An intelligent evaluation method for flow velocity and flow rate of municipal drainage pipes

Abstract

The present invention discloses a method for intelligently evaluating the flow velocity and flow rate of a municipal drainage pipeline, and belongs to the field of municipal drainage technology. The system includes an image acquisition module, a device fixing module, a data transmission module, and a data processing module. The image acquisition module is located at the upper part of the inner wall of the drainage pipeline and is connected to the data transmission module via a cable. The data transmission module is located on the wall of a manhole and is connected to the data processing module via wireless transmission. The pipeline flow velocity and flow rate evaluation system of the present invention can monitor the flow velocity and flow rate information in the pipeline for a long time, does not require regular manual detection, reduces the manpower and material resources for monitoring the water flow rate of the pipeline network, improves the monitoring efficiency, and improves the monitoring accuracy of the flow velocity and flow rate by taking the average of multiple groups of monitoring data.

Description

Technical Field

[0001] The present invention relates to the technical field of municipal drainage, and in particular to a method for intelligently evaluating the flow velocity and flow rate of a municipal drainage pipeline. Background Art

[0002] The monitoring of drainage status inside municipal drainage pipes mainly includes the monitoring of flow velocity and flow rate, which is an important link to ensure the normal operation of the drainage network and an important data source for cities facing flood disasters and daily construction. By monitoring the flow velocity and flow rate of drainage pipes, the management efficiency of the drainage network by urban water management departments can be improved, and the city's flood prevention and control capabilities can be improved. Manual methods can be used for more accurate monitoring, but due to the large number and wide distribution of drainage networks, automated internal monitoring methods for drainage pipes are very necessary.

[0003] The existing technologies widely used in the aforementioned fields, methods for monitoring the inside of drainage pipes and their disadvantages are:

[0004] Ultrasonic flow monitoring method, specifically, this method uses the Doppler principle to measure the flow velocity using ultrasound, radio waves, etc., and then combines with a liquid level measurement device to measure the fluid flow. However, there are the following disadvantages: the ultrasonic instrument is installed at the bottom of the drainage pipe and is immersed in water for a long time. The instrument and cable are susceptible to corrosion and scaling. At the same time, the ultrasonic transceiver channel is often blocked by garbage, silt, etc.

[0005] Electromagnetic level meter detection method, specifically, this method uses the principle of electromagnetic induction to measure the flow rate through the pipeline and uses a corresponding device to measure the liquid level to measure the fluid flow. However, there are the following disadvantages: when the water level in the pipeline is too high, the radar level meter is soaked and cannot work normally, and loses its monitoring ability.

[0006] The equivalent calculation method of open channel flowmeter, specifically, this method uses a liquid level meter to detect the liquid level in the pipeline, and establishes a calculation relationship between the liquid level and the flow rate and flow rate under regular sections such as circles and rectangles. The flow rate and flow rate are calculated based on the liquid level. However, there are the following disadvantages: if the pipeline structure is not standardized, and it is affected by sediment scaling, etc., a unified and standardized calculation relationship cannot be established, and the flow rate and flow rate cannot be calculated.

[0007] On the other hand, convolutional neural network technology has been widely used in the field of image recognition in recent years. Convolutional neural network technology is used to obtain information about solid floating objects inside the pipeline, and then intelligently evaluate the flow rate and flow rate of the liquid in the pipeline. This can overcome the shortcomings of the above technologies and monitor the internal status of the drainage pipeline economically and efficiently. Summary of the invention

[0008] The technical problem to be solved by the present invention is to provide a method for intelligently evaluating the flow velocity and flow rate of a municipal drainage pipeline to solve the problems mentioned in the above background technology.

[0009] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0010] A method for intelligently evaluating flow velocity and flow rate in a municipal drainage pipeline, the method comprising an intelligent evaluation system for flow velocity and flow rate in a drainage pipeline, the intelligent evaluation system comprising an image acquisition module, a device fixing module, a data transmission module and a data processing module, the image acquisition module being located at the upper part of the inner wall of the drainage pipeline and connected to the data transmission module via a cable, the data transmission module being located at the wall of a manhole and connected to the data processing module via a wireless transmission mode, the device fixing module being used to fix the image acquisition module, the data transmission module and the cable;

[0011] The image acquisition module is used to acquire image information inside the drainage pipe;

[0012] The data transmission module is used to transmit the image information obtained by the image acquisition module to the data processing module in a wireless manner;

[0013] The data processing module is used to control the working state of the image acquisition module, and to perform intelligent recognition and analysis on the image information transmitted by the data transmission module, and to perform intelligent evaluation on the flow and velocity information of the drainage pipe;

[0014] The data processing module includes a working control unit and an identification and evaluation unit. The working control unit sends a signal to the data transmission module in a wireless transmission mode. The signal is transmitted to the image acquisition module through a cable to control the working state of the image acquisition module. The identification and evaluation unit is used to identify and analyze the internal image information of the drainage pipe transmitted by the data transmission module, and to perform intelligent evaluation on the flow velocity and flow information of the drainage pipe.

