CN112885049B - Intelligent cable early warning system, method and device based on operation data - Google Patents
Intelligent cable early warning system, method and device based on operation data Download PDFInfo
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Abstract
The embodiment of the application discloses an intelligent cable early warning system, a method and a device based on operation data, wherein the system comprises a first data acquisition cluster, a second data acquisition cluster, an intelligent early warning server, a data storage and an intelligent analysis server; the intelligent early warning system comprises a first data acquisition cluster, a data storage and an intelligent analysis server, wherein the first data acquisition cluster, the data storage and the intelligent analysis server are connected with the intelligent early warning server, the data storage is respectively connected with a second data acquisition cluster and the intelligent analysis server, the first data acquisition cluster is used for acquiring operating data of an intelligent cable, the second data acquisition cluster is used for acquiring physical data of the intelligent cable, a data early warning module on the intelligent early warning server is provided with a data early warning model for carrying out fault prediction on the operating data and outputting an early warning result, when the early warning result shows that the fault occurs, the physical data are read, further secondary judgment is carried out by combining the condition of the physical data and the early warning result, and the accuracy of the early warning result is detected in an auxiliary mode.
Description
Technical Field
The embodiment of the application relates to the technical field of cables, in particular to an intelligent cable early warning system, method and device based on operation data.
Background
Modern electric energy is related to various aspects of daily life, production and the like of people, so once an electric accident happens, serious consequences are very likely to be caused, and the fault needs to be quickly positioned and repaired. At present, the operation and maintenance of the cable are more and more intelligent in order to better monitor the operation state of the cable in real time and realize better operation and maintenance effects on the cable. The intelligent cable can realize real-time monitoring on parameters such as voltage, current and local current of the cable through detection setting of relevant states, and even can monitor cable faults, so that operation management of the cable is realized, and operation and maintenance effects of the cable are optimized.
But at present, the fault of each operating parameter of the intelligent cable is difficult to early warn, and once the fault occurs, more manpower is consumed for maintenance.
Disclosure of Invention
The embodiment of the application provides an intelligent cable early warning system, method and device based on operation data, so that fault early warning of an intelligent cable is achieved in advance.
In a first aspect, an embodiment of the present application provides an intelligent cable early warning system based on operational data, which includes a first data acquisition cluster, a second data acquisition cluster, an intelligent early warning server, a data storage, and an intelligent analysis server; the first data acquisition cluster, the data storage and the intelligent analysis server are all connected with the intelligent early warning server, and the data storage is respectively connected with the second data acquisition cluster and the intelligent analysis server;
the first data acquisition cluster is used for acquiring operation data of the intelligent cable and uploading the operation data to the intelligent early warning server, and the operation data comprises time information and a line number corresponding to the intelligent cable;
the second data acquisition cluster is used for acquiring physical data of the intelligent cable and transmitting the physical data to the data storage device for storage; the physical data comprises time information and a line number corresponding to the intelligent cable;
the intelligent early warning server comprises a data management module and a data early warning module, wherein the data management module is used for receiving operation data uploaded by a first data acquisition cluster, and storing the operation data, corresponding time information and a line number of an intelligent cable in a data storage as historical data; the data early warning module is provided with a pre-trained operation data early warning model and is used for inputting operation data into the operation data early warning model, acquiring a corresponding early warning result output by the operation data early warning model and sending the early warning result to the intelligent analysis server;
the intelligent analysis server is used for receiving the early warning result, judging whether the early warning result is correct according to corresponding physical data when the early warning result is a fault, and issuing alarm information when the early warning result is correct; and when the early warning result is wrong, giving up the early warning result.
Optionally, the first data collection cluster includes first monitoring modules and first gateways corresponding to the intelligent cables, and the first gateways are connected to the first monitoring modules and used for summarizing running data uploaded by the first monitoring modules and uploading the running data to the intelligent early warning server.
Optionally, the second data collection cluster includes second monitoring modules and second gateways corresponding to the respective smart cables, and the second gateways are connected to the respective second monitoring modules, and configured to summarize operation data uploaded by the respective second monitoring modules and upload the operation data to the data storage.
Optionally, the physical data comprises any one or more of smart cable image data, user evaluation data, surface defect monitoring data.
