CN114049336B - GIS sleeve temperature anomaly detection method, device, equipment and readable storage medium - Google Patents
GIS sleeve temperature anomaly detection method, device, equipment and readable storage medium Download PDFInfo
- Publication number
- CN114049336B CN114049336B CN202111370068.5A CN202111370068A CN114049336B CN 114049336 B CN114049336 B CN 114049336B CN 202111370068 A CN202111370068 A CN 202111370068A CN 114049336 B CN114049336 B CN 114049336B
- Authority
- CN
- China
- Prior art keywords
- temperature
- points
- gis sleeve
- pixel points
- region
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 41
- 230000002159 abnormal effect Effects 0.000 claims abstract description 49
- 238000000034 method Methods 0.000 claims abstract description 37
- 238000009499 grossing Methods 0.000 claims abstract description 10
- 238000002372 labelling Methods 0.000 claims description 13
- 238000004590 computer program Methods 0.000 claims description 11
- 238000004422 calculation algorithm Methods 0.000 claims description 8
- 238000012800 visualization Methods 0.000 claims description 4
- 239000003086 colorant Substances 0.000 claims description 2
- 230000005856 abnormality Effects 0.000 description 19
- 238000004364 calculation method Methods 0.000 description 4
- 238000013136 deep learning model Methods 0.000 description 4
- 238000012549 training Methods 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000013527 convolutional neural network Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
-
- 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
-
- 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
- G06T2207/20081—Training; Learning
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Molecular Biology (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Health & Medical Sciences (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Quality & Reliability (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Radiation Pyrometers (AREA)
Abstract
The invention discloses a GIS sleeve temperature anomaly detection method, device and equipment and a readable storage medium, wherein the method comprises the following steps: acquiring an infrared image marked with a GIS sleeve area, and acquiring temperatures corresponding to all pixel points in the GIS sleeve area to form a temperature set; constructing a GIS sleeve region temperature space distribution model, removing invalid data, and smoothing single-point noise in an infrared image; constructing a GIS sleeve region temperature frequency distribution model, establishing a double base line, dividing an interference region and a normal region, and extracting main information; and marking the pixel points after noise removal, respectively marking the pixel points after noise removal as suspected abnormal points when the temperature corresponding to the pixel points exceeds a preset threshold value, and marking the pixel points not exceeding the preset threshold value as the highest temperature point and the lowest temperature point. The method, the device, the equipment and the readable storage medium realize automatic detection of the suspected abnormal point of the temperature of the GIS sleeve region, and improve the detection efficiency and the accuracy.
Description
Technical Field
The invention relates to the technical field of infrared image processing, in particular to a GIS sleeve temperature anomaly detection method, device and equipment and a readable storage medium.
Background
With the wide application of infrared equipment in GIS sleeve region live detection, power supply companies accumulate a large number of operation and maintenance infrared images of GIS sleeve regions. For these infrared images of the GIS bushing area, manual classification screening is generally required for these infrared images to detect the infrared images of the GIS bushing area with abnormal temperature points.
And because the GIS sleeve areas are more in number, corresponding infrared images are more, and the similarity of a plurality of devices is higher, the task amount of detection operation is larger. And the efficiency of manual detection is relatively slow, and error and leakage are also unavoidable. If the abnormal GIS sleeve region cannot be detected in time, electric power accidents are likely to be caused. Therefore, the prior art has the defects of low efficiency and difficult guarantee of accuracy.
Therefore, how to improve the detection efficiency and accuracy of the suspected abnormal point of the temperature of the GIS sleeve region is a problem to be solved by the technicians in the field.
Disclosure of Invention
The invention aims to provide a GIS sleeve temperature anomaly detection method, device and equipment and a readable storage medium, so as to improve the detection efficiency and accuracy of a suspected anomaly point of the temperature of a GIS sleeve region; the invention also aims to provide a GIS sleeve temperature anomaly detection device, equipment and a readable storage medium comprising the method, which can also improve the detection efficiency and the accuracy of the suspicious anomaly points of the GIS sleeve region temperature.
