CN113418617A - Three-dimensional temperature field measuring and diagnosing method for box type transformer of wind power plant - Google Patents
Three-dimensional temperature field measuring and diagnosing method for box type transformer of wind power plant Download PDFInfo
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- CN113418617A CN113418617A CN202110801868.1A CN202110801868A CN113418617A CN 113418617 A CN113418617 A CN 113418617A CN 202110801868 A CN202110801868 A CN 202110801868A CN 113418617 A CN113418617 A CN 113418617A
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- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000003745 diagnosis Methods 0.000 claims abstract description 13
- 238000013528 artificial neural network Methods 0.000 claims abstract description 6
- 238000003709 image segmentation Methods 0.000 claims abstract description 4
- 230000011218 segmentation Effects 0.000 claims abstract description 4
- 238000005259 measurement Methods 0.000 claims description 6
- 238000010586 diagram Methods 0.000 claims description 3
- 230000003685 thermal hair damage Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 abstract description 2
- 230000005856 abnormality Effects 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/48—Thermography; Techniques using wholly visual means
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N25/00—Investigating or analyzing materials by the use of thermal means
- G01N25/72—Investigating presence of flaws
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10048—Infrared image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
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Abstract
The invention discloses a three-dimensional temperature field measuring and diagnosing method for a box-type transformer of a wind power plant, measuring equipment and a diagnosing method, wherein the measuring equipment comprises a binocular infrared imager and a computer platform, the temperature information of the equipment is obtained through the binocular infrared imager, angular point matching and infrared image matching are carried out through an SIFT algorithm, and three-dimensional surface temperature information is obtained through calculation of a space point reconstruction algorithm; acquiring temperature resistance threshold values and working ranges of components of each box-type transformer, carrying out gridding segmentation on a temperature field according to different areas of the components by using an image segmentation algorithm, and obtaining working temperature rise of elements in corresponding grid areas through image identification comparison. The technical scheme is characterized in that an infrared imager is used as information acquisition hardware equipment, three-dimensional temperature field reconstruction of a box-type transformer is carried out through a heat conduction method, and a neural network is used for carrying out gridding comparison on the three-dimensional temperature field so as to realize the regional fault diagnosis of different temperature-resistant regions of equipment devices.
Description
Technical Field
The invention relates to the field of transformer measurement and diagnosis methods, in particular to a method for measuring and diagnosing a three-dimensional temperature field of a box type transformer of a wind power plant.
Background
The infrared imager can image a target in a 'surface' mode in real time, the temperature abnormality of an object can be judged by analyzing and identifying images, but an observer cannot acquire three-dimensional temperature information of a device immediately, and the state can be judged by combining the temperature tolerance capability of different device parts.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a three-dimensional temperature field measuring and diagnosing method for a box type transformer of a wind power plant.
The technical purpose of the invention is realized by the following technical scheme:
a three-dimensional temperature field measuring and diagnosing method for a box-type transformer of a wind power plant comprises a binocular infrared imager and a computer platform, and comprises the following diagnosing steps:
the method comprises the following steps: acquiring temperature information of equipment through a binocular infrared imager, performing corner matching and infrared image matching through an SIFT algorithm, and calculating through a space point reconstruction algorithm to obtain three-dimensional surface temperature information;
step two: obtaining the material characteristics and the heat conduction characteristics of the box-type transformer, and calculating to obtain a three-dimensional temperature field model by a finite formula method;
step three: acquiring temperature-resistant threshold values and working ranges of components of the box-type transformer, performing gridding segmentation on a temperature field according to different regions of the components by using an image segmentation algorithm, and acquiring working temperature rise of elements in corresponding grid regions by image identification comparison so as to judge whether the running state of equipment is normal.
Further, the binocular infrared imager is calibrated through an angle calibration based on sub-pixels and a Zhang calibration method, and geometric parameters of the binocular infrared imager are obtained; the temperature information of the equipment is obtained through an infrared imager, corner matching and infrared image matching are carried out through an SIFT algorithm, and three-dimensional surface temperature information is obtained through calculation of a space point reconstruction algorithm.
