CN110045211A - A kind of unmanned ships and light boats fault diagnosis filter method - Google Patents
A kind of unmanned ships and light boats fault diagnosis filter method Download PDFInfo
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- CN110045211A CN110045211A CN201910404657.7A CN201910404657A CN110045211A CN 110045211 A CN110045211 A CN 110045211A CN 201910404657 A CN201910404657 A CN 201910404657A CN 110045211 A CN110045211 A CN 110045211A
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- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/005—Testing of electric installations on transport means
- G01R31/008—Testing of electric installations on transport means on air- or spacecraft, railway rolling stock or sea-going vessels
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Abstract
The present invention relates to a kind of unmanned ships and light boats fault diagnosis filter methods.Its daily record data is transmitted to Cloud Server in real time by unmanned ships and light boats, and is monitored in real time by Cloud Server；When expert system detects that unmanned ships and light boats break down, then enter troubleshooting secondary response mechanism: with reference first to the failure cause of previous diagnosis number of success descending arrangement, it determines its failure cause using expert system one by one and handles, it is sounded an alarm if processing is unsuccessful, prompts bank base operator to log in Cloud Server and check simultaneously handling failure.It is calculated the present invention is based on cloud and the technology of expert system can carry out automatic fault detection and processing for the partial electric system failure, improved the efficiency for solving failure, the reliability of unmanned ships and light boats can be greatly improved.
Description
Technical field
The present invention relates to intelligent specialized robot technical field, specifically a kind of unmanned ships and light boats fault diagnosis filter side
Method.
Background technique
Unmanned water surface ships and light boats, or " unmanned water surface aircraft " are a kind of directly by autonomous navigation or remote control with reality
Existing normal/cruise, manipulation and the water surface of operation ships and light boats, are substantially the mobile robots applied to the water surface, research origin is in army
Thing scouts strike.At civilian aspect, unmanned ships and light boats technique functions step a little later, but is equally quickly grown.Have multinational put at present
In the research of unmanned ships and light boats, future will play an increasingly important role, or even can gradually replace manned ships and light boats.
As unmanned boat is using more and more extensive, being completed for task is also more and more arduous, and working environment is increasingly
Complexity, more stringent requirements are proposed for this reliability to unmanned boat.On the other hand, the intelligence and integration degree of unmanned ships and light boats
It improves, boat-carrying electronic electric equipment is more and more, and system also becomes increasingly complex, and electrical system once breaks down, it is possible to
Task performance can be impacted, or even will cause ships and light boats lost contact or major accident.
Using various inspections and test method, discovery system and equipment are fault detections with the presence or absence of the process of failure；And
The process for further determining that guilty culprit substantially position is fault location.And it is replaceable when fault location to implementation being required to repair
The process of product level (replaceable unit) be known as Fault Isolation.Fault diagnosis just refers to the mistake of fault detection and Fault Isolation
Journey.The development of modern age fault diagnosis technology has undergone 30 years, but forms the new integrated discipline of one " fault diagnostics ", still
Gradually grew up in recent years, at different angles from the point of view of, there are many classification methods of fault diagnosis, these methods respectively have spy
Point.Generally, method for diagnosing faults can be divided into: the method for diagnosing faults based on mathematical model, the event based on artificial intelligence
Hinder diagnostic method and other diagnostic methods.
Expert system is a kind of computer intelligence program system with special knowledge and experience based on artificial intelligence technology
System solves the modeling of ability the problem of by human expert, using the representation of knowledge and knowledge reasoning technology in artificial intelligence
The challenge that usually just can solve by expert is simulated, can reach the ability to solve problem same with human expert.This base
It in the design method of knowledge is unfolded centered on knowledge base and inference machine, it may be assumed that expert system=knowledge base+reasoning
Machine.
The technology development of current unmanned ships and light boats is swift and violent, but still suffers from many technologies by unmanned substitution pilot steering
Difficult point.If one of them important viewpoint is exactly all crewman cancelled on ship, the various prominent of navigating ship can not be handled
Send out failure.And fault diagnosis technology will just be puted forth effort to solve this technological difficulties.
And automatic failure can be carried out for the partial electric system failure with the technology of expert system by being calculated based on cloud
Detection and processing, which improves the efficiency for solving failure, can greatly improve the reliability of unmanned ships and light boats.