In order to solve the technical problems, the embodiment of the invention provides the following technical scheme:
A GIS sleeve temperature anomaly detection method comprises the following steps:
and acquiring an infrared image marked with the GIS sleeve region, and acquiring temperatures corresponding to all pixel points in the GIS sleeve region to form a temperature set.
Constructing a GIS sleeve region temperature space distribution model, removing invalid data, and smoothing single-point noise in an infrared image;
Constructing a GIS sleeve region temperature frequency distribution model, establishing a double base line, dividing an interference region and a normal region, and extracting main information;
And marking the pixel points after noise removal, respectively marking the pixel points after noise removal as suspected abnormal points when the temperature corresponding to the pixel points exceeds a preset threshold value, and marking the pixel points not exceeding the preset threshold value as the highest temperature point and the lowest temperature point.
Preferably, the method further comprises:
And marking the pixel points with the temperature not exceeding the preset threshold value as the highest temperature point and the lowest temperature point respectively by using different colors, and taking the rest of the unmarked pixel points as normal pixel points.
Preferably, constructing a GIS sleeve region temperature space distribution model, removing invalid data, and performing smoothing treatment on single-point noise in an infrared image, wherein the method comprises the following steps:
Determining that a temperature abnormal continuous area or a continuous area with temperature suspected abnormal points reaching a specified threshold value is not a temperature abnormal point by traversing the temperature set, wherein the temperature abnormal single point is regarded as noise to be processed; wherein the GIS casing region radius or the specified threshold value can be specified manually or determined through learning by a learning algorithm.
Preferably, a GIS sleeve region temperature frequency distribution model is constructed, a double base line is designed, an interference region and a normal region are divided, and main information extraction is carried out, wherein the method comprises the following steps:
Setting a low Wen Jixian L1 and a high-temperature baseline L2, wherein the low Wen Jixian L1 and the high-temperature baseline L2 are parallel to an X axis and are mutually independent, the height is adjustable, the percentage or absolute value of the relative highest frequency is adjustable, starting from the leftmost low temperature of the temperature-frequency distribution, if a certain temperature frequency is lower than L1, all pixels corresponding to the temperature are excluded until the certain temperature frequency is higher than L1, and all pixels of the temperature are reserved; continuing to judge that if the frequency of a certain temperature is higher than L2, reserving all pixel points corresponding to the temperature, and if the frequency of the temperature is lower than L2, eliminating all pixel points corresponding to the temperature until all temperature judgment is finished; the highest temperature and the lowest temperature in all the reserved pixel points are the effective highest temperature and the effective lowest temperature, and the temperature difference between the highest temperature and the lowest temperature is the effective temperature difference; and eliminating all the excluded pixel points.
Preferably, after the marking that the temperature corresponding to the pixel point after the noise removal exceeds the preset threshold is a suspected abnormal point, the method further includes:
And marking suspected abnormal points, the highest temperature points and the lowest temperature points in the infrared image to obtain an infrared marked image.
Preferably, after the obtaining the infrared labeling image, the method further includes:
and correspondingly storing the infrared labeling image and the identification information of the GIS sleeve region in the infrared labeling image to a preset target file.
Preferably, after the infrared labeling image and the identification information of the GIS sleeve region in the infrared labeling image are correspondingly stored in a preset target file, the method further includes:
And displaying the target file through a preset visualization tool.
In order to solve the technical problem, the invention also provides a device for detecting the abnormal temperature of the GIS sleeve, which comprises the following components:
the acquisition module is used for acquiring an infrared image marked with a GIS sleeve area, acquiring temperatures corresponding to all pixel points in the GIS sleeve area and forming a temperature set;
The computing module is used for constructing a GIS sleeve region temperature space distribution model, removing invalid data and smoothing single-point noise in an infrared image;
The dividing module is used for constructing a GIS sleeve region temperature frequency distribution model, setting up a double base line, dividing an interference region and a normal region, and extracting main information;
the marking module is used for marking the pixel points after noise removal respectively, marking the pixel points after noise removal, corresponding to which the temperature exceeds a preset threshold value, as suspected abnormal points, and marking the pixel points which do not exceed the preset threshold value as the highest temperature point and the lowest temperature point.
