CN112036610A - Intelligent cable early warning platform and early warning method based on big data analysis - Google Patents
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Abstract
The embodiment of the application discloses an intelligent cable early warning platform and an early warning method based on big data analysis. According to the technical scheme, the operation monitoring data corresponding to the intelligent cable are extracted through the intelligent analysis server, the operation monitoring data are input into a preset big data analysis model to carry out operation fault prediction analysis on the intelligent cable, a corresponding prediction analysis result is obtained, the prediction analysis result is sent to the fault early warning server, and early warning prompt of operation faults of the intelligent cable is carried out by the fault early warning server based on the prediction analysis result. By adopting the technical means, the operation fault prediction of the intelligent cable can be realized, and the early warning prompt is carried out according to the prediction result, so that the potential operation fault risk can be avoided well, the economic loss caused by the intelligent cable fault is avoided, and the operation management of the intelligent cable is optimized.
Description
Technical Field
The embodiment of the application relates to the technical field of cable monitoring, in particular to an intelligent cable early warning platform and an early warning method based on big data analysis.
Background
Electrical cables are a common facility for the transportation of electricity or information. At present, in order to better monitor the running state of the cable in real time and realize better operation and maintenance effects on the cable, the operation and maintenance setting of the cable tends to be more and more intelligent. The intelligent cable can realize real-time monitoring on parameters such as voltage, current, local current and the like of the cable through detection setting of relevant operation states, and even can monitor cable faults, so that operation management on the cable can be well realized, and the operation and maintenance effects of the cable are optimized.
However, real-time monitoring of the operating state and fault condition of the intelligent cable is difficult to avoid potential operating faults of the cable, and once faults occur, economic loss caused by the faults is difficult.
Disclosure of Invention
The embodiment of the application provides an intelligent cable early warning platform based on big data analysis, which can early warn potential operation faults of cables and optimize operation management of intelligent cables.
In a first aspect, an embodiment of the present application provides an intelligent cable early warning platform based on big data analysis, which includes a data acquisition cluster, an intelligent analysis server, a data storage server, and a fault early warning server, where the intelligent analysis server is in signal connection with the data acquisition cluster, the data storage server, and the fault early warning server;
the data acquisition cluster is used for acquiring operation monitoring data of the intelligent cable and uploading the operation monitoring data to the intelligent analysis server, and the operation monitoring data comprises a line number corresponding to the intelligent cable;
the intelligent analysis server comprises a data management module and a data analysis module, wherein the data management module is used for receiving the operation monitoring data uploaded by the data acquisition cluster and storing time information and line numbers corresponding to the operation monitoring data in the data storage server as historical data; the data analysis module is used for extracting the operation monitoring data of the intelligent cable corresponding to the line number, inputting the operation monitoring data into a preset big data analysis model for operation fault prediction analysis of the intelligent cable to obtain a corresponding prediction analysis result, and sending the prediction analysis result to the fault early warning server;
and the fault early warning server is used for receiving the prediction analysis result and carrying out early warning prompt on the operation fault of the intelligent cable based on the prediction analysis result.
Furthermore, the data acquisition cluster includes the monitoring module and the gateway that correspond each intelligent cable, gateway signal connection each the monitoring module is used for summarizing each the operation monitoring data that the monitoring module uploaded will the operation monitoring data upload to intelligent analysis server.
Furthermore, the monitoring module comprises a temperature monitoring module, a current monitoring module, a partial discharge monitoring module and a vibration monitoring module which are distributed at each position of the intelligent cable.
Furthermore, each of the temperature monitoring module, the current monitoring module, the partial discharge monitoring module and the vibration monitoring module collects the operation monitoring data to the gateway through data skip transmission.
Further, the data management module comprises a data labeling unit for labeling the operation monitoring data based on a set labeling standard.
Further, the fault early warning server comprises a display for displaying the early warning prompt of the operation fault of the intelligent cable in real time.
Further, the fault early warning server comprises a line map marking module, and is used for performing fault early warning marking on a corresponding position pre-stored in the intelligent cable line map according to a prediction analysis result, and outputting the marked intelligent cable line map to the display for displaying.
Further, the fault early warning server is further in signal connection with the monitoring terminal and used for sending the early warning prompt of the operation fault of the intelligent cable and the intelligent cable line map after the fault early warning mark to the monitoring terminal.