[0015] The recognition and evaluation unit adopts image convolution neural network recognition technology to identify solid floating objects such as plastic bottles, branches, and leaves inside the drainage pipe according to the internal image information of the pipe transmitted by the image acquisition module, and evaluates the height h and movement distance s of the solid floating objects;

[0016] The water level in the pipe is h w , the calculation formula is: Where n is the total number of solid floating objects identified, h i ,h k is the height of the solid floating object at the time of two image acquisitions;

[0017] The average speed v of the solid floating object s The calculation formula is:

[0018] Among them, S i is the movement distance of the solid floating object along the pipeline axis when two images are collected, t is the time interval between the two sets of image information collection, and t is 0.5s;

[0019] According to the average speed v of the solid floating object movement s Calculate the surface velocity v of the liquid in the pipe w ;

[0020] The surface velocity v of the liquid in the pipe w , the calculation formula is:

[0021] Where m is the mass of the floating solids, θ is the slope of the drainage pipe, and B is the viscosity coefficient. Since the mass m of the floating solids in the pipe is small, the slope θ of the drainage pipe is 5‰-35‰, and the slope is also small, so the surface velocity v of the liquid in the pipe w The average velocity v of the solid floating object s Basically the same, that is, v w ≈v s

[0022] The image acquisition module works based on an infrared camera, which is used to collect image information inside the drainage pipe. The infrared camera has a waterproof function, which can prevent the normal operation of the infrared camera from being affected by the high water level in the drainage pipe. The infrared camera has a rotation function, which can collect image information from all directions inside the drainage pipe.

[0023] The data transmission module includes a power supply unit and a communication unit. The power supply unit is used to supply power to the image acquisition module and the communication unit. The communication unit is used to transmit the image information acquired by the image acquisition module to the data processing module.

[0024] The data transmission module has a waterproof function, the power supply unit is powered by a lithium battery, the communication unit transmits signals by wireless transmission, the device fixing module includes a fixing support, a cable fixing device and a camera fixing clamp, the fixing support is used to fix the data transmission module, the cable fixing device is used to fix the cable used to connect the data transmission module and the image acquisition module, and the camera fixing clamp is used to fix the image acquisition module without affecting the rotation function of the infrared camera.

[0025] The working control unit sets a cycle to control the opening and closing of the image acquisition module, sends a working signal and a sleep signal, thereby controlling the image acquisition module to switch between the working state and the sleep state according to the set cycle. After the image acquisition module enters the working state, it collects two sets of image information.

[0026] According to the surface velocity v of the liquid in the pipeline w Estimate the equivalent flow velocity v inside the drainage pipe d , the flow velocity variation trend of the cross section in the pipe is:

[0027] As the water level in the pipe increases, the flow rate increases. When the water level in the pipe is r, the flow rate reaches the maximum value.

[0028] The water level in the pipe continues to increase and the flow rate decreases;

[0029] Therefore, when the water level in the pipe is h w ≤r, where r is the pipe radius, take v d =0.7v w ;

[0030] When the water level in the pipe is h w >r, take v d =0.9v w ;

[0031] According to the water level, calculate the pipeline flow Q = v d ×A, where A is the water flow cross-sectional area;

[0032] The water flow cross-sectional area A is: Where d is the pipe diameter and θ is the filling angle;

[0033] The filling angle θ is:

[0034] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0035] 1. The present invention provides a method for intelligently evaluating the velocity and flow rate of a municipal drainage pipeline. Through ingenious design and the use of a fixed detection method, water level, flow rate, mud level and other detection equipment are installed at the pipe well location.

[0036] 2. The present invention provides a method for intelligently evaluating the flow velocity and flow rate of a municipal drainage pipeline. The pipeline flow velocity and flow rate evaluation system can monitor the flow velocity and flow rate information in the pipeline for a long time without the need for regular manual inspection, thereby reducing the manpower and material resources for monitoring the water flow rate in the pipeline network and improving the monitoring efficiency. By taking the average of multiple groups of monitoring data, the monitoring accuracy of the flow velocity and flow rate is improved.