In order to solve the technical problem, the invention also provides a GIS casing temperature anomaly detection device, which comprises:
A memory for storing a computer program;
And the processor is used for realizing the steps of the GIS sleeve temperature abnormality detection method when executing the computer program.
In order to solve the technical problem, the invention also provides a readable storage medium, wherein the readable storage medium stores a computer program, and the computer program realizes the steps of the GIS sleeve temperature anomaly detection method according to any one of the above steps when being executed by a processor.
According to the scheme, the GIS sleeve temperature anomaly detection method provided by the embodiment of the invention comprises the following steps: acquiring an infrared image marked with a GIS sleeve area, and acquiring temperatures corresponding to all pixel points in the GIS sleeve area to form a temperature set; constructing a GIS sleeve region temperature space distribution model, removing invalid data, and smoothing single-point noise in an infrared image; constructing a GIS sleeve region temperature frequency distribution model, establishing a double base line, dividing an interference region and a normal region, and extracting main information; and marking the pixel points after noise removal, respectively marking the pixel points after noise removal as suspected abnormal points when the temperature corresponding to the pixel points exceeds a preset threshold value, and marking the pixel points not exceeding the preset threshold value as the highest temperature point and the lowest temperature point.
Therefore, the method can automatically calculate the pixel points with abnormal temperature in the GIS sleeve region based on the infrared image of the GIS sleeve region marked with the GIS sleeve region, so that the automatic detection of the suspected abnormal point of the temperature in the GIS sleeve region is realized, the manual detection process is replaced, and the detection efficiency and the detection accuracy are improved. The detection efficiency is improved, so that the GIS sleeve region with the abnormality can be detected in time, and the occurrence of electric power accidents can be avoided to a certain extent.
Correspondingly, the GIS sleeve temperature abnormality detection device, the GIS sleeve temperature abnormality detection equipment and the readable storage medium provided by the embodiment of the invention also have the technical effects.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a GIS sleeve temperature anomaly detection method disclosed by the embodiment of the invention;
fig. 2 is a schematic diagram of a device for detecting temperature abnormality of a GIS sleeve according to an embodiment of the present invention;
Fig. 3 is a schematic diagram of a device for detecting temperature abnormality of a GIS sleeve according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. 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.
The embodiment of the invention discloses a method, a device and equipment for detecting temperature abnormality of a GIS sleeve and a readable storage medium, which are used for improving the detection efficiency and the accuracy of suspected abnormal points of the temperature of a GIS sleeve region.
Referring to fig. 1, a method for detecting temperature abnormality of a GIS sleeve according to an embodiment of the present invention includes:
S101, acquiring an infrared image marked with a GIS sleeve area, and acquiring temperatures corresponding to all pixel points in the GIS sleeve area to form a temperature set;
It should be noted that, the manner of acquiring the infrared image of the GIS sleeve region may be: the method comprises the steps of obtaining the images from a database through a software interface, obtaining the images from a storage medium through a hardware interface, or receiving the GIS sleeve region infrared images sent by an image sending end through a network line.
It should be noted that, each pixel point in the GIS sleeve area corresponds to a temperature, and the higher the temperature is, the higher the probability of abnormality in the GIS sleeve area is.
S102, constructing a GIS sleeve region temperature space distribution model, removing invalid data, and smoothing single-point noise in an infrared image;
Determining a continuous area with abnormal temperature or a continuous area with suspected abnormal temperature points reaching a specified threshold value by traversing the temperature set, and not the points with abnormal temperature, wherein single points with abnormal temperature are classified as noise treatment; wherein the region radius or threshold may be specified manually or determined by learning through a learning algorithm.
