CN117173258A - Method and device for identifying PH value of water-soluble acid of transformer oil and related equipment - Google Patents
Method and device for identifying PH value of water-soluble acid of transformer oil and related equipment Download PDFInfo
- Publication number
- CN117173258A CN117173258A CN202310915825.5A CN202310915825A CN117173258A CN 117173258 A CN117173258 A CN 117173258A CN 202310915825 A CN202310915825 A CN 202310915825A CN 117173258 A CN117173258 A CN 117173258A
- Authority
- CN
- China
- Prior art keywords
- target
- image
- transformer oil
- value
- water
- 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.)
- Pending
Links
- 239000002253 acid Substances 0.000 title claims abstract description 109
- 238000000034 method Methods 0.000 title claims abstract description 62
- 238000012360 testing method Methods 0.000 claims abstract description 53
- 238000007781 pre-processing Methods 0.000 claims abstract description 19
- 238000004590 computer program Methods 0.000 claims description 12
- 238000006243 chemical reaction Methods 0.000 claims description 10
- 238000003709 image segmentation Methods 0.000 claims description 6
- 230000011218 segmentation Effects 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 4
- 230000008569 process Effects 0.000 abstract description 17
- 238000005259 measurement Methods 0.000 abstract description 8
- 230000002159 abnormal effect Effects 0.000 abstract description 6
- 239000003921 oil Substances 0.000 description 98
- 230000006870 function Effects 0.000 description 7
- 238000004422 calculation algorithm Methods 0.000 description 6
- 230000009286 beneficial effect Effects 0.000 description 4
- 238000001914 filtration Methods 0.000 description 4
- 238000012423 maintenance Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 230000003993 interaction Effects 0.000 description 3
- 239000010723 turbine oil Substances 0.000 description 3
- 230000000007 visual effect Effects 0.000 description 3
- 238000000605 extraction Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical group [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 1
- 230000005856 abnormality Effects 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000002146 bilateral effect Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000013527 convolutional neural network Methods 0.000 description 1
- 239000002826 coolant Substances 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000003708 edge detection Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000004804 winding Methods 0.000 description 1
Abstract
The application provides a method, a device and related equipment for identifying the PH value of water-soluble acid of transformer oil, and relates to the technical field of computer vision, wherein the method comprises the steps of preprocessing an image to be identified of the transformer oil; performing target recognition on the preprocessed image to be recognized, and determining a target sample image in a target area where transformer oil is subjected to water-soluble acid test; inputting the target sample image in the target area into a trained target color space recognition model to calculate a target color parameter value; and comparing the target color parameter value with a standard PH color card to determine the PH value of the water-soluble acid of the transformer oil. According to the application, the target color parameter value is extracted through the target color space recognition model in the transformer oil water-soluble acid PH value recognition process, automatic recognition and measurement are realized by utilizing computer vision, the working efficiency and accuracy of transformer oil water-soluble acid PH value recognition are improved, and the transformer abnormal condition can be accurately judged.
Description
Technical Field
The application relates to the technical field of computer vision, in particular to a method and a device for identifying the PH value of water-soluble acid of transformer oil and related equipment.
Background
In the maintenance process of power equipment, the detection of the PH value of water-soluble acid in transformer oil is a critical ring. In a laboratory, when the PH value of oil water-soluble acid of transformer oil and turbine oil in operation is measured, the PH value is usually measured by a manual visual method, the operation is time-consuming and labor-consuming, the efficiency is low, and the error caused by subjective observation is large. Based on the water-soluble acid tester, a water-soluble acid tester is also provided, and the water-soluble acid tester has an automatic colorimetric function and adopts the principle of photoelectric colorimetric. However, the function is single, only the chromatic aberration can be measured, the absolute value (L, a, b) of the color coordinate space cannot be accurately given, and the reading results of the water-soluble acid measuring instruments produced by different enterprises or the water-soluble acid measuring instruments of different types produced by the same enterprise have deviation, and the deviation can be expanded along with the time. Therefore, in the prior art, when the water-soluble acid tester tests the PH value of the water-soluble acid of the transformer oil and the turbine oil through an automatic colorimetric function, the accurate coordinate cannot be obtained, and the measurement error is large.
Disclosure of Invention
The application aims to solve the problems that in the prior art, when a water-soluble acid tester tests the PH values of oil and water-soluble acid of a turbine oil through an automatic colorimetric function, accurate coordinates cannot be obtained and measurement errors are large, and provides a method, a device and related equipment for identifying the PH values of the oil and water-soluble acid of the transformer. The method comprises the steps of preprocessing an image to be identified of transformer oil, carrying out target identification, obtaining a target sample image from the image to be identified, taking the target sample image as input data, inputting the input data into a trained target color space identification model to calculate a target color parameter value of the target sample image, and comparing the target color parameter value with a standard PH color card to obtain the PH value of the water-soluble acid of the transformer oil. According to the application, the target color parameter value is extracted by the target color space identification model, automatic identification and measurement are realized by utilizing computer vision, the working efficiency and accuracy are improved, the abnormal condition can be accurately judged, and the maintenance efficiency of the power equipment is improved.
