An open channel / underflow pipe flow monitoring system and method with self-cleaning function

Abstract

This invention belongs to the field of water resource management technology, specifically relating to a flow monitoring system and method for open channels / partially full pipes with self-cleaning function. It includes a self-cleaning flow metering sensor, a controller, and a host computer. The self-cleaning flow metering sensor is communicatively connected to the controller, and the controller is communicatively connected to the host computer. The self-cleaning flow metering sensor is used to collect real-time flow velocity data, real-time water level data, and real-time water quality data in open channels / partially full pipes, and performs self-cleaning operations in response to control commands. This invention effectively counteracts the interference of water temperature and water quality changes on flow velocity and flow rate measurement by calibrating ultrasonic velocity with real-time water temperature, combined with multi-channel weighted average flow velocity calculation, cross-sectional fitting parameters, and water temperature and turbidity correction coefficients, significantly reducing data errors. Simultaneously, dynamic self-cleaning promptly removes deposits on the sensor surface, avoiding signal attenuation and data distortion caused by contamination, and improving the accuracy of flow measurement during long-term operation.

Description

Technical Field

[0001] This invention belongs to the field of water resource management technology, specifically relating to a flow monitoring system and method for open channels / non-full pipes with self-cleaning function. Background Technology

[0002] In fields such as water conservancy, urban drainage, industrial wastewater, and agricultural irrigation, flow monitoring in open channels or non-full pipes is a crucial link in water resource management and process control, but its technical implementation faces numerous challenges. Traditional flow monitoring equipment, such as contact mechanical flow meters, is prone to decreased measurement accuracy due to the adhesion of impurities such as silt and algae in the water, and requires frequent manual cleaning and maintenance, increasing operation and maintenance costs. While non-contact monitoring solutions (such as radar flow measurement) reduce the risk of sensor contamination, they are susceptible to interference from environmental factors (such as wind) and lack stability in complex cross-sections or scenarios with variable water quality.

[0003] Existing technologies include some flow monitoring devices with self-cleaning functions, such as sensors that use high-pressure gas purging or simple timed flushing. However, these solutions mostly rely on fixed-cycle cleaning modes and lack the ability to judge the actual degree of contamination of the sensors in real time. This results in cleaning operations being either too frequent (increasing energy consumption and equipment wear) or having a delayed response (affecting data accuracy). In addition, traditional self-cleaning systems do not consider the dynamic changes in water quality parameters (such as turbidity and pollutant type) and cannot adopt differentiated cleaning strategies for different pollution mechanisms such as sediment deposition and biofilm adhesion. As a result, it is still difficult to maintain stable measurement accuracy in long-term operation.

[0004] On the other hand, existing monitoring systems are inadequate in terms of data integration and intelligent control. Most devices only achieve basic data acquisition and transmission, and have not established pollution assessment models based on multiple parameters (such as flow rate, water temperature, and turbidity). They also cannot dynamically optimize cleaning frequency, intensity, and methods through adaptive algorithms, which makes the system less adaptable to complex application scenarios (such as high-turbidity rivers and algae-proliferating channels). Summary of the Invention

[0005] To address the aforementioned shortcomings of the prior art, this invention provides a flow monitoring system, method, and storage medium for open channels / partially full pipes with self-cleaning function.

[0006] In a first aspect, the present invention provides a flow monitoring system for open channels / partially full pipes with self-cleaning function, comprising a self-cleaning flow metering sensor, a controller, and a host computer; the self-cleaning flow metering sensor is communicatively connected to the controller, and the controller is communicatively connected to the host computer; the self-cleaning flow metering sensor is used to collect real-time flow velocity data, real-time water level data, and real-time water quality data in open channels / partially full pipes, and performs self-cleaning operations in response to control commands; the controller includes a communication module, a storage unit, and a computing unit, used to receive real-time data, calculate flow data, assess the degree of pollution, dynamically adjust self-cleaning parameters, and generate control commands through the computing unit; the host computer is used to display various types of data, configure self-cleaning reference parameters, receive operating status information uploaded by the controller, and support remote control.

