CN112163738B - Service-oriented ship remote guarantee resource allocation method - Google Patents
Service-oriented ship remote guarantee resource allocation method Download PDFInfo
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses a service-oriented ship remote guarantee resource distribution method, namely a remote guarantee resource distribution method, which mainly comprises the following functions: (1) Integrating and transmitting equipment state data acquired by a ship equipment monitor; (2) predicting a likely failure; (3) Rapidly organizing the guarantee resources capable of effectively solving the fault; and (4) informing the ship closest to the ship and providing spare parts.
Description
Technical Field
The invention belongs to the technical support field of ships, and particularly relates to a service-oriented remote support resource allocation method for ships.
Background
When equipment failure occurs during ship sailing, if technicians of the ship cannot solve the problem, a solution cannot be found or the ship lacks spare parts and cannot be repaired, the solution needs to be reported to a remote shore-based guarantee center, technical strength behind or around the failed ship is organized by the guarantee center, and timely and accurate technical guarantee is provided, wherein scheduling distribution of guaranteed resources (including technical strength and spare parts) is very critical, and an effective solution in the aspect is lacked at present.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a service-oriented ship remote guarantee resource allocation method for solving the coordination problem of guarantee resources.
In order to achieve the above object, the invention provides a service-oriented ship remote guarantee resource allocation method, which is characterized in that: the ship equipment sensors deployed at different monitoring points of a ship are connected with a ship technical state server through a ship domain network, the monitoring sensors of the ship equipment sensors have different characteristics according to different monitored equipment, and data acquired by the sensors reflect the working state of the equipment.
Firstly, the ship technical state server integrates the sensing data transmitted from each monitoring point and detects possible faults.
Secondly, the technical state server carries out preliminary diagnosis, if the fault can not be eliminated, a guarantee request is sent to a remote guarantee center, a diagnosis algorithm can estimate possible fault reasons according to the fault phenomenon represented by the sensing data, and the diagnosis algorithm is described as follows. Suppose F j Representing the cause of the fault, j =1,2, ·, m, x j i Represents a correspondence F j I =1,2, ·, n, the ith observable fault phenomenon of (1). If a certain type of failure F j Probability of occurrence p (F) j ) Known and corresponding to a j-th fault F j Phenomenon x of 1 j ，x 2 j ，···，x l j It is known that (1. Ltoreq. L. Ltoreq.n) has the following formula according to Bayes's rule
Let p (x) 1 j |F j )，p(x 2 j |F j )，···，p(x l j |F j ) Statistically irrelevant, then there are
Substituting equation (3) and equation (2) into equation (1) has
Wherein p (F) k ) Representing the probability of occurrence of a class k fault, p (x) i j |F j ) Representing the occurrence of a fault of type j (F) j ) Observed when the phenomenon x i The above 2 values determine the accuracy of equation (4), where p (x) i j |F j ) Can be obtained by counting the historical failure phenomenon of the equipment and the corresponding reason, and y is set j As fault class j F j Observation of phenomenon x at occurrence i j Possibility of (a) y j Is 0 or 1, then there is (1-p) j ) No phenomenon x was observed i j Has p of j Possibility of observing x i j ，y j Can be expressed by Bernoulli experiment as
When the ship technicians cannot solve equipment faults, a guarantee request signal is sent to the surrounding water area through a remote broadcasting means, meanwhile, a guarantee request message is sent to a remote guarantee center through a marine satellite or other remote communication equipment, and if other ships surrounding the faulty ship receive the guarantee request signal and have corresponding spare parts or technical experts, a receiving request message is sent to the guarantee center and actively get close to the faulty ship.
If the support of surrounding ships cannot be obtained, the support center firstly searches expert rosters in related fields according to the types of fault equipment, and in order to improve the resource utilization efficiency, remote support experts implement grouping management, which can be longitudinally grouped according to units or transversely grouped according to industry associations. When receiving the guarantee request message, the guarantee center firstly sends out the guarantee request to the expert group manager, and then the expert group manager informs subordinate units or individuals who can participate in the guarantee. The safeguard request message should include basic information about the fault, such as the type, name, delivery time, current location of the ship, fault phenomenon, current operating condition, collected equipment monitoring data, and type of the required safeguard.
When the expert shows that the expert is willing to participate in the remote consultation or the guarantee action, the expert is marked as a supporter, and a supporter code is given as the access right for participating in the remote guarantee. Each support person has a digital resume describing his identity, current location, specialty, historical support records, etc. the support person's computer or cell phone should have client software installed to enable the discovery, joining or leaving of the remote consultation group and to enable the interaction with other support persons through the system client.
