CN109751986A - A kind of processing system and method generating AR image according to pipe network attribute data - Google Patents
A kind of processing system and method generating AR image according to pipe network attribute data Download PDFInfo
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Abstract
The present invention relates to the visual images of pipe network to generate field, a kind of processing system that AR image is generated according to pipe network attribute data, including memory module is specifically provided, for storing the threedimensional model and corresponding coordinate of pipe network；Locating module, for being positioned to current location；Locating module, which uses, is based on GPS, GLONASS, the compound fixed resolving Algorithm of BEI-DOU position system, also uses SLAM and high-precision spatial location technology；Calling module transfers the threedimensional model of the pipe network of current location from memory module；Shooting module is acquired for the outdoor scene to current location；AR generation module generates pipe network AR image according to the pipe network in three-dimensional model of current location and outdoor scene picture；Display module shows pipe network AR image.It is affected using the signal of this system, i.e. some satellite positioning, also can accurately obtain the coordinate of current location.The present invention also provides a kind of processing methods that AR image is generated according to pipe network attribute data.
Description
Technical field
Field is generated the present invention relates to the visual image of pipe network more particularly to a kind of according to pipe network attribute data generation AR
The processing system and method for image.
Background technique
Pipe network refers to and is usually all embedded in underground for transporting water, gas or the pipeline of liquefied petroleum, pipe network.When to pipe network into
When row maintenance, current main stream approach is after manually finding the position of pipe network, to safeguard to pipe network, but such mode
To the more demanding of staff, since pipe network is largely all embedded in underground, as peripherally target changes, the position of pipe network is searched
It is easy to appear deviations when setting, and therefore, the road surface for being frequently seen embedding pipe network is excavated everywhere, exactly in order to find pipe network really
Positioning is set.
The unresolved above problem, Chinese patent CN106990419A disclose a kind of based on the accurate service network of Beidou and AR skill
The gas leakage detection system of art, including Beidou positioning module, infrared laser leak detection module, data processing module, AR increase
Strong reality module.The patent can look into pipe network using visual mode by the utilization to AR augmented reality
It sees, when being excavated, can accurately find the position of pipe network.
But the locating module of the patent only uses Beidou positioning module, and Beidou navigation is started late in navigation field,
Development is not full maturity can be relatively accurate under the preferable environment of signal, but in the place of dtr signal, positions meeting
There is failure, e.g., in the region that high-lager building is intensive, since signal will receive the influence of building, the accuracy of positioning is difficult
To guarantee.The system is used when positioning accuracy is difficult to ensure, still will appear to excavate everywhere can just find the correct position of pipe network
The case where setting.
Summary of the invention
The present invention for the prior art under the preferable environment of signal, can be relatively accurate, but in the place of dtr signal,
Its positioning will appear failure, still will appear the problem of excavating the case where capable of just finding pipe network correct position everywhere, provides one
Kind generates the processing system and method for AR image according to pipe network attribute data.
Base case provided by the invention are as follows:
A kind of processing system generating AR image according to pipe network attribute data, including server and user terminal；
Server includes memory module, for storing the threedimensional model and corresponding coordinate of pipe network；
User terminal includes locating module, calling module, shooting module, AR generation module and display module；
Locating module, for being positioned to current location；Locating module is used to be positioned based on GPS, GLONASS, Beidou
The compound fixed resolving Algorithm of system also uses SLAM and high-precision spatial location technology；
Calling module transfers the threedimensional model of the pipe network of current location from memory module；
Shooting module is acquired for the outdoor scene to current location；
AR generation module generates pipe network AR image according to the pipe network in three-dimensional model of current location and outdoor scene picture；
Display module shows pipe network AR image.
Explanation of nouns: SLAM (simultaneous localization and mapping), also referred to as CML
(Concurrent Mapping and Localization), immediately positioning and map structuring, can in moving process basis
Location estimation and sensing data carry out self poisoning, while building increment type map；
GLONASS, the GPS made for Russia；
Fixed resolving Algorithm: when positioning using carrier phase observation data, fuzziness can be generated, fuzziness is theoretically
Integer.After the fuzziness for solving integer by algorithm, positioning accuracy can be increased substantially.
