CN111107327A - Insulating equipment abnormity alarm method based on Internet of things - Google Patents
Insulating equipment abnormity alarm method based on Internet of things Download PDFInfo
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- CN111107327A CN111107327A CN202010005263.7A CN202010005263A CN111107327A CN 111107327 A CN111107327 A CN 111107327A CN 202010005263 A CN202010005263 A CN 202010005263A CN 111107327 A CN111107327 A CN 111107327A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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Abstract
The invention relates to an insulating equipment abnormity alarm method based on the Internet of things, which comprises the following steps of S1: establishing an insulation equipment identification model, inputting an image of the insulation equipment, and outputting the image as the state of the insulation equipment; s2: installing a plurality of cameras on a transmission tower, wherein the shooting angles covered by all the cameras cover the insulation equipment at all angles on the transmission tower; s3: the camera collects images of the insulating equipment at regular time, the collected images are identified by the identification model in the step S1, and the state of the insulating equipment is judged; s4: and when the identification result is that the camera is damaged, transmitting the image collected by the camera to a control center. The method can effectively judge whether the insulator is damaged or not, and reduce loss caused by misjudgment.
Description
Technical Field
The invention belongs to the field of fault detection of distribution lines, and particularly relates to an insulating equipment abnormity alarm method based on the Internet of things.
Background
The insulator is one of the main insulating devices in the distribution line, and the main function of the insulator is to firmly support and fix the current-carrying conductor and form good insulation between the current-carrying conductor and the ground. The insulator (commonly called as porcelain bottle) is composed of porcelain part and hardware fitting, the middle part is glued by cement adhesive, the porcelain part ensures that the insulator has good electrical insulation strength, and the hardware fitting is used for fixing the insulator.
The insulator is in flashover or severe discharge, which can cause short circuit of one phase grounding or interphase grounding of the circuit, so that electric arc is generated to burn wires and equipment. When one phase is grounded and short-circuited, the weak part of the phase is broken down possibly, two phases or even three phases are grounded and short-circuited, and a large-area power failure accident is caused. Therefore, when the insulator of the power line of the neutral point insulation system is found to be flashover or severely discharged, the transformer substation, distribution substation operators and electrical facility managers should be notified in time and promptly treated to prevent the expansion of the accident. If the faulty line is directly connected to the system grid. The power supply office's authorities should be notified to assist with the process.
The existing methods for inspecting insulators mainly comprise visual observation, telescope observation, sound judgment and a megohmmeter resistance measurement method during power failure.
1. Visual observation and telescope observation mainly depend on manpower, are limited more during observation, and can not find some damages which are difficult to observe in time.
2. The sound judgment method is limited by the surrounding environment, and it is difficult to estimate the degree of damage, and the experience of the examiner is required to be high.
3. The megameter method is firstly used in power failure, has large limitation, and in addition, needs personnel to carry equipment to ascend for inspection, and may cause certain threat to the safety of the inspection personnel.
The method has higher requirements on manpower, and is not beneficial to saving the labor cost.
Disclosure of Invention
The invention aims to provide an insulating equipment abnormity alarm method based on the Internet of things, which can effectively judge whether an insulator is damaged or not and reduce loss caused by misjudgment.
In order to achieve the above object, the technical solution of the present invention comprises the steps of,
s1: establishing an insulation equipment identification model, inputting an image of the insulation equipment, and outputting the image as the state of the insulation equipment, wherein the state of the insulation equipment comprises normal state and damaged state;
s2: installing a plurality of cameras on a transmission tower, and installing one camera at each position of the insulating equipment; the camera comprises a lamp cap, a track and a camera body, wherein the lamp cap and the camera body are arranged on the track, and the track is arranged on a transmission tower;
s3: the camera collects images of the insulating equipment at regular time, the collected images are identified by the identification model in the step S1, and the state of the insulating equipment is judged;
s4: and when the identification result is that the camera is damaged, transmitting the image collected by the camera to a control center.
Further, the insulation device is an insulator.