Furthermore, the binocular infrared imager is distributed at the positions of four corners of the equipment, so that the equipment information can be collected without dead angles, and the collection accuracy is improved.
Furthermore, the binocular infrared imager is connected with a computer platform, the binocular infrared imager is connected with the computer through an acquisition card, acquired image data are sent to the computer platform through the acquisition card, a finite formula method model established according to parameter information such as box-type transformer materials and structural heat conduction characteristics is operated, surface three-dimensional temperature is combined, information of each point of a three-dimensional space temperature field is calculated, and a dynamic temperature three-dimensional temperature field is drawn.
Furthermore, after the three-dimensional temperature field information is obtained, the images are identified and marked through a neural network algorithm according to a distribution reference model diagram of the transformer device, so that the cutting division of the temperature field is realized, the temperature rise of each region is judged and analyzed, and the diagnosis of a temperature rise fault point and the early warning of equipment thermal damage are realized.
In conclusion, the invention has the following beneficial effects:
the method comprises the steps of utilizing an infrared imager as information acquisition hardware equipment, reconstructing a three-dimensional temperature field of a box-type transformer through a heat conduction method, and carrying out gridding comparison on the three-dimensional temperature field by using a neural network to realize regional fault diagnosis on different temperature-resistant regions of equipment devices.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In a preferred embodiment of the invention, a method for measuring a three-dimensional temperature field of a box-type transformer of a wind power plant comprises the following steps: a binocular infrared imager and a computer platform,
the binocular infrared imager is calibrated by an angle calibration method and a Zhang calibration method based on sub-pixels, and geometric parameters of the binocular infrared imager are obtained; acquiring temperature information of equipment through an infrared imager, performing corner matching and infrared image matching through an SIFT algorithm, and calculating through a space point reconstruction algorithm to obtain three-dimensional surface temperature information;
the binocular infrared imager is connected with a computer platform, the binocular infrared imager and the computer are connected through an acquisition card, acquired image data are sent to the computer platform through the acquisition card, a finite formula method model established according to parameter information such as box-type transformer materials and structural heat conduction characteristics is operated, surface three-dimensional temperature is combined, information of each point of a three-dimensional space temperature field is calculated, and a dynamic temperature three-dimensional temperature field is drawn;
after the three-dimensional temperature field information is obtained, the image is identified and marked through a neural network algorithm according to a distribution reference model diagram of the transformer device, so that the cutting division of the temperature field is realized, the temperature rise of each region is judged and analyzed, the diagnosis of a temperature rise fault point and the early warning of equipment thermal damage are realized,
a diagnosis method for a three-dimensional temperature field of a box-type transformer of a wind power plant comprises the following steps:
the method comprises the following steps: acquiring temperature information of equipment through a binocular infrared imager, performing corner matching and infrared image matching through an SIFT algorithm, and calculating through a space point reconstruction algorithm to obtain three-dimensional surface temperature information;
step two: obtaining the material characteristics and the heat conduction characteristics of the box-type transformer, and calculating to obtain a three-dimensional temperature field model by a finite formula method;
step three: acquiring temperature-resistant threshold values and working ranges of components of the box-type transformer, performing gridding segmentation on a temperature field according to different regions of the components by using an image segmentation algorithm, and acquiring working temperature rise of elements in corresponding grid regions by image identification comparison so as to judge whether the running state of equipment is normal.