In a second aspect, an embodiment of the present application provides an intelligent cable early warning method based on operational data, including:
receiving operation data acquired through a first data acquisition cluster, wherein the operation data comprises time information and a line number corresponding to an intelligent cable;
storing the operation data as historical data, inputting the operation data into a pre-trained operation data early warning model, and acquiring an early warning result output by the operation data early warning model;
when the early warning result is a fault, receiving physical data acquired by a second data acquisition cluster;
judging whether the early warning result is correct or not according to the physical data, and issuing alarm information when the early warning result is correct; and when the early warning result is wrong, giving up the early warning result.
Further, the physical data comprises any one or more of intelligent cable image data, user evaluation data and surface defect monitoring data;
the judging whether the early warning result is correct according to the physical data comprises the following steps:
detecting whether the physical data contain user evaluation data and/or surface defect monitoring data, when the physical data contain the user evaluation data, obtaining the evaluation content of the user evaluation data, and comparing whether the evaluation content is consistent with the early warning result; when the surface defect monitoring data is contained, defining the early warning result to be correct;
and when the physical data does not contain user evaluation data and surface defect monitoring data, comparing whether the intelligent cable image data is consistent with preset reference image data or not.
Optionally, the operation data early warning model is trained by:
selecting historical data corresponding to the fault result as a fault from a plurality of groups of historical data as target historical data;
acquiring historical data of a last acquisition time point adjacent to an acquisition time point of the target historical data;
and performing operation data early warning model training by taking the historical data of the last acquisition time point as a model input characteristic and taking a fault result of the target historical data as a model output characteristic.
In a third aspect, an embodiment of the present application provides an intelligent cable early warning device based on operation data, including:
a first data module: the intelligent cable management system is used for receiving operation data acquired by the first data acquisition cluster, wherein the operation data comprises time information and a line number corresponding to an intelligent cable;
the early warning output module: the early warning system is used for storing the operation data as historical data, inputting the operation data into a pre-trained operation data early warning model and acquiring an early warning result output by the operation data early warning model;
a second data module: the early warning device is used for receiving physical data acquired by the second data acquisition cluster when the early warning result is a fault;
a result determination module: the early warning device is used for judging whether the early warning result is correct or not according to the physical data and issuing warning information when the early warning result is correct; and when the early warning result is wrong, giving up the early warning result.
Optionally, the physical data includes any one of smart cable image data, user evaluation data, and surface defect monitoring data;
the judging whether the early warning result is correct according to the physical data comprises the following steps:
detecting whether the physical data contain user evaluation data and/or surface defect monitoring data, when the physical data contain the user evaluation data, obtaining the evaluation content of the user evaluation data, and comparing whether the evaluation content is consistent with the early warning result; when the surface defect monitoring data is contained, defining the early warning result to be correct;
and when the physical data does not contain user evaluation data and surface defect monitoring data, comparing the intelligent cable image data with preset reference image data to determine whether the intelligent cable image data is consistent with the preset reference image data.
Optionally, the operation data early warning model is trained by:
selecting historical data corresponding to the fault result as a fault from a plurality of groups of historical data as target historical data;
acquiring historical data of a last acquisition time point adjacent to an acquisition time point of the target historical data;
and performing operation data early warning model training by taking the historical data of the last acquisition time point as a model input characteristic and taking a fault result of the target historical data as a model output characteristic.
In a fourth aspect, an embodiment of the present application provides a computer device, including: a memory and one or more processors;
the memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the intelligent cable warning method based on operational data according to the first aspect.
In a fifth aspect, embodiments of the present application provide a storage medium containing computer-executable instructions for performing the intelligent cable warning method based on operational data according to the first aspect when the computer-executable instructions are executed by a computer processor.
According to the embodiment of the application, the operation data of the intelligent cable is collected through the first data collection cluster, the physical data of the intelligent cable is collected through the second data collection cluster, the data early warning module on the intelligent early warning server is provided with the operation data early warning model to carry out fault prediction on the operation data and output an early warning result, when the early warning result shows that the operation data is a fault, the physical data is read, further secondary judgment is carried out by combining the condition of the physical data and the early warning result, and the accuracy of the early warning result is assisted to be detected.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent cable early warning system based on operational data according to an embodiment of the present disclosure;
fig. 2 is a flowchart of an intelligent cable early warning method based on operation data according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an intelligent cable warning device based on operation data according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a computer device according to 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 are described in detail below 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. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, subprograms, and the like.
