CN114154585A - Big data analysis system for operation of converter valve of converter station - Google Patents
Big data analysis system for operation of converter valve of converter station Download PDFInfo
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Abstract
The invention discloses a big data analysis system for operation of a converter valve of a converter station, which comprises a central processing module, wherein the central processing module is respectively and electrically connected with a working parameter acquisition unit and a parameter queuing analysis unit in a bidirectional mode, the central processing module is respectively and electrically connected with a characteristic vector construction unit and a parameter analysis processing unit in the bidirectional mode, and the central processing module is respectively and electrically connected with an acquisition parameter integration unit and a characteristic value identification degree analysis module in the bidirectional mode. The converter station converter valve operation big data analysis system can realize real-time monitoring on the blockage condition and the stress condition of the converter valve to ensure normal and safe operation of the converter valve, well achieve the purpose of quickly and accurately monitoring the converter valve in real time, well perfect working condition monitoring operation of the converter valve, greatly improve the safety of the converter station and further ensure normal and safe operation of the whole converter station.
Description
Technical Field
The invention relates to the technical field of water conservancy data analysis, in particular to a big data analysis system for operation of a converter valve of a converter station.
Background
The hydraulic engineering refers to various engineering (including new construction, extension, reconstruction, reinforcement, restoration, dismantling and other projects) such as flood control, waterlogging drainage, irrigation, hydroelectric generation, water diversion (supply), mud flat treatment, water conservation, water resource protection and the like, and matching and auxiliary engineering thereof, the hydraulic engineering is generated by mainly eliminating water damage, and has the main characteristics that:
1. large scale and complicated engineering. The hydraulic engineering is generally large in scale, complex in engineering and long in construction period. The work involves the accumulation and implementation of natural knowledge such as astronomy and geography, and professional knowledge such as thrust and seepage of various kinds of water and humanistic and traditional knowledge of various regions. The construction time of hydraulic engineering is very long, preparation and planning need several years or even longer, and the consumption of manpower and material resources is also big. Such as the Danjiang estuary hydro-hub project.
2. The comprehensive performance is strong, and the influence is large. The construction of hydraulic engineering can bring many benefits for the resident, eliminates natural disasters. However, the development causes the migration of human and animals, has certain ecological damage, and is organically combined with other water conservancy projects, thereby conforming to the policy of national economy. In order to reduce the loss and the influence area, each expert and staff are required to carefully and conscientiously massage, and from the global viewpoint, the overall consideration is given to the optimal combination of economic and social environments.
The converter valve of the converter station in hydraulic engineering is core equipment and used for controlling the flow speed and the flow direction of water flow, however, the working condition monitoring of the existing converter valve is not perfect enough, the blockage condition and the stress condition of the converter valve cannot be monitored in real time, the normal and safe work of the converter valve is ensured, the purpose of quickly and accurately monitoring the converter valve in real time cannot be achieved, the safety of the converter station is greatly reduced, and the normal and safe work of the whole converter station cannot be ensured.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a converter station converter valve operation big data analysis system, which solves the problems that the working condition monitoring of the existing converter valve is not perfect, the real-time monitoring on the blockage condition and the stress condition of the converter valve cannot be realized, the normal and safe operation of the converter valve is ensured, the purpose of quickly and accurately monitoring the converter valve in real time cannot be achieved, the safety of the converter station is greatly reduced, and the normal and safe operation of the whole converter station cannot be ensured.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme: the big data analysis system for the operation of the converter valve of the converter station comprises a central processing module, wherein the central processing module is respectively in bidirectional electric connection with a working parameter acquisition unit and a parameter queuing analysis unit, and is respectively in bidirectional electric connection with a characteristic vector construction unit and a parameter analysis processing unit, the central processing module is respectively in bidirectional electric connection with an acquisition parameter integration unit and a characteristic value identification degree analysis module, and is respectively in bidirectional electric connection with an adaptive data analysis module and a user interaction terminal.
Preferably, the working parameter acquisition unit is composed of n acquisition modules, and the parameter queuing analysis unit is composed of n arrangement modules.
Preferably, the feature vector construction unit includes a standard parameter feature vector construction module and a maximum difference feature vector construction module.
Preferably, the parameter analysis processing unit includes an input single-team parameter vector matrix generation module, a parameter comparison module, an output analysis data vector matrix generation module, and a CNN convolutional neural network extraction module, and an output end of the input single-team parameter vector matrix generation module is electrically connected with an input end of the parameter comparison module.
Preferably, the output end of the parameter comparison module is electrically connected with the input end of the output analysis data vector matrix generation module, and the output end of the output analysis data vector matrix generation module is electrically connected with the input end of the CNN convolutional neural network extraction module.
Preferably, the acquisition parameter integration unit comprises a valve body water flow flux parameter conversion module, a valve body section stress parameter conversion module and a parameter integration module.