[0007] Further improvements to this technical solution include a self-cleaning flow metering sensor comprising an outer protective housing, an inner support housing, a monitoring component, and a self-cleaning functional module. The outer protective housing is cylindrical with a flange connection at one axial end for sealing and fixing to the side wall of the open channel / partially full pipe to be monitored. The other axial end of the outer protective housing is an open end with an internal threaded connection on its inner side. The inner support housing is disc-shaped with an external threaded connection on its outer periphery that mates with the internal threaded connection. The inner support housing is screwed onto the open end of the outer protective housing for a detachable sealed connection. The end face of the inner support housing facing the interior of the open channel / partially full pipe is defined as the monitoring mounting surface. The central area of ​​the monitoring mounting surface is the monitoring component mounting area. Several self-cleaning functional mounting ports are evenly distributed circumferentially on the outer protective housing around the monitoring component mounting area. The outer protective housing and the inner support housing together form a sealed electrical chamber for housing the electrical connection lines of the monitoring component and the self-cleaning functional module.

[0008] Further improvements to this technical solution include that the monitoring components include an ultrasonic flow velocity sensor, a pressure level module, and a water quality monitoring unit; the ultrasonic flow velocity sensor includes several sets of ultrasonic transducer pairs, each set of ultrasonic transducer pairs includes a transmitting transducer and a receiving transducer, the transmitting and receiving transducers are arranged diagonally on both sides of the monitoring component installation area, their detection surfaces are flush with or protrude from the monitoring installation surface, and face the direction of water flow inside the open channel / non-full pipe; the pressure level module is embedded in the geometric center of the monitoring component installation area, the pressure sensing diaphragm of the pressure level module is flush with and sealed to the monitoring installation surface, and is used to directly withstand water pressure; The water quality monitoring unit is integrated on one side of the monitoring component installation area, including a turbidity sensor probe, a water temperature sensor probe, and a pollutant type identification probe. The detection end of each sensor probe is flush with the monitoring installation surface. The self-cleaning module includes a medium-frequency ultrasonic cleaning component and a high-pressure water rinsing component, which are alternately arranged in their respective cleaning function installation ports. The medium-frequency ultrasonic cleaning component includes an ultrasonic generator and an ultrasonic transmission block. The ultrasonic generator is fixedly installed in the electrical chamber, and its vibration output end is tightly coupled to the inner end face of the ultrasonic transmission block. The ultrasonic transmission block is sealed and embedded in the self-cleaning function installation port, and its outer end face is flush with or protrudes from the monitoring installation surface. The outer end face of the ultrasonic transmission block is tilted towards the installation area of ​​the monitoring component, so that the ultrasonic vibration energy is focused on the detection surface area of ​​the monitoring component. The high-pressure water flushing assembly includes a high-pressure nozzle, a water delivery channel, and a high-pressure water supply interface. The high-pressure nozzle is sealed and installed in the self-cleaning function mounting port, with its spray nozzle flush with or protruding from the monitoring mounting surface, and the spray nozzle is tilted towards the monitoring assembly mounting area. The water delivery channel is located inside the inner support shell, connecting the high-pressure nozzle to the high-pressure water supply interface located in the electrical chamber. The high-pressure water supply interface is connected to an external water storage tank or an external water supply system via a flexible high-pressure pipeline. Secondly, the present invention provides a method for monitoring the flow of open channels / non-full pipes with self-cleaning function, applicable to the open channel flow monitoring system with self-cleaning function described in any of the above claims, the method comprising: S1. The self-cleaning flow metering sensor collects real-time flow velocity, real-time water level data, and water quality data including turbidity, water temperature, and pollutant type in open channels / non-full pipes through multi-channel synchronous acquisition, and sends the data to the controller in a package. S2. The controller calculates the current ultrasonic velocity based on the real-time water temperature and calibrates the real-time flow velocity data of a single channel by combining the pre-stored standard sound velocity deviation coefficient. S3. The controller calculates the flow rate data of open channel / non-full pipe based on real-time water level data, preset cross-sectional fitting parameters and calibrated weighted average flow velocity, combined with water temperature and turbidity correction coefficients. S4. The controller calculates the ultrasonic signal attenuation rate, flow velocity fluctuation coefficient and water level fluctuation coefficient, dynamically allocates weights according to pollutant type, and comprehensively evaluates the degree of sensor contamination. S5. The controller calculates the biofilm thickness on the sensor by combining turbidity, weighted average flow rate and cumulative time since the last cleaning, and dynamically adjusts the frequency, power, pressure and time parameters of the self-cleaning function module based on the measured flow data of open channel / non-full pipe, pollution level and calculated biofilm thickness. S6. The controller generates adaptive control commands based on dynamically adjusted parameters and sends them to the self-cleaning function module to perform cleaning operations; it also records cleaning parameters, monitoring data before and after cleaning, and uploads them to the host computer.