The embodiment of the application provides an intelligent cable early warning system, method and device based on operation data. According to the embodiment of the application, the operation data of the intelligent cable is collected through the first data collection cluster, the physical data of the intelligent cable is collected through the second data collection cluster, the data early warning module on the intelligent early warning server is provided with the operation data early warning model to carry out fault prediction on the operation data and output an early warning result, when the early warning result shows that the operation data is a fault, the physical data is read, further secondary judgment is carried out by combining the condition of the physical data and the early warning result, and the accuracy of the early warning result is assisted to be detected.
The following are detailed below.
Fig. 1 shows a schematic structural diagram of an intelligent cable early warning system based on operational data according to an embodiment of the present disclosure, and referring to fig. 1, the intelligent cable early warning system based on operational data according to an embodiment of the present disclosure includes a first data collection cluster 101, a second data collection cluster 102, an intelligent early warning server 103, a data storage 104, and an intelligent analysis server 105. The first data collection cluster 101, the data storage 104 and the intelligent analysis server 105 are all connected to the intelligent early warning server 103, and the data storage 104 is connected to the second data collection cluster 102 and the intelligent analysis server 105.
The first data collection cluster 101 and the second data collection cluster 102 mainly achieve the collection effect on different data. The intelligent analysis server 105 is used for analyzing and comparing required data in the system subsequently, and the intelligent early warning server 103 is used for analyzing and predicting whether a fault occurs in the acquired data.
Specifically, the first data collection cluster 101 is configured to collect operation data of the smart cable, and upload the operation data to the intelligent early warning server 103, where the operation data includes time information and a line number corresponding to the smart cable. The second data acquisition cluster 102 is configured to acquire physical data of the smart cable, and transmit the physical data to a data storage device for storage; the physical data includes time information and a line number corresponding to the smart cable.
The operation data collected by the first data collection cluster 101 and the physical data collected by the second data collection cluster 102 correspond to time information and line numbers of the intelligent cables respectively, the time information generally refers to collection time, which intelligent cable the current operation data and the physical data correspond to can be known definitely through the line numbers of the intelligent cables, and the intelligent cables can be corresponding to in time when the faults are analyzed and predicted through the intelligent early warning 103 at the back.
In an embodiment, the first data collection cluster 101 includes first monitoring modules corresponding to the smart cables and first gateways, and the first gateways are connected to the first monitoring modules, and are configured to summarize operation data uploaded by the first monitoring modules and upload the operation data to the smart warning server 103.
Correspondingly, the second data acquisition cluster comprises second monitoring modules corresponding to the intelligent cables and second gateways, the second gateways are connected with the second monitoring modules and used for summarizing the operation data uploaded by the second monitoring modules and uploading the operation data to the data storage.
In this embodiment, the intelligent early warning server 103 includes a data management module 1031 and a data early warning module 1032, where the data management module 1031 is configured to receive the operation data uploaded by the first data collection cluster 101, and store the operation data, the corresponding time information, and the line number of the intelligent cable in the data storage 104 as historical data; the data early warning module 1032 is provided with a pre-trained operation data early warning model, and is configured to input operation data into the operation data early warning model, obtain a corresponding early warning result output by the operation data early warning model, and send the early warning result to the intelligent analysis server 105.
The intelligent analysis server 105 is configured to receive the early warning result, read corresponding physical data when the early warning result is a fault, determine whether the early warning result is correct according to the physical data, issue alarm information when the early warning result is correct, and abandon the early warning result when the early warning result is wrong.
According to the embodiment of the application, firstly, fault prediction is performed on the operation data collected by the first data collection cluster 101, the operation data is input to the operation data early warning model trained in the data early warning module 1032 in advance to perform fault prediction, and an early warning result output by the operation data early warning model is obtained. In one embodiment, the data alert model is trained by: selecting historical data corresponding to the fault result as a fault from a plurality of groups of historical data as target historical data; acquiring historical data of a last acquisition time point adjacent to an acquisition time point of the target historical data; and performing operation data early warning model training by taking the historical data of the last acquisition time point as a model input characteristic and taking the fault result of the target historical data as a model output characteristic.
