CN116008724A - Overhead line monitoring method and device - Google Patents
Overhead line monitoring method and device Download PDFInfo
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- CN116008724A CN116008724A CN202211620502.5A CN202211620502A CN116008724A CN 116008724 A CN116008724 A CN 116008724A CN 202211620502 A CN202211620502 A CN 202211620502A CN 116008724 A CN116008724 A CN 116008724A
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
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Abstract
The invention discloses a method and a device for monitoring an overhead line, wherein the method comprises the following steps: according to a preset period, acquiring field picture information of the overhead line and operation information and tree barrier early warning information of an overhead line monitoring system, judging whether data in the operation information is out of limit or has obvious data errors, if not, judging whether the operation information is abnormal, if so, judging whether the difference between the distance data of the overhead line and the tree in the field picture information and the tree barrier confidence result data and a preset abnormal threshold value is larger than the preset comparison threshold value, if not, judging that the tree barrier early warning information is not abnormal, if so, judging that the tree barrier early warning information is abnormal, and acquiring and operating an operation and maintenance scheme corresponding to the abnormal data from a preset operation and maintenance database. The technical problem that the normal power supply of the power distribution network is seriously affected due to frequent occurrence of the tree obstacle problem of the overhead line of the power distribution network is solved, and the power supply reliability of the power distribution network is improved.
Description
Technical Field
The invention relates to the technical field of operation management of power distribution networks, in particular to a method and a device for monitoring an overhead line.
Background
With the development of society, the electricity demand of each area is increased to different degrees, and a distribution circuit is used as a medium for electric energy transmission and is the basis for stable operation of a power grid. The power distribution network overhead line has the characteristics of wide points and multiple faces and various operating environments, and the operation and maintenance capacities of power grid companies are tested at any time. In mountain areas, the power supply reliability is seriously affected due to frequent occurrence of tree barriers of overhead lines of power distribution networks, and the problem of pain points in operation and maintenance work of the power grid is solved.
The problem of overhead line tree obstacle is avoided, and early prevention is critical. However, the conventional manual inspection mode is still adopted for inspecting the tree obstacle hidden trouble of the overhead line of the power distribution network, if inspection in urban areas can be completed under the condition of spending a certain time, if the inspection is performed in hilly and mountainous areas, the operation and maintenance working pressure is quite high, and even a great deal of manpower and time are spent, so that unexpected operation and maintenance effects are achieved. Therefore, to prevent the problem of the tree obstacle of the overhead line of the power distribution network, an intelligent means is needed.
Therefore, in order to improve the power supply reliability of the power distribution network, the technical problem that the normal power supply of the power distribution network is seriously affected by the frequent occurrence of the tree obstacle problem of the overhead line of the power distribution network at present is solved, and a monitoring method of the overhead line is needed to be constructed.
Disclosure of Invention
The invention provides a method and a device for monitoring an overhead line, which solve the problem that the normal power supply of a power distribution network is seriously affected by frequent occurrence of tree barriers of the overhead line of the power distribution network at present.
In a first aspect, the present invention provides a method for monitoring an overhead line, including:
step S1, acquiring field picture information of an overhead line, operation information of an overhead line monitoring system and tree obstacle early warning information according to a preset period;
step S2, judging whether the data in the operation information has the condition of out-of-limit or obvious data error; if not, determining that the running information is not abnormal, and executing a step S3; if yes, determining that the operation information is abnormal, and executing a step S6;
step S3, judging whether the difference between the distance data of the overhead line and the tree in the field picture information and a preset distance threshold value is larger than a preset first threshold value; if not, executing the step S4; if yes, determining that the tree barrier early warning information is abnormal, and executing a step S6;
step S4, calculating to obtain the tree barrier confidence result data based on the multi-type tree barrier picture data in the field picture information;
step S5, judging whether the difference between the tree barrier confidence result data and a preset matching threshold is larger than a preset second threshold; if not, determining that the tree obstacle early warning information is abnormal, and returning to the step S1; if yes, determining that the tree barrier early warning information is abnormal, and executing a step S6;
and S6, acquiring and operating an operation and maintenance scheme corresponding to the abnormal operation information and/or tree obstacle early warning information from a preset operation and maintenance database.
Optionally, the step S4 includes:
step S41, a preliminary tree barrier confidence calculation model is established according to the multi-type tree barrier picture data;
step S42, training and verifying the preliminary tree obstacle confidence calculation model based on the multi-type tree obstacle picture data to obtain the tree obstacle confidence calculation model;
and step S43, inputting the multi-type tree barrier picture data into the tree barrier confidence coefficient calculation model, and calculating to obtain the tree barrier confidence coefficient result data.
