A GIS monitoring system, method, device and storage medium for an intelligent substation

Abstract

This application belongs to the field of environmental monitoring technology, and discloses a GIS monitoring system, method, device and storage medium for an intelligent substation. The space of the substation is evenly divided into multiple monitoring areas; the system includes monitoring and control devices arranged at the central positions of each monitoring area; the monitoring and control devices include a main control module, a lighting module, an image acquisition module and a dust removal module; the image acquisition module is used to obtain the real-scene image of the monitoring area after the lighting module is turned on, and send the real-scene image to the main control module; the main control module is used to identify the dust density of the monitoring area based on the light power of the lighting module and the real-scene image; and when the dust density is greater than the preset density threshold, start the dust removal module. This application improves the real-time performance and accuracy of environmental monitoring, reduces the requirement for the operating power of the dust removal module, and avoids waste of electric energy.

Description

Technical Field

[0001] This application relates to the technical field of environmental monitoring, and particularly to a GIS monitoring system, method, device and storage medium for intelligent substations. Background Art

[0002] With the gradual development of intelligent substations, GIS (Gas Insulated Substation) has become the core equipment for power transformation. The requirements for the installation environment of GIS have become more stringent, especially the cleanliness level of the installation environment needs to reach above the million level of the ISO14644 standard, that is, the number of particles with a size of 0.5 microns per cubic meter of air should be less than 35.2 million. However, in the actual use process, due to the entry and exit of staff, there are often problems such as excessive on-site pollution by hair, dust, sundries, etc. For this reason, robots for intelligent patrol in substations have been developed, and various sensors are mounted on robots that can move intelligently and avoid obstacles, so as to realize the automatic monitoring of the environmental quality of substations.

[0003] However, due to the large number of large equipment in the substation, the internal environmental quality is not uniform, the sensing range of the sensor is limited, and the sensing area is affected by the moving position of the robot. It is easy to occur that the environmental quality of the area where the robot is currently located is okay, while there are environmental problems in the areas that have not been patrolled yet, resulting in poor real-time performance and accuracy of robot monitoring. If the number of robots is increased, it will not only affect the entry and exit of substation staff, but also increase the risk of being accidentally bumped by staff and scratching the power transformation equipment, with many potential safety hazards. In addition, after detecting environmental problems in a certain area, usually the whole substation is dusted, and the power requirement for the dust removal device is extremely high, which is likely to cause waste of resources. Summary of the Invention

[0004] This application provides a GIS monitoring system, method, device and storage medium for intelligent substations, which can improve the real-time performance and accuracy of environmental monitoring, reduce the power requirement for the operation of the dust removal module, and avoid waste of electric energy.

[0005] In the first aspect, an embodiment of this application provides a GIS monitoring system for an intelligent substation. The space of the intelligent substation is evenly divided into multiple monitoring areas. The system includes monitoring and control devices arranged at the central positions of the respective monitoring areas.

[0006] The monitoring and control device includes a main control module, a lighting module, an image acquisition module and a dust removal module. The image acquisition module is used to obtain the real scene image of the monitoring area after the lighting module is turned on, and send the real scene image to the main control module.

[0007] The main control module is used to obtain the light power of the lighting module; obtain the brightness value of the real scene image according to the light power; perform light correction on the real scene image based on the brightness value and the background extraction method to obtain a corrected image; segment the corrected image using the gray-level co-occurrence matrix to obtain a dust texture image; binarize the dust texture image to obtain a gray-scale image; calculate the first area of the first pixel value and the second area of the gray-scale image in the gray-scale image; compare the first area with the second area to obtain the dust density; and determine whether the dust density is greater than a preset density threshold; if so, start the dust removal module.

[0008] Further, it also includes temperature sensors and humidity sensors installed on each insulating switch device in the intelligent substation;

[0009] Each temperature sensor and each humidity sensor are respectively connected to the main control module in the monitoring and control device corresponding to the monitoring area where the insulating switch device is located; the monitoring and control device also includes an alarm module, a dehumidification module, and a cooling module;

[0010] The temperature sensor is used to obtain the real-time device temperature of the insulating switch device and send it to the main control module;

[0011] The humidity sensor is used to obtain the real-time device humidity of the insulating switch device and send it to the main control module;

[0012] The main control module is also used to, when any real-time device temperature is higher than the first preset temperature threshold, control the alarm module to generate an over-temperature alarm message according to the device number of the corresponding insulating switch device and start the cooling module;

[0013] And, when any real-time device humidity is higher than the preset humidity threshold, control the alarm module to generate an over-humidity alarm message according to the device number of the corresponding insulating switch device and start the dehumidification module.