Further, the fault early warning server further comprises a result storage module, and the result storage module is used for storing the prediction analysis results meeting the early warning prompt standard.
Further, the intelligent analysis server further comprises a modification module for modifying the big data analysis model based on the historical data.
In a second aspect, an embodiment of the present application provides an intelligent cable early warning method based on big data analysis, including:
the intelligent analysis server extracts operation monitoring data corresponding to the intelligent cable through the data analysis module;
the data analysis module inputs the operation monitoring data into a preset big data analysis model to carry out operation fault prediction analysis on the intelligent cable to obtain a corresponding prediction analysis result, and the big data analysis model is a linear regression mathematical model based on a machine learning algorithm;
and the data analysis module sends the prediction analysis result to a fault early warning server, and the fault early warning server carries out early warning prompt on the operation fault of the intelligent cable based on the prediction analysis result.
Further, the big data analysis model is as follows:
f(xi)＝w1x1+w2x2+...+wnxn
wherein [ w1,w2...,wn]To predict the coefficients, [ x ]1,x2...,xn]For each type of operational monitoring data, f (x)i) And the predicted value of the corresponding operation monitoring data is obtained.
Further, the fault early warning server carries out early warning prompt of the operation fault of the intelligent cable based on the prediction analysis result, and the early warning prompt comprises the following steps:
and comparing the predicted value obtained by calculation of the big data analysis model with a set early warning prompt standard, and carrying out early warning prompt on the operation fault of the intelligent cable based on the predicted value reaching the early warning prompt standard.
Further, the fault early warning server carries out early warning suggestion of intelligent cable operation fault based on the predictive analysis result, and the fault early warning method further comprises the following steps:
and extracting an intelligent cable line map through a line map marking module of the fault early warning server, carrying out fault early warning marking on the corresponding position of the intelligent cable line map according to the prediction analysis result, and outputting the marked intelligent cable line map to a display for displaying.
Further, after the fault early warning server performs early warning prompting of the intelligent cable operation fault based on the prediction analysis result, the method further comprises the following steps:
and extracting historical data corresponding to the operation monitoring data through a correction module of the intelligent analysis server, and correcting the big data analysis model by combining a prediction analysis result corresponding to the operation monitoring data.
According to the intelligent cable early warning platform based on big data analysis, the operation monitoring data corresponding to the intelligent cable are extracted through the intelligent analysis server, the operation monitoring data are input into a preset big data analysis model to conduct operation fault prediction analysis on the intelligent cable, a corresponding prediction analysis result is obtained, the prediction analysis result is sent to the fault early warning server, and early warning prompt of operation faults of the intelligent cable is conducted by the fault early warning server based on the prediction analysis result. By adopting the technical means, the operation fault prediction of the intelligent cable can be realized, and the early warning prompt is carried out according to the prediction result, so that the potential operation fault risk can be avoided well, the economic loss caused by the intelligent cable fault is avoided, and the operation management of the intelligent cable is optimized.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent cable early warning platform based on big data analysis according to an embodiment of the present application;
fig. 2 is a schematic flowchart of an intelligent cable early warning method based on big data analysis according to an embodiment of the present application;
FIG. 3 is a schematic connection diagram of modules of a cable early warning platform according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a data collection cluster in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, specific embodiments of the present application will be described in detail with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some but not all of the relevant portions of the present application are shown in the drawings. The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that all other embodiments obtained by a person of ordinary skill in the art without any creative effort based on the embodiments of the present application belong to the protection scope of the present application. In the embodiments of the present application, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings. These terms are used primarily to better describe the present application and its embodiments, and are not used to limit the indicated devices, elements or components to a particular orientation or to be constructed and operated in a particular orientation. Moreover, some of the above terms may be used to indicate other meanings besides the orientation or positional relationship, for example, the term "on" may also be used to indicate some kind of attachment or connection relationship in some cases. The specific meaning of these terms in this application will be understood by those of ordinary skill in the art as appropriate. Furthermore, the terms "mounted," "disposed," "provided," "connected," and "connected" are to be construed broadly. For example, it may be a fixed connection, a removable connection, or a unitary construction; can be a mechanical connection, or an electrical connection; may be directly connected, or indirectly connected through intervening media, or may be in internal communication between two devices, elements or components. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as appropriate.
