CN107545250A - A kind of ocean floating motion Real-time Forecasting System based on the remote sensing of wave image and artificial intelligence - Google Patents
A kind of ocean floating motion Real-time Forecasting System based on the remote sensing of wave image and artificial intelligence Download PDFInfo
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- CN107545250A CN107545250A CN201710769596.5A CN201710769596A CN107545250A CN 107545250 A CN107545250 A CN 107545250A CN 201710769596 A CN201710769596 A CN 201710769596A CN 107545250 A CN107545250 A CN 107545250A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
- B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING
- B63B79/00—Monitoring properties or operating parameters of vessels in operation
- B63B79/30—Monitoring properties or operating parameters of vessels in operation for diagnosing, testing or predicting the integrity or performance of vessels
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
- B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING
- B63B35/00—Vessels or similar floating structures specially adapted for specific purposes and not otherwise provided for
- B63B35/44—Floating buildings, stores, drilling platforms, or workshops, e.g. carrying water-oil separating devices
- B63B2035/4433—Floating structures carrying electric power plants
- B63B2035/446—Floating structures carrying electric power plants for converting wind energy into electric energy
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/044—Recurrent networks, e.g. Hopfield networks
- G06N3/0442—Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0464—Convolutional networks [CNN, ConvNet]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/09—Supervised learning
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Abstract
The present invention relates to a kind of ocean floating motion Real-time Forecasting System based on the remote sensing of wave image and artificial intelligence.Marine environment big data is obtained by marine environment sensor assembly first, floating body dynamic response big data is obtained by floating body dynamic response sensor assembly simultaneously, then two class data are sent to data storage, it is then stored into database, trained followed by the data stored in data storage to train artificial intelligence learning module, establish the artificial intelligence forecasting model of the reaction floating motion based on ocean imagery input, finally by the artificial intelligence forecasting model after training, and it is based on marine environment big data and floating body dynamic response big data, establish floating motion response real-time prediction module, and result is completely transferred in aid decision module and computer.The present invention provides safe operation window and decision-making assistant information for the operation on the sea influenceed by floating motion, solves the problems, such as how safe efficient operation is carried out in the case of floating body sways.
Description
Technical field
The invention belongs to Naval Architecture and Ocean Engineering field, and in particular to a kind of based on the remote sensing of wave image and artificial intelligence
Ocean floating motion Real-time Forecasting System.
Background technology
Ocean platform is that people explore ocean, develop the important tool of oceanic mineral resources, is widely used in ocean engineering
Every field in remittance.From being designed into the Life cycle of operation for ocean platform, ocean stormy waves environment and its caused
Ocean platform motor imagination is platform operation on the sea and the major influence factors of platform structure safety all the time.Excessive wave is with putting down
Platform athletic meeting to offshore lifting, oil recovery, drilling well, dynamic positioning, platform helicopter take off landing etc. operation bring adverse effect.
The influence of ocean stormy waves and platform motion to operation on the sea safety can be embodied by the following aspects：
First is drillng operation, when ocean platform carries out drillng operation, it is necessary to drilling rod is put down from platform until
Seabed, drillng operation is carried out by the Mechanical Driven drilling rod carried on platform.This requires platform relative to drilling well position remains stationary
Or can only in allowed band small movements.
Second is helicopter landing, and platform is located on sea, and the transportation means of routine replenishment and personnel equipment are difficult to
Realize, helicopter is especially suitable for the transport on platform as a kind of air transport mode.But helicopter is in landing operation pair
Having a great influence for platform deck motion, usually requires that the motion of helicopter deck is less than certain value, otherwise helicopter can be caused to drop
Deck is hit when falling, leads to not regular descent or even threatens the safety of helicopter and platform.