[0014] Further, the monitoring and control device also includes an electrostatic monitoring module; the electrostatic monitoring module is arranged on the inner wall of the air extraction pipeline of the dust removal module; the electrostatic monitoring module is used to calculate the air flow static electricity and send it to the main control module when the dust removal module is turned on;

[0015] The main control module is used to obtain the gas flow rate of the dust removal module and the monitoring area of the electrostatic monitoring module; perform differentiation based on the air flow static electricity and the monitoring area to obtain the current per unit area; calculate the collision probability according to the current per unit area, the dust density, and the gas flow rate; obtain the Stokes number of the particles according to the collision probability and the correction coefficient; obtain the average dust diameter based on the Stokes number, the dust density, and the slip correction coefficient; and determine whether the average dust diameter is greater than the preset inhalation threshold; if so, determine whether there is anyone in the real scene image; if there is, control the alarm module to generate a keep-away alarm message.

[0016] Further, the image acquisition module is further configured to acquire an infrared image of the monitoring area and send it to the main control module;

[0017] The main control module is further configured to, when it determines that there is a person in the real scene image, remove the pixel points corresponding to the human body in the infrared image; calculate the gray values of each pixel point in the infrared image; obtain the real-time temperature of each pixel point according to the gray values of each pixel point; average the real-time temperatures of each pixel point to obtain the real-time area temperature; and determine whether the real-time area temperature is greater than the second preset temperature threshold. If so, start the cooling module.

[0018] Further, the dust removal module further includes a gas analysis unit; the gas analysis unit is configured to analyze the components and proportions of the inhaled gas when the dust removal module is started, and send the analysis results to the main control module for display.

[0019] Further, the dust removal module further includes a heavy metal monitoring unit; the heavy metal monitoring unit includes a magnetic sheet and an X-ray spectrometer; the magnetic sheet is used to adsorb metal particles in the filtering substance; the spectrometer is used to perform fluorescence spectrometer tests on each metal particle on the magnetic sheet to obtain quantitative results of different elements, and send them to the main control module for display.

[0020] Further, the system further includes a ground wave monitoring module; the ground wave monitoring module is installed at the center of the floor of the monitoring area;

[0021] The ground wave monitoring module is configured to issue a seismic alarm when seismic waves are detected.

[0022] Further, the main control module is further configured to, when starting the dust removal module, input the dust density, the average dust diameter, and the real-time area temperature into the trained power adjustment model to obtain the operating power of the dust removal module; and control the dust removal module to work according to the operating power.

[0023] In a second aspect, an embodiment of the present application provides a GIS monitoring method for an intelligent substation, which is applied to the GIS monitoring system of the intelligent substation as described in any of the above embodiments. The method includes:

[0024] Obtain the illumination power of the lighting module and the real scene image of the image acquisition module;

[0025] Obtain the brightness value of the real scene image according to the illumination power;

[0026] Perform illumination correction on the real scene image based on the brightness value and the background extraction method to obtain a corrected image;

[0027] Segment the corrected image using a gray level co-occurrence matrix to obtain a dust texture image;

[0028] Binarize the dust texture image to obtain a gray scale image;

[0029] Calculate the first area of the first pixel value in the grayscale image and the second area of the grayscale image;

[0030] Let the first area be compared with the second area to obtain the dust density;

[0031] Judge whether the dust density is greater than a preset density threshold; if so, start the dust removal module.

[0032] Furthermore, the method further includes:

[0033] Obtain the gas flow rate of the dust removal module, the monitoring area of the electrostatic monitoring module, and the air flow static electricity;

[0034] Differentiate according to the air flow static electricity and the monitoring area to obtain the current per unit area;

[0035] Calculate the collision probability according to the current per unit area, the dust density, and the gas flow rate;

[0036] Obtain the Stokes number of the particles according to the collision probability and the correction coefficient;

[0037] Obtain the average dust diameter based on the Stokes number, the dust density, and the slip correction coefficient;

[0038] Judge whether the average dust diameter is greater than a preset inhalation threshold; if so, judge whether there is anyone in the real scene image; if so, control the alarm module to generate a warning message to stay away.

[0039] Furthermore, the above judgment of whether there is anyone in the real scene image includes:

[0040] Obtain the historical real scene image set of the monitoring area, and the historical real scene images include real scene images with people and real scene images without people;

[0041] Train the neural network with the historical real scene image set to obtain a trained human body detection model;

[0042] Input the real scene image into the human body detection model to obtain the detection result.

[0043] Furthermore, the method further includes:

[0044] Obtain the detection results of the infrared image and the real scene image of the image acquisition module;

[0045] If the detection result is that there is someone, remove the pixel points corresponding to the human body in the infrared image;

[0046] Calculate the grayscale values of each pixel point in the infrared image;

[0047] Obtain the real-time temperature of each pixel point according to the grayscale values of each pixel point;

[0048] Average the real-time temperatures of each pixel to obtain the real-time regional temperature;

[0049] Determine whether the real-time regional temperature is greater than the second preset temperature threshold. If so, start the cooling module.

[0050] Further, the method further includes:

[0051] Obtain the dust density, the average dust diameter, and the real-time regional temperature, and input them into the trained power adjustment model to obtain the operating power of the dust removal module; control the dust removal module to work according to the operating power.

[0052] In a third aspect, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it executes the steps of a GIS monitoring method for an intelligent substation according to any one of the above embodiments.

[0053] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of a GIS monitoring method for an intelligent substation according to any one of the above embodiments.

[0054] In summary, compared with the prior art, the beneficial effects brought by the technical solution provided by the embodiment of the present application at least include:

[0055] A GIS monitoring system for an intelligent substation provided by an embodiment of the present application. First, by evenly dividing the monitoring area, targeted environmental monitoring and dust removal for a single monitoring area are realized. Since the working range of the dust removal module is reduced, the requirement for the operating power of the dust removal module is reduced, avoiding waste of electric energy caused by cleaning the entire substation at the same time. Second, the dust density monitored in this application is judged through real-scene images in the lighting environment. Compared with setting up smoke sensors, the image processing-based method in this application will not miss any corner of the monitoring area, and the monitoring is more comprehensive. Moreover, compared with analyzing the images of the entire substation, the real-scene images in this application only target one monitoring area, with higher resolution and better calculation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a layout diagram of a GIS monitoring system for an intelligent substation provided by an embodiment of the present application.

[0057] Figure 2 It is a structural diagram of a monitoring and control device provided by an embodiment of the present application.

[0058] Figure 3 It is a flowchart of a GIS monitoring method for an intelligent substation provided by an embodiment of the present application.

[0059] Figure 4 The flowchart of the method for calculating the average diameter of dust provided by an embodiment of the present application. Detailed implementation manners

[0060] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments.

[0061] All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0062] Please refer to Figure 1 , an embodiment of the present application provides a GIS monitoring system for an intelligent substation, and the space of the intelligent substation is evenly divided into a plurality of monitoring areas; the system includes monitoring control devices arranged at the central positions of the respective monitoring areas.

[0063] As Figure 1 shown, the monitoring control devices and the corresponding monitoring areas have corresponding numbers: monitoring area 1 corresponds to monitoring control device 1, monitoring area 2 corresponds to monitoring control device 2... and so on.

[0064] The monitoring control device includes a main control module, a lighting module, an image acquisition module, and a dust removal module; the image acquisition module is used to obtain the real-scene image of the monitoring area after the lighting module is turned on, and send the real-scene image to the main control module.

[0065] The main control module is used to obtain the light power of the lighting module; obtain the brightness value of the real-scene image according to the light power; perform light correction on the real-scene image based on the brightness value and the background extraction method to obtain a corrected image; segment the corrected image by using a gray-level co-occurrence matrix to obtain a dust texture image; perform binarization on the dust texture image to obtain a gray-scale image; calculate the first area of the first pixel value in the gray-scale image and the second area of the gray-scale image; make the first area and the second area compared to obtain the dust density; and determine whether the dust density is greater than a preset density threshold; if so, start the dust removal module.

[0066] As Figure 1 shown, the monitoring control device is arranged at the central position of the ceiling of each monitoring area. The main control module can control the lighting module to turn on according to the received artificial light-on instruction. The dust removal module uses a bag-type filter element made of fiber fabric to capture solid particles in the dust-containing gas, and can achieve a dust removal effect with an accuracy of 0.3 μm.

[0067] Among them, the setting of the preset density threshold can refer to the requirements in the "Control Record Card for Key Processes of the Installation Quality and Technology of Main Electrical Equipment in Substation Projects": 0.5μm particles < 3.52×10 per m 3 particles < 3.52×10 7 , 1μm particles < 8.32×l0 per m 3 particles < 8.32×l0 6 , 5μm particles < 2.93×l0 per m 3 particles < 2.93×l0 5 . That is, dust-free operation does not completely eliminate dust, but controls it within a certain range.

[0068] Furthermore, after starting the dust removal module, the main control module continues to monitor the dust density in the monitoring area in real time. If it detects that the dust density is lower than the preset density threshold and the difference from the preset density threshold reaches the pause value, it stops the operation of the dust removal module.

[0069] The GIS monitoring system of an intelligent substation provided by the above embodiment, first, by evenly dividing the monitoring area, targeted environmental monitoring and dust removal of a single monitoring area are realized. Since the working range of the dust removal module is reduced, the requirement for the operating power of the dust removal module is thus reduced, avoiding waste of electric energy caused by cleaning the entire substation at the same time; secondly, the dust density monitored in this application is judged by the real-scene image in the lighting environment. Compared with setting a smoke sensor, the method based on image processing in this application will not miss any corner of the monitoring area, and the monitoring is more comprehensive. Moreover, compared with analyzing the images of the entire substation, the real-scene image in this application only targets one monitoring area, with higher resolution and better calculation accuracy.

[0070] Please refer to Figure 2 , in some embodiments, the system further includes temperature sensors and humidity sensors installed on each insulating switch device in the intelligent substation; each temperature sensor and each humidity sensor are respectively connected to the main control module in the monitoring control device corresponding to the monitoring area where the insulating switch device is located; the monitoring control device further includes an alarm module, a dehumidification module and a cooling module.

[0071] The temperature sensor is used to obtain the real-time device temperature of the insulating switch device and send it to the main control module; the humidity sensor is used to obtain the real-time device humidity of the insulating switch device and send it to the main control module; the main control module is further used to control the alarm module to generate an over-temperature alarm message according to the device number of the corresponding insulating switch device and start the cooling module when any real-time device temperature is higher than the first preset temperature threshold; and, when any real-time device humidity is higher than the preset humidity threshold, control the alarm module to generate an over-humidity alarm message according to the device number of the corresponding insulating switch device and start the dehumidification module.

[0072] Among them, the resolution of the temperature sensor is 0.1°C, and the measurement range of the humidity sensor is 0%RH - 100%RH. The dehumidification module sucks in humid air into the machine through a fan, and through heat exchange, the moisture in the air condenses into water droplets at this time. The processed dry air is discharged outside the machine, and such a cycle reduces the humidity in the monitoring area.

[0073] Furthermore, the temperature sensor, humidity sensor, etc. are all detachably arranged, which facilitates the staff to realize the dynamic digital detection of key construction processes and process quality, avoids the disadvantages of being prone to omission in the conventional manual review based on experience judgment, empowers the project quality and can trace the construction quality.

[0074] Specifically, the insulated switchgear is usually a gas-insulated switchgear. Since its interior is filled with insulating gas, it has relatively high requirements for temperature and humidity; and the main control module has already set the number of the insulated switchgear where each sensor is located inside, and when it detects that the temperature or humidity of the corresponding insulated switchgear exceeds the standard, it can quickly remind the staff to handle it.

[0075] In specific implementation, the main control module can be connected to an electronic screen to display the dust density, real-time device temperature, real-time device humidity, etc. as curves, and can extract the corresponding data curves for display through the time period input by the user; the electronic screen can also display the alarm records of all data, sorted by alarm time, location area, device name, alarm level, and alarm content.

[0076] In the above embodiment, the temperature sensor and the humidity sensor are arranged on the insulated switchgear of the substation, which can accurately obtain the real-time situation of the device, and the monitoring and processing of temperature and humidity are more accurate and real-time.

[0077] In some embodiments, the monitoring and control device further includes an electrostatic monitoring module; the electrostatic monitoring module is arranged on the inner wall of the exhaust duct of the dust removal module; the electrostatic monitoring module is used to calculate the air flow static electricity and send it to the main control module when the dust removal module is turned on.

[0078] The main control module is used to obtain the gas flow rate of the dust removal module and the monitoring area of the electrostatic monitoring module; perform differentiation based on the air flow static electricity and the monitoring area to obtain the current per unit area; calculate the collision probability according to the current per unit area, dust density, and gas flow rate; obtain the Stokes number of the particles according to the collision probability and the correction coefficient; obtain the average dust diameter based on the Stokes number, dust density, and slip correction coefficient; and determine whether the average dust diameter is greater than the preset inhalation threshold; if so, determine whether there is a person in the real scene image; if so, control the alarm module to generate a warning message to stay away.

[0079] Among them, the preset inhalation threshold is between 5μm and 10μm. Further, the dust removal module is usually selected as an exhaust filtration device, and the electrostatic monitoring module is arranged on the inner wall of the exhaust duct. When the dust removal module works, the dust particles in the flowing gas in the exhaust duct collide and move with each other, thereby generating charges to form static current. In addition to calculating whether the particle size meets the human inhalation standard according to the generated static current, this application can also make the main control module reduce the operating power of the dust removal module when the air flow static electricity is greater than a certain value, thereby reducing the gas flow rate, and avoiding the influence of the dust air flow static electricity in the monitoring area on various electrical equipment.

[0080] The above-mentioned embodiment calculates the average diameter of the dust through the air flow static electricity and gives an alarm based on the average diameter of the dust, which can prevent the dust particles from being inhaled by the staff in the monitoring area before being inhaled into the dust removal module, and takes care of the physical health of the staff while ensuring the dust cleanliness of the monitoring area.

[0081] In some embodiments, the image acquisition module is further configured to acquire an infrared image of the monitoring area and send it to the main control module.

[0082] The main control module is further configured to remove the pixel points corresponding to the human body in the infrared image when it determines that there is someone in the real scene image; calculate the gray values of each pixel point in the infrared image; obtain the real-time temperature of each pixel point according to the gray values of each pixel point; average the real-time temperatures of each pixel point to obtain the real-time area temperature; determine whether the real-time area temperature is greater than the second preset temperature threshold. If so, start the cooling module. Among them, the second preset temperature threshold is less than the first preset temperature threshold.

[0083] Specifically, in a substation, in addition to the temperature of the insulation switch equipment itself, the temperature of the entire environment is also within the monitoring range of this application. Because even when the insulation switch equipment itself does not overheat due to internal faults, the external area temperature will also affect the insulation switch equipment. Therefore, this application can also dynamically adjust the cooling module according to the real-time area temperature to ensure the stability of the internal environment temperature of the substation, thereby ensuring that the operation of the electrical equipment is not affected by the external temperature.

[0084] Based on the monitoring of the implementation equipment temperature of the insulation switch equipment, the above-mentioned embodiment realizes the monitoring of the real-time area temperature and the control of the cooling module, further ensuring the monitoring accuracy and control stability of the substation environment temperature.

[0085] In some embodiments, the dust removal module further includes a gas analysis unit; the gas analysis unit is configured to analyze the composition and proportion of the inhaled gas when the dust removal module is started, and send the analysis result to the main control module for display.

[0086] Among them, the gas analysis unit may include an SF6 pressure sensor to control SF6 pressure data, thereby realizing the conversion of SF6 gas density and weight, and providing functions such as SF6 data monitoring, data meter reading, pressure warning, and leakage monitoring.

[0087] Specifically, the main control module can internally store a list of harmful gases and a list of combustible gases, such as SF 6 , CO, sulfur dioxide, nitrogen oxides, fluorine gas, and hydrogen gas, etc. If the gas components in the analysis result appear in the list and the proportion exceeds the requirements in the "Control Record Card for Key Process of Installation Quality and Technology of Main Electrical Equipment in Substation Project", the alarm module will also be controlled to give an alarm; at the same time, the gas exchange function of the dust removal module will be started to exchange the inhaled gas with the outside air after filtration.

[0088] The above embodiments realize the monitoring of gas components and proportions in the substation, enabling the staff in the monitoring area to observe in real time whether there are harmful gases or combustible gases, so as to stay away or handle them in time and avoid serious safety accidents.

[0089] In some embodiments, the dust removal module further includes a heavy metal monitoring unit; the heavy metal monitoring unit includes a magnetic sheet and an X-ray spectrometer; the magnetic sheet is used to adsorb metal particles in the filtering substance; the spectrometer is used to perform fluorescence spectrometer tests on each metal particle on the magnetic sheet to obtain quantitative results of different elements and send them to the main control module for display.

[0090] Among them, the magnetic sheet can be an array-type Hall sensor.

[0091] Specifically, there are many power equipment or combined electrical appliances in the substation, and a lot of metal materials will be used when generating these equipment and appliances. As the use time increases, it is very likely that metal chips will fall off; once these metal chips enter the human body with the dust, they will accumulate in the body and be difficult to discharge, which will seriously damage people's health over the years.

[0092] Therefore, this application detects the content of heavy metal particles contained in the air in each monitoring area of the substation by setting up a heavy metal monitoring unit. The main control module can also set corresponding thresholds for each heavy metal element, and mark the metal elements exceeding the corresponding thresholds in red on the display screen to further remind the staff in the substation to be careful of inhaling heavy metal particles.

[0093] Furthermore, the metal particles adsorbed by the magnetic sheet can be regularly pasted on the filter membrane for easy removal for chemical analysis.

[0094] In some embodiments, the system further includes a ground wave monitoring module; the ground wave monitoring module is installed at the center of the floor of the monitoring area; the ground wave monitoring module is used to issue an earthquake alarm when detecting seismic waves. Specifically, the relevant data of on-site monitoring will be automatically transmitted to the electronic large screen, enabling electrical construction personnel to have a clear view and take different measures in a timely manner according to the situation.

[0095] In some embodiments, the main control module is further configured to, when starting the dust removal module, input the dust density, the average dust diameter, and the real-time regional temperature into the trained power adjustment model to obtain the operating power of the dust removal module; and control the dust removal module to work according to the operating power. Among them, the setting standard of the operating power of the dust removal module is to ensure that the filtration efficiency is greater than or equal to 95%.

[0096] Specifically, considering the Brownian motion of dust particles and the influence of the sedimentation velocity of dust particles of different sizes on the suction efficiency, it can be obtained that the dust density and the average diameter are positively correlated with the operating power of the dust removal module, and the implementation area temperature is negatively correlated; therefore, comprehensively considering these three factors to adjust the appropriate dust removal operating power can greatly reduce the dust removal energy consumption.

[0097] Please refer to Figure 3 , another embodiment of the present application provides a GIS monitoring method for an intelligent substation, which is applied to a GIS monitoring system for an intelligent substation as described in any one of the above embodiments. The method includes:

[0098] Step S01, obtaining the illumination power of the lighting module and the real-scene image of the image acquisition module.

[0099] Step S02, obtaining the brightness value of the real-scene image according to the illumination power.

[0100] Step S03, performing illumination correction on the real-scene image based on the brightness value and the background extraction method to obtain a corrected image.

[0101] Specifically, the real-scene image can be a real-scene video composed of multiple real-scene image frames. The background extraction method can specifically adopt the optical flow method or the inter-frame difference method. The brightness value is used to correct each image frame so that the brightness of each image frame obtained at different times is the same, thereby ensuring the accuracy of the background extraction algorithm; the corrected image is a certain physical image frame after cutting the background.

[0102] Step S04, segmenting the corrected image by using the gray-level co-occurrence matrix to obtain a dust texture image.

[0103] Specifically, the gray-level co-occurrence matrix is obtained by statistically analyzing the situation where two pixels at a certain distance on the image have certain gray levels. It is defined as the frequency or probability P(i,j) of the gray level being j at a point that is at a certain fixed position (with a distance d and an orientation θ) starting from a pixel with a gray value of i (statistically analyzing the frequency or probability of the gray value pair being (i,j) in a pair of pixels according to a certain positional relationship), that is, all estimated values can be expressed in the form of a matrix, and thus it is called the gray-level co-occurrence matrix.

[0104] The dust texture features in the corrected image can be identified through the gray-level co-occurrence matrix and used as the dust texture image.

[0105] In this application, extracting texture features before image binarization can make the recognition accuracy of the pixels where dust particles are located higher during binarization, and the accuracy of the generation of the first pixel value and the calculation result of the first area higher.

[0106] Step S05: Binarize the dust texture image to obtain a grayscale image.

[0107] Step S06: Calculate the first area of the first pixel value and the second area of the grayscale image in the grayscale image.

[0108] Step S07: Compare the first area with the second area to obtain the dust density.

[0109] Among them, the first pixel value is 0, and the pixel points corresponding to the pixel value of 0 are the pixel points where the dust particles are located. The second area is the overall area of the grayscale image. By making the first area ratio the second area, the density of dust in the air can be obtained.

[0110] Step S08: Determine whether the dust density is greater than a preset density threshold; if so, activate the dust removal module.

[0111] The above embodiments identify the dust density in the monitoring area based on the illumination brightness and the real scene image. Compared with the method of using a sensor mounted on a robot for sensing, the method of this application is not affected by distance, improving the accuracy and real-time performance of substation dust monitoring.

[0112] In some embodiments, the main control module is further connected to an electrostatic monitoring module, and the electrostatic monitoring module is arranged on the inner wall of the air extraction pipeline of the dust removal module. Specifically, the method may further include:

[0113] Step S11: Obtain the gas flow rate of the dust removal module, the monitoring area of the electrostatic monitoring module, and the airflow static electricity.

[0114] Step S12: Differentiate the airflow static electricity and the monitoring area to obtain the current per unit area.

[0115] Step S13: Calculate the collision probability based on the current per unit area, the dust density, and the gas flow velocity.

[0116] Step S14: Obtain the Stokes number of the particles based on the collision probability and the correction factor.

[0117] Step S15: Obtain the average dust diameter based on the Stokes number, the dust density, and the slip correction factor.

[0118] Step S16: Determine whether the average dust diameter is greater than a preset inhalation threshold; if so, determine whether there is a person in the real scene image; if there is, control the alarm module to generate a warning message to stay away.

[0119] Wherein, it is assumed that the gas flow velocity is , the monitoring area is , the air flow static electricity is , t is the monitoring time, the dust density is , after differentiating the monitoring area, the current per unit area obtained is expressed as ; the collision probability The calculation formula of is:

[0120]

[0121] Let the known correction factor be , divide the collision probability by the correction factor and then square it to obtain the Stokes number .

[0122] Let the known slip correction factor be , then the average dust diameter The calculation formula of is:

[0123]

[0124] Further, to determine whether there is a person in the real scene image above, a target detection model can be used: obtain a historical real scene image set of the monitoring area, where the historical real scene images include real scene images with people and real scene images without people; train a neural network using the historical real scene image set to obtain a trained human detection model; input the real scene image into the human detection model to obtain the detection result.

[0125] Since a large amount of dust will be sucked up when the dust removal module is working, if there are staff members staying in the monitoring area at this time, they will inevitably inhale a part of the dust; therefore, the above embodiment can judge whether the air quality of the current substation meets the standard of being inhaled by the human body by calculating the average dust diameter, and warns people to stay away from the area when it does not meet the standard.

[0126] In some embodiments, the method further includes:

[0127] Step S21, obtain the detection results of the infrared image and the real scene image of the image acquisition module.

[0128] Step S22, if the detection result is that there is a person, remove the pixel points corresponding to the human body in the infrared image.

[0129] Step S23, calculate the gray value of each pixel point in the infrared image.

[0130] Step S24, obtain the real-time temperature of each pixel point according to the gray value of each pixel point.

[0131] Step S25, average the real-time temperatures of each pixel point to obtain the real-time regional temperature.

[0132] Step S26, determine whether the real-time regional temperature is greater than the second preset temperature threshold. If so, start the cooling module.

[0133] Specifically, the output result of the human body detection model is also a real scene image. If a human body is detected, it will be framed by a rectangular box. Therefore, after aligning the image output by the human body detection model with the infrared image, the infrared image can be cut using the rectangular box therein, so as to shield the influence of the human body temperature when calculating the implementation area temperature.

