CN115409210A

CN115409210A - Control method and device of monitoring equipment, computer equipment and storage medium

Info

Publication number: CN115409210A
Application number: CN202211005241.6A
Authority: CN
Inventors: 王玉俊; 禹晋云; 乔柱桥; 李少森; 张任驰; 吴斌; 任君; 柳坤; 吕俊瑶; 杨启宾; 阮峻; 陈图腾; 王超; 周乐; 周翔; 马正霖; 黄剑湘; 孙豪; 黄大彬; 杨锐雄
Original assignee: Kunming Bureau of Extra High Voltage Power Transmission Co
Current assignee: Kunming Bureau of Extra High Voltage Power Transmission Co
Priority date: 2022-08-22
Filing date: 2022-08-22
Publication date: 2022-11-29

Abstract

The present application relates to a method of controlling a monitoring apparatus, an apparatus, a computer device, a storage medium and a computer program product. The method comprises the following steps: acquiring first parameter fitness of a first monitoring image acquired by each of at least two candidate devices; comparing the first parameter fitness of the at least two candidate equipment, and determining target equipment from the at least two candidate equipment according to the comparison result; adjusting initial acquisition parameters of the target equipment to obtain initial adjustment parameters, outputting the initial adjustment parameters to the target equipment, and obtaining second parameter fitness of a second monitoring image acquired by the target equipment according to the initial adjustment parameters; and acquiring target acquisition parameters of the target equipment based on the first parameter fitness and the second parameter fitness of the target equipment, and taking monitoring images acquired according to the target acquisition parameters as target monitoring images. By adopting the method, the fault processing efficiency of the converter station can be improved.

Description

Control method and device of monitoring equipment, computer equipment and storage medium

Technical Field

The present application relates to the field of converter station fault monitoring technologies, and in particular, to a method and an apparatus for controlling monitoring equipment, a computer device, a storage medium, and a computer program product.

Background

In a direct current transmission system, a converter station is an important ring, and the mutual exchange of alternating current and direct current is realized through the converter station, so that the quality of electric energy is ensured. With the development of converter station fault monitoring technology, various intelligent monitoring devices for converter station fault monitoring appear.

In the conventional technology, fault monitoring is carried out on the converter station through intelligent monitoring equipment such as a patrol robot, an unmanned aerial vehicle, a valve hall temperature measurement system and a patrol system, and fault judgment is carried out on the converter station through monitoring data generated by the intelligent monitoring equipment.

However, because the intelligent monitoring equipment for fault monitoring in the converter station has a plurality of types and a large number, when the intelligent monitoring equipment in the conventional technology shoots a fault position, a large number of similar pictures appear in monitoring data due to the fact that monitoring probes of the intelligent monitoring equipment all point to the fault position, so that the monitoring data is redundant, and the fault processing efficiency of the converter station is affected.

Disclosure of Invention

In view of the above, it is necessary to provide a control method, an apparatus, a computer device, a computer readable storage medium and a computer program product of a monitoring device capable of improving the efficiency of converter station fault handling in view of the above technical problems.

In a first aspect, the present application provides a method of controlling a monitoring apparatus. The method comprises the following steps:

acquiring first parameter fitness of a first monitoring image acquired by each of at least two alternative devices, wherein the first parameter fitness represents the monitoring effect of the first monitoring image;

comparing the first parameter fitness of each of the at least two candidate equipment, and determining target equipment from the at least two candidate equipment according to the comparison result;

adjusting initial acquisition parameters of the target equipment to obtain initial adjustment parameters, outputting the initial adjustment parameters to the target equipment, and obtaining second parameter fitness of a second monitoring image acquired by the target equipment according to the initial adjustment parameters;

and acquiring target acquisition parameters of the target equipment based on the first parameter fitness and the second parameter fitness of the target equipment, and taking monitoring images acquired according to the target acquisition parameters as target monitoring images.

In one embodiment, the obtaining the first parameter fitness of the first monitoring image acquired by each of the at least two candidate devices comprises:

acquiring first monitoring images acquired by at least two alternative devices respectively;

respectively carrying out image effect evaluation on the first monitoring images acquired by the at least two alternative devices according to a preconfigured first monitoring image evaluation mode to obtain image effect evaluation results of the first monitoring images acquired by the at least two alternative devices;

and respectively obtaining the first parameter fitness of the first monitoring image acquired by the at least two alternative devices based on the image effect evaluation result of the first monitoring image acquired by the at least two alternative devices.

In one embodiment, the image effect evaluation result includes at least two quantitative parameter effect values, and the obtaining the first parameter fitness of the first monitoring image respectively acquired by the at least two candidate devices based on the image effect evaluation result of the first monitoring image respectively acquired by the at least two candidate devices includes:

and for each of the at least two alternative equipment, weighting and fusing at least two quantitative parameter effect values of the first monitoring image acquired by the alternative equipment according to the parameter weight pre-configured for each quantitative parameter effect value to obtain the first parameter fitness of the first monitoring image acquired by the alternative equipment.

In one embodiment, obtaining the target acquisition parameter of the target equipment based on the first parameter fitness and the second parameter fitness of the target equipment comprises:

comparing the first parameter fitness and the second parameter fitness of the target equipment, and determining the acquisition parameters to be optimized of the target equipment according to the comparison result;

and performing iterative optimization on the acquisition parameters to be optimized until an iteration stop condition is met, and obtaining target acquisition parameters of the target equipment.

In one embodiment, iteratively optimizing the acquisition parameters to be optimized until an iteration stop condition is satisfied, and obtaining the target acquisition parameters of the target equipment includes:

adjusting the acquisition parameters to be optimized to obtain adjusted acquisition parameters;

outputting the adjusted acquisition parameters to target equipment, and acquiring third parameter fitness of a third monitoring image acquired by the target equipment according to the adjusted acquisition parameters;

comparing the third parameter fitness with the parameter fitness of the monitoring image acquired according to the acquisition parameters to be optimized;

and determining new acquisition parameters to be optimized according to the comparison result, and continuously optimizing the new acquisition parameters to be optimized until an iteration stop condition is met to obtain target acquisition parameters of the target equipment.

In one embodiment, after obtaining a target acquisition parameter of the target equipment based on the first parameter fitness and the second parameter fitness of the target equipment and taking a monitoring image acquired according to the target acquisition parameter as a target monitoring image, the method further includes:

fitting the target monitoring image with a three-dimensional model at a pre-configured fault position to obtain a model fitting result;

and when the model fitting result is characterized in that the fault position is not comprehensively monitored based on the target monitoring image, controlling the standby equipment to monitor the fault position to obtain the monitoring image acquired by the standby equipment.

In a second aspect, the application further provides a control device of the monitoring equipment. The device comprises:

the fitness acquisition module is used for acquiring first parameter fitness of a first monitoring image acquired by each of at least two alternative devices, and the first parameter fitness represents a monitoring effect of the first monitoring image;

the first processing module is used for comparing the first parameter fitness of each of the at least two candidate equipment and determining target equipment from the at least two candidate equipment according to a comparison result;

the second processing module is used for adjusting the initial acquisition parameters of the target equipment to obtain initial adjustment parameters, outputting the initial adjustment parameters to the target equipment, and obtaining second parameter fitness of a second monitoring image acquired by the target equipment according to the initial adjustment parameters;

and the third processing module is used for obtaining target acquisition parameters of the target equipment based on the first parameter fitness and the second parameter fitness of the target equipment, and taking monitoring images acquired according to the target acquisition parameters as target monitoring images.

In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:

In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:

comparing the first parameter fitness of the at least two candidate equipment, and determining target equipment from the at least two candidate equipment according to the comparison result;

In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:

acquiring first parameter fitness of a first monitoring image acquired by each of at least two candidate devices, wherein the first parameter fitness represents a monitoring effect of the first monitoring image;

According to the control method, the device, the computer equipment, the storage medium and the computer program product of the monitoring equipment, the first parameter fitness of the first monitoring image acquired by the at least two alternative equipment is obtained, the first parameter fitness of the monitoring effect of the first monitoring image is compared with the first parameter fitness of the first monitoring image, the target equipment can be selected preferably according to the comparison result of the size relation of the first parameter fitness of the at least two alternative equipment, the initial acquisition parameter of the target equipment is adjusted to obtain the initial adjustment parameter, the initial adjustment parameter is output to the target equipment, the second parameter fitness of the second monitoring image acquired by the target equipment according to the initial adjustment parameter is obtained, the target acquisition parameter of the target equipment is obtained based on the first parameter fitness and the second parameter fitness of the target equipment, the acquisition parameter of the target equipment is optimized, the monitoring image acquired according to the target acquisition parameter is used as the target monitoring image, the whole process is carried out, the conversion efficiency of monitoring position monitoring image processing on the target position can be improved by comparing the first parameter fitness and the second parameter fitness of the target equipment is improved.

Drawings

FIG. 1 is a diagram of an application environment of a control method of monitoring equipment in one embodiment;

FIG. 2 is a schematic flow chart diagram of a method for controlling monitoring equipment in one embodiment;

FIG. 3 is a flow diagram illustrating a method for controlling backup equipment in one embodiment;

fig. 4 is a schematic flow chart of a control method of monitoring equipment in another embodiment;

FIG. 5 is a schematic flow diagram of a control device of the monitoring apparatus in one embodiment;

FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The control method of the monitoring equipment provided by the embodiment of the application can be applied to the application environment shown in fig. 1. Where alternative equipment 102 communicates with server 104 over a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be placed on the cloud or other network server. The server 104 obtains first parameter fitness of first monitoring images acquired by the at least two candidate devices 102, compares the first parameter fitness of the at least two candidate devices 102, determines target devices from the at least two candidate devices 102 according to comparison results, adjusts initial acquisition parameters of the target devices to obtain primary adjustment parameters, outputs the primary adjustment parameters to the target devices, obtains second parameter fitness of second monitoring images acquired by the target devices according to the primary adjustment parameters, obtains target acquisition parameters of the target devices based on the first parameter fitness and the second parameter fitness of the target devices, and takes the monitoring images acquired according to the target acquisition parameters as target monitoring images. The alternative equipment 102 may be, but is not limited to, various equipment for monitoring converter stations, among others. The server 104 may be implemented as a stand-alone server or as a server cluster comprised of multiple servers.

In one embodiment, as shown in fig. 2, a method for controlling monitoring equipment is provided, which is described by taking the method as an example applied to the server 104 in fig. 1, and includes the following steps:

step 202, obtaining first parameter fitness of a first monitoring image acquired by each of at least two candidate devices, wherein the first parameter fitness represents a monitoring effect of the first monitoring image.

The standby equipment is fixed intelligent monitoring equipment which is located around the fault position of the converter station and can shoot the fault position and the surrounding environment of the fault position, and the number of the standby equipment is at least two. For example, the alternative equipment may be a fixed probe around the fault location. The first parameter fitness is in a numerical value form, and the monitoring effect of the first monitoring image acquired by each alternative equipment is represented through the numerical value. For example, the higher the first parameter fitness of the first monitoring image acquired by the alternative equipment is, the better the monitoring effect of the first monitoring image acquired by the alternative equipment is represented.

Specifically, after a fault occurs, the server selects at least two pieces of fixed intelligent monitoring equipment capable of shooting a fault position and the surrounding environment of the fault position from the three-dimensional model of the converter station, the selected pieces of fixed intelligent monitoring equipment are used as alternative equipment, the alternative equipment is controlled to point to the fault position, the fault position is shot, a first monitoring image acquired by each alternative equipment is obtained, then image effect evaluation is performed on the first monitoring image acquired by each alternative equipment according to a preconfigured first monitoring image evaluation mode, an image effect evaluation result of the first monitoring image acquired by each alternative equipment is obtained, and first parameter fitness of the first monitoring image acquired by each alternative equipment is obtained based on the image effect evaluation result of the first monitoring image acquired by each alternative equipment.

In a specific application, in the process that a server carries out image effect evaluation on a first monitoring image acquired by each alternative device, according to the respective evaluation mode of each evaluation parameter in the preconfigured first monitoring image evaluation modes, effect evaluation is carried out on the image monitoring angle of the first monitoring image, the shielding degree of the monitoring image, the definition of the monitoring image, the distance between each alternative device and a fault when acquiring the first monitoring image and other evaluation parameters, the image effect evaluation result of the first monitoring image acquired by each alternative device is obtained, and the first parameter adaptability of the first monitoring image acquired by each alternative device is obtained based on the image effect evaluation result of the first monitoring image acquired by each alternative device.

And 204, comparing the first parameter fitness of the at least two candidate equipment, and determining the target equipment from the at least two candidate equipment according to the comparison result.

Specifically, the server compares the respective first parameter fitness of all the alternative equipment to obtain a comparison result, ranks the respective first parameter fitness of all the alternative equipment based on the comparison result, and obtains a ranking result of all the alternative equipment according to the ranking result of the first parameter fitness because the alternative equipment is in one-to-one correspondence with the first parameter fitness, and finally selects the alternative equipment with higher first parameter fitness from all the alternative equipment as the target equipment according to the ranking result of all the alternative equipment. The number of target devices may be one or more.

In a specific application, the server sorts the first parameter fitness of all the alternative equipment from large to small, the larger first parameter fitness is ranked in the front, the ranking results of all the alternative equipment are obtained according to the ranking results of all the first parameter fitness, the alternative equipment ranked in the front is selected from the ranking results of all the alternative equipment as target equipment, namely, the fixed intelligent monitoring equipment with a proper monitoring angle, a low shielding degree of a monitoring picture, a high definition of the monitoring result and a short distance from a fault position is selected as the target equipment, the fixed intelligent monitoring equipment with a askew monitoring angle, a high shielding degree of the monitoring picture, an unclear monitoring result and a long distance from the fault position is abandoned, and the alternative equipment with a poor monitoring effect is abandoned through the ranking and preference selecting processes.

And step 206, adjusting the initial acquisition parameters of the target equipment to obtain initial adjustment parameters, outputting the initial adjustment parameters to the target equipment, and obtaining second parameter fitness of a second monitoring image acquired by the target equipment according to the initial adjustment parameters.

The initial acquisition parameters of the target equipment refer to acquisition parameters preconfigured for the target device, for example, the initial acquisition parameters include an initial angle and an initial focal length of the target equipment, and a primary adjustment parameter of the target equipment is obtained by performing primary adjustment on the initial angle and the initial focal length of the target equipment, and the primary adjustment parameter refers to parameters obtained after the initial acquisition parameters are adjusted, for example, the primary adjustment parameter of the target equipment includes a primary adjustment angle and a primary adjustment focal length. The second parameter fitness is in a numerical value form, and the monitoring effect of the second monitoring image acquired by the target equipment is represented by the numerical value. For example, the higher the adaptability of the second parameter of the second monitoring image acquired by the target equipment is, the better the monitoring effect of the second monitoring image acquired by the characteristic target equipment is.

Specifically, the server performs primary adjustment on an initial acquisition parameter of the target equipment to obtain a primary adjustment parameter of the target equipment, then outputs the primary adjustment parameter of the target equipment to the target equipment, controls the target equipment to monitor a fault position under a primary adjustment angle and a primary adjustment focal length, obtains a second monitoring image acquired by the target equipment on the fault position based on the primary adjustment parameter, performs image effect evaluation on the second monitoring image based on a preconfigured second monitoring image evaluation mode to obtain an image effect evaluation result of the second monitoring image, and then obtains a second parameter fitness of the second monitoring image acquired by the target equipment according to the primary adjustment parameter based on the image effect evaluation result of the second monitoring image.

In a specific application, in the process of evaluating the image effect of the second monitoring image of the target equipment, the server can evaluate the effect of the evaluation parameters such as the monitoring angle and the monitoring definition of the second monitoring image according to the respective evaluation mode of each evaluation parameter in the preconfigured second monitoring image evaluation modes to obtain the image effect evaluation result of the second monitoring image, and obtain the second parameter fitness of the second monitoring image acquired by the target equipment based on the image effect evaluation result of the second monitoring image.

And 208, acquiring target acquisition parameters of the target equipment based on the first parameter fitness and the second parameter fitness of the target equipment, and taking the monitoring image acquired according to the target acquisition parameters as a target monitoring image.

The target acquisition parameters are acquisition parameters corresponding to the target monitoring images determined by parameter adjustment, and the target monitoring images are images with image effects meeting preconfigured monitoring requirements determined by a second monitoring image evaluation mode. The preconfigured monitoring requirements can be configured according to the actual application scenario. For example, a fitness threshold is preconfigured for a second parameter fitness of a second monitoring image acquired by the target equipment, and when the second parameter fitness reaches the fitness threshold, the second monitoring image is represented as an image meeting the preconfigured monitoring requirement. The fitness threshold value can be configured according to the actual application scene.

Specifically, the server compares the first parameter fitness of the target equipment with the second parameter fitness, when the second parameter fitness of the target equipment is larger than the first parameter fitness of the target equipment, the primary adjustment parameter of the target equipment is used as a parameter to be optimized of the target equipment, iterative optimization is conducted on the parameter to be optimized of the target equipment until an iteration stop condition is met, the target acquisition parameter of the target equipment is obtained, the target equipment is controlled to monitor the fault position under the target acquisition parameter, and a monitoring image acquired by the target equipment according to the target acquisition parameter is used as a target monitoring image.

In a specific application, the server can optimize the initial acquisition parameters of the target equipment by adopting the ant lion algorithm to obtain the target acquisition parameters of the target equipment. The ant lion algorithm simulates the ant lion hunting scene, the ants are controlled to swim nearby the ant lions, results brought by all the ants and the ant lions are compared, and more optimal ant lions are quickly screened.

In a specific application, the server can optimize the initial acquisition parameters of the target equipment by adopting the ant lion algorithm to obtain the target acquisition parameters of the target equipment. At the moment, the initial acquisition parameter of the target equipment is an initial ant lion, the first parameter fitness parameter of the target equipment is a result corresponding to the initial ant lion, the primary adjustment parameter is an ant, the second parameter fitness parameter of the target equipment is a result corresponding to the ant, the first parameter fitness and the second parameter fitness are compared, namely the result corresponding to the initial ant lion and the result corresponding to the ant are compared, when the second parameter fitness is larger than the first parameter fitness, the result corresponding to the ant is the result corresponding to the initial ant lion, the server replaces the initial ant lion, the primary adjustment parameter is used as a new ant lion, namely the primary adjustment parameter is used as an acquisition parameter to be optimized, then the new ant lion is continuously subjected to iterative optimization, namely the iterative optimization is carried out on the acquisition parameter to be optimized until an iteration stop condition is met, and the elite lion is obtained, namely the target acquisition parameter of the target equipment.

In the control method of the monitoring equipment, the server obtains the first parameter fitness of the first monitoring image acquired by each of the at least two alternative equipment, compares the first parameter fitness of the first monitoring image representing the monitoring effect of the first monitoring image of each of the at least two alternative equipment, can preferably select the target equipment according to the comparison result representing the size relationship of the first parameter fitness of each of the at least two alternative equipment, further can obtain the initial adjustment parameter by adjusting the initial acquisition parameter of the target equipment, outputs the initial adjustment parameter to the target equipment, obtains the second parameter fitness of the second monitoring image acquired by the target equipment according to the initial adjustment parameter, obtains the target acquisition parameter of the target equipment based on the first parameter fitness and the second parameter fitness of the target equipment, realizes the optimization of the acquisition parameter of the target equipment, takes the monitoring image acquired according to the target acquisition parameter as the target monitoring image, and in the whole process, optimizes the acquisition parameter of the target equipment by comparing the first parameter fitness, can obtain the target image, further can realize the monitoring of the fault position by using the target image, avoids the monitoring image of the monitoring station from similar monitoring data, and can improve the commutation efficiency of the monitoring station.

respectively carrying out image effect evaluation on the first monitoring images acquired by the at least two alternative devices according to a pre-configured first monitoring image evaluation mode to obtain image effect evaluation results of the first monitoring images acquired by the at least two alternative devices;

and respectively obtaining the first parameter fitness of the first monitoring image acquired by the at least two alternative equipment based on the image effect evaluation result of the first monitoring image acquired by the at least two alternative equipment.

The pre-configured first monitoring image evaluation mode is used for evaluating the image effect of the first monitoring image based on the evaluation parameter. The evaluation parameter of the first monitoring image may specifically be an image monitoring angle, a shielding degree of the monitoring image, a definition of the monitoring image, a distance from the standby equipment to a fault position when the standby equipment acquires the first monitoring image, and the like, and the evaluation parameter is not limited here in this embodiment.

Specifically, the server obtains first monitoring images acquired by at least two alternative devices respectively, performs effect evaluation on each evaluation parameter according to the respective evaluation mode of each evaluation parameter in the preconfigured first monitoring image evaluation modes, obtains a quantitative parameter effect value of each evaluation parameter, obtains image effect evaluation results of the first monitoring images acquired by at least two alternative devices respectively based on the quantitative parameter effect value of each evaluation parameter of the first monitoring image, and obtains first parameter fitness of the first monitoring images acquired by at least two alternative devices respectively based on the image effect evaluation results of the first monitoring images acquired by at least two alternative devices respectively. In a specific application, the evaluation parameter is the distance between the candidate equipment and the fault position when the candidate equipment acquires the first monitoring image, and after the server acquires the first monitoring image acquired by each of the at least two candidate equipment, the server performs image effect evaluation on the distance between each candidate equipment and the fault position when the candidate equipment acquires the first monitoring image according to the evaluation mode of the distance between each candidate equipment and the fault position when the candidate equipment acquires the first monitoring image in the preconfigured first monitoring image evaluation mode, so as to obtain the quantitative parameter effect value of the distance between each candidate equipment and the fault position when each candidate equipment acquires the first monitoring image. For example, the closer the distance from the fault position when the candidate device acquires the first monitoring image is, the larger the effect value of the quantization parameter of the distance from the fault position when the candidate device acquires the first monitoring image is. In a specific application, after the server acquires the first monitoring images acquired by the at least two candidate devices, the candidate devices acquire the first monitoring images from the side of the fault position, and therefore geometric correction is performed on target equipment shot in the first monitoring images acquired by the candidate devices.

The geometric correction is to perform line segment fitting and screening on a first monitoring image acquired by each candidate device to obtain an effective line segment of the target device in the first monitoring image, namely an effective contour of the target device shot in the first monitoring image, extract the target device image based on the effective contour of the target device, compare the target device image with a target device front view prestored in a monitoring system database, and stretch the target device image based on the target device front view to enable the target device image to be close to the target device front view. The target equipment is to-be-monitored equipment at a fault position, and the fault position comprises a plurality of to-be-monitored equipment, such as a disconnecting link, an isolating switch, a meter, an indicator lamp, a sleeve, gas insulated metal enclosed switchgear (GIS) and the like. The disconnecting link is a switch of power equipment in the converter station, the isolating switch is a switch device which is used for isolating a power supply and connecting and cutting off a small current circuit in the converter station, the meter is an electric energy meter measuring and detecting device which is used for measuring and recording data such as power consumption of the converter station and the like in the converter station, the indicator lamp is a device which is used for monitoring the working or position state of equipment in the converter station by using lamplight, the sleeve is an insulating device which leads a live conductor into the electrical equipment or penetrates through a wall in the converter station, and the gas insulated metal enclosed switch equipment (GIS) is a high-voltage power distribution device in the converter station. In a specific application, the evaluation parameter is an image monitoring angle, and the server obtains the geometric correction degree of the target device image shot in the first monitoring image acquired by each candidate device in the geometric correction process, so that the image monitoring angle can be subjected to effect evaluation based on the geometric correction degree, and the quantitative parameter effect value of the image monitoring angle can be obtained. For example, the higher the geometric correction degree of the target device image captured in the first monitoring image acquired by the alternative equipment is, the more the first parameter monitoring angle representing the alternative equipment is inclined, and the lower the quantitative parameter effect value of the image monitoring angle of the first monitoring image acquired by the alternative equipment is.

In a specific application, the evaluation parameter is the shielded degree of the monitored image, and the server can evaluate the shielded degree of the monitored image according to the evaluation mode of the shielded degree of the monitored image in the pre-configured first monitoring image evaluation mode. In a specific application, the method for evaluating the effect of the shielded degree of the monitored image may be as follows: after geometric correction is carried out on the target equipment image, feature points of the target equipment image and the target equipment front view are extracted through angular point detection, image registration is carried out on the target equipment image and the target equipment front view based on the feature points of the target equipment image and the target equipment front view to obtain a registration result, and a quantitative parameter effect value of the shielding degree of the monitored image is obtained based on the registration result. In a specific application, the shielded proportion of the target device shot in the first monitoring image can be obtained based on the registration result, and the higher the shielded proportion of the target device is, the lower the quantitative parameter effect value of the shielded degree of the monitoring image is.

The angular point detection is implemented by Harris angular point detection, adopting a first-order partial derivative to describe gray level change, adopting a two-dimensional Gaussian window function to calculate a gray level change value in an image, finding edges, corners and flat areas in the image by judging gray level change conditions, and extracting feature points. And the image registration is to extract the features of the two images to obtain feature points, find matched feature point pairs by similarity measurement, obtain image space coordinate transformation parameters through the matched feature point pairs, and finally register the coordinate transformation parameters, namely realize the image registration of the target equipment image and the front view of the target equipment based on the matched feature point pairs in the target equipment image and the front view of the target equipment.

In a specific application, based on the registration result, state information of the target device in the image of the target device may also be obtained, and the state information may be used to analyze the state of the target device to visually determine whether the target device has a fault. Wherein the state information of the target device includes: disconnecting or closing a disconnecting switch and an isolating switch, extinguishing or lighting an indicator light, distributing the cracks on a sleeve and gas insulated metal enclosed switchgear (GIS), reading by a meter and the like. For example, image registration is performed on the feature points in the target equipment image corresponding to the knife switch at the fault position and the feature points of the opened knife switch in the front view of the target equipment, so that whether the knife switch is opened or closed can be determined.

In specific application, the evaluation parameter may specifically be the definition of the monitored image, and the server may perform image definition processing on the first monitored image according to a preset resolution standard to obtain the degree of the first monitored image that needs to be defined, and obtain a quantitative parameter effect value of the definition of the monitored image based on the degree of the first monitored image that needs to be defined. For example, when the first monitoring image is subjected to the sharpening process by the laplacian operator, so that the first monitoring image reaches a preset resolution standard, the higher the degree of sharpening of the first monitoring image is, the lower the definition of the first monitoring image is represented, and the lower the effect value of the quantization parameter of the definition of the monitoring image is.

The image sharpening processing is based on a Laplacian operator of the image processing, the area with the gray level mutation of the image is enhanced, and the image is filtered to remove noise points and enhance lines, so that the image sharpness is close to a preset resolution standard.

In this embodiment, the image effect evaluation is performed on the first monitoring image acquired by each of the candidate devices according to the preconfigured first monitoring image evaluation manner, so as to obtain the image effect evaluation result of the first monitoring image acquired by each of the at least two candidate devices, and the corresponding first parameter fitness can be obtained based on the image effect evaluation result.

and for each of the at least two alternative equipment, performing weighted fusion on the at least two quantitative parameter effect values of the first monitoring image acquired by the alternative equipment according to the parameter weight preconfigured for each quantitative parameter effect value, and obtaining the first parameter fitness of the first monitoring image acquired by the alternative equipment.

And the parameter weight pre-configured for each quantization parameter effect value is different for different target devices. For example, in a disconnecting link and an isolating switch, the parameter weight ratio of an image monitoring angle is the largest, in a meter, the parameter weight ratio of monitoring image definition is the largest, in an indicator lamp, the parameter weight ratio of the image monitoring angle is the largest, and in a sleeve and gas insulated metal enclosed switchgear (GIS), the parameter weight ratio of the image monitoring angle is the largest.

Specifically, for each of the at least two candidate devices, according to a parameter weight preconfigured for each quantization parameter effect value, weighting and fusing at least two quantization parameter effect values of the first monitoring image acquired by the candidate device, that is, weighting and fusing the respective quantization parameter effect value and the parameter weight of the quantization parameter in each candidate device, so as to obtain the first parameter fitness of the first monitoring image acquired by each candidate device.

In a specific application, the parameter weight corresponding to each quantization parameter effect value can be preconfigured in the following way: firstly, manually inputting the initial parameter weights of different quantization parameters in each target device, and then optimizing the initial parameter weights by an analytic hierarchy process to determine the respective corresponding parameter weights of the different quantization parameters in each target device. For example, when the preliminary parameter weight of different quantitative parameters in each target device is manually input, the preliminary parameter weight may be input by using an empirical method, wherein the empirical method may determine the quantitative parameter having the greatest influence on the monitored fault condition in each target device by integrating historical experiences, thereby completing the setting of the preliminary parameter weight in each target device.

The analytic hierarchy process includes decomposing the decision problem into different hierarchical structures according to the sequence of the total target, sub-targets of each layer, evaluation criteria and specific alternative schemes, solving and judging matrix characteristic vector to obtain the priority weight of each element of each hierarchy to one element of the previous hierarchy, and finally conducting hierarchical weighted sum to merge the final weight of each alternative scheme to the total target, wherein the maximum final weight is the optimal scheme.

In a specific application, when at least two quantitative parameter effect values of a first monitoring image acquired by the alternative equipment are subjected to weighted fusion, the fitness of each evaluation parameter can be calculated respectively based on a formula (1), and then the fitness of each evaluation parameter is superposed to realize weighted fusion.

R＝p·L (1)

Wherein, R is the fitness of the evaluation parameter, p is the parameter weight of the evaluation parameter, and L is the quantitative parameter effect value of the evaluation parameter.

For example, when a target device shot in a first monitoring image acquired by a certain candidate device is a disconnecting link, firstly, according to a preconfigured first monitoring image evaluation mode, a quantitative parameter effect value of each evaluation parameter of the first monitoring image is acquired, that is, an image monitoring angle in the first monitoring image, a shielding degree of the monitoring image, a definition of the monitoring image, and a quantitative parameter effect value of a distance from a fault position when the candidate device acquires the first monitoring image are acquired, and then, a preconfigured parameter weight for each quantitative parameter effect value in the disconnecting link is acquired, wherein the parameter weight of the image monitoring angle is the largest in the disconnecting link. Then, based on a formula (1), multiplying a quantitative parameter effect value of an image monitoring angle in the disconnecting link by a parameter weight to obtain the fitness of the image monitoring angle, then based on a similar mode, obtaining the shielding degree of the monitoring image in the disconnecting link, the monitoring image definition and the respective fitness of the distance between the standby equipment and the fault position when the standby equipment collects the first monitoring image, and obtaining the first parameter fitness of the first monitoring image by summing the image monitoring angle, the shielding degree of the monitoring image, the monitoring image definition and the respective fitness of the distance between the standby equipment and the fault position when the standby equipment collects the first monitoring image.

In this embodiment, at least two quantization parameter effect values of the first monitoring image acquired by the candidate device are weighted and fused according to the parameter weight preconfigured for each quantization parameter effect value for each candidate device of the at least two candidate devices, so that the technical effect of obtaining the first parameter fitness of the first monitoring image acquired by the candidate device can be achieved.

The iteration stop condition refers to a condition for stopping iteration. For example, the iteration stop condition may specifically be that the iteration is stopped when the number of iterations reaches a preset number.

Specifically, the server compares the first parameter fitness and the second parameter fitness of the target equipment to obtain a comparison result, and determines the acquisition parameter to be optimized of the target equipment according to the comparison result, namely when the first parameter fitness of the target equipment is greater than the second parameter fitness, the initial adjustment parameter of the target equipment is used as the acquisition parameter to be optimized of the target equipment, and when the first parameter fitness of the target equipment is less than the second parameter fitness, the initial acquisition parameter of the target equipment is used as the acquisition parameter to be optimized of the target equipment. After the acquisition parameters to be optimized are determined, the server performs iterative optimization on the acquisition parameters to be optimized, when the iteration times meet the iteration stop condition, the iteration is stopped, and the acquisition parameters of the target equipment after the iteration is stopped are used as the target acquisition parameters of the target equipment.

In specific application, the server can optimize the initial acquisition parameters of the target equipment by adopting the ant lion algorithm to obtain the target acquisition parameters of the target equipment. At the moment, the initial acquisition parameter of the target equipment is an initial ant lion, the first parameter adaptability parameter of the target equipment is a result corresponding to the initial ant lion, the primary adjustment parameter is an ant, the second parameter adaptability parameter of the target equipment is a result corresponding to the ant, the first parameter adaptability and the second parameter adaptability are compared, namely the result corresponding to the initial ant lion is compared with the result corresponding to the ant, when the second parameter adaptability is larger than the first parameter adaptability, the result corresponding to the ant is superior to the result corresponding to the initial ant lion, the server replaces the initial ant lion, the primary adjustment parameter is used as a new ant lion, the primary adjustment parameter is used as an acquisition parameter to be optimized, then the new lion is continuously subjected to iterative optimization, namely the iterative optimization is carried out on the acquisition parameter to be optimized, and the target lion, namely the target acquisition parameter of the target equipment is obtained until the iterative stop condition is met. When the second parameter fitness is smaller than the first parameter fitness, the result corresponding to the initial ant lion is superior to the result corresponding to the ant, the server does not replace the initial ant lion, namely, the initial acquisition parameter is used as the acquisition parameter to be optimized, and iterative optimization is continuously carried out on the initial ant lion.

In this embodiment, the first parameter fitness and the second parameter fitness of the target equipment are compared, the acquisition parameter to be optimized of the target equipment is determined according to the comparison result, iterative optimization is performed on the acquisition parameter to be optimized, and when the iteration stop condition is met, the technical effect of acquiring the target acquisition parameter of each target equipment can be achieved.

outputting the adjusted acquisition parameters to the target equipment, and acquiring third parameter fitness of a third monitoring image acquired by the target equipment according to the adjusted acquisition parameters;

and determining a new acquisition parameter to be optimized according to the comparison result, and continuously optimizing the new acquisition parameter to be optimized until an iteration stop condition is met to obtain the target acquisition parameter of the target equipment.

Specifically, the server adjusts the acquisition parameter to be optimized, obtains an adjusted acquisition parameter, outputs the adjusted acquisition parameter to the target equipment, obtains a third parameter fitness of a third monitoring image acquired by the target equipment according to the adjusted acquisition parameter, compares the third parameter fitness with the parameter fitness of the monitoring image acquired according to the acquisition parameter to be optimized, determines a new acquisition parameter to be optimized according to a comparison result, takes the adjusted acquisition parameter as the new acquisition parameter to be optimized when the third parameter fitness is greater than the parameter fitness of the monitoring image acquired according to the acquisition parameter to be optimized, takes the acquisition parameter to be optimized as the new acquisition parameter to be optimized when the third parameter fitness is less than the parameter fitness of the monitoring image acquired according to the acquisition parameter to be optimized, and continues to optimize the new acquisition parameter to be optimized until an iteration stop condition is met, thereby obtaining the target acquisition parameter of the target equipment.

In a specific application, when the ant lion algorithm is adopted to adjust the acquisition parameters, and when the third parameter adaptability is greater than the parameter adaptability of the monitoring image acquired according to the acquisition parameters to be optimized, the server takes the adjusted acquisition parameters as new acquisition parameters to be optimized, namely, the adjusted acquisition parameters as new ant lions, and performs iterative optimization on the new acquisition parameters to be optimized, the adjusted acquisition parameters are adjusted to obtain the acquisition parameters to be adjusted again, namely, the ants are controlled to walk around the new ant lions to obtain ants at new positions, the parameter adaptability of the monitoring image acquired by the target equipment under the acquisition parameters to be adjusted again is obtained, and when the parameter adaptability of the monitoring image acquired by the target equipment under the acquisition parameters to be adjusted again is higher than the parameter adaptability of the monitoring image acquired by the target equipment under the acquisition parameters to be adjusted, the acquisition parameters to be adjusted again are taken as new ant lions. And before the iteration stop condition is met, based on the ant lion algorithm, continuously controlling ants to move around the ant lion, performing iterative optimization on the ant lion, namely optimizing the acquisition parameters of the target equipment, selecting the acquisition parameters which can enable the parameter fitness to be better after each iteration is finished, and obtaining the target acquisition parameters of the target equipment when the iteration times meet the iteration stop condition.

In this embodiment, the acquisition parameter to be optimized is adjusted to obtain an adjusted acquisition parameter, the adjusted acquisition parameter is output to the target equipment, the third parameter fitness of a third monitoring image acquired by the target equipment according to the adjusted acquisition parameter is obtained, the third parameter fitness is compared with the parameter fitness of the monitoring image acquired according to the acquisition parameter to be optimized, a new acquisition parameter to be optimized is determined according to a comparison result, the new acquisition parameter to be optimized is continuously optimized until an iteration stop condition is met, the acquisition parameter of each target equipment can be optimized in an iteration process, and finally the target acquisition parameter of each target equipment is obtained.

The monitoring system is pre-configured with a three-dimensional model of the converter station, and the standby equipment is movable intelligent monitoring equipment, such as a robot and an unmanned aerial vehicle controlled by the monitoring system of the converter station.

Specifically, the server fits a target monitoring image with a three-dimensional model of a fault position in a three-dimensional model of the converter station to obtain a model fitting result, determines a missed position to be monitored of the target equipment when the model fitting result represents that the target monitoring image does not comprehensively monitor the fault position, controls the standby equipment to move to the missed position to be monitored, monitors the missed position to be monitored, and obtains a missed monitoring image of the missed position to be monitored, wherein the missing monitoring image is acquired by the standby equipment.

In specific application, after the missing position to be monitored of the target equipment is determined based on a model fitting result, the server controls the standby equipment in the converter station to automatically generate a path to reach the missing position to be monitored, acquisition parameters such as an angle and a focal length when the position to be monitored of the standby equipment is missed are obtained, the acquisition parameters such as the angle and the focal length of the standby equipment are subjected to iterative optimization by using a ant lion algorithm, the target acquisition parameters of the standby equipment are obtained after an iteration stop condition is met, and a monitoring image acquired according to the target acquisition parameters is used as a target monitoring image of the standby equipment.

In a specific application, aiming at each omitted position to be monitored, the server firstly controls one piece of standby equipment to monitor the omitted position to be monitored, and when one piece of standby equipment is not enough to comprehensively monitor the omitted position to be monitored, more pieces of standby equipment are controlled to monitor the omitted position to be monitored until the monitoring images of the target equipment and the standby equipment and the model fitting results of the three-dimensional models at the fault positions represent that the target equipment and the standby equipment realize the comprehensive monitoring of the fault positions.

In the embodiment, the standby equipment is controlled to perform supplementary monitoring on the position which is not monitored by the target equipment, so that the technical effects of increasing effective monitoring data, avoiding insufficient monitoring data and improving the fault processing efficiency can be achieved.

In a specific application, after it is determined that the target equipment has comprehensively monitored the fault position based on the model fitting result, the server controls the standby equipment to perform targeted monitoring on the target equipment at the fault position, wherein when the standby equipment performs targeted monitoring on the target equipment, the server may perform iterative optimization on acquisition parameters of the standby equipment based on an ant-lion algorithm. The control standby equipment carries out targeted monitoring to the target equipment, can be used for carrying out auxiliary monitoring to the target equipment of trouble, realizes the accurate collection to fault information, is convenient for judge the fault condition better, improves fault handling efficiency.

In one embodiment, as shown in fig. 3, the control method for the backup device in this embodiment is described by a backup device applied to a robot and a drone.

The robot and the unmanned aerial vehicle in the server control convertor station start, and control robot and unmanned aerial vehicle reach trouble position department, when the trouble position department can not be monitored comprehensively to fixed probe (being the target equipment) around the trouble position department, the monitoring data that fixed probe gathered exist not enoughly, on the monitoring data basis that fixed probe gathered, based on the ant lion algorithm, carry out iterative optimization to robot and unmanned aerial vehicle's collection parameter, obtain robot and unmanned aerial vehicle's target acquisition parameter, and control robot and unmanned aerial vehicle monitor the data missing position under the target acquisition parameter, supplement the not enough of monitoring data. When the fixed probe around the fault position department can monitor fault position department comprehensively, the monitoring data that the fixed probe gathered are sufficient, obtain robot and unmanned aerial vehicle's target acquisition parameter based on similar mode, control robot and unmanned aerial vehicle and carry out the pertinence monitoring to the target equipment of fault position department under the target acquisition parameter for monitoring data obtains optimizing.

In a specific application, after the target monitoring images of the target equipment and the standby equipment are obtained, operation and maintenance personnel can select and control the intelligent monitoring equipment to monitor any position of the converter station according to actual requirements.

The inventor thinks that the control method of the monitoring equipment selects the target equipment by preferentially selecting all the fixed alternative equipment at the fault position, abandons the alternative equipment with poor monitoring effect, can avoid that a large number of similar monitoring images are acquired because a large number of the fixed alternative equipment simultaneously point to the fault position to cause monitoring data redundancy, carries out iterative optimization of acquisition parameters on the target equipment by using the ant lion algorithm to obtain target acquisition parameters of the target equipment, uses the monitoring images acquired according to the target acquisition parameters as target monitoring images, fits the target monitoring images with a three-dimensional model at the fault position to obtain a model fitting result, controls the standby equipment to monitor the omitted position to be monitored under the target acquisition parameters after iterative optimization when the target equipment does not realize the comprehensive monitoring on the fault position according to the model fitting result, avoids insufficient monitoring data, and controls the standby equipment to carry out one-to-one monitoring on the target equipment at the fault position under the target acquisition parameters after iterative optimization when the target equipment does not realize the comprehensive monitoring on the fault position according to the model fitting result, thereby realizing the accurate acquisition of fault information. In the whole process, redundant monitoring data can be reduced, effective monitoring data are increased, and the fault processing efficiency is improved.

In one embodiment, as shown in fig. 4, the control method of the monitoring equipment of the present application is illustrated by an intelligent equipment applied to the converter station, wherein the intelligent equipment is an alternative equipment, and the control method of the monitoring equipment comprises the following steps:

intelligent equipment near the fault location is automatically selected at the three-dimensional platform of the converter station, step 402.

After the fault occurs, the server automatically selects fixed intelligent equipment near the fault position in the three-dimensional platform of the converter station as alternative equipment.

And step 404, controlling the selected intelligent equipment to shoot the fault position and the surrounding environment of the fault position for the first time to obtain a first shot image.

The server controls the alternative equipment to shoot the fault position and the surrounding environment of the fault position for the first time according to the default parameters, and collects a first monitoring image.

And step 406, performing image processing on the first shot image, and sequencing parameters in the first shot image to obtain a sequencing result.

The method comprises the steps of carrying out image processing on an image shot by each candidate device for the first time, namely carrying out image effect evaluation on a first monitoring image collected by each candidate device, obtaining an image evaluation result of the first monitoring image of each candidate device according to a pre-configured first monitoring image evaluation mode, and obtaining first parameter fitness of the first monitoring image of each candidate device based on the image evaluation result of the first monitoring image of each candidate device. And sequencing the first parameter fitness of the first monitoring images of all the alternative equipment to obtain a sequencing result of the first parameter fitness, and obtaining the sequencing result of all the alternative equipment based on the sequencing result of the first parameter fitness.

And step 408, based on the sorting result, preferentially selecting three-four alternative equipment as the target equipment.

Specifically, the server preferentially selects three to four candidate equipment with higher first parameter fitness as the target equipment based on the ranking results of all the candidate equipment.

And step 410, adjusting parameters of the selected target equipment by using the ant lion algorithm, and controlling the target equipment to shoot the fault position under the adjusted parameters.

Specifically, the server adjusts initial acquisition parameters of the target equipment based on the ant lion algorithm, and controls the target equipment to monitor the fault position under the adjusted acquisition parameters.

And step 412, comparing the shot images of the target equipment under different parameters, and selecting the parameters with good shot image effect, so that the characteristic mark at the fault position clearly appears in the middle of the image shot by the target equipment, and the fault is processed conveniently.

Specifically, the server respectively compares the fitness of monitoring images acquired by each target device under different acquisition parameters, selects parameters with good shooting image effects as target acquisition parameters, namely performs iterative optimization on the acquisition parameters of the target devices by using the ant lion algorithm to obtain the target acquisition parameters of the target devices. After the target acquisition parameters are obtained, the server can control the target equipment to monitor the fault position under the target acquisition parameters, and a target acquisition image of the target equipment is obtained, so that the target equipment at the fault position clearly appears in the middle of the target acquisition image.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.

Based on the same inventive concept, the embodiment of the application also provides a control device of the monitoring equipment, which is used for realizing the control method of the monitoring equipment. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the method, so specific limitations in the embodiments of the control device for one or more monitoring devices provided below can be referred to the limitations on the control method for the monitoring device in the above description, and details are not repeated here.

In one embodiment, as shown in fig. 5, there is provided a control device of a monitoring apparatus, including: a fitness obtaining module 502, a first processing module 504, a second processing module 506, and a third processing module 508, wherein:

a fitness obtaining module 502, configured to obtain first parameter fitness of a first monitoring image acquired by each of at least two candidate devices, where the first parameter fitness represents a monitoring effect of the first monitoring image;

a first processing module 504, configured to compare respective first parameter fitness of the at least two candidate devices, and determine a target device from the at least two candidate devices according to a comparison result;

the second processing module 506 is configured to adjust an initial acquisition parameter of the target equipment, obtain a primary adjustment parameter, output the primary adjustment parameter to the target equipment, and obtain second parameter fitness of a second monitoring image acquired by the target equipment according to the primary adjustment parameter;

and the third processing module 508 is configured to obtain a target acquisition parameter of the target equipment based on the first parameter fitness and the second parameter fitness of the target equipment, and use a monitoring image acquired according to the target acquisition parameter as a target monitoring image.

