Photovoltaic field video monitoring management method and system

Abstract

The invention relates to the technical field of photovoltaic monitoring, and discloses a photovoltaic field video monitoring management method and system. The method comprises the following steps: acquiring an original monitoring video of a photovoltaic power plant, and dividing the original monitoring video into at least two sub-monitoring videos; performing video set division on all the sub-monitoring videos to obtain a first video set and a second video set, and allocating the sub-monitoring videos in the first video set to a temporary storage space according to the data identification codes; acquiring a first sub-monitoring video in the first video set, and extracting a corresponding sub-monitoring image; calculating an approximation degree between the sub-monitoring image and the standardized image according to the sub-monitoring image and the standardized image; and judging whether the photovoltaic power plant is abnormal or not according to the approximation degree, and giving an alarm prompt when the photovoltaic power plant is abnormal, so that efficient and automatic monitoring of the photovoltaic field is realized, video data can be automatically analyzed, abnormal conditions can be identified, and early warning can be given out in time, thereby greatly improving the safety management level and the operation efficiency of the photovoltaic field.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic monitoring technology, and in particular to a photovoltaic field video monitoring management method and system. Background Art

[0002] With the development of renewable energy technology, photovoltaic power generation has become an important part of the global energy structure transformation. As a key facility for producing clean electricity, the safe and efficient operation of photovoltaic fields is crucial to ensuring energy supply. However, photovoltaic fields usually occupy a large area, have scattered equipment, and are mostly located in remote areas or areas with complex natural environments, which brings challenges to on-site management and safety monitoring.

[0003] Although current video surveillance systems can provide real-time images, they are deficient in data processing and analysis. Large amounts of video data require manual review, which is time-consuming and labor-intensive, and is easily affected by subjective factors, resulting in unstable monitoring results. In addition, existing systems often lack intelligent anomaly detection and early warning mechanisms, and are unable to proactively identify and handle potential risks. Summary of the invention

[0004] In response to the above problems, the present invention proposes a photovoltaic field video monitoring management method and system, which aims to achieve efficient and automated monitoring of photovoltaic fields through image processing technology and intelligent algorithms. It can automatically analyze video data, identify abnormal situations, and issue early warnings in a timely manner, thereby greatly improving the safety management level and operational efficiency of photovoltaic fields.

[0005] In order to achieve the above object, the present invention provides a photovoltaic field video monitoring management method, comprising:

[0006] Acquire an original monitoring video of a photovoltaic power plant, and divide the original monitoring video into at least two sub-monitoring videos, wherein the formats of the sub-monitoring videos and the original monitoring video satisfy a decoding strategy;

[0007] Dividing all sub-surveillance videos into video sets and obtaining a first video set and a second video set, generating data identification codes for the sub-surveillance videos in the first video set, and allocating the sub-surveillance videos in the first video set to temporary storage space according to the data identification codes;

[0008] Capturing a first sub-surveillance video in the first video set, and extracting a corresponding sub-surveillance image;

[0009] Acquire a preset standardized image, and calculate the degree of similarity between the sub-monitoring image and the standardized image according to the sub-monitoring image and the standardized image;

[0010] It is determined whether there is any abnormality in the photovoltaic power plant according to the degree of similarity, and an alarm is issued when an abnormality exists.

[0011] Furthermore, when obtaining the original monitoring video of the photovoltaic power plant, dividing the original monitoring video into at least two sub-monitoring videos includes:

[0012] Obtaining a video division limit, and determining a video division threshold or a video division threshold range according to the video division limit, wherein the video division limit is used to characterize the video division threshold or the video division threshold range used when dividing the original surveillance video into the sub-surveillance videos;

[0013] When the video division limit is determined as the video division threshold, the original surveillance video is divided into at least two sub-surveillance videos based on the video division threshold;

[0014] When the video division limit is determined as the video division threshold range, a threshold is randomly selected from the video division threshold range, and the original monitoring video is divided into at least two sub-monitoring videos according to the selected threshold.

[0015] Further, when generating a data identification code for the sub-surveillance video in the first video set and allocating the sub-surveillance video in the first video set to a temporary storage space according to the data identification code, the method includes:

[0016] The video frames of all sub-monitoring videos are obtained respectively, and all sub-monitoring videos are divided into video sets according to the relationship between the video frames and the preset video frames.

[0017] When the video frame is greater than or equal to the preset video frame, the corresponding sub-surveillance video is divided into the first video set;

[0018] When the video frame is smaller than the preset video frame, the corresponding sub-surveillance video is divided into the second video set;

[0019] The second video set is deleted, and a data identification code generated by a sub-surveillance video in the first video set is obtained, and the data identification code is randomly intercepted to determine a sub-surveillance video to be processed;

[0020] Obtaining video parameters of the sub-surveillance video to be processed, and calculating the importance level coefficient of the sub-surveillance video to be processed according to the video parameters, wherein the video parameters include: a video frame of the sub-surveillance video to be processed and a weight corresponding to the i-th video frame of the sub-surveillance video to be processed;

[0021] The sub-surveillance videos in the first video set are sorted according to the importance level coefficients of the sub-surveillance videos to be processed, and the sub-surveillance videos in the first video set are sequentially allocated to the temporary storage space according to the sorting result.

[0022] Further, when obtaining the video parameters of the sub-surveillance video to be processed and calculating the importance level coefficient of the sub-surveillance video to be processed according to the video parameters, it includes:

[0023] The importance level coefficient of the sub-surveillance video to be processed is calculated according to the following formula:

[0024]

[0025] Wherein, W is the importance level coefficient of the sub-monitoring video to be processed, k1 is the video frame of the sub-monitoring video to be processed, and qi is the weight corresponding to the i-th video frame of the sub-monitoring video to be processed.

[0026] Furthermore, when a preset standardized image is acquired and the degree of similarity between the sub-monitoring image and the standardized image is calculated according to the sub-monitoring image and the standardized image, the method includes:

[0027] Performing grayscale conversion on the sub-monitoring image and the standardized image respectively to obtain a corresponding sub-monitoring grayscale image and a standardized grayscale image;

[0028] Deploying a plurality of pixel detection points on the sub-monitoring grayscale image and the standardized grayscale image;

[0029] Extracting pixel points on the sub-monitoring grayscale image based on pixel detection points, and constructing a first pixel point set;

[0030] Extracting pixel points on the standardized grayscale image based on pixel detection points, and constructing a second pixel point set;

[0031] Randomly select a pixel point from the first pixel point set, obtain corresponding feature data, and traverse the second pixel points based on the feature data to determine whether there is a pixel point that is the same as the pixel point;

[0032] If it exists, an identical identifier is generated for the pixel point; if it does not exist, a different identifier is generated for the pixel point;

[0033] Traversing the remaining pixel points in the first pixel point set;

[0034] Deleting pixels carrying the same identifier in the first pixel point set, and generating a first to-be-processed pixel point set according to pixels carrying different identifiers;

[0035] Acquire second pixel points to be processed corresponding to the first pixel point set to be processed from the second pixel point set, and construct a second pixel point set to be processed;

[0036] The degree of approximation between the sub-monitoring image and the standardized image is calculated according to the first set of pixel points to be processed and the second set of pixel points to be processed.

[0037] Further, when calculating the degree of approximation between the sub-monitoring image and the standardized image according to the first set of pixels to be processed and the second set of pixels to be processed, it includes:

[0038] Determine the cluster center of the second set of pixels to be processed based on the K-Means clustering algorithm;

[0039] respectively determining the distances from the pixels in the first set of pixels to be processed to the cluster center;

[0040] Obtaining a preset distance threshold, and generating a first distance set according to all distances less than the distance threshold;

[0041] generating a second distance set according to all distances equal to the distance threshold;

[0042] Generate a third distance set according to all distances greater than the distance threshold;

[0043] The degree of similarity between the sub-monitoring image and the standardized image is calculated based on the first distance set, the second distance set, and the third distance set.

[0044] Further, when calculating the degree of similarity between the sub-monitoring image and the standardized image based on the first distance set, the second distance set and the third distance set, it includes:

[0045] The degree of similarity between the sub-monitoring image and the standardized image is calculated according to the following formula:

[0046]

[0047] Where G is the approximation between the sub-monitoring image and the standardized image, m1 is the number of distances in the first distance set, and h1 j is the jth distance in the first distance set, y is the distance threshold, u1 is the calculation coefficient corresponding to the first distance set, e1 max The maximum distance in the first distance set, m2 is the number of distances in the second distance set, and h2 is the maximum distance in the first distance set. i is the i-th distance in the second distance set, u2 is the calculation coefficient corresponding to the second distance set, e2 max The maximum distance in the second distance set, m3 is the number of distances in the third distance set, and h3 is the maximum distance in the second distance set. x is the xth distance in the third distance set, u3 is the calculation coefficient corresponding to the third distance set, e3 maxThe largest distance in the third distance set.

[0048] Further, when judging whether the photovoltaic power plant is abnormal according to the approximation degree, it includes:

[0049] Obtaining a preset approximation degree threshold, and judging whether the photovoltaic power plant is abnormal according to the relationship between the approximation degree and the approximation degree threshold;

[0050] When the degree of similarity is less than or equal to the degree of similarity, it is determined that an abnormality exists in the photovoltaic power plant;

[0051] When the degree of similarity is greater than the degree of similarity, it is determined that there is no abnormality in the photovoltaic power plant.

[0052] In order to achieve the above object, the present invention also provides a photovoltaic field video monitoring management system, comprising:

[0053] The first module is used to obtain the original monitoring video of the photovoltaic power plant, and divide the original monitoring video into at least two sub-monitoring videos, and the formats of the sub-monitoring videos and the original monitoring video meet the decoding strategy;

[0054] The second module is used to divide all sub-surveillance videos into video sets and obtain a first video set and a second video set, generate data identification codes for the sub-surveillance videos in the first video set, and allocate the sub-surveillance videos in the first video set to temporary storage space according to the data identification codes;

[0055] A third module is used to collect the first sub-surveillance video in the first video set and extract the corresponding sub-surveillance image;

[0056] A fourth module is used to obtain a preset standardized image, and calculate the approximation between the sub-monitoring image and the standardized image according to the sub-monitoring image and the standardized image;

[0057] The fifth module is used to determine whether there is any abnormality in the photovoltaic power plant according to the degree of similarity, and to issue an alarm when there is an abnormality.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] The present invention discloses a photovoltaic field video monitoring management method and system. The method comprises: obtaining the original monitoring video of the photovoltaic power plant, dividing the original monitoring video into at least two sub-monitoring videos; dividing all the sub-monitoring videos into video sets to obtain a first video set and a second video set, and allocating the sub-monitoring videos in the first video set to a temporary storage space according to a data identification code; collecting the first sub-monitoring video in the first video set, and extracting the corresponding sub-monitoring image; calculating the approximation between the sub-monitoring image and the standardized image according to the sub-monitoring image and the standardized image; judging whether there is an abnormality in the photovoltaic power plant according to the approximation, and issuing an alarm reminder when there is an abnormality, realizing efficient and automated monitoring of the photovoltaic field, being able to automatically analyze video data, identify abnormal conditions, and issue early warnings in a timely manner, thereby greatly improving the safety management level and operation efficiency of the photovoltaic field. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0061] Figure 1 A schematic diagram of the process of the photovoltaic field video monitoring management method in an embodiment of the present invention is shown;

[0062] Figure 2 The schematic diagram of the structure of the photovoltaic field video monitoring management system in the embodiment of the present invention is shown. DETAILED DESCRIPTION

[0063] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0064] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0065] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0066] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0067] The following is a description of preferred embodiments of the present invention with reference to the accompanying drawings.

[0068] like Figure 1 As shown, an embodiment of the present invention discloses a photovoltaic field video monitoring management method, including:

[0069] S110: Acquire an original monitoring video of the photovoltaic power plant, and divide the original monitoring video into at least two sub-monitoring videos, where the formats of the sub-monitoring videos and the original monitoring video satisfy a decoding strategy;

[0070] In some embodiments of the present application, when an original monitoring video of a photovoltaic power plant is obtained and the original monitoring video is divided into at least two sub-monitoring videos, the method includes:

[0071] Obtaining a video division limit, and determining a video division threshold or a video division threshold range according to the video division limit, wherein the video division limit is used to characterize the video division threshold or the video division threshold range used when dividing the original surveillance video into the sub-surveillance videos;

[0072] When the video division limit is determined as the video division threshold, the original surveillance video is divided into at least two sub-surveillance videos based on the video division threshold;

[0073] When the video division limit is determined as the video division threshold range, a threshold is randomly selected from the video division threshold range, and the original monitoring video is divided into at least two sub-monitoring videos according to the selected threshold.

[0074] In this embodiment, the video segmentation threshold refers to different segmentation granularity parameters corresponding to different thresholds. The threshold may be a fixed value, and a threshold is selected among these fixed values ​​for segmenting the original medical video.

[0075] In this embodiment, the video segmentation threshold range refers to that the segmentation granularity parameter fluctuates within a threshold interval, and the threshold is not a fixed value.

[0076] In this embodiment, different numbers of sub-surveillance videos can be obtained according to different video division thresholds. For example, when the division granularity parameter is the first threshold, a video can be divided into 6 sub-video frames; when the division granularity parameter is the second threshold, a video can be divided into 8 sub-video frames; using different thresholds, the division granularity is different, and the number of sub-surveillance videos obtained is also different.

[0077] In this embodiment, when the video formats of the original surveillance video and the divided sub-surveillance video are the same, it is determined that the formats of the sub-surveillance video and the original surveillance video meet the decoding strategy, and the video formats include: AVI video format, the file name ends with ".avi", Mpeg-4 video format, the file name ends with ".mp4", MPEG video format, the file name ends with ".mpg" or ".mpeg", etc.

[0078] The beneficial effect of the above technical solution is: the present invention can effectively improve work efficiency by dividing the original monitoring video into several sub-monitoring videos, and can also ensure the accuracy of subsequent data analysis and processing. By selecting different thresholds to divide the original medical video, the clarity of the sub-monitoring videos can be ensured.

[0079] S120: Divide all sub-surveillance videos into video sets to obtain a first video set and a second video set, generate data identification codes for the sub-surveillance videos in the first video set, and allocate the sub-surveillance videos in the first video set to temporary storage space according to the data identification codes;

[0080] In some embodiments of the present application, when a data identification code is generated for a sub-surveillance video in the first video set, and the sub-surveillance video in the first video set is allocated to a temporary storage space according to the data identification code, the method includes:

[0081] The video frames of all sub-monitoring videos are obtained respectively, and all sub-monitoring videos are divided into video sets according to the relationship between the video frames and the preset video frames.

[0082] When the video frame is greater than or equal to the preset video frame, the corresponding sub-surveillance video is divided into the first video set;

[0083] When the video frame is smaller than the preset video frame, the corresponding sub-surveillance video is divided into the second video set;

[0084] The second video set is deleted, and a data identification code generated by a sub-surveillance video in the first video set is obtained, and the data identification code is randomly intercepted to determine a sub-surveillance video to be processed;

[0085] Obtaining video parameters of the sub-surveillance video to be processed, and calculating the importance level coefficient of the sub-surveillance video to be processed according to the video parameters, wherein the video parameters include: a video frame of the sub-surveillance video to be processed and a weight corresponding to the i-th video frame of the sub-surveillance video to be processed;

[0086] The sub-surveillance videos in the first video set are sorted according to the importance level coefficients of the sub-surveillance videos to be processed, and the sub-surveillance videos in the first video set are sequentially allocated to the temporary storage space according to the sorting result.

[0087] In this embodiment, the frame number refers to the number of still images, and the higher the frame number, the smoother the image.

[0088] In this embodiment, when sub-surveillance videos in the first video set are allocated to temporary storage space in sequence according to the sorting result, they are sorted by importance level coefficients of the sub-surveillance videos to be processed, and sub-surveillance videos to be processed with higher importance level coefficients are stored preferentially.

[0089] The beneficial effect of the above technical solution is: the present invention can delete unclear sub-surveillance videos and reduce the difficulty of video information analysis by deleting the second video set and retaining the first video set. At the same time, the present invention allocates the sub-surveillance videos in the first video set to the temporary storage space in sequence according to the sorting results, and then in subsequent processing, it can start analysis and processing from the sub-surveillance videos with higher importance level coefficients, thereby greatly improving the efficiency of video information processing.

[0090] In some embodiments of the present application, when obtaining the video parameters of the sub-surveillance video to be processed and calculating the importance level coefficient of the sub-surveillance video to be processed according to the video parameters, it includes:

[0091] The importance level coefficient of the sub-surveillance video to be processed is calculated according to the following formula:

[0092]

[0093] Wherein, W is the importance level coefficient of the sub-monitoring video to be processed, k1 is the video frame of the sub-monitoring video to be processed, and qi is the weight corresponding to the i-th video frame of the sub-monitoring video to be processed.

[0094] S130: capturing a first sub-surveillance video in the first video set, and extracting a corresponding sub-surveillance image;

[0095] S140: acquiring a preset standardized image, and calculating the degree of similarity between the sub-monitoring image and the standardized image according to the sub-monitoring image and the standardized image;

[0096] In some embodiments of the present application, when a preset standardized image is acquired and the degree of similarity between the sub-monitoring image and the standardized image is calculated according to the sub-monitoring image and the standardized image, the method includes:

[0097] Performing grayscale conversion on the sub-monitoring image and the standardized image respectively to obtain a corresponding sub-monitoring grayscale image and a standardized grayscale image;

[0098] Deploying a plurality of pixel detection points on the sub-monitoring grayscale image and the standardized grayscale image;

[0099] Extracting pixel points on the sub-monitoring grayscale image based on pixel detection points, and constructing a first pixel point set;

[0100] Extracting pixel points on the standardized grayscale image based on pixel detection points, and constructing a second pixel point set;

[0101] Randomly select a pixel point from the first pixel point set, obtain corresponding feature data, and traverse the second pixel points based on the feature data to determine whether there is a pixel point that is the same as the pixel point;

[0102] If it exists, an identical identifier is generated for the pixel point; if it does not exist, a different identifier is generated for the pixel point;

[0103] Traversing the remaining pixel points in the first pixel point set;

[0104] Deleting pixels carrying the same identifier in the first pixel point set, and generating a first to-be-processed pixel point set according to pixels carrying different identifiers;

[0105] Acquire second pixel points to be processed corresponding to the first pixel point set to be processed from the second pixel point set, and construct a second pixel point set to be processed;

[0106] The degree of approximation between the sub-monitoring image and the standardized image is calculated according to the first set of pixel points to be processed and the second set of pixel points to be processed.

[0107] In this embodiment, the standardized image refers to an image without abnormalities and is acquired in advance.

[0108] In this embodiment, the grayscale conversion method is complicated and mature, and is not specifically limited here.

[0109] In this embodiment, the feature data refers to the brightness, color, and contrast of the pixel points.

[0110] The beneficial effect of the above technical solution is that: the present invention calculates the degree of approximation between the sub-monitoring image and the standardized image based on the first set of pixel points to be processed and the second set of pixel points to be processed, which can lay the foundation for judging whether there is an abnormality in the monitoring video of the photovoltaic power plant and provide reliable data support.

[0111] In some embodiments of the present application, when calculating the degree of approximation between the sub-monitoring image and the standardized image according to the first set of pixels to be processed and the second set of pixels to be processed, the method includes:

[0112] Determine the cluster center of the second set of pixels to be processed based on the K-Means clustering algorithm;

[0113] respectively determining the distances from the pixels in the first set of pixels to be processed to the cluster center;

[0114] Obtaining a preset distance threshold, and generating a first distance set according to all distances less than the distance threshold;

[0115] generating a second distance set according to all distances equal to the distance threshold;

[0116] Generate a third distance set according to all distances greater than the distance threshold;

[0117] The degree of similarity between the sub-monitoring image and the standardized image is calculated based on the first distance set, the second distance set, and the third distance set.

[0118] In this embodiment, the distance threshold can be set according to actual conditions.

[0119] The beneficial effect of the above technical solution is: the present invention calculates the degree of approximation between the sub-monitoring image and the standardized image based on the first distance set, the second distance set and the third distance set, thereby achieving accurate calculation of the degree of approximation, avoiding errors, and ensuring calculation accuracy and precision.

[0120] In some embodiments of the present application, when calculating the degree of approximation between the sub-monitoring image and the standardized image based on the first distance set, the second distance set, and the third distance set, the method includes:

[0121] The degree of similarity between the sub-monitoring image and the standardized image is calculated according to the following formula:

[0122]

[0123] Where G is the approximation between the sub-monitoring image and the standardized image, m1 is the number of distances in the first distance set, and h1 j is the jth distance in the first distance set, y is the distance threshold, u1 is the calculation coefficient corresponding to the first distance set, e1 max The maximum distance in the first distance set, m2 is the number of distances in the second distance set, and h2 is the maximum distance in the first distance set. i is the i-th distance in the second distance set, u2 is the calculation coefficient corresponding to the second distance set, e2 max The maximum distance in the second distance set, m3 is the number of distances in the third distance set, and h3 is the maximum distance in the second distance set. x is the xth distance in the third distance set, u3 is the calculation coefficient corresponding to the third distance set, e3 max The largest distance in the third distance set.

[0124] S150: Determine whether there is any abnormality in the photovoltaic power plant according to the degree of similarity, and issue an alarm when there is any abnormality.

[0125] In some embodiments of the present application, when judging whether the photovoltaic power plant is abnormal according to the approximation degree, it includes:

[0126] Obtaining a preset approximation degree threshold, and judging whether the photovoltaic power plant is abnormal according to the relationship between the approximation degree and the approximation degree threshold;

[0127] When the degree of similarity is less than or equal to the degree of similarity, it is determined that an abnormality exists in the photovoltaic power plant;

[0128] When the degree of similarity is greater than the degree of similarity, it is determined that there is no abnormality in the photovoltaic power plant.

[0129] In this embodiment, the similarity degree threshold can be set according to actual conditions and is not specifically limited here.

[0130] The beneficial effects of the above technical solution are: achieving efficient and automated monitoring of photovoltaic fields, being able to automatically analyze video data, identify abnormal situations, and issue early warnings in a timely manner, thereby greatly improving the safety management level and operational efficiency of photovoltaic fields.

[0131] In order to further explain the technical idea of ​​the present invention, the technical solution of the present invention is now described in combination with specific application scenarios.

[0132] Correspondingly, such as Figure 2 As shown, the present application also provides a photovoltaic field video monitoring management system, including:

[0133] The first module is used to obtain the original monitoring video of the photovoltaic power plant, and divide the original monitoring video into at least two sub-monitoring videos, and the formats of the sub-monitoring videos and the original monitoring video meet the decoding strategy;

[0134] The second module is used to divide all sub-surveillance videos into video sets and obtain a first video set and a second video set, generate data identification codes for the sub-surveillance videos in the first video set, and allocate the sub-surveillance videos in the first video set to temporary storage space according to the data identification codes;

[0135] A third module is used to collect the first sub-surveillance video in the first video set and extract the corresponding sub-surveillance image;

[0136] A fourth module is used to obtain a preset standardized image, and calculate the approximation between the sub-monitoring image and the standardized image according to the sub-monitoring image and the standardized image;

[0137] The fifth module is used to determine whether there is any abnormality in the photovoltaic power plant according to the degree of similarity, and to issue an alarm when there is an abnormality.

[0138] In the description of the above embodiments, specific features, structures, materials or characteristics may be combined in a suitable manner in any one or more embodiments or examples.

[0139] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced with equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed by the present invention may be used in combination with each other in any manner, and the fact that these combinations are not fully described in this specification is only for the sake of omitting space and saving resources.