In a first aspect, a technical solution provided in an embodiment of the present application is a method for identifying a PH value of a water-soluble acid of transformer oil, including the following steps:
preprocessing an image to be identified of transformer oil;
performing target recognition on the preprocessed image to be recognized, and determining a target sample image in a target area where transformer oil is subjected to water-soluble acid test;
inputting the target sample image in the target area into a trained target color space recognition model to calculate a target color parameter value;
and comparing the target color parameter value with a standard PH color card to determine the PH value of the water-soluble acid of the transformer oil.
Further, the inputting the target sample image in the target area into the trained target color space recognition model to calculate the target color parameter value includes:
inputting a target sample image in the target area into the trained target color space recognition model, wherein model parameters of the target color space recognition model comprise hue, saturation and brightness;
reading RGB values of a target sample image in the target area;
and converting the RGB values of the target sample image into target color parameter values, and taking the target color parameter values corresponding to the RGB values of the target sample image obtained through conversion as target color parameter values.
Further, the converting the RGB values of the target sample image into corresponding target color parameter values has the following conversion formula:
v＝max(r,g,b)
wherein (r, g, b) represents coordinates of RGB values of the target sample image, max represents a maximum value of r, g, and b, min represents a maximum value of r, g, and b, v represents brightness in the model parameter, s represents saturation in the model parameter, and h represents hue angle of hue in the model parameter.
Further, the step of comparing the target color parameter value with a standard PH color card to determine the PH value of the water-soluble acid of the transformer oil comprises the following steps:
comparing the calculated brightness, saturation and hue angle of the hue with the brightness, saturation and hue angle of each color in the standard PH color card respectively, and determining that the target color parameter value corresponds to the color in the standard PH color card;
and determining the PH value of the water-soluble acid of the transformer oil according to the corresponding color of the target color parameter value in the standard PH color card.
Further, before the preprocessing of the image to be identified of the transformer oil, the method further comprises:
testing the transformer oil through water-soluble acid to obtain a test sample of the PH value of the water-soluble acid of the transformer oil;
and acquiring the test sample through image acquisition equipment to obtain the image to be identified.
Further, the preprocessing of the image to be identified of the transformer oil comprises the following steps:
denoising the image to be identified of the transformer oil, and removing interference information in the image to be identified;
and carrying out image enhancement and region segmentation on the denoised image to be identified to obtain a preprocessed image to be identified.
Further, the target recognition is performed on the preprocessed image to be recognized, and the determination of the target sample image in the target area where the transformer oil is subjected to the water-soluble acid test comprises the following steps:
extracting the RGB value of the preprocessed image to be identified and the edge characteristics of the test sample in the image to be identified; and determining a target area where transformer oil in the image to be identified is subjected to water-soluble acid test according to the edge characteristics, taking the image in the target area as the target sample image, and taking the RGB value of the image in the target area as the RGB value of the template sample image.
In a second aspect, a technical solution provided in an embodiment of the present application is a device for identifying PH value of water-soluble acid of transformer oil, where the device includes:
the pretreatment module is used for carrying out pretreatment on an image to be identified of the transformer oil;
the identification module is used for carrying out region identification on the sample image through image segmentation and determining a target sample image in a target region where the transformer oil is subjected to water-soluble acid test;
the calculation module is used for inputting the target sample image in the target area into the trained target color space recognition model to calculate a target color parameter value;
and the comparison module is used for comparing the target color parameter value with a standard PH color card to determine the PH value of the water-soluble acid of the transformer oil.
In a third aspect, a technical solution provided in an embodiment of the present application is an electronic device, including: the method comprises the steps of any embodiment of a method for identifying the PH value of the water-soluble acid of the transformer oil, a memory, a processor and a computer program stored in the memory and capable of running on the processor.
In a fourth aspect, an embodiment of the present application further provides a computer readable storage medium, where a computer program is stored, where the computer program is executed by a processor to implement the steps in the method for identifying a PH value of a water-soluble acid of transformer oil in any one of the embodiments.
The application has the beneficial effects that: according to the method, the target recognition is carried out after preprocessing the image to be recognized of the transformer oil, the target sample image is obtained from the image to be recognized and is used as input data to be input into the trained target color space recognition model so as to calculate the target color parameter value of the target sample image, and the target color parameter value is compared with the standard PH color card, so that the PH value of the water-soluble acid of the transformer oil is obtained. According to the application, the target color parameter value is extracted through the target color space recognition model in the transformer oil water-soluble acid PH value recognition process, automatic recognition and measurement are realized by utilizing computer vision, the working efficiency and accuracy of transformer oil water-soluble acid PH value recognition are improved, and the transformer abnormal condition can be accurately judged.
