Apparatus for monitoring abnormality of diffuser for detecting water-surface pattern of digestion tank

Abstract

This apparatus for monitoring an abnormality of a diffuser that detects a water-surface pattern of a digestion tank comprises: a plurality of cameras for photographing the water surface of the digestion tank from a plurality of directions; and a control unit for storing an abnormal water-surface pattern at the time of abnormal operation of the diffuser, by using an artificial intelligence model, the abnormal water-surface pattern being obtained from a plurality of images of the water surface of the digestion tank photographed at a plurality of angles by the plurality of cameras, and comparing a water-surface pattern in the images photographed by the plurality of cameras with an abnormal-operation pattern, by using the artificial intelligence model, wherein when it is determined from a result of the comparison that a similarity between the patterns is equal to or greater than a predetermined threshold, the control unit determines that the diffuser is operating abnormally.

Description

Abnormal monitoring device for detecting the sleep pattern of the digester and the acid pipe

[0001] The present invention relates to an abnormality monitoring device for a digestion tank water surface pattern detection diffuser, and more specifically, to an abnormality monitoring device for a digestion tank water surface pattern detection diffuser that detects an abnormality in the diffuser by analyzing an image taken of the digestion tank water surface.

[0002] Aerobic digesters for sewage treatment typically have multiple air aeration pipes installed at the bottom to supply dissolved oxygen for aerobic microorganisms. The oxygen from the supplied air bubbles dissolves in the sewage inside the digester, supplying dissolved oxygen to aerobic microorganisms, effectively digesting the organic matter in the sewage. While these aeration pipes are equipped with pores, they can become clogged by organic matter or aerobic microorganisms in the sewage, or by accumulated sediment.

[0003] However, since the existing method of checking whether there is a problem with the aeration pipe is by determining the degree to which water gushes to the surface of the aerobic digester, there is a waste of manpower, and there is also the problem that it is difficult to determine with the naked eye in dark conditions. In addition, the bottom area of ​​the aerobic digester where the aeration pipe is installed is deep, about 6 to 10 m from the surface of the water, and it is very dark, so when a problem with the aeration pipe occurs, in order to replace the aeration pipe, a diver must be dispatched to perform the replacement work directly or all the sewage inside the aerobic digester must be drained before the work is done. However, both of these methods have the problem of being very risky and causing very large economic losses.

[0004] Accordingly, the purpose of the present invention is to provide a device for monitoring abnormalities in a digester water pattern detection system, which can determine abnormalities in a digester water pattern due to abnormalities in a digester water pattern.

[0005] In order to achieve the above object, the present invention provides a device for monitoring abnormalities in a water distribution system for detecting a water surface pattern of a digester tank, including: a plurality of cameras for photographing the water surface of the digester tank from a plurality of directions; and a control unit for storing abnormal water surface patterns in the case of abnormal operation of the water distribution system using an artificial intelligence model from a plurality of images of the water surface of the digester tank photographed by the plurality of cameras from a plurality of angles, and comparing the water surface patterns in the images photographed by the plurality of cameras using the artificial intelligence model with the abnormal operation pattern, and determining that the water distribution system is abnormal if the water surface pattern is determined to be similar to a predetermined degree of similarity or higher. Since the convenience of the manager and the accuracy of determining abnormalities in the water distribution system can be improved by learning and storing whether the water surface pattern of the digester tank is a normal operation pattern or an abnormal operation pattern using the artificial intelligence model and then determining that the water distribution system is abnormal if the water surface pattern in the image photographed of the digester tank is determined to be similar to the abnormal operation pattern, the device can be used to improve the accuracy of determining abnormalities in the water distribution system.

[0006] Here, the control unit preferably stores a normal water surface pattern when the aeration device is operating normally from images taken from multiple angles of the digester surface using an artificial intelligence model, and when the aeration device is determined to be abnormal, compares the water surface pattern in images taken from the multiple cameras with the normal operation pattern to identify an area having the abnormal operation pattern, and determines the location of the abnormal aeration device based on the identified area, and determines an area where the normal operation pattern is not visible as an abnormal area of ​​the aeration device, and calculates location information of the aeration device corresponding to the abnormal area.