Summary of the invention
The purpose of the present invention is to provide a kind of unmanned ships and light boats fault diagnosis filter methods, based on cloud calculating and expert
The technology of system can carry out automatic fault detection and processing for the partial electric system failure, improve the effect for solving failure
Rate can greatly improve the reliability of unmanned ships and light boats.
To achieve the above object, the technical scheme is that a kind of unmanned ships and light boats fault diagnosis filter method, nobody
Its daily record data is transmitted to Cloud Server in real time by ships and light boats, and is monitored in real time by Cloud Server；When expert system detects
Unmanned ships and light boats break down, then enter troubleshooting secondary response mechanism: with reference first to previous diagnosis number of success descending arrangement
Failure cause, determine its failure cause one by one and handle using expert system, if handle it is unsuccessful if sound an alarm, prompt bank
Base operator logs in Cloud Server and checks simultaneously handling failure.
In an embodiment of the present invention, this method the specific implementation process is as follows:
(1) expert system is established:
(1.1) data collection: obtaining previous data, establishes unmanned ships and light boats electrical malfunction diagnostic knowledge base；The number
According to including electrical system historical failure case, electrical malfunction diagnostic logic is regular, the navigational posture information of unmanned ships and light boats, electricity
Machine status information, battery status information, each sensor working condition, control software log information；
(1.2) representation of knowledge: fault diagnosis knowledge is described using production rule, the fundamental form of production rule
Formula is IF P THEN Q<CF>, and wherein P and Q respectively corresponds the premise and conclusion of rule, and CF indicates that confidence level, a failure are examined
Disconnected production rule includes rule numbers, regular premise, rule conclusion and confidence level；
(1.3) knowledge acquisition: if the case where encountering with single determining rule threshold or not can determine that failure, uses fuzzy rule
Then diagnose the uncertain problem in electrical malfunction；
(1.4) checkout procedure: after the unmanned ships and light boats electrical malfunction diagnostic knowledge base of Primary Construction, using computer program
In data structure the representation of knowledge is come out, then described in words and shown by man-machine interface again, so as to nothing
Production rule in people's ships and light boats electrical malfunction diagnostic knowledge base is verified；
(1.5) inference machine constructs: inference machine, inference machine implementation are constructed by the way of forward reasoning are as follows: expert system
System by real-time reception to log information be loaded into integrated database, then with unmanned ships and light boats electrical malfunction diagnostic knowledge base
In fault diagnosis production rule matched one by one, using the conclusion of the fault diagnosis production rule of successful match as new
The fact be added in integrated database, matched again with updated integrated database, until drawing a conclusion or
Until not new fault diagnosis production rule can match；
(2) Cloud Server is by the daily record data received and the corresponding storage of address mark, and monitors in real time, and constantly detection is
It is no there are failure symptom or to have occurred and that failure, if identified successfully, carry out failure diagnostic process:
Firstly, by corresponding failure cause in unmanned ships and light boats electrical malfunction diagnostic knowledge base according to diagnosing successfully in the past
Number carries out descending arrangement；Then, it is generated using all fault diagnosises in unmanned ships and light boats electrical malfunction diagnostic knowledge base
Formula rule is matched, and by diagnosing in unmanned ships and light boats electrical malfunction diagnostic knowledge base, the most failure cause of number of success is first
First exported as fault diagnosis and prediction result；Check that electrical system whether there is each failure symptom item by item, if unmanned ships and light boats are electrical
There are failure symptoms for system, and make a definite diagnosis failure cause, then execute exception handles；Using the resource in cloud according to checkout and diagnosis
The information that Obj State obtains, in conjunction with known diagnosis object structure characteristic, parameter, environmental condition and history run, to nobody
Failure that is that ships and light boats electrical system may occur or having occurred and that is analyzed and is judged, determines the property, classification, journey of failure
Degree, reason and position, it is indicated that the trend and consequence of failure occurrence and development propose that control failure continues to develop and eliminate failure
Measure；
(3) it if the untreated success of failure, repeats n times step (2), until n times processing is failed, then sounds an alarm, and
The failure result of initial data and fault diagnosis is exported, operator is fed back to by Web interactive interface, prompts bank base operation
Personnel log in Cloud Server and check simultaneously handling failure；If troubleshooting success, executes step (4)；
(4) if output last diagnostic is as a result, failure is handled successfully by bank base operator simultaneously, operator will most
Effective fault diagnosis report is supplied to Cloud Server eventually, learns for Cloud Server.