The application provides an intelligent cable early warning platform based on big data analysis aims at carrying out real-time analysis based on the operation monitoring data of the intelligent cable that gathers in real time, carries out the prediction of intelligent cable running state through big data analysis model to carry out early warning suggestion according to the prediction result. Therefore, the intelligent cable early warning platform can early warn potential operation faults of the intelligent cable, and operation management of the intelligent cable is optimized. Compared with the traditional intelligent cable operation and maintenance management system, the intelligent cable operation and maintenance management system can only detect faults through operation monitoring data and prompt faults according to the operation monitoring data. Because the potential operation fault of the intelligent cable cannot be found as early as possible, even if the operation fault can be found in time and maintained through fault detection, when the operation and maintenance cost is relatively high, the economic loss caused by the fault is difficult to estimate. Therefore, the intelligent cable early warning platform and the intelligent cable early warning method based on big data analysis are provided to solve the technical problem that the existing intelligent cable operation and maintenance system cannot predict operation faults in time.
The first embodiment is as follows:
fig. 1 shows a schematic structural diagram of an intelligent cable early warning platform based on big data analysis according to an embodiment of the present application, and referring to fig. 1, the intelligent cable early warning platform based on big data analysis specifically includes: the system comprises a data acquisition cluster, an intelligent analysis server, a data storage server and a fault early warning server, wherein the intelligent analysis server is in signal connection with the data acquisition cluster, the data storage server and the fault early warning server; the intelligent analysis server is used for performing operation fault prediction analysis on the intelligent cable according to the operation monitoring data to obtain a corresponding prediction analysis result, and sending the prediction analysis result to the fault early warning server; the data acquisition cluster is used for acquiring operation monitoring data of the intelligent cable and uploading the operation monitoring data to the intelligent analysis server, and the operation monitoring data comprises a line number corresponding to the intelligent cable; and the fault early warning server is used for receiving the prediction analysis result and carrying out early warning prompt on the operation fault of the intelligent cable based on the prediction analysis result.
Specifically, in this application embodiment, the data collection cluster is disposed at the front end and used for collecting operation monitoring data of each intelligent cable line, wherein the operation monitoring data can be periodically collected by the data collection cluster according to a set data collection period and uploaded to the intelligent analysis server. Or the intelligent analysis server periodically issues a data acquisition request to acquire the operation monitoring data cached in the data acquisition cluster. It should be noted that the operation monitoring data collected by the data collection cluster needs to include the line number information of the intelligent cable corresponding to the operation monitoring data, so as to ascertain the intelligent cable line to which the corresponding operation monitoring data belongs when performing the storage and analysis of the operation monitoring data subsequently.
And the intelligent analysis server performs operation fault prediction analysis based on the received operation monitoring data and the operation monitoring data in real time. And performing prediction analysis by using a preset big data analysis model to obtain a corresponding prediction result. The prediction result is sent to a fault early warning server, and the fault early warning server carries out early warning prompt on the operation fault of the intelligent cable based on the prediction result, so that the potential operation fault risk can be avoided better, and the operation management of the intelligent cable is optimized.
Further, referring to fig. 2, a flowchart of an intelligent cable early warning method based on big data analysis is provided, and the intelligent cable early warning platform based on big data analysis according to the embodiment of the present application can implement early warning prompt of an intelligent cable operation fault by using the intelligent cable early warning method based on big data analysis, wherein the intelligent cable early warning method based on big data analysis includes:
s110, the intelligent analysis server extracts operation monitoring data corresponding to the intelligent cable through a data analysis module;
s120, the data analysis module inputs the operation monitoring data into a preset big data analysis model to perform operation fault prediction analysis on the intelligent cable to obtain a corresponding prediction analysis result, wherein the big data analysis model is a linear regression mathematical model based on a machine learning algorithm;
s130, the data analysis module sends the prediction analysis result to a fault early warning server, and the fault early warning server carries out early warning prompt on the operation fault of the intelligent cable based on the prediction analysis result.
In the embodiment of the application, the intelligent analysis server performs prediction analysis through a big data analysis model constructed by a linear regression mathematical model based on a machine learning algorithm based on the received operation monitoring data. Wherein, the big data analysis model is as follows:
f(xi)＝w1x1+w2x2+...+wnxn
wherein [ w1,w2...,wn]Is a prediction coefficient, which is constructed according to the historical data rule of the operation monitoring data, [ x ]1,x2...,xn]For various operation monitoring data, such as current, voltage, temperature, partial discharge, etc., f (x)i) And the predicted value of the corresponding operation monitoring data is obtained.