S103, constructing a GIS sleeve region temperature frequency distribution model, setting up a double base line, dividing an interference region and a normal region, and extracting main information;
Setting a temperature frequency distribution model based on an effective temperature set, setting a low Wen Jixian L1 and a high-temperature baseline L2, wherein the baselines are parallel to an X axis, are mutually independent and adjustable in height and can be adjusted to be a percentage or absolute value of the relative highest frequency, starting from the leftmost low temperature of temperature-frequency distribution, and if a certain temperature frequency is lower than L1, excluding all pixel points of the temperature; until the frequency of a certain temperature is higher than L1, reserving all pixel points of the temperature; continuously judging that if the frequency of a certain temperature is higher than L2, reserving all pixel points of the temperature, and if the frequency of the temperature is lower than L2, eliminating all pixel points of the temperature; and until all the temperature judgment is finished, the highest temperature and the lowest temperature in all the reserved pixel points are the effective highest temperature and the effective lowest temperature, and the temperature difference is the effective temperature difference.
And S104, respectively marking the pixel points after noise removal, marking the pixel points after noise removal with the temperature exceeding a preset threshold as suspected abnormal points, and marking the pixel points without the temperature exceeding the preset threshold as the highest temperature point and the lowest temperature point.
The pixel points exceeding the preset threshold are marked with purple as suspected abnormal points, the pixel points not exceeding the preset threshold are respectively marked with red as the highest point, and the pixel points not exceeding the preset threshold are respectively marked with blue as the lowest temperature point.
It can be seen that the embodiment provides a method for detecting abnormal temperature of a GIS sleeve, which can automatically calculate and obtain pixel points with abnormal temperature in the GIS sleeve area based on an infrared image of the GIS sleeve area marked with the GIS sleeve area, so that automatic detection of suspected abnormal points of the temperature of the GIS sleeve area is realized, a manual detection process is replaced, and detection efficiency and accuracy are improved. The detection efficiency is improved, so that the GIS sleeve region with the abnormality can be detected in time, and the occurrence of electric power accidents can be avoided to a certain extent.
Based on any of the above embodiments, it should be noted that, after marking the pixel point with the temperature exceeding the preset threshold as the suspected abnormal point, the method further includes: marking the highest temperature point and the lowest temperature point of the temperature in the infrared image to obtain an infrared marked image.
Preferably, after obtaining the infrared labeling image, the method further comprises: and correspondingly storing the infrared marked image and the identification information of the GIS sleeve region in the infrared marked image to a preset target file.
Preferably, after the infrared labeling image and the identification information of the GIS sleeve region in the infrared labeling image are correspondingly stored in the preset target file, the method further comprises: and displaying the target file through a preset visualization tool.
According to the identification information of the GIS sleeve region, which GIS sleeve region is can be known, so that the infrared labeling image and the identification information of the GIS sleeve region in the infrared labeling image are correspondingly stored in a preset target file, and an operation and maintenance technician can conveniently know which GIS sleeve region has a suspected abnormal temperature point by searching the target file. The corresponding storage is to store in a one-to-one correspondence, for example, the corresponding storage is to store a table with a specified format, and the information is recorded in a uniform format so as to facilitate subsequent management and analysis.
Based on any of the above embodiments, it should be noted that the infrared image of the GIS bushing region marked with the GIS bushing region may be obtained by a deep learning model. Namely: and inputting the infrared image of the GIS sleeve region acquired by the infrared terminal into a deep learning model, outputting the position information (namely the GIS sleeve region) of the GIS sleeve region in the infrared image, and labeling the position information in the original infrared image to obtain the GIS sleeve region labeled with the GIS sleeve region. The deep learning model can be obtained through SSD algorithm training. The training process of the deep learning model can refer to the prior art (convolutional neural network model, etc.), and the training framework can adopt TensorFlow.