In an embodiment of the present invention, the expert system is developed on Windows NT4.0 platform using VC++6.0,
And the foundation and storage of knowledge base are carried out using Microsoft Access.
Compared to the prior art, the invention has the following advantages: the present invention is based on clouds to calculate and expert system
Technology can carry out automatic fault detection and processing for the partial electric system failure, improve the efficiency for solving failure, energy
Enough greatly improve the reliability of unmanned ships and light boats.
Detailed description of the invention
Fig. 1 is the method for the present invention schematic diagram.
Fig. 2 is the method for the present invention flow chart.
Fig. 3 is expert system structure schematic diagram.
Fig. 4 is linear membership function.
Fig. 5 is inference engine schematic diagram.
Fig. 6 is that one embodiment of the invention identifies that ship power supply system jumps the schematic diagram of electricity.
Specific embodiment
With reference to the accompanying drawing, technical solution of the present invention is specifically described.
The present invention provides a kind of unmanned ships and light boats fault diagnosis filter method, unmanned ships and light boats in real time pass its daily record data
Cloud Server is transported to, and is monitored in real time by Cloud Server；When expert system detects that unmanned ships and light boats break down, then enter
Troubleshooting secondary response mechanism: with reference first to the failure cause of previous diagnosis number of success descending arrangement, expert is used one by one
System determines its failure cause and handles, and sounds an alarm if processing is unsuccessful, bank base operator is prompted to log in Cloud Server
Check simultaneously handling failure.This method the specific implementation process is as follows:
(1) expert system is established:
(1.1) data collection: obtaining previous data, establishes unmanned ships and light boats electrical malfunction diagnostic knowledge base；The number
According to including electrical system historical failure case, electrical malfunction diagnostic logic is regular, the navigational posture information of unmanned ships and light boats, electricity
Machine status information, battery status information, each sensor working condition, control software log information；
(1.2) representation of knowledge: fault diagnosis knowledge is described using production rule, the fundamental form of production rule
Formula is IF P THEN Q<CF>, and wherein P and Q respectively corresponds the premise and conclusion of rule, and CF indicates that confidence level, a failure are examined
Disconnected production rule includes rule numbers, regular premise, rule conclusion and confidence level；
(1.3) knowledge acquisition: if the case where encountering with single determining rule threshold or not can determine that failure, uses fuzzy rule
Then diagnose the uncertain problem in electrical malfunction；
(1.4) checkout procedure: after the unmanned ships and light boats electrical malfunction diagnostic knowledge base of Primary Construction, using computer program
In data structure the representation of knowledge is come out, then described in words and shown by man-machine interface again, so as to nothing
Production rule in people's ships and light boats electrical malfunction diagnostic knowledge base is verified；
(1.5) inference machine constructs: inference machine, inference machine implementation are constructed by the way of forward reasoning are as follows: expert system
System by real-time reception to log information be loaded into integrated database, then with unmanned ships and light boats electrical malfunction diagnostic knowledge base
In fault diagnosis production rule matched one by one, using the conclusion of the fault diagnosis production rule of successful match as new
The fact be added in integrated database, matched again with updated integrated database, until drawing a conclusion or
Until not new fault diagnosis production rule can match；
(2) Cloud Server is by the daily record data received and the corresponding storage of address mark, and monitors in real time, and constantly detection is
It is no there are failure symptom or to have occurred and that failure, if identified successfully, carry out failure diagnostic process:
Firstly, by corresponding failure cause in unmanned ships and light boats electrical malfunction diagnostic knowledge base according to diagnosing successfully in the past
Number carries out descending arrangement；Then, it is generated using all fault diagnosises in unmanned ships and light boats electrical malfunction diagnostic knowledge base
Formula rule is matched, and by diagnosing in unmanned ships and light boats electrical malfunction diagnostic knowledge base, the most failure cause of number of success is first
First exported as fault diagnosis and prediction result；Check that electrical system whether there is each failure symptom item by item, if unmanned ships and light boats are electrical
There are failure symptoms for system, and make a definite diagnosis failure cause, then execute exception handles；Using the resource in cloud according to checkout and diagnosis
The information that Obj State obtains, in conjunction with known diagnosis object structure characteristic, parameter, environmental condition and history run, to nobody
Failure that is that ships and light boats electrical system may occur or having occurred and that is analyzed and is judged, determines the property, classification, journey of failure
Degree, reason and position, it is indicated that the trend and consequence of failure occurrence and development propose that control failure continues to develop and eliminate failure
Measure；
(3) it if the untreated success of failure, repeats n times step (2), until n times processing is failed, then sounds an alarm, and
The failure result of initial data and fault diagnosis is exported, operator is fed back to by Web interactive interface, prompts bank base operation
Personnel log in Cloud Server and check simultaneously handling failure；If troubleshooting success, executes step (4)；
(4) if output last diagnostic is as a result, failure is handled successfully by bank base operator simultaneously, operator will most
Effective fault diagnosis report is supplied to Cloud Server eventually, learns for Cloud Server.