Optionally, the step S42 includes:
step S421, dividing the multi-type tree barrier picture data into training data and verification data;
step S422, training the preliminary tree-obstacle confidence calculation model based on the training data, to obtain a trained preliminary tree-obstacle confidence calculation model;
step S423, based on the verification data, verifying the trained preliminary tree barrier confidence calculation model to obtain the tree barrier confidence calculation model.
Optionally, the step S422 includes:
step S4221, inputting the training data into the preliminary tree obstacle confidence calculation model to obtain corresponding tree obstacle confidence prediction result data;
step S4222, determining training errors according to the data labels corresponding to the training data and the tree barrier confidence prediction result data;
step S4223, based on the training error, adjusting the preliminary tree-barrier confidence calculation model to obtain optimal parameters, and optimizing the preliminary tree-barrier confidence calculation model by adopting the optimal parameters to obtain the trained preliminary tree-barrier confidence calculation model.
Optionally, after the step S6, the method further includes:
and sending the abnormal operation information and/or tree obstacle early warning information and the operation and maintenance scheme to corresponding operation and maintenance personnel.
In a second aspect, the present invention provides an overhead line monitoring device, comprising:
the acquisition module is used for acquiring the field picture information of the overhead line, the operation information of the overhead line monitoring system and the tree obstacle early warning information according to a preset period;
the first judging module is used for judging whether the data in the operation information has the condition of out-of-limit or obvious data errors or not; if not, determining that the running information is not abnormal, and executing a second judging module; if yes, determining that the operation information is abnormal, and executing an operation and maintenance module;
the second judging module is used for judging whether the difference between the distance data of the overhead line and the tree in the field picture information and the preset distance threshold value is larger than a preset first threshold value or not; if not, executing a calculation module; if yes, determining that the tree barrier early warning information is abnormal, and executing an operation and maintenance module;
the calculation module is used for calculating and obtaining the tree barrier confidence result data based on the multi-type tree barrier picture data in the field picture information;
the third judging module is used for judging whether the difference between the tree barrier confidence coefficient result data and a preset matching threshold value is larger than a preset second threshold value or not; if not, determining that the tree obstacle early warning information is abnormal, and returning to the acquisition module; if yes, determining that the tree barrier early warning information is abnormal, and executing an operation and maintenance module;
and the operation and maintenance module is used for acquiring and operating an operation and maintenance scheme corresponding to the abnormal operation information and/or tree obstacle early warning information from a preset operation and maintenance database.
Optionally, the computing module includes:
the establishing sub-module is used for establishing a preliminary tree barrier confidence calculation model according to the multi-type tree barrier picture data;
the training sub-module is used for training and verifying the preliminary tree obstacle confidence calculation model based on the multi-type tree obstacle picture data to obtain the tree obstacle confidence calculation model;
and the calculation sub-module is used for inputting the multi-type tree barrier picture data into the tree barrier confidence calculation model, and calculating to obtain the tree barrier confidence result data.
Optionally, the training submodule includes:
the dividing unit is used for dividing the multi-type tree barrier picture data into training data and verification data;
the training unit is used for training the preliminary tree obstacle confidence calculation model based on the training data to obtain a trained preliminary tree obstacle confidence calculation model;
and the verification unit is used for verifying the trained preliminary tree barrier confidence calculation model based on the verification data to obtain the tree barrier confidence calculation model.
Optionally, the training unit includes:
the prediction subunit is used for inputting the training data into the preliminary tree obstacle confidence calculation model to obtain corresponding tree obstacle confidence prediction result data;
the error subunit is used for determining training errors according to the data labels corresponding to the training data and the tree obstacle confidence prediction result data;
and the optimization subunit is used for adjusting the preliminary tree-obstacle confidence coefficient calculation model based on the training error to obtain optimal parameters, and optimizing the preliminary tree-obstacle confidence coefficient calculation model by adopting the optimal parameters to obtain the trained preliminary tree-obstacle confidence coefficient calculation model.
Optionally, the apparatus further comprises:
and the sending module is used for sending the abnormal operation information and/or tree obstacle early warning information and the operation and maintenance scheme to corresponding operation and maintenance personnel.