The foregoing summary is merely an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more fully understood, and in order that the same or additional objects, features and advantages of the present application may be more fully understood.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to designate like parts throughout the figures.
FIG. 1 is a flow chart of a method for identifying the PH value of water-soluble acid of transformer oil provided by an embodiment of the application;
FIG. 2 is a schematic diagram of a device for identifying PH value of water-soluble acid of transformer oil according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail with reference to the accompanying drawings and examples, it being understood that the detailed description herein is merely a preferred embodiment of the present application, which is intended to illustrate the present application, and not to limit the scope of the application, as all other embodiments obtained by those skilled in the art without making any inventive effort fall within the scope of the present application.
Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart depicts operations (or steps) as a sequential process, many of the operations (or steps) can be performed in parallel, concurrently, or at the same time. Furthermore, the order of the operations may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figures; the processes may correspond to methods, functions, procedures, subroutines, and the like.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. It should also be understood that, in various embodiments of the present application, the sequence number of each process does not mean the order of execution, and the order of execution of each process should be determined by its functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.
It should be understood that in the present application, "plurality" means two or more. "and/or" is merely a variable relationship describing an associated object, meaning that there may be three relationships, e.g., and/or B, may represent: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. "comprising A, B and C", "comprising A, B, C" means that all three of A, B, C comprise, "comprising A, B or C" means that one of the three comprises A, B, C, and "comprising A, B and/or C" means that any 1 or any 2 or 3 of the three comprises A, B, C.
It should be understood that in the present application, "B corresponding to a", "a corresponding to B", or "B corresponding to a" means that B is associated with a, from which B can be determined. Determining B from a does not mean determining B from a alone, but may also determine B from a and/or other information. The matching of A and B is that the similarity of A and B is larger than or equal to a preset threshold value.
Example 1
Referring to fig. 1, fig. 1 is a flowchart of a method for identifying PH of water-soluble acid of transformer oil according to an embodiment of the present application. The method for identifying the PH value of the water-soluble acid of the transformer oil comprises the following steps:
s101, preprocessing an image to be identified of transformer oil;
s102, carrying out target recognition on the preprocessed image to be recognized, and determining a target sample image in a target area where transformer oil is subjected to a water-soluble acid test;
s103, inputting the target sample image in the target area into a trained target color space recognition model to calculate a target color parameter value;
s104, comparing the target color parameter value with a standard PH color card to determine the PH value of the water-soluble acid of the transformer oil.
The method for identifying the PH value of the transformer oil water-soluble acid can be used in a scene of power equipment abnormality judgment, and the electronic equipment running the method for identifying the PH value of the transformer oil water-soluble acid can communicate with other electronic equipment in a wireless connection/wired connection mode. It should be noted that the wireless connection includes, but is not limited to, a 4G/5G connection, a WiFi connection, a bluetooth connection, a WiMAX connection, a Zigbee connection, a UWB connection, and other wireless connection methods now known or developed in the future.
Specifically, in this embodiment, the transformer oil may be used as a coolant, and heat generated during operation of the transformer causes oil close to the iron core and the winding to expand and rise due to heating, and heat is dissipated through the radiator by up-down convection of the oil, so that normal operation of the transformer is ensured, and burnout of the transformer is avoided. The image to be identified can be acquired by an image acquisition device, before the acquisition, a test sample is obtained by testing transformer oil through water-soluble acid, and then the image acquisition device is used for acquiring the image of the test sample to obtain the image to be identified, for example: and shooting the test sample, and taking the shot image as an image to be identified. The image acquisition device comprises, but is not limited to, a camera, a video camera, a camera or other electronic devices with photographing function and capable of realizing data interaction. The image acquisition equipment can realize data interaction with the electronic equipment operated by the transformer oil water-soluble acid PH value identification, so that the acquired image to be identified is uploaded to the electronic equipment, and the electronic equipment is used for data processing.
More specifically, preprocessing the image to be identified of the transformer oil can include operations such as image denoising, image enhancement, image segmentation and the like, so that clearer and more accurate images can be obtained when target identification is performed. The image to be identified may include a test sample containing a transformer oil water-soluble acid PH, and a container or other irrelevant information for holding the test sample, for example: the image to be identified comprises a test sample, a containing cup filled with the test sample, a tabletop, the ground and the like. The target recognition can refer to recognizing the test sample in the image to be recognized, determining the target area of the test sample in the image to be recognized, and determining the image in the target area as the target sample image by determining the target area. Wherein the target sample image refers to an image for measurement identification.
The target color space recognition model represents a model constructed according to the HSV model for recognizing color parameters in the target sample image, and model parameters can be calculated through the target color space recognition model. Wherein, the model parameter h represents Hue, hue; s represents Saturation; v represents Value and brightness. The target color space identification model is obtained by performing continuous iterative model training based on images of n pieces of pre-acquired transformer oil subjected to water-soluble acid test, and when the iteration number reaches the preset iteration number or the model converges. Thus, the target color parameter value of the target sample image can be calculated by inputting the target sample image in the target region as input data into the trained target color space recognition model. And finally, comparing the calculated target color parameter value with a standard PH color card, so as to determine the PH color corresponding to the target color parameter value, and finally obtaining the PH value of the water-soluble acid of the transformer oil. The identification of the PH value of the water-soluble acid of the transformer oil can be performed in real time and can be performed regularly. The PH value of the transformer oil water-soluble acid can have a standard range, and when the PH value of the transformer oil water-soluble acid obtained by testing does not meet the standard range, the abnormal condition of the transformer can be rapidly found, thereby being beneficial to improving the maintenance efficiency of the transformer in the power equipment.
In the embodiment of the application, the target recognition is carried out after preprocessing an image to be recognized of transformer oil is firstly obtained, a target sample image is obtained from the image to be recognized and is used as input data to be input into a trained target color space recognition model so as to calculate a target color parameter value of the target sample image, and the target color parameter value is compared with a standard PH color card, so that the PH value of the water-soluble acid of the transformer oil is obtained. According to the application, the target color parameter value is extracted through the target color space recognition model in the transformer oil water-soluble acid PH value recognition process, automatic recognition and measurement are realized by utilizing computer vision, the working efficiency and accuracy of transformer oil water-soluble acid PH value recognition are improved, and the transformer abnormal condition can be accurately judged.
Optionally, step S101 is as follows: the preprocessing of the image to be identified of the transformer oil comprises the following steps:
s1011, denoising the image to be identified of the transformer oil, and removing interference information in the image to be identified;
s1012, carrying out image enhancement and region segmentation on the denoised image to be identified to obtain a preprocessed image to be identified.
Specifically, in order to obtain a high-quality image, the image to be identified may be denoised, the integrity of original information in the image to be identified may be maintained by denoising, and interference information unrelated to the image to be identified may be removed, for example: ground, desktop or some other irrelevant information in the image to be identified is removed by denoising. Denoising methods include, but are not limited to, arithmetic mean filtering, gaussian filtering, statistical median filtering, bilateral filtering, and the like. Also, in order to acquire a clearer image, image enhancement is further included in the image to be recognized, and the image enhancement includes brightness, definition, contrast, and the like of the image to be recognized. The visual effect of the image can be improved by image enhancement, converting the image into a form more suitable for analysis and processing by the machine. At the same time, the image to be identified can be segmented into areas, for example: dividing the image to be identified into M multiplied by N matrix blocks, or respectively labeling the images with different gray values in the image to be identified by rectangular frames. After the region division, the rapid target identification is facilitated.
Optionally, step S102 is as follows: target identification is carried out on the preprocessed image to be identified, and a target sample image in a target area where transformer oil is located after water-soluble acid testing is determined, wherein the target sample image comprises the following components:
s1021, extracting the RGB value of the preprocessed image to be identified and the edge characteristics of the test sample in the image to be identified;
s1022, determining a target area where transformer oil in the image to be identified is subjected to water-soluble acid test according to the edge characteristics, taking the image in the target area as the target sample image, and taking the RGB value of the image in the target area as the RGB value of the template sample image.
Specifically, the target recognition of the preprocessed image to be recognized can be realized through an image segmentation algorithm. Image segmentation algorithms include, but are not limited to, VGGNet (Visual Geometry Group Network) algorithms, R-CNN (Region-based Convolutional Neural Network) algorithms, FCN (Fully Convolutional Network) algorithms, and the like. As a possible implementation manner, based on the relative rule of the edges of the test sample contained in the container in the image to be identified, the gray value of the contact edge of the container and the test sample is discontinuous, so that the edge characteristics of the test sample can be extracted through an edge detection algorithm. And detecting the edge of the target area in the image based on the edge characteristics, and then sequentially connecting the edges in all directions to form the target area by combining the spatial variation relation of the pixel points at the edge. The spatial variation relation describes the condition that the gray values of two different areas at the edge are continuous, discontinuous or jumped, and the gray values of the contact edges of the container and the test sample in the image to be identified are discontinuous or even jumped. After the target area is determined, the image within the target area may be taken as the target sample image. In addition, the RGB values of the image to be identified can be extracted, the RGB values of the whole image to be identified can be extracted before the target area is determined, and the RGB values outside the target area are screened after the target area is determined. After the target area is determined, the RGB values of the target sample image may be extracted, and the RGB values obtained finally may be used as the RGB values of the target sample image. Wherein, extracting after determining the target area can reduce the extraction area and reduce the workload.
Optionally, step S103 is described above: the inputting the target sample image in the target area into the trained target color space recognition model to calculate the target color parameter value comprises the following steps:
s1031, inputting a target sample image in the target area into the trained target color space recognition model, wherein model parameters of the target color space recognition model comprise hue, saturation and brightness;
s1032, reading RGB values of the target sample image in the target area;
s1033, converting the RGB values of the target sample image into target color parameter values, and taking the converted target color parameter values corresponding to the RGB values of the target sample image as target color parameter values.
Specifically, the model parameters identified based on the constructed target color space identification model are not RGB values, so that the RGB values of the target sample image in the target area can be read and converted into target color parameter values in the HSV space, the coordinates of the target color parameter values are expressed as (h, s, v), and a specific conversion formula is shown in the following formula (1):
v＝max(r,g,b)
wherein (r, g, b) represents coordinates of RGB values of the target sample image, max represents a maximum value of r, g, and b, min represents a maximum value of r, g, and b, v represents brightness in the model parameter, s represents saturation in the model parameter, and h represents hue angle of hue in the model parameter.
The value of each coordinate in (r, g, b) is a real number between 0 and 1, the hue h is measured by an angle h e [0 °,360 °), calculated in a counterclockwise direction from red, red is 0 °, green is 120 °, blue is 240 °, the respective complementary colors are yellow 60 °, cyan is 180 °, and magenta is 300 °. The upper value range of s is 0.0-1.0, and the larger the value is, the more saturated the color is. The range of the brightness v is 0 (black) to 255 (white), and when represents a condition to be satisfied.
Based on the above formula (1), RGB values of the target sample image may be converted into corresponding target color parameter values by the target color space recognition model, and the converted target color parameter values corresponding to the RGB values of the target sample image may be used as the target color parameter values.
In this embodiment, the RGB values of the target sample image are converted to obtain corresponding HSV values (target color parameter values) by inputting the target sample image as input data into the trained target color space recognition model, and finally the HSV values are compared with the standard PH color card, so as to obtain the PH value of the transformer oil water-soluble acid. According to the application, the target color parameter value is extracted through the target color space recognition model in the transformer oil water-soluble acid PH value recognition process, automatic recognition and measurement are realized by utilizing computer vision image recognition, recognition errors caused by manual recognition are avoided, the working efficiency and accuracy of the transformer oil water-soluble acid PH value are improved, the transformer is favorably and accurately judged whether abnormal conditions exist, and the maintenance efficiency of power equipment is improved.
Optionally, step S104 is as follows: and comparing the target color parameter value with a standard PH color card to determine the PH value of the water-soluble acid of the transformer oil, wherein the method comprises the following steps:
s1041, comparing the calculated brightness, saturation and hue angle of the hue with the brightness, saturation and hue angle of each color in the standard PH color chart respectively, and determining that the target color parameter value corresponds to the color in the standard PH color chart;
s1042, determining the PH value of the transformer oil water-soluble acid according to the corresponding color of the target color parameter value in the standard PH color card.
Specifically, each color in the standard PH chart corresponds to a standard hue angle of brightness, saturation, and hue, and each color corresponds to a PH value or a PH range. Therefore, the calculated brightness, saturation and hue angle of the target sample image can be respectively compared with the standard PH color card, the corresponding color of the target color parameter value in the standard PH color card can be finally determined, and the PH value of the transformer oil water-soluble acid can be obtained according to the corresponding color. By calculating the same parameters as the PH color card and comparing, the corresponding color can be more accurately identified so as to obtain the more accurate PH value of the transformer oil water-soluble acid.
Example two
As shown in fig. 2, fig. 2 is a device for identifying PH of water-soluble acid of transformer oil, which is provided corresponding to a method for identifying PH of water-soluble acid of transformer oil, and the device 20 includes:
the preprocessing module 201 is used for preprocessing an image to be identified of the transformer oil;
the identification module 202 is used for carrying out region identification on the sample image through image segmentation and determining a target sample image in a target region where the transformer oil is subjected to a water-soluble acid test;
a calculation module 203, configured to input the target sample image in the target area into a trained target color space recognition model to calculate a target color parameter value;
and the comparison module 204 is used for comparing the target color parameter value with a standard PH color card to determine the PH value of the water-soluble acid of the transformer oil.
Optionally, the computing module 203 includes:
an input submodule 2031 for inputting a target sample image in the target area into the trained target color space recognition model, wherein model parameters of the target color space recognition model include hue, saturation and brightness;
a reading submodule 2032 for reading RGB values of a target sample image in the target area;
the conversion submodule 2033 is configured to convert the RGB values of the target sample image into target color parameter values, and take the converted target color parameter values corresponding to the RGB values of the target sample image as target color parameter values.
