Temperature curve splicing method and system for super-long string disc-shaped suspension porcelain insulators

Abstract

The present application discloses a temperature curve splicing method and system for an ultra-long string of disc-shaped suspension porcelain insulators, belonging to the technical field of power transmission lines; the method comprises: obtaining a first infrared image and a second infrared image corresponding to a first target position and a second target position in an ultra-long string of disc-shaped suspension porcelain insulators; preprocessing the first infrared image and the second infrared image to obtain a first binary image and a second binary image corresponding thereto; obtaining a corresponding first temperature curve and a second temperature curve; optimizing the first temperature curve and the second temperature curve to obtain a corresponding first optimized temperature curve and a second optimized temperature curve; calculating a splicing point between the first optimized temperature curve and the second optimized temperature curve according to a window variance algorithm, so as to splice the first optimized temperature curve and the second optimized temperature curve according to the splicing point; finding the splicing point by using the window variance algorithm, so as to make the spliced ​​temperature curve more accurate.

Description

Technical Field

[0001] The present application belongs to the technical field of power transmission lines, and in particular relates to a temperature curve splicing method and system for super-long string disc-shaped suspension porcelain insulators. Background Art

[0002] The zero-value detection methods for high-voltage porcelain insulators mainly include spark gap method, insulation resistance method, voltage distribution method, infrared thermal imaging method, ultraviolet imaging method, etc.; among them, infrared detection is a safe and effective detection method. It can detect zero-value porcelain insulators without contact or power off, and has high safety. In addition, it can quickly obtain results and is suitable for large-scale inspections. The temperature distribution on the surface of the insulator is detected by an infrared thermal imager to find abnormal temperature areas to determine the possible existence of zero-value insulators. Since the length of the extra-long string of disc-shaped suspended porcelain insulators is too long, the pixel value of the infrared thermal imager is not high, and it is impossible to take an infrared image of the entire string of porcelain insulators, and thus it is impossible to directly obtain the temperature curve of the entire string of insulators.

[0003] At present, the temperature curve of an extra-long string of disc-shaped suspension porcelain insulators is usually obtained by taking two infrared images of the extra-long string of disc-shaped suspension porcelain insulators, obtaining two sections of the temperature curve of the insulator, and then splicing the two sections of the curve to obtain the temperature curve of the entire string of insulators; however, the precise connection point cannot be obtained during the splicing process, resulting in inaccurate temperature curves after splicing. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a temperature curve splicing method and system for an ultra-long string of disc-shaped suspension porcelain insulators, which can solve the technical problem that the temperature curve in the prior art often cannot obtain accurate connection points during the splicing process, resulting in inaccurate temperature curves after splicing.

[0005] In order to solve the above technical problems, this application is implemented as follows:

[0006] In a first aspect, an embodiment of the present application provides a temperature curve splicing method for an ultra-long string of disc-shaped suspension porcelain insulators, the method comprising:

[0007] Acquire a first infrared image corresponding to a first target position in the super-long string of disc-shaped suspension porcelain insulators and a second infrared image corresponding to a second target position, wherein the first target position and the second target position partially overlap;

[0008] Preprocessing the first infrared image to obtain a first binary image containing only a first trunk portion of the super-long string of disc-shaped suspension porcelain insulators, and preprocessing the second infrared image to obtain a second binary image containing only a second trunk portion of the super-long string of disc-shaped suspension porcelain insulators;

[0009] Acquire a first backbone line including a first steel cap surface in the first trunk portion according to the first binary image, and acquire a second backbone line including a second steel cap surface in the second trunk portion according to the second binary image;

[0010] Acquire a first temperature curve corresponding to the first target position according to the first backbone line, and acquire a second temperature curve corresponding to the second target position according to the second backbone line;

[0011] Optimizing the first temperature curve and the second temperature curve to obtain a corresponding first optimized temperature curve and a second optimized temperature curve, wherein the first optimized temperature curve partially overlaps with the second optimized temperature curve;

[0012] A splicing point between the first optimized temperature curve and the second optimized temperature curve is calculated according to a window variance algorithm, so as to splice the first optimized temperature curve and the second optimized temperature curve according to the splicing point.

[0013] As an optional implementation manner of the first aspect of the present application, the first infrared image is preprocessed to obtain a first binary image containing only the first trunk portion of the super-long string of disc-shaped suspension porcelain insulators, and the second infrared image is preprocessed to obtain a second binary image containing only the second trunk portion of the super-long string of disc-shaped suspension porcelain insulators; specifically:

[0014] Automatically selecting a threshold value according to an Ostu algorithm to process the first infrared image and the second infrared image;

[0015] Marking all connected domains in the first infrared image and the second infrared image after being processed by the Ostu algorithm;

[0016] The first infrared image after the connected domain is marked is processed according to the expansion corrosion method to obtain the first binary image containing only the first trunk part of the long string of disc-shaped suspension porcelain insulators. The second infrared image after the connected domain is marked is processed according to the expansion corrosion method to obtain the second binary image containing only the second trunk part of the long string of disc-shaped suspension porcelain insulators.