From the above technical scheme, the invention has the following advantages: the invention provides a method for monitoring an overhead line, which comprises the steps of obtaining field picture information of the overhead line and operation information and tree barrier early warning information of an overhead line monitoring system according to a preset period through a step S1, judging whether the situation of out-of-limit or obvious data errors occurs in data in the operation information or not through a step S2, if not, determining that the operation information is abnormal, executing the step S3, if yes, determining that the operation information is abnormal, executing the step S6, judging whether the difference between the distance data of the overhead line and a tree in the field picture information and a preset distance threshold is larger than a preset first threshold, if not, executing the step S4, determining that the tree barrier early warning information is abnormal, executing the step S6, calculating to obtain tree barrier confidence result data based on the multi-type tree barrier picture data in the field picture information, and judging whether the difference between the tree barrier confidence result data and the preset matching threshold is larger than a preset second threshold or not, if not, determining that the tree barrier does not exist in the field picture information, returning the tree barrier information to the step S6, and carrying out the pre-warning information to the power distribution network is corresponding to the step S6, and the problem that the tree barrier is normal operation information exists is detected, and the power distribution network is normally occurs, and the problem is solved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained from these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a flowchart illustrating a first embodiment of a method for monitoring an overhead line according to the present invention;
fig. 2 is a flowchart illustrating a second embodiment of a method for monitoring an overhead line according to the present invention;
fig. 3 is a block diagram of an overhead line monitoring system of the present invention;
fig. 4 is a block diagram of an embodiment of an overhead line monitoring device of the present invention.
Detailed Description
The embodiment of the invention provides a method and a device for monitoring an overhead line, which are used for solving the problem that the normal power supply of a power distribution network is seriously affected by frequent occurrence of the problem of tree barriers of the overhead line of the power distribution network at present.
In order to make the objects, features and advantages of the present invention more comprehensible, the technical solutions in the embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, fig. 1 is a flowchart of a first embodiment of a method for monitoring an overhead line according to the present invention, including:
step S101, acquiring field picture information of an overhead line, operation information of an overhead line monitoring system and tree obstacle early warning information according to a preset period;
step S102, judging whether the data in the operation information has the condition of out-of-limit or obvious data error; if not, determining that the operation information is not abnormal, and executing step S103; if yes, determining that the operation information is abnormal, and executing step S106;
step S103, judging whether the difference between the distance data of the overhead line and the tree in the field picture information and a preset distance threshold value is larger than a preset first threshold value; if not, executing step S104; if yes, determining that the tree barrier early warning information is abnormal, and executing step S106;
step S104, calculating to obtain the tree barrier confidence result data based on the multi-type tree barrier picture data in the field picture information;
in the embodiment of the invention, a preliminary tree barrier confidence coefficient calculation model is established according to the multi-type tree barrier picture data, the preliminary tree barrier confidence coefficient calculation model is trained and verified based on the multi-type tree barrier picture data to obtain the tree barrier confidence coefficient calculation model, the multi-type tree barrier picture data is input into the tree barrier confidence coefficient calculation model, and the tree barrier confidence coefficient result data is obtained through calculation.
Step S105, judging whether the difference between the tree barrier confidence result data and a preset matching threshold is larger than a preset second threshold; if not, determining that the tree obstacle early warning information is abnormal, and returning to the step S101; if yes, determining that the tree barrier early warning information is abnormal, and executing step S106;
step S106, acquiring and operating an operation and maintenance scheme corresponding to abnormal operation information and/or tree obstacle early warning information from a preset operation and maintenance database;
in the embodiment of the invention, an operation and maintenance scheme corresponding to abnormal operation information and/or tree obstacle early warning information is acquired and operated from a preset operation and maintenance database, and the abnormal operation information and/or tree obstacle early warning information and the operation and maintenance scheme are sent to corresponding operation and maintenance personnel.
According to the method for monitoring the overhead line, provided by the embodiment of the invention, through the step S1, the on-site picture information of the overhead line and the operation information and tree barrier early warning information of an overhead line monitoring system are obtained according to a preset period, the step S102 is used for judging whether the situation of out-of-limit or obvious data errors occurs in the data in the operation information, if not, whether the operation information is abnormal or not is determined, the step S103 is executed, if yes, the operation information is determined to be abnormal, the step S106 is executed, the step S103 is executed, whether the difference between the distance data between the overhead line and a tree in the on-site picture information and the preset distance threshold is larger than the preset first threshold is judged, if not, the step S104 is executed, the abnormality of the tree barrier early warning information is determined, the step S106 is executed, the step S104 is executed, the tree barrier reliability result data is calculated and is obtained, and if the difference between the tree barrier reliability result data and the preset matching threshold is larger than the preset second threshold is not calculated, and if not, the abnormality of the tree barrier information is determined to exist in the on-site picture information, the power distribution network is not normally, the power distribution network is normally run, the problem is solved, and the problem of the power distribution network is normally is solved, and the power supply is normally occurs due to the tree barrier is normally, and the power distribution network is normally run, and the problem is normally is solved, and the problem is obtained.