Base case working principle and beneficial effect:
After locating module positions current location, calling module recalls the threedimensional model of the pipe network in the region, acquisition
After module is acquired current outdoor scene, the pipe network AR image of current location is generated, overhauls and uses for staff.This system
Locating module use be based on GPS, GLONASS, the compound fixed resolving Algorithm of BEI-DOU position system, can be by the accuracy of outdoor positioning
Control can accurately be completed to position when signal is preferable within 1 centimetre of error；The locating module of this system also uses simultaneously
SLAM and high-precision spatial location technology can be generated current in time by SLAM and the auxiliary of high-precision spatial location technology
The map of position.Compared in the prior art using single location technology, this system due to used be based on GPS, GLONASS,
The compound fixed resolving Algorithm of BEI-DOU position system, is able to carry out more accurate positioning.
Further, the shooting module completes material object in the real world with the artificial intelligence learning art of FusionNet
Identification.
Currently, being still for identification in kind in the real world in the environment of the picture recognitions technology maturation such as two dimensional code
One huge challenge.This system completes this demand using the artificial intelligence learning art of FusionNet, and FusionNet is three
The mixing of kind neural network, they are V-CNN I, V-CNN II and MV-CNN respectively, and MV-CNN neural network is to be based on
The building of AlexNet structure, and pass through ImageNet data set pre-training mistake, these three networks are merged in scoring layer,
The classification finally predicted is found in linear combination by calculating marking.V-CNN I and V-CNN II has used the CAD of voxelization
Model, MV-CNN then use 2D projection as input.This system has used standard pre-training neural network model (AlexNet) to make
For the basis of 2D network MV-CNN, warm starting pre-training is carried out to the network of three-dimension object 2D projection and is based on extensive 2D pixel map
Sheet data collection ImageNet.It is influenced by pre-training, feature of many for 2D image classification does not need to have trained from the beginning.
Further, in the generating process of AR image, locating module also uses magnetic other than being positioned with GNSS and SLAM
Power meter carries out space and moves towards sensing, is sensed with accelerometer to space plane, is sensed with gyroscope to rotary viewing angle.
By the sensing of space trend, space plane and rotary viewing angle, the pipe network in three-dimensional model for enabling modeling module to establish
It is enough accurately to be projected in real space, realize the mapping one by one of Virtual Space data and real space data.
Another object of the present invention is to provide a kind of processing method that AR image is generated according to pipe network attribute data, comprising:
Storing step, by the threedimensional model of pipe network and the storage of corresponding coordinate into server；
Positioning step positions current location；Positioning step, which uses, is based on GPS, GLONASS, BEI-DOU position system
Compound fixed resolving Algorithm also uses SLAM and high-precision spatial location technology；
Invocation step transfers the threedimensional model of the pipe network of current location from server；
Step is shot, the outdoor scene of current location is acquired；
AR generation step generates pipe network AR image according to the pipe network in three-dimensional model of current location and outdoor scene picture；
It shows step, pipe network AR image is shown.
Further, it shoots in step, completes knowledge in kind in the real world with the artificial intelligence learning art of FusionNet
Not.
Further, in AR generation step, other than being held in position with GNSS and SLAM, space also is carried out with magnetometer and is walked
To sensing, space plane is sensed with accelerometer, rotary viewing angle is sensed with gyroscope.
Detailed description of the invention
Fig. 1 is a kind of logical framework for the processing system embodiment that AR image is generated according to pipe network attribute data of the present invention
Figure.
Specific embodiment
It is further described below by specific embodiment:
As shown in Figure 1, a kind of system that three-dimensional visualization image is generated according to pipe network attribute data, including server and use
Family terminal.
Server
Server is used to store the attribute data of pipe network, the coordinate including pipe network, the pipe network diameter of pipe network, pipe network model and
Pipe network depth；Server is Tencent's Cloud Server in the present embodiment；
User terminal
User terminal include locating module, matching module, calling module, modeling module, shooting module, AR generation module and
Display module.