Optionally, the conversion submodule 2033 converts the RGB values of the target sample image into corresponding target color parameter values according to the following conversion formula:
v＝max(r,g,b)
wherein (r, g, b) represents coordinates of RGB values of the target sample image, max represents a maximum value of r, g, and b, min represents a maximum value of r, g, and b, v represents brightness in the model parameter, s represents saturation in the model parameter, and h represents hue angle of hue in the model parameter.
Optionally, the comparing module 204 includes:
a comparing sub-module 2041, configured to compare the brightness, the saturation, and the hue angle of the hue calculated based on the conversion formula with the brightness, the saturation, and the hue angle of the hue of each color in the standard PH color chart, respectively, and determine that the target color parameter value corresponds to the color in the standard PH color chart;
and the determining submodule 2042 is used for determining the PH value of the transformer oil water-soluble acid according to the corresponding color of the target color parameter value in the standard PH color card.
Optionally, the apparatus 20 further includes:
the testing module 205 is configured to test the transformer oil with water-soluble acid to obtain a test sample of the PH value of the water-soluble acid of the transformer oil;
and the acquisition module 206 is used for acquiring the test sample through image acquisition equipment to obtain the image to be identified.
Optionally, the preprocessing module 201 includes:
the denoising submodule 2011 is used for denoising the image to be identified of the transformer oil and removing interference information in the image to be identified;
the image enhancement and segmentation sub-module 2012 is configured to perform image enhancement and region segmentation on the denoised image to be identified to obtain a preprocessed image to be identified.
Optionally, the identification module 202 includes:
an extraction submodule 2021, configured to extract the RGB values of the preprocessed image to be identified and edge features of a test sample in the image to be identified;
and a target area selection submodule 2022, configured to determine a target area where transformer oil in the image to be identified is located after a water-soluble acid test is performed according to the edge feature, take an image in the target area as the target sample image, and take an RGB value of the image in the target area as an RGB value of the template sample image.
The device for identifying the PH value of the water-soluble acid of the transformer oil provided by the embodiment of the application can realize all the processes realized by the method for identifying the PH value of the water-soluble acid of the transformer oil in the method embodiment, and can achieve the same beneficial effects. In order to avoid repetition, a description thereof is omitted.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application, as shown in fig. 3, including: memory 302, processor 301 and a computer program stored on memory 302 and operable on processor 301 for a method of identifying the PH of a water-soluble acid of transformer oil for an integrated inspection regulation platform, wherein:
the processor 301 is configured to call a computer program stored in the memory 302, and perform the following steps:
preprocessing an image to be identified of transformer oil;
performing target recognition on the preprocessed image to be recognized, and determining a target sample image in a target area where transformer oil is subjected to water-soluble acid test;
inputting the target sample image in the target area into a trained target color space recognition model to calculate a target color parameter value;
and comparing the target color parameter value with a standard PH color card to determine the PH value of the water-soluble acid of the transformer oil.
Optionally, the inputting the target sample image in the target area into the trained target color space recognition model by the processor 301 calculates a target color parameter value, including:
inputting a target sample image in the target area into the trained target color space recognition model, wherein model parameters of the target color space recognition model comprise hue, saturation and brightness;
reading RGB values of a target sample image in the target area;
and converting the RGB values of the target sample image into target color parameter values, and taking the target color parameter values corresponding to the RGB values of the target sample image obtained through conversion as target color parameter values.
Optionally, the converting, performed by the processor 301, the RGB values of the target sample image into corresponding target color parameter values is as follows:
v＝max(r,g,b)
wherein (r, g, b) represents coordinates of RGB values of the target sample image, max represents a maximum value of r, g, and b, min represents a maximum value of r, g, and b, v represents brightness in the model parameter, s represents saturation in the model parameter, and h represents hue angle of hue in the model parameter.
Optionally, the determining, by the processor 301, the PH value of the water-soluble acid of the transformer oil according to comparing the target color parameter value with a standard PH color chart includes:
comparing the calculated brightness, saturation and hue angle of the hue with the brightness, saturation and hue angle of each color in the standard PH color card respectively, and determining that the target color parameter value corresponds to the color in the standard PH color card;
and determining the PH value of the water-soluble acid of the transformer oil according to the corresponding color of the target color parameter value in the standard PH color card.
Optionally, before the preprocessing the image to be identified of the transformer oil, the processor 301 is further configured to perform: further comprises:
testing the transformer oil through water-soluble acid to obtain a test sample of the PH value of the water-soluble acid of the transformer oil;
and acquiring the test sample through image acquisition equipment to obtain the image to be identified.
Optionally, the preprocessing the image to be identified of the transformer oil performed by the processor 301 includes:
denoising the image to be identified of the transformer oil, and removing interference information in the image to be identified;
and carrying out image enhancement and region segmentation on the denoised image to be identified to obtain a preprocessed image to be identified.