Referring to fig. 2, fig. 2 is a flow chart of a method for monitoring an overhead line according to the present invention, including:
step S201, acquiring field picture information of an overhead line, operation information of an overhead line monitoring system and tree obstacle early warning information according to a preset period;
in the embodiment of the invention, the operation information and the tree obstacle early warning information of the monitoring system are collected once according to the period of 30 minutes, and the field picture information of the overhead line is obtained every 30 minutes through the camera.
In a specific implementation, referring to fig. 3, fig. 3 is an overhead line monitoring system according to the present invention, where 301 is a camera module, 302 is a collecting module, 303 is a monitoring module, and 304 is a system background; the camera module 301, the collecting module 302, the monitoring module 303 and the system background 304 are connected with each other;
the camera module 301 is configured to obtain, according to a preset period, field picture information of the overhead line through a camera, and obtain operation information and tree obstacle early warning information of the overhead line monitoring system;
the aggregation module 302 is configured to store the field picture information, the operation information, and the tree obstacle early warning information;
the monitoring module 303 is configured to determine, based on the field picture information, whether the operation information and the tree barrier early warning information are abnormal;
the system background 304 is configured to generate a corresponding operation and maintenance scheme when the operation information and/or the tree barrier early warning information are abnormal.
Specifically, the camera module 301 includes a camera sub-module and an acquisition sub-module that are connected to each other;
the camera sub-module is used for acquiring the field picture information of the overhead line through a camera according to the preset period;
and the acquisition sub-module is used for acquiring the operation information and the tree obstacle early warning information of the overhead line monitoring system according to the preset period.
Specifically, the aggregation module 302 includes a control sub-module, and a power sub-module, a first storage sub-module, and a first communication sub-module that are respectively connected with the control sub-module;
the control submodule is used for controlling the aggregation module 302;
the power supply sub-module is configured to supply power to the aggregation module 302;
the first storage sub-module is used for storing the field picture information, the operation information and the tree obstacle early warning information;
the first communication sub-module is configured to communicate with the monitoring module 303 and the system background 304.
Specifically, the pooling module 302 further includes a data interface and pooling shell located at the periphery of the pooling module 302;
the data interface is configured to connect the aggregation module 302 with the camera module 301;
the collection housing is used to protect the collection module 302.
Specifically, the power supply submodule comprises a photovoltaic power generation submodule, a power management submodule and a standby power supply which are connected in sequence
The photovoltaic power generation unit is used for collecting solar energy and converting the solar energy into electric energy;
the power supply unit is configured to preferentially provide the electric energy obtained by the photovoltaic power generation unit for the collecting module 302;
the backup power source is configured to provide backup power to the aggregation module 302.
Specifically, the first communication submodule is specifically a 4G wireless communication chip and a low-power wireless LoRa communication chip.
Specifically, the monitoring module 303 includes a ranging sub-module, a determining sub-module, an alarm sub-module, a second storage sub-module, and a second communication sub-module that are connected to each other;
the distance measuring sub-module is used for acquiring distance information of the overhead line and the tree in the field picture information;
the determining submodule is used for determining whether the operation information and the tree obstacle early warning information are abnormal or not based on the on-site picture information and the distance information;
the alarm sub-module is used for sending out corresponding alarm signals when the operation information and/or the tree barrier early warning information are abnormal;
the second storage sub-module is used for storing the field picture information, the distance information, the operation information and the tree obstacle early warning information;
the second communication sub-module is used for communicating with the aggregation module and the system background.
Specifically, the monitoring module 303 further includes a micro control sub-module and a capacitor sub-module that are connected to each other, and a monitoring housing and a self-taking electronic module that are located at the periphery of the monitoring module 303;
the micro control sub-module is used for controlling the monitoring module 303;
the super capacitor is configured to supply power to the monitoring module 303;
the self-taking electronic module is configured to supply power to the monitoring module 303.
Specifically, the determining submodule comprises an operation unit and an early warning unit which are connected with each other;
the operation unit is used for determining that the operation information is abnormal when the data in the operation information is out of limit or has obvious data errors;
the early warning unit is used for determining whether the tree obstacle early warning information is abnormal or not based on the on-site picture information and the distance information.