[0140] Those skilled in the art can understand that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A photovoltaic field video monitoring management method, characterized in that: include: Acquire an original monitoring video of a photovoltaic power plant, and divide the original monitoring video into at least two sub-monitoring videos, wherein the formats of the sub-monitoring videos and the original monitoring video satisfy a decoding strategy; Dividing all sub-surveillance videos into video sets and obtaining a first video set and a second video set, generating data identification codes for the sub-surveillance videos in the first video set, and allocating the sub-surveillance videos in the first video set to temporary storage space according to the data identification codes; Capturing a first sub-surveillance video in the first video set, and extracting a corresponding sub-surveillance image; Acquire a preset standardized image, and calculate the degree of similarity between the sub-monitoring image and the standardized image according to the sub-monitoring image and the standardized image; It is determined whether there is any abnormality in the photovoltaic power plant according to the degree of similarity, and an alarm is issued when an abnormality exists.

2. The photovoltaic field video monitoring management method according to claim 1, characterized in that: When an original monitoring video of a photovoltaic power plant is obtained and the original monitoring video is divided into at least two sub-monitoring videos, the method includes: Obtaining a video division limit, and determining a video division threshold or a video division threshold range according to the video division limit, wherein the video division limit is used to characterize the video division threshold or the video division threshold range used when dividing the original surveillance video into the sub-surveillance videos; When the video division limit is determined as the video division threshold, the original surveillance video is divided into at least two sub-surveillance videos based on the video division threshold; When the video division limit is determined as the video division threshold range, a threshold is randomly selected from the video division threshold range, and the original monitoring video is divided into at least two sub-monitoring videos according to the selected threshold.

3. The photovoltaic field video monitoring management method according to claim 1, characterized in that: When a data identification code is generated for a sub-surveillance video in the first video set, and the sub-surveillance video in the first video set is allocated to a temporary storage space according to the data identification code, the method includes: The video frames of all sub-monitoring videos are obtained respectively, and all sub-monitoring videos are divided into video sets according to the relationship between the video frames and the preset video frames. When the video frame is greater than or equal to the preset video frame, the corresponding sub-surveillance video is divided into the first video set; When the video frame is smaller than the preset video frame, the corresponding sub-surveillance video is divided into the second video set; The second video set is deleted, and a data identification code generated by a sub-surveillance video in the first video set is obtained, and the data identification code is randomly intercepted to determine a sub-surveillance video to be processed; Obtaining video parameters of the sub-surveillance video to be processed, and calculating the importance level coefficient of the sub-surveillance video to be processed according to the video parameters, wherein the video parameters include: a video frame of the sub-surveillance video to be processed and a weight corresponding to the i-th video frame of the sub-surveillance video to be processed; The sub-surveillance videos in the first video set are sorted according to the importance level coefficients of the sub-surveillance videos to be processed, and the sub-surveillance videos in the first video set are sequentially allocated to the temporary storage space according to the sorting result.

4. The photovoltaic field video monitoring management method according to claim 3, characterized in that: When obtaining the video parameters of the sub-surveillance video to be processed and calculating the importance level coefficient of the sub-surveillance video to be processed according to the video parameters, it includes: The importance level coefficient of the sub-surveillance video to be processed is calculated according to the following formula: Wherein, W is the importance level coefficient of the sub-monitoring video to be processed, k1 is the video frame of the sub-monitoring video to be processed, and qi is the weight corresponding to the i-th video frame of the sub-monitoring video to be processed.