[0017] As an optional implementation of the first aspect of the present application, the first backbone line including the first steel cap disk surface in the first trunk part is obtained according to the first binary image, and the second backbone line including the second steel cap disk surface in the second trunk part is obtained according to the second binary image; specifically:

[0018] Processing the first binary image according to a skeletonization processing method in an image morphology processing manner to obtain the first trunk portion of the first binary image, and processing the second binary image according to a skeletonization processing method in an image morphology processing manner to obtain the second trunk portion of the second binary image;

[0019] The midlines of the first trunk portion and the second trunk portion are the corresponding first backbone line and the second backbone line;

[0020] Selecting a portion of the first backbone line including the first steel cap surface and a portion of the second backbone line including the second steel cap surface;

[0021] The first backbone line including the first steel cap plate in the first backbone part and the second backbone line including the second steel cap plate in the second backbone part are obtained.

[0022] As an optional implementation of the first aspect of the present application, the first temperature curve and the second temperature curve are optimized to obtain corresponding first optimized temperature curve and second optimized temperature curve; specifically:

[0023] Smoothing the first temperature curve and the second temperature curve according to a smoothing algorithm to delete short-term fluctuation data in the first temperature curve and the second temperature curve;

[0024] Performing filtering processing on the first temperature curve and the second temperature curve after the smoothing processing to remove noise data in the first temperature curve and the second temperature curve;

[0025] performing an offset process on the first temperature curve and the second temperature curve after the filtering process according to an offset algorithm, so as to reduce an error generated when acquiring the first temperature curve and the second temperature curve;

[0026] The first optimized temperature curve after the first temperature curve is optimized is obtained, and the second optimized temperature curve after the second temperature curve is optimized is obtained.

[0027] As an optional implementation of the first aspect of the present application, the specific formula of the smoothing algorithm is as follows:

[0028] ;

[0029] in, represents the smoothed temperature value of the i-th point, represents the actual temperature value of the i-th point, i represents the i-th point in the temperature curve, and n represents the total number of points in the temperature curve;

[0030] The specific formula of the offset algorithm is as follows:

[0031] ;

[0032] in, represents the average temperature of the first temperature curve, represents the average temperature of the second temperature curve, Indicates the offset factor.

[0033] As an optional implementation manner of the first aspect of the present application, the splicing point between the first optimized temperature curve and the second optimized temperature curve is calculated according to the window variance algorithm, so as to splice the first optimized temperature curve and the second optimized temperature curve according to the splicing point; specifically:

[0034] Setting a plurality of first windows on the overlapping portion of the first optimized temperature curve and the second optimized temperature curve, and setting a plurality of second windows having the same size as the first windows on the overlapping portion of the second optimized temperature curve and the first optimized temperature curve;

[0035] Calculate the first variance corresponding to each of the first windows and the second variance corresponding to each of the second windows respectively according to the variance operation;

[0036] Finding a first target window and a second target window, wherein the first target window is the first window corresponding to the minimum value in the first variance, and the second target window is the second window corresponding to the minimum value in the second variance;

[0037] splicing the first optimized temperature curve and the second optimized temperature curve according to the positions of the first target window and the second target window to obtain a spliced ​​temperature curve;

[0038] Calculating whether the number of spliced ​​insulators corresponding to the splicing temperature curve meets the actual number of insulators according to the periodogram analysis, if the number of spliced ​​insulators meets the actual number of insulators, the first target window and the second target window are the splicing points;

[0039] If the number of the spliced ​​insulators does not meet the actual number of insulators, the first target window and the second target window are eliminated, and the search continues until a new first target window and a new second target window are found.

[0040] As an optional implementation manner of the first aspect of the present application, the variance operation is specifically:

[0041] ;

[0042] in, represents the variance of the c-th window, represents the temperature of the i-th point in the c-th window, represents the average temperature of the cth window, and m is the area of ​​the window.

[0043] In a second aspect, an embodiment of the present application provides a temperature curve splicing system for an ultra-long string of disc-shaped suspension porcelain insulators, the system comprising:

[0044] A first acquisition module is used to acquire a first infrared image corresponding to a first target position and a second infrared image corresponding to a second target position in the super-long string of disc-shaped suspension porcelain insulators, wherein the first target position and the second target position partially overlap;

[0045] A preprocessing module is used to preprocess the first infrared image to obtain a first binary image containing only a first trunk portion of the super-long string of disc-shaped suspension porcelain insulators, and to preprocess the second infrared image to obtain a second binary image containing only a second trunk portion of the super-long string of disc-shaped suspension porcelain insulators;

[0046] A second acquisition module is used to acquire a first backbone line including a first steel cap disk surface in the first trunk part according to the first binary image, and to acquire a second backbone line including a second steel cap disk surface in the second trunk part according to the second binary image;

[0047] a third acquisition module, configured to acquire a first temperature curve corresponding to the first target position according to the first backbone line, and acquire a second temperature curve corresponding to the second target position according to the second backbone line;

[0048] an optimization module, configured to optimize the first temperature curve and the second temperature curve to obtain a corresponding first optimized temperature curve and a second optimized temperature curve, wherein the first optimized temperature curve partially overlaps with the second optimized temperature curve;

[0049] A processing module is used to calculate a splicing point between the first optimized temperature curve and the second optimized temperature curve according to a window variance algorithm, so as to splice the first optimized temperature curve and the second optimized temperature curve according to the splicing point.

[0050] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method described in the first aspect.