[0037] 3. The present invention provides a method for intelligently evaluating the flow velocity and flow rate of municipal drainage pipes. The intelligent evaluation system for the flow velocity and flow rate of drainage pipes can be used in urban drainage pipe networks, such as rainwater pipes and sewage pipes, to collect image information in the pipes, evaluate the flow velocity and flow rate information in the pipes through a data processing module, collect and evaluate the rainwater information and sewage information in the city, and report the information to a monitoring center to monitor rainwater and sewage discharge in a timely manner. By optimizing the scheduling of sewage treatment plants and manual cleaning, urban waterlogging caused by factors such as heavy rainfall or garbage blockage in pipes can be avoided, and economic losses caused by improper sewage treatment can be reduced. It can also be used for flow monitoring of rivers and channels, and provide support for flood control and drainage, river hydrological monitoring, and irrigation area information collection.

[0038] 4. The present invention provides a method for intelligently evaluating the flow velocity and flow rate of a municipal drainage pipeline. The intelligent evaluation system for the flow velocity and flow rate of the drainage pipeline can be used to monitor the total drainage volume of each section of the pipeline, optimize the design of the pipe section with a larger drainage load, and reduce its drainage load by increasing the number of pipes, increasing the pipe diameter, changing the laying method, etc. It can also determine whether someone is secretly discharging sewage based on the flow monitoring between upstream and downstream, especially by monitoring the flow changes in adjacent pipe sections to obtain the approximate location of the secretly discharged sewage.

[0039] 5. The present invention provides a method for intelligently evaluating the flow velocity and flow rate of a municipal drainage pipeline. By utilizing the image information obtained by the image acquisition module, it can also be used to monitor whether the pipeline has defects and deformation, monitor whether there is leakage, monitor whether there is garbage blockage, and perform repairs and cleaning in a timely manner to avoid quicksand and soil from rushing into the pipeline and prevent ground collapse and garbage from clogging the drainage pipeline. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of a method and device for intelligently evaluating the flow velocity and flow rate of a municipal drainage pipeline in the present invention;

[0041] Figure 2 It is a simplified flow chart of the intelligent evaluation method for flow velocity and flow rate of municipal drainage pipelines in the present invention;

[0042] Figure 3 It is a detailed flow chart of the intelligent evaluation method for flow velocity and flow rate of municipal drainage pipelines in the present invention;

[0043] Figure 4 It is a schematic diagram of the force on the solid floating objects in the drainage pipe of the present invention;

[0044] Figure 5 The flow velocity distribution diagram along the height direction at the same cross section of the drainage pipe in the present invention;

[0045] Figure 6 It is a schematic cross-sectional view of the drainage pipe in the present invention;

[0046] Figure 7 This is a flow chart of the convolutional neural network image recognition and evaluation of the data processing module in the present invention.

[0047] In the figure, 1 is the ground, 10 is the image acquisition module, 11 is the infrared camera, 2 is the manhole cover, 20 is the device fixing module, 21 is the fixed support, 22 is the cable fixing device, 23 is the camera fixing clamp, 3 is the manhole wall, 30 is the data transmission module, 31 is the power supply unit, 32 is the communication unit, 4 is the drainage pipe, 40 is the data processing module, 41 is the work control unit, 42 is the identification and evaluation unit, 421 is the data input layer, 422 is the middle layer, 423 is the full link layer, 5 is the water level, 6 is the cable, and 7 is the solid floating object. DETAILED DESCRIPTION

[0048] The present invention is described in detail below in conjunction with the accompanying drawings and specific implementation cases. The following examples will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, without departing from the concept of the present invention, several variations and improvements can also be made, which all belong to the protection scope of the present invention.

[0049] Example 1

[0050] like Figure 1 - Figure 7 As shown, the present invention provides a method for intelligently evaluating flow velocity and flow rate of a municipal drainage pipeline, including an image acquisition module 10, a device fixing module 20, a data transmission module 30 and a data processing module 40.

[0051] The image acquisition module 10 is located at the upper part of the inner wall of the drainage pipe 4 and is connected to the data transmission module 30 via a cable 6. It is used to collect image information inside the drainage pipe 4 and works based on the infrared camera 11, wherein the infrared camera 11 is used to collect image information inside the drainage pipe 4.