Specifically, according to the actual operation monitoring requirement, the operation monitoring data may be operation state data of the circuit, voltage, temperature, partial discharge, vibration condition, and the like of the smart cable. The operation state data is input into the big data analysis model, and a predicted value corresponding to the operation monitoring data can be obtained. Correspondingly, when the fault early warning server carries out early warning prompting on the operation fault of the intelligent cable based on the prediction analysis result, the predicted value obtained through calculation of the big data analysis model can be compared with a set early warning prompting standard, and early warning prompting on the operation fault of the intelligent cable is carried out based on the predicted value reaching the early warning prompting standard. It can be understood that a warning prompt standard is established in advance for fault warning, the warning prompt standard defines warning prompt indexes of various kinds of operation state data, and when the predicted value of the operation monitoring data obtained according to the big data prediction model exceeds the corresponding warning prompt index, it is indicated that operation fault warning prompt of the corresponding intelligent cable is required. For example, a temperature upper limit is defined, a predicted temperature value of the intelligent cable is extracted from a prediction analysis result obtained according to the big data analysis model, the predicted value is compared with the corresponding temperature upper limit, and if the predicted temperature value is larger than the temperature upper limit, when the temperature monitoring of the intelligent cable exceeds the standard, the fault early warning server outputs an early warning prompt corresponding to the temperature exceeding of the intelligent cable based on the prediction analysis result. Further, in an embodiment, early warning indication indexes of different levels may be set corresponding to one type of operation monitoring data, and subsequently, when early warning indication is performed, early warning indication of a corresponding level is output according to a prediction indication index that the operation monitoring data is out of limit. For example, A, B and C temperature early warning indicators are set, corresponding to the first-level early warning, the second-level early warning and the third-level early warning, respectively. The higher the warning level, the more serious the predicted operational failure. Based on the method, when the early warning prompt is determined according to the comparison of the prediction values of the prediction prompt indexes, the corresponding early warning amount can be clearly prompted, and operation and maintenance personnel can conveniently know the serious condition of the current operation fault early warning.
More specifically, referring to fig. 3, in the embodiment of the present application, the intelligent analysis server includes a data management module and a data analysis module, where the data management module is configured to receive the operation monitoring data uploaded by the data acquisition cluster, and store time information and a line number corresponding to the operation monitoring data in the data storage server as historical data; the data analysis module is used for extracting the operation monitoring data of the intelligent cable corresponding to the line number, inputting the operation monitoring data into a preset big data analysis model for operation fault prediction analysis of the intelligent cable, obtaining a corresponding prediction analysis result, and sending the prediction analysis result to the fault early warning server. The operation monitoring data are managed by the data management module and are stored in the data storage server as historical data, so that operation and maintenance personnel can conveniently inquire the operation monitoring data. And the historical data stored by the data storage server can be used for correcting the big data analysis model subsequently, so that the prediction result of the big data prediction model is more accurate. In addition, it should be noted that, when the data storage server stores the operation monitoring data, the data storage server stores the time information and the line number corresponding to the operation monitoring data, so that the time information or the line number of the smart cable is used as a data index to search the historical data when the historical data is queried subsequently. Similarly, when the data analysis module analyzes the operation monitoring data, the operation monitoring data corresponding to the intelligent cable with the line number is extracted according to the analysis requirement and input into the big data analysis model for prediction analysis, the operation fault prediction analysis result of the intelligent cable with the line number is obtained, and then the operation fault early warning prompt of the intelligent cable with the line number is carried out through the fault early warning service according to the prediction analysis result.
In one embodiment, the data management module includes a data labeling unit, configured to label the operation monitoring data based on a set labeling standard. When the operation monitoring data is stored in the data storage server, part of the operation monitoring data is marked in advance through the marking unit. The operation monitoring data marking is mainly to determine abnormal or nearly abnormal operation monitoring data by comparing marking standards. By marking the operation monitoring data, follow-up operation and maintenance personnel can conveniently inquire the abnormal data. The intelligent cable is confirmed to have an abnormal or nearly abnormal condition at a certain time point. The marking standard defines the marking index of various kinds of operation state data, when the operation monitoring data exceeds the corresponding marking index, the data is marked, and then the abnormal condition of the operation monitoring data is informed to operation and maintenance personnel in a highlight or marking symbol mode. For example, a current abnormality labeling standard value is defined, subsequently, during data labeling, operation monitoring data corresponding to the intelligent cable are extracted, a current value of the operation monitoring data is extracted, and if the current value is larger than the current abnormality labeling standard value, the current data of the operation monitoring data is labeled.