Preferably, the output end of the valve body water flow flux parameter conversion module is electrically connected with the input end of the valve body section stress parameter conversion module, and the output end of the valve body section stress parameter conversion module is electrically connected with the input end of the parameter integration module.
Preferably, the output end of the parameter queuing analysis unit is electrically connected with the input end of the parameter analysis processing unit, and the output end of the parameter analysis processing unit is electrically connected with the input end of the user interaction terminal.
(III) advantageous effects
The invention provides a big data analysis system for operation of a converter valve of a converter station. Compared with the prior art, the method has the following beneficial effects: the converter station converter valve operation big data analysis system comprises a central processing module, wherein the central processing module is respectively in bidirectional electric connection with a working parameter acquisition unit and a parameter queuing analysis unit, the central processing module is respectively in bidirectional electric connection with a characteristic vector construction unit and a parameter analysis processing unit, the central processing module is respectively in bidirectional electric connection with a acquisition parameter integration unit and a characteristic value identification analysis module, the central processing module is respectively in bidirectional electric connection with a self-adaptive data analysis module and a user interaction terminal, the real-time monitoring on the blockage condition and the stress condition of the converter valve can be realized, the normal and safe operation of the converter valve is ensured, the purpose of quickly and accurately monitoring the converter valve in real time is well achieved, the working condition monitoring operation of the converter valve is well perfected, and the safety of the converter station is greatly improved, thereby ensuring a normal and safe operation of the entire converter station.
Drawings
FIG. 1 is a schematic block diagram of the architecture of the system of the present invention;
FIG. 2 is a schematic block diagram of the structure of a parameter analyzing and processing unit according to the present invention;
fig. 3 is a schematic block diagram of the structure of the acquisition parameter integration unit according to the present invention.
In the figure, 1 a central processing module, 2 a working parameter acquisition unit, 3 a parameter queue analysis unit, 4 an eigenvector construction unit, 41 a standard parameter eigenvector construction module, 42 a maximum difference finding eigenvector construction module, 5 a parameter analysis processing unit, 51 an input single queue parameter vector matrix generation module, 52 a parameter comparison module, 53 an output analysis data vector matrix generation module, 54CNN convolutional neural network extraction module, 6 an acquisition parameter integration unit, 61 a valve body water flow parameter conversion module, 62 a valve body section stress parameter conversion module, 63 a parameter integration module, 7 an eigenvalue identification analysis module, 8 an adaptive data analysis module, 9 a user interaction terminal, 10 an acquisition module, 11 an arrangement module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-3, an embodiment of the present invention provides a technical solution: the utility model provides a big data analysis system of converter station converter valve operation, including central processing module 1, central processing module 1 realizes two-way electric connection with working parameter acquisition unit 2 and parameter queue analysis unit 3 respectively, and central processing module 1 realizes two-way electric connection with eigenvector construction unit 4 and parameter analysis processing unit 5 respectively, central processing module 1 realizes two-way electric connection with collection parameter integration unit 6 and eigenvalue recognition degree analysis module 7 respectively, and central processing module 1 realizes two-way electric connection with self-adaptation data analysis module 8 and user interaction terminal 9 respectively, the output of parameter queue analysis unit 3 and the input electric connection of parameter analysis processing unit 5, and the output of parameter analysis processing unit 5 and the input electric connection of user interaction terminal 9.
In the embodiment of the invention, the working parameter acquisition unit 2 is composed of n acquisition modules 10, and the parameter queuing analysis unit 3 is composed of n arrangement modules 11.
In the embodiment of the present invention, the feature vector constructing unit 4 includes a standard parameter feature vector constructing module 41 and a maximum difference feature vector constructing module 42.
In the embodiment of the present invention, the parameter analysis processing unit 5 includes an input single team parameter vector matrix generating module 51, a parameter comparing module 52, an output analysis data vector matrix generating module 53, and a CNN convolutional neural network extracting module 54, an output end of the input single team parameter vector matrix generating module 51 is electrically connected to an input end of the parameter comparing module 52, an output end of the parameter comparing module 52 is electrically connected to an input end of the output analysis data vector matrix generating module 53, and an output end of the output analysis data vector matrix generating module 53 is electrically connected to an input end of the CNN convolutional neural network extracting module 54.
In the embodiment of the present invention, the acquisition parameter integration unit 6 includes a valve body water flux parameter conversion module 61, a valve body section stress parameter conversion module 62 and a parameter integration module 63, an output end of the valve body water flux parameter conversion module 61 is electrically connected to an input end of the valve body section stress parameter conversion module 62, and an output end of the valve body section stress parameter conversion module 62 is electrically connected to an input end of the parameter integration module 63.