Specifically, the early warning unit comprises a distance subunit and a matching subunit which are connected with each other;
the distance subunit is used for determining that the tree obstacle early warning information is abnormal when the difference between the distance value in the distance information and the preset distance threshold value is larger than a preset first threshold value;
the matching subunit is configured to determine that the tree barrier early warning information is abnormal when a difference between the tree barrier confidence result data calculated based on the multi-type tree barrier picture data in the field picture information and a preset matching threshold is greater than a preset second threshold.
Step S202, judging whether the data in the operation information has the condition of out-of-limit or obvious data error; if not, determining that the operation information is not abnormal, and executing step S203; if yes, determining that the operation information is abnormal, and executing step S208;
in the embodiment of the invention, whether the operation information of the overhead line monitoring system is abnormal is judged by judging whether the operation information such as current, voltage, battery electric quantity and temperature is out of limit or has obvious data errors.
Step S203, judging whether the difference between the distance data of the overhead line and the tree in the field picture information and a preset distance threshold value is larger than a preset first threshold value; if not, executing step S204; if yes, determining that the tree barrier early warning information is abnormal, and executing step S208;
in the embodiment of the invention, the distance between the overhead line and the tree barrier data in the picture information is measured by means of the distance measuring module, the distance is compared with the preset distance threshold value, and if the difference between the distance value and the preset distance threshold value is larger than the preset first threshold value, the tree barrier early warning information is determined to be abnormal.
Step S204, a preliminary tree barrier confidence calculation model is established according to the multi-type tree barrier picture data;
step S205, training and verifying the preliminary tree obstacle confidence calculation model based on the multi-type tree obstacle picture data to obtain a tree obstacle confidence calculation model;
in an alternative embodiment, the step S205 includes:
step S2051, dividing the multi-type tree barrier picture data into training data and verification data;
step S2052, inputting the training data into the preliminary tree obstacle confidence calculation model to obtain corresponding tree obstacle confidence prediction result data;
step S2053, determining a training error according to the data label corresponding to the training data and the tree barrier confidence prediction result data;
step S2054, based on the training error, adjusting the preliminary tree-barrier confidence calculation model to obtain optimal parameters, and optimizing the preliminary tree-barrier confidence calculation model by adopting the optimal parameters to obtain a trained preliminary tree-barrier confidence calculation model;
step S2055, based on the verification data, verifies the trained preliminary tree barrier confidence calculation model to obtain the tree barrier confidence calculation model.
In the embodiment of the invention, the multi-type tree barrier picture data are divided into training data and verification data, the training data are input into the preliminary tree barrier confidence calculation model to obtain corresponding tree barrier confidence prediction result data, training errors are determined according to data labels corresponding to the training data and the tree barrier confidence prediction result data, the preliminary tree barrier confidence calculation model is adjusted based on the training errors to obtain optimal parameters, the optimal parameters are adopted to optimize the preliminary tree barrier confidence calculation model to obtain a trained preliminary tree barrier confidence calculation model, and the trained preliminary tree barrier confidence calculation model is verified based on the verification data to obtain the tree barrier confidence calculation model.
In specific implementation, by means of an image recognition technology, a preliminary tree barrier confidence coefficient calculation model is established according to the multi-type tree barrier picture data, the preliminary tree barrier confidence coefficient calculation model is trained and verified to obtain a tree barrier confidence coefficient calculation model, the multi-type tree barrier picture data are input into the tree barrier confidence coefficient calculation model, tree barrier confidence coefficient result data are obtained through calculation, the tree barrier confidence coefficient result data are compared with a preset matching threshold value, and if the difference between the tree barrier confidence coefficient result and the preset matching threshold value is larger than a preset second threshold value, abnormality of tree barrier early warning information is determined.
Step S206, inputting the multi-type tree barrier picture data into the tree barrier confidence calculation model, and calculating to obtain tree barrier confidence result data;
step S207, judging whether the difference between the tree barrier confidence result data and a preset matching threshold is larger than a preset second threshold; if not, determining that the tree obstacle early warning information is abnormal, and returning to the step S201; if yes, determining that the tree barrier early warning information is abnormal, and executing step S208;
in the embodiment of the invention, the tree barrier confidence result data is compared with a preset matching threshold, when the difference between the tree barrier confidence result and the preset matching threshold is larger than a preset second threshold, the tree barrier early warning information is determined to be abnormal, and when the difference between the tree barrier confidence result and the preset matching threshold is smaller than or equal to the preset second threshold, the tree barrier early warning information is determined to be not abnormal, and the step S201 is returned.
Step S208, acquiring and operating an operation and maintenance scheme corresponding to abnormal operation information and/or tree obstacle early warning information from a preset operation and maintenance database;
in an alternative embodiment, after the step S208, the method further includes:
and sending the abnormal operation information and/or tree obstacle early warning information and the operation and maintenance scheme to corresponding operation and maintenance personnel.
According to the embodiment of the invention, according to the actual information abnormality problem, an operation and maintenance scheme corresponding to abnormal operation information and/or tree obstacle early warning information is extracted from a preset operation and maintenance database, the operation and maintenance are carried out on the overhead line, and then the abnormal operation information and/or tree obstacle early warning information and the operation and maintenance scheme are sent to corresponding operation and maintenance personnel.
Wherein, the preset operation and maintenance database stores: the method comprises the following steps of an operation and maintenance scheme aiming at obvious abnormality of data in operation information, an operation and maintenance scheme aiming at the condition that the data in the operation information exceeds the upper limit and the lower limit, an operation and maintenance scheme aiming at huge deviation of the distance between an overhead line and a tree, an operation and maintenance scheme aiming at huge deviation of the tree barrier confidence calculated based on multi-type tree barrier picture data and the like.
The specific operation and maintenance scheme comprises the following steps: the method comprises the steps of obtaining a transformer substation name, a 10kV line name, operation and maintenance point line tower numbers, operation information of an overhead line monitoring system, tree obstacle early warning information, operation and maintenance personnel information and operation and maintenance content, notifying relevant operation and maintenance personnel, carrying out operation and maintenance according to the obtained information by the relevant operation and maintenance personnel, adjusting the operation information of the overhead line monitoring system if the operation information of the overhead line monitoring system is abnormal, eliminating the actual operation abnormal problem of the overhead line monitoring system, and eliminating the tree obstacle problem nearby the overhead line corresponding to the abnormal tree obstacle early warning information if the tree obstacle early warning information is abnormal.
The transformer substation name, the 10kV line name and the operation and maintenance point line tower number can be obtained from the installation position of the overhead line monitoring system, the operation information of the overhead line monitoring system comprises information such as current, voltage, battery power, temperature and the like, the tree obstacle early warning information comprises radar ranging distance, tree obstacle pictures and tree obstacle confidence coefficient results, the operation and maintenance personnel information comprises power supply office names, functions and mobile phone numbers, and the operation and maintenance content comprises the operation abnormality problems existing in the monitoring system and the tree obstacle problems nearby the monitoring system.
According to the method for monitoring the overhead line, provided by the embodiment of the invention, through the step S1, the on-site picture information of the overhead line and the operation information and tree barrier early warning information of an overhead line monitoring system are obtained according to a preset period, the step S2 is used for judging whether the situation of out-of-limit or obvious data errors occurs in the data in the operation information, if not, whether the operation information is abnormal or not is determined, the step S3 is executed, if yes, the operation information is determined to be abnormal, the step S6 is executed, the step S3 is executed, whether the difference between the distance data between the overhead line and a tree and a preset distance threshold in the on-site picture information is larger than a preset first threshold is judged, if not, the step S4 is executed, the abnormality of the tree barrier early warning information is determined, the step S6 is executed, the step S4 is executed, the tree barrier reliability result data is calculated and is obtained based on the multiple types of tree barrier picture data in the on the basis of the on-site picture information, if not, the difference between the tree barrier reliability result data and the preset matching threshold is larger than a preset second threshold is determined, if not, and the abnormality of the tree barrier information is determined to exist, the power distribution network is not corresponding to the step S6, the problem of the power distribution network is normally occurs, and the power distribution network is normally occurs, or the power supply has been normally occurs due to the tree barrier information, or the abnormality is not has been determined, and the problem is normally occurs in the power distribution network is normally has been met, and the tree barrier has the problem is normally has been met.
Referring to fig. 4, fig. 4 is a block diagram of an overhead line monitoring device according to an embodiment of the present invention, including:
the acquisition module 401 is configured to acquire field picture information of the overhead line, and operation information and tree obstacle early warning information of the overhead line monitoring system according to a preset period;
a first judging module 402, configured to judge whether an out-of-limit or obvious data error condition occurs in the data in the operation information; if not, determining that the operation information is not abnormal, and executing a second judging module 403; if yes, determining that the operation information is abnormal, and executing an operation maintenance module 406;
a second judging module 403, configured to judge whether a difference between the distance data of the overhead line and the tree in the field picture information and a preset distance threshold is greater than a preset first threshold; if not, executing the calculation module 404; if yes, determining that the tree barrier early warning information is abnormal, and executing an operation and maintenance module 406;
a calculation module 404, configured to calculate the tree barrier confidence result data based on the multi-type tree barrier picture data in the field picture information;
the third judging module is used for judging whether the difference between the tree barrier confidence coefficient result data and a preset matching threshold value is larger than a preset second threshold value or not; if not, determining that the tree barrier early warning information is not abnormal, and returning to the acquisition module 401; if yes, determining that the tree barrier early warning information is abnormal, and executing an operation and maintenance module 406;
and the operation and maintenance module 406 is configured to obtain and operate an operation and maintenance scheme corresponding to the abnormal operation information and/or the tree obstacle early warning information from a preset operation and maintenance database.