[0051] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0052] In the embodiment of the present application, through infrared imaging technology and image preprocessing, the temperature distribution information of the insulator can be accurately obtained, avoiding the errors caused by contact temperature measurement in the traditional method; by using backbone line extraction and temperature curve optimization processing, the influence of noise and outliers is reduced, and the reliability and accuracy of the temperature curve are improved; the method can realize the splicing of temperature curves of ultra-long string disc-shaped suspension porcelain insulators, providing an effective technical means for online monitoring of long-distance transmission lines; by finding the splicing point through the window variance algorithm, the spliced ​​temperature curve can be made more accurate, so that potential overheating fault points can be more accurately discovered, providing a strong guarantee for the safe operation of the power system; through the automated and intelligent splicing method, manual intervention is reduced, monitoring efficiency is improved, and operation and maintenance costs are reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a flow chart of a temperature curve splicing method of an ultra-long string of disc-shaped suspension porcelain insulators provided in some embodiments of the present application. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0055] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here. In addition, the "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally represents that the objects associated with each other are in an "or" relationship.

[0056] In conjunction with the accompanying drawings, a temperature curve splicing method and system for an ultra-long string of disc-shaped suspension porcelain insulators provided in an embodiment of the present application are described in detail through specific embodiments and application scenarios.

[0057] Example

[0058] A temperature curve splicing method for super-long string disc-shaped suspension porcelain insulators comprises the following steps:

[0059] S100: Acquire a first infrared image corresponding to a first target position in an ultra-long string of disc-shaped suspension porcelain insulators, and a second infrared image corresponding to a second target position;

[0060] Wherein, the first target position and the second target position partially overlap;

[0061] It should be understood that, by using infrared imaging technology, infrared images of two adjacent and partially overlapping target positions (a first target position and a second target position) in an ultra-long string of disc-shaped suspension porcelain insulators are obtained, namely, a first infrared image and a second infrared image;

[0062] S200: preprocessing the first infrared image to obtain a first binary image containing only a first trunk portion of the super-long string of disc-shaped suspension porcelain insulators, and preprocessing the second infrared image to obtain a second binary image containing only a second trunk portion of the super-long string of disc-shaped suspension porcelain insulators;

[0063] It should be understood that the first infrared image and the second infrared image obtained in S100 are pre-processed to highlight the trunk part of the insulator; then, the trunk part of the insulator is separated from the background through image binarization processing to obtain binary image No. 1 and binary image No. 2, which respectively contain only the first trunk part and the second trunk part of the insulator.

[0064] Further, in S200, the first infrared image is preprocessed to obtain a first binary image containing only the first trunk portion of the super-long string of disc-shaped suspension porcelain insulators, and the second infrared image is preprocessed to obtain a second binary image containing only the second trunk portion of the super-long string of disc-shaped suspension porcelain insulators; specifically:

[0065] S210: automatically selecting a threshold value according to the Ostu algorithm to process the first infrared image and the second infrared image;

[0066] S220: marking all connected domains in the first infrared image and the second infrared image after the Ostu algorithm processing;

[0067] S230: Process the first infrared image after the connected domain is marked according to the expansion corrosion method to obtain a first binary image containing only the first trunk part of the long string of disc-shaped suspension porcelain insulators, and process the second infrared image after the connected domain is marked according to the expansion corrosion method to obtain a second binary image containing only the second trunk part of the long string of disc-shaped suspension porcelain insulators.

[0068] It should be understood that, based on the above-mentioned feature definition, first, the Otsu algorithm is used to select the threshold of the first infrared image and the second infrared image; the Otsu algorithm is an adaptive threshold determination method, which can automatically find an optimal threshold according to the grayscale histogram of the image and divide the image into two parts, the foreground and the background. In this step, the Otsu algorithm will calculate a threshold so that the intra-class variance between the foreground (i.e., the trunk of the insulator) and the background is minimized, or equivalently, the inter-class variance is maximized; in this way, the trunk of the insulator can be effectively separated from the background; then, all connected domains in the image processed by the Otsu algorithm are marked; a connected domain refers to a set of interconnected pixels in an image, which have the same grayscale value or color. In this step, each pixel in the image will be traversed to find all connected domains and assign them unique labels; in this way, different parts of the insulator can be distinguished; finally, the image with connected domain marking is dilated and eroded. The dilation operation can expand the boundary of the object, while the erosion operation, on the contrary, will shrink the boundary of the object. In this step, the erosion operation is first used to remove small noise points or small connected parts in the image, and then the dilation operation is used to restore the eroded parts, but the shape of the object is kept basically unchanged; in this way, a binary image No. 1 containing only the first trunk part of the long string of disc-shaped suspended porcelain insulators and a binary image No. 2 containing only the second trunk part can be obtained.

[0069] It should be noted that the automatic selection of thresholds by the Otsu algorithm can avoid the subjectivity and uncertainty caused by manually setting the thresholds, and improve the accuracy of image segmentation; the connected domain marking and expansion and corrosion processing can effectively remove small noise points and small connected parts in the image, and reduce the impact of noise on subsequent processing; after preprocessing, the main part of the insulator in the image will become clearer and more prominent, which is conducive to the subsequent backbone line extraction and temperature curve acquisition; accurate preprocessing steps can provide a reliable basis for the subsequent temperature curve splicing, ensuring the accuracy and reliability of the splicing results.