[0052] The infrared camera 11 has a waterproof function, which can prevent the normal operation of the infrared camera 11 from being affected by the excessively high water level in the drainage pipe 4; the infrared camera 11 has a rotation function, which can collect image information from all directions inside the drainage pipe 4. There are often many solid floating objects in the drainage pipe, which are easily entangled on the image acquisition module when flowing on the water surface with the sewage, covering and blocking the infrared camera 11, affecting the camera's normal collection of image information inside the drainage pipe.

[0053] When the image acquisition module 10 is in a dormant state, the infrared camera 11 rotates to the same direction as the water flow. Solid floating objects are not easily entangled in the infrared camera 11 under the action of the water flow. At the same time, the scouring of the surface of the infrared camera 11 by water flow, silt and other debris is reduced, thereby protecting the image acquisition module 10.

[0054] The housing of the image acquisition module 10 is made of 5A06 aluminum, and its surface is hard anodized, so it can adapt to the humid working environment in the drainage pipe, withstand sewage corrosion, and effectively extend the service life of the infrared camera 11.

[0055] The data transmission module 30 includes a power supply unit 31, which uses a lithium battery as an energy source. A lithium battery is a type of battery that uses lithium metal or lithium alloy as a negative electrode material and a non-aqueous electrolyte solution. A lithium battery has the advantages of high energy density, long service life, and strong environmental adaptability. It is green and environmentally friendly. Even if the battery is damaged in the drainage pipe, it will not produce any toxic and harmful heavy metals such as lead, mercury, and fluorine.

[0056] like Figure 1 As shown, the recognition and evaluation unit 42 adopts image convolution neural network recognition technology to identify solid floating objects such as plastic bottles, branches, leaves, etc. inside the drainage pipe according to the internal image information of the pipe transmitted by the image acquisition module 10, and evaluates the height h and movement distance s of the solid floating objects.

[0057] like Figure 4 As shown in the figure, assuming that the pipeline inclination angle is α, the solid floating object in the pipeline is acted upon by three forces, namely: gravity G, buoyancy f, and the force F exerted on it by the liquid along the liquid surface. The motion equation of the solid floating object in the x direction is: The calculated liquid surface velocity is

[0058] like Figure 5 The figure shows the liquid velocity distribution in the pipeline, v w is the liquid surface velocity, v d is the equivalent flow velocity inside the drainage pipe, r is the pipe radius;

[0059] When the water level in the pipe is h w ≤r, the surface velocity of the liquid is the maximum velocity along the height direction of the same cross section, so v is taken d =0.7v w ; When the water level in the pipe is h w >r, as the liquid level increases, the surface velocity decreases, so v d =0.9v w .

[0060] like Figure 6 As shown, the water level in the pipe is h wCalculate the full angle The cross-sectional area of ​​water is obtained by the filling angle θ and the pipe diameter d Pipeline flow rate Q = v d ×A.

[0061] Example 2

[0062] The present invention provides a method for evaluating the flow velocity and flow rate of a municipal drainage pipeline based on the intelligent evaluation system of the first embodiment. The method for evaluating the flow velocity and flow rate of a municipal drainage pipeline adopts the following steps:

[0063] Step L1: The data processing module 40 sets a cycle to control the opening and closing of the image acquisition module 10. When the data processing module 40 sends a working signal I, the image acquisition module 10 enters the working state and transmits the collected internal image information of the drainage pipe 4 to the data processing module 40 through the data transmission module 30. The data processing module 40 identifies and evaluates the internal image of the drainage pipe 4 to obtain the pipe flow velocity v w and flow rate Q value; record flow velocity v w After the flow Q value is determined, the data processing module 40 sends a sleep signal, and the image acquisition module 10 enters a sleep state. The working signal I is sent once every 1 hour.

[0064] Step L2: If the pipeline flow velocity v cannot be estimated due to factors such as too few solid floating objects in the pipeline or inability to identify the solid floating objects after identification and evaluation by the data processing module 40, w and the flow rate Q value, then 1 minute later, the data processing module 40 sends a working signal II to control the image acquisition module 10 to collect the image information inside the drainage pipe 4 again, and the image information is transmitted to the data processing module 40 through the data transmission module 30, and the data processing module 40 evaluates the flow rate v of the drainage pipe 4 again. w If the evaluation is still not possible, send the working signal II again after 1 minute and repeat the above steps until the pipeline flow velocity v can be evaluated. w The working signal II is sent up to 3 times in a row. If the pipeline flow velocity v cannot be evaluated, w With the flow Q value, the data processing module 40 sends a sleep signal, and the image acquisition module 10 enters a sleep state.

