, the probability of failure is greatly increased due to the long-term coupling action of external forces such as hull vibration, equipment vibration and the like of the ship propulsion shafting.
In the prior art, each operation data of a ship propulsion shafting is monitored and evaluated generally, and the influence of the monitoring data loss on the accuracy of health evaluation is ignored.
Disclosure of Invention
The embodiment of the application aims to provide a propulsion shaft health management method and system, which are used for collecting operation data of a target propulsion shaft in a current period; detecting abnormal data in any one of the operation data; correcting the operation data containing the abnormal data to obtain reconstruction data; and determining the health state of the target propulsion shaft according to the reconstruction data. Therefore, the accurate identification of the health state of the ship propulsion shaft is realized, and the sailing safety is improved. The specific technical scheme is as follows:
in a first aspect of an embodiment of the present application, there is provided a propeller shaft health management method, including: s1, collecting operation data of a target propulsion shaft in a current period; s2, detecting abnormal data in any one of the operation data; s3, correcting operation data containing abnormal data to obtain reconstruction data; and S4, determining the health state of the target propulsion shaft according to the reconstruction data.
Optionally, the operation data includes: stern shaft temperature, stern shaft pressure, main machine rotational speed and propeller rotational speed.
Optionally, the step S3 of correcting the operation data including the abnormal data to obtain the reconstructed data includes: step S31, collecting operation data of any period of the target propulsion shaft, and constructing a reference sequence x; wherein the operational data of any period is complete; step S32, constructing an abnormal sequence y based on the operation data of the current period; the abnormal data at the time k+1 in the abnormal sequence y is recorded as y k+1 The method comprises the steps of carrying out a first treatment on the surface of the Step S33, calculating a first similarity between the reference sequence x and the abnormal sequence y; step S34, calculating the variation of the adjacent moments of the reference sequence x; step S35, calculating y based on the variation k+1 Is a variable amount of estimation of (a); step S36, calculating y based on the estimated variation k+1 Reconstructed values of (a)Step S37, using said reconstruction value +.>Replacing y in said abnormal sequence y k+1 Obtaining a reconstructed sequence y.
Optionally, in step S33, a cosine similarity calculation method is specifically adopted, and a first similarity between the reference sequence x and the reconstructed sequence y is calculated and denoted as sim.
Optionally, the step S34 of calculating a variation of the reference sequence x at adjacent time instants includes:
Δx t,t+1 ＝x t+1 -x t
wherein ,xt+1 Representing the running data of the reference sequence x at time t+1, x t Representing the running data of the reference sequence x at time t, deltax t,t+1 The amount of change of the reference sequence x at time t+1 with respect to time t is shown.
Optionally, the step S35 calculates y based on the variation k+1 Comprises:
Δy k,k+1 ＝sim×Δx k,k+1
wherein ,Δxk,k+1 Represents the variation of the reference sequence x at time k+1 with respect to time k, Δy k,k+1 The estimated variation of the abnormal sequence y at time k+1 from time k is shown.
Optionally, said calculating y based on said estimated variation k+1 Reconstructed values of (a)Comprising the following steps:
wherein ,representing the reconstructed value at time k+1, y k The operation data of the abnormal sequence y at the time k is shown.
Optionally, the step S4 of determining the health status of the target propulsion shaft according to the reconstruction data includes: calculating a second similarity between the reference sequence x and the reconstructed sequence y; if the second similarity is greater than a preset threshold, determining that the target propulsion shaft is in a healthy state; and if the second similarity is smaller than or equal to a preset threshold value, determining that the target propulsion shaft is in an unhealthy state.
Further, after the determining that the target propulsion axis is in the unhealthy state, the method further includes: s5, notifying a manager to maintain and manage the target propulsion shaft
In yet another aspect of an embodiment of the present application, there is provided a propeller shaft health management system, the system comprising: the system comprises a data acquisition module, an abnormality detection module, a data correction module and a health management module; the data acquisition module is used for acquiring operation data of the target propulsion shaft in the current period; the abnormality detection module is used for detecting abnormal data in any one of the operation data; the data correction module is used for correcting the operation data containing the abnormal data to obtain reconstruction data; the health management module is used for determining the health state of the target propulsion shaft according to the reconstruction data.