Further, when the insulating equipment identification model is established, a database is established firstly, the database comprises states corresponding to the insulating equipment images in different states, and modeling is carried out by training and learning data in the database.
Further, modeling is performed by a deep-learned VGG model.
Further, the database includes images of the insulated equipment in normal and damaged states.
Further, the number of the cameras is more than 1.
Further, in step S3, when the recognition result is normal, the step S3 is repeated.
Further, S5 is also included; s5, the image collected by the camera is checked by the detector through the control center, and then the image is confirmed, and the damaged insulation equipment is repaired or replaced.
Further, in step S4, when the recognition result is that the camera is damaged, the image captured by the camera and the position of the camera are transmitted to the control center.
Furthermore, the camera comprises an acquisition module for acquiring images of the insulating equipment, a positioning module for positioning and a transmission module for storing and transmitting data, and when the identification result is that the camera is damaged, the acquisition module and the positioning module transmit the acquired images and the positioning information to the control center through the transmission module.
The invention has the following positive effects:
1. aiming at the characteristic that the damage of the insulator is not easy to find, the method can effectively judge whether the insulator is damaged or not, and reduce the loss caused by misjudgment.
2. The frequent inspection of inspection personnel is not needed, and manpower and material resources can be effectively saved.
3. The damage degree can be accurately judged, and later maintenance or replacement is facilitated.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In order to better illustrate the invention, the following examples are given by way of further illustration.
Examples
The invention provides an insulating equipment abnormity alarm method based on the Internet of things, which comprises the following steps,
s1: establishing an insulation equipment identification model, inputting an image of the insulation equipment, and outputting the image as the state of the insulation equipment, wherein the state of the insulation equipment comprises a normal state and a damaged state, and the output is normal or damaged; that is to say, the setting of all cameras can guarantee to shoot the insulating equipment of all angles on this transmission tower.
S2: installing a plurality of cameras on a transmission tower, and installing one camera at each position of the insulating equipment; the camera comprises a lamp cap, a track and a camera body, wherein the lamp cap and the camera body are arranged on the track, and the track is arranged on a transmission tower;
s3: the camera collects images of the insulating equipment at regular time, the images can be set at regular time, for example, shooting is carried out at intervals of 10-50min, the collected images are identified by the identification model in the step S1, and the state of the insulating equipment is judged;
s4: when the recognition result is that the insulator is damaged, the image collected by the camera is transmitted to the control center through the wireless network, the control center receives the image collected by the camera and displays the image to the display equipment, and the detection personnel can know the state of the damaged insulator and know the position of the insulator through checking the image in the display equipment.
Preferably, the method is applied to the abnormity warning of insulator equipment, and the insulator equipment is an insulator.
Further, when the insulating equipment identification model is established, a database is established firstly, the database comprises states corresponding to the insulating equipment images in different states, and modeling is carried out by training and learning data in the database.
Further, modeling is performed by a deep-learned VGG model.
Further, the database includes images of the insulated equipment in normal and different damage states. The image reflects appearance information such as the shape, style and characteristics of the insulator.
Further, the number of the cameras is more than 1.
Further, in step S3, when the recognition result is normal, the step S3 is repeated.
Further, S5 is also included; s5, the image collected by the camera is checked by the detector through the control center, and then the image is confirmed, and the damaged insulation equipment is repaired or replaced.
Further, in step S4, when the recognition result is that the camera is damaged, the image captured by the camera and the position of the camera are transmitted to the control center.
Furthermore, the camera comprises an acquisition module for acquiring images of the insulating equipment, a positioning module for positioning and a transmission module for storing and transmitting data, and when the identification result is that the camera is damaged, the acquisition module and the positioning module transmit the acquired images and the positioning information to the control center through the transmission module.
The invention has the advantages that:
1. aiming at the characteristic that the damage of the insulator is not easy to find, the method can effectively judge whether the insulator is damaged or not, and reduce the loss caused by misjudgment.
2. The frequent inspection of inspection personnel is not needed, and manpower and material resources can be effectively saved.