According to the control device of the monitoring equipment, the first parameter fitness of the first monitoring image acquired by each of the at least two candidate equipment is obtained, the first parameter fitness of the first monitoring image which represents the monitoring effect of the first monitoring image of each of the at least two candidate equipment is compared, the target equipment can be preferably selected according to the comparison result representing the magnitude relation of the first parameter fitness of each of the at least two candidate equipment, the initial acquisition parameter of the target equipment can be adjusted to obtain the initial adjustment parameter, the initial adjustment parameter is output to the target equipment, the second parameter fitness of the second monitoring image acquired by the target equipment according to the initial adjustment parameter is obtained, the target acquisition parameter of the target equipment is obtained based on the first parameter fitness and the second parameter fitness of the target equipment, the optimization of the acquisition parameter of the target equipment is realized, the monitoring image acquired according to the target acquisition parameter is used as the target monitoring image, the whole process is realized, the target equipment is preferably selected by comparing the first parameter fitness, the acquisition parameter fitness of the target equipment is optimized, the target image can be obtained, the monitoring image at the fault position can be further utilized, the monitoring image at the fault position is avoided, and the conversion efficiency of a large number of monitoring data in the monitoring station can be improved.

In one embodiment, the fitness obtaining module is further configured to obtain first monitoring images acquired by the at least two candidate devices, perform image effect evaluation on the first monitoring images acquired by the at least two candidate devices according to a preconfigured first monitoring image evaluation mode, obtain image effect evaluation results of the first monitoring images acquired by the at least two candidate devices, and obtain first parameter fitness of the first monitoring images acquired by the at least two candidate devices based on the image effect evaluation results of the first monitoring images acquired by the at least two candidate devices.

In one embodiment, the fitness obtaining module is further configured to perform weighted fusion on at least two quantization parameter effect values of a first monitoring image acquired by the candidate equipment according to a parameter weight preconfigured for each quantization parameter effect value for each candidate equipment in the at least two candidate equipment, so as to obtain the first parameter fitness of the first monitoring image acquired by the candidate equipment.

In one embodiment, the third processing module is further configured to compare the first parameter fitness and the second parameter fitness of the target equipment, determine an acquisition parameter to be optimized of the target equipment according to a comparison result, perform iterative optimization on the acquisition parameter to be optimized until an iteration stop condition is met, and obtain the target acquisition parameter of the target equipment.

In one embodiment, the third processing module is further configured to adjust the acquisition parameter to be optimized, obtain the adjusted acquisition parameter, output the adjusted acquisition parameter to the target equipment, obtain a third parameter fitness of a third monitoring image acquired by the target equipment according to the adjusted acquisition parameter, compare the third parameter fitness with the parameter fitness of the monitoring image acquired according to the acquisition parameter to be optimized, determine a new acquisition parameter to be optimized according to a comparison result, and continue to optimize the new acquisition parameter to be optimized until an iteration stop condition is met, so as to obtain the target acquisition parameter of the target equipment.

In one embodiment, the third processing module is further configured to fit the target monitoring image with a three-dimensional model at a preconfigured fault location to obtain a model fitting result, and when the model fitting result is characterized that the fault location is not fully monitored based on the target monitoring image, the standby equipment is controlled to monitor the fault location to obtain a monitoring image acquired by the standby equipment.

The various modules in the control device of the monitoring apparatus described above may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 6. The computer device comprises a processor, a memory, an Input/Output (I/O) interface and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing control data of the monitoring equipment. The input/output interface of the computer device is used for exchanging information between the processor and an external device. The communication interface of the computer device is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to implement a method of controlling monitoring equipment.

It will be appreciated by those skilled in the art that the configuration shown in fig. 6 is a block diagram of only a portion of the configuration associated with the present application, and is not intended to limit the computing device to which the present application may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the above-described method embodiments when executing the computer program.

In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, carries out the steps in the method embodiments described above.

It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the relevant laws and regulations and standards of the relevant country and region.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include a Read-Only Memory (ROM), a magnetic tape, a floppy disk, a flash Memory, an optical Memory, a high-density embedded nonvolatile Memory, a resistive Random Access Memory (ReRAM), a Magnetic Random Access Memory (MRAM), a Ferroelectric Random Access Memory (FRAM), a Phase Change Memory (PCM), a graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method of controlling monitoring equipment, the method comprising:

acquiring first parameter fitness of a first monitoring image acquired by at least two alternative devices respectively, wherein the first parameter fitness represents the monitoring effect of the first monitoring image;

2. The method of claim 1, wherein obtaining the first parameter fitness of the first monitored image acquired by each of the at least two candidate pieces of equipment comprises:

3. The method of claim 2, wherein the image effect evaluation result comprises at least two quantization parameter effect values;

the obtaining the first parameter fitness of the first monitoring image respectively acquired by the at least two candidate devices based on the image effect evaluation result of the first monitoring image respectively acquired by the at least two candidate devices comprises:

4. The method of claim 1, wherein obtaining target acquisition parameters for the target equipment based on the first and second parameter fitness of the target equipment comprises:

5. The method of claim 4, wherein iteratively optimizing the acquisition parameters to be optimized until an iteration stop condition is satisfied, and obtaining target acquisition parameters of the target equipment comprises:

comparing the third parameter fitness with the parameter fitness of the monitoring image acquired according to the acquisition parameter to be optimized;

6. The method according to any one of claims 1 to 5, wherein the obtaining of the target acquisition parameter of the target equipment based on the first parameter fitness and the second parameter fitness of the target equipment, and after taking the monitoring image acquired according to the target acquisition parameter as a target monitoring image, further comprises:

and when the model fitting result is characterized in that the fault position is not comprehensively monitored based on the target monitoring image, controlling the standby equipment to monitor the fault position, and obtaining the monitoring image acquired by the standby equipment.

7. A control device of a monitoring apparatus, characterized in that the device comprises:

the system comprises a fitness acquisition module, a first monitoring image acquisition module and a second monitoring image acquisition module, wherein the fitness acquisition module is used for acquiring first parameter fitness of a first monitoring image acquired by each of at least two candidate devices, and the first parameter fitness represents a monitoring effect of the first monitoring image;

the first processing module is used for comparing the first parameter fitness of the at least two candidate equipment and determining target equipment from the at least two candidate equipment according to a comparison result;

and the third processing module is used for obtaining the target acquisition parameters of the target equipment based on the first parameter fitness and the second parameter fitness of the target equipment, and taking the monitoring images acquired according to the target acquisition parameters as target monitoring images.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.

9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 6 when executed by a processor.