Optionally, the operation data includes: stern shaft temperature, stern shaft pressure, main machine rotational speed and propeller rotational speed.
Optionally, the data correction module is further configured to perform the following steps: step S31, collecting operation data of any period of the target propulsion shaft, and constructing a reference sequence x; wherein the operational data of any period is complete; step S32, constructing an abnormal sequence y based on the operation data of the current period; the abnormal data at the time k+1 in the abnormal sequence y is recorded as y k+1 The method comprises the steps of carrying out a first treatment on the surface of the Step S33, calculating a first similarity between the reference sequence x and the abnormal sequence y; step S34, calculating the variation of the adjacent moments of the reference sequence x; step S35, calculating y based on the variation k+1 Is a variable amount of estimation of (a); step S36, calculating y based on the estimated variation k+1 Reconstructed values of (a)Step S37, using said reconstruction value +.>Replacing y in said abnormal sequence y k+1 Obtaining a reconstructed sequence y.
Optionally, in step S33, a cosine similarity calculation method is specifically adopted, and a first similarity between the reference sequence x and the reconstructed sequence y is calculated and denoted as sim.
Optionally, the step S34 of calculating a variation of the reference sequence x at adjacent time instants includes:
Δx t,t+1 ＝x t+1 -x t
wherein ,xt+1 Representing the running data of the reference sequence x at time t+1, x t Representing the running data of the reference sequence x at time t, deltax t,t+1 The amount of change of the reference sequence x at time t+1 with respect to time t is shown.
Optionally, the step S35 calculates y based on the variation k+1 Comprises:
Δy k,k+1 ＝sim×Δx k,k+1
wherein ,Δxk,k+1 Represents the variation of the reference sequence x at time k+1 with respect to time k, Δy k,k+1 The estimated variation of the abnormal sequence y at time k+1 from time k is shown.
Optionally, said calculating y based on said estimated variation k+1 Reconstructed values of (a)Comprising the following steps:
wherein ,representing the reconstructed value at time k+1, y k The operation data of the abnormal sequence y at the time k is shown.
Optionally, the health management module is further configured to: calculating a second similarity between the reference sequence x and the reconstructed sequence y; if the second similarity is greater than a preset threshold, determining that the target propulsion shaft is in a healthy state; and if the second similarity is smaller than or equal to a preset threshold value, determining that the target propulsion shaft is in an unhealthy state.
Further, the system also comprises a management module for informing a manager to carry out maintenance management on the target propulsion shaft.
The beneficial effects are that:
the method comprises the steps of collecting operation data of a target propulsion shaft in a current period; detecting abnormal data in any one of the operation data; correcting the operation data containing the abnormal data to obtain reconstruction data; and determining the health state of the target propulsion shaft according to the reconstruction data. Therefore, the accurate identification of the health state of the ship propulsion shaft is realized, and the sailing safety is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for health management of a propeller shaft according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a propulsion shaft health management system according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
The embodiment of the application provides a method and a system for health management of a propeller shaft, comprising the steps of collecting operation data of a target propeller shaft in a current period; detecting abnormal data in any one of the operation data; correcting the operation data containing the abnormal data to obtain reconstruction data; and determining the health state of the target propulsion shaft according to the reconstruction data. Therefore, the accurate identification of the health state of the ship propulsion shaft is realized, and the sailing safety is improved.
The propulsion shaft health management method and system can be integrated in electronic equipment, wherein the electronic equipment can be a terminal, a server and other equipment. The terminal can be a light field camera, a vehicle-mounted camera, a mobile phone, a tablet computer, an intelligent Bluetooth device, a notebook computer, a personal computer (Personal Computer, PC) or the like; the server may be a single server or a server cluster composed of a plurality of servers.
Artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application that uses a digital computer or a machine controlled by a digital computer to simulate, extend and expand human intelligence, sense the environment, acquire knowledge and use the knowledge to obtain optimal results. The artificial intelligence software technology mainly comprises a computer vision technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.
In recent years, with research and progress of artificial intelligence technology, the artificial intelligence technology is widely applied in a plurality of fields, and the scheme provided by the embodiment of the disclosure relates to the technologies of computer vision technology, machine learning/deep learning of artificial intelligence and the like, and is specifically described by the following embodiments:
fig. 1 is a flow chart of a method for health management of a propeller shaft according to an embodiment of the present application, please refer to fig. 1, which specifically includes the following steps:
firstly, a ship propulsion shafting is a ship propulsion system, and is composed of a middle shaft, a middle bearing, a stern shaft, a stern bearing, a propeller and a front sealing device and a rear sealing device, wherein the front sealing device and the rear sealing device are integrally connected and then provided with power by a main machine to play a role. The ship propulsion shafting has the functions that the power generated by the main engine is transmitted to the propeller, the axial thrust generated after the propeller rotates is transmitted to the thrust bearing through the shafting, and then the thrust bearing transmits the thrust to the ship body, so that the ship can advance or retreat.
The application will now be described in detail with reference to the drawings and to specific embodiments.
Step S110, collecting operation data of the current period of the target propulsion shaft.
Wherein the operational data may include: stern shaft temperature, stern shaft pressure, main machine rotational speed and propeller rotational speed.
In particular, the operational data may be collected by a plurality of sensors.
Step S120, detecting abnormal data in any operation data.
Specifically, the temperature of the stern shaft, the pressure of the stern shaft, the rotational speed of the main engine, and the rotational speed of the propeller are detected, respectively, for example, abnormal data in the temperature operation data of the stern shaft is detected, and according to the abnormal data, step S130 is performed.
And step S130, correcting the operation data containing the abnormal data to obtain reconstruction data.
In one embodiment, the step S130 may specifically include the following steps:
step S131, collecting operation data of any period of the target propulsion shaft, and constructing a reference sequence x.
For example, the operation data of the temperature of the stern shaft of the target propulsion shaft in any period is collected, the reference sequence x is constructed, and the operation data is complete.
Step S132, constructing an abnormal sequence y based on the operation data of the current period.
For example, the operation data of the temperature of the stern shaft of the target propulsion shaft in the current period is collected, and the abnormal sequence y of the components is formed. Wherein, the abnormal data at the time of k+1 in the abnormal sequence y is denoted as y k+1 。
Step S133, calculating a first similarity between the reference sequence x and the abnormal sequence y.
Specifically, a cosine similarity calculation method may be used to calculate the first similarity between the reference sequence x and the reconstructed sequence y, denoted as sim.
Step S134, calculating the variation of the adjacent moments of the reference sequence x.
Wherein, the variable quantity calculation formula is as follows:
Δx t,t+1 ＝x t+1 -x t
wherein ,xt+1 Representing the running data of the reference sequence x at time t+1, x t Representing the running data of the reference sequence x at time t, deltax t,t+1 The amount of change of the reference sequence x at time t+1 with respect to time t is shown.
Step S135, calculating y based on the variation k+1 Is a function of the estimated variation of (a).
Wherein, the calculation formula of the estimated variation is as follows:
Δy k,k+1 ＝sim×Δx k,k+1
wherein ,Δxk,k+1 Represents the variation of the reference sequence x at time k+1 with respect to time k, Δy k,k+1 The estimated variation of the abnormal sequence y at time k+1 from time k is shown.
Step S136, calculating y based on the estimated variation k+1 Reconstructed values of (a)
Wherein, the calculation formula of the reconstruction value is as follows:
wherein ,representing the reconstructed value at time k+1, y k The operation data of the abnormal sequence y at the time k is shown.
Step S137, using the reconstructed valueReplacing y in said abnormal sequence y k+1 Obtaining a reconstructed sequence y.
For example, the abnormal sequence is y= { y1, y2, …, yk+1, …, y2k }, and the abnormal sequence after the reconstruction value is replaced isConvert it into a reconstruction sequence->
According to the embodiment, a brand new data reconstruction mode is introduced, and the monitoring data is reconstructed through calculation of similarity, variation, estimated variation and reconstruction values, so that an accurate health assessment result is obtained.