[0070] S300: acquiring a first backbone line including a first steel cap surface in a first backbone portion according to the first binary image, and acquiring a second backbone line including a second steel cap surface in a second backbone portion according to the second binary image;

[0071] It should be understood that in the first binary image and the second binary image, the first backbone line including the first steel cap disk surface and the second backbone line including the second steel cap disk surface are extracted respectively, and these backbone lines represent the temperature distribution characteristics of the main part of the insulator.

[0072] Further, in S300, a first backbone line including a first steel cap disk surface in the first trunk part is obtained according to the first binary image, and a second backbone line including a second steel cap disk surface in the second trunk part is obtained according to the second binary image; specifically:

[0073] S310: processing the first binary image according to a skeletonization processing method in an image morphology processing manner to obtain a first trunk portion of the first binary image, and processing the second binary image according to a skeletonization processing method in an image morphology processing manner to obtain a second trunk portion of the second binary image;

[0074] S320: The midlines of the first trunk portion and the second trunk portion are the corresponding first backbone line and second backbone line;

[0075] S330: selecting a portion of the first backbone line including the first steel cap surface and a portion of the second backbone line including the second steel cap surface;

[0076] S340: Obtain a first backbone line including a first steel cap plate in the first trunk portion, and a second backbone line including a second steel cap plate in the second trunk portion.

[0077] It should be understood that, based on the above-mentioned feature definition, first, the skeletonization processing method in image morphology is applied to the first binary image and the second binary image; the skeletonization processing is a process of continuously stripping off the edge pixels of the image until only the "skeleton" of the image is left. In this step, the skeletonization processing will gradually strip off the pixels along the boundary of the object in the image until a long and thin line is formed. This line is the skeleton of the object, that is, the midline or backbone line of the object; after the skeletonization processing, the first trunk part and the second trunk part in the first binary image and the second binary image will be respectively Simplified into a long and thin line, namely the first backbone line and the second backbone line, these two backbone lines represent the center lines of the first trunk part and the second trunk part respectively, and are the basis for the subsequent temperature curve acquisition; on the first backbone line and the second backbone line, it is necessary to select the part containing the first steel cap disk surface and the second steel cap disk surface, which is achieved by identifying the area with specific shapes or features on the backbone line. In this step, image processing and recognition techniques, such as edge detection, shape matching, etc., can be used to identify the part containing the steel cap disk surface on the backbone line, which will be used for the subsequent temperature curve acquisition and splicing.

[0078] It should be noted that skeletonization can significantly simplify the image structure and simplify the complex shape of an object into a thin line, which is convenient for subsequent processing and analysis; the backbone line obtained by skeletonization can more accurately reflect the shape and position information of the object, thereby improving the accuracy of subsequent temperature curve acquisition; the simplified image structure can reduce the amount of calculation in subsequent processing and improve the processing speed; the skeletonization process has a certain robustness to noise and subtle changes in the image, and can reduce the impact of these factors on subsequent processing to a certain extent.

[0079] S400: Acquire a first temperature curve corresponding to a first target position according to the first backbone line, and acquire a second temperature curve corresponding to a second target position according to the second backbone line;

[0080] It should be understood that, based on the extracted backbone lines, the temperature curves corresponding to the first target position and the second target position, ie, the first temperature curve and the second temperature curve, are obtained using the temperature information in the infrared image.

[0081] S500: Optimizing the first temperature curve and the second temperature curve to obtain corresponding first optimized temperature curve and second optimized temperature curve;

[0082] Wherein, the first optimized temperature curve partially overlaps with the second optimized temperature curve;

[0083] It should be understood that the first temperature curve and the second temperature curve are optimized to reduce the influence of noise and outliers, thereby obtaining a first optimized temperature curve and a second optimized temperature curve; the two optimized temperature curves should be consistent in the partially overlapping area.

[0084] Furthermore, in S500, the first temperature curve and the second temperature curve are optimized to obtain corresponding first optimized temperature curve and second optimized temperature curve; specifically:

[0085] S510: Smoothing the first temperature curve and the second temperature curve according to a smoothing algorithm to delete short-term fluctuation data in the first temperature curve and the second temperature curve;

[0086] S520: performing filtering processing on the smoothed first temperature curve and the second temperature curve to remove noise data in the first temperature curve and the second temperature curve;

[0087] S530: performing an offset process on the first temperature curve and the second temperature curve after the filtering process according to an offset algorithm, so as to reduce an error generated when acquiring the first temperature curve and the second temperature curve;

[0088] S540: Obtaining a first optimized temperature curve after the first temperature curve is optimized, and a second optimized temperature curve after the second temperature curve is optimized.

[0089] Specifically, the specific formula of the smoothing algorithm in S510 is as follows:

[0090] ;

[0091] in, represents the smoothed temperature value of the i-th point, represents the actual temperature value of the i-th point, i represents the i-th point in the temperature curve, and n represents the total number of points in the temperature curve;

[0092] Specifically, the specific formula of the offset algorithm in S530 is as follows:

[0093] ;

[0094] in, represents the average temperature of the first temperature curve, represents the average temperature of the second temperature curve, Indicates the offset factor.