In addition, refer to fig. 4, provide the schematic structure diagram of the data acquisition cluster of this application embodiment, wherein, the data acquisition cluster includes the monitoring module and the gateway that correspond each smart cable, gateway signal connection each the monitoring module is used for summarizing each the monitoring module uploads the operation monitoring data will the operation monitoring data upload to the intelligent analysis server. In this application embodiment, the operation monitoring data that the monitoring module of the intelligent cable of each different circuit gathered can be gathered through the gateway as the network relay who connects each intelligent cable monitoring module and intelligent analysis server to the gateway. It should be noted that, when the monitoring module of each smart cable uploads the operation monitoring data, the time information of the current data monitoring and the line number information of the smart cable need to be attached to the operation monitoring data, so as to store and analyze the data subsequently.
Furthermore, the monitoring module comprises a temperature monitoring module, a current monitoring module, a partial discharge monitoring module and a vibration monitoring module which are distributed at each position of the intelligent cable. And the temperature monitoring modules, the current monitoring modules, the partial discharge monitoring modules and the vibration monitoring modules gather the operation monitoring data to the gateway through data skip transmission. The operation monitoring data mainly collected by the embodiment of the application are temperature data, current data, partial discharge conditions and vibration monitoring data. According to the actual operation monitoring requirement, the voltage and other related operation state data of the intelligent cable can be acquired. When monitoring the running state data of partial discharge, arranging a partial discharge monitoring module on a cable accessory and/or a ground wire return line, wherein the partial discharge monitoring module comprises a polarized light unit, an optical fiber sensing unit and a light intensity measuring unit; the polarized light unit is used for forming a polarized light group comprising at least two polarized lights, and the polarized light intensity value of the output end of the polarized light unit is used as a first light intensity value; the optical fiber sensing unit is connected with the polarized light unit and is used for transmitting polarized light; the light intensity measuring unit is connected with the optical fiber sensing unit and is used for performing coherent superposition on the polarized light passing through the optical fiber sensing unit, and the light intensity value of the polarized light at the output end of the light intensity measuring unit is used as a second light intensity value; the partial discharge monitoring module obtains a partial discharge detection result according to the first light intensity value and the second light intensity value. Partial discharge signals in a larger frequency range can be detected through the partial discharge monitoring module, the partial discharge condition can be monitored in real time, and the accuracy of partial discharge detection is improved. The temperature monitoring module, the current monitoring module, the partial discharge monitoring module and the vibration monitoring module are arranged on the base. The specific implementation modes of monitoring the operation monitoring data corresponding to the intelligent cable are many, and the embodiment of the application is not subject to fixed limitation and is not described herein repeatedly.
Furthermore, when the temperature monitoring module, the current monitoring module, the partial discharge monitoring module and the vibration monitoring module are used for collecting operation monitoring data, the distributed setting mode is adopted to set the operation monitoring data at each position of the intelligent cable, and the quantity of each type of monitoring module is set according to the collection requirement of the operation monitoring data of the intelligent cable. In addition, it should be noted that when various monitoring modules upload operation monitoring data, the corresponding monitoring module numbers of the monitoring modules need to be attached to the operation monitoring data, so that when the operation monitoring data is uploaded to an intelligent analysis server for analysis and storage, it can be known that the operation monitoring data comes from a certain monitoring module of a certain line intelligent cable. Therefore, different monitoring module numbers and the set geographic positions are bound, and a certain position of the intelligent cable from which certain operation monitoring data comes can be confirmed. In one embodiment, the current monitoring module position can be determined by using GPS positioning, and the operation monitoring data is uploaded together with the current GPS positioning information. Specifically, when various monitoring modules of this application are gathering operation monitoring data to the gateway, each monitoring module can establish communication link with the gateway one by one through wired or wireless mode to gather operation monitoring data to the gateway. In one embodiment, the data can be uploaded in a data hopping mode. For example, a plurality of temperature monitoring modules are correspondingly arranged on one intelligent cable, the temperature monitoring modules are distributed on the line of the intelligent cable according to set intervals, and one or more host nodes are selected as data transmission host nodes. Furthermore, after each temperature monitoring module collects temperature data, the temperature data is subjected to skip transmission to the adjacent temperature monitoring modules, and by analogy, the temperature data is subjected to skip transmission on the temperature monitoring modules on the intelligent cable line and is gathered to the nearest main node, and the main node uploads the temperature data to the gateway, so that data skip transmission is completed. The monitoring modules can adopt communication modules such as Bluetooth or ZigBee and the like to realize communication among the monitoring modules. Compared with the remote transmission of monitoring data to a gateway, the embodiment of the application carries out data skip transmission and collection through Bluetooth or ZigBee, so that the interference in the data transmission process can be reduced, and the communication charge is reduced.