Optionally, the target recognition of the preprocessed image to be recognized by the processor 301 determines a target sample image in a target area where the transformer oil is subjected to the water-soluble acid test, including:
extracting the RGB value of the preprocessed image to be identified and the edge characteristics of the test sample in the image to be identified; and determining a target area where transformer oil in the image to be identified is subjected to water-soluble acid test according to the edge characteristics, taking the image in the target area as the target sample image, and taking the RGB value of the image in the target area as the RGB value of the template sample image.
The electronic equipment provided by the embodiment of the application can realize all the processes realized by the transformer oil water-soluble acid PH value identification method in the method embodiment, and can achieve the same beneficial effects. In order to avoid repetition, a description thereof is omitted.
It should be noted that, as those skilled in the art will appreciate, the electronic device herein is a device capable of automatically performing numerical calculation and/or information processing according to a predetermined or stored instruction, and its hardware includes, but is not limited to, a microprocessor, an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a Programmable gate array (FPGA), a digital processor (Digital Signal Processor, DSP), an embedded device, and the like. The electronic device may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, and the like. The electronic equipment can perform man-machine interaction in a mode of a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.
The embodiment of the application also provides a computer readable storage medium, and a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the process of the method for identifying the PH value of the transformer oil water-soluble acid provided by the embodiment of the application is realized, and the same technical effect can be achieved, so that repetition is avoided, and the description is omitted.
The readable storage medium includes flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the memory may be an internal storage unit of the electronic device, such as a hard disk or a memory of the electronic device. In other embodiments, the memory may also be an external storage device of the electronic device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like. Of course, the memory may also include both internal storage units of the electronic device and external storage devices. In this embodiment, the memory is generally used to store the operating device installed in the electronic device and various application software, such as a program code of a method for identifying PH of water-soluble acid of transformer oil. In addition, the memory can be used to temporarily store various types of data that have been output or are to be output.
Those skilled in the art will appreciate that the processes implementing all or part of the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, and the program may be stored in a computer readable storage medium, and the program may include the processes of the embodiments of the methods as above when executed. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM) or the like.
The above embodiments are preferred embodiments of a method for identifying PH of water-soluble acid of transformer oil according to the present application, and are not intended to limit the scope of the present application, which includes but is not limited to the present embodiments, and all equivalent changes in shape and structure according to the present application are within the scope of the present application.
Claims (10)
1. The method for identifying the PH value of the water-soluble acid of the transformer oil is characterized by comprising the following steps of:
preprocessing an image to be identified of transformer oil;
performing target recognition on the preprocessed image to be recognized, and determining a target sample image in a target area where transformer oil is subjected to water-soluble acid test;
inputting the target sample image in the target area into a trained target color space recognition model to calculate a target color parameter value;
and comparing the target color parameter value with a standard PH color card to determine the PH value of the water-soluble acid of the transformer oil.
2. The method for identifying the PH value of the water-soluble acid of the transformer oil according to claim 1, wherein the step of inputting the target sample image in the target area into the trained target color space identification model to calculate the target color parameter value comprises the steps of:
inputting a target sample image in the target area into the trained target color space recognition model, wherein model parameters of the target color space recognition model comprise hue, saturation and brightness;
reading RGB values of a target sample image in the target area;
and converting the RGB values of the target sample image into target color parameter values, and taking the target color parameter values corresponding to the RGB values of the target sample image obtained through conversion as target color parameter values.
3. The method for identifying the PH value of the water-soluble acid of the transformer oil according to claim 2, wherein the conversion formula of converting the RGB value of the target sample image into the corresponding target color parameter value is as follows:
v＝max(r，g，b)
wherein (r, g, b) represents coordinates of RGB values of the target sample image, max represents a maximum value of r, g, and b, min represents a maximum value of r, g, and b, v represents brightness in the model parameter, s represents saturation in the model parameter, and h represents hue angle of hue in the model parameter.
4. The method for identifying the PH value of the water-soluble acid of the transformer oil according to claim 3, wherein the step of comparing the target color parameter value with a standard PH chart to determine the PH value of the water-soluble acid of the transformer oil comprises the following steps: comparing the calculated brightness, saturation and hue angle of the hue with the brightness, saturation and hue angle of each color in the standard PH color card respectively, and determining that the target color parameter value corresponds to the color in the standard PH color card;
and determining the PH value of the water-soluble acid of the transformer oil according to the corresponding color of the target color parameter value in the standard PH color card.
5. The method for identifying the PH of a water-soluble acid of transformer oil according to any one of claims 1 to 4, further comprising, before the preprocessing of the image to be identified of transformer oil:
testing the transformer oil through water-soluble acid to obtain a test sample of the PH value of the water-soluble acid of the transformer oil;
and acquiring the test sample through image acquisition equipment to obtain the image to be identified.