[0095] It should be understood that, based on the above-mentioned feature definition, first, a smoothing algorithm is applied to the first temperature curve and the second temperature curve; the purpose of the smoothing algorithm is to delete short-term fluctuation data in the curve, which is caused by measurement errors, environmental interference and other factors; the smoothing algorithm provided in this embodiment calculates the average value of adjacent data points to smooth the curve, thereby reducing short-term fluctuations; then, the first temperature curve and the second temperature curve after smoothing are filtered, and the purpose of the filtering process is to remove noise data in the curve, which is caused by sensor failure, signal interference and other factors; the filtering process can use various filters, such as low-pass filters, high-pass filters, band-pass filters, etc. For the temperature curve of this embodiment, a low-pass filter is usually used to remove high-frequency noise; finally, the first temperature curve and the second temperature curve after filtering are offset; the purpose of the offset process is to reduce the system error or offset that may be generated when acquiring the temperature curve; the offset algorithm provided in this embodiment can adjust the overall offset of the temperature curve according to the known standard temperature value or reference point, so that the temperature curve is closer to the true value.

[0096] It should be noted that smoothing and filtering can significantly reduce short-term fluctuations and noise data in the temperature curve, thereby improving the accuracy and reliability of the data; through smoothing and filtering, the overall trend of the temperature curve will be more obvious and stable, which is conducive to subsequent data analysis and processing; offset processing can reduce the systematic error or offset that may occur when acquiring the temperature curve, making the temperature curve closer to the true value, thereby improving the measurement accuracy; the temperature curve after optimization processing will be smoother and more stable, which is conducive to subsequent splicing, analysis and other work, and improves the overall processing efficiency.

[0097] S600: Calculating a splicing point between the first optimized temperature curve and the second optimized temperature curve according to a window variance algorithm, so as to splice the first optimized temperature curve and the second optimized temperature curve according to the splicing point;

[0098] It should be understood that the window variance algorithm is used to calculate the variance of the first optimized temperature curve and the second optimized temperature curve in the overlapping area, and the position with the smallest variance is found as the splicing point; the splicing point represents the most consistent position of the two temperature curves in the overlapping area; according to the determined splicing point, the first optimized temperature curve and the second optimized temperature curve are spliced ​​to obtain a complete temperature curve of the super-long string disc suspension porcelain insulator.

[0099] Further, in S600, the splicing point between the first optimized temperature curve and the second optimized temperature curve is calculated according to the window variance algorithm, so as to splice the first optimized temperature curve and the second optimized temperature curve according to the splicing point; specifically:

[0100] S610: setting a plurality of first windows on the overlapping portion of the first optimized temperature curve and the second optimized temperature curve, and setting a plurality of second windows having the same size as the first windows on the overlapping portion of the second optimized temperature curve and the first optimized temperature curve;

[0101] S620: Calculate the first variance corresponding to each first window and the second variance corresponding to each second window respectively according to the variance operation;

[0102] S630: Find a first target window and a second target window, where the first target window is a first window corresponding to a minimum value in the first variance, and the second target window is a second window corresponding to a minimum value in the second variance;

[0103] S640: splicing the first optimized temperature curve and the second optimized temperature curve according to positions of the first target window and the second target window to obtain a spliced ​​temperature curve;

[0104] S650: Calculate, according to the periodogram, whether the number of spliced ​​insulators corresponding to the splicing temperature curve meets the actual number of insulators. If the number of spliced ​​insulators meets the actual number of insulators, the first target window and the second target window are splicing points.

[0105] S660: If the number of spliced ​​insulators does not meet the actual number of insulators, the first target window and the second target window are eliminated, and the search continues until a new first target window and a new second target window are found.

[0106] Specifically, the variance calculation in S620 is:

[0107] ;

[0108] in, represents the variance of the c-th window, represents the temperature of the i-th point in the c-th window, represents the average temperature of the cth window, and m is the area of ​​the window.

[0109] It should be understood that a plurality of first windows are set on the overlapping portion of the first optimized temperature curve with the second optimized temperature curve, and a plurality of second windows with the same size as the first windows are set on the overlapping portion of the second optimized temperature curve with the first optimized temperature curve; these windows are used to calculate variances to evaluate the stability or consistency of the temperature curves; variance operations are performed on the temperature data in each first window to obtain respective first variances; similarly, variance operations are performed on the temperature data in each second window to obtain respective second variances; among all the first variances, the first window corresponding to the minimum value is found, which is recorded as the first target window, which means that in the first In the overlapping part of the optimized temperature curve, the temperature data in this window is the most stable; similarly, in all the second variances, find the second window corresponding to the minimum value, which is recorded as the second target window; according to the position of the first target window and the second target window, splice the first optimized temperature curve and the second optimized temperature curve, and the splicing point is the two target windows; use periodogram analysis and other methods to calculate the number of insulators corresponding to the spliced ​​temperature curve; compare the calculated result with the actual number of insulators; if the number of spliced ​​insulators matches the actual number, the splicing is confirmed to be successful, and the first target window and the second target window are the final splicing point. If the number of spliced ​​insulators does not match the actual number, the current first target window and the second target window are eliminated, and the above steps are repeated to continue looking for a new target window.

[0110] It should be noted that the accuracy of splicing can be significantly improved by finding the most stable temperature data segment as the splicing point through variance calculation; this helps to ensure that the temperature curve after splicing can truly reflect the temperature distribution of the insulator; the method can automatically find the splicing point and verify it according to the splicing result. If the splicing result does not meet the expectations, it will automatically adjust and continue to find new splicing points, which enhances the robustness and adaptability of the method; by setting the window and calculating the variance, a large amount of temperature data can be efficiently processed; at the same time, this method avoids the subjectivity and uncertainty of manually selecting splicing points, and improves the efficiency and reliability of data processing; this method is suitable for temperature curve splicing in real-time monitoring systems. By calculating the variance in real time and verifying the splicing results, abnormal situations can be discovered and handled in a timely manner to ensure the accuracy and reliability of the monitoring system.