On the other hand, the fault early warning server comprises a display for displaying the early warning prompt of the intelligent cable operation fault in real time. The fault early warning server comprises a line map marking module which is used for carrying out fault early warning marking on the corresponding position pre-stored in the intelligent cable line map according to the prediction analysis result and outputting the marked intelligent cable line map to the display for displaying. By arranging the display, operation and maintenance personnel can conveniently and visually know the early warning prompt information. And according to actual needs, an acousto-optic early warning form can be adopted to output early warning prompts so as to better prompt the early warning of the operation fault. The sound and light early warning is prompted through a loudspeaker and an LED indicating lamp, the loudspeaker and the LED indicating lamp are respectively controlled by a fault early warning server, and the sound and light early warning is prompted according to a control signal of the fault early warning server. Furthermore, when fault early warning is carried out, an intelligent cable line map is extracted through a line map marking module of the fault early warning server, fault early warning marking is carried out on the corresponding position of the intelligent cable line map according to the prediction analysis result, and the marked intelligent cable line map is output to a display to be displayed. According to the method and the device, the intelligent cable line map is constructed on the fault early warning server in advance corresponding to the actual arrangement of the intelligent cables, and fault early warning marking is carried out on the intelligent cable line map according to the position information of operation monitoring information and the corresponding line number information when fault early warning is carried out according to the operation monitoring information subsequently. And outputs it to the display for display. Operation and maintenance personnel can confirm that a certain position of the intelligent cable of a certain current line has a potential fault risk through the marked intelligent cable line map, and then the operation and maintenance monitoring of the intelligent cable is optimized. In addition, the fault early warning server is further connected with a monitoring terminal through signals and used for sending the early warning prompt of the operation fault of the intelligent cable and the intelligent cable line map after the fault early warning mark to the monitoring terminal. The intelligent cable early warning system is connected with the monitoring terminal through the fault early warning server in a signal mode, operation fault early warning prompt of the intelligent cable can be carried out anytime and anywhere, and operation and maintenance personnel can be guaranteed to carry out early warning prompt through various channels or operation faults of the intelligent cable. And the early warning prompts can be graded according to actual needs, and different channels are adopted for early warning prompts according to different grades. It can be understood that the early warning prompt corresponding to the early warning prompt with a lower level is directly performed through the display. If the intelligent cable operation fault is an urgent early warning prompt, the early warning prompt of the intelligent cable operation fault can be carried out through a plurality of channels such as a display and a monitoring terminal of operation and maintenance personnel.
In addition, the fault early warning server further comprises a result storage module, and the result storage module is used for storing the prediction analysis results meeting the early warning prompt standard. The predictive analysis result meeting the early warning prompt standard is stored through the storage module, so that the statistical analysis of the predictive analysis result is conveniently carried out subsequently. According to the prediction analysis result stored in the storage module, the prediction precision of the big data analysis model can be determined by comparing the operation monitoring data generated by the actual operation of the intelligent cable, and whether the model correction is carried out or not can be further judged according to the prediction precision. On the other hand, according to the prediction analysis result which is stored by the storage module and meets the early warning prompt standard, the intelligent cable with the operation fault can be determined to be predicted for many times, and then the intelligent cable of the corresponding line is subjected to targeted operation and maintenance management, so that the operation and maintenance management efficiency of the intelligent cable can be improved.
In one embodiment, the intelligent analytics server further comprises a revising module for revising the big data analytics model based on the historical data. And extracting historical data corresponding to the operation monitoring data through a correction module of the intelligent analysis server, and correcting the big data analysis model by combining a prediction analysis result corresponding to the operation monitoring data. Specifically, on the basis of the big data analysis model, the embodiment of the application provides a model correction method based on a cost function. The cost function is formulated as:
wherein X is a historical data matrix corresponding to the operation monitoring data, and Y is a prediction analysis result corresponding to the operation monitoring data, namely a prediction value f (X) of the operation monitoring datai) A matrix of components. And W is a prediction coefficient matrix of the big data analysis model. And correcting the prediction coefficient of the big data analysis model based on the cost function, and further performing prediction analysis according to the corrected prediction coefficient.