In an alternative embodiment, the computing module 404 includes:
the establishing sub-module is used for establishing a preliminary tree barrier confidence calculation model according to the multi-type tree barrier picture data;
the training sub-module is used for training and verifying the preliminary tree obstacle confidence calculation model based on the multi-type tree obstacle picture data to obtain the tree obstacle confidence calculation model;
and the calculation sub-module is used for inputting the multi-type tree barrier picture data into the tree barrier confidence calculation model, and calculating to obtain the tree barrier confidence result data.
In an alternative embodiment, the training submodule includes:
the dividing unit is used for dividing the multi-type tree barrier picture data into training data and verification data;
the training unit is used for training the preliminary tree obstacle confidence calculation model based on the training data to obtain a trained preliminary tree obstacle confidence calculation model;
and the verification unit is used for verifying the trained preliminary tree barrier confidence calculation model based on the verification data to obtain the tree barrier confidence calculation model.
In an alternative embodiment, the training unit comprises:
the prediction subunit is used for inputting the training data into the preliminary tree obstacle confidence calculation model to obtain corresponding tree obstacle confidence prediction result data;
the error subunit is used for determining training errors according to the data labels corresponding to the training data and the tree obstacle confidence prediction result data;
and the optimization subunit is used for adjusting the preliminary tree-obstacle confidence coefficient calculation model based on the training error to obtain optimal parameters, and optimizing the preliminary tree-obstacle confidence coefficient calculation model by adopting the optimal parameters to obtain the trained preliminary tree-obstacle confidence coefficient calculation model.
In an alternative embodiment, the apparatus further comprises:
and the sending module is used for sending the abnormal operation information and/or tree obstacle early warning information and the operation and maintenance scheme to corresponding operation and maintenance personnel.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the embodiments provided in the present application, it should be understood that the methods and apparatuses disclosed in the present application may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a readable storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned readable storage medium includes: a usb disk, a removable hard disk, a Read-only memory (ROM), a random access memory (RAM, randomAccessMemory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method of monitoring an overhead line, comprising:
step S1, acquiring field picture information of an overhead line, operation information of an overhead line monitoring system and tree obstacle early warning information according to a preset period;
step S2, judging whether the data in the operation information has the condition of out-of-limit or obvious data error; if not, determining that the running information is not abnormal, and executing a step S3; if yes, determining that the operation information is abnormal, and executing a step S6;
step S3, judging whether the difference between the distance data of the overhead line and the tree in the field picture information and a preset distance threshold value is larger than a preset first threshold value; if not, executing the step S4; if yes, determining that the tree barrier early warning information is abnormal, and executing a step S6;
step S4, calculating to obtain the tree barrier confidence result data based on the multi-type tree barrier picture data in the field picture information;
step S5, judging whether the difference between the tree barrier confidence result data and a preset matching threshold is larger than a preset second threshold; if not, determining that the tree obstacle early warning information is abnormal, and returning to the step S1; if yes, determining that the tree barrier early warning information is abnormal, and executing a step S6;
and S6, acquiring and operating an operation and maintenance scheme corresponding to the abnormal operation information and/or tree obstacle early warning information from a preset operation and maintenance database.
2. The method for monitoring an overhead line according to claim 1, wherein the step S4 comprises:
step S41, a preliminary tree barrier confidence calculation model is established according to the multi-type tree barrier picture data;
step S42, training and verifying the preliminary tree obstacle confidence calculation model based on the multi-type tree obstacle picture data to obtain the tree obstacle confidence calculation model;
and step S43, inputting the multi-type tree barrier picture data into the tree barrier confidence coefficient calculation model, and calculating to obtain the tree barrier confidence coefficient result data.
3. The method of monitoring an overhead line according to claim 2, wherein the step S42 includes:
step S421, dividing the multi-type tree barrier picture data into training data and verification data;
step S422, training the preliminary tree-obstacle confidence calculation model based on the training data, to obtain a trained preliminary tree-obstacle confidence calculation model;
step S423, based on the verification data, verifying the trained preliminary tree barrier confidence calculation model to obtain the tree barrier confidence calculation model.
4. A method of monitoring an overhead line according to claim 3, wherein step S422 comprises:
step S4221, inputting the training data into the preliminary tree obstacle confidence calculation model to obtain corresponding tree obstacle confidence prediction result data;
step S4222, determining training errors according to the data labels corresponding to the training data and the tree barrier confidence prediction result data;
step S4223, based on the training error, adjusting the preliminary tree-barrier confidence calculation model to obtain optimal parameters, and optimizing the preliminary tree-barrier confidence calculation model by adopting the optimal parameters to obtain the trained preliminary tree-barrier confidence calculation model.
5. The method for monitoring an overhead line according to claim 1, further comprising, after the step S6:
and sending the abnormal operation information and/or tree obstacle early warning information and the operation and maintenance scheme to corresponding operation and maintenance personnel.
6. An overhead line monitoring device, comprising:
the acquisition module is used for acquiring the field picture information of the overhead line, the operation information of the overhead line monitoring system and the tree obstacle early warning information according to a preset period;
the first judging module is used for judging whether the data in the operation information has the condition of out-of-limit or obvious data errors or not; if not, determining that the running information is not abnormal, and executing a second judging module; if yes, determining that the operation information is abnormal, and executing an operation and maintenance module;
the second judging module is used for judging whether the difference between the distance data of the overhead line and the tree in the field picture information and the preset distance threshold value is larger than a preset first threshold value or not; if not, executing a calculation module; if yes, determining that the tree barrier early warning information is abnormal, and executing an operation and maintenance module;
the calculation module is used for calculating and obtaining the tree barrier confidence result data based on the multi-type tree barrier picture data in the field picture information;
the third judging module is used for judging whether the difference between the tree barrier confidence coefficient result data and a preset matching threshold value is larger than a preset second threshold value or not; if not, determining that the tree obstacle early warning information is abnormal, and returning to the acquisition module; if yes, determining that the tree barrier early warning information is abnormal, and executing an operation and maintenance module;
and the operation and maintenance module is used for acquiring and operating an operation and maintenance scheme corresponding to the abnormal operation information and/or tree obstacle early warning information from a preset operation and maintenance database.
7. The overhead line monitoring device of claim 6, wherein the computing module comprises:
the establishing sub-module is used for establishing a preliminary tree barrier confidence calculation model according to the multi-type tree barrier picture data;
the training sub-module is used for training and verifying the preliminary tree obstacle confidence calculation model based on the multi-type tree obstacle picture data to obtain the tree obstacle confidence calculation model;
and the calculation sub-module is used for inputting the multi-type tree barrier picture data into the tree barrier confidence calculation model, and calculating to obtain the tree barrier confidence result data.
8. The overhead line monitoring device of claim 7, wherein the training submodule comprises:
the dividing unit is used for dividing the multi-type tree barrier picture data into training data and verification data;
the training unit is used for training the preliminary tree obstacle confidence calculation model based on the training data to obtain a trained preliminary tree obstacle confidence calculation model;
and the verification unit is used for verifying the trained preliminary tree barrier confidence calculation model based on the verification data to obtain the tree barrier confidence calculation model.
9. The overhead line monitoring device of claim 8, wherein the training unit comprises:
the prediction subunit is used for inputting the training data into the preliminary tree obstacle confidence calculation model to obtain corresponding tree obstacle confidence prediction result data;
the error subunit is used for determining training errors according to the data labels corresponding to the training data and the tree obstacle confidence prediction result data;
and the optimization subunit is used for adjusting the preliminary tree-obstacle confidence coefficient calculation model based on the training error to obtain optimal parameters, and optimizing the preliminary tree-obstacle confidence coefficient calculation model by adopting the optimal parameters to obtain the trained preliminary tree-obstacle confidence coefficient calculation model.
10. The overhead line monitoring device of claim 6, further comprising:
and the sending module is used for sending the abnormal operation information and/or tree obstacle early warning information and the operation and maintenance scheme to corresponding operation and maintenance personnel.
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| CN202211620502.5A CN116008724A (en) | 2022-12-15 | 2022-12-15 | Overhead line monitoring method and device |
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| CN202211620502.5A CN116008724A (en) | 2022-12-15 | 2022-12-15 | Overhead line monitoring method and device |
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