The following are specific implementation processes of the invention.
As shown in Figure 1, unmanned ships and light boats fault diagnosis filter method provided by the invention, including expert system fault diagnosis
Method and cloud calculation method.Focus on solving the partial electric system fault diagnosis and processing problem of unmanned ships and light boats.Detailed process
Are as follows: its daily record data is transmitted to Cloud Server in real time by unmanned ships and light boats, and is monitored in real time by Cloud Server.Once expert is
System detects that unmanned ships and light boats break down, then enters troubleshooting secondary response mechanism.With reference first to previous diagnosis number of success
The failure cause of descending arrangement, is determined its failure cause and is attempted to solve, if do not solved the problems, such as using expert system one by one
It then sounds an alarm, prompts bank base operator to log in cloud and check fault condition, taken into account efficiency of fault diagnosis and effect.Such as figure
Shown in 2, process is implemented for the method for the present invention:
(1) expert system is established
The separation of expert system knowledge base and inference machine is highly important technology in Expert System Design.Modern data library
The development of interfacing enables knowledge base preferably to separate with inference machine between technology and programming software and database.It is whole
A system is to be developed on Windows NT4.0 platform using VC++6.0, and this patent is known using Microsoft Access
The foundation and storage in library are known, to play the feature that Input of Data is simple, entry is apparent.
Expert system structure as shown in figure 3, expert system establishment process are as follows:
(1) data collection: engineer and expert or veteran maintenance personnel form team's acquisition and previous data,
For establishing unmanned ships and light boats electrical malfunction diagnostic knowledge base.The data include: electrical system historical failure case, electrically
System fault diagnosis logic rules, navigational posture information, motor status information and the battery status information of unmanned ships and light boats, each sensing
The working condition of device, the log information for controlling software etc..
(2) representation of knowledge: this Expert System Knowledge Expression is described fault diagnosis knowledge using production rule, produces
As soon as raw formula rule is the sentence with " if meeting this condition, what result should be generated " form, citation form is
IF P THEN Q<CF>, wherein P and Q respectively corresponds the premise and conclusion of rule, and CF indicates confidence level, and a rule generally wraps
Include rule numbers, regular premise, rule conclusion and confidence level.
Such as: the starting failure of IF generator, and exciting current is close to zero THEN failure cause: field power supply disappearance confidence
Degree: 0.7, wherein confidence level is for carrying out inexact reasoning.
(3) it knowledge acquisition: if the case where encountering with single determining rule threshold or not can determine that failure, can be used fuzzy
Uncertain problem in rule diagnosis electrical malfunction.For example, working as ship section transmission line of electricity in the event of a failure, merely
Fault point cannot be accurately positioned by comparing nearby voltage and current value and threshold value, therefore the linear membership function pair such as Fig. 4 can be used
Voltage and current value carries out Fuzzy Processing.
Membership function when electric current is normal is
Membership function when electric current is high is
Assuming that u (x)=0.75, i.e., as Ix=20A, the normal confidence level of electric current is 0.75 when current value is 20A.
Membership function when voltage is low is
Membership function when voltage value is normal is
I.e. as Vx=360V, the normal confidence level of voltage is 0.75, and the voltage and current confidence level acquired is fuzzy rule
Confidence level then matches with fuzzy rule as shown in Table 1 available diagnosis again by pretreated voltage and current value
As a result.
