CN110580385A - data processing method, device and equipment for underground pipeline and computer storage medium - Google Patents
data processing method, device and equipment for underground pipeline and computer storage medium Download PDFInfo
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- CN110580385A CN110580385A CN201910774978.6A CN201910774978A CN110580385A CN 110580385 A CN110580385 A CN 110580385A CN 201910774978 A CN201910774978 A CN 201910774978A CN 110580385 A CN110580385 A CN 110580385A
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- 238000003672 processing method Methods 0.000 title claims abstract description 21
- 238000012545 processing Methods 0.000 claims description 17
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- 238000004590 computer program Methods 0.000 claims description 8
- 238000012986 modification Methods 0.000 claims description 7
- 230000004048 modification Effects 0.000 claims description 7
- 238000013528 artificial neural network Methods 0.000 claims description 5
- 238000012549 training Methods 0.000 claims description 5
- 238000001514 detection method Methods 0.000 claims description 3
- 239000013589 supplement Substances 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 claims description 2
- 238000012800 visualization Methods 0.000 claims description 2
- 238000000034 method Methods 0.000 description 11
- 238000013507 mapping Methods 0.000 description 5
- 239000000463 material Substances 0.000 description 5
- 238000009933 burial Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000001788 irregular Effects 0.000 description 2
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/258—Data format conversion from or to a database
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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
- G06N3/084—Backpropagation, e.g. using gradient descent
Abstract
The invention discloses a data processing method, a device, equipment and a computer storage medium of an underground pipeline, wherein the data processing method comprises the steps of acquiring underground pipeline data; analyzing the acquired underground pipeline data; establishing an underground pipeline model; establishing an underground pipeline model; correcting the underground pipeline model by using the trained relearning model; the relearning model is additionally established after the underground pipeline model is established, the relearning model is trained, the trained relearning model is used for correcting the original underground pipeline model, wrong data can be distinguished after the relearning model is trained for multiple times, and therefore workers are reminded to modify or delete the data automatically, the error rate of the data is greatly reduced, the accuracy is improved, the workers only need to collect or input the data, the data accuracy is not worried, and the working efficiency is greatly improved.
Description
Technical Field
The present invention relates to the field of data processing technologies for underground pipelines, and in particular, to a data processing method, device, and apparatus for an underground pipeline, and a computer storage medium.
Background
The processing of city underground pipeline data is the most important part among the city underground pipeline management, the speed efficiency and the degree of accuracy direct influence of underground pipeline data processing are modelled and are maintained in the later stage, present underground pipeline data processing all needs the manual work to type in data earlier stage, handling data, model building at last, because the data of city underground pipeline is very huge, and the underground pipeline often can change, just so need carry out the manual work and revise data and model, the efficiency is underground very, and the degree of accuracy is low, cause the mistake easily.
Disclosure of Invention
in order to solve the problems of low efficiency and poor accuracy of the existing underground pipeline data processing, the invention provides an underground pipeline data processing method, device and equipment with high efficiency and high accuracy and a computer storage medium.
in order to achieve the above object, in one aspect, the present invention provides a data processing method for an underground pipeline, including the steps of:
1) Acquiring underground pipeline data, detecting the underground pipeline data through detection equipment, and transmitting the data to a server database;
2) Analyzing the obtained underground pipeline data, classifying, arranging and numbering the obtained underground pipeline data, and finally obtaining an underground pipeline database;
3) Establishing an underground pipeline model, and establishing the underground pipeline model by utilizing an underground pipeline database;
4) Establishing a relearning model, manually modifying the analyzed underground pipeline data, introducing the modified relearning model into the relearning model, and training the relearning model;
5) And correcting the underground pipeline model by using the trained relearning model.
In the above data method, the analyzing of the underground pipeline data in step 2) specifically includes classifying the underground pipeline data and extracting nodes of the pipeline.
in the data method, the step 3) of establishing the underground pipeline model specifically includes establishing a three-dimensional visualized model of data in a database, and displaying corresponding underground pipeline data.
in the above data method, the relearning model is constructed using a BP neural network.
In the data method, the manual modification in the step 4) includes manual de-noising, manual modification of obviously erroneous data, and supplement of non-recorded data.
In another aspect, the present invention is also directed to an underground pipeline data processing apparatus, including:
The acquiring unit is used for acquiring underground pipeline data;
The analysis unit is used for analyzing the acquired underground pipeline data;
The underground pipeline model unit is used for establishing an underground pipeline model by utilizing the analyzed underground pipeline data;
A relearning model unit for creating a relearning model and training the relearning model.
in the device, the underground pipeline model unit comprises a model for establishing three-dimensional visualization on data in the database and displaying corresponding underground pipeline data.