[0007] And it further includes an abnormal repair robot that performs repairs including replacement of the above-mentioned aeration pipe; and a communication unit that communicates with the above-mentioned aeration pipe, wherein the control unit controls the communication unit to transmit location information of the above-mentioned aeration pipe and a control signal for repairing the aeration pipe to the above-mentioned aeration pipe, so that the abnormal repair robot, which has learned about the replacement work of the aeration pipe by an artificial intelligence model, is deployed instead of a diver to replace the aeration pipe, thereby resolving the problems of risk and economic loss, which is preferable.

[0008] Here, the above abnormal sleep pattern includes multiple abnormal sleep patterns when multiple diffusers are operating abnormally, and the control unit stores the positions of multiple abnormal diffusers corresponding to the multiple abnormal life patterns, and when an area having the above abnormal operation pattern is determined to be caused by the multiple diffusers, the sleep pattern in the images captured by the multiple cameras is compared with the multiple abnormal sleep patterns, and based on the multiple abnormal sleep patterns determined to have a similarity higher than a predetermined degree, the positions of the multiple abnormal diffusers are calculated, so that when multiple diffusers have an abnormality, it is possible to identify a case in which an abnormality has occurred and enable the diffusers to be replaced, which is preferable.

[0009] And the control unit transmits the location information of the plurality of abnormal air vents to the abnormal repair robot to control the plurality of abnormal air vents to be repaired, and when the plurality of air vents repair completion information is received from the abnormal repair robot, the sleep pattern in the images captured by the plurality of cameras is compared with the abnormal operation pattern, the plurality of abnormal sleep patterns, and the normal sleep pattern to confirm the completion of the repair of the plurality of air vents, so that it is preferable to accurately confirm whether the air vent replacement work of the abnormal repair robot has been properly performed.

[0010] According to the present invention, an artificial intelligence model is used to learn whether a digester water surface pattern is a normal operation pattern or an abnormal operation pattern and store the learned pattern. Then, if the water surface pattern is determined to be similar to the abnormal operation pattern in an image taken of the digester water surface, the acid pipe is determined to be abnormal, so that the convenience of the manager and the accuracy of determining the abnormality of the acid pipe can be improved.

[0011] In addition, it is possible to determine an area that does not show a normal operating pattern as an abnormal area of ​​the scattering device and calculate the location information of the scattering device corresponding to the abnormal area, and by replacing the scattering device with an abnormal repair robot that has learned the replacement work of the scattering device through an artificial intelligence model, it is possible to resolve the problem of risk and economic loss by replacing the scattering device.

[0012] In addition, it is possible to identify cases where multiple arbors have malfunctioned so that the arbors can be replaced, and it is possible to accurately confirm whether the arbor replacement work of the abnormal repair robot has been properly performed.

[0013] Figures 1 and 2 are plan views illustrating an abnormality monitoring device for detecting a water surface pattern of a digestion tank according to the present invention, which identifies a water surface pattern of a digestion tank.

[0014] Figures 3 and 4 are side views illustrating the sleep pattern of a digester.

[0015] Figure 5 is an example of multiple ideal repair patterns.

[0016] Figures 6 to 8 are examples of detecting the pressure of a mountain stream according to height using an ideal repair robot.

[0017] Figures 9 to 12 are examples of performing the replacement work of a mountain ridge using an ideal repair robot.

[0018] Figure 13 is a control block diagram of an abnormality monitoring device for detecting a water surface pattern in a digestion tank.

[0019] Hereinafter, with reference to the attached drawings, an abnormality monitoring device (1) of a digestion tank water surface pattern detection device according to a preferred embodiment of the present invention will be described in detail.

[0020] FIGS. 1 and 2 are plan views illustrating an abnormality monitoring device (1) for detecting a water surface pattern of a digester according to the present invention, FIGS. 3 and 4 are side views illustrating an abnormality monitoring device for detecting a water surface pattern of a digester, FIG. 5 is an exemplary view of multiple abnormal operation patterns, FIGS. 6 and 8 are exemplary views illustrating an abnormality monitoring device (1) for detecting a water surface pattern of a digester according to height using an abnormality repair robot (20), FIGS. 9 and 12 are exemplary views illustrating an abnormality monitoring device (1) for detecting a water surface pattern of a digester according to height using an abnormality repair robot (20), and FIGS. 13 is a control block diagram of an abnormality monitoring device (1) for detecting a water surface pattern of a digester according to height.

[0021] Referring to FIGS. 1 to 12, the configuration of an abnormality monitoring device (1) of a digestion tank sleep pattern detection device is described.

[0022] The abnormality monitoring device (1) of the digestion tank sleep pattern detection apparatus includes a camera (10), an abnormality repair robot (20), a communication unit (30), a display unit (40), a user input unit (50), and a control unit (60).

[0023] The camera (10) is a plurality of configurations that photograph the water surface of the digester (2) from multiple directions. The camera (10) includes a first camera (11), a second camera (12), a third camera (13), and a fourth camera (14).

[0024] The first camera (11) photographs the water surface of the digestion tank (2) from the first direction viewed from the upper left area of ​​the digestion tank (2).

[0025] The second camera (12) photographs the water surface of the digester (2) from the first direction looking from the lower left area of ​​the digester (2).

[0026] The third camera (13) photographs the water surface of the digester (2) from the first direction looking at the upper right area of ​​the digester (2).

[0027] The fourth camera (14) photographs the water surface of the digestion tank (2) from the first direction looking from the lower right area of ​​the digestion tank (2).

[0028] The abnormal repair robot (20) can perform repairs including replacement of the oxygen supply pipe (3). The abnormal repair robot (20) includes a robot body (21), an oxygen supply pressure sensor (22), a robot arm (23), and a moving part (24).

[0029] The robot body (21) is a frame that forms the exterior of the robot.

[0030] The oxygen pressure sensor (22) is mounted at the end of the height adjustment arm (231) and can detect the oxygen pressure of the oxygen pipe (3).

[0031] The robot arm (23) includes a height adjustment arm (231) and a repair arm (232).

[0032] The height adjustment arm (231) can be positioned above the air pressure sensor (22) of the air pressure pipe (3), and the height of the air pressure sensor (22) can be arranged to be different.

[0033] The repair rock (232) is configured to be able to connect and release the clamp (4), bolt (5) and nut (6) that are installed to connect the acid pipe (3).

[0034] The moving part (24) is arranged on the lower side of the robot body (21) and is configured to move the robot body (21). The moving part (24) may be formed of wheels and a motor, or may be formed in the shape of a leg made up of a plurality of joints.

[0035] The fluid injection unit (25) can inject fluid toward the blocked air hole (3-1) of the air diffuser (3).

[0036] The communication unit (30) can communicate with the abnormal repair robot (20). The communication unit (30) can perform wireless communication, and the wireless communication includes at least one of infrared communication, RF, Zigbee, and Bluetooth. The communication unit (30) receives a video signal and transmits it to the control unit (60) described later, and can be implemented in various ways corresponding to the standard of the video signal to be received and the implementation form of the user terminal. For example, the communication unit (30) can wirelessly receive an RF (radio frequency) signal transmitted from a broadcasting station (not shown), or can wiredly receive a video signal according to the composite video, component video, super video, SCART, HDMI (high definition multimedia interface) standard, etc. When the video signal is a broadcast signal, the communication unit (30) can include a tuner that tunes the broadcast signal by channel.

[0037] The display unit (40) displays an image based on an image signal processed by image processing. The implementation method of the display unit (40) is not limited, and may be implemented in various display methods such as liquid crystal, plasma, light-emitting diode, organic light-emitting diode, surface conduction electron-emitter, carbon nano-tube, nano-crystal, etc.

[0038] The display unit (40) may additionally include additional components depending on its implementation method. For example, when the display unit (40) is a liquid crystal display, the display unit (40) includes a liquid crystal display panel (not shown), a backlight unit (not shown) for supplying light thereto, and a panel driving board (not shown) for driving the panel (not shown). The display unit (40) may display a voice recognition result as information on the recognized voice. Here, the voice recognition result may be displayed in various forms such as text, graphics, and icons, and the text may include letters and numbers. The display unit (40) may further display candidate commands and application information according to the voice recognition result. The user may check whether the voice has been recognized correctly by the voice recognition result displayed on the display unit (40), and may select a command corresponding to the voice spoken by the user from among the displayed candidate commands by operating the user input unit (50) provided on the remote control, or select and check information related to the voice recognition result.

[0039] The user input unit (50) may be formed by an input means through which a user can input a user command. The user input unit (50) may receive a user's touch input or a user's remote input using a remote controller and transmit the received input to the corresponding control unit (60). In addition, the user input unit (50) may receive a voice input spoken by the user and transmit the voice signal to the control unit (60). In this case, the user input unit (50) may be implemented by, for example, a microphone. The user input unit (50) may also independently perform signal processing on the received voice signal. However, the form of the user input that the user input unit (50) can receive is not limited thereto, and for example, user input through motion recognition, etc. may also be received.

[0040] The control unit (60) uses an artificial intelligence model to store an abnormal water surface pattern in the case of abnormal operation of the aeration system from a plurality of images taken by a plurality of cameras (10) from a plurality of angles of the water surface of the digestion tank (2), and compares the water surface pattern in the images taken by a plurality of cameras (10) using the artificial intelligence model with the abnormal operation pattern. If it is determined that the water surface pattern is higher than a predetermined similarity, it determines that the aeration system (3) is abnormal.

[0041] The control unit (60) uses an artificial intelligence model to store a normal water surface pattern when the aeration pipe (3) is operating normally from images taken from multiple angles of the water surface of the digester (2), and when the aeration pipe (3) is judged to be abnormal, the control unit compares the water surface pattern in images taken from multiple cameras (10) with the normal operation pattern to identify an area having an abnormal operation pattern, and can determine the location of the aeration pipe (3) based on the identified area.

[0042] The control unit (60) can control the communication unit (30) to transmit the location information of the abnormality repair facility (3) and a control signal to repair the abnormality repair facility (3) to the abnormality repair robot (20).

[0043] The control unit (60) stores the positions of a plurality of abnormal diffusers (3) corresponding to a plurality of abnormal life patterns, and when it is determined that an area having an abnormal operation pattern is caused by a plurality of diffusers (3), the control unit (60) compares the sleep patterns in the images captured by the plurality of cameras (10) with the plurality of abnormal sleep patterns, and calculates the positions of the plurality of abnormal sleep patterns (3) based on the plurality of abnormal sleep patterns determined to have a predetermined degree of similarity or higher. The abnormal sleep pattern may include a plurality of abnormal sleep patterns when a plurality of diffusers (3) are abnormally operated.

[0044] The control unit (60) transmits the location information of a plurality of abnormal air vents (3) to the abnormal repair robot (20) to control the repair of the plurality of abnormal air vents (3), and when the repair completion information of the plurality of air vents (3) is received from the abnormal repair robot (20), the sleep pattern in the image captured by the plurality of cameras (10) is compared with the abnormal operation pattern, the plurality of abnormal sleep patterns, and the normal sleep pattern to confirm the completion of the repair of the plurality of air vents (3).

[0045] Figures 1 and 2 are plan views illustrating an abnormality monitoring device for detecting a water surface pattern of a digestion tank according to the present invention, which identifies a water surface pattern of a digestion tank.

[0046] Figure 1 shows a plane of the normal operating pattern for the surface of the digestion tank (2).

[0047] Figure 2 shows a plane of an abnormal operation pattern in area a, unlike the normal operation pattern of Figure 1.

[0048] Figures 3 and 4 are side views illustrating the sleep pattern of a digester.

[0049] Figure 3 shows an aspect of the normal operating pattern for the surface of the digestion tank (2).

[0050] Figure 4 shows the side of the abnormal operation pattern in area a, unlike the normal operation pattern of Figure 1.

[0051] Figure 5 is an example of multiple ideal repair patterns.

[0052] Areas a, b, and c of the digestion tank (2) are abnormal operating patterns with shapes different from the normal operating pattern. This means that the acid pipe (3) corresponding to areas a, b, and c is abnormal.

[0053] Figures 6 to 8 are examples of detecting the air pressure of the air vent (3) according to height using an ideal repair robot (20).

[0054] Figure 6 is an example of a pressure sensor (22) mounted at the end of a height adjustment arm (231) detecting pressure at a first height.