In particular, a historical data matrix of operational monitoring data is assumed
The historical data matrix represents various operation monitoring data in the operation process of the intelligent cable, such as temperature data, current data and partial discharge data set vibration monitoring data; and further using a Y matrix to represent a predicted value Y ═ Y corresponding to each operation monitoring data1,y2...yn](ii) a The prediction coefficient matrix is
From this, a linear model h can be obtainedW(X) ═ XW; in order to make the prediction more accurate, the difference between the actual operation monitoring data and the predicted value needs to be as small as possible, so as to obtain the cost function. Finally solving to obtain W ═ X based on the cost functionTX)-1XTY；XTRepresenting the transpose of matrix X. And then, carrying out a new round of analysis and prediction of the big data prediction model according to the new prediction coefficient.
The operation monitoring data corresponding to the intelligent cable are extracted through the intelligent analysis server, the operation monitoring data are input into a preset big data analysis model to carry out operation fault prediction analysis on the intelligent cable, a corresponding prediction analysis result is obtained, the prediction analysis result is sent to the fault early warning server, and early warning prompt of the operation fault of the intelligent cable is carried out by the fault early warning server based on the prediction analysis result. By adopting the technical means, the operation fault prediction of the intelligent cable can be realized, and the early warning prompt is carried out according to the prediction result, so that the potential operation fault risk can be avoided well, the economic loss caused by the intelligent cable fault is avoided, and the operation management of the intelligent cable is optimized.
Example two:
the present application also provides a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform a big data analysis-based intelligent cable early warning method, where the big data analysis-based intelligent cable early warning method includes: the intelligent analysis server extracts operation monitoring data corresponding to the intelligent cable through the data analysis module; the data analysis module inputs the operation monitoring data into a preset big data analysis model to carry out operation fault prediction analysis on the intelligent cable to obtain a corresponding prediction analysis result, and the big data analysis model is a linear regression mathematical model based on a machine learning algorithm; and the data analysis module sends the prediction analysis result to a fault early warning server, and the fault early warning server carries out early warning prompt on the operation fault of the intelligent cable based on the prediction analysis result.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in a first computer system in which the program is executed, or may be located in a different second computer system connected to the first computer system through a network (such as the internet). The second computer system may provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media residing in different locations, e.g., in different computer systems connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium containing the computer-executable instructions provided in the embodiments of the present application is not limited to the above-described intelligent cable warning method based on big data analysis, and may also perform related operations in the intelligent cable warning method based on big data analysis provided in any embodiments of the present application.
The intelligent cable early warning platform and the storage medium based on big data analysis provided in the above embodiments may execute the intelligent cable early warning method based on big data analysis provided in any embodiment of the present application, and the technical details not described in detail in the above embodiments may be referred to the intelligent cable early warning method based on big data analysis provided in any embodiment of the present application.
The foregoing is considered as illustrative of the preferred embodiments of the invention and the technical principles employed. The present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the claims.
Claims (15)
1. The utility model provides an intelligence cable early warning platform based on big data analysis which characterized in that includes: the system comprises a data acquisition cluster, an intelligent analysis server, a data storage server and a fault early warning server, wherein the intelligent analysis server is in signal connection with the data acquisition cluster, the data storage server and the fault early warning server;
the data acquisition cluster is used for acquiring operation monitoring data of the intelligent cable and uploading the operation monitoring data to the intelligent analysis server, and the operation monitoring data comprises a line number corresponding to the intelligent cable;
the intelligent analysis server comprises a data management module and a data analysis module, wherein the data management module is used for receiving the operation monitoring data uploaded by the data acquisition cluster and storing time information and line numbers corresponding to the operation monitoring data in the data storage server as historical data; the data analysis module is used for extracting the operation monitoring data of the intelligent cable corresponding to the line number, inputting the operation monitoring data into a preset big data analysis model for operation fault prediction analysis of the intelligent cable to obtain a corresponding prediction analysis result, and sending the prediction analysis result to the fault early warning server;
and the fault early warning server is used for receiving the prediction analysis result and carrying out early warning prompt on the operation fault of the intelligent cable based on the prediction analysis result.