The following describes a device for detecting temperature abnormality of a GIS bushing provided by the embodiment of the present invention, and the device for detecting temperature abnormality of a GIS bushing described below and the method for detecting temperature abnormality of a GIS bushing described above may be referred to each other.
Referring to fig. 2, a device for detecting temperature abnormality of a GIS sleeve according to an embodiment of the present invention includes:
the acquiring module 301 is configured to acquire an infrared image marked with a GIS sleeve area, acquire temperatures corresponding to all pixel points in the GIS sleeve area, and form a temperature set;
The computing module 302 is configured to construct a temperature space distribution model of the GIS sleeve region, reject invalid data, and smooth single-point noise in the infrared image;
The dividing module 303 is configured to construct a temperature frequency distribution model of the GIS sleeve region, set up a double baseline, divide an interference region and a normal region, and extract main information;
the marking module 304 is configured to mark the pixel points after noise removal, respectively, mark the pixel points after noise removal with a temperature exceeding a preset threshold as suspected abnormal points, and mark the pixel points without exceeding the preset threshold as a highest temperature point and a lowest temperature point.
Preferably, the calculation module comprises:
the determining unit is used for determining the temperature higher than the average value in the temperature set as an effective temperature to obtain an effective temperature set;
The calculation unit is used for determining that a temperature abnormal continuous area or a continuous area with temperature suspected abnormal points reaching a specified threshold value is not a temperature abnormal point by traversing the temperature set, and the single point of the temperature abnormal point is classified as noise treatment; wherein the region radius or threshold may be specified manually or determined by learning through a learning algorithm.
Preferably, the dividing unit is specifically configured to:
Setting a temperature frequency distribution model based on an effective temperature set, setting a low Wen Jixian L1 and a high-temperature baseline L2, wherein the baselines are parallel to an X axis, are mutually independent and adjustable in height and can be adjusted to be a percentage or absolute value of the relative highest frequency, starting from the leftmost low temperature of temperature-frequency distribution, and if a certain temperature frequency is lower than L1, excluding all pixel points of the temperature; until the frequency of a certain temperature is higher than L1, reserving all pixel points of the temperature; continuously judging that if the frequency of a certain temperature is higher than L2, reserving all pixel points of the temperature, and if the frequency of the temperature is lower than L2, eliminating all pixel points of the temperature; and until all the temperature judgment is finished, the highest temperature and the lowest temperature in all the reserved pixel points are the effective highest temperature and the effective lowest temperature, and the temperature difference is the effective temperature difference.
Preferably, the method further comprises:
And the marking module is used for marking the suspected abnormal points of the temperature in the infrared image to obtain the infrared marked image.
Preferably, the method further comprises:
the storage module is used for correspondingly storing the infrared marked image and the identification information of the GIS sleeve region in the infrared marked image to a preset target file.
Preferably, the method further comprises:
and the display module is used for displaying the target file through a preset visualization tool.
It can be seen that this embodiment provides a device for detecting temperature abnormality of a GIS sleeve, including: the device comprises an acquisition module, a calculation module, a division module and a marking module. Firstly, acquiring infrared images of a GIS sleeve region marked with the GIS sleeve region by an acquisition module, and acquiring temperatures corresponding to all pixel points in the GIS sleeve region to form a temperature set; then, the calculation module traverses the temperature set, a GIS sleeve region temperature space distribution model is constructed, invalid data is removed, and single-point noise in the infrared image is smoothed; the dividing module builds a GIS sleeve region temperature frequency distribution model, designs a double base line, divides an interference region and a normal region, and extracts main information; and finally, respectively marking the pixel points with noise removed by a marking module, wherein the pixel points with the noise removed are marked as suspected abnormal points and the pixel points with the noise removed are marked as the highest temperature point and the lowest temperature point. Therefore, the modules work together, so that the automatic detection of the suspected abnormal point of the temperature of the GIS sleeve region is realized, and the detection efficiency and accuracy are improved.