Locating module is used to obtain the coordinate of user terminal current location；Locating module is GNSS positioning, using being based on
The compound fixed resolving Algorithm of GPS, GLONASS, BEI-DOU position system, can be by the accuracy controlling of outdoor positioning at 1 centimetre of error
Within；Meanwhile locating module also facilitates SLAM and high-precision spatial location technology, influences since GNSS will receive building etc.
Its precision, therefore auxiliary is positioned with SLAM, guarantees the accuracy of the coordinate of acquisition.
Matching module is used for the coordinate obtained according to locating module, and coordinate matching is carried out in Cloud Server, matches position
In the pipe network of the coordinate；By matching module, the attribute data of the pipe network at present co-ordinate position is found.
Calling module is used to transfer the attribute data of the matched pipe network of matching module to Cloud Server；
There is the bare bones of pipe network in three-dimensional model in modeling module；After calling module transfers the attribute data of pipe network, modeling
Module carries out the three-dimensional modeling of the pipe network of changing coordinates according to the attribute data transferred on the basis of bare bones.
Shooting module is for being acquired the outdoor scene of current location；Currently, the picture recognitions technology maturation such as two dimensional code
It is still a huge challenge for identification in kind in the real world, this system is artificial using FusionNet's under environment
Intelligence learning technology completes this demand.FusionNet is the mixing of three kinds of neural networks, they are V-CNN I, V-CNN respectively
II and MV-CNN, MV-CNN neural network are to be constructed based on AlexNet structure, and pass through ImageNet data set pre-training
It crosses, these three networks are merged in scoring layer, and the classification finally predicted is found in the linear combination by calculating marking.V-
CNN I and V-CNN II has used the CAD model of voxelization, and MV-CNN then uses 2D projection as input.This system uses
Basis of the standard pre-training neural network model (AlexNet) as 2D network MV-CNN, to the network of three-dimension object 2D projection
It carries out warm starting pre-training and is based on extensive 2D pixel picture data set ImageNet.It is influenced by pre-training, many is schemed for 2D
As the feature of classification does not need to have trained from the beginning.
The outdoor scene picture for threedimensional model and the shooting module shooting that AR generation module is used to be established according to modeling module generates
The AR image of pipe network；In the generating process of AR image, locating module also uses magnetic force other than being positioned with GNSS and SLAM
Meter carries out space and moves towards sensing, is sensed with accelerometer to space plane, is sensed, made to rotary viewing angle with gyroscope
Modeling module establish pipe network in three-dimensional model can accurately be projected in real space, realize Virtual Space data with really
The mapping one by one of spatial data.
The AR image for the pipe network that display module is used to establish AR generation module is shown.
Staff can be very intuitively to present co-ordinate position by the AR image that display module on user terminal is shown
Pipe network checked.
User terminal can be to hold plate or wearable device, and in the present embodiment, user terminal is hand-held plate.It is hand-held flat
The chip of the user terminal of plate is kylin 970, and the chip functions are powerful and performance is stablized, and is able to carry out rapid modeling and generates AR
Projected image；Positioning chip is the BU12G8 model of century-old star brand, model GLONASS+GPS+ Beidou it is three-in-one fixed
Position chip, is able to carry out accurate positionin；Staff can be very intuitive by the AR image that display module on user terminal is shown
The pipe network of present co-ordinate position is checked；Camera is Sony IMX 586, which is 48,000,000 pixels, imaging
Quality is outstanding；Magnetic force is calculated as the MAG3110FCR1 model of Freescale brand；Accelerometer is the MPU6050 of all brands of electricity；
Gyroscope is the ICS-40300 model of invensense brand；Display screen is the TA062VGHX01 model of heavenly steed brand.
It, can be accurately to working as by the AR image of the pipe network of present co-ordinate position when needing to overhaul pipe network
It is excavated on the road surface of preceding coordinate position.