[0055] Figure 7 is an example of a height adjustment arm (231) having its height adjusted so that the position of the acid pressure sensor (22) mounted at the end is placed at a second height higher than the first height and detects acid pressure.

[0056] Figure 8 is an example of a height adjustment arm (231) having its height adjusted so that the position of the acid pressure sensor (22) mounted at the end is placed at a third height higher than the second height and detects acid pressure.

[0057] Figures 9 to 12 are examples of performing the replacement work of a mountaineering equipment (3) using an ideal repair robot (20).

[0058] In Fig. 9, the repair arm (232) is positioned to release the bolt (5) that connects the clamp (4) up and down after moving to the location of the mountain cradle (3) to be replaced by the ideal repair robot (20).

[0059] Fig. 10 shows the clamp (4), bolt (5) and nut (6) separated by being disengaged by the repair arm (232).

[0060] Fig. 11 shows the arrangement for replacing the acid pipe (2) A before replacement with B, and aligning the clamp (4), bolt (5), and nut (6) to the joining position.

[0061] Fig. 12 completes the replacement work by connecting the acid pipe (2) B with the repair rock (232).

[0062] Describes embodiments that can be modified other than the above embodiments.

[0063] The control unit outputs air from the air distribution pipe in response to the temperature and dissolved oxygen content within the digester, stores the normal air pressure range output from the air distribution pipe analyzed using an artificial intelligence model, and determines that there is an abnormality in the air distribution pipe if the air pressure detected by the abnormality repair robot exceeds the normal air pressure range.

[0064] The control unit uses an artificial intelligence model to store a first similarity and a second similarity lower than the first similarity for the abnormal water surface pattern of the digester for determining the abnormality of the aeration pipe when the aeration pipe is operating abnormally, and a plurality of images taken by a plurality of cameras from a plurality of angles of the digester surface, and compares the water surface pattern in the images taken by a plurality of cameras with the abnormal operation pattern, and if the water surface pattern is lower than the first similarity and higher than the second similarity, the location of the aeration pipe is identified based on the area having the abnormal operation pattern higher than the second similarity, and the aeration pipe management robot (20) can be controlled to move to the identified location of the aeration pipe to detect the aeration pressure.

[0065] The control unit stores a first normal oxygen pressure range at a first height above the oxygen pipe, a second normal oxygen pressure range at a second height above the oxygen pipe that is higher than the first height, and a third normal oxygen pressure range at a third height above the oxygen pipe that is higher than the second height. When the first oxygen pressure at the first height detected by the abnormal repair robot is outside the first normal oxygen pressure range, it determines whether the second oxygen pressure at the second height detected by the abnormal repair robot is outside the second normal oxygen pressure range. If it is determined to be outside the range, it determines whether the third oxygen pressure at the third height detected by the abnormal repair robot is outside the third normal oxygen pressure range. If it is determined to be outside the range, it can be determined that there is an abnormality in the corresponding oxygen pipe.

[0066] The control unit can control the abnormality repair robot to move to the location of the identified diffuser, and if the diffuser is determined to be abnormal, control the robot to spray fluid toward the blocked diffuser hole of the diffuser, and then control the robot to detect the diffuser pressure of the diffuser.

[0067] The control unit detects the air pressure of the air diffuser after injecting fluid toward the blocked air hole of the air diffuser, and if it determines that the air diffuser is abnormal, it controls the air diffuser to be repaired. When the air diffuser repair completion information is received from the air diffuser management robot, the control unit detects the air diffuser pressure of the repaired air diffuser and compares the first air diffuser pressure at the first height and the first normal air diffuser pressure range, the second air diffuser pressure at the second height and the second normal air diffuser pressure range, and the third air diffuser pressure at the third height and the third normal air diffuser pressure range to confirm the completion of the repair of the corresponding air diffuser.

[0068] The ideal repair robot may further include a suction unit that sucks fluid from the ventilation hole while in close contact with the ventilation hole to remove foreign substances stuck in the blocked ventilation hole.

[0069] The ideal repair robot is rotatably mounted at the end of the repair arm and may further include a rotating brush for removing foreign substances from the outside of the air diffuser. The control unit can remove foreign substances from the outside of the air diffuser periodically or when the air diffuser is determined to be abnormal.