The following describes a device for detecting temperature abnormality of a GIS sleeve according to an embodiment of the present invention, and the device for detecting temperature abnormality of a GIS sleeve described below and the method and apparatus for detecting temperature abnormality of a GIS sleeve described above may be referred to each other.
Referring to fig. 3, a device for detecting temperature abnormality of a GIS sleeve according to an embodiment of the present invention includes:
a memory 401 for storing a computer program;
and a processor 402, configured to implement the steps of the GIS bushing temperature anomaly detection method according to any of the foregoing embodiments when executing the computer program.
The following describes a readable storage medium provided in the embodiments of the present invention, and the readable storage medium described below and the method, apparatus and device for detecting temperature anomaly of a GIS sleeve described above may be referred to with each other.
A readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the GIS bushing temperature anomaly detection method according to any of the embodiments described above.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
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 (8)
1. The GIS sleeve temperature anomaly detection method is characterized by comprising the following steps:
Acquiring an infrared image marked with a GIS sleeve area, and acquiring temperatures corresponding to all pixel points in the GIS sleeve area to form a temperature set;
constructing a GIS sleeve region temperature space distribution model, removing invalid data, and smoothing single-point noise in an infrared image;
Constructing a GIS sleeve region temperature frequency distribution model, establishing a double base line, dividing an interference region and a normal region, and extracting main information;
Marking the pixel points after noise removal respectively, marking the points, corresponding to the pixel points after noise removal, with the temperature exceeding a preset threshold value as suspected abnormal points, marking the points, with the temperature not exceeding the preset threshold value, with the highest temperature as the highest temperature points, and marking the points, with the lowest temperature, as the lowest temperature points;
Constructing a GIS sleeve region temperature space distribution model, removing invalid data, and smoothing single-point noise in an infrared image, wherein the method comprises the following steps:
Determining that a temperature abnormal continuous area or a continuous area with temperature suspected abnormal points reaching a specified threshold value is not a temperature abnormal point by traversing the temperature set, wherein the temperature abnormal single point is regarded as noise to be processed; wherein the radius of the GIS sleeve region or the specified threshold is manually specified or determined by learning through a learning algorithm;
constructing a GIS sleeve region temperature frequency distribution model, designing a double base line, dividing an interference region and a normal region, and extracting main information, wherein the method comprises the following steps:
Setting a low Wen Jixian L1 and a high-temperature baseline L2, wherein the low Wen Jixian L1 and the high-temperature baseline L2 are parallel to an X axis and are mutually independent, the height is adjustable, the percentage or absolute value of the relative highest frequency is adjustable, starting from the leftmost low temperature of the temperature-frequency distribution, if a certain temperature frequency is lower than L1, all pixels corresponding to the temperature are excluded until the certain temperature frequency is higher than L1, and all pixels of the temperature are reserved; continuing to judge that if the frequency of a certain temperature is higher than L2, reserving all pixel points corresponding to the temperature, and if the frequency of the temperature is lower than L2, eliminating all pixel points corresponding to the temperature until all temperature judgment is finished; the highest temperature and the lowest temperature in all the reserved pixel points are the effective highest temperature and the effective lowest temperature, and the temperature difference between the highest temperature and the lowest temperature is the effective temperature difference; and eliminating all the excluded pixel points.
2. The method as recited in claim 1, further comprising:
And marking the point with the highest temperature and the point with the lowest temperature in the preset threshold value, which are not exceeded by the temperature, as the highest temperature point and the lowest temperature point respectively by using different colors, and taking the rest of the unlabeled points as normal pixel points.
3. The method according to any one of claims 1 or 2, wherein after marking the pixel point with the noise removed, which corresponds to the temperature exceeding the preset threshold, as a suspected abnormal point, the method further comprises:
And marking suspected abnormal points, the highest temperature points and the lowest temperature points in the infrared image to obtain an infrared marked image.
4. The method of claim 3, further comprising, after the obtaining the infrared-labeled image:
and correspondingly storing the infrared labeling image and the identification information of the GIS sleeve region in the infrared labeling image to a preset target file.