[0009] Further improvements to this technical solution include step S1, which includes: S11, Response time of ultrasonic flow velocity sensor based on self-cleaning flow metering sensor Set the data sampling frequency , Simultaneously, the effective water level range for open channels / partially full pipes is preset. ; S12, Ultrasonic flow velocity sensor according to sampling frequency Raw flow velocity data was collected simultaneously through n audio channels. The pressure water level module collects raw water level data at preset time intervals. The water quality monitoring unit simultaneously collects turbidity data. Water temperature and pollutant types ; S13. Perform moving average noise reduction processing on the raw flow velocity data: ; in, This is the preprocessed monochannel flow velocity data; N is the sliding window length; data exceeding the limit are removed from the original water level data. After identifying outliers, the average value is calculated as the water level data: ; in, This provides real-time water level data. This is the effective water level data format; S14, after pretreatment Water quality data The data is packaged according to a preset data frame format and sent to the controller via the communication link between the self-cleaning flow metering sensor and the controller.

[0010] Further improvements to this technical solution include step S2, which includes: S21. The controller extracts the real-time water temperature from the data packaged in step S1. The ultrasonic velocity in the current environment is calculated based on a nonlinear correlation formula between water temperature and ultrasonic velocity. ; in, The ultrasonic velocity corresponding to the current water temperature; S22. The controller retrieves the standard ultrasonic velocity at standard water temperature pre-stored in the storage unit. Calculate the sound speed deviation coefficient to quantify the difference between the current sound speed and the standard sound speed: ; in, This is the sound speed deviation coefficient; S23. The controller calls the preprocessed monochannel flow velocity raw data from step S1 and performs linear calibration on it using the sound velocity deviation coefficient: ; in, This is the calibrated monochannel flow rate data.

[0011] Further improvements to this technical solution include step S3, which includes: S31, The controller retrieves the preset channel flow rate weighting coefficients from the storage unit. Combined with the monochannel flow rate data calibrated in step S2 Calculate the weighted average flow velocity : ; S32. The controller calls the real-time water level data h collected in step S1 and the pre-stored cross-section fitting parameters. The cross-sectional area of ​​the water passage is calculated by integrating the fitting formula for the cross-sectional width: ; ; in, Water level The cross-sectional width at that location; This refers to the cross-sectional area of ​​the water passage. S33. The controller extracts the real-time water temperature θ and turbidity T from step S1 and calculates the flow correction coefficient. : ; S34, The controller combines the weighted average flow rate from step S31. The cross-sectional area of ​​the water passage in step S32 and the flow correction coefficient in step S33 Calculate real-time flow data for open channels / non-full pipes : .

[0012] Further improvements to this technical solution include step S4, which includes: S41. The controller retrieves the initial ultrasonic signal strength of the sensor pre-stored in the storage unit. Extract the current ultrasonic signal intensity in step S1 Monophonic flow rate data after step S2 calibration and the water level sampling data collected in step S1 within the preset time period. Simultaneously, obtain the pollutant types identified in step S1. ; S42. Calculate the ultrasonic signal attenuation rate. : ; Calculate the velocity fluctuation coefficient : ; Calculate the water level fluctuation coefficient : ; in, This is the average water level over a preset time period. ; S43. Dynamically allocate the weights of each coefficient according to the type of pollutant. And combined with the ultrasonic signal attenuation rate calculated in step S42 Flow velocity fluctuation coefficient and water level fluctuation coefficient Comprehensive assessment of pollution levels : ; in, Slight pollution. Moderate pollution. It is severely polluted.