And when the early warning result shows that the fault occurs, further carrying out secondary inspection through the physical data. In this embodiment, the physical data includes any one or more of smart cable image data, user evaluation data, and surface defect monitoring data. The step of determining whether the warning result is correct according to the physical data may include the following steps: detecting whether the physical data contain user evaluation data and/or surface defect monitoring data, acquiring the evaluation content of the user evaluation data when the physical data contain the user evaluation data, and comparing whether the evaluation content is consistent with the early warning result; when the surface defect monitoring data is contained, defining the early warning result to be correct; and when the physical data does not contain user evaluation data and surface defect monitoring data, comparing whether the intelligent cable image data is consistent with preset reference image data or not.
Fig. 2 is a flowchart of an intelligent cable early warning method based on operating data according to an embodiment of the present disclosure, where the intelligent cable early warning method based on operating data according to an embodiment of the present disclosure may be executed by an intelligent cable early warning apparatus based on operating data, and the intelligent cable early warning apparatus based on operating data may be implemented in a hardware and/or software manner and integrated in a computer device.
The following description will be given by taking an example in which the intelligent cable early warning apparatus based on the operation data executes an intelligent cable early warning method based on the operation data. Referring to fig. 2, the intelligent cable early warning method based on operation data includes:
201: and receiving operation data acquired through the first data acquisition cluster, wherein the operation data comprises time information and a line number corresponding to the intelligent cable.
In this embodiment of the application, the number of the first data collection clusters may be multiple, and the first data collection clusters are respectively in one-to-one correspondence with the smart cables, and each smart cable is provided with one first data collection cluster. In the subsequent storage of the operating data, the line numbers of the intelligent cables can be used as keywords for classified storage, and the operating data under the same line number are stored in the same storage area according to the time information.
202: and storing the operation data as historical data, inputting the operation data into a pre-trained operation data early warning model, and acquiring an early warning result output by the operation data early warning model.
And the data of each operation is stored as historical data, so that the tracing is convenient. And training an operation data early warning model, and using the historical data.
203: and when the early warning result is a fault, receiving the physical data acquired by the second data acquisition cluster.
204: and detecting whether the early warning result is correct or not according to the physical data, issuing warning information when the early warning result is correct, and giving up the early warning result when the early warning result is wrong.
In this step, when the early warning result is correct, the warning information is issued, that is, the warning information is notified to the staff, and a sound-light warning mode can be adopted, or a warning mail is automatically generated and sent to the staff, and the like. When the early warning result is wrong, the early warning result is not issued in the embodiment, and the early warning result is optionally discarded. As an optional implementation manner, the operation data corresponding to the early warning error and the result that the operation data is corresponding to a non-fault may be used as new model training data to correct the data early warning model.
In the embodiment of the present application, the physical data includes any one or more of smart cable image data, user evaluation data, and surface defect monitoring data.
Judging whether the early warning result is correct according to the physical data, comprising the following steps:
firstly, detecting whether physical data contains user evaluation data and/or surface defect monitoring data, when the physical data contains the user evaluation data, obtaining evaluation content of the user evaluation data, and comparing whether the evaluation content is consistent with an early warning result; when the surface defect monitoring data is contained, defining the early warning result to be correct; and when the physical data does not contain user evaluation data and surface defect monitoring data, comparing whether the intelligent cable image data is consistent with preset reference image data or not.
The pre-trained operation data early warning model is trained in the following way: selecting historical data corresponding to the fault result as a fault from a plurality of groups of historical data as target historical data; acquiring historical data of a last acquisition time point adjacent to the acquisition time point of the target historical data; and performing operation data early warning model training by taking the historical data of the last acquisition time point as a model input characteristic and taking a fault result of the target historical data as a model output characteristic.
As shown in fig. 3, an embodiment of the present application further provides an intelligent cable early warning device based on operation data, which includes a first data module 301, an early warning output module 302, a second data module 303, and a result determination module 304. The first data module 301 is configured to receive operation data collected by the first data collection cluster, where the operation data includes time information and a line number corresponding to the smart cable. The early warning output module 302 is configured to store the operation data as historical data, input the operation data into a pre-trained operation data early warning model, and obtain an early warning result output by the operation data early warning model. The second data module 303 is configured to receive the physical data acquired by the second data acquisition cluster when the early warning result is a failure. The result determining module 304 is configured to determine whether the early warning result is correct according to the physical data, and issue an alarm message when the early warning result is correct; and when the early warning result is wrong, giving up the early warning result.