5. The method according to claim 4, wherein after storing the ir-labeled image and the identification information of the GIS sleeve region in the ir-labeled image in the preset target file, the method further comprises:
And displaying the target file through a preset visualization tool.
6. The utility model provides a GIS sleeve pipe temperature anomaly detection device which characterized in that includes:
the acquisition module is used for acquiring an infrared image marked with a GIS sleeve area, acquiring temperatures corresponding to all pixel points in the GIS sleeve area and forming a temperature set;
The computing module is used for constructing a GIS sleeve region temperature space distribution model, removing invalid data and smoothing single-point noise in an infrared image;
The dividing module is used for constructing a GIS sleeve region temperature frequency distribution model, setting up a double base line, dividing an interference region and a normal region, and extracting main information;
The marking module is used for marking the pixel points after noise removal respectively, marking the points with the temperatures exceeding a preset threshold value corresponding to the pixel points after noise removal as suspected abnormal points, marking the points with the highest temperatures not exceeding the preset threshold value as the highest temperature points, and marking the points with the lowest temperatures as the lowest temperature points;
Constructing a GIS sleeve region temperature space distribution model, removing invalid data, and smoothing single-point noise in an infrared image, wherein the method comprises the following steps:
Determining that a temperature abnormal continuous area or a continuous area with temperature suspected abnormal points reaching a specified threshold value is not a temperature abnormal point by traversing the temperature set, wherein the temperature abnormal single point is regarded as noise to be processed; wherein the radius of the GIS sleeve region or the specified threshold is manually specified or determined by learning through a learning algorithm;
constructing a GIS sleeve region temperature frequency distribution model, designing a double base line, dividing an interference region and a normal region, and extracting main information, wherein the method comprises the following steps:
Setting a low Wen Jixian L1 and a high-temperature baseline L2, wherein the low Wen Jixian L1 and the high-temperature baseline L2 are parallel to an X axis and are mutually independent, the height is adjustable, the percentage or absolute value of the relative highest frequency is adjustable, starting from the leftmost low temperature of the temperature-frequency distribution, if a certain temperature frequency is lower than L1, all pixels corresponding to the temperature are excluded until the certain temperature frequency is higher than L1, and all pixels of the temperature are reserved; continuing to judge that if the frequency of a certain temperature is higher than L2, reserving all pixel points corresponding to the temperature, and if the frequency of the temperature is lower than L2, eliminating all pixel points corresponding to the temperature until all temperature judgment is finished; the highest temperature and the lowest temperature in all the reserved pixel points are the effective highest temperature and the effective lowest temperature, and the temperature difference between the highest temperature and the lowest temperature is the effective temperature difference; and eliminating all the excluded pixel points.
7. GIS sleeve pipe temperature anomaly detection equipment, characterized by comprising:
A memory for storing a computer program;
A processor for implementing the steps of the GIS bushing temperature anomaly detection method according to any one of claims 1-5 when executing the computer program.