Once receiving the guarantee request message, the guarantee center firstly preliminarily analyzes to obtain the fault level, then contacts with an expert group manager or an expert to select the expert group members for remote consultation, and establishes a remote consultation room on the network after the expert group members participating in the guarantee are completely determined, so as to help each member to enter the on-network consultation room to analyze and process the fault.
The expert selection algorithm is as follows. Let E k K ∈ {1,2, ·, N } represents technical experts registered in the remote security center and related organizations, each expert is assigned an attribute table, where X1 represents the speciality of the expert, X2 represents the history of providing remote security of the ship, and X3 represents the degree of trust of the security center for him. The expert attribute table is maintained and modified by the assurance center.
In addition, a guarantee center is arranged to set M emergency levels, and each emergency level e i (i e.g. {1,2, ·, M }) and a corresponding attribute X j (j epsilon {1,2, ·, t }), the assurance center assigns a weight w ij And three parameters, which are respectively (1) minimum support time, in terms of θ i A representation representing the minimum required time for technical support of the class of emergency level failures; (2) Selecting an acceptance threshold for the candidate expert using gamma i A representation representing a quantified difference between the candidate expert expertise and the skill required to resolve the class of fault; (3) Maximum wait time before receiving guarantee request message from expert, using tau i Indicating that it represents the minimum time interval from the sending of a message to the receipt of a reply for that type of urgency level. The emergency level is determined by the security center personnel according to the fault type and the task type, and after a candidate expert is selected, the system forwards a joining request message for joining the candidate group to the candidate expert, wherein the message field comprisesCandidate group code, notes to handle this type of fault, location of the faulty vessel, required spare part information (name, type and number), etc. Professional proximity according to experts (gamma) i Expressed) and a minimum support time (θ) i Expression), and the like, and further filtering from the ranked list of experts according to the following formula,
in the above formula, X k,p Representing an attribute in the expert resume matrix table, w m,p Representing the weights in the emergency level matrix table.
The invention has the following advantages and beneficial effects:
the invention relates to a method for distributing remote guarantee resources, which mainly comprises the following functions: (1) Equipment state data collected by a ship equipment monitor is fused and transmitted; (2) predicting a likely failure; (3) Rapidly organizing the guarantee resources capable of effectively solving the fault; and (4) informing the ship closest to the ship and providing spare parts.
Drawings
FIG. 1 is a flow chart of ship technical support data according to the present invention;
FIG. 2 is a block diagram of the present invention;
FIG. 3 is a diagram of message interactions among the guaranteed participants of the present invention;
FIG. 4 is an information interaction diagram of the process of establishing a consultation group according to the present invention;
FIG. 5 is a diagram illustrating an expert building a matrix table according to the present invention;
FIG. 6 is a diagram of a matrix table for ensuring urgency levels according to the present invention.
Detailed description of the preferred embodiments
The invention is explained in further detail below with reference to the figures and the embodiments.
The implementation can be realized in the form of 3-layer middleware, the data flow is shown in figure 1, and the module implementation is shown in figure 2.
The working process of the bottom monitoring layer is as follows: (1) managing a shipborne equipment monitoring sensor; (2) Collecting sensor data, and fusing the sensor data into equipment working condition information; (3) Distributing the equipment working condition information to the required diagnosis monitoring service; (4) judging whether the ship fails or not; and (5) alarming to a remote security center in case of emergency. The monitoring layer can be developed on top of an open service gateway initiative (OGSI) structure, and the OGSI provides service-oriented component support, so that software lifecycle management of the sensor is simplified. The working steps are described in detail below.
Step 1: the working condition acquisition service sends a request to the ship equipment sensor to obtain the equipment monitoring data of the sensor, and the acquisition frequency can be preset by ship technicians or changed by configuration files sent by remote experts.
Step 2: and after the working condition data are collected, the collection service transfers the sensing data to a working condition storage service and an aggregation service, and the storage service stores important monitoring data according to a storage rule so as to facilitate failure backtracking analysis.
And 3, step 3: the aggregation service can extract the equipment working condition information under the normal condition stored in the past from the storage service, perform correlation analysis and form a formatted equipment baseline working condition. If the currently collected working condition information is changed greatly compared with the baseline working condition, the fault is indicated to be possible, and a guarantee request message needs to be sent to the upper-layer service. The aggregation service comprehensively associates data of different devices and detects possible faults.
The diagnostic algorithm is described below. Suppose F j Representing the cause of the fault, j =1,2, ·, m, x j i Represents a correspondence F j I =1,2, ·, n, the ith observable fault phenomenon of (1). If a certain type of failure F j Probability of occurrence p (F) j ) Known and corresponding to fault class j F j Phenomenon x of 1 j ，x 2 j ，···，x l j Given that (1. Ltoreq. L. Ltoreq.n), the calculation formula is as follows according to Bayesian rule
Wherein p (F) k ) Representing the probability of occurrence of a class k fault, p (x) i j |F j ) Representing the occurrence of a fault of type j (F) j ) Observed phenomenon x i Wherein p (x) i j |F j ) The method can be obtained by counting historical failure phenomena of the equipment and corresponding reasons.
And 4, step 4: and finally, the distribution service distributes and sends the working condition data to a ship working condition monitoring workbench or a remote security center which has subscribed the working condition information, for example, when an emergency occurs, the distribution service sends a call request message to the remote security center.
Wherein figure 3 depicts the message interaction between the securing participants.
The expert selection algorithm is as follows. Let E k K e {1,2, ·, N } represents technical experts registered in the remote security center and related organizations, each expert is assigned an attribute table, the structure of the attribute table is shown in fig. 5, for example, X1 represents the speciality of the expert, X2 represents the history record of providing the ship remote security, and X3 represents the trust degree of the security center for the expert. The expert attribute table is maintained and modified by the assurance center.
In addition, a safeguard center is arranged to set M emergency levels, and a safeguard emergency level matrix table is shown inAs shown in fig. 6. For each emergency level e i (i e {1,2, ·, M }) and a corresponding attribute X j (j epsilon {1,2, ·, t }), the assurance center assigns a weight w ij And three parameters, which are respectively (1) minimum support time, in terms of θ i A representation representing the minimum required time for technical support of the class of emergency level failures; (2) Selecting an acceptance threshold of candidate experts by gamma i A representation representing a quantified difference between the candidate expert expertise and the skill required to resolve the class of fault; (3) Maximum wait time before receiving guarantee request message from expert, using tau i Indicating that it represents the minimum time interval from the sending of a message to the receipt of a reply for that type of urgency level. The emergency level is judged by the personnel of the security center according to the fault type and the task type, after a candidate expert is selected, the system forwards a joining request message for joining a candidate group to the candidate expert, and the message field comprises a candidate group code, a notice for processing the type of fault, the position of a fault ship, required spare part information (name, type and quantity) and the like.
After the 'expert allocation decision support service' sends the join request message, the join request message waits for a threshold time tau m Waiting for the candidate expert's response message during the period of time, when tau m Upon expiration or receipt of a requested number of technical expert responses, "expert assignment decision support service" based on expert closeness (γ) of expertise i Representation) and a minimum support time (theta) i Expression), and the like, and further filtering from the ranked list of experts according to the following formula,
in the above formula, X k,p Representing an attribute in the expert resume matrix table, w m,p And representing the weight in the emergency level matrix table, and after the consultation expert group members are determined, interacting an expert distribution decision support service with a consultation assistance layer to start remote guarantee.
During consultation, the 'view management service' creates, maintains and distributes consultation group member views, and each consultation view comprises a group member list of the consultation, resume information of a corresponding expert, fault equipment, maintenance records of a ship, attention matters and the like. In addition, since the expert may be on the move or something in the middle may be temporarily exited, the "view management service" needs to cooperate with the "group management service" to maintain the view, which periodically sends broadcast messages to all group members, who may be considered to be out of contact if no reply message is received within a threshold time. By the above approach, the "group management service" can monitor the join, leave or exit events of the group members.
The ship technical state server needs to be provided with an operating system and a monitoring layer, and simultaneously needs to be supported by remote communication capability and a GPS (global positioning system), a remote security center needs to be provided with a resource distribution layer and a cooperation layer, and an expert terminal can be a computer or a mobile phone and is provided with the cooperation layer. The ship needs to be registered in a security center, and the experts need to be registered in the security center or subordinate expert group managers. The consultation procedure is described below.
When the ship equipment fails, a guarantee request message is sent to a guarantee center, the guarantee center is in contact with the candidate experts through an expert group manager, and once a reply message of the experts is received, the guarantee center establishes a consultation group through a selection algorithm and establishes an online consultation television conference room. Firstly, a consultation group identifier and a group member expert identifier are created through a consultation establishing service and an authority management service of a guarantee center, a group management service module installed on an expert access terminal can receive a consultation group broadcast message and invite a selected expert to join a consultation conference, and after the expert joins the consultation group through the group management service, the view management service provides resumes, service time, basic failure conditions, work division cooperation conditions, attention items and the like of each expert in a group view.
Claims (2)
1. A service-oriented ship remote guarantee resource allocation method is characterized by comprising the following steps: the method comprises the following steps:
1) The ship technical state server integrates the sensing data transmitted from each monitoring point and detects possible faults;
2) The technical state server carries out preliminary diagnosis, if the fault can not be eliminated, a guarantee request is sent to a remote guarantee center, and a possible fault reason can be estimated by a diagnosis algorithm according to the fault phenomenon represented by the sensing data;
3) When the ship technicians cannot solve equipment faults, a guarantee request signal is sent to the surrounding water area through a remote broadcasting means, meanwhile, a guarantee request message is sent to a remote guarantee center through a marine satellite or other remote communication equipment, and if other ships surrounding the faulty ship receive the guarantee request signal and have corresponding spare parts or technical experts, a receiving request message is sent to the guarantee center and actively get close to the faulty ship;
4) The expert shows that the expert is willing to participate in the remote consultation or guarantee action:
marking an expert as a supporter and endowing a supporter code as an access authority for participating in the current remote guarantee; the support is provided with a digital resume, the resume describes the identity, the current position, the professional specialties and the historical guarantee records of the support, and the support can discover, join or leave the remote consultation group through client software and can interact with other supports through the client of the system;
5) The guarantee center receives the guarantee request message:
(1) Obtaining a fault level through preliminary analysis;
(2) Contacting with an expert group manager or an expert to select an expert group member for remote consultation;
(3) After the members of the expert group participating in the guarantee are completely determined, establishing a remote consultation room on the network to help each member to enter the consultation room on the network to analyze and process faults;
in the step 3), if the support of the surrounding ships cannot be obtained, the specific processing method of the security center is as follows:
(1) Searching expert rosters in related fields according to the types of the fault equipment, and implementing grouping management by the remote security experts to improve the resource utilization efficiency: the grouping management comprises longitudinal grouping by unit and transverse grouping by industry association;
(2) When receiving the guarantee request message, the guarantee center firstly sends a guarantee request to the expert group manager, and then the expert group manager informs subordinate units or individuals who can participate in the guarantee;
the safeguard request message includes basic information of the fault, that is: the type, name and delivery time of the failed equipment, the current position of the ship, the fault phenomenon, the current working condition, the collected equipment monitoring data and the required guarantee type;
selecting the expert group members for remote consultation in the step 5):
the emergency level of the fault is judged by a support center personnel according to the fault type and the task type, after a candidate expert is selected, the system forwards a joining request message for joining the candidate group to the candidate expert, and the message field comprises a candidate group code, a notice for processing the type of fault, the position of a fault ship and required spare part information, namely name, type and quantity;
using gamma according to expert's professional proximity i Theta for indicating and minimum support time i Representing, sorting the candidate experts, and further screening from the sorted expert list according to the following formula,
wherein, X k,p Representing an attribute in the expert resume matrix table, w m,p Representing weights in the emergency level matrix table;
the expert selection algorithm is specifically as follows:
let E k K ∈ {1,2, ·, N } represents technical experts registered in the remote security center and related institutions, each expert is assigned an attribute table, wherein X1 represents the speciality of the expert, X2 represents a history record for providing remote security of a ship, and X3 represents the trust degree of the security center for the expert; maintaining and modifying the expert attribute table by the security center;
in addition, a guarantee center is arranged to set M emergency levels, and each emergency level e i I e {1,2, ·, M } and a corresponding attribute X j J is equal to {1,2, ·, t }, the security center assigns a weight w ij And three parameters, which are:
(1) minimum support time in theta i A representation representing the minimum required time for technical support of the class of emergency level failures;
(2) selecting an acceptance threshold for the candidate expert using gamma i A representation representing a quantified difference between the candidate expert expertise and the skill required to resolve the type of fault;
(3) maximum wait time before receiving reply guarantee request message from expert, using tau i Indicating that it represents the minimum time interval from the sending of a message to the receipt of a reply for that type of urgency level.
2. The service-oriented ship remote securing resource allocation method according to claim 1, wherein: in the step 2), the diagnosis algorithm is specifically as follows:
suppose F j Representing the cause of the fault, j =1,2, ·, m, x j i Represents a correspondence F j I =1,2, ·, n; if a certain type of failure F j Probability of occurrence p (F) j ) Known and corresponding to fault class j F j Is the phenomenon of 1 j ，x 2 j ，···，x l j If 1 is equal to or less than l and equal to n, according to Bayes' rule, the following are known:
let p (x) 1 j |F j )，p(x 2 j |F j )，···，p(x l j |F j ) Statistics are irrelevant, then:
substituting equation (3) and equation (2) into equation (1) has:
wherein, p (F) k ) Representing the probability of occurrence of a class k fault, p (x) i j |F j ) Representing the occurrence of a fault of type j (F) j ) Observed when the phenomenon x i The above 2 values determine the accuracy of equation (4), where p (x) i j |F j ) Can be obtained by counting the historical failure phenomenon of the equipment and the corresponding reason, and y is set j As a class j fault F j Observation of phenomenon x at occurrence i j Possibility of (a), y j Is 0 or 1, then there is (1-p) j ) No phenomenon x was observed i j Has p of j Possibility of observing x i j ，y j The distribution of (d) can be expressed by bernoulli experiments as:
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