[0111] According to a temperature curve splicing method for an ultra-long string of disc-shaped suspension porcelain insulators provided in this embodiment, first, infrared images of two adjacent and partially overlapping target positions (a first target position and a second target position) in an ultra-long string of disc-shaped suspension porcelain insulators are obtained by infrared imaging technology, namely, a first infrared image and a second infrared image; the two infrared images are preprocessed, such as automatically selecting a threshold, a connected domain marker, and expansion corrosion by the Ostu algorithm, so as to highlight the trunk part of the insulator; then, the trunk part of the insulator is separated from the background by image binarization processing to obtain a first binary image and a second binary image, which respectively contain only the first trunk part and the second trunk part of the insulator; in the first binary image and the second binary image, the first trunk part containing the first steel cap disk surface is respectively extracted backbone line and a second backbone line including a second steel cap disk; these backbone lines represent the temperature distribution characteristics of the first trunk part and the second trunk part of the insulator; according to the extracted first backbone line and the second backbone line, using the temperature information in the infrared image, obtain the temperature curves corresponding to the first target position and the second target position, that is, the first temperature curve and the second temperature curve; the first temperature curve and the second temperature curve are optimized, such as smoothing, filtering and offsetting, to reduce the influence of noise and outliers, to obtain the first optimized temperature curve and the second optimized temperature curve; these two optimized temperature curves should be consistent in the partially overlapping area; finally, the window variance algorithm is used to calculate the variance of the first optimized temperature curve and the second optimized temperature curve in the overlapping area, and the point with the smallest variance is found as the splicing point. This point represents the most consistent position of the two temperature curves in the overlapping area; according to the determined splicing point, the first optimized temperature curve and the second optimized temperature curve are spliced ​​to obtain the complete temperature curve of the super-long string disc-shaped suspension porcelain insulator; the spliced ​​temperature curve is verified, and if the spliced ​​temperature curve meets the requirements, the splicing point is valid; if the spliced ​​temperature curve does not meet the requirements, the current splicing point is eliminated, and the search continues until a new splicing point that meets the requirements is found.

[0112] Beneficial effects: Through infrared imaging technology and image preprocessing, the temperature distribution information of the insulator can be accurately obtained, avoiding the errors caused by contact temperature measurement in traditional methods; by using backbone line extraction and temperature curve optimization processing, the influence of noise and outliers is reduced, and the reliability and accuracy of the temperature curve are improved; this method can realize the splicing of temperature curves of super-long disc-shaped suspension porcelain insulators, providing an effective technical means for online monitoring of long-distance transmission lines; by finding splicing points through the window variance algorithm, the spliced ​​temperature curve can be made more accurate, so that potential overheating fault points can be more accurately discovered, providing strong guarantees for the safe operation of the power system; through automated and intelligent splicing methods, manual intervention is reduced, monitoring efficiency is improved, and operation and maintenance costs are reduced.

[0113] It should be noted that the temperature curve splicing method for an ultra-long string of disc-shaped suspended porcelain insulators provided in the embodiment of the present application can be executed by a temperature curve splicing system for an ultra-long string of disc-shaped suspended porcelain insulators, or a control module in the temperature curve splicing system for an ultra-long string of disc-shaped suspended porcelain insulators for executing a temperature curve splicing method for loading an ultra-long string of disc-shaped suspended porcelain insulators. In the embodiment of the present application, a temperature curve splicing system for an ultra-long string of disc-shaped suspended porcelain insulators executes a temperature curve splicing method for loading an ultra-long string of disc-shaped suspended porcelain insulators as an example to illustrate a temperature curve splicing method for an ultra-long string of disc-shaped suspended porcelain insulators provided in the embodiment of the present application.

[0114] A temperature curve splicing system for super-long string disc-shaped suspension porcelain insulators, comprising:

[0115] A first acquisition module is used to acquire a first infrared image corresponding to a first target position and a second infrared image corresponding to a second target position in the super-long string of disc-shaped suspension porcelain insulators, wherein the first target position and the second target position partially overlap;

[0116] A preprocessing module is used to preprocess the first infrared image to obtain a first binary image containing only a first trunk portion of the super-long string of disc-shaped suspension porcelain insulators, and to preprocess the second infrared image to obtain a second binary image containing only a second trunk portion of the super-long string of disc-shaped suspension porcelain insulators;

[0117] The second acquisition module is used to acquire a first backbone line including a first steel cap disk surface in the first trunk part according to the first binary image, and acquire a second backbone line including a second steel cap disk surface in the second trunk part according to the second binary image;

[0118] A third acquisition module, configured to acquire a first temperature curve corresponding to a first target position according to the first backbone line, and acquire a second temperature curve corresponding to a second target position according to the second backbone line;

[0119] An optimization module, used for optimizing the first temperature curve and the second temperature curve to obtain corresponding first optimized temperature curve and second optimized temperature curve, wherein the first optimized temperature curve partially overlaps with the second optimized temperature curve;

[0120] The processing module is used to calculate the splicing point between the first optimized temperature curve and the second optimized temperature curve according to the window variance algorithm, so as to splice the first optimized temperature curve and the second optimized temperature curve according to the splicing point.