8. A readable storage medium, wherein a computer program is stored on the readable storage medium, and the computer program when executed by a processor implements the steps of the GIS bushing temperature anomaly detection method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111370068.5A CN114049336B (en) | 2021-11-18 | 2021-11-18 | GIS sleeve temperature anomaly detection method, device, equipment and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111370068.5A CN114049336B (en) | 2021-11-18 | 2021-11-18 | GIS sleeve temperature anomaly detection method, device, equipment and readable storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114049336A CN114049336A (en) | 2022-02-15 |
| CN114049336B true CN114049336B (en) | 2024-06-14 |
Family
ID=80210519
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111370068.5A Active CN114049336B (en) | 2021-11-18 | 2021-11-18 | GIS sleeve temperature anomaly detection method, device, equipment and readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114049336B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115128447A (en) * | 2022-07-14 | 2022-09-30 | 华能罗源发电有限责任公司 | Method for detecting state quantity of middle casing pipe in GIS of thermal power energy storage system |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109804119B (en) * | 2016-12-30 | 2021-03-19 | 同济大学 | Asphalt pavement crack development degree detection method based on infrared thermography analysis |
| CN109671078B (en) * | 2018-12-24 | 2022-11-01 | 广东理致技术有限公司 | Method and device for detecting product surface image abnormity |
| CN111426387A (en) * | 2019-01-10 | 2020-07-17 | 杭州海康威视数字技术股份有限公司 | Temperature anomaly detection method and device |
| CN109900366B (en) * | 2019-03-22 | 2021-05-07 | 国网重庆市电力公司电力科学研究院 | Method and device for detecting abnormal temperature point of lightning arrester |
| CN110866503B (en) * | 2019-11-19 | 2024-01-05 | 圣点世纪科技股份有限公司 | Abnormality detection method and abnormality detection system for finger vein equipment |
| CN111845448B (en) * | 2020-07-31 | 2021-11-30 | 中国汽车工程研究院股份有限公司 | Temperature anomaly probe identification algorithm based on probability mutation rule |
-
2021
- 2021-11-18 CN CN202111370068.5A patent/CN114049336B/en active Active
Non-Patent Citations (2)
| Title |
|---|
| Processing Thermal Infrared Imagery Time-Series from Volcano Permanent Ground-Based Monitoring Network. Latest Methodological Improvements to Characterize Surface Temperatures Behavior of Thermal Anomaly Areas;Fabio Sansivero 等;《remote sensing》;20190306;1-22 * |
| 石化泵房设备异常检测及处置系统研制;宋佳润;《中国优秀硕士学位论文全文数据库工程科技I辑》;20210515;B016-20 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114049336A (en) | 2022-02-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109900366B (en) | Method and device for detecting abnormal temperature point of lightning arrester | |
| CN101957325B (en) | Substation equipment appearance abnormality recognition method based on substation inspection robot | |
| CN111369516B (en) | Transformer bushing heating defect detection method based on infrared image recognition | |
| CN103150557B (en) | A kind of operation of the display terminal based on machine vision responses match pick-up unit | |
| CN105957088B (en) | Transformer composite insulator casing monitoring method and system based on computer vision | |
| CN102915432B (en) | A kind of vehicle-mounted microcomputer image/video data extraction method and device | |
| US10430687B2 (en) | Trademark graph element identification method, apparatus and system, and computer storage medium | |
| CN114049336B (en) | GIS sleeve temperature anomaly detection method, device, equipment and readable storage medium | |
| CN108009547A (en) | A kind of nameplate recognition methods of substation equipment and device | |
| CN102346153A (en) | Method for detecting tunnel defect | |
| CN110569774B (en) | Automatic line graph image digitalization method based on image processing and pattern recognition | |
| CN111044149A (en) | Method and device for detecting temperature abnormal point of voltage transformer and readable storage medium | |
| CN108427959A (en) | Board state collection method based on image recognition and system | |
| CN115151952A (en) | High-precision identification method and system for power transformation equipment | |
| CN111881867A (en) | Video analysis method and device and electronic equipment | |
| CN116055690A (en) | Method and equipment for processing machine room monitoring video | |
| CN112381800A (en) | Wire diameter abnormity identification method and device, electronic equipment and computer readable storage medium | |
| CN113343998A (en) | Reading monitoring system and method for electric power mechanical meter, computer equipment and application | |
| CN111950745B (en) | Image processing-based switching operation management method and system | |
| CN115841731B (en) | Infrared monitoring park fire early warning method | |
| CN117114420A (en) | Image recognition-based industrial and trade safety accident risk management and control system and method | |
| CN114627463B (en) | Non-contact power distribution data identification method based on machine identification | |
| CN108986175B (en) | Temperature interpretation method for temperature indicating paint area | |
| CN109087311B (en) | Temperature judging and reading method for temperature indicating paint | |
| CN113947563A (en) | Cable process quality dynamic defect detection method based on deep learning |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |