Intelligent cleaning system applied to dust removal equipment

Abstract

The invention relates to the technical field of tunnel dust removal, in particular to an intelligent cleaning system applied to dust removal equipment, which comprises an electrostatic dust removal device, discharge pieces and dust collection plates are arranged in the electrostatic dust removal device, the discharge pieces and the dust collection plates are arranged in a staggered manner, and the discharge pieces and the dust collection plates are vertically arranged; a spraying mechanism is further arranged in the electrostatic dust collection device and faces the discharge pieces and the dust collection plates; the device further comprises a main control module, the main control module is used for starting the spraying mechanism in a timed mode, and the spraying mechanism is used for spraying cleaning liquid to the discharging pieces and the dust collecting plates. By adopting the scheme, the dust collection plate can be automatically cleaned.

Description

Technical Field

[0001] The invention relates to the technical field of tunnel dust removal, and in particular to an intelligent cleaning system applied to dust removal equipment. Background Art

[0002] During the driving process, the wheels rub against the road surface, the impurities outside the tunnel are brought in by the vehicle, and the harmful gases such as automobile exhaust, carbon monoxide, and sulfur dioxide are generated during the driving process, which causes an increase in dust in the tunnel. A large amount of dust in the tunnel will interfere with the driver's vision, making the visibility of the tunnel environment, which is already poor, even lower; secondly, the dust can easily enter the equipment in the tunnel, causing equipment abnormalities or failures, causing great safety hazards, and at the same time increasing the frequency of maintenance. Maintenance in the tunnel will interfere with the tunnel's traffic, further increasing safety hazards. Therefore, in the prior art, an air purification device is installed in the tunnel to purify the air in the tunnel and collect and uniformly treat the dust in the air.

[0003] At present, electrostatic dust removal is mainly used in tunnels. The dust is charged by discharging a stage, and a dust collecting plate is set with an opposite charge to the dust. The dust moves toward the dust collecting plate under the action of the charge and adheres to the dust collecting plate to achieve dust collection. When there is too much dust attached to the dust collecting plate, the subsequent dust will be farther away from the dust collecting plate when passing through, and the adsorption capacity will be weakened. It may fall off the dust collecting plate under the action of airflow, and even fail to adsorb dust, resulting in the inability to achieve air dust removal in the tunnel. At the same time, the existing air purifier is installed on the top of the tunnel and is difficult to clean. Therefore, the staff usually cleans the air purification device at the same time. However, in actual applications, due to changes in the traffic volume in the tunnel and the influence of external weather, the amount of dust in the tunnel is different. Before cleaning, the air purifier can no longer achieve the cleaning effect. Summary of the invention

[0004] The present invention aims to provide an intelligent cleaning system for dust removal equipment, which can automatically clean the dust collecting plate.

[0005] The present invention provides the following basic scheme: An intelligent cleaning system applied to dust removal equipment includes an electrostatic dust removal device, wherein a discharge sheet and a dust collecting plate are arranged in the electrostatic dust removal device, the discharge sheet and the dust collecting plate are arranged alternately, and the discharge sheet and the dust collecting plate are arranged vertically; a spray mechanism is also arranged in the electrostatic dust removal device, and the spray mechanism is directed toward the discharge sheet and the dust collecting plate; It also includes a main control module, which is used to start the spray mechanism at a fixed time, and the spray mechanism is used to spray cleaning liquid to the discharge plate and the dust collecting plate.

[0006] Furthermore, it also includes a detection end, which is used to detect the air before and after entering the electrostatic dust removal device to generate an air parameter group; The main control module is used to determine whether the electrostatic dust removal device has dust removal abnormality according to the air parameter group, and is also used to start the spray mechanism when it is determined that the electrostatic dust removal device has dust removal abnormality.

[0007] Furthermore, the main control module is preset with a timing duration, and the main control module is also used to re-time according to the timing duration each time the spray mechanism is started, and start the spray mechanism when the timing ends.

[0008] Furthermore, it also includes a fan, and the main control module also has preset air-drying parameters. The main control module is also used to control the wind speed of the fan according to the air-drying parameters after closing the spray mechanism.

[0009] Furthermore, the spray mechanism includes a water inlet pipe and a plurality of nozzles arranged on the water inlet pipe, the water inlet pipe is located at the top of the electrostatic precipitator, and the nozzles face the discharge sheet and the dust collecting plate.

[0010] Furthermore, the electrostatic precipitator is connected to a drain pipe, the drain pipe is connected to the electrostatic precipitator, and the drain pipe is located at the bottom of the electrostatic precipitator; the bottom of the electrostatic precipitator is inclined.

[0011] Furthermore, it also includes a dust removal air duct, which includes an air inlet, and an electrostatic dust removal device is installed in the dust removal air duct; it also includes a monitoring terminal, which is used to capture the air intake image of the air inlet; the main control module is also used to re-acquire the current air parameter group when it is determined that the electrostatic dust removal device has a dust removal abnormality and the spray mechanism is controlled to be closed, and to re-determine whether the electrostatic dust removal device has a dust removal abnormality based on the current air parameter group; it is also used to start the monitoring terminal when it is determined again that the electrostatic dust removal device has a dust removal abnormality; it is also used to make an abnormality judgment based on the air intake image when it is determined again that the electrostatic dust removal device has a dust removal abnormality.

[0012] Furthermore, the abnormality determination result includes human factors. The main control module is also used to mark the abnormal object according to the air intake image when the abnormality determination result is a human factor, and call the tunnel image of the same period to identify the trajectory of the abnormal object according to the tunnel image, and generate a source video containing the source of the abnormality.

[0013] Furthermore, the main control module includes an image processing submodule, which is used to call the air intake image for contour processing after it is determined again that the electrostatic dust removal device has dust removal abnormality, identify abnormal objects based on the processed air intake image, and make abnormality judgment based on the abnormal objects.

[0014] Furthermore, the image processing submodule presets a plurality of sets of processing weights, and the image processing submodule is also used to obtain real scene parameters, filter the processing weights according to the real scene parameters, and perform contour processing on the air intake image according to the filtered processing weights.

[0015] Beneficial effects of the basic program: 1. In this solution, the setting of the discharge sheet makes the dust and impurities in the air charged, so that they are adsorbed on the dust collecting plate, so as to realize the collection of dust and impurities. The timing duration is the preset interval duration for cleaning the dust collecting plate. The setting of the spray mechanism, whose nozzle is facing the dust collecting plate, during the use of the electrostatic dust removal device, the spray mechanism is started at a time to spray through the nozzle, and the dust adsorbed on the dust collecting plate is cleaned by the water sprayed from the nozzle. The setting of the drain pipe, the sewage generated by cleaning the dust collecting plate is discharged from the drain pipe, so as to automatically clean the dust collecting plate and remove the adsorbed dust, so as to ensure the subsequent dust collecting plate's dust adsorption effect, thereby ensuring the air purification effect in the tunnel.

[0016] At the same time, an air parameter group is set in this scheme. The air parameter group is the parameters collected by sensors such as carbon dioxide sensors, carbon monoxide sensors, VOC sensors, nitric oxide sensors, and sulfur dioxide sensors at the same time. The air parameter group includes parameters before and after entering the electrostatic dust removal device. The air parameter group is used to determine whether the electrostatic dust removal device still has a cleaning effect. If it does not have a cleaning effect, it is determined that dust removal is abnormal, and the spray mechanism is started for cleaning. In this scheme, on the basis of regular cleaning of the electrostatic dust removal device, real-time monitoring is performed based on the air parameter group, and cleaning is also performed when dust removal is abnormal. In this way, when the traffic volume in the tunnel increases and the dust increases due to the influence of external weather, the electrostatic dust removal device is cleaned in time to ensure the cleaning effect of the electrostatic dust removal device on the air in the tunnel.

[0017] 2. The fan is used to centrally transport air and speed up the air flow rate. The air-drying parameter is the parameter for controlling the fan speed, which is smaller than the fan speed during the dust removal process. After each start-up of the spray mechanism, the fan speed is reduced according to the air-drying parameter to accelerate the evaporation of water through the airflow, reduce the risk of leakage, and at the same time reduce corrosion to related structures and extend the service life.

[0018] 3. In this solution, when the spray mechanism is activated due to dust removal anomaly, after the dust collecting plate is cleaned, the air parameter group is obtained again for judgment. If the dust removal anomaly still occurs, it is considered that there are other problems. At this time, the monitoring terminal is started to obtain the air intake image of the air inlet of the dust removal duct for abnormal judgment. For example, the dust removal anomaly may be caused by foreign objects such as plastic bags, leaves, and flying birds appearing at the air inlet, resulting in abnormalities in the air parameter group. At this time, the judgment is made through the air intake image. Among them, plastic bags are mostly caused by uncivilized behavior of people in the vehicle, such as discarding plastic bags, while leaves and flying birds are caused by the natural environment. These anomalies are very likely to cause safety accidents in the tunnel. For example, plastic bags and flying birds interfere with the driver's sight and pose safety hazards. Therefore, in this solution, for the anomaly caused by human factors, it is traced. When the anomaly judgment result is human factors, the anomaly is marked, and the tunnel image of the same period is called. The tunnel image is an image collected by a camera set in the tunnel. The movement trajectory of the anomaly is identified based on the tunnel image to find the source of the anomaly, that is, the vehicle that discarded the plastic bag. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a structural schematic diagram of Embodiment 1 of the intelligent cleaning system for dust removal equipment of the present invention; Figure 2 This is a schematic structural diagram of an electrostatic dust removal device and a sterilization device in Embodiment 1 of the intelligent cleaning system of the present invention applied to dust removal equipment; Figure 3 This is a logic block diagram of the main control module of Embodiment 2 of the intelligent cleaning system for dust removal equipment according to the present invention. DETAILED DESCRIPTION

[0020] The following is further described in detail through specific implementation methods: The reference numerals in the drawings of the specification include: electrostatic dust removal device 1, sterilization device 2, dust removal air duct 3, air inlet 4, air outlet 5, pre-filter 6, ultraviolet lamp 7, discharge sheet 8, dust collecting plate 9. Example

[0021] The intelligent cleaning system for dust removal equipment includes an electrostatic dust removal device 1, a main control module, a detection terminal, a fan, a sterilization device 2, and a dust removal air duct 3. Figure 1 As shown, the dust removal duct 3 includes an air inlet 4 and an air outlet 5. The sterilization device 2, the electrostatic dust removal device 1, and the fan are all installed in the dust removal duct 3 and are arranged in sequence from the air inlet 4 to the air outlet 5.

[0022] As attached Figure 2As shown, the two ends of the sterilization device 2 are connected to form a channel for air to pass through (i.e., the dust removal duct 3). A pre-filter 6 and an ultraviolet lamp 7 are provided in the sterilization device 2. The pre-filter 6 is arranged vertically, and the plane of the pre-filter 6 is perpendicular to the air flow direction. The pre-filter 6 is used to filter large-particle dust, thereby reducing the large-particle dust that subsequently enters the electrostatic dust removal device 1, thereby reducing the large-particle dust adsorbed in the electrostatic dust removal device 1, reducing the interference of large-particle dust on the adsorption of small-particle dust, and improving the adsorption effect of small-particle dust. The ultraviolet lamp 7 is installed at the top of the sterilization device 2. In this embodiment, the ultraviolet lamp 7 adopts the existing ultraviolet lamp 7 tube, and the ultraviolet lamp 7 is installed in the sterilization body by screws. The sterilizer is used to disinfect bacteria in the air.

[0023] The two ends of the electrostatic precipitator 1 are connected to form a channel for air to pass through (i.e., the dust removal air duct 3). The electrostatic precipitator 1 is provided with a discharge sheet 8 and a dust collecting plate 9. The discharge sheet 8 and the dust collecting plate 9 are located in the channel. The discharge sheet 8 and the dust collecting plate 9 are staggered. The discharge sheet 8 and the dust collecting plate 9 are both arranged vertically. The discharge sheet 8 and the dust collecting plate 9 adopt a plate-type electrostatic precipitator. An opening is provided on one side of the electrostatic precipitator 1 (i.e., an opening is provided on one side of the dust removal air duct 3, and the opening is directly opposite to the plate-type electrostatic precipitator). The opening is hinged with a baffle, and the plate-type electrostatic precipitator can be taken out from the opening for maintenance or replacement.

