CN117093954A - Fault diagnosis system with efficient management - Google Patents
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Abstract
The invention discloses a fault diagnosis system with high-efficiency management, which comprises the following operation methods: selecting and processing the power transmission operation data stream through a sliding window; grid clustering management is carried out on the power transmission operation data stream; performing data analysis control processing of fault diagnosis; and transmitting data information and carrying out manual review processing. The selecting and processing the power transmission operation data stream through the sliding window comprises the following steps: the data is selected from the data stream to be processed by setting a fixed window, and the data which continuously flows through the window along with the time change is controlled to only process the data in the current window at a time. The grid cluster management of the power transmission operation data stream comprises the following steps: after window data Stream selection is completed, grid initial micro-cluster division is carried out on the data Stream through a D-Stream algorithm. The invention has the characteristics of accurate analysis management and high processing efficiency.
Description
Technical Field
The invention relates to the technical field of fault diagnosis, in particular to a fault diagnosis system with efficient management.
Background
The bus bar is one of the most important components in the power system, and is connected to various devices such as a generator, a transmission line, and a load. Traditionally, bus bars are used for power distribution in switchgear, control equipment assemblies, and buildings. In a power transmission and distribution system, bus power transmission is gradually replaced by electric wires and cables, so that the power transmission and distribution system becomes a preferred power distribution mode of a high-rise building and a factory building. Compared with the traditional power distribution mode, the bus has the advantages of small installation and construction difficulty, safety, attractive appearance, convenience in disassembly and assembly, long service life and the like, and particularly shows the superiority of the bus power distribution mode under the high-current power transmission and distribution scene. However, as the demand for electric power in production and life increases year by year, the pressure born by the power transmission and distribution system is also increased, the tightening torque is too low due to loosening and non-tightening in the power transmission operation or the contact surface oxidation is aggravated due to work in a long-term high-temperature environment, so that the abnormal increase of contact resistance is brought, the temperature rise of the bus connector is increased, the occurrence of power transmission faults is further caused, and accidents are difficult to be stopped by regular replacement and maintenance. Therefore, a fault diagnosis system with accurate design analysis management and high processing efficiency is needed.
Disclosure of Invention
The present invention is directed to a fault diagnosis system with efficient management, so as to solve the problems set forth in the background art.
In order to solve the technical problems, the invention provides the following technical scheme: a fault diagnosis system with high-efficiency management comprises: comprising the following steps:
selecting and processing the power transmission operation data stream through a sliding window;
grid clustering management is carried out on the power transmission operation data stream;
performing data analysis control processing of fault diagnosis;
and transmitting data information and carrying out manual review processing.
According to the above technical solution, the selecting the power transmission operation data stream through the sliding window includes:
the data is selected from the data stream to be processed by setting a fixed window, and the data which continuously flows through the window along with the time change is controlled to only process the data in the current window at a time.
According to the above technical solution, the grid cluster management of the power transmission operation data stream includes:
after window data Stream selection is completed, grid initial micro-clustering division is carried out on the data Stream through a D-Stream algorithm, received power transmission operation data are mapped into grids, initial micro-clustering is completed based on real-time grid density data, initial grid clusters are formed, and existing grid clusters are trimmed along with continuous data reception;
after the initial clustering of the micro clusters is completed, the corresponding data are temporarily stored in a buffer area, after the next time interval t arrives and the clustering is completed again, whether the data in the buffer area are distributed in the new micro clusters is detected, if the data are distributed in the new micro clusters, the data are moved out of the buffer area, otherwise, the data are removed from the clustering result, only the data are reserved in the buffer area, and after a set period, the data are filtered.
According to the above technical solution, the data analysis control process for performing fault diagnosis includes:
each bus joint is monitored on line through a wireless sensor network, so that real-time diagnosis of faults of the bus joints is realized;
after the power transmission operation data stream is clustered by the data stream, further carrying out manual detection and filtering noise data in the power transmission operation data stream;
after the data of the denoising process is obtained, four parameters are used for connecting according to the bus: bus current, joint surface temperature, contact resistance and environmental temperature data information, and a diagnostic analysis model is established by using a regression algorithm of the LSSVM.
According to the above technical scheme, the transmission of the data information and the manual review process include:
after receiving the data information output by the diagnosis and analysis model, performing tracing and tracking processing on the data information, determining a bus branch of a data source, and transmitting the bus branch to a staff for review and audit;
and immediately carrying out early warning notification to maintenance personnel after receiving the result information of the setting pass.
According to the technical scheme, the fault diagnosis system with high efficiency management comprises:
the management optimization module is used for performing management optimization processing on the data information flow;
the analysis diagnosis module is used for carrying out analysis diagnosis management on bus operation;
and the transmission early warning module is used for carrying out transmission early warning notification of the data information.
According to the above technical solution, the management optimization module includes:
the window management module is used for selecting and processing window data streams;
the data flow clustering module is used for carrying out clustering analysis management on the data flow;
and the optimization processing module is used for analyzing and optimizing the clustering processing.