And step 140, determining the health state of the target propulsion shaft according to the reconstruction data.
Specifically, a second similarity between the reference sequence x and the reconstructed sequence y is calculated; if the second similarity is greater than a preset threshold, determining that the target propulsion shaft is in a healthy state; and if the second similarity is smaller than or equal to a preset threshold value, determining that the target propulsion shaft is in an unhealthy state.
Further, the method further comprises step S150 of notifying a manager to perform maintenance management on the target propulsion shaft.
In one embodiment, a plurality of managers may be notified at the same time, feedback information of the plurality of managers is collected, and a maintenance management policy is formulated according to the feedback information. Wherein the feedback information may include free and busy.
In summary, the present application collects the operation data of the current period of the target propulsion shaft; detecting abnormal data in any one of the operation data; correcting the operation data containing the abnormal data to obtain reconstruction data; and determining the health state of the target propulsion shaft according to the reconstruction data. Therefore, the accurate identification of the health state of the ship propulsion shaft is realized, and the sailing safety is improved.
The present embodiment also provides an approach health management system, as shown in fig. 2, including: a data acquisition module 210, an anomaly detection module 220, a data correction module 230, and a health management module 240.
The data acquisition module 210 is configured to acquire operation data of a current period of the target propulsion shaft.
The anomaly detection module 220 is configured to detect anomaly data in any one of the operation data.
The data correction module 230 is configured to correct the operation data including the abnormal data to obtain the reconstructed data.
The health management module 240 is configured to determine a health status of the target propulsion axis according to the reconstructed data.
Optionally, the operation data includes: stern shaft temperature, stern shaft pressure, main machine rotational speed and propeller rotational speed.
Optionally, the data correction module 230 is further configured to perform the following steps: step S31, collecting operation data of any period of the target propulsion shaft, and constructing a reference sequence x; wherein the operational data of any period is complete; step S32, constructing an abnormal sequence y based on the operation data of the current period; the abnormal data at the time k+1 in the abnormal sequence y is recorded as y k+1 The method comprises the steps of carrying out a first treatment on the surface of the Step S33, calculating a first similarity between the reference sequence x and the abnormal sequence y; step S34, calculating the variation of the adjacent moments of the reference sequence x; step S35, calculating y based on the variation k+1 Is a variable amount of estimation of (a); step S36, calculating y based on the estimated variation k+1 Reconstructed values of (a)Step S37, using said reconstruction value +.>Replacing y in said abnormal sequence y k+1 Obtaining a reconstructed sequence y.
Optionally, in step S33, a cosine similarity calculation method is specifically adopted, and a first similarity between the reference sequence x and the reconstructed sequence y is calculated and denoted as sim.
Optionally, the step S34 of calculating a variation of the reference sequence x at adjacent time instants includes:
Δx t,t+1 ＝x t+1 -x t
wherein ,xt+1 Representing the running data of the reference sequence x at time t+1, x t Representing the running data of the reference sequence x at time t, deltax t,t+1 The amount of change of the reference sequence x at time t+1 with respect to time t is shown.
Optionally, the step S35 calculates y based on the variation k+1 Comprises:
Δy k,k+1 ＝sim×Δx k,k+1
wherein ,Δxk,k+1 Represents the variation of the reference sequence x at time k+1 with respect to time k, Δy k,k+1 The estimated variation of the abnormal sequence y at time k+1 from time k is shown.
Optionally, said calculating y based on said estimated variation k+1 Reconstructed values of (a)Comprising the following steps:
wherein ,representing the reconstructed value at time k+1, y k The operation data of the abnormal sequence y at the time k is shown.
Optionally, the health management module 240 is further configured to: calculating a second similarity between the reference sequence x and the reconstructed sequence y; if the second similarity is greater than a preset threshold, determining that the target propulsion shaft is in a healthy state; and if the second similarity is smaller than or equal to a preset threshold value, determining that the target propulsion shaft is in an unhealthy state.
Further, the system further comprises a management module 250 for informing a manager to perform maintenance management on the target propulsion shaft.