[0065] Steps L1 and L2 are performed cyclically to continuously monitor the flow velocity and flow information in the pipeline.

[0066] The recognition and evaluation unit 42 is used to recognize and analyze the image information of the interior of the drainage pipe 4 transmitted by the data transmission module 30 .

[0067] More specifically, the recognition and evaluation unit 42 adopts image convolution neural network recognition technology. The convolution neural network used in the recognition and evaluation unit 42 has been modified by a large number of machine learning and back propagation algorithms, and can recognize common solid floating objects inside pipelines, such as plastic bottles, branches, leaves, etc. The recognition and evaluation unit 42 consists of a data input layer 421, an intermediate layer 422, and a full-link layer 423. The image information is input by the data input layer 421, and after operations such as de-averaging, the data is passed to the intermediate layer 422; the intermediate layer 422 performs convolution, pooling, excitation, etc. on the data to obtain a feature array, and passes the feature array to the full-link layer 423; the full-link layer 423 operates the feature array weights of the image information to obtain the information of solid floating objects inside the pipeline, and records the height and movement distance information of all solid floating objects collected in two images, and evaluates the flow velocity and flow in the pipeline through data processing.

[0068] The drainage pipe velocity and flow intelligent assessment system in the example of the present invention can be used in urban drainage pipe networks, such as rainwater pipes and sewage pipes, to collect image information in the pipes, evaluate the flow velocity and flow information in the pipes through the data processing module 40, collect and evaluate the city's rainwater information and sewage information, and report the information to the monitoring center, so as to timely monitor the discharge of rainwater and sewage, avoid urban waterlogging caused by factors such as heavy rainfall or garbage blockage inside the pipes through optimizing the scheduling of sewage treatment plants and manual cleaning, and reduce economic losses caused by improper sewage treatment. It can also be used for flow monitoring of rivers and channels, and provide support for flood control and drainage, river hydrological monitoring and irrigation area information collection.

[0069] The drainage pipe flow velocity and flow intelligent assessment system in the example of the present invention can be used to monitor the total drainage volume of each section of the pipe, optimize the design of the pipe section with a larger drainage load, and reduce its drainage load by increasing the number of pipes, increasing the pipe diameter, changing the laying method, etc. It can also determine whether someone is secretly discharging sewage based on the flow monitoring between upstream and downstream, especially by monitoring the flow changes in adjacent pipe sections to obtain the approximate location of the secretly discharged sewage.

[0070] In addition, the image information obtained by the image acquisition module 10 in the example of the present invention can also be used to monitor whether there are defects and deformations in the pipeline, monitor whether there is leakage, monitor whether there is garbage blockage, and perform repairs and cleaning in a timely manner to avoid quicksand and soil from rushing into the pipeline and prevent ground collapse and garbage from clogging the drainage pipeline.

[0071] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for intelligently evaluating flow velocity and flow rate of a municipal drainage pipeline, the method comprising an intelligent evaluation system for flow velocity and flow rate of a drainage pipeline, the intelligent evaluation system comprising an image acquisition module (10), a device fixing module (20), a data transmission module (30) and a data processing module (40), characterized in that: The image acquisition module (10) is located on the upper part of the inner wall of the drainage pipe (4) and is connected to the data transmission module (30) via a cable (6); the data transmission module (30) is located on the wall of the manhole (3) and is connected to the data processing module (40) via a wireless transmission method; the device fixing module (20) is used to fix the image acquisition module (10), the data transmission module (30) and the cable (6); The image acquisition module (10) is used to acquire image information inside the drainage pipe (4); The data transmission module (30) is used to transmit the image information obtained by the image acquisition module (10) to the data processing module (40) in a wireless manner; The data processing module (40) is used to control the working state of the image acquisition module (10), and to perform intelligent recognition and analysis on the image information transmitted by the data transmission module (30), and to perform intelligent evaluation on the flow rate and flow velocity information of the drainage pipe (4); The data processing module (40) comprises a working control unit (41) and an identification and evaluation unit (42); the working control unit (41) sends a signal to the data transmission module (30) in a wireless transmission manner; the signal is transmitted to the image acquisition module (10) via a cable (6) to control the working state of the image acquisition module (10); the identification and evaluation unit (42) is used to identify and analyze the internal image information of the drainage pipe (4) transmitted by the data transmission module (30), and to perform intelligent evaluation on the flow velocity and flow rate information of the drainage pipe (4); The recognition and evaluation unit (42) uses image convolution neural network recognition technology to identify solid floating objects (7) such as plastic bottles, branches, and leaves inside the drainage pipe (4) based on the internal image information of the pipe transmitted by the image acquisition module (10), and evaluates the height h and movement distance s of the solid floating objects (7); The water level (5) in the pipeline is h w , the calculation formula is: Where n is the total number of solid floating objects (7) identified, h i ,h k is the height of the solid floating object (7) at the time of two image acquisitions; The average speed v of the solid floating object (7) is s The calculation formula is: Among them, S i is the movement distance of the solid floating object (7) along the pipeline axis when two images are collected, t is the time interval between the two sets of image information collection, and t is 0.5s; According to the average speed v of the solid floating object (7) s Calculate the surface velocity v of the liquid in the pipe w ; The surface velocity v of the liquid in the pipe w , the calculation formula is: Where m is the mass of the solid floating object (7), θ is the slope of the drainage pipe (4), and B is the viscosity coefficient. Since the mass m of the solid floating object (7) in the pipe is small, the slope θ of the drainage pipe (4) is 5‰-35‰, and the slope is also small, the surface velocity v of the liquid in the pipe is w The average velocity v of the solid floating object (7) s Basically the same, that is, v w ≈v s .