3rd is hoisting operation, and lifting is the most frequently one of operation on ocean platform, carrying, goods such as equipment
Supply of thing etc..During hoisting operation, crane gear can there are certain requirements when lifting goods to the motion of platform.Work as wave
When larger, excessive transverse movement can cause lifting goods generation acutely to be waved, and be threatened to platform and operation on the sea safety belt：
On the one hand the safety that other structures threaten platform can be hit, on the other hand can also increase the load of crane gear, it is possible to break
Rope causes huge wink to lose.And excessive catenary motion, jack machinism can be caused to have a volume when crane gear
Outer acceleration, can cause jack machinism stress suddenly increase or reduce, cause crane inadequacy of lifting capacity or
Crane instantaneous power is excessive, burn motor, cause machinery burn or cord break, serious threat lifting process and lifting
The safety of machine in itself.
4th is personnel's conveying, and in addition to helicopter, ship is to the another important of platform transportation work personnel
Means.And personnel from ship to platform or be from platform to ship on, be all real by taking similar lift " hanging basket "
Existing (as shown in Figure 3).During personnel lifting, platform athletic meeting is to equipment safety or even the life security of staff
Cause serious threat.
5th is work compound between platform, for ocean platform, when production platform store a number of crude oil with
Afterwards, it is necessary to which this part oil is carried out, this is needed by means of shuttle tanker, when platform and shuttle tanker carry out oil transportation operation
When, due to conventional transportation oil be by the way of suspension cable pipeline, it is no therefore it is required that the relative position of the two is less than certain value
Then operation be able to not will be normally carried out resulting even in the safety that pipeline is torn threat platform and shuttle tanker.Except the oil that shuttles
Outside wheel, some ocean platforms need other assistance platforms to help to carry out operation, such as：982 platforms need Eton platform to make
Coordinate for power management platform and be operated；Production platform needs to coordinate shuttle tanker or FPSO to carry out transport and the place of oil
Reason.Among the process transported and handled, it is desirable to which the relative displacement between platform need to be less than the boundary allowed, otherwise, it is most likely that
The destruction of attachment structure between platform is caused, danger is brought to operating personnel and equipment safety.
6th is platform Attention problems, and during platform construction, the installation of top module is generally at sea carried out.And
During stage+module, target platform does not allow to occur significantly moving with job platform.For floating support mounting operation, API
The limitation of barge mooring line limit tension and factor of safety is given, when wave is larger, mooring line stress exceedes code requirement
Installation process can be influenceed or even the safety of platform and barge can be threatened.For crane barge method, when crane barge is in larger wave
During operation, it can be difficult to be directed at installation site influence normal mounting platform, when motion amplitude is excessive, result even in safe thing
Therefore.
To sum up analyze, ocean stormy waves is the principal element for causing platform motion external drive, and platform motion can be to flat
Platform operation on the sea and platform structure threaten safely.Thus, the exercise performance of wave and platform carries out pre- in real time around platform
Report, to ensureing that ocean floating operation has great importance safely.On the one hand, can be to carry out drillng operation, go straight up to by forecast
Machine takes off landing, platform Attention problems, platform hoisting operation etc., there is provided the operation window of a safety；On the other hand, oceanic winds
Wave and the real-time prediction information of platform motion input but also as the control decision of dynamic positioning system, improve determining for ocean platform
Position performance.
On the real-time prediction of floating motion, existing method is based primarily upon the theoretical modeling with floating body hydrodynamics of wave
Method.Because physical process is complicated, this kind of modeling method is realized difficult, it is necessary to very long lead time, and needs what is put into
Research cost is larger.And as the development of computer level, artificial intelligence technology are developed rapidly, due to its have it is powerful
Learning ability, artificial intelligence technology is widely used in the complicated physical problem of analysis.Therefore, the present invention proposes a kind of based on sea
Unrestrained image remote sensing and the ocean floating motion Real-time Forecasting System of artificial intelligence, by artificial intelligence forecasting model, realize to floating
The real-time prediction of body exercise performance, decision support is provided safely for operation on the sea.
And it is current, there are not similar or like ocean floating motion real-time prediction and aid decision to support system both at home and abroad
System.