Preferably, in this embodiment, the physical data includes any one of smart cable image data, user evaluation data, and surface defect monitoring data. In the result determining module 304, determining whether the early warning result is correct according to the physical data includes: detecting whether the physical data contain user evaluation data and/or surface defect monitoring data, acquiring the evaluation content of the user evaluation data when the physical data contain the user evaluation data, and comparing whether the evaluation content is consistent with the early warning result; when the surface defect monitoring data is contained, defining the early warning result to be correct; and when the physical data do not contain user evaluation data and surface defect monitoring data, comparing whether the intelligent cable image data are consistent with preset reference image data or not.
In the early warning output module 302, the pre-trained data early warning model is trained in the following way: selecting historical data corresponding to a fault result as fault in a plurality of groups of historical data as target historical data; acquiring historical data of a last acquisition time point adjacent to an acquisition time point of the target historical data; and performing operation data early warning model training by taking the historical data of the last acquisition time point as a model input characteristic and taking the fault result of the target historical data as a model output characteristic.
As shown in fig. 4, an embodiment of the present application further provides a computer device, including: a memory 401 and one or more processors 402; the memory 401 is used for storing one or more programs; when executed by the one or more processors 402, cause the one or more processors to implement the intelligent cable warning method based on operational data as described herein.
Embodiments of the present application further provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform the intelligent cable warning method based on operating data provided by the above embodiments, where the intelligent cable warning method based on operating data includes: receiving operation data acquired through a first data acquisition cluster, wherein the operation data comprises time information and a line number corresponding to an intelligent cable; storing operation data as historical data, inputting the operation data into a pre-trained operation data early warning model, and acquiring an early warning result output by the operation data early warning model; when the early warning result is a fault, receiving physical data acquired by the second data acquisition cluster; and judging whether the early warning result is correct or not according to the physical data, issuing alarm information when the early warning result is correct, and giving up the early warning result when the early warning result is wrong.
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 media" may include two or more storage media that may reside in different locations, such as in different computer systems that are 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 provided in the embodiments of the present application contains computer-executable instructions, and the computer-executable instructions are not limited to the above-mentioned intelligent cable warning method based on operation data, and may also perform related operations in the intelligent cable warning method based on operation data provided in any embodiments of the present application.
The intelligent cable early warning device, the equipment and the storage medium based on the operation data provided in the above embodiments may execute the intelligent cable early warning method based on the operation data provided in any embodiment of the present application, and reference may be made to the intelligent cable early warning method based on the operation data provided in any embodiment of the present application without detailed technical details described in the above embodiments.
The foregoing is considered as illustrative only of the preferred embodiments of the invention and the principles of the technology 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 (9)
1. An intelligent cable early warning system based on operating data is characterized by comprising a first data acquisition cluster, a second data acquisition cluster, an intelligent early warning server, a data storage and an intelligent analysis server; the first data acquisition cluster, the data storage and the intelligent analysis server are all connected with the intelligent early warning server, and the data storage is respectively connected with the second data acquisition cluster and the intelligent analysis server;
the first data acquisition cluster is used for acquiring operation data of the intelligent cable and uploading the operation data to the intelligent early warning server, and the operation data comprises time information and a line number corresponding to the intelligent cable;
the second data acquisition cluster is used for acquiring physical data of the intelligent cable and transmitting the physical data to the data storage device for storage; the physical data comprises time information and a line number corresponding to the intelligent cable;
the intelligent early warning server comprises a data management module and a data early warning module, wherein the data management module is used for receiving operation data uploaded by a first data acquisition cluster, and storing the operation data, corresponding time information and a line number of an intelligent cable in a data storage as historical data; the data early warning module is provided with a pre-trained operation data early warning model and is used for inputting operation data into the operation data early warning model, acquiring a corresponding early warning result output by the operation data early warning model and sending the early warning result to the intelligent analysis server;
the intelligent analysis server is used for receiving the early warning result, reading corresponding physical data when the early warning result is a fault, judging whether the early warning result is correct according to the physical data, and issuing warning information when the early warning result is correct; when the early warning result is wrong, giving up the early warning result;
the physical data includes any one or more of smart cable image data, user evaluation data, surface defect monitoring data.
2. The intelligent cable early warning system of claim 1, wherein the first data collection cluster comprises first monitoring modules corresponding to the intelligent cables and first gateways, and the first gateways are connected with the first monitoring modules and used for summarizing operation data uploaded by the first monitoring modules and uploading the operation data to the intelligent early warning server.