[0013] Further improvements to this technical solution include step 5, which includes: S51, The controller extracts the real-time turbidity T from step S1 and the weighted average flow rate from step S3. Flow velocity fluctuation coefficient in step S4 Retrieve the cumulative time since the last cleaning recorded in the storage unit. Preset initial thickness of biofilm and adhesion coefficient Calculate biofilm thickness : ; S52. Real-time flow data of open channels / non-full pipes calculated based on step S3 The pollution level P in step S4 and the biofilm thickness δ in step S51 are determined by a preset reference ultrasonic frequency. Turbidity Influence Coefficient Pollution level influence coefficient Biofilm thickness influence coefficient and thickness threshold Adjust the ultrasonic frequency : ; S53. Combining the pollution level P from step S4, the biofilm thickness δ from step S51, and the real-time water temperature θ from step S1, preset the baseline cleaning power. Pollution level and power coefficient Biofilm thickness power coefficient and water temperature correction factor Adjust the cleaning power of the ultrasonic generator : ; S54. Based on the pollution level P in step S4 and the real-time flow data of the open channel / non-full pipe calculated in step S3. and the weighted average flow rate in step S3 and preset baseline flushing pressure Pollution level and pressure coefficient Turbidity pressure coefficient and flow velocity influence coefficient Adjust the high-pressure water pressure : ; S55. Combining the contamination level P from step S4, the biofilm thickness δ from step S51, and the contaminant type C from step S1, a preset baseline cleaning time is determined. Pollution Degree Duration Coefficient Biofilm thickness duration factor Pollutant type coefficient Define the correction function Adjust cleaning time : .

[0014] Further improvements to this technical solution include step 6, which includes: S61, The controller retrieves the contamination level P from step S4 and the ultrasonic frequency f and cleaning power after dynamic adjustment in step S5. Flushing pressure and cleaning time Determine the cleaning mode based on the degree of contamination: If Then select the high-pressure water flushing mode. Then select the single mode according to the pollutant type in step S1. Then select the combination mode; S62. The controller encapsulates the cleaning mode, adjusted self-cleaning parameters, and execution timing into standardized control instructions. S63. The controller sends standardized control commands to the self-cleaning function module of the self-cleaning flow metering sensor through its 4G / 5G dual-mode communication module. The module responds to the command and starts the corresponding cleaning component to perform the cleaning operation. S64. During the cleaning process, the controller synchronously records the cleaning start time. End time The actual execution parameters and real-time monitoring data before and after cleaning are verified through a data integrity formula. Validate the data validity, among which, To effectively record the number of data entries, This represents the total number of records to be recorded. S65. After the verification is successful, the controller stores the above-mentioned recorded data in its storage unit and simultaneously uploads it to the host computer via the communication module with encryption. The host computer's display unit displays the data, and the storage and forwarding unit archives and manages it.

[0015] The beneficial effects of this invention are as follows: This invention calibrates ultrasonic velocity in real time by water temperature, and combines this with multi-channel weighted average flow velocity calculation, cross-sectional fitting parameters, and water temperature and turbidity correction coefficients to effectively counteract the interference of water temperature and water quality changes on flow velocity and flow rate measurement, significantly reducing data errors. Simultaneously, dynamic self-cleaning promptly removes deposits from the sensor surface, avoiding signal attenuation and data distortion caused by contamination, thus improving the accuracy of flow rate measurement during long-term operation.