[0070] The abnormal repair robot is equipped with a position sensor so that when repairing a mountain crater, it can continuously transmit position information to the control unit, and the control unit can store the installation position information of the mountain crater and control the movement of the abnormal repair robot.

[0071] By using the above-mentioned digestion tank sleep pattern detection and aeration device (1), the digestion tank sleep pattern is learned and stored using an artificial intelligence model to determine whether it is a normal operation pattern or an abnormal operation pattern, and if the sleep pattern is determined to be similar to the abnormal operation pattern in an image taken of the digestion tank sleep surface, the aeration device is determined to be abnormal, so the convenience of the manager and the accuracy of determining anomalies in the aeration device can be improved.

[0072] In addition, the area that does not show a normal operation pattern can be judged as an abnormal area of ​​the scattering device, and the location information of the scattering device corresponding to the abnormal area can be calculated. In addition, an abnormal repair robot that has learned about the replacement work of the scattering device through an artificial intelligence model can be deployed instead of a diver to replace the scattering device, thereby solving the problem of risk and economic loss.

[0073] In addition, it is possible to identify cases where multiple sanitation facilities have malfunctioned so that the sanitation facilities can be replaced, and it is possible to accurately confirm whether the sanitation facility replacement work of the abnormality repair robot has been properly performed.

Claims

1. In the abnormality monitoring device of the digestion tank sleep pattern detection apparatus, A plurality of cameras that photograph the water surface of the above digestion tank from multiple directions; and A device for monitoring abnormalities in a digester water surface pattern detection and aeration pipe, characterized in that it includes a control unit that stores an abnormal water surface pattern in a plurality of images taken by a plurality of cameras from a plurality of angles of the digester water surface using an artificial intelligence model when the aeration pipe is operating abnormally, and compares the water surface pattern in the images taken by the plurality of cameras using the artificial intelligence model with the abnormal operation pattern and determines that the aeration pipe is abnormal if it is determined to have a similarity level higher than a predetermined level.

2. In paragraph 1, The above control unit, A device for monitoring abnormalities in a digester water surface pattern detection and aeration pipe, characterized in that the device stores a normal water surface pattern when the aeration pipe is operating normally from images taken from multiple angles of the digester water surface using an artificial intelligence model, compares the water surface pattern in images taken from the multiple cameras with the normal operation pattern when the aeration pipe is determined to be abnormal, identifies an area having the abnormal operation pattern, and determines the location of the abnormal aeration pipe based on the identified area.

3. In paragraph 2, A repair robot that performs repairs including replacement of the above-mentioned ventilation system; and It further includes a communication unit that communicates with the above-mentioned abnormal repair robot, The above control unit, An abnormality monitoring device for detecting a water surface pattern of a digestion tank, characterized in that the communication unit is controlled to transmit location information of the above abnormal water source and a control signal for repairing the above abnormal water source to the above abnormality repair robot.

4. In paragraph 3, The above abnormal sleep pattern includes multiple abnormal sleep patterns when multiple oxygen stimuli are operating abnormally. The above control unit, An abnormality monitoring device for detecting a digestion tank sleep pattern, characterized in that it stores the locations of a plurality of abnormal sleep ducts corresponding to the above-mentioned multiple abnormal life patterns, and when an area having the above-mentioned abnormal operation pattern is determined to be caused by the above-mentioned multiple sleep ducts, it compares the sleep patterns in the images captured by the multiple cameras with the above-mentioned multiple abnormal sleep patterns, and calculates the locations of the above-mentioned multiple abnormal sleep ducts based on the above-mentioned multiple abnormal sleep patterns determined to have a predetermined degree of similarity or higher.

5. In paragraph 4, The above control unit, A device for monitoring abnormalities in a digester sleep pattern detection system, characterized in that it transmits location information of the plurality of abnormal sleep ducts to the abnormality repair robot to control the plurality of abnormal sleep ducts to be repaired, and when information on completion of repair of the plurality of sleep ducts is received from the abnormality repair robot, it compares the sleep pattern in the images captured by the plurality of cameras with the abnormal operation pattern, the plurality of abnormal sleep patterns, and the normal sleep pattern to confirm completion of repair of the plurality of sleep ducts.

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