[0024] A spray mechanism is also provided in the electrostatic precipitator 1, and the spray mechanism faces the discharge sheet 8 and the dust collecting plate 9. The spray mechanism includes a water inlet pipe and a plurality of nozzles provided on the water inlet pipe. The water inlet pipe is located at the top of the electrostatic precipitator 1, and the nozzles face the discharge sheet 8 and the dust collecting plate 9. Specifically, a water inlet pipe is provided at the top of the electrostatic precipitator 1 in the dust removal air duct 3. One end of the water inlet pipe passes through the dust removal air duct 3 and is connected to the water tank. A water pump is provided on the water inlet pipe. Cleaning liquid is stored in the water tank. In this embodiment, the cleaning liquid is clean water. In other embodiments, the cleaning liquid is a liquid with a decontamination effect. Water is supplied to the spray mechanism through the water tank and the water pump. The water inlet pipe is connected to a plurality of nozzles, which are distributed in a matrix. The top of the plate-type electrostatic precipitator is open, and the nozzle faces the plate-type electrostatic precipitator. The nozzle is used to spray the dust collecting plate 9 to achieve automatic cleaning of the dust collecting plate 9.

[0025] The electrostatic precipitator 1 is connected to a drain pipe, which is connected to the electrostatic precipitator 1. The drain pipe is located at the bottom of the electrostatic precipitator 1, and the bottom of the electrostatic precipitator 1 is inclined. Specifically, the bottom of the plate-type electrostatic precipitator is open, and a drain port is provided at the bottom of the electrostatic precipitator 1 in the dust removal air duct 3, which is connected to the drain pipe. The bottom of the electrostatic precipitator 1 is inclined from high to low in a direction away from the drain port. The sewage after spraying is discharged from the bottom opening of the plate-type electrostatic precipitator and the drain port at the bottom of the electrostatic precipitator 1.

[0026] The spray mechanism is used to spray cleaning liquid to the discharge sheet 8 and the dust collecting plate 9. The main control module is used to start the spray mechanism at a fixed time. Specifically, the main control module is preset with a timing duration, and the main control module is used to count according to the timing duration, and start the spray mechanism when the timing ends. In this way, the dust collecting plate 9 is automatically and regularly cleaned.

[0027] The main control module is also preset with air-drying parameters. The main control module is also used to control the wind speed of the fan according to the air-drying parameters after closing the spray mechanism. Specifically, the main control module is preset with air-drying parameters and dust removal parameters. When the air is dusted, the main control module is used to control the wind speed of the fan according to the dust removal parameters. After the spray mechanism is started for a certain period of time, the cleaning of the dust collecting plate 9 is completed by default, and the spray mechanism is closed at this time, that is, the main control module is preset with a cleaning time. The main control module is also used to call the cleaning time when starting the spray mechanism, and count according to the cleaning time. When the timing ends, the spray mechanism is closed. The main control module is also used to call the air-drying parameters after closing the spray mechanism, and control the wind speed of the fan according to the air-drying parameters. The air-drying parameters are less than the dust removal parameters, that is, after cleaning the dust collecting plate 9, the wind speed of the fan is reduced, and the evaporation of water is accelerated through the airflow, the risk of leakage is reduced, and the corrosion to the related structures is reduced, and the service life is extended.

[0028] The detection end is used to detect the air before and after entering the electrostatic dust removal device 1 and generate an air parameter group. The detection end is set at the air inlet 4 and the air outlet 5 of the dust removal air duct 3, and is used to collect parameters before and after air treatment. The detection end includes a carbon dioxide sensor, a carbon monoxide sensor, a VOC sensor, a nitrogen monoxide sensor, a sulfur dioxide sensor, a PM2.5 detection sensor, etc. The detection end is used to generate an air parameter group based on the data collected by the sensors at the same time, and upload the air parameter group to the main control module.

[0029] The main control module is used to determine whether the electrostatic precipitator 1 has a dust removal anomaly based on the air parameter group, and is also used to start the spray mechanism when it is determined that the electrostatic precipitator 1 has a dust removal anomaly. Specifically, the air parameter group includes sulfur dioxide parameters and PM2.5 parameters before and after treatment. In this embodiment, the main control module is also used to calculate the difference between the air parameter group before and after air treatment. When the difference is greater than the preset parameter threshold, it is determined that the electrostatic precipitator 1 has a dust removal anomaly. In other embodiments, the main control module is also used to screen the parameters after air treatment in the air parameter group, determine whether the parameters are greater than the preset parameter threshold, and if so, determine that the electrostatic precipitator 1 has a dust removal anomaly.

[0030] The main control module is also used to reset the time according to the timing duration each time the spray mechanism is started, and start the spray mechanism when the timing ends. When it is determined that the electrostatic dust removal device 1 has dust removal abnormality, the spray mechanism will be started. At this time, the timing duration has not been reached, but the dust collecting plate 9 has been cleaned, so the timing duration is called to reset the time.

[0031] By adopting this scheme, dust and impurities in the air are collected through the electrostatic dust removal device 1. At the same time, the dust adsorbed on the dust collecting plate 9 is cleaned regularly through the setting of the spray mechanism. On the basis of regularly cleaning the electrostatic dust removal device 1, real-time monitoring is performed based on the air parameter group, and cleaning is also performed when the dust removal is abnormal. In this way, when the traffic volume in the tunnel increases and the dust increases due to the influence of external weather, the electrostatic dust removal device 1 is cleaned in time to remove the adsorbed dust, so as to ensure the adsorption effect of the subsequent dust collecting plate 9 on the dust, thereby ensuring the purification effect of the air in the tunnel. Example

[0032] The difference between this embodiment and the first embodiment is that: The intelligent cleaning system applied to the dust removal equipment also includes a monitoring terminal, which is used to capture the image of the air intake of the air intake 4. The monitoring terminal is arranged at the air intake 4 of the dust removal air duct 3, facing the pre-filter 6, and is used to capture the image of the air intake including the pre-filter 6. The monitoring terminal can also be arranged on the tunnel, facing the air intake 4 of the dust removal air duct 3, and is used to capture the image of the air intake including the air intake 4 and the pre-filter 6.

[0033] As attached Figure 3 As shown, the main control module includes a dust removal abnormality determination submodule, a monitoring management submodule, an image abnormality determination submodule, an image processing submodule, an image calling submodule and a video combination submodule.

[0034] In this embodiment, the air parameter group also includes air volume, and the main control module is used to screen the parameters after air treatment in the air parameter group, and determine whether the parameters are greater than the preset parameter threshold. If so, it is determined that the electrostatic dust removal device 1 has a dust removal abnormality. The main control module is also used to re-acquire the current air parameter group when it is determined that the electrostatic dust removal device 1 has a dust removal abnormality and the spray mechanism is controlled to be closed, and to determine whether the electrostatic dust removal device 1 has a dust removal abnormality again based on the current air parameter group. Specifically, the dust removal abnormality determination submodule is used to calculate the difference between the air parameter group before and after air treatment, and when the difference is greater than the preset parameter threshold, it is determined that the electrostatic dust removal device 1 has a dust removal abnormality. The dust removal abnormality determination submodule is also used to determine that the electrostatic dust removal device 1 has a dust removal abnormality and the spray mechanism is controlled to be closed, and to re-acquire the current air parameter group, and to determine whether the parameters are greater than the preset parameter threshold based on the parameters after air treatment in the current air parameter group. If so, it is determined that the electrostatic dust removal device 1 has a dust removal abnormality again. After cleaning the dust collecting plate 9, a secondary determination is made based on the air parameter group. If the dust removal is still determined to be abnormal, there may be other reasons leading to the abnormality, such as the air inlet 4 being blocked or obstructed.

[0035] The main control module is also used to start the monitoring terminal when it is determined that the electrostatic precipitator 1 has dust removal abnormality again; it is also used to make an abnormality determination based on the air intake image after it is determined that the electrostatic precipitator 1 has dust removal abnormality again. The monitoring management submodule is used to generate a monitoring start signal and send it to the monitoring terminal when it is determined again that the electrostatic precipitator 1 has a dust removal abnormality, so as to control the monitoring terminal to start.

[0036] The image processing submodule is used to call the air intake image for contour processing after it is determined that the electrostatic dust removal device 1 has dust removal anomalies again, identify abnormal objects based on the processed air intake image, and make an abnormality determination based on the abnormal objects. The image processing submodule is preset with multiple sets of processing weights. The image processing submodule is also used to obtain real scene parameters, filter the processing weights based on the real scene parameters, and perform contour processing on the air intake image based on the filtered processing weights. Specifically, the following steps are included: Step 1: Get the real scene image captured by the camera in the tunnel, and generate real scene parameters by comparing the real scene image with the preset standard scene image. The real scene parameters are used to characterize the color preference of the real scene image. For example, in autumn and winter, the tunnel is warm white, in haze days, the tunnel is yellow, and the brightness of the tunnel during the day is higher than at night. The color preference of the current real scene image is analyzed by image comparison.

[0037] Step 3: Calculate the G value of each pixel based on the selected processing weight and RGB three-channel values. The calculation formula is as follows:

[0038] Where (x, y) is used to represent the pixel points at the corresponding coordinates. They are the RGB three-channel values ​​of the pixel point respectively. is the G value of the pixel.

[0039] Step 4: Assign the G value to the RGB three-channel value of the corresponding pixel point, perform the above steps one by one for each pixel point, obtain the processed air intake image, and complete the contour processing.

[0040] Step 5: Identify abnormal objects based on the processed air intake image. A standard air intake image is preset. The standard air intake image is an image collected under the same viewing angle as the air intake image under normal circumstances. The standard air intake image has been processed by contour processing. Compare the standard air intake image and the processed air intake image to identify abnormal objects.

[0041] Step 6: Perform abnormality determination based on the abnormal object, identify the abnormal object through image recognition technology, and determine the abnormal object. In this embodiment, the abnormal object can be determined as leaves, plastic bags, organisms, and unrecognizable.

[0042] The image abnormality determination submodule is used to perform abnormality determination based on the air intake image and generate abnormality determination results after it is determined again that the electrostatic dust removal device 1 has a dust removal abnormality. The abnormality determination results include human causes, natural causes and other causes. When the abnormal objects are determined to be leaves and organisms, the abnormality determination results generated are natural causes; when the abnormal objects are determined to be plastic bags, the abnormality determination results generated are human causes; when the abnormal objects are determined to be unrecognizable, the abnormality determination results generated are other causes. Based on different abnormal objects, the causes induced by them are determined to belong to different categories, and different measures are taken for different causes. For example, for natural causes, the device can be improved or new induction devices can be added, such as bird repellers, to reduce the probability of occurrence. For other causes, the types of abnormal object identification can be strengthened or the device can be improved to improve the accuracy of image recognition and reduce the probability of occurrence. For human causes, trace the source and prevent them from happening at the source.

[0043] The main control module is also used to mark the abnormal object according to the air intake image when the abnormality is determined to be caused by human factors, and call the tunnel image of the same period, identify the trajectory of the abnormal object according to the tunnel image, and generate a source video containing the source of the abnormality. Specifically: the attribute information of the air intake image and the tunnel image includes the corresponding shooting time. The tunnel image is an image captured by an existing camera in the tunnel. The image calling submodule is used to obtain the marked abnormal object and the shooting time corresponding to the air intake image when the abnormality is determined to be caused by human factors, obtain the tunnel image of the same period according to the shooting time, filter the tunnel image according to the abnormal object, and filter out the tunnel image containing the abnormal object for calling. The same period is a period of time before the corresponding shooting time of the air intake image. In this embodiment, the duration of the same period is 30 minutes. For example, if the shooting time corresponding to the air intake image is 13:25, then the same period is from 12:55 to 13:25.

[0044] The image processing submodule is also used to perform contour processing on the tunnel image called by the image calling submodule according to the same processing weight.

[0045] The video combination submodule is used to identify the track of the abnormal object according to the tunnel image after contour processing, the shooting time corresponding to the tunnel image, and the position of the abnormal object in the tunnel image, and to filter and combine the tunnel image according to the track identification to generate a temporary video. The video combination submodule is also used to filter the corresponding tunnel image according to the tunnel image called by the image calling submodule from the temporary video to replace it and generate the source video. Both the source video and the temporary video contain the abnormal object, the moving track of the abnormal object, and the abnormal source. The image in the temporary video is the image after contour processing, and the image in the source video is the image without contour processing. The image after contour processing is easy for machine recognition, while the image without contour processing is easy for human eyes to observe. The abnormal source is the source of the plastic bag, such as the uncivilized behavior of a vehicle discarding a garbage bag while driving, and the abnormal source is the corresponding vehicle.

[0046] In this solution, when the spray mechanism is started due to dust removal anomaly, after the dust collecting plate 9 is cleaned, the air parameter group is obtained again for judgment. If the dust removal anomaly still occurs, it is considered that there are other problems. At this time, the monitoring terminal is started, and the air intake image of the air inlet 4 of the dust removal air duct 3 is obtained for abnormal judgment. For example, the dust removal anomaly may be caused by foreign objects such as plastic bags, leaves, and flying birds appearing at the air inlet 4, resulting in abnormalities in the air parameter group. At this time, the judgment is made through the air intake image. Among them, plastic bags are mostly caused by uncivilized behavior of people in the vehicle, such as discarding plastic bags, while leaves and flying birds are caused by the natural environment. These anomalies are very likely to cause safety accidents in the tunnel. For example, plastic bags, flying birds, etc. interfere with the driver's line of sight and pose a safety hazard. Therefore, in this solution, for man-made anomalies, tracing is carried out. When the abnormality is determined to be a man-made cause, the abnormal object is marked, and the tunnel image of the same period is called. The tunnel image is an image collected by a camera set in the tunnel. The movement trajectory of the abnormal object is identified based on the tunnel image to find the source of the abnormal object, that is, the vehicle that discarded the plastic bag. Implement different solutions for different causes to reduce the probability of abnormalities.

[0047] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field of the invention before the application date or priority date, can know all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. Intelligent cleaning system for dust removal equipment, characterized by: The electrostatic dust removal device comprises a discharge sheet and a dust collecting plate, which are arranged alternately and vertically; the electrostatic dust removal device is also provided with a spray mechanism, which faces the discharge sheet and the dust collecting plate; It also includes a main control module, which is used to start the spray mechanism at a fixed time, and the spray mechanism is used to spray cleaning liquid to the discharge plate and the dust collecting plate.

2. The intelligent cleaning system for dust removal equipment according to claim 1 is characterized in that: It also includes a detection end, which is used to detect the air before and after entering the electrostatic dust removal device to generate an air parameter group; The main control module is used to determine whether the electrostatic dust removal device has dust removal abnormality according to the air parameter group, and is also used to start the spray mechanism when it is determined that the electrostatic dust removal device has dust removal abnormality.

3. The intelligent cleaning system for dust removal equipment according to claim 2 is characterized in that: The main control module is preset with a timing duration. The main control module is also used to re-time according to the timing duration each time the spray mechanism is started, and start the spray mechanism when the timing ends.

4. The intelligent cleaning system for dust removal equipment according to claim 3 is characterized in that: It also includes a fan, and the main control module also has preset air-drying parameters. The main control module is also used to control the wind speed of the fan according to the air-drying parameters after closing the spray mechanism.

5. The intelligent cleaning system for dust removal equipment according to claim 4 is characterized in that: The spray mechanism comprises a water inlet pipe and a plurality of nozzles arranged on the water inlet pipe. The water inlet pipe is located at the top of the electrostatic dust removal device, and the nozzles face the discharge sheet and the dust collecting plate.

6. The intelligent cleaning system for dust removal equipment according to claim 5 is characterized in that: The electrostatic precipitator is connected with a drainage pipe, the drainage pipe is connected with the electrostatic precipitator, and the drainage pipe is located at the bottom of the electrostatic precipitator; the bottom of the electrostatic precipitator is inclined.

7. The intelligent cleaning system for dust removal equipment according to claim 6 is characterized in that: It also includes a dust removal air duct, the dust removal air duct includes an air inlet, and the electrostatic dust removal device is installed in the dust removal air duct; It also includes a monitoring terminal, which is used to capture an image of air intake at the air inlet; The main control module is also used to re-acquire the current air parameter group when it is determined that the electrostatic dust removal device has a dust removal abnormality and the spray mechanism is controlled to be closed, and to determine again whether the electrostatic dust removal device has a dust removal abnormality based on the current air parameter group; It is also used to start the monitoring terminal when it is determined again that the electrostatic precipitator has a dust removal abnormality; it is also used to make an abnormality determination based on the air intake image after it is determined again that the electrostatic precipitator has a dust removal abnormality.

8. The intelligent cleaning system for dust removal equipment according to claim 7 is characterized in that: The abnormality determination result includes human factors. The main control module is also used to mark the abnormal object according to the air intake image when the abnormality determination result is human factors, and call the tunnel image of the same period to identify the trajectory of the abnormal object according to the tunnel image, and generate a source video containing the source of the abnormality.

9. The intelligent cleaning system for dust removal equipment according to claim 8, characterized in that: The main control module includes an image processing submodule, which is used to call the air intake image for contour processing after it is determined that the electrostatic dust removal device has dust removal abnormality again, identify abnormal objects based on the processed air intake image, and make abnormality judgment based on the abnormal objects.

10. The intelligent cleaning system for dust removal equipment according to claim 9, characterized in that: The image processing submodule has multiple sets of processing weights preset. The image processing submodule is also used to obtain real scene parameters, filter the processing weights according to the real scene parameters, and perform contour processing on the air intake image according to the filtered processing weights.

Images