Video monitoring automatic networking monitoring analysis method for hydroelectric power plant

Abstract

The invention belongs to the technical field of video monitoring, and particularly discloses and provides a video monitoring automatic networking monitoring analysis method for a hydroelectric power plant, and the method comprises the steps: extracting the layout position of each piece of concerned monitoring equipment, each set camera parameter, networking related data and each piece of monitoring data; performing operation state analysis and transmission state analysis on each concerned monitoring device; performing adjustment demand evaluation on each concerned monitoring device; and confirming an adjustment strategy of the adjustment equipment, and performing feedback. According to the invention, the limitation of current video monitoring automatic networking monitoring analysis is effectively solved, the stability of subsequent monitoring, the timeliness of subsequent data transmission and the timeliness of abnormal event response are ensured, and the reliability and safety of corresponding power generation of a hydroelectric power plant are maintained; meanwhile, the risk and the accident rate of hydroelectric generation are reduced as much as possible, errors in the follow-up monitoring process are reduced, and the monitoring target is ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of video monitoring and relates to an automatic networking monitoring and analysis method for video monitoring in a hydropower plant. Background Art

[0002] Hydropower is a clean, renewable energy source that is widely used in the field of power generation. However, in the process of hydropower generation, multiple links such as reservoirs, dams, and water flows need to be monitored to ensure the safety and stability of operation. Traditional manual inspection methods have problems such as low efficiency, high cost, and difficulty in ensuring monitoring accuracy. Therefore, it is necessary to introduce video surveillance automatic networking monitoring. In order to ensure the monitoring effect, it is necessary to analyze its automatic networking.

[0003] At present, the automatic networking monitoring and analysis of video surveillance mainly focuses on the monitoring deployment and the subsequent assessment of abnormal conditions in power plants. Obviously, the current automatic networking monitoring and analysis of video surveillance still has certain limitations, which are specifically reflected in the following aspects: 1. The stability of monitoring cannot be guaranteed. The current dynamic analysis is based on the historical monitoring data of different monitoring points, which makes it impossible to gain insight into the monitoring status of each monitoring point, and it is not convenient to make timely adjustments to the monitoring equipment in each monitoring point, thereby failing to improve the reliability and stability of the monitoring equipment.

[0004] 2. The timeliness of transmission of abnormal monitoring conditions cannot be guaranteed. Most of the equipment is placed outdoors, and some are affected by various natural factors such as water flow. There is a possibility of monitoring deviation. No further analysis has been conducted on this, and the timeliness of correction and maintenance of the monitoring equipment cannot be ensured, which makes it impossible to reduce the error of monitoring.

[0005] 3. The timeliness of response to abnormal monitoring situations cannot be guaranteed. Currently, the transmission conditions of different monitoring points have not been analyzed to optimize the network. There is a possibility of transmission delay, which may lead to the inability to handle abnormal situations in a timely manner, resulting in little significant improvement in the reliability and safety of hydropower plant operation and maintenance. Summary of the invention

[0006] In view of this, in order to solve the problems raised in the above background technology, a video surveillance automatic networking monitoring and analysis method for a hydropower plant is proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a video surveillance automatic networking monitoring and analysis method for a hydropower plant, including: S1, monitoring related information extraction: taking the monitoring cameras in the key monitoring areas set in the target hydropower plant as each monitoring device of interest, extracting the transmission network bandwidth, each set camera parameter and networking related data of each monitoring device of interest.

[0008] S2. Extraction of equipment monitoring data: Extracting monitoring data of each monitoring equipment of interest.

[0009] S3. Equipment monitoring data analysis: Analyze the operating status of each monitoring device of concern to obtain the operating compliance of each monitoring device of concern.

[0010] S4. Extraction of monitoring transmission data: extracting the marking timestamp of each monitoring image transmission corresponding to each monitoring device of concern.

[0011] S5. Monitoring transmission data analysis: Analyze the transmission status of each monitoring device of concern to obtain the transmission timeliness status of each monitoring device of concern.

[0012] S6. Monitoring equipment adjustment assessment: Assess the need for adjustment of each monitoring equipment of concern, and the assessment result is either required or not required.

[0013] S7. Determine the equipment adjustment plan: The monitoring equipment that is evaluated as a demand is selected as the adjustment equipment, and the adjustment strategy of the adjustment equipment is confirmed.

[0014] S8. Monitoring equipment adjustment feedback: Feedback the adjustment strategy of the adjustment equipment and the operating stability and transmission timeliness status of each monitoring equipment to the monitoring and operation management personnel of the target hydropower plant.

[0015] Preferably, the operating status analysis of each monitoring device of interest includes: locating the monitoring time point and monitoring image of each monitoring from the monitoring data, and calculating the monitoring image quality compliance δ of each monitoring device of interest. j , j represents the monitoring device number, j=1,2,......m.

[0016] Use feature extraction algorithm to monitor the key feature points in the monitoring images of each monitoring device of interest, extract the position of each key feature point, evaluate the deviation image based on it, and count the number of deviation images corresponding to each monitoring device of interest P j , and at the same time extract the monitoring time point of each deviation image.

[0017] Count the number of key feature points in the monitoring images of each monitoring device of interest, and extract the highest number of key feature points M j and the minimum number of key feature points M j ′.

[0018] Statistics on the compliance of monitoring content of each monitoring device of concern β j , ΔM is the difference in the number of reference key feature points, and P′ is the number of set reference deviation images.

[0019] Statistics on the operation compliance of each monitoring device δ′ and β′ are respectively the monitoring image quality conformity and monitoring content conformity of the set reference.

[0020] Preferably, the counting of the monitoring image quality compliance of each monitoring device of interest includes: confirming the reference image quality index of each monitoring device of interest according to each set camera parameter of each monitoring device of interest.

[0021] The value of each image evaluation index is located from the monitoring image of each monitoring device corresponding to each monitoring, imported into the image quality evaluation model, and the monitoring image quality index of each monitoring device corresponding to each monitoring is output.

[0022] The monitoring time point is used as the horizontal axis and the monitoring image quality parameter is used as the vertical axis to construct the monitoring image quality index change curve of each monitoring device of interest, from which the slope (k 质 ) j and the number of fluctuation points D j Extract and locate the curve segment length l below its reference image quality index j .

[0023] Statistical analysis of the monitoring image quality compliance of each monitoring device j , l j ′ represents the length of the monitoring image quality index change curve of the jth monitoring device of interest, k′ 质 is the reference change rate, and D′ is the number of reference fluctuation points.

[0024] Preferably, the transmission status analysis of each monitoring device of interest includes: locating a collection mark timestamp and a transmission mark timestamp from the mark timestamp of each monitoring device corresponding to each monitoring image transmission, and taking the interval duration between the two mark timestamps as the transmission interval duration.

[0025] With the transmission interval duration as the horizontal axis and the monitoring image transmission order as the vertical axis, a transmission interval duration change curve of each monitoring device of concern is constructed, and the slope is extracted from it as the transmission interval duration change rate.

[0026] If the transmission interval duration change rate of a certain monitoring device is greater than 0, the transmission delay is used as the transmission timeliness status of the monitoring device.

[0027] If the transmission interval duration change rate of a monitored device is less than or equal to 0, the monitored device is recorded as a device to be confirmed, and the transmission timeliness is judged according to the transmission timeliness judgment rule.

[0028] If the transmission timeliness judgment result is timely, the transmission timeliness is used as the transmission timeliness status of the device to be confirmed. If the transmission timeliness judgment result is untimely, the transmission delay is used as the transmission timeliness status of the device to be confirmed, so as to obtain the transmission timeliness status of each monitored device.

[0029] Preferably, the transmission timeliness judgment is performed through the transmission timeliness judgment rule, including: dividing the transmission interval duration change curve of the device to be confirmed into two equal parts to obtain two divided curve segments, extracting the slopes of the two curve segments, sorting the two curve segments according to the monitoring order, and recording the slopes as k1 and k2 in turn according to the sorting results.

[0030] If k1≤0 and k2≤0 or k1<0 or k2=0, timeliness is used as the result of transmission timeliness judgment.

[0031] If k1=0 and k2<0, untimely is used as the result of transmission timeliness judgment.

[0032] Preferably, the step of assessing the adjustment requirements of each monitoring device of interest includes: taking the operation compliance being less than the set monitoring device operation compliance as assessment condition 1.

[0033] The transmission timeliness state is set as transmission delay as evaluation condition 2.

[0034] If the operational compliance of a certain monitoring device meets assessment condition 1 or its transmission timeliness status meets assessment condition 2, the demand adjustment will be taken as the adjustment demand assessment result of the monitoring device.

[0035] If the operational compliance of a certain monitoring device does not meet assessment condition 1 and the transmission timeliness status of the monitoring device does not meet assessment condition 2, no adjustment will be required as the adjustment need assessment result of the monitoring device.

[0036] Preferably, the confirming the adjustment strategy of the adjustment device includes: evaluating the adjustment device through an adjustment type evaluation model, and outputting the adjustment type of the adjustment device, wherein the adjustment type consists of one or more of type A, type B and type C.

[0037] If the adjustment type is type A, extract the monitoring image quality index change curve and reference image quality index of the adjustment equipment to confirm the appropriate cleaning frequency p of the adjustment equipment 清 , p 清 as an adjustment strategy.

[0038] If the adjustment type is type B, confirm the appropriate viewing angle correction frequency p of the adjustment device. 矫 , p 矫 as an adjustment strategy.

[0039] If the adjustment type is type C, extract the networking-related data of each monitored device, and confirm the additional network transmission channel of the adjusted device based on it, and use it as the adjustment strategy.

[0040] If the adjustment type is type A and type B, p 清 and p 矫 as an adjustment strategy.

[0041] If the adjustment type is type A and type C, p 清 and increase network transmission channels as adjustment strategies.

[0042] If the adjustment type is type B and type C, p 矫 and increase network transmission channels as adjustment strategies.

[0043] If the adjustment type is type A, type B, and type C, p 清 、p 矫 and increase network transmission channels as adjustment strategies.

[0044] Preferably, the confirmation of the appropriate cleaning frequency of the adjustment device includes: locating each curve segment located below the reference image quality index of the adjustment device from the monitoring image quality index change curve of the adjustment device as each deviation segment, and extracting the monitoring time point at the starting point of the change curve as the starting monitoring time point.

[0045] The monitoring time point of each deviation segment is extracted, and the monitoring interval duration between each deviation segment is obtained by comparison. The monitoring interval dispersion μ of the deviation segment is calculated by variance.

[0046] Sort each deviation segment in the order of its monitoring time, take the starting monitoring time point of the first deviation segment as the deviation monitoring time point, and extract the interval monitoring time length t between the deviation monitoring time point and the starting monitoring time point 间 .

[0047] Statistically adjust the appropriate cleaning frequency p of the equipment 清 , p0 is the reference suitable cleaning frequency corresponding to the set unit interval deviation factor, μ′, t′ 间 Set the reference monitoring interval discreteness and deviation interval duration respectively.

[0048] Preferably, the confirming of the appropriate viewing angle correction frequency of the adjustment device includes: extracting each deviation image corresponding to the adjustment device, and sorting them according to the monitoring time, and taking the deviation image ranked first as the target image.

[0049] Count and adjust the monitoring times of the equipment, and select the monitoring times before the monitoring time point of the target image as the stable monitoring times M 稳 .

[0050] The appropriate viewing angle correction frequency p of the statistical adjustment device 矫 , p 矫 =p 基 +max(M′ 稳 -M 稳 ,0)*p1,p 基 is the reference correction frequency corresponding to the set surveillance camera, M′ 稳 is the set reference stability monitoring times, p1 is the set unit stability monitoring times difference corresponding to the reference increase correction frequency.

[0051] Preferably, the confirming the increase of the network transmission channel of the adjustment device includes: recording the transmission network bandwidth of the adjustment device as K0.

[0052] The bandwidth and transmission times of each set network transmission channel are located from the networking related data, and the utilization rate of each set network transmission channel of each monitoring device is calculated based on this.

[0053] The network transmission channels with utilization rates less than 20% are set as idle channels, and the idle channels of the various monitoring devices of concern are integrated to construct an idle channel set.

[0054] The idle channels with bandwidth less than K0 are filtered out from the idle channels, and the idle channels with the lowest utilization rate are selected from the idle channels remaining after filtering as the additional network transmission channels for adjusting the equipment.

[0055] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention combines the layout position of the monitoring equipment, the setting of camera parameters and various monitoring data, conducts operation status analysis and transmission status analysis and adjustment demand assessment, and then confirms the adjustment strategy of the adjustment equipment, which effectively solves the limitations of the current video monitoring automatic networking monitoring and analysis, ensures the stability of subsequent monitoring and the timeliness of subsequent data transmission and the timeliness of abnormal event response, maintains the reliability and safety of the corresponding power generation of the hydropower plant, and at the same time reduces the risk and accident rate of hydropower generation as much as possible.

[0056] (2) When performing operating status analysis, the present invention conducts dynamic regularity analysis from the two dimensions of image quality and image content, intuitively displaying the monitoring status of each monitoring device, thereby facilitating timely adjustment of the monitoring device as needed, and also avoids the shortcomings of the current camera operating status analysis from the image quality level, thereby improving the reliability and persuasiveness of the monitoring device operating status analysis results, and also provides a data basis for the formulation of subsequent monitoring device adjustment strategies, thereby improving the reliability and stability of subsequent corresponding monitoring of the monitoring device.

[0057] (3) The present invention performs content analysis on the monitoring images of the monitoring device at each monitoring time, thereby statistically analyzing the compliance of the monitoring content, and further reveals the deviation of the monitoring angle of the current monitoring device, so as to facilitate the timeliness of subsequent monitoring device angle correction and maintenance, while also reducing the error in the subsequent monitoring process, ensuring the monitoring scope and monitoring targeting.

[0058] (4) The present invention analyzes the transmission status of each monitoring device and intuitively displays the transmission delay of each monitoring device, thereby facilitating timely optimization of the network status of the monitoring device and timely handling of subsequent abnormal situations, thereby ensuring the timeliness of abnormal event detection and handling.

[0059] (5) When confirming the adjustment strategy of the adjustment equipment, the present invention formulates targeted strategies from three aspects: the monitoring image quality compliance, monitoring content compliance and transmission timeliness status of the monitoring equipment, thereby greatly improving the recognition, reference and authenticity of the subsequent monitoring equipment monitoring screens, and also reducing the probability of transmission delay events, thereby significantly improving the reliability and safety of the operation and maintenance of the hydropower plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0061] Figure 1 The present invention is a schematic flow chart of the steps for implementing the method. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] See also Figure 1 As shown, the present invention provides a method for automatic networking monitoring and analysis of video surveillance for a hydropower plant, the method comprising: S1, extraction of monitoring related information: taking the monitoring cameras in the key monitoring areas set in the target hydropower plant as each monitoring device of interest, extracting the transmission network bandwidth, each set camera parameter and networking related data of each monitoring device of interest.

[0064] In a specific embodiment, the camera parameters include but are not limited to resolution and frame rate, and the networking related data include but are not limited to bandwidth and transmission times of each set network transmission channel.

[0065] S2. Extraction of equipment monitoring data: Extract monitoring data of each monitoring equipment of interest, including monitoring time points and monitoring images of each monitoring.

[0066] S3. Equipment monitoring data analysis: Analyze the operating status of each monitoring device of concern to obtain the operating compliance of each monitoring device of concern.

[0067] Specifically, the operation status of each monitoring device of interest is analyzed, including: S31, locating the monitoring time point and monitoring image of each monitoring from the monitoring data, and calculating the monitoring image quality compliance degree δ of each monitoring device of interest j , j represents the monitoring device number, j=1,2,......m.

[0068] Understandably, the statistics of the monitoring image quality compliance of each monitoring device of interest include: F1, confirming the reference image quality index of each monitoring device of interest according to each set camera parameter of each monitoring device of interest.

[0069] F2. Locate the value of each image evaluation index from the monitoring image of each monitoring device corresponding to each monitoring, import it into the image quality evaluation model, and output the monitoring image quality index of each monitoring device corresponding to each monitoring.

[0070] In a specific embodiment, image evaluation indicators include but are not limited to resolution, contrast, saturation, signal-to-noise ratio, and clarity, and the image quality evaluation model is an existing evaluation algorithm, such as the structural similarity index SSIM, the perceptual model quality index PIQI, VIF and other algorithms. The specific selection can refer to the actual scene requirements, and the specific evaluation process is not described in detail.

[0071] F3, using the monitoring time point as the horizontal axis and the monitoring image quality parameter as the vertical axis to construct the monitoring image quality index change curve of each monitoring device of concern, from which the slope (k 质 ) j and the number of fluctuation points D j Extract and locate the curve segment length l below its reference image quality index j .

[0072] In a specific embodiment, extracting the slope from a curve refers to extracting the slope of the regression line corresponding to the curve. The subsequent extraction of the curve slope is not repeated here. The fluctuation point refers to a point with opposite growth directions on the left and right, such as a point where the left side rises and the right side falls, or a point where the left side falls and the right side rises.

[0073] F4. Count the monitoring image quality compliance of each monitoring device δ j , l j ′ represents the length of the monitoring image quality index change curve of the jth monitoring device of interest, k′ 质 is the reference change rate, and D′ is the number of reference fluctuation points.

[0074] S32, using a feature extraction algorithm to monitor each key feature point in the monitoring image corresponding to each monitoring of each monitoring device, and extracting the position of each key feature point, based on which to evaluate the deviation image, and counting the number of deviation images corresponding to each monitoring device of interest P j , and at the same time extract the monitoring time point of each deviation image.

[0075] In a specific embodiment, the specific evaluation process for deviation image evaluation is: sorting the monitoring images of each monitoring according to the monitoring time, taking the monitoring image ranked first as the benchmark image, and taking the images in other rankings as reference images.

[0076] The positions of the key feature points in the monitoring images of each monitoring device of concern at each monitoring time are compared with each other, and the positions of the key feature points in the benchmark images of each monitoring device of concern are compared with the positions of the key feature points in its reference images. If there are key feature points with inconsistent positions between the benchmark image and a reference image, the reference image is used as the deviation image, and the number of deviation images corresponding to each monitoring device of concern is counted.

[0077] It should be added that the feature point extraction algorithm is an existing relatively mature algorithm, which includes but is not limited to SIFT, SURF and ORB, and its specific extraction process is not described here.

[0078] S33, counting the number of key feature points in the monitoring images of each monitoring device of interest corresponding to each monitoring, and extracting the highest number of key feature points M j and the minimum number of key feature points M j ′.

[0079] S34. Count the compliance of monitoring content of each monitoring device of interest β j , ΔM is the difference in the number of reference key feature points, and P′ is the number of set reference deviation images.

[0080] The embodiment of the present invention performs content analysis on the monitoring images of the monitoring device at each monitoring, thereby counting the compliance of the monitoring content, and further reveals the deviation of the monitoring angle of view of the current monitoring device, so as to facilitate the timeliness of subsequent monitoring device angle correction and maintenance, while also reducing the error in the subsequent monitoring process, ensuring the monitoring scope and monitoring targeting.

[0081] S35. Count the operational compliance of each monitoring device δ′ and β′ are respectively the monitoring image quality conformity and monitoring content conformity of the set reference.

[0082] When performing operating status analysis, the embodiment of the present invention intuitively displays the monitoring status of each monitoring device by performing dynamic regularity analysis from the two dimensions of image quality and image content, thereby facilitating timely adjustment of the monitoring device according to demand, and also avoids the shortcomings of the current camera operating status analysis from the image quality level, thereby improving the reliability and persuasiveness of the monitoring device operating status analysis results, and also provides a data basis for the formulation of subsequent monitoring device adjustment strategies, thereby improving the reliability and stability of subsequent corresponding monitoring of monitoring devices.

[0083] S4. Extraction of monitoring transmission data: extracting the marking timestamp of each monitoring image transmission corresponding to each monitoring device of concern.

[0084] S5. Monitoring transmission data analysis: Analyze the transmission status of each monitoring device of concern to obtain the transmission timeliness status of each monitoring device of concern.

[0085] Specifically, the transmission status of each monitoring device of interest is analyzed, including: S51, locating the acquisition mark timestamp and the transmission mark timestamp from the mark timestamp of each monitoring device corresponding to each monitoring image transmission, and taking the interval length between the two mark timestamps as the transmission interval length.

[0086] S52, using the transmission interval duration as the horizontal axis and the monitoring image transmission order as the vertical axis, construct a transmission interval duration change curve for each monitoring device of interest, and extract the slope from it as the transmission interval duration change rate.

[0087] S53: If the transmission interval duration change rate of a certain monitoring device is greater than 0, the transmission delay is used as the transmission timeliness status of the monitoring device.

[0088] S54: If the transmission interval duration change rate of a monitored device is less than or equal to 0, the monitored device is recorded as a device to be confirmed, and the transmission timeliness is judged according to the transmission timeliness judgment rule.

[0089] Furthermore, the transmission timeliness judgment is performed through the transmission timeliness judgment rule, including: dividing the transmission interval duration change curve of the device to be confirmed into two equal parts to obtain two divided curve segments, extracting the slopes of the two curve segments, sorting the two curve segments according to the monitoring order, and recording the slopes as k1 and k2 according to the sorting results.

[0090] If k1≤0 and k2≤0 or k1<0 or k2=0, timeliness is used as the result of transmission timeliness judgment.

[0091] If k1=0 and k2<0, untimely is used as the result of transmission timeliness judgment.

[0092] S55. If the result of the transmission timeliness judgment is timely, the transmission timeliness is used as the transmission timeliness status of the device to be confirmed. If the result of the transmission timeliness judgment is untimely, the transmission delay is used as the transmission timeliness status of the device to be confirmed, thereby obtaining the transmission timeliness status of each monitored device.

[0093] The embodiment of the present invention analyzes the transmission status of each monitoring device and intuitively displays the transmission delay of each monitoring device, thereby facilitating timely optimization of the network status of the monitoring device and timely handling of subsequent abnormal situations, thereby ensuring the timeliness of abnormal event detection and processing.

[0094] S6. Monitoring equipment adjustment assessment: Assess the need for adjustment of each monitoring equipment of concern, and the assessment result is either required or not required.

[0095] Specifically, the adjustment needs of each monitoring device of concern are assessed, including: taking the operation compliance less than the set monitoring device operation compliance as assessment condition 1.

[0096] The transmission timeliness state is set as transmission delay as evaluation condition 2.

[0097] If the operational compliance of a certain monitoring device meets assessment condition 1 or its transmission timeliness status meets assessment condition 2, the demand adjustment will be taken as the adjustment demand assessment result of the monitoring device.

[0098] If the operational compliance of a certain monitoring device does not meet assessment condition 1 and the transmission timeliness status of the monitoring device does not meet assessment condition 2, no adjustment will be required as the adjustment need assessment result of the monitoring device.

[0099] S7. Determine the equipment adjustment plan: The monitoring equipment that is evaluated as a demand is selected as the adjustment equipment, and the adjustment strategy of the adjustment equipment is confirmed.

[0100] Specifically, confirming the adjustment strategy of the adjustment device includes: S71, evaluating the adjustment device through an adjustment type evaluation model, and outputting the adjustment type of the adjustment device, where the adjustment type consists of one or more of type A, type B and type C.

[0101] In a specific embodiment, for ease of understanding, Type A, Type B, and Type C are camera cleaning adjustment, camera orientation correction, and transmission network channel adjustment, respectively.

[0102] In a specific embodiment, the adjustment device is evaluated by an adjustment type evaluation model, including: extracting the monitoring image quality compliance, monitoring content compliance and transmission timeliness status of the adjustment device.

[0103] The monitoring image quality compliance and monitoring content compliance of the adjusted equipment are denoted as δ 调 and β 调 , the adjustment type assessment model is as follows:

[0104]

[0105] S72: If the adjustment type is type A, extract the monitoring image quality index change curve and the reference image quality index of the adjustment device to confirm the appropriate cleaning frequency p of the adjustment device. 清 , p 清 as an adjustment strategy.

[0106] Further, confirming the appropriate cleaning frequency of the adjustment device includes: R1, locating each curve segment located below the reference image quality index of the adjustment device from the monitoring image quality index change curve of the adjustment device as each deviation segment, and extracting the monitoring time point at the starting point of the change curve as the starting monitoring time point.

[0107] R2. Extract the monitoring time point of each deviation segment, compare and obtain the monitoring interval duration between each deviation segment, and calculate the monitoring interval dispersion μ of the deviation segment through variance.

[0108] R3. Sort the deviation segments in the order of their monitoring time, take the starting monitoring time point of the first deviation segment as the deviation monitoring time point, and extract the interval monitoring time length t between the deviation monitoring time point and the starting monitoring time point 间 .

[0109] R4. Statistically adjust the appropriate cleaning frequency p of the equipment 清 , p0 is the reference suitable cleaning frequency corresponding to the set unit interval deviation factor, μ′, t′ 间 Set the reference monitoring interval discreteness and deviation interval duration respectively. Represents the interval deviation factor.

[0110] S73: If the adjustment type is type B, confirm the appropriate viewing angle correction frequency p of the adjustment device. 矫 , p 矫 as an adjustment strategy.

[0111] Further, confirming the appropriate viewing angle correction frequency of the adjustment device includes: extracting each deviation image corresponding to the adjustment device, and sorting them according to the monitoring time, and taking the deviation image ranked first as the target image.

[0112] Count and adjust the monitoring times of the equipment, and select the monitoring times before the monitoring time point of the target image as the stable monitoring times M 稳 .

[0113] The appropriate viewing angle correction frequency p of the statistical adjustment device 矫 , p 矫 =p 基 +max(M′ 稳 -M 稳 ,0)*p1,p 基 is the reference correction frequency corresponding to the set surveillance camera, M′ 稳 is the set reference stability monitoring times, p1 is the set unit stability monitoring times difference corresponding to the reference increase correction frequency.

[0114] S74. If the adjustment type is type C, extract the networking related data of each monitored device, confirm the additional network transmission channel of the adjusted device based on the data, and use it as the adjustment strategy.

[0115] Specifically, confirming the added network transmission channel of the adjustment device includes: J1. Recording the transmission network bandwidth of the adjustment device as K0.

[0116] J2. Locate the bandwidth and transmission times of each set network transmission channel from the networking related data, and calculate the utilization rate of each set network transmission channel of each monitoring device based on this.

[0117] In a specific embodiment, the utilization rate of each set network transmission channel is the ratio of the number of transmissions of each set network transmission channel to the sum of the corresponding number of transmissions of each set network transmission channel.

[0118] J3. Set the network transmission channels with utilization rates less than 20% as idle channels, integrate the idle channels of each monitoring device, and construct an idle channel set.

[0119] J4. Filter out idle channels with bandwidth less than K0 from the idle channels, and select the idle channel with the lowest utilization rate from the idle channels remaining after filtering as the additional network transmission channel for the adjustment device.

[0120] S75. If the adjustment type is type A or type B, p 清 and p 矫 as an adjustment strategy.

[0121] S76. If the adjustment type is type A or type C, p清 and increase network transmission channels as adjustment strategies.

[0122] S77. If the adjustment type is type B or type C, p 矫 and increase network transmission channels as adjustment strategies.

[0123] S78. If the adjustment type is type A, type B, or type C, p 清 、p 矫 and increase network transmission channels as adjustment strategies.

[0124] When confirming the adjustment strategy of the adjustment device, the embodiment of the present invention formulates targeted strategies from three aspects: the monitoring image quality compliance, monitoring content compliance and transmission timeliness status of the monitoring device, thereby greatly improving the recognition, reference and authenticity of the subsequent monitoring images of the monitoring device, and also reducing the probability of transmission delay events, thereby significantly improving the reliability and safety of the operation and maintenance of the hydropower plant.

[0125] S8. Monitoring equipment adjustment feedback: Feedback the adjustment strategy of the adjustment equipment and the operating stability and transmission timeliness status of each monitoring equipment to the monitoring and operation management personnel of the target hydropower plant.

[0126] The embodiment of the present invention combines the layout position of the monitoring equipment, the setting of camera parameters and various monitoring data, performs operation status analysis and transmission status analysis and adjustment demand assessment, and then confirms the adjustment strategy of the adjustment equipment, thereby effectively solving the limitations of the current video monitoring automatic networking monitoring and analysis, ensuring the stability of subsequent monitoring and the timeliness of subsequent data transmission and the timeliness of abnormal event response, maintaining the reliability and safety of the corresponding power generation of the hydropower plant, and at the same time reducing the risk and accident rate of hydropower generation as much as possible.