[0134] In some embodiments, the method further includes: obtaining the dust density, the average dust diameter, and the real-time regional temperature, and inputting them into the trained power adjustment model to obtain the operating power of the dust removal module; controlling the dust removal module to work according to the operating power.

[0135] Specifically, for the dust removal module, its energy consumption is affected by the operating power and the operating time; therefore, when creating and training the power adjustment model, the calculation formula of the energy consumption is used as the objective function, and the power adjustment range of the dust removal module is used as the constraint condition. The regional volume, the dust density, the average dust diameter, and the real-time regional temperature are input into the model, and the time required for dust removal at different powers is calculated and substituted into the objective function. After multiple iterations, the operating power value that minimizes the objective function, that is, the energy consumption, is obtained and output.

[0136] The above embodiments optimize the operating power of the dust removal module by training the power adjustment model, can minimize the energy consumption of the dust removal module, and further reduce the power consumption of the dust removal module on the basis of reducing the dust removal range.

[0137] An embodiment of the present application provides a computer device, which may include a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer device is used 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 the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the processor executes the steps of a GIS monitoring method for an intelligent substation as described in any of the above embodiments.

[0138] For the working process, working details, and technical effects of the computer device provided in this embodiment, reference may be made to the embodiments of a GIS monitoring method for an intelligent substation in the foregoing text, and details will not be repeated here.

[0139] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of a GIS monitoring method for an intelligent substation as described in any of the above embodiments. Among them, the computer-readable storage medium refers to a carrier for storing data, and may include, but is not limited to, a floppy disk, an optical disc, a hard disk, a flash memory, a USB flash drive, and / or a Memory Stick, etc. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. For the working process, working details, and technical effects of the computer-readable storage medium provided in this embodiment, reference may be made to the embodiments of a GIS monitoring method for an intelligent substation in the foregoing text, and details will not be repeated here.

[0140] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM).

[0141] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0142] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the appended claims.

Claims

1. A GIS monitoring system for a smart substation, characterized in that: The space of the smart substation is evenly divided into a plurality of monitoring areas; the system includes a monitoring control device located at the center of each monitoring area; The monitoring and control device includes a main control module, a lighting module, an image acquisition module and a dust removal module; The image acquisition module is used to obtain a real-scene image of the monitoring area after the lighting module is turned on, and send the real-scene image to the main control module; The main control module is used to obtain the illumination power of the lighting module; obtain the brightness value of the real scene image according to the illumination power; perform illumination correction on the real scene image based on the brightness value and background extraction method to obtain a corrected image; segment the corrected image using a grayscale co-occurrence matrix to obtain a dust texture image; binarize the dust texture image to obtain a grayscale image; calculate a first area of ​​a first pixel value in the grayscale image and a second area of ​​the grayscale image; compare the first area with the second area to obtain a dust density; and determine whether the dust density is greater than a preset density threshold; if so, start the dust removal module; The monitoring and control device also includes a static electricity monitoring module and an alarm module; The electrostatic monitoring module is arranged on the inner wall of the exhaust duct of the dust removal module; the electrostatic monitoring module is used to calculate the airflow static electricity and send it to the main control module when the dust removal module is turned on; the main control module is also used to obtain the gas flow rate of the dust removal module and the monitoring area of ​​the electrostatic monitoring module; according to the airflow static electricity and the monitoring area, the unit area current is obtained by differentiation; according to the unit area current, the dust density and the gas flow rate, the collision probability is calculated; specifically: in, The gas flow rate, Dust density, is the current per unit area, is the collision probability; The Stokes number of the particle is obtained according to the collision probability and the correction coefficient; specifically, the collision probability is divided by the correction coefficient and then squared to obtain the Stokes number; The average diameter of the dust is obtained based on the Stokes number, the dust density and the slip correction coefficient ;Specifically: in, is the Stokes number, The monitoring area, is the slip correction coefficient; And, determine whether the average diameter of the dust is greater than a preset inhalation threshold; if so, determine whether there is a person in the real scene image; if so, control the alarm module to generate a stay away alarm message.

2. The GIS monitoring system for smart substation according to claim 1 is characterized in that: It also includes temperature sensors and humidity sensors installed on each insulating switchgear in the smart substation; Each of the temperature sensors and each of the humidity sensors is respectively connected to the main control module in the monitoring and control device corresponding to the monitoring area where the insulating switchgear is located; The monitoring and control equipment also includes a dehumidification module and a cooling module; The temperature sensor is used to obtain the real-time device temperature of the insulating switch device and send it to the main control module; The humidity sensor is used to obtain the real-time equipment humidity of the insulating switchgear and send it to the main control module; The main control module is also used to control the alarm module to generate over-temperature alarm information according to the device number corresponding to the insulating switch device and start the cooling module when any of the real-time device temperatures is higher than the first preset temperature threshold; Furthermore, when the humidity of any of the real-time devices is higher than a preset humidity threshold, the alarm module is controlled to generate over-humidity alarm information according to the device number corresponding to the insulating switch device, and the dehumidification module is started.