The content of the invention
It is an object of the invention to provide a kind of ocean floating motion based on the remote sensing of wave image and artificial intelligence is real-time
Forecast system, it is intended to which the operation on the sea to be influenceed by floating motion provides the operation window and decision-making assistant information of safety, solves
How safe efficient operation is carried out in the case of floating body sways the problem of.
The object of the present invention is achieved like this：
A kind of ocean floating motion Real-time Forecasting System based on the remote sensing of wave image and artificial intelligence, including marine environment
Sensor assembly 8, floating body dynamic response sensor assembly 10, marine environment big data 9, floating body dynamic response big data 11, number
It is described according to storage 12, artificial intelligence study module 14, floating body dynamic response real-time prediction module 16, aid decision module 17
Marine environment sensor assembly 8 obtains the marine environment big data 9 of floating body position and surrounding, while by floating body dynamic response
Sensor assembly 10 obtains floating body dynamic response big data 11；Then by marine environment big data 9 and the big number of floating body dynamic response
Data storage 12 is sent to according to 11 obtained data, is then stored into database 13；Followed by what is stored in data storage 12
Data are trained to train artificial intelligence learning module 14, and depth is carried out to floating motion And Real-time Forecasting Model using big data
Practise, neural network model is largely trained, the artificial intelligence for establishing the reaction floating motion based on ocean imagery input is pre-
Report model；Finally by the artificial intelligence forecasting model after training, and the big number of marine environment that sensor based system gathers in real time
According to 9 and floating body dynamic response big data 11, floating motion response real-time prediction module 16 is established；Floating motion responds real-time prediction
The result that module 16 obtains is completely transferred in aid decision module 17 and computer 18.
Described marine environment sensor assembly 8 is by X-band navigation radar system 1, binocular vision system 4, high with ship wave
Instrument 5, integrated number are adopted 6, sensor acquisition terminal 7 and formed.
Described binocular vision system 4 by left video camera 2 and right video camera 3, manipulation unit, power module, measurement module,
Locating module, interchanger and mounting bracket composition, wherein, measurement module is marked level large area array high-sensitivity camera by Liang Ge armies and determined
Position support composition, locating module are made up of compass, accelerometer and differential GPS.
Rolling, pitching, yawing, swaying, surging and heaving of the described floating body dynamic response big data 11 including floating body are
The motion of six-freedom degree and the structural parameters in key operation region.
In described artificial intelligence study module 14, wave characteristics of image is extracted using convolutional neural networks (CNN)；Simultaneously
Using the exercise performance of LSTM network model real-time prediction platforms.
Described artificial intelligence study module 14 is based on the basis of a high-performance server 15.
The beneficial effects of the present invention are：
Object platform Life cycle operation on the sea of the present invention, there is provided a kind of based on the remote sensing of wave image and artificial intelligence
Ocean floating motion forecast system, service is provided for operation on the sea security decision.As China is to ocean exploration and marine resources
Exploitation is progressively goed deep into, and operation on the sea will be increased, how to ensure that platform and its safety of operation on the sea will turn into stormy waves
The problem of becoming increasingly conspicuous is the research emphasis of Abroad in Recent Years scholar, and current, and domestic correlative study is few, and there is no has
Autonomous achievement in research and products application.Therefore, the present invention has very strong application prospect and good economic value.
Brief description of the drawings
Fig. 1 be a kind of ocean floating motion forecast system based on the remote sensing of wave image and artificial intelligence structure composition and
Workflow diagram.
Fig. 2 is the cut-away view that binocular vision of the present invention surveys unrestrained system.
Fig. 3 is wave image characteristics extraction convolutional neural networks (CNN) model structure of the present invention and flow chart.
Fig. 4 is that floating motion real-time prediction shot and long term of the present invention remembers (LSTM) model structure and flow chart.