According to the above technical solution, the analysis and diagnosis module includes:
the networking transmission module is used for managing and controlling networking transmission;
the denoising processing module is used for removing noise of the data information;
and the model construction module is used for constructing an analytical diagnosis model.
According to the above technical scheme, the transmission early warning module includes:
the transmission tracing module is used for carrying out transmission tracing processing of the data information;
and the early warning notification module is used for carrying out early warning notification management of information.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, the management optimization module, the analysis diagnosis module and the transmission early warning module are arranged, so that the occurrence of operation faults caused by overlarge load of subsequent analysis processing due to selection processing of a large number of data streams is effectively avoided, the processing delay caused by increasing the data quantity is avoided, the pressure of data storage is effectively relieved, and the timeliness and the accuracy of clustering results are ensured.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a fault diagnosis method for efficient management according to a first embodiment of the present invention;
fig. 2 is a block diagram of a fault diagnosis system with efficient management according to a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one: fig. 1 is a flowchart of a fault diagnosis method with high efficiency management according to an embodiment of the present invention, where the method may be implemented by a fault diagnosis system with high efficiency management according to an embodiment of the present invention, and the system is composed of a plurality of software and hardware modules, as shown in fig. 1, and the method specifically includes the following steps:
s101, selecting and processing power transmission operation data streams through a sliding window;
in the embodiment of the invention, the data is selected from the data stream to be processed by setting a fixed window, and the data flowing through the window continuously along with time is controlled to only process the data in the current window each time; in the step, the fixed window size L is set, and the window is pushed forward along with the power transmission operation data flow along with time, after the time reaches the time T, the control window only selects the data in the processing (T-L, T) time period, compared with a large number of continuously arrived data flows, the data is processed by utilizing the sliding window model through the processing, the selection processing of the data flow can be completed only with small memory consumption, so that the subsequent data analysis processing is more convenient and accurate, and the situation that the load of the subsequent analysis processing is overlarge and the operation fault is caused due to the selection processing of a large number of data flows is effectively avoided.
S102, grid clustering management is carried out on the power transmission operation data stream;
in an exemplary embodiment of the present invention, after window data Stream selection is completed, grid initial micro-cluster division is performed on the data Stream by using a D-Stream algorithm, received power transmission operation data is mapped into grids, then initial micro-clusters are completed based on real-time grid density data, initial grid clusters are formed, and existing grid clusters are trimmed along with continuous data reception; in the step, clustering is carried out on the data Stream by using a density grid through a D-Stream algorithm, specifically, the grid is subjected to micro clustering through a specified time interval along with the continuous arrival of the data Stream which is selected in real time, a clustering result is formed, the last clustering result is used as the center of the class of the next clustering to start new data integration processing, all data are mapped to the corresponding grids, after the feature vectors of all grids are updated, if the grid density of the grids is larger than a set threshold value and neighbor grids exist, the two grids are combined into one grid cluster, otherwise, the grid is independently used as a new grid cluster, the next grid cluster is continuously divided until the attribute of all grids is not changed, and the processing delay caused by the increase of the data quantity can be avoided through the processing, so that the pressure of data storage is effectively relieved.
After the initial clustering of the micro clusters is completed, corresponding data are temporarily stored in a buffer area, after the next time interval t arrives and the clustering is completed again, whether the data in the buffer area are distributed in a new micro cluster or not is detected, if the data are distributed in the new micro cluster, the data are moved out of the buffer area, otherwise, the data are removed from the clustering result and only remain in the buffer area, the data are filtered after a set period, and the timeliness and the accuracy of the clustering result can be effectively ensured through the processing.
S103, performing data analysis control processing of fault diagnosis;
in the embodiment of the invention, each bus joint is monitored on line through a wireless sensor network, so that real-time diagnosis of faults of the bus joints is realized; because the LoRa adopts a linear modulation spread spectrum mode, the receiving sensitivity can be obviously improved, the communication distance farther than other modulation modes is realized, and the anti-interference capability is stronger, so that through the step, the sensor network is networked and data are transmitted through the LoRa communication protocol, the data communication functions including the sending and receiving of temperature acquisition signals, the transmission of temperature data and the like are realized, the transmission of data information is more efficient and stable, and the transmission power consumption is effectively reduced.
After the power transmission operation data stream is clustered by the data stream, further carrying out manual detection and filtering noise data in the power transmission operation data stream; when the bus works normally, the actually collected data can contain various abnormal fluctuation or random errors due to environmental factors, data transmission errors and the like, noise data can be inevitably generated, and the existence of the noise data can greatly influence analysis and diagnosis of faults, so that the data flow is subjected to data flow clustering processing in the step, the noise data is kept in a buffer area to be filtered, and the filtered data flow is further subjected to manual review processing and then is waited for subsequent processing.
After the data of the denoising process is obtained, four parameters are used for connecting according to the bus: bus current, joint surface temperature, contact resistance and environmental temperature data information, and establishing a diagnosis analysis model by using a regression algorithm of the LSSVM; in the step, the data after denoising is input into a diagnosis analysis model, the result data is compared with a set threshold range after being analyzed and processed by an LSSVM regression algorithm according to the set bus joint four parameter data, when the result data exceeds the range, the bus operation is indicated to be faulty, the result data is output, and otherwise, the result data is not output.