3. The GIS monitoring system for smart substation according to claim 2 is characterized in that: The image acquisition module is also used to obtain the infrared image of the monitoring area and send it to the main control module; The main control module is also used to remove the pixel points corresponding to the human body in the infrared image when it is determined that there is a person in the real-scene image; calculate the grayscale value of each pixel point in the infrared image; obtain the real-time temperature of each pixel point according to the grayscale value of each pixel point; average the real-time temperature of each pixel point to obtain the real-time regional temperature; determine whether the real-time regional temperature is greater than a second preset temperature threshold, and if so, start the cooling module.

4. The GIS monitoring system for smart substation according to claim 1 is characterized in that: The dust removal module also includes a gas analysis unit; the gas analysis unit is used to analyze the composition and proportion of the inhaled gas when the dust removal module is started, and send the analysis results to the main control module for display.

5. The GIS monitoring system for smart substation according to claim 1 is characterized in that: The dust removal module also includes a heavy metal monitoring unit; the heavy metal monitoring unit includes a magnetic sheet and an X-ray spectrometer; The magnetic sheet is used to absorb metal particles in the filtered material; the spectrometer is used to perform fluorescence spectrometer test on each of the metal particles on the magnetic sheet to obtain quantitative results of different elements and send them to the main control module for display.

6. The GIS monitoring system for smart substation according to claim 1 is characterized in that: It also includes a ground wave monitoring module; the ground wave monitoring module is installed at the center of the floor of the monitoring area; The ground wave monitoring module is used to issue an earthquake alarm when a seismic wave is detected.

7. The GIS monitoring system for smart substation according to claim 3 is characterized in that: The main control module is also used to input the dust density, the average dust diameter and the real-time regional temperature into the trained power regulation model when starting the dust removal module to obtain the operating power of the dust removal module; And, controlling the dust removal module to work according to the operating power.

8. A GIS monitoring method for a smart substation, characterized in that: A GIS monitoring system for a smart substation according to at least one of claims 1 to 7, comprising: Acquire the illumination power of the illumination module and the real scene image of the image acquisition module; Obtaining a brightness value of the real scene image according to the light power; Performing illumination correction on the real scene image based on the brightness value and background extraction method to obtain a corrected image; Using a gray level co-occurrence matrix to segment the corrected image to obtain a dust texture image; Binarizing the dust texture image to obtain a grayscale image; Calculating a first area of ​​a first pixel value in the grayscale image and a second area of ​​the grayscale image; Compare the first area with the second area to obtain dust density; Determine whether the dust density is greater than a preset density threshold; if so, start the dust removal module; Obtain the gas flow rate of the dust removal module, the monitoring area of ​​the electrostatic monitoring module, and the airflow static electricity; Differentiate the airflow static electricity and the monitoring area to obtain a current per unit area; The collision probability is calculated according to the current per unit area, the dust density and the gas flow rate; specifically: in, The gas flow rate, Dust density, is the current per unit area, is the collision probability; The Stokes number of the particle is obtained according to the collision probability and the correction coefficient; specifically, the collision probability is divided by the correction coefficient and then squared to obtain the Stokes number; The average diameter of the dust is obtained based on the Stokes number, the dust density and the slip correction coefficient ;Specifically: in, is the Stokes number, The monitoring area, is the slip correction coefficient; Determine whether the average diameter of the dust is greater than a preset inhalation threshold; if so, determine whether there is a person in the real scene image; if so, control the alarm module to generate a stay away alarm message.

9. The GIS monitoring method for smart substation according to claim 8, characterized in that: The determining whether there is a person in the real scene image includes: Acquire a set of historical real-scene images of the monitoring area, wherein the historical real-scene images include real-scene images with people in them and real-scene images without people in them; The historical real-life image set is used to train the neural network to obtain a trained human body detection model; The real scene image is input into the human body detection model to obtain a detection result.

10. The GIS monitoring method for smart substation according to claim 9, characterized in that: Also includes: Acquire the detection results of the infrared image of the image acquisition module and the real scene image; If the detection result is that there is a person, then remove the pixel points corresponding to the human body in the infrared image; Calculating the grayscale value of each pixel in the infrared image; Obtaining the real-time temperature of each pixel point according to the grayscale value of each pixel point; Averaging the real-time temperatures of the pixels to obtain the real-time regional temperature; Determine whether the real-time regional temperature is greater than a second preset temperature threshold, and if so, start the cooling module.

11. The GIS monitoring method for smart substation according to claim 10, characterized in that: Also includes: The dust density, the average dust diameter and the real-time regional temperature are obtained and input into a trained power regulation model to obtain the operating power of the dust removal module; and the dust removal module is controlled to work according to the operating power.

12. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the GIS monitoring method for the smart substation as described in any one of claims 8 to 11 are implemented.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the GIS monitoring method for a smart substation as claimed in any one of claims 8 to 11 are implemented.

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