The present invention can also store the threedimensional model of pipe network on the server, before maintenance, by the pipe network three of corresponding region
Dimension module server downloads to user terminal, after having overhauled a region, the pipe network in three-dimensional model in the region is deleted, Zhi Houzai
The threedimensional model of next service area is downloaded, the maintenance in a region is carried out.The only memory space of such user terminal
It is required that it is larger, and the pipe network in three-dimensional model for downloading some region but can only be used once in a short time, also seem very time-consuming laborious；If pipe
The time spent in leakage accident occurs for net, needs to overhaul as early as possible, and the prior art downloads pipe network in three-dimensional model before maintenance, may make
The seriousness of leakage accident aggravates.
It is to carry out pipe network in three-dimensional modeling with the mode of Real-time modeling set, it is only necessary to the coordinate of current location is collected, it can root
Real-time modeling set is carried out according to the attribute data of the pipe network of changing coordinates, is carrying out AR generation and display, it is empty to the storage of user terminal
Between require it is smaller；And the mode of pipe network in three-dimensional model modeling, before maintenance or maintenance, staff's it goes without doing what beam worker
Make, only user terminal need to be taken and take with oneself, system can carry out automatically current location generate corresponding pipe network in three-dimensional model and and
The outdoor scene picture of user terminal acquisition generates AR picture, emergency is occurring, when needing to overhaul as early as possible, staff can be fast
Speed obtains the pipe network AR picture of the position, and then can carry out at the first time excavation and service work.Expense when avoiding maintenance expense
Power, and the case where the seriousness of leakage accident may be aggravated.
The present invention also provides a kind of methods for generating three-dimensional visualization image according to pipe network attribute data, comprising:
The attribute data of pipe network is stored in Cloud Server by storing step, and the data of pipe network include the coordinate of pipe network, pipe
Pipe network diameter, pipe network model and the pipe network depth of net；
Positioning step obtains the coordinate of user terminal current location；Positioning step, which uses, is based on GPS, GLONASS, Beidou
The compound fixed resolving Algorithm of positioning system, can be by the accuracy controlling of outdoor positioning within 1 centimetre of error；Meanwhile positioning step
Suddenly SLAM and high-precision spatial location technology are also facilitated, influences its precision, auxiliary since GNSS will receive building etc.
It is positioned with SLAM, guarantees the accuracy of the coordinate of acquisition；
Matching step carries out coordinate matching according to the coordinate that positioning step obtains in Cloud Server, matches to be located at and be somebody's turn to do
The pipe network of coordinate；By matching step, the attribute data of the pipe network at present co-ordinate position is found；
Invocation step transfers the attribute data of the matched pipe network of matching step to Cloud Server；
Modeling procedure, according to the attribute data for the pipe network that invocation step is transferred, the pipe network of real-time perfoming present co-ordinate position
Three-dimensional modeling；
Step is shot, the outdoor scene of current location is acquired；
The outdoor scene picture of AR generation step, the threedimensional model established according to modeling procedure and shooting step shooting generates pipe network
AR image；In AR generation step, user terminal in addition to keep GNSS and SLAM high accuracy positioning other than, also with magnetometer into
Sensing is moved towards in row space, is sensed with accelerometer to space plane, is sensed with gyroscope to rotary viewing angle, make to model
The pipe network in three-dimensional model that step is established can accurately be projected in real space, realize Virtual Space data and real space
The mapping one by one of data.
It shows step, the AR image for the pipe network that AR generation module is established is shown.
Staff can intuitively visualize the pipe network of present co-ordinate position very much by the AR image shown
It checks.
Embodiment two
Since pipe network is embedded in underground, after disaster occurs, it cannot find whether the attribute of pipe network changes in time.Especially
When the earth's surface of embedding pipe network changes and pipe network and when being not affected by apparent damage (surrounding do not occur having a power failure, cut off the water), it is difficult
The state current to pipe network judges, if carrying out comprehensive investigation to the radiation areas of disaster, and when can spend very much
Between, it takes time and effort and inefficiency, also, in disaster, when occurring such as landslide, it is also difficult to enough finding at the first time
Staff and equipment disaster radiation areas are carried out with comprehensive inspection.
The coping style of the prior art is, when embedding pipe network, sensor is installed on pipe network, sensor includes pressure sensing
Device, temperature sensor and humidity sensor understand whether pipe network receives damage or deformation occurs by the feedback of sensor,
If pipe network receives damage or deformation has occurred, staff is sent to safeguard, overhaul.