Has the advantages that: the method comprises the steps of utilizing an infrared imager as information acquisition hardware equipment, reconstructing a three-dimensional temperature field of a box-type transformer through a heat conduction method, and carrying out gridding comparison on the three-dimensional temperature field by using a neural network to realize regional fault diagnosis on different temperature-resistant regions of equipment devices.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. A three-dimensional temperature field measuring and diagnosing method for a box-type transformer of a wind power plant is characterized by comprising the following steps: the method comprises the following steps of:
the method comprises the following steps: acquiring temperature information of equipment through a binocular infrared imager, performing corner matching and infrared image matching through an SIFT algorithm, and calculating through a space point reconstruction algorithm to obtain three-dimensional surface temperature information;
step two: obtaining the material characteristics and the heat conduction characteristics of the box-type transformer, and calculating to obtain a three-dimensional temperature field model by a finite formula method;
step three: acquiring temperature resistance threshold values and working ranges of components of each box-type transformer, carrying out gridding segmentation on a temperature field according to different areas of the components by using an image segmentation algorithm, and obtaining working temperature rise of elements in corresponding grid areas through image identification comparison.
2. The three-dimensional temperature field measurement and diagnosis method for the box-type transformer of the wind power plant according to claim 1, characterized in that: the binocular infrared imager is calibrated by an angle calibration method and a Zhang calibration method based on sub-pixels, and geometric parameters of the binocular infrared imager are obtained.
3. The three-dimensional temperature field measurement and diagnosis method for the box-type transformer of the wind power plant according to claim 2, characterized in that: the infrared imager acquires temperature information of equipment, carries out corner matching and infrared image matching through an SIFT algorithm, and calculates three-dimensional surface temperature information through a space point reconstruction algorithm.
4. The three-dimensional temperature field measurement and diagnosis method for the box-type transformer of the wind power plant according to claim 3, characterized in that: the binocular infrared imager is connected with the computer platform, the binocular infrared imager is connected with the computer through the acquisition card, then the acquired image data are sent to the computer platform through the acquisition card, a finite formula method model established according to parameter information such as box-type transformer materials and structural heat conduction characteristics is operated, surface three-dimensional temperature is combined, each point information of a three-dimensional space temperature field is calculated, and a dynamic temperature three-dimensional temperature field is drawn.
5. The three-dimensional temperature field measurement and diagnosis method for the box-type transformer of the wind power plant according to claim 4, characterized in that: after the binocular infrared imager acquires the three-dimensional temperature field information, the image is identified and marked through a neural network algorithm according to a transformer device distribution reference model diagram, so that the cutting division of the temperature field is realized, the temperature rise of each region is judged and analyzed, and the diagnosis of a temperature rise fault point and the early warning of equipment thermal damage are realized.
6. The three-dimensional temperature field measurement and diagnosis method for the box-type transformer of the wind power plant according to claim 2, characterized in that: the binocular infrared imager is distributed at the four corners of the equipment.
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| CN202110801868.1A CN113418617A (en) | 2021-07-15 | 2021-07-15 | Three-dimensional temperature field measuring and diagnosing method for box type transformer of wind power plant |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115183876A (en) * | 2022-09-09 | 2022-10-14 | 国网山西省电力公司电力科学研究院 | Power equipment temperature measuring method and device, storage medium and computer equipment |
| WO2024055548A1 (en) * | 2022-09-16 | 2024-03-21 | 广东邦普循环科技有限公司 | Power battery gradient utilization screening method and apparatus, and device and storage medium |
| WO2024082658A1 (en) * | 2022-10-17 | 2024-04-25 | 青岛海尔空调器有限总公司 | Method and system for temperature rise detection of air conditioner |
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| WO2024082658A1 (en) * | 2022-10-17 | 2024-04-25 | 青岛海尔空调器有限总公司 | Method and system for temperature rise detection of air conditioner |
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Effective date of registration: 20220507 Address after: 751300 guest house of Tongxin County People's government, Wuzhong City, Ningxia Hui Autonomous Region Applicant after: Ningxia Longyuan new energy Co.,Ltd. Applicant after: XI'AN HUAKONG INTELLIGENT SYSTEM ENGINEERING Co.,Ltd. Address before: Room 11703, 17th floor, unit 1, building 1, oak block, 36 Fenghui South Road, high tech Zone, Xi'an City, Shaanxi Province, 710065 Applicant before: XI'AN HUAKONG INTELLIGENT SYSTEM ENGINEERING Co.,Ltd. |
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Application publication date: 20210921 |