Embodiment：
The present invention will be further described below in conjunction with the accompanying drawings：
Embodiment 1
As shown in Fig. 1 to 4, the invention mainly relates to a kind of ocean floating body based on the remote sensing of wave image and artificial intelligence to transport
Dynamic Real-time Forecasting System, including marine environment sensor assembly 8, floating body dynamic response sensor assembly 10, the big number of marine environment
According to 9, floating body dynamic response big data 11, data storage 12, artificial intelligence study module 14, floating body dynamic response real-time prediction mould
Block 16, aid decision module 17.The wave environment big data 9 that the present invention is obtained based on marine environment sensor assembly 8, by floating
The floating body dynamic response big data 11 of body dynamic response sensor assembly 10, then the deep learning by artificial intelligence, extract ocean
The feature of stormy waves ambient image, the intelligent prediction model of wave stormy waves ambient image and floating body dynamic response is improved, is then established
Floating body dynamic response real-time prediction module 16, realizes the real-time prediction to floating motion performance.Specifically, first, sea is passed through
Foreign environmental sensor module 8 obtains marine environment image big data, and X-band navigation radar system 1 is several around floating body for measuring
The ocean stormy waves information of kilometer range, binocular vision system 4 are used in instrumentation radar system blind area tens meters of scopes around floating body
Ocean stormy waves information, be used to measure the wave stormy waves information of floating body position with ship wave height recorder 5；Rung simultaneously by floating body power
Inductive sensing device module 10 obtains floating motion big data；Secondly, by data storage 12 and database 13, to marine environment and float
Body response big data is stored.And artificial intelligence study module 14 is largely trained using data, establish based on sea
The floating body dynamic response real-time prediction module 16 of foreign image, and result is fed back in computer 18 and aid decision module 17,
The real-time prediction to floating motion response is realized, technical support is provided for operation on the sea based on forecast result.It is contemplated that it is
The operation on the sea influenceed by floating motion provides the decision-making assistant information in the operation window and aid decision module 17 of safety, solution
Certainly how safe efficient operation is carried out in the case of floating body sways the problem of.
Marine environment sensor assembly 8 by X-band navigation radar system 1, binocular vision system 4, with ship wave height recorder 5, collection
6, sensor acquisition terminal 7 is adopted into number to form, X-band navigation radar system 1 is used for the sea for measuring several kilometer ranges around floating body
Foreign stormy waves information, binocular vision system 4 are used in instrumentation radar system blind area the ocean stormy waves letter of tens meters of scopes around floating body
Breath, the wave stormy waves information for measuring floating body position is then used for ship wave height recorder 5, passes through the sensor system of different measurement ranges
System combination, structure measurement range can cover floating body position to the marine environment sensing module of several kilometers of surrounding.It is therein
Binocular vision system 4 is by left video camera 2 and right video camera 3, manipulation unit, power module, measurement module, locating module, exchange
Machine and mounting bracket composition, wherein, measurement module marks level large area array high-sensitivity camera by Liang Ge armies and locating support forms, fixed
Position module is made up of compass, accelerometer and differential GPS.
Rolling, pitching, yawing, swaying, surging and the heaving of floating body dynamic response big data 11 including floating body be six from
By the motion spent and the structural parameters in key operation region.
The present invention specific implementation flow be：
(1) the marine environment image big data of floating body position and surrounding is obtained by marine environment sensor assembly 8, is led to
The sensing system combination of different measurement ranges is crossed, structure measurement range can cover floating body position to several kilometers of surrounding
Marine environment sensing module.
(2) floating motion big data is obtained by floating body dynamic response sensor assembly 10.
(3) on sensor acquisition terminal 7,6 is adopted by integrated number and is rung by marine environment sensor assembly 8 and floating body power
Inductive sensing device module 10 obtains marine environment big data 9 and floating body dynamic response big data 11 in real time.
(4) data that marine environment big data 9 and floating body dynamic response big data 11 obtain are sent to data storage 12,
It is then stored into database 13.