[0121] A temperature curve splicing system for an ultra-long string of disc-shaped suspended porcelain insulators in an embodiment of the present application may be a device, or a component, integrated circuit or chip in a terminal. The device may be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device may be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA), etc., and the non-mobile electronic device may be a server, a network attached storage (NAS), a personal computer (PC), etc., which is not specifically limited in the embodiment of the present application.

[0122] A temperature curve splicing system for super-long string disc-shaped suspension porcelain insulators in the embodiment of the present application can be a device with an operating system. The operating system can be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0123] The temperature curve splicing system of the super-long string disc-shaped suspension porcelain insulator provided in the embodiment of the present application can achieve Figure 1 The various processes of implementing the temperature curve splicing method of an ultra-long string disc-shaped suspension porcelain insulator in the method embodiment will not be repeated here to avoid repetition.

[0124] According to a temperature curve splicing system for an ultra-long string of disc-shaped suspension porcelain insulators of this embodiment, by acquiring infrared images of the first target position and the second target position in the ultra-long string of disc-shaped suspension porcelain insulators, the system can capture the temperature distribution information of the insulator at different positions; since the first target position and the second target position partially overlap, this provides the necessary overlapping area for subsequent temperature curve splicing, ensuring the accuracy and continuity of the splicing; the preprocessing module performs necessary processing on the infrared image to improve the image quality; by converting the infrared image into a binary image containing only the main part of the insulator, the system can more accurately identify the characteristics of the insulator and provide a clear data basis for subsequent temperature curve extraction; the second acquisition module can automatically identify and extract the backbone lines in the first binary image and the second binary image, which represent the main part of the insulator and are the key to temperature curve extraction; by extracting the backbone lines, the system can more accurately locate the temperature curve The starting point and end point of the temperature curve, as well as the distribution of the curve on the insulator; according to the backbone line information, the third acquisition module can extract the temperature curves of the first target position and the second target position; these temperature curves reflect the temperature distribution of the insulator at different positions, and provide important data for subsequent temperature analysis and fault warning; the optimization module processes the extracted temperature curves, removes outliers and noise, and improves the accuracy and reliability of the curves; through optimization processing, the system can generate smoother and continuous temperature curves, and provide high-quality data for subsequent temperature curve splicing; the processing module uses the window variance algorithm to process the first optimized temperature curve and the second optimized temperature curve to find the best splicing point; through the splicing point, the system can seamlessly splice the two temperature curves together to form a complete temperature curve; the spliced ​​temperature curve can more accurately reflect the overall temperature distribution of the insulator, and provide strong support for the status monitoring and fault warning of the insulator.

[0125] Optionally, an embodiment of the present application also provides an electronic device, including a processor, a memory, and a program or instruction stored in the memory and executable on the processor. When the program or instruction is executed by the processor, each process of the above-mentioned temperature curve splicing method embodiment of an ultra-long string disc-shaped suspension porcelain insulator is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0126] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned temperature curve splicing method embodiment of an ultra-long string disc-shaped suspension porcelain insulator is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0127] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0128] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0129] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods of each embodiment of the present application.

[0130] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A temperature curve splicing method for super-long string disc-shaped suspension porcelain insulators, characterized in that: The method comprises: Acquire a first infrared image corresponding to a first target position in the super-long string of disc-shaped suspension porcelain insulators and a second infrared image corresponding to a second target position, wherein the first target position and the second target position partially overlap; Preprocessing the first infrared image to obtain a first binary image containing only a first trunk portion of the super-long string of disc-shaped suspension porcelain insulators, and preprocessing the second infrared image to obtain a second binary image containing only a second trunk portion of the super-long string of disc-shaped suspension porcelain insulators; Acquire a first backbone line including a first steel cap surface in the first trunk portion according to the first binary image, and acquire a second backbone line including a second steel cap surface in the second trunk portion according to the second binary image; Acquire a first temperature curve corresponding to the first target position according to the first backbone line, and acquire a second temperature curve corresponding to the second target position according to the second backbone line; Optimizing the first temperature curve and the second temperature curve to obtain a corresponding first optimized temperature curve and a second optimized temperature curve, wherein the first optimized temperature curve partially overlaps with the second optimized temperature curve; Calculating a splicing point between the first optimized temperature curve and the second optimized temperature curve according to a window variance algorithm, so as to splice the first optimized temperature curve and the second optimized temperature curve according to the splicing point; The first temperature curve and the second temperature curve are optimized to obtain the corresponding first optimized temperature curve and second optimized temperature curve; specifically: Smoothing the first temperature curve and the second temperature curve according to a smoothing algorithm to delete short-term fluctuation data in the first temperature curve and the second temperature curve; Performing filtering processing on the first temperature curve and the second temperature curve after the smoothing processing to remove noise data in the first temperature curve and the second temperature curve; performing an offset process on the first temperature curve and the second temperature curve after the filtering process according to an offset algorithm, so as to reduce an error generated when acquiring the first temperature curve and the second temperature curve; Obtaining the first optimized temperature curve after the first temperature curve is optimized, and the second optimized temperature curve after the second temperature curve is optimized; The specific formula of the smoothing algorithm is as follows: ； in, represents the smoothed temperature value of the i-th point, represents the actual temperature value of the i-th point, i represents the i-th point in the temperature curve, and n represents the total number of points in the temperature curve; The specific formula of the offset algorithm is as follows: ； in, represents the average temperature of the first temperature curve, represents the average temperature of the second temperature curve, represents the offset coefficient; The step of calculating the splicing point between the first optimized temperature curve and the second optimized temperature curve according to the window variance algorithm, so as to splice the first optimized temperature curve and the second optimized temperature curve according to the splicing point, is specifically: Setting a plurality of first windows on the overlapping portion of the first optimized temperature curve and the second optimized temperature curve, and setting a plurality of second windows having the same size as the first windows on the overlapping portion of the second optimized temperature curve and the first optimized temperature curve; Calculate the first variance corresponding to each of the first windows and the second variance corresponding to each of the second windows respectively according to the variance operation; Finding a first target window and a second target window, wherein the first target window is the first window corresponding to the minimum value in the first variance, and the second target window is the second window corresponding to the minimum value in the second variance; splicing the first optimized temperature curve and the second optimized temperature curve according to the positions of the first target window and the second target window to obtain a spliced ​​temperature curve; Calculating whether the number of spliced ​​insulators corresponding to the splicing temperature curve meets the actual number of insulators according to the periodogram analysis, if the number of spliced ​​insulators meets the actual number of insulators, the first target window and the second target window are the splicing points; If the number of the spliced ​​insulators does not meet the actual number of insulators, the first target window and the second target window are eliminated, and the search continues until a new first target window and a new second target window are found; The variance operation is specifically: ； in, represents the variance of the c-th window, represents the temperature of the i-th point in the c-th window, represents the average temperature of the cth window, and m is the area of ​​the window.