3. The intelligent cable early warning system of claim 1 or 2, wherein the second data collection cluster comprises second monitoring modules corresponding to the intelligent cables and second gateways, and the second gateways are connected with the second monitoring modules and used for summarizing the operation data uploaded by the second monitoring modules and uploading the operation data to the data storage.
4. An intelligent cable early warning method based on operation data is characterized by comprising the following steps:
receiving operation data acquired through a first data acquisition cluster, wherein the operation data comprises time information and a line number corresponding to an intelligent cable;
storing the operation data as historical data, inputting the operation data into a pre-trained operation data early warning model, and acquiring an early warning result output by the operation data early warning model;
when the early warning result is a fault, receiving physical data acquired by a second data acquisition cluster;
judging whether the early warning result is correct or not according to the physical data, and issuing alarm information when the early warning result is correct; when the early warning result is wrong, giving up the early warning result;
the physical data includes any one or more of smart cable image data, user evaluation data, surface defect monitoring data.
5. The intelligent cable early warning method as claimed in claim 4, wherein the determining whether the early warning result is correct according to the physical data comprises:
detecting whether the physical data contain user evaluation data and/or surface defect monitoring data, when the physical data contain the user evaluation data, obtaining the evaluation content of the user evaluation data, and comparing whether the evaluation content is consistent with the early warning result; when the surface defect monitoring data is contained, defining the early warning result to be correct;
and when the physical data does not contain user evaluation data and surface defect monitoring data, comparing the intelligent cable image data with preset reference image data to determine whether the intelligent cable image data is consistent with the preset reference image data.
6. A smart cable pre-warning method as claimed in claim 4 or 5, wherein the operational data pre-warning model is trained by:
selecting historical data corresponding to the fault result as a fault from a plurality of groups of historical data as target historical data;
acquiring historical data of a last acquisition time point adjacent to an acquisition time point of the target historical data;
and performing operation data early warning model training by taking the historical data of the last acquisition time point as a model input characteristic and taking a fault result of the target historical data as a model output characteristic.
7. The utility model provides an intelligence cable early warning device based on operational data which characterized in that includes:
a first data module: the intelligent cable management system is used for receiving operation data acquired by a first data acquisition cluster, wherein the operation data comprises time information and a line number corresponding to an intelligent cable;
the early warning output module: the operation data are stored as historical data and input to a pre-trained operation data early warning model, and an early warning result output by the operation data early warning model is obtained;
a second data module: the early warning device is used for receiving physical data acquired by the second data acquisition cluster when the early warning result is a fault;
a result determination module: the early warning device is used for judging whether the early warning result is correct or not according to the physical data and issuing warning information when the early warning result is correct; when the early warning result is wrong, giving up the early warning result;
the physical data includes any one or more of smart cable image data, user evaluation data, surface defect monitoring data.
8. A computer device, comprising: a memory and one or more processors;
the memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the intelligent cable warning method based on operational data as recited in any of claims 4-6.
9. A storage medium containing computer-executable instructions for performing the intelligent cable warning method based on operational data according to any one of claims 4 to 6 when executed by a computer processor.
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| CN106771806A (en) * | 2016-12-13 | 2017-05-31 | 国网山东省电力公司电力科学研究院 | A kind of Voltage for Insulators on HV Lines surface filth state remote viewing method of telemetering and system |
| CN108879798B (en) * | 2018-07-04 | 2021-07-02 | 广东电网有限责任公司 | Over-current control method, system, equipment and medium for preventing error based on mutation |
| CN110716102A (en) * | 2019-09-10 | 2020-01-21 | 广州供电局有限公司 | High-voltage cable external-damage-prevention monitoring and early-warning method and monitoring and early-warning system |
| CN110875851B (en) * | 2019-10-25 | 2022-04-19 | 袁茂银 | Underground cable fault early warning method and device |
| CN111353911A (en) * | 2020-04-28 | 2020-06-30 | 深圳力维智联技术有限公司 | Power equipment operation and maintenance method, system, equipment and storage medium |
| CN112036610A (en) * | 2020-08-11 | 2020-12-04 | 广州番禺电缆集团有限公司 | Intelligent cable early warning platform and early warning method based on big data analysis |
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