The prior art can in time safeguard the pipe network being damaged or deformation occurs, be overhauled, can to by
The pipe network of damage is more timely overhauled.But this mode can only be safeguarded to the pipe network of significant change is had occurred and that, be examined
It repairs, and for there are the pipe networks of damaged risk cannot then detect in time.
If the crowd is dense, regional pipe network is not overhauled timely there are damaged risk, is safeguarded, once pipe network occurs
Damage, can make the life of a large amount of residents in the region be affected.The prior art, cannot be right when sensing data shows normal
There may be the pipe network regions of risk to patrol.
Based on this, a kind of system that three-dimensional visualization image is generated according to pipe network attribute data is present embodiments provided,
Unlike embodiment one, pipe network is mounted with that sensor, sensor include pressure when embedding in the present embodiment
Sensor, humidity sensor and temperature sensor, in the present embodiment, the PHS-A type of the model KYOWA brand of pressure sensor
Number, the happy DHT11 model for enjoying brand of the model of humidity sensor, temperature degree sensor is the AR25 model of RIJING brand；
Certainly, those skilled in the art can also be specifically chosen the model of sensor according to specific terrain environment.
When pipe network is installed, also it is mounted with that photographic device, photographic device are used for above pipe network on the ground above pipe network
Ground shot；In the present embodiment, photographic device carries out once photo taking to site environment daily, is equipped on photographic device
Gyroscope；In the present embodiment, gyroscope is the WT901 model of Wei Te intelligence brand.
The memory module of server is also used to receive and store pressure sensor, humidity sensor, temperature sensor feedback
Data and camera passback scene photograph and camera correspond to gyroscope return data.
Server further include data obtaining module, population distribution analyze certain block, picture correction module, live contrast module and
Evaluation module；
Data obtaining module is for obtaining disaster information；
Population distribution analysis module, for obtaining population distribution data；In the present embodiment, population distribution analysis module is from working as
Population distribution data are grabbed in ground government；
Picture correction module corresponds to the data of gyroscope passback for the photo site and camera according to acquisition, will scheme
Piece is modified；Due to camera when in use especially disaster occur when, it may occur that inclination, lead to the photo taken not
It is convenient for on-the-spot testing；By the amendment of picture correction module, the angle of photo can be made to be consistent as far as possible；
Live contrast module, for revised photo site to be compared with last revised picture；
Evaluation module, for being commented according to the information of live contrast module and sensor feedback the actual conditions of pipe network
Estimate；
If the sensing data of passback is normal, the photo site of this area of acquisition is also normal, then illustrates the pipe of this area
Net state is normal；The pipe network of this area can be used normally；
If exception occurs in the sensing data of passback, illustrates that the pipe network of sensor region there is a problem, need
It is overhauled；At this point, the pipe network attribute data repaired is sent to user terminal by server, staff according to
The pipe network attribute data that family terminal receives can find the pipe network to go wrong and be overhauled；
If the sensing data of passback is normal, but there are larger differences with picture before for the photo site of the terrestrial reference obtained
It is different, then illustrate that the earth's surface in the region receives damage, such as cracking occurs in ground, building tilts, the pipe network in the region can
There can be impaired potential risk；At this point, the pipe network attribute data of this area is sent to user terminal, staff by server
The pipe network attribute data received according to user terminal is verified and is safeguarded to the pipe network there may be damaged risk, is such as carried out
Consolidation process.
When evaluation module is assessed, preferentially the density of population is assessed greatly and from the closer region in disaster spot,
Analysis；Secondly the region relatively close but less big the density of population from disaster spot is assessed；It is big to the density of population later
But it is assessed from the farther away area in disaster spot；It is finally big to the density of population and apart from the farther away area in disaster spot into
Row assessment.