Table 1
(4) checkout procedure: after Primary Construction knowledge base, the representation of knowledge can be gone out with the data structure in computer program
Come, then described in words and shown by man-machine interface again, so that electrical system domain expert or engineer are to knowing
The rule known in library is verified.Such as find that rule is wrong, electrical system expert and engineer negotiate to repair rule together
Change, then repeat the work of (2) and (3), until the rule is identified errorless.
(5) inference machine constructs: the program of inference machine and the particular content of knowledge base are unrelated, i.e., inference machine and knowledge base are point
From, this is the important feature of expert system.Its advantages are that the modification to knowledge base need not change inference machine.Inference machine is former
Reason is as shown in Figure 5.
In order to simplify programming system, the method that the reasoning of this patent uses forward reasoning, expert system arrives real-time reception
Log information be loaded into integrated database, then matched, will be succeeded one by one with the diagnostic rule of production in knowledge base
The conclusion of matched rule is added in integrated database as the new fact, carries out again with updated database
Match, until drawing a conclusion or not new rule can match.
Such as shown in Fig. 6: identification ship power supply system jumps electricity, and starting backup power source guarantees that unmanned ship normally supplies first
Electricity, later item by item by investigation failure cause.
(2) server is supervised the daily record data received and the corresponding storage of address mark by Cloud Server in real time
Control.And constantly detect it with the presence or absence of failure symptom or have occurred and that failure, if identified successfully, carry out fault diagnosis mistake
Journey.
Failure cause corresponding in knowledge base is first subjected to descending arrangement according to previous diagnosis number of success, preferentially to power grid
Module carries out the working efficiency that fault diagnosis will greatly improve expert system.Fault diagnosis knowledge base in step (1) is utilized later
In all Failure Diagnostic Codes matched, the most failure cause of number of success will be diagnosed in knowledge base and be used as failure first
The output of diagnosis prediction result.Check that electrical system whether there is each failure symptom item by item, if unmanned ship electrical system exists respectively
Failure symptom then executes exception handles once making a definite diagnosis failure cause.Using the resource in cloud according to checkout and diagnosis object shape
The information that state obtains may send out system in conjunction with known diagnosis object structure characteristic, parameter, environmental condition and history run
Failure that is raw or having occurred and that is analyzed and is judged, determines property, classification, degree, reason and the position of failure, it is indicated that therefore
Hinder the trend and consequence of occurrence and development, proposes that control failure continues to develop and eliminate the measure of failure.
Such as: the reason for causing engine speed unstable can be by previous diagnosis number of success arrangement are as follows:
1, speed probe false alarm
2, sea situation is severe, stormy waves leads to greatly rotary speed unstabilization
3, Main Engine Fuel System is mixed into air
4, governor fault
(3) such as failure is unresolved, optionally, handles according to whether setting carries out second of third time.
(4) last such as failure does not solve yet, then prompts bank base operator's handling failure.Later by initial data and event
The failure result output of barrier diagnosis, feeds back to operator by Web interactive interface, operator debugs accordingly.
(5) last diagnostic result is exported.On the other hand, operator should also propose final effective fault diagnosis report
Cloud Server is supplied, is learnt in this way for Cloud Server, the malfunction elimination ability of server will constantly enhance.
The above are preferred embodiments of the present invention, all any changes made according to the technical solution of the present invention, and generated function is made
When with range without departing from technical solution of the present invention, all belong to the scope of protection of the present invention.
Claims (3)
1. a kind of unmanned ships and light boats fault diagnosis filter method, which is characterized in that unmanned ships and light boats in real time transmit its daily record data
To Cloud Server, and monitored in real time by Cloud Server；When expert system detects that unmanned ships and light boats break down, then into event
Barrier processing secondary response mechanism: with reference first to the failure cause of previous diagnosis number of success descending arrangement, it is using expert one by one
It unites and determines its failure cause and handle, sounded an alarm if processing is unsuccessful, prompt bank base operator to log in Cloud Server and look into
See simultaneously handling failure.