[0127] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A video surveillance automatic networking monitoring and analysis method for a hydropower plant, characterized by: include: S1. Extraction of monitoring-related information: Taking the monitoring cameras in the key monitoring areas of the target hydropower plant as the monitoring devices of interest, extracting the transmission network bandwidth, the camera parameters and networking-related data of the monitoring devices of interest; S2. Extraction of equipment monitoring data: Extracting monitoring data of each monitoring equipment of interest; S3. Equipment monitoring data analysis: Analyze the operating status of each monitoring device of concern to obtain the operating compliance of each monitoring device of concern; S4, monitoring transmission data extraction: extracting the marking timestamp of each monitoring image transmission corresponding to each monitoring device of concern; S5. Monitoring transmission data analysis: Analyze the transmission status of each monitoring device of interest to obtain the transmission timeliness status of each monitoring device of interest; S6. Monitoring equipment adjustment assessment: Evaluate the adjustment needs of each monitoring equipment of concern, and the assessment result is either required or not required; S7. Determine the equipment adjustment plan: take the monitoring equipment with the assessment result as the demand as the adjustment equipment, and confirm the adjustment strategy of the adjustment equipment; S8. Monitoring equipment adjustment feedback: Feedback the adjustment strategy of the adjustment equipment and the operating stability and transmission timeliness status of each monitoring equipment to the monitoring and operation management personnel of the target hydropower plant.

2. The video surveillance automatic networking monitoring and analysis method for a hydropower plant as claimed in claim 1, characterized in that: The operating status analysis of each monitoring device includes: Locate the monitoring time point and monitoring image of each monitoring from the monitoring data, and calculate the monitoring image quality compliance δ of each monitoring device of interest j , j represents the monitoring device number, j=1,2,......m; Use feature extraction algorithm to monitor the key feature points in the monitoring images of each monitoring device of interest, extract the position of each key feature point, evaluate the deviation image based on it, and count the number of deviation images corresponding to each monitoring device of interest P j , and at the same time extract the monitoring time point of each deviation image; Count the number of key feature points in the monitoring images of each monitoring device of interest, and extract the highest number of key feature points M j and the minimum number of key feature points M j ′; Statistics on the compliance of monitoring content of each monitoring device of concern β j , ΔM is the difference in the number of reference key feature points, and P′ is the number of set reference deviation images; Statistics on the operation compliance of each monitoring device δ′ and β′ are respectively the monitoring image quality conformity and monitoring content conformity of the set reference.

3. The video surveillance automatic networking monitoring and analysis method for a hydropower plant as claimed in claim 2, characterized in that: The counting of the monitoring image quality compliance of each monitoring device of interest includes: Determine the reference image quality index of each monitoring device of interest according to each set camera parameter of each monitoring device of interest; Locate the value of each image evaluation index from the monitoring image of each monitoring device corresponding to each monitoring, import it into the image quality evaluation model, and output the monitoring image quality index of each monitoring device corresponding to each monitoring; The monitoring time point is used as the horizontal axis and the monitoring image quality parameter is used as the vertical axis to construct the monitoring image quality index change curve of each monitoring device of interest, from which the slope (k 质 ) j and the number of fluctuation points D j Extract and locate the curve segment length l below its reference image quality index j ; Statistical analysis of the monitoring image quality compliance of each monitoring device j , l j ′ represents the length of the monitoring image quality index change curve of the jth monitoring device of interest, k′ 质 is the reference change rate, and D′ is the number of reference fluctuation points.

4. A video surveillance automatic networking monitoring and analysis method for a hydropower plant as claimed in claim 3, characterized in that: The transmission status analysis of each monitoring device includes: Locate the acquisition mark timestamp and the transmission mark timestamp from the mark timestamps of each monitoring image transmission corresponding to each monitoring device of interest, and use the interval between the two mark timestamps as the transmission interval; With the transmission interval duration as the horizontal axis and the monitoring image transmission order as the vertical axis, a transmission interval duration change curve of each monitoring device of interest is constructed, and the slope is extracted from it as the transmission interval duration change rate; If the transmission interval duration change rate of a certain monitoring device is greater than 0, the transmission delay is used as the transmission timeliness status of the monitoring device; If the transmission interval duration change rate of a monitored device is less than or equal to 0, the monitored device is recorded as a device to be confirmed, and the transmission timeliness is judged according to the transmission timeliness judgment rule; If the transmission timeliness judgment result is timely, the transmission timeliness is used as the transmission timeliness status of the device to be confirmed. If the transmission timeliness judgment result is untimely, the transmission delay is used as the transmission timeliness status of the device to be confirmed, so as to obtain the transmission timeliness status of each monitored device.

5. The video surveillance automatic networking monitoring and analysis method for a hydropower plant as claimed in claim 4, characterized in that: The timeliness of transmission is judged by using a timeliness of transmission judgment rule, including: Divide the transmission interval duration change curve of the device to be confirmed into two equal parts to obtain two divided curve segments, extract the slopes of the two curve segments, sort the two curve segments according to the monitoring order, and record the slopes as k1 and k2 in turn according to the sorting results; If k1≤0 and k2≤0 or k1<0 or k2=0, the timely transmission will be regarded as the result of the judgment of transmission timeliness; If k1=0 and k2<0, untimely is used as the result of transmission timeliness judgment.