(5) big data stored in database 13 is utilized to train artificial intelligence learning module 14.Specifically, it is using big
Data carry out deep learning to floating motion And Real-time Forecasting Model, and neural network model is largely trained, and establish based on sea
The floating motion artificial intelligence forecasting model of foreign image input.
(6) by the artificial intelligence forecasting model after training, based on marine environment big data 9 and floating body dynamic response big data
11, floating motion response real-time prediction module 16 is established, realizes the real-time prediction to floating motion response, floating motion response is in fact
When the obtained result of forecast module 16 be completely transferred in aid decision module 17 and computer 18, influenceed by floating motion
Operation on the sea provides the decision-making assistant information in the operation window and aid decision module 17 of safety, solves how in floating body to occur
The problem of safe efficient operation is carried out in the case of swaying
In manual's intelligence learning module 14, wave image characteristics extraction is carried out using convolutional neural networks (CNN)；
There is preferable property in terms of the temporal aspect extraction of processing dynamic data in view of shot and long term memory (LSTM) network model simultaneously
Can, the real-time prediction that platform exercise performance is carried out using LSTM network models is studied.CNN neural network models and LSTM nerve nets
The structure difference of network model is as shown in Figure 3 and Figure 4.
Embodiment 2
The present invention relates to a kind of ocean floating motion Real-time Forecasting System based on the remote sensing of wave image and artificial intelligence, it is
System includes marine environment sensor assembly 8, floating body dynamic response sensor assembly 10, marine environment big data 9, floating body power and rung
Answer big data 11, data storage 12, artificial intelligence study module 14, floating body dynamic response real-time prediction module 16, aid decision
Module 17.
Marine environment sensor assembly 8 by X-band navigation radar system 1, binocular vision system 4, with ship wave height recorder 5, collection
6, sensor acquisition terminal 7 is adopted into number to form.Wherein X-band navigation radar system 1 is used to measure several kilometer ranges around floating body
Ocean stormy waves information, binocular vision system 4 is used for the oceanic winds of tens meters of scopes around floating body in instrumentation radar system blind area
Unrestrained information, the wave stormy waves information for measuring floating body position is then used for ship wave height recorder 5, passes through the sensing of different measurement ranges
Device system in combination, structure measurement range can cover floating body position to the marine environment sensing module of several kilometers of surrounding.And
And on sensor acquisition terminal 7,6 are adopted by marine environment sensor assembly 8 and floating body dynamic response sensor by integrated number
Module 10 obtains marine environment big data 9 and floating body dynamic response big data 11 in real time.
Binocular vision system 4 is by left video camera 2 and right video camera 3, manipulation unit, power module, measurement module, positioning mould
Block, interchanger and mounting bracket composition, wherein, measurement module marks level large area array high-sensitivity camera and locating support by Liang Ge armies
Composition, locating module are made up of compass, accelerometer and differential GPS.
Marine environment sensor assembly 8 obtains the marine environment big data 9 of floating body position and surrounding, while by floating body
Dynamic response sensor assembly 10 obtains floating body dynamic response big data 11, and floating body dynamic response big data 11 includes floating body
Rolling, pitching, yawing, swaying, surging and heaving are motion and the structural parameters in key operation region of six-freedom degree；Then
Send the data that marine environment big data 9 and floating body dynamic response big data 11 obtain to data storage 12, be then stored into number
According in storehouse 13；Trained followed by the data stored in data storage 12 to train artificial intelligence learning module 14, utilize big number
Deep learning is carried out according to floating motion And Real-time Forecasting Model, neural network model is largely trained, foundation is based on ocean
The artificial intelligence forecasting model of the reaction floating motion of image input.It is worth noting that, in artificial intelligence study module 14,
Wave characteristics of image is extracted using convolutional neural networks (CNN)；Locating simultaneously in view of shot and long term memory (LSTM) network model
There is preferable performance in terms of the temporal aspect extraction for managing dynamic data, using the motility of LSTM network model real-time prediction platforms
Can, and the use of artificial intelligence module will be based on a high-performance server 15, so accelerate the processing speed of data；
Finally by the artificial intelligence forecasting model after training, based on marine environment big data 9 and floating body dynamic response big data 11, establish
Floating motion response real-time prediction module 16, the result that floating motion response real-time prediction module 16 obtains are completely transferred to calculate
Machine 18 and aid decision module 17, the operation on the sea to be influenceed by floating motion provide the operation window and aid decision mould of safety
Decision-making assistant information in block 17, solve the problems, such as how safe efficient operation is carried out in the case of floating body sways.