2. The temperature curve splicing method of a super-long string of disc-shaped suspension porcelain insulators according to claim 1 is characterized in that: The first infrared image is preprocessed to obtain a first binary image containing only the first trunk portion of the super-long string of disc-shaped suspension porcelain insulators, and the second infrared image is preprocessed to obtain a second binary image containing only the second trunk portion of the super-long string of disc-shaped suspension porcelain insulators; specifically: Automatically selecting a threshold value according to an Ostu algorithm to process the first infrared image and the second infrared image; Marking all connected domains in the first infrared image and the second infrared image after being processed by the Ostu algorithm; The first infrared image after the connected domain is marked is processed according to the expansion corrosion method to obtain the first binary image containing only the first trunk part of the long string of disc-shaped suspension porcelain insulators. The second infrared image after the connected domain is marked is processed according to the expansion corrosion method to obtain the second binary image containing only the second trunk part of the long string of disc-shaped suspension porcelain insulators.

3. The temperature curve splicing method of a super-long string of disc-shaped suspension porcelain insulators according to claim 1 is characterized in that: The first backbone line including the first steel cap disk surface in the first trunk part is obtained according to the first binary image, and the second backbone line including the second steel cap disk surface in the second trunk part is obtained according to the second binary image; specifically: Processing the first binary image according to a skeletonization processing method in an image morphology processing manner to obtain the first trunk portion of the first binary image, and processing the second binary image according to a skeletonization processing method in an image morphology processing manner to obtain the second trunk portion of the second binary image; The midlines of the first trunk portion and the second trunk portion are the corresponding first backbone line and the second backbone line; Selecting a portion of the first backbone line including the first steel cap surface and a portion of the second backbone line including the second steel cap surface; The first backbone line including the first steel cap plate in the first backbone part and the second backbone line including the second steel cap plate in the second backbone part are obtained.

4. A temperature curve splicing system for super-long string disc-shaped suspension porcelain insulators, used to implement a temperature curve splicing method for super-long string disc-shaped suspension porcelain insulators as described in any one of claims 1 to 3, characterized in that: The system comprises: A first acquisition module is used to acquire a first infrared image corresponding to a first target position and a second infrared image corresponding to a second target position in the super-long string of disc-shaped suspension porcelain insulators, wherein the first target position and the second target position partially overlap; A preprocessing module is used to preprocess the first infrared image to obtain a first binary image containing only a first trunk portion of the super-long string of disc-shaped suspension porcelain insulators, and to preprocess the second infrared image to obtain a second binary image containing only a second trunk portion of the super-long string of disc-shaped suspension porcelain insulators; A second acquisition module is used to acquire a first backbone line including a first steel cap disk surface in the first trunk part according to the first binary image, and to acquire a second backbone line including a second steel cap disk surface in the second trunk part according to the second binary image; a third acquisition module, configured to acquire a first temperature curve corresponding to the first target position according to the first backbone line, and acquire a second temperature curve corresponding to the second target position according to the second backbone line; an optimization module, configured to optimize the first temperature curve and the second temperature curve to obtain a corresponding first optimized temperature curve and a second optimized temperature curve, wherein the first optimized temperature curve partially overlaps with the second optimized temperature curve; A processing module is used to calculate a splicing point between the first optimized temperature curve and the second optimized temperature curve according to a window variance algorithm, so as to splice the first optimized temperature curve and the second optimized temperature curve according to the splicing point.

5. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of a temperature curve splicing method for super-long string disc-shaped suspension porcelain insulators as described in any one of claims 1 to 3 are implemented.

6. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the temperature curve splicing method of an ultra-long string disc-shaped suspension porcelain insulator as described in any one of claims 1-3 are implemented.

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