6. The video surveillance automatic networking monitoring and analysis method for a hydropower plant as claimed in claim 1, characterized in that: The adjustment requirement assessment for each monitoring device of concern includes: The operation compliance degree is less than the set monitoring equipment operation compliance degree as evaluation condition 1; The transmission timeliness state is transmission delay as evaluation condition 2; If the operational compliance of a certain monitoring device meets the assessment condition 1 or its transmission timeliness status meets the assessment condition 2, the demand adjustment will be regarded as the adjustment demand assessment result of the monitoring device; If the operational compliance of a certain monitoring device does not meet assessment condition 1 and the transmission timeliness status of the monitoring device does not meet assessment condition 2, no adjustment will be required as the adjustment need assessment result of the monitoring device.

7. The video surveillance automatic networking monitoring and analysis method for a hydropower plant as claimed in claim 4, characterized in that: The step of confirming and adjusting the adjustment strategy of the device includes: Evaluate the adjustment device through the adjustment type evaluation model, and output the adjustment type of the adjustment device, where the adjustment type consists of one or more of type A, type B and type C; If the adjustment type is type A, extract the monitoring image quality index change curve and reference image quality index of the adjustment equipment to confirm the appropriate cleaning frequency p of the adjustment equipment 清 , p 清 As an adjustment strategy; If the adjustment type is type B, confirm the appropriate viewing angle correction frequency p of the adjustment device. 矫 , p 矫 As an adjustment strategy; If the adjustment type is type C, extract the networking related data of each monitoring device of concern, confirm the additional network transmission channel of the adjusted device based on it, and use it as the adjustment strategy; If the adjustment type is type A and type B, p 清 and p 矫 As an adjustment strategy; If the adjustment type is type A and type C, p 清 and increase network transmission channels as an adjustment strategy; If the adjustment type is type B and type C, p 矫 and increasing network transmission channels as an adjustment strategy; If the adjustment type is type A, type B, and type C, p 清 、p 矫 and increase network transmission channels as adjustment strategies.

8. The video surveillance automatic networking monitoring and analysis method for a hydropower plant as claimed in claim 7, characterized in that: The confirmation and adjustment of the appropriate cleaning frequency of the equipment includes: Locating each curve segment located below the reference image quality index of the adjustment device from the monitoring image quality index change curve of the adjustment device as each deviation segment, and extracting the monitoring time point at the starting point of the change curve as the starting monitoring time point; Extract the monitoring time point of each deviation segment, compare and obtain the monitoring interval length between each deviation segment, and calculate the monitoring interval dispersion μ of the deviation segment through variance; Sort each deviation segment in the order of its monitoring time, take the starting monitoring time point of the first deviation segment as the deviation monitoring time point, and extract the interval monitoring time length t between the deviation monitoring time point and the starting monitoring time point 间 ; Statistically adjust the appropriate cleaning frequency p of the equipment 清 , p0 is the reference suitable cleaning frequency corresponding to the set unit interval deviation factor, μ′, t′ 间 Set the reference monitoring interval discreteness and deviation interval duration respectively.

9. The video surveillance automatic networking monitoring and analysis method for a hydropower plant as claimed in claim 7, characterized in that: The step of confirming and adjusting the appropriate viewing angle correction frequency of the device comprises: Extract the deviation images corresponding to the adjustment equipment, sort them according to the monitoring time, and take the deviation image ranked first as the target image; Count and adjust the monitoring times of the equipment, and select the monitoring times before the monitoring time point of the target image as the stable monitoring times M 稳 ; The appropriate viewing angle correction frequency p of the statistical adjustment device 矫 , p 矫 =p 基 +max(M′ 稳 -M 稳 ,0)*p1,p 基 is the reference correction frequency corresponding to the set surveillance camera, M′ 稳 is the set reference stability monitoring times, p1 is the set unit stability monitoring times difference corresponding to the reference increase correction frequency.

10. The video surveillance automatic networking monitoring and analysis method for a hydropower plant as claimed in claim 7, characterized in that: The step of confirming and adjusting the increase of the network transmission channel of the device includes: The transmission network bandwidth of the adjustment device is recorded as K0; Locate the bandwidth and transmission times of each set network transmission channel from the networking related data, and calculate the utilization rate of each set network transmission channel of each monitoring device based on this; The network transmission channels with utilization rates less than 20% are set as idle channels, and the idle channels of the monitoring devices of concern are integrated to construct an idle channel set; The idle channels with bandwidth less than K0 are filtered out from the idle channels, and the idle channels with the lowest utilization rate are selected from the idle channels remaining after filtering as the additional network transmission channels for adjusting the equipment.

Images