In the above apparatus, the relearning model unit is constructed using a BP neural network.
Further, the present invention also provides a data processing device for an underground pipeline, the device includes a memory, a processor and a computer program stored in the memory and operable on the processor, and the processor implements the steps of the data processing method when executing the computer program.
finally, the invention also provides a computer storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the data processing method described above.
compared with the prior art, the invention has the beneficial effects that: according to the invention, the relearning model is additionally established after the underground pipeline model is established, the relearning model is trained, and finally the trained relearning model is used for correcting the original underground pipeline model, and the relearning model can distinguish wrong data after being trained for multiple times, so that a worker is reminded to modify or delete the data automatically, the error rate of the data is greatly reduced, the accuracy is improved, and the worker only needs to acquire or input the data, so that the data accuracy is not worried about, and the working efficiency is greatly improved.
drawings
FIG. 1 is a flow chart of a data processing method in the present invention;
FIG. 2 is a flow chart of establishing an underground utility model;
FIG. 3 is a block diagram of a data processing apparatus according to the present invention;
Fig. 4 is a block diagram of a data processing apparatus in the present invention.
Detailed Description
The following further describes embodiments of the present invention with reference to the drawings. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1, the present invention provides a data processing method for an underground pipeline, comprising the following steps:
S10: acquiring underground pipeline data, detecting the underground pipeline data through detection equipment, and transmitting the data to a server database;
s20: analyzing the obtained underground pipeline data, classifying, arranging and numbering the obtained underground pipeline data, and finally obtaining an underground pipeline database; specifically, the pipeline is generally divided into two categories, namely a pipe body and a pipe point, wherein the pipe body comprises a square pipe and a round pipe, the pipe point comprises irregular equipment such as a valve, a bolt, a joint and the like, more specifically, the purposes of the pipeline can be classified, such as a drinking water pipe, a rain and sewage combined flow pipe, a gas pipe, a power supply pipe, a traffic signal pipe, a communication pipe, a monitoring signal pipe and the like, and the data of the pipeline are numbered, so that the subsequent modeling is facilitated; in addition, statistics needs to be performed on attribute data of the pipeline, for example, information such as pipe diameter, service life and material of the pipeline can be displayed through a human-computer interaction interface after modeling.
s30: establishing an underground pipeline model, and establishing the underground pipeline model by utilizing an underground pipeline database; modeling can be performed through various modes and software, in the embodiment, Skyline software is used for modeling the underground pipeline, and Skyline software self objects, namely Cylinder and Box objects, are used for creating the representation pipe body, so that system resources required by the software for rendering external model display can be greatly reduced.
specifically, the step S30 includes the following steps, as shown in fig. 2:
S301: for the tube point data, which are special and irregular entities such as valves, bolts, joints and the like, firstly classifying each type of tube point data, respectively adopting a modeling tool (such as SketchUp) for each type of object, carrying out three-dimensional model modeling simulation according to the actual photo or design drawing of the tube point in a ratio of 1:1, and then endowing the tube point data with textures acquired according to the actual.
S302: creating a pipeline point data base according to numbered pipeline point data, and importing the pipeline point data into the database, wherein the data format of the pipeline point data comprises but is not limited to gdb, mdb, shpfile, access, excel and other data formats;
S303: extracting necessary fields for constructing the pipeline, wherein the fields included in the pipeline data include, but are not limited to, the pipe diameter, the pipe material, the pipeline carrier and the application, the number, the voltage, the cross-sectional size, the length, the burial depth, the position information and the like of the pipeline, the fields included in the pipeline data include, but are not limited to, the position coordinate information, the burial depth, the pipe diameter, the pipe material and the like of the pipe point, and then establishing a mapping relation from the fields, for example, when the type field of the pipeline indicates that the pipeline is a round pipe, according to the field value corresponding to the necessary field of the pipe diameter, the field value corresponding to the necessary field of the color, the field value corresponding to the necessary field of the material, and the field value corresponding to the necessary field of the node coordinate, the mapping relation is mapped to the pipeline element in the rule model base for the three-dimensional environment, so that, when modeling is performed subsequently, therefore, the three-dimensional pipeline element is generated by taking the node coordinate as a central line, the pipe diameter as a radius and the color and the material as attributes.
S304: and establishing a three-dimensional underground pipeline model according to the mapping relation.
and after the three-dimensional underground pipeline model is established, the following steps are continued.
S40: and establishing a relearning model, and constructing the relearning model capable of performing deep learning by using the BP neural network. The BP network can learn and store a large number of input-output pattern mappings without prior disclosure of mathematical equations describing such mappings. The learning rule is that the steepest descent method is used, and the weight and the threshold value of the network are continuously adjusted through back propagation, so that the error square sum of the network is minimum. The BP neural network model topology structure comprises an input layer (input), a hidden layer (hidden layer) and an output layer (output layer).