6. The method for identifying the PH value of water-soluble acid in transformer oil according to any one of claims 1 to 4, wherein the preprocessing of the image to be identified of transformer oil comprises:
denoising the image to be identified of the transformer oil, and removing interference information in the image to be identified;
and carrying out image enhancement and region segmentation on the denoised image to be identified to obtain a preprocessed image to be identified.
7. The method for identifying the PH value of water-soluble acid in transformer oil according to any one of claims 1 to 4, wherein the step of performing target identification on the preprocessed image to be identified to determine a target sample image in a target area of the transformer oil after the water-soluble acid test comprises the steps of:
extracting the RGB value of the preprocessed image to be identified and the edge characteristics of the test sample in the image to be identified;
and determining a target area where transformer oil in the image to be identified is subjected to water-soluble acid test according to the edge characteristics, taking the image in the target area as the target sample image, and taking the RGB value of the image in the target area as the RGB value of the template sample image.
8. A transformer oil water-soluble acid PH identification device, the device comprising:
the pretreatment module is used for carrying out pretreatment on an image to be identified of the transformer oil;
the identification module is used for carrying out region identification on the sample image through image segmentation and determining a target sample image in a target region where the transformer oil is subjected to water-soluble acid test;
the calculation module is used for inputting the target sample image in the target area into the trained target color space recognition model to calculate a target color parameter value;
and the comparison module is used for comparing the target color parameter value with a standard PH color card to determine the PH value of the water-soluble acid of the transformer oil.
9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of a method for identifying the PH of a water-soluble acid of transformer oil according to any one of claims 1 to 7 when the computer program is executed by the processor.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of a method for identifying the PH of a transformer oil water-soluble acid according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310915825.5A CN117173258A (en) | 2023-07-25 | 2023-07-25 | Method and device for identifying PH value of water-soluble acid of transformer oil and related equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310915825.5A CN117173258A (en) | 2023-07-25 | 2023-07-25 | Method and device for identifying PH value of water-soluble acid of transformer oil and related equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117173258A true CN117173258A (en) | 2023-12-05 |
Family
ID=88940193
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310915825.5A Pending CN117173258A (en) | 2023-07-25 | 2023-07-25 | Method and device for identifying PH value of water-soluble acid of transformer oil and related equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117173258A (en) |
-
2023
- 2023-07-25 CN CN202310915825.5A patent/CN117173258A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111028213B (en) | Image defect detection method, device, electronic equipment and storage medium | |
| WO2021000524A1 (en) | Hole protection cap detection method and apparatus, computer device and storage medium | |
| CN111008597B (en) | Space identification method and device for CAD drawing, electronic equipment and storage medium | |
| US10824906B2 (en) | Image processing device, non-transitory computer readable storage medium, and image processing system | |
| WO2017181724A1 (en) | Inspection method and system for missing electronic component | |
| CN109685075A (en) | A kind of power equipment recognition methods based on image, apparatus and system | |
| CN110596120A (en) | Glass boundary defect detection method, device, terminal and storage medium | |
| WO2020173177A1 (en) | Object color difference defect detection method, device, computer device, and storage medium | |
| CN109911481B (en) | Cabin frame target visual identification and positioning method and system for metallurgical robot plugging | |
| Laga et al. | Image-based plant stornata phenotyping | |
| CN102706274A (en) | System for accurately positioning mechanical part by machine vision in industrially-structured scene | |
| CN110598795A (en) | Image difference detection method and device, storage medium and terminal | |
| DK2447884T3 (en) | A method for the detection and recognition of an object in an image and an apparatus and a computer program therefor | |
| WO2021046726A1 (en) | Method and device for detecting mechanical equipment parts | |
| CN111598913A (en) | Image segmentation method and system based on robot vision | |
| CN113469971B (en) | Image matching method, detection device and storage medium | |
| US11922680B2 (en) | Image determination device, image determination method, and non-transitory computer readable medium storing program | |
| CN117173258A (en) | Method and device for identifying PH value of water-soluble acid of transformer oil and related equipment | |
| CN114782822A (en) | Method and device for detecting state of power equipment, electronic equipment and storage medium | |
| KR101944604B1 (en) | Apparatus and method for inspection automation to count object quantity | |
| CN115546141A (en) | Small sample Mini LED defect detection method and system based on multi-dimensional measurement | |
| CN116993654A (en) | Camera module defect detection method, device, equipment, storage medium and product | |
| CN115115596A (en) | Electronic component detection method and device and automatic quality inspection equipment | |
| CN114820707A (en) | Calculation method for camera target automatic tracking | |
| CN114581536A (en) | Image color difference detection method based on feature perception and multi-channel 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 |