2. a kind of unmanned ships and light boats fault diagnosis filter method according to claim 1, which is characterized in that this method is specific
Realization process is as follows:
(1) expert system is established:
(1.1) data collection: obtaining previous data, establishes unmanned ships and light boats electrical malfunction diagnostic knowledge base；The data packet
Include electrical system historical failure case, electrical malfunction diagnostic logic rule, the navigational posture information of unmanned ships and light boats, motor shape
State information, battery status information, each sensor working condition, control software log information；
(1.2) representation of knowledge: fault diagnosis knowledge is described using production rule, the citation form of production rule is
IF P THEN Q<CF>, wherein P and Q respectively corresponds the premise and conclusion of rule, and CF indicates confidence level, a failure
Diagnosis production rule includes rule numbers, regular premise, rule conclusion and confidence level；
(1.3) knowledge acquisition: if the case where encountering with single determining rule threshold or not can determine that failure, is examined using fuzzy rule
Uncertain problem in disconnected electrical malfunction；
(1.4) checkout procedure: after the unmanned ships and light boats electrical malfunction diagnostic knowledge base of Primary Construction, using in computer program
Data structure comes out the representation of knowledge, is then described in words and is shown by man-machine interface again, so as to unmanned boat
Production rule in ship electrical malfunction diagnostic knowledge base is verified；
(1.5) inference machine constructs: inference machine, inference machine implementation are constructed by the way of forward reasoning are as follows: expert system will
Real-time reception to log information be loaded into integrated database, then in unmanned ships and light boats electrical malfunction diagnostic knowledge base
Fault diagnosis production rule is matched one by one, using the conclusion of the fault diagnosis production rule of successful match as new thing
It is added in integrated database in fact, is matched again with updated integrated database, until drawing a conclusion or not having
Until new fault diagnosis production rule can match；
(2) Cloud Server is by the daily record data received and the corresponding storage of address mark, and monitors in real time, constantly detects whether to deposit
It in failure symptom or has occurred and that failure, if identified successfully, carries out failure diagnostic process:
Firstly, by corresponding failure cause in unmanned ships and light boats electrical malfunction diagnostic knowledge base according to previous diagnosis number of success
Carry out descending arrangement；Then, it is advised using all fault diagnosis production in unmanned ships and light boats electrical malfunction diagnostic knowledge base
It is then matched, the most failure cause of number of success will be diagnosed in unmanned ships and light boats electrical malfunction diagnostic knowledge base and is made first
For the output of fault diagnosis and prediction result；Check that electrical system whether there is each failure symptom item by item, if unmanned ships and light boats electrical system
There are failure symptoms, and make a definite diagnosis failure cause, then execute exception handles；Using the resource in cloud according to checkout and diagnosis object
The information that state obtains, in conjunction with known diagnosis object structure characteristic, parameter, environmental condition and history run, to unmanned ships and light boats
Failure that is that electrical system may occur or having occurred and that is analyzed and is judged, determines property, classification, degree, the original of failure
Cause and position, it is indicated that the trend and consequence of failure occurrence and development propose that control failure continues to develop and eliminate the measure of failure；
(3) it if the untreated success of failure, repeats n times step (2), until n times processing is failed, then sounds an alarm, and will be former
The output of the failure result of beginning data and fault diagnosis feeds back to operator by Web interactive interface, prompts bank base operator
It logs in Cloud Server and checks simultaneously handling failure；If troubleshooting success, executes step (4)；
(4) if output last diagnostic is as a result, failure is handled successfully by bank base operator simultaneously, operator will finally have
The fault diagnosis report of effect is supplied to Cloud Server, learns for Cloud Server.
3. a kind of unmanned ships and light boats fault diagnosis filter method according to claim 1 or 2, which is characterized in that described special
Family's system is developed on Windows NT4.0 platform using VC++6.0, and carries out knowledge base using Microsoft Access
Foundation and storage.
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| CN112256538A (en) * | 2020-09-01 | 2021-01-22 | 北京航天控制仪器研究所 | Unmanned ship equipment information acquisition processing and control method |
| CN113281616A (en) * | 2021-05-28 | 2021-08-20 | 国网冀北电力有限公司承德供电公司 | Power transmission line fault diagnosis method, system and framework based on expert system |
| CN113433874A (en) * | 2021-07-21 | 2021-09-24 | 广东工业大学 | 5G-based unmanned ship comprehensive control management system and method |
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