After a relearning model is established, the analyzed underground pipeline data are manually modified and then led into the relearning model, and the relearning model is trained; it should be explained here that, as modeling is a long-time process, not just kicking, especially for modeling of urban underground pipelines, the data volume is very huge, errors are easy to occur in the acquisition or recording process, the error rate is reduced as much as possible around the role of the relearning model, the specific operation mode is that a large amount of data is imported into the relearning model in the early stage and the data is modified manually, the manual modification includes but is not limited to manual de-noising, manual modification of obvious error data, supplement of unrecorded data and the like, the relearning model can distinguish the wrong data after being trained for many times, so that the worker is reminded to modify or delete the data, the error rate of the data is greatly reduced, the accuracy is improved, and the worker only needs to acquire or record the data, the data accuracy is not worried, and the working efficiency is greatly improved.
S50: and finally, correcting the original underground pipeline model by using the trained relearning model, thereby ensuring the accuracy of the underground pipeline model.
As shown in fig. 3, the present invention further provides a data processing apparatus for an underground pipeline, which corresponds to the data processing method for an underground pipeline in the foregoing embodiment, and the data processing apparatus 10 further includes several units, which are used for implementing corresponding functions corresponding to corresponding steps of the data processing method. Since the steps of the data processing method have been described in detail in the above embodiments, they are not described in detail in this apparatus.
The device acquires underground pipeline data through an acquisition unit 11; analyzing the obtained underground pipeline data through an analyzing unit 12; an underground pipeline model is established through an underground pipeline model unit 13; in addition, a relearning model and training of the relearning model are created by the relearning model unit 14.
As shown in fig. 4, the embodiment of the present invention further provides a data processing device 20 for an underground pipeline, which includes a memory 21, a processor 22 and a computer program 23 stored in the memory and running on the processor, and when the computer program is executed by the processor, the steps of the fan control method are implemented.
in addition, an embodiment of the present invention further provides a computer storage medium, where the computer storage medium may store a program, and the program includes, when executed, some or all of the steps of any one of the fan control methods described in the above method embodiments.
in addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
the integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. It will be apparent to those skilled in the art that various changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, and the scope of protection is still within the scope of the invention.
Claims (10)
1. A data processing method of an underground pipeline is characterized by comprising the following steps:
1) Acquiring underground pipeline data, detecting the underground pipeline data through detection equipment, and transmitting the data to a server database;
2) analyzing the obtained underground pipeline data, classifying, arranging and numbering the obtained underground pipeline data, and finally obtaining an underground pipeline database;
3) establishing an underground pipeline model, and establishing the underground pipeline model by utilizing an underground pipeline database;
4) Establishing a relearning model, manually modifying the analyzed underground pipeline data, introducing the modified relearning model into the relearning model, and training the relearning model;
5) And correcting the underground pipeline model by using the trained relearning model.
2. The data processing method of claim 1, wherein: the analyzing of the underground pipeline data in the step 2) specifically comprises classifying the underground pipeline data and extracting nodes of the pipeline.
3. The data processing method of claim 1, wherein: the step 3) of establishing the underground pipeline model specifically comprises the steps of establishing a three-dimensional visualized model for data in the database and displaying corresponding underground pipeline data.
4. the data processing method of claim 1, wherein: the relearning model is constructed by using a BP neural network.
5. The data processing method of claim 4, wherein: the manual modification in the step 4) comprises manual denoising, manual modification of obviously wrong data and supplement of data which is not recorded.
6. A data processing apparatus for an underground utility, comprising:
the acquiring unit is used for acquiring underground pipeline data;
the analysis unit is used for analyzing the acquired underground pipeline data;
the underground pipeline model unit is used for establishing an underground pipeline model by utilizing the analyzed underground pipeline data;
A relearning model unit for creating a relearning model and training the relearning model.
7. the data processing apparatus of claim 6, wherein: the underground pipeline model unit comprises a model for establishing three-dimensional visualization on data in the database and displaying corresponding underground pipeline data.
8. The data processing apparatus of claim 6, wherein: the relearning model unit is constructed by utilizing a BP neural network.
9. Data processing device of an underground pipeline, the device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the steps of a data processing method according to any one of claims 1 to 5.
10. A computer storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of a data processing method according to any one of claims 1 to 5.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112231874A (en) * | 2020-10-19 | 2021-01-15 | 中铁建华南建设有限公司 | Method and device for establishing underground pipeline model, computer equipment and storage medium |
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