2. The intelligent cable early warning platform based on big data analysis of claim 1, wherein the data collection cluster comprises monitoring modules corresponding to the intelligent cables and a gateway, and the gateway is in signal connection with the monitoring modules and is used for summarizing the operation monitoring data uploaded by the monitoring modules and uploading the operation monitoring data to the intelligent analysis server.
3. The intelligent cable early warning platform based on big data analysis of claim 2, wherein the monitoring module comprises a temperature monitoring module, a current monitoring module, a partial discharge monitoring module and a vibration monitoring module which are distributed at each position of the intelligent cable.
4. The intelligent cable early warning platform based on big data analysis of claim 3, wherein each of the temperature monitoring module, the current monitoring module, the partial discharge monitoring module and the vibration monitoring module collects the operation monitoring data to the gateway through data hopping.
5. The intelligent cable early warning platform based on big data analysis of claim 1, wherein the data management module comprises a data labeling unit for labeling the operation monitoring data based on a set labeling standard.
6. The intelligent cable early warning platform based on big data analysis of claim 1, wherein the fault early warning server comprises a display for displaying early warning prompts of intelligent cable operation faults in real time.
7. The intelligent cable early warning platform based on big data analysis of claim 6, wherein the fault early warning server comprises a line map labeling module, which is used for performing fault early warning labeling on a corresponding position pre-stored in the intelligent cable line map according to a prediction analysis result, and outputting the labeled intelligent cable line map to the display for displaying.
8. The intelligent cable early warning platform based on big data analysis of claim 7, wherein the fault early warning server is further in signal connection with a monitoring terminal, and is configured to send an early warning prompt of an operating fault of an intelligent cable and an intelligent cable line map after fault early warning marking to the monitoring terminal.
9. The intelligent cable early warning platform based on big data analysis of any one of claims 1 to 8, wherein the fault early warning server further comprises a result storage module, and the result storage module is used for storing the prediction analysis results meeting the early warning prompt criteria.
10. The intelligent cable early warning platform based on big data analysis of any one of claims 1 to 8, wherein the intelligent analysis server further comprises a modification module for modifying the big data analysis model based on the historical data.
11. An intelligent cable early warning method based on big data analysis is characterized by comprising the following steps:
the intelligent analysis server extracts operation monitoring data corresponding to the intelligent cable through the data analysis module;
the data analysis module inputs the operation monitoring data into a preset big data analysis model to carry out operation fault prediction analysis on the intelligent cable to obtain a corresponding prediction analysis result, and the big data analysis model is a linear regression mathematical model based on a machine learning algorithm;
and the data analysis module sends the prediction analysis result to a fault early warning server, and the fault early warning server carries out early warning prompt on the operation fault of the intelligent cable based on the prediction analysis result.
12. The intelligent cable early warning method based on big data analysis of claim 11, wherein the big data analysis model is:
f(xi)＝w1x1+w2x2+...+wnxn
wherein [ w1,w2...,wn]To predict the coefficients, [ x ]1,x2...,xn]For each type of operational monitoring data, f (x)i) And the predicted value of the corresponding operation monitoring data is obtained.
13. The intelligent cable early warning method based on big data analysis according to claim 12, wherein the fault early warning server performs early warning prompt of the operation fault of the intelligent cable based on the prediction analysis result, and the method comprises:
and comparing the predicted value obtained by calculation of the big data analysis model with a set early warning prompt standard, and carrying out early warning prompt on the operation fault of the intelligent cable based on the predicted value reaching the early warning prompt standard.
14. The intelligent cable early warning method based on big data analysis according to claim 12, wherein the fault early warning server performs early warning prompt of the operation fault of the intelligent cable based on the prediction analysis result, further comprising:
and extracting an intelligent cable line map through a line map marking module of the fault early warning server, carrying out fault early warning marking on the corresponding position of the intelligent cable line map according to the prediction analysis result, and outputting the marked intelligent cable line map to a display for displaying.
15. The intelligent cable warning method based on big data analysis according to claim 11, wherein after the warning prompt of the intelligent cable operation fault is performed by the fault warning server based on the prediction analysis result, the method further comprises:
and extracting historical data corresponding to the operation monitoring data through a correction module of the intelligent analysis server, and correcting the big data analysis model by combining a prediction analysis result corresponding to the operation monitoring data.
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