When the device is used, firstly, the water flow and the section stress of the converter valve are respectively detected in real time through n acquisition modules 10 in a working parameter acquisition unit 2, the acquired data are transmitted into a central processing module 1, the central processing module 1 transmits the acquired data into an acquisition parameter integration unit 6, a valve body water flow parameter conversion module 61 in the acquisition parameter integration unit converts the acquired water flow data, a valve body section stress parameter conversion module 62 converts the acquired section pressure data, the converted parameters are integrated and processed through a parameter integration module 63, the integrated data are transmitted into a parameter queue analysis unit 3 through the central processing module 1, and the acquisition parameters integrated in real time are queued for analysis through n arrangement modules 11 in time sequence.
Before data analysis, a standard parameter characteristic vector, a standard section pressure parameter characteristic vector, a maximum water flow difference parameter characteristic vector and a maximum section pressure difference parameter characteristic vector are respectively constructed by a standard parameter characteristic vector construction module 41 and a maximum difference characteristic vector construction module 42 in a characteristic vector construction unit 4, and the constructed characteristic vectors are transmitted to an adaptive data analysis module 8 to wait for identification and analysis.
The central processing module 1 controls the parameter analyzing and processing unit 5 to process the parameters of the acquisition queue, specifically: an input single-queue parameter vector matrix generating module 51 in the parameter analyzing and processing unit 5 extracts a parameter queue and generates input parameter comparison characteristics through a vector matrix algorithm, a parameter comparison module 52 compares the generated input parameter comparison characteristics with the four constructed characteristic vectors, then an output analysis data vector matrix generating module 53 integrates the compared characteristics to generate output characteristics, then a CNN convolutional neural network extracting module 54 adaptively extracts the output characteristics into the central processing module 1, then the central processing module 1 transmits the output characteristics into the adaptive data analyzing module 8 for data analysis, analyzes and compares the output characteristics again through the characteristic value identification degree analyzing module 7, and finally constructs an analysis result into a parameter chart model which is transmitted to the user interaction terminal 9 to be displayed.
In conclusion, the invention can realize real-time monitoring on the blockage condition and the stress condition of the converter valve to ensure the normal and safe work of the converter valve, well achieve the aim of quickly and accurately monitoring the converter valve in real time, well perfect the working condition monitoring work of the converter valve, and greatly improve the safety of the converter station, thereby ensuring the normal and safe work of the whole converter station.
And those not described in detail in this specification are well within the skill of those in the art.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. The big data analysis system for the operation of the converter valve of the converter station comprises a central processing module (1), and is characterized in that: central processing module (1) realizes two-way electric connection with working parameter acquisition unit (2) and parameter queue analysis unit (3) respectively, and central processing module (1) respectively with eigenvector construction unit (4) and parameter analysis processing unit (5) realization two-way electric connection, central processing module (1) respectively with gather parameter integration unit (6) and eigenvalue recognition degree analysis module (7) realization two-way electric connection, and central processing module (1) respectively with self-adaptation data analysis module (8) and user interaction terminal (9) realization two-way electric connection.
2. The big data analysis system for operation of the converter valves of the converter station according to claim 1, characterized in that: the working parameter acquisition unit (2) is composed of n acquisition modules (10), and the parameter queuing analysis unit (3) is composed of n arrangement modules (11).
3. The big data analysis system for operation of the converter valves of the converter station according to claim 1, characterized in that: the feature vector construction unit (4) comprises a standard parameter feature vector construction module (41) and a maximum difference feature vector construction module (42).
4. The big data analysis system for operation of the converter valves of the converter station according to claim 1, characterized in that: the parameter analysis processing unit (5) comprises an input single-team parameter vector matrix generation module (51), a parameter comparison module (52), an output analysis data vector matrix generation module (53) and a CNN convolutional neural network extraction module (54), and the output end of the input single-team parameter vector matrix generation module (51) is electrically connected with the input end of the parameter comparison module (52).
5. The big data analysis system for operation of the converter valves of the converter station according to claim 4, wherein: the output end of the parameter comparison module (52) is electrically connected with the input end of the output analysis data vector matrix generation module (53), and the output end of the output analysis data vector matrix generation module (53) is electrically connected with the input end of the CNN convolutional neural network extraction module (54).
6. The big data analysis system for operation of the converter valves of the converter station according to claim 1, characterized in that: the acquisition parameter integration unit (6) comprises a valve body water flux parameter conversion module (61), a valve body section stress parameter conversion module (62) and a parameter integration module (63).
7. The big data analysis system for operation of the converter valves of the converter station according to claim 6, wherein: the output end of the valve body water flow flux parameter conversion module (61) is electrically connected with the input end of the valve body section stress parameter conversion module (62), and the output end of the valve body section stress parameter conversion module (62) is electrically connected with the input end of the parameter integration module (63).
8. The big data analysis system for operation of the converter valves of the converter station according to claim 1, characterized in that: the output end of the parameter queuing analysis unit (3) is electrically connected with the input end of the parameter analysis processing unit (5), and the output end of the parameter analysis processing unit (5) is electrically connected with the input end of the user interaction terminal (9).
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