Here it must be noted that other the unaccounted structures provided in the present invention are because be all the known knot of this area
Structure, according to title of the present invention or function, those skilled in the art can just find the document of related record, therefore not do
Further illustrate.Technological means disclosed in this programme is not limited only to the technological means disclosed in above-mentioned embodiment, in addition to
Formed technology is combined by above technical characteristic.
Claims (6)
1. a kind of ocean floating motion Real-time Forecasting System based on the remote sensing of wave image and artificial intelligence, including marine environment pass
Sensor module (8), floating body dynamic response sensor assembly (10), marine environment big data (9), floating body dynamic response big data
(11), data storage (12), artificial intelligence study module (14), floating body dynamic response real-time prediction module (16), aid decision
Module (17), it is characterised in that:Described marine environment sensor assembly (8) obtains the ocean ring of floating body position and surrounding
Border big data (9), while floating body dynamic response big data (11) is obtained by floating body dynamic response sensor assembly (10)；Then will
The data that marine environment big data (9) and floating body dynamic response big data (11) obtain send data storage (12) to, then store
Into database (13)；Trained followed by the data of storage in data storage (12) to train artificial intelligence learning module
(14) deep learning, is carried out to floating motion And Real-time Forecasting Model using big data, neural network model is largely trained,
Establish the artificial intelligence forecasting model of the reaction floating motion based on ocean imagery input；It is finally pre- by the artificial intelligence after training
Model, and the marine environment big data (9) and floating body dynamic response big data (11) that sensor based system gathers in real time are reported, is built
Vertical floating motion response real-time prediction module (16)；The result that floating motion response real-time prediction module (16) obtains all transmits
Into aid decision module (17) and computer (18).
A kind of 2. ocean floating motion real-time prediction based on the remote sensing of wave image and artificial intelligence according to claim 1
System, it is characterised in that：Described marine environment sensor assembly (8) is by X-band navigation radar system (1), binocular vision system
Unite (4), with ship wave height recorder (5), integrated number adopt (6), sensor acquisition terminal (7) forms.
A kind of 3. ocean floating motion real-time prediction based on the remote sensing of wave image and artificial intelligence according to claim 1
System, it is characterised in that：Described binocular vision system (4) is by left video camera (2) and right video camera (3), manipulation unit, power supply
Module, measurement module, locating module, interchanger and mounting bracket composition, wherein, measurement module marks level large area array height by Liang Ge armies
Sensitivity camera and locating support composition, locating module are made up of compass, accelerometer and differential GPS.
A kind of 4. ocean floating motion real-time prediction based on the remote sensing of wave image and artificial intelligence according to claim 1
System, it is characterised in that：It is the rolling of described floating body dynamic response big data (11) including floating body, pitching, yawing, swaying, vertical
Swing the structural parameters with the heaving i.e. motion of six-freedom degree and key operation region.
A kind of 5. ocean floating motion real-time prediction based on the remote sensing of wave image and artificial intelligence according to claim 1
System, it is characterised in that：In described artificial intelligence study module (14), wave figure is extracted using convolutional neural networks (CNN)
As feature；Simultaneously using the exercise performance of LSTM network model real-time prediction platforms.
A kind of 6. ocean floating motion real-time prediction based on the remote sensing of wave image and artificial intelligence according to claim 5
System, it is characterised in that：Described artificial intelligence study module (14) is based on the basis of a high-performance server (15).
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