The propulsion shaft health management system provided by the application can realize accurate identification of the health state of the ship propulsion shaft and improve the sailing safety.
Finally, it should be noted that: the above examples are only specific embodiments of the present application, and are not intended to limit the scope of the present application, but it should be understood by those skilled in the art that the present application is not limited thereto, and that the present application is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the corresponding technical solutions. Are intended to be encompassed within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A propeller shaft health management method, comprising:
s1, collecting operation data of a target propulsion shaft in a current period;
s2, detecting abnormal data in any one of the operation data;
s3, correcting operation data containing abnormal data to obtain reconstruction data;
and S4, determining the health state of the target propulsion shaft according to the reconstruction data.
2. The propeller shaft health management method of claim 1, wherein the operational data comprises: stern shaft temperature, stern shaft pressure, main machine rotational speed and propeller rotational speed.
3. The propeller shaft health management method of claim 1, wherein the step S3 of correcting the operation data including the abnormal data to obtain the reconstructed data includes:
step S31, collecting operation data of any period of the target propulsion shaft, and constructing a reference sequence x; wherein the operational data of any period is complete;
step S32, constructing an abnormal sequence y based on the operation data of the current period; the abnormal data at the time k+1 in the abnormal sequence y is recorded as y k+1 ；
Step S33, calculating a first similarity between the reference sequence x and the abnormal sequence y;
step S34, calculating the variation of the adjacent moments of the reference sequence x;
step S35, calculating y based on the variation k+1 Is a variable amount of estimation of (a);
step S36, calculating y based on the estimated variation k+1 Reconstructed values of (a)
Step S37, using the reconstructed valueReplacing y in said abnormal sequence y k+1 Obtaining a reconstructed sequence y.
4. The propeller shaft health management method of claim 3, wherein the step S33 specifically uses a cosine similarity calculation method to calculate a first similarity between the reference sequence x and the reconstructed sequence y, denoted as sim.
5. The propeller shaft health management method of claim 4, wherein said step S34 of calculating the amount of change in the reference sequence x at adjacent times includes:
Δx t,t+1 ＝x t+1 -x t
wherein ,xt+1 Representing the running data of the reference sequence x at time t+1, x t Representing the running data of the reference sequence x at time t, deltax t,t+1 The amount of change of the reference sequence x at time t+1 with respect to time t is shown.
6. The propeller shaft health management method of claim 5, wherein said step S35 calculates y based on said variation amount k+1 Comprises:
Δy k,k+1 ＝sim×Δx k,k+1
wherein ,Δxk,k+1 Represents the variation of the reference sequence x at time k+1 with respect to time k, Δy k,k+1 The estimated variation of the abnormal sequence y at time k+1 from time k is shown.
7. The propeller axis health management method of claim 6, wherein the calculating y is based on the estimated variation k+1 Reconstructed values of (a)Comprising the following steps:
wherein ,representing the reconstructed value at time k+1, y k The operation data of the abnormal sequence y at the time k is shown.
8. The propeller shaft health management method of claim 7, wherein the step S4 of determining the health status of the target propeller shaft from the reconstructed data includes:
calculating a second similarity between the reference sequence x and the reconstructed sequence y;
if the second similarity is greater than a preset threshold, determining that the target propulsion shaft is in a healthy state;
and if the second similarity is smaller than or equal to a preset threshold value, determining that the target propulsion shaft is in an unhealthy state.
9. The propeller shaft health management method of claim 8, wherein after the determination that the target propeller shaft is in an unhealthy state, further comprising:
and S5, notifying a manager to repair and manage the target propulsion shaft.
10. The propulsion shaft health management system is characterized by comprising a data acquisition module, an abnormality detection module, a data correction module and a health management module;
the data acquisition module is used for acquiring operation data of the target propulsion shaft in the current period;
the abnormality detection module is used for detecting abnormal data in any one of the operation data;
the data correction module is used for correcting the operation data containing the abnormal data to obtain reconstruction data;
the health management module is used for determining the health state of the target propulsion shaft according to the reconstruction data.
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