It compared to the prior art, can not only be when disaster occurs, in time to being damaged using the system in the present embodiment
Bad pipe network is overhauled, can also be to there are the pipe networks of damaged risk to be checked in time, safeguards；Also, this system is right
When pipe network is analyzed, using the density of population as an important parameter, the biggish area of the density of population can be divided in time
Analysis, repairs in time when pipe network is damaged, can be as far as possible in pipe network there are being checked, being safeguarded in time when damaged risk
Influence of the reduction pipe network problem to the resident living of density of population larger area.
What has been described above is only an embodiment of the present invention, and the common sense such as well known specific structure and characteristic are not made herein in scheme
Excessive description, technical field that the present invention belongs to is all before one skilled in the art know the applying date or priority date
Ordinary technical knowledge can know the prior art all in the field, and have using routine experiment hand before the date
The ability of section, one skilled in the art can improve and be implemented in conjunction with self-ability under the enlightenment that the application provides
This programme, some typical known features or known method should not become one skilled in the art and implement the application
Obstacle.It should be pointed out that for those skilled in the art, without departing from the structure of the invention, can also make
Several modifications and improvements out, these also should be considered as protection scope of the present invention, these all will not influence the effect that the present invention is implemented
Fruit and patent practicability.The scope of protection required by this application should be based on the content of the claims, the tool in specification
The records such as body embodiment can be used for explaining the content of claim.
Claims (6)
1. a kind of processing system for generating AR image according to pipe network attribute data, it is characterised in that: whole including server and user
End；
Server includes memory module, for storing the threedimensional model and corresponding coordinate of pipe network；
User terminal includes locating module, calling module, shooting module, AR generation module and display module；
Locating module, for being positioned to current location；Locating module, which uses, is based on GPS, GLONASS, BEI-DOU position system
Compound fixed resolving Algorithm also uses SLAM and high-precision spatial location technology；
Calling module transfers the threedimensional model of the pipe network of current location from memory module；
Shooting module is acquired for the outdoor scene to current location；
AR generation module generates pipe network AR image according to the pipe network in three-dimensional model of current location and outdoor scene picture；
Display module shows pipe network AR image.
2. the processing system according to claim 1 for generating AR image according to pipe network attribute data, it is characterised in that: described
Shooting module completes identification in kind in the real world with the artificial intelligence learning art of FusionNet.
3. the processing system according to claim 1 for generating AR image according to pipe network attribute data, it is characterised in that: in AR
In the generating process of image, locating module also carries out space with magnetometer and moves towards sense other than being positioned with GNSS and SLAM
It surveys, space plane is sensed with accelerometer, rotary viewing angle is sensed with gyroscope.
4. a kind of processing method for generating AR image according to pipe network attribute data, it is characterised in that: including,
Storing step, by the threedimensional model of pipe network and the storage of corresponding coordinate into server；
Positioning step positions current location；Positioning step uses compound based on GPS, GLONASS, BEI-DOU position system
Fixed resolving Algorithm, also uses SLAM and high-precision spatial location technology；
Invocation step transfers the threedimensional model of the pipe network of current location from server；
Step is shot, the outdoor scene of current location is acquired；
AR generation step generates pipe network AR image according to the pipe network in three-dimensional model of current location and outdoor scene picture；
It shows step, pipe network AR image is shown.
5. the processing method according to claim 4 for generating AR image according to pipe network attribute data, it is characterised in that: shooting
In step, identification in kind in the real world is completed with the artificial intelligence learning art of FusionNet.
6. the processing method according to claim 5 for generating AR image according to pipe network attribute data, it is characterised in that: in AR
In generation step, other than being held in position with GNSS and SLAM, space also is carried out with magnetometer and moves towards sensing, with accelerometer pair
Space plane is sensed, and is sensed with gyroscope to rotary viewing angle.
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| CN110888148A (en) * | 2019-12-09 | 2020-03-17 | 浙江浙能嘉华发电有限公司 | Underground pipe network viewing method based on GNSS positioning and APP |
| CN113239445A (en) * | 2021-06-11 | 2021-08-10 | 重庆电子工程职业学院 | AR-based indoor pipeline information display method and system |
| CN113239447A (en) * | 2021-06-11 | 2021-08-10 | 重庆电子工程职业学院 | Indoor pipeline abnormity detection system and method |
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