5. The photovoltaic field video monitoring management method according to claim 1, characterized in that: When a preset standardized image is acquired and a degree of similarity between the sub-monitoring image and the standardized image is calculated according to the sub-monitoring image and the standardized image, the method includes: Performing grayscale conversion on the sub-monitoring image and the standardized image respectively to obtain a corresponding sub-monitoring grayscale image and a standardized grayscale image; Deploying a plurality of pixel detection points on the sub-monitoring grayscale image and the standardized grayscale image; Extracting pixel points on the sub-monitoring grayscale image based on pixel detection points, and constructing a first pixel point set; Extracting pixel points on the standardized grayscale image based on pixel detection points, and constructing a second pixel point set; Randomly select a pixel point from the first pixel point set, obtain corresponding feature data, and traverse the second pixel points based on the feature data to determine whether there is a pixel point that is the same as the pixel point; If it exists, an identical identifier is generated for the pixel point; if it does not exist, a different identifier is generated for the pixel point; Traversing the remaining pixel points in the first pixel point set; Deleting pixels carrying the same identifier in the first pixel point set, and generating a first to-be-processed pixel point set according to pixels carrying different identifiers; Acquire second pixel points to be processed corresponding to the first pixel point set to be processed from the second pixel point set, and construct a second pixel point set to be processed; The degree of approximation between the sub-monitoring image and the standardized image is calculated according to the first set of pixel points to be processed and the second set of pixel points to be processed.

6. The photovoltaic field video monitoring management method according to claim 5, characterized in that: When calculating the degree of approximation between the sub-monitoring image and the standardized image according to the first set of pixels to be processed and the second set of pixels to be processed, the method includes: Determine the cluster center of the second set of pixels to be processed based on the K-Means clustering algorithm; respectively determining the distances from the pixels in the first set of pixels to be processed to the cluster center; Obtaining a preset distance threshold, and generating a first distance set according to all distances less than the distance threshold; generating a second distance set according to all distances equal to the distance threshold; Generate a third distance set according to all distances greater than the distance threshold; The degree of similarity between the sub-monitoring image and the standardized image is calculated based on the first distance set, the second distance set, and the third distance set.

7. The photovoltaic field video monitoring management method according to claim 6, characterized in that: When calculating the degree of approximation between the sub-monitoring image and the standardized image based on the first distance set, the second distance set, and the third distance set, the method includes: The degree of similarity between the sub-monitoring image and the standardized image is calculated according to the following formula: Where G is the approximation between the sub-monitoring image and the standardized image, m1 is the number of distances in the first distance set, and h1 j is the jth distance in the first distance set, y is the distance threshold, u1 is the calculation coefficient corresponding to the first distance set, e1 max The maximum distance in the first distance set, m2 is the number of distances in the second distance set, and h2 is the maximum distance in the first distance set. i is the i-th distance in the second distance set, u2 is the calculation coefficient corresponding to the second distance set, e2 max The maximum distance in the second distance set, m3 is the number of distances in the third distance set, and h3 is the maximum distance in the second distance set. x is the xth distance in the third distance set, u3 is the calculation coefficient corresponding to the third distance set, e3 max The largest distance in the third distance set.

8. The photovoltaic field video monitoring management method according to claim 1, characterized in that: When judging whether the photovoltaic power plant is abnormal according to the approximation degree, the method includes: Obtaining a preset approximation degree threshold, and judging whether the photovoltaic power plant is abnormal according to the relationship between the approximation degree and the approximation degree threshold; When the degree of similarity is less than or equal to the degree of similarity, it is determined that an abnormality exists in the photovoltaic power plant; When the degree of similarity is greater than the degree of similarity, it is determined that there is no abnormality in the photovoltaic power plant.

9. A photovoltaic field video monitoring management system, applied to the photovoltaic field video monitoring management method according to any one of claims 1 to 8, characterized in that: include: The first module is used to obtain the original monitoring video of the photovoltaic power plant, and divide the original monitoring video into at least two sub-monitoring videos, and the formats of the sub-monitoring videos and the original monitoring video meet the decoding strategy; The second module is used to divide all sub-surveillance videos into video sets and obtain a first video set and a second video set, generate data identification codes for the sub-surveillance videos in the first video set, and allocate the sub-surveillance videos in the first video set to temporary storage space according to the data identification codes; A third module is used to collect the first sub-surveillance video in the first video set and extract the corresponding sub-surveillance image; A fourth module is used to obtain a preset standardized image, and calculate the approximation between the sub-monitoring image and the standardized image according to the sub-monitoring image and the standardized image; The fifth module is used to determine whether there is any abnormality in the photovoltaic power plant according to the degree of similarity, and to issue an alarm when there is an abnormality.

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