2. According to claim 1, a method for intelligently evaluating flow velocity and flow rate of a municipal drainage pipeline is characterized by: The image acquisition module (10) operates based on an infrared camera (11). The infrared camera (11) is used to collect image information from inside the drainage pipe (4). The infrared camera (11) has a waterproof function, which can prevent the normal operation of the infrared camera (11) from being affected by the excessively high water level (5) in the drainage pipe (4). The infrared camera (11) has a rotation function, which can collect image information from all directions inside the drainage pipe (4).

3. A method for intelligently evaluating flow velocity and flow rate of a municipal drainage pipeline according to claim 2, characterized in that: The data transmission module (30) comprises a power supply unit (31) and a communication unit (32); the power supply unit (31) is used to supply power to the image acquisition module (10) and the communication unit (32); and the communication unit (32) is used to transmit image information acquired by the image acquisition module (10) to the data processing module (40).

4. A method for intelligently evaluating flow velocity and flow rate of a municipal drainage pipeline according to claim 3, characterized in that: The data transmission module (30) has a waterproof function, the power supply unit (31) is powered by a lithium battery, the communication unit (32) performs signal transmission by wireless transmission, the device fixing module (20) comprises a fixing support (21), a cable (6) fixing device (22) and a camera fixing clamp seat (23), the fixing support (21) is used to fix the data transmission module, the cable (6) fixing device (22) is used to fix the cable (6) used to connect the data transmission module (30) and the image acquisition module (10), and the camera fixing clamp seat (23) is used to fix the image acquisition module (10) without affecting the rotation function of the infrared camera (11).

5. A method for intelligently evaluating flow velocity and flow rate of a municipal drainage pipeline according to claim 4, characterized in that: The working control unit (41) sets a cycle to control the opening and closing of the image acquisition module (10), and sends a working signal and a sleep signal, thereby controlling the image acquisition module (10) to switch between a working state and a sleep state according to the set cycle. After the image acquisition module (10) enters the working state, it acquires two sets of image information.

6. The method for intelligently evaluating flow velocity and flow rate of a municipal drainage pipeline according to claim 1, characterized in that: According to the surface velocity v of the liquid in the pipeline w Estimate the equivalent flow velocity v inside the drainage pipe (4) d , the flow velocity variation trend of the cross section in the pipe is: As the height of the water level (5) in the pipe increases, the flow velocity increases, and when the height of the water level (5) in the pipe is r, the flow velocity reaches a maximum value; The water level (5) in the pipe continues to increase, and the flow rate decreases; Therefore, when the water level (5) in the pipe is h w ≤r, where r is the pipe radius, take v d =0.7v w ; When the water level (5) in the pipe is h w >r, take v d =0.9v w .

7. The method for intelligently evaluating flow velocity and flow rate of a municipal drainage pipeline according to claim 1, characterized in that: According to the water level (5), calculate the pipeline flow rate Q = v d ×A, where A is the water flow cross-sectional area; The water flow cross-sectional area A is: Where d is the pipe diameter and θ is the filling angle; The filling angle θ is:

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