3. The damage degree can be accurately judged, and later maintenance or replacement is facilitated.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. An insulating equipment abnormity alarm method based on the Internet of things is characterized in that: which comprises the following steps of,
s1: establishing an insulation equipment identification model, inputting an image of the insulation equipment, and outputting the image as the state of the insulation equipment, wherein the state of the insulation equipment comprises normal state and damaged state;
s2: installing a plurality of cameras on a transmission tower, and installing one camera at each position of the insulating equipment; the camera comprises a lamp cap, a track and a camera body, wherein the lamp cap and the camera body are arranged on the track, and the track is arranged on a transmission tower;
s3: the camera collects images of the insulating equipment at regular time, the collected images are identified by the identification model in the step S1, and the state of the insulating equipment is judged;
s4: and when the identification result is that the camera is damaged, transmitting the image collected by the camera to a control center.
2. The insulating equipment abnormity warning method based on the Internet of things according to claim 1, characterized in that: the insulating device is an insulator.
3. The insulating equipment abnormity warning method based on the Internet of things according to claim 1, characterized in that: when the insulating equipment identification model is established, a database is established firstly, the database comprises states corresponding to insulating equipment images in different states, and modeling is carried out by training and learning data in the database.
4. The insulating equipment abnormity warning method based on the Internet of things according to claim 3, characterized in that: modeling is performed by a deep-learned VGG model.
5. The insulating equipment abnormity warning method based on the Internet of things according to claim 3, characterized in that: the database includes images of the insulated equipment in normal and damaged states.
6. The insulating equipment abnormity warning method based on the Internet of things according to claim 1, characterized in that: the number of the cameras is more than 1.
7. The insulating equipment abnormity warning method based on the Internet of things according to claim 1, characterized in that: in step S3, when the recognition result is normal, the step S3 is repeated.
8. The insulating equipment abnormity warning method based on the Internet of things according to claim 1, characterized in that: further comprising S5; s5, the image collected by the camera is checked by the detector through the control center, and then the image is confirmed, and the damaged insulation equipment is repaired or replaced.
9. The insulating equipment abnormity warning method based on the Internet of things according to claim 1, characterized in that: in step S4, when the recognition result is a damage, the image captured by the camera and the position of the camera are transmitted to the control center.
10. The insulating equipment abnormity warning method based on the Internet of things according to claim 9, characterized in that: the camera comprises an acquisition module for acquiring images of the insulating equipment, a positioning module for positioning and a transmission module for storing and transmitting data, and when the identification result is damaged, the acquisition module and the positioning module transmit the acquired images and positioning information to the control center through the transmission module.
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| CN202010005263.7A CN111107327A (en) | 2020-01-03 | 2020-01-03 | Insulating equipment abnormity alarm method based on Internet of things |
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| CN202010005263.7A CN111107327A (en) | 2020-01-03 | 2020-01-03 | Insulating equipment abnormity alarm method based on Internet of things |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114943884A (en) * | 2022-06-10 | 2022-08-26 | 慧之安信息技术股份有限公司 | Equipment protection method based on deep learning |
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| CN108919031A (en) * | 2018-07-26 | 2018-11-30 | 沈阳工业大学 | A kind of HV Insulator On-line Monitoring Systems and method |
| WO2019098430A1 (en) * | 2017-11-16 | 2019-05-23 | 주식회사 아이오티봇 | Site safety management system using unmanned detection device |
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2020
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Patent Citations (5)
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| CN106250920A (en) * | 2016-07-26 | 2016-12-21 | 国网福建省电力有限公司 | The insulator state detection merged based on multicharacteristic information and diagnostic method |
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| CN110501616A (en) * | 2018-05-16 | 2019-11-26 | 刘琳 | A kind of electric power pylon insulator dielectric condition monitoring system |
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| CN114943884A (en) * | 2022-06-10 | 2022-08-26 | 慧之安信息技术股份有限公司 | Equipment protection method based on deep learning |
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