S104, transmitting data information and performing manual review processing;
exemplary, in the embodiment of the invention, after receiving the data information output by the diagnosis and analysis model, tracing the data information, determining a bus branch of a data source, and transmitting the bus branch to a staff for review and audit;
and immediately carrying out early warning notification to maintenance personnel after receiving the result information of the setting pass.
Embodiment two: the second embodiment of the present invention provides a fault diagnosis system with high efficiency management, and fig. 2 is a schematic diagram of module configuration of the fault diagnosis system with high efficiency management provided in the second embodiment, as shown in fig. 2, where the system includes:
the management optimization module is used for performing management optimization processing on the data information flow;
the analysis diagnosis module is used for carrying out analysis diagnosis management on bus operation;
and the transmission early warning module is used for carrying out transmission early warning notification of the data information.
In some embodiments of the invention, the management optimization module comprises:
the window management module is used for selecting and processing window data streams;
the data flow clustering module is used for carrying out clustering analysis management on the data flow;
and the optimization processing module is used for analyzing and optimizing the clustering processing.
In some embodiments of the invention, the analytical diagnostic module includes:
the networking transmission module is used for managing and controlling networking transmission;
the denoising processing module is used for removing noise of the data information;
and the model construction module is used for constructing an analytical diagnosis model.
In some embodiments of the present invention, the transmission early warning module includes:
the transmission tracing module is used for carrying out transmission tracing processing of the data information;
and the early warning notification module is used for carrying out early warning notification management of information.
It is noted that relational terms such as first and second, and the like are 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. Moreover, 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.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. A fault diagnosis method for efficient management is characterized in that: comprising the following steps:
selecting and processing the power transmission operation data stream through a sliding window;
grid clustering management is carried out on the power transmission operation data stream;
performing data analysis control processing of fault diagnosis;
and transmitting data information and carrying out manual review processing.
2. The efficiently managed fault diagnosis method of claim 1, wherein: the selecting and processing the power transmission operation data stream through the sliding window comprises the following steps:
the data is selected from the data stream to be processed by setting a fixed window, and the data which continuously flows through the window along with the time change is controlled to only process the data in the current window at a time.
3. The efficiently managed fault diagnosis method of claim 1, wherein: the grid cluster management of the power transmission operation data stream comprises the following steps:
after window data Stream selection is completed, grid initial micro-clustering division is carried out on the data Stream through a D-Stream algorithm, received power transmission operation data are mapped into grids, initial micro-clustering is completed based on real-time grid density data, initial grid clusters are formed, and existing grid clusters are trimmed along with continuous data reception;
after the initial clustering of the micro clusters is completed, the corresponding data are temporarily stored in a buffer area, after the next time interval t arrives and the clustering is completed again, whether the data in the buffer area are distributed in the new micro clusters is detected, if the data are distributed in the new micro clusters, the data are moved out of the buffer area, otherwise, the data are removed from the clustering result, only the data are reserved in the buffer area, and after a set period, the data are filtered.
4. The efficiently managed fault diagnosis method of claim 1, wherein: the data analysis control process for performing the fault diagnosis includes:
each bus joint is monitored on line through a wireless sensor network, so that real-time diagnosis of faults of the bus joints is realized;
after the power transmission operation data stream is clustered by the data stream, further carrying out manual detection and filtering noise data in the power transmission operation data stream;
after the data of the denoising process is obtained, four parameters are used for connecting according to the bus: bus current, joint surface temperature, contact resistance and environmental temperature data information, and a diagnostic analysis model is established by using a regression algorithm of the LSSVM.
5. The efficiently managed fault diagnosis method of claim 1, wherein: the transmission and manual review processing of the data information comprise the following steps:
after receiving the data information output by the diagnosis and analysis model, performing tracing and tracking processing on the data information, determining a bus branch of a data source, and transmitting the bus branch to a staff for review and audit;
and immediately carrying out early warning notification to maintenance personnel after receiving the result information of the setting pass.
6. A highly efficient managed fault diagnosis system characterized by: comprising the following steps:
the management optimization module is used for performing management optimization processing on the data information flow;
the analysis diagnosis module is used for carrying out analysis diagnosis management on bus operation;
and the transmission early warning module is used for carrying out transmission early warning notification of the data information.
7. The efficiently managed fault diagnostic system of claim 6 wherein: the management optimization module comprises:
the window management module is used for selecting and processing window data streams;
the data flow clustering module is used for carrying out clustering analysis management on the data flow;
and the optimization processing module is used for analyzing and optimizing the clustering processing.
8. The efficiently managed fault diagnostic system of claim 6 wherein: the analytical diagnostic module includes:
the networking transmission module is used for managing and controlling networking transmission;
the denoising processing module is used for removing noise of the data information;
and the model construction module is used for constructing an analytical diagnosis model.
9. The efficiently managed fault diagnostic system of claim 6 wherein: the transmission early warning module comprises:
the transmission tracing module is used for carrying out transmission tracing processing of the data information;
and the early warning notification module is used for carrying out early warning notification management of information.
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