[0016] The system abandons the fixed-cycle cleaning mode and comprehensively assesses the degree of pollution by using ultrasonic signal attenuation rate and flow velocity / water level fluctuation coefficient. Combined with water quality parameters (turbidity, pollutant type) and biofilm thickness calculation results, it dynamically adjusts the cleaning frequency, power, pressure, and duration. High-pressure water flushing is used for sediment deposition, ultrasonic cleaning is used for algae adhesion, and a combined mode is used for heavy pollution, which improves cleaning efficiency, avoids energy waste and equipment wear caused by over-cleaning, and prevents cleaning lag from affecting monitoring accuracy.

[0017] The controller integrates a computing unit to continuously optimize pollution assessment weights and cleaning parameters based on historical data, adapting to dynamic changes in water quality and flow rate. During the cleaning process, pre- and post-cleaning monitoring data and operational parameters are recorded synchronously. After data integrity verification, the data is encrypted, stored, and uploaded to ensure traceability and prevent data loss. The host computer supports remote configuration and status monitoring, achieving an intelligent closed-loop monitoring and management system that meets the digital needs of refined water resource management. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic block diagram of a system according to an embodiment of the present invention.

[0020] Figure 2 This is a layout diagram of the monitoring system on site.

[0021] Figure 3 This is a schematic diagram of the structure of a self-cleaning flow metering sensor.

[0022] Figure 4 This is a schematic flowchart illustrating a method according to an embodiment of the present invention.

[0023] 110 is a self-cleaning flow metering sensor, 111 is an outer protective housing, 1111 is a self-cleaning function mounting port, 112 is a monitoring component, 1121 is an ultrasonic flow velocity sensor, 1122 is a pressure water level module, 1123 is a water quality monitoring unit, 113 is a self-cleaning function module, 1131 is a medium-frequency ultrasonic cleaning component, 1132 is a high-pressure water flushing component, 114 is an inner support housing, 1141 is a monitoring mounting surface, 120 is a control box, 121 is a controller, 130 is a solar panel, and 140 is an external water storage tank. Detailed Implementation

[0024] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the specific embodiments. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0026] like Figure 1 As shown, this invention provides a flow monitoring system for open channels / partially filled pipes with self-cleaning function, including a self-cleaning flow metering sensor 110, a controller 121, and a host computer. The self-cleaning flow metering sensor 110 is communicatively connected to the controller 121, and the controller 121 is communicatively connected to the host computer. The self-cleaning flow metering sensor 110 is used to collect real-time flow velocity data, real-time water level data, and real-time water quality data in open channels / partially filled pipes, and performs self-cleaning operations in response to control commands. The controller 121 includes a communication module, a storage unit, and a computing unit, used to receive real-time data, calculate flow data, assess the degree of pollution, dynamically adjust self-cleaning parameters, and generate control commands through the computing unit. The host computer is used to display various data, configure self-cleaning reference parameters, receive operating status information uploaded by the controller 121, and support remote control.

[0027] like Figure 2 As shown, a control box 120 is configured on the outside of the controller 121. A power module that supplies power to the entire system is installed inside the control box 120. A solar panel 130 connected to the power module is installed outside the control box 120.

[0028] like Figure 3 As shown, the self-cleaning flow metering sensor 110 includes an outer protective housing 111, an inner support housing 114, a monitoring component 112, and a self-cleaning function module 113. The outer protective housing 111 has a cylindrical structure with a flange connection at one axial end for sealing and fixing to the side wall of the open channel / non-full pipe to be monitored. The other axial end of the outer protective housing 111 is an open end with an internal thread connection on its inner side. The inner support housing 114 has a disc-shaped structure with an external thread connection on its outer periphery that mates with the internal thread connection. The inner support housing 114 is connected by a threaded connection. The sealing is installed at the open end of the outer protective housing 111 to form a detachable sealed connection; the end face of the inner support housing 114 facing the interior of the open channel / non-full pipe is defined as the monitoring mounting surface 1141, the central area of ​​the monitoring mounting surface 1141 is the monitoring component installation area, and a number of self-cleaning function installation ports 1111 are evenly distributed around the outer protective housing 111 on the outer periphery of the monitoring component installation area; the outer protective housing 111 and the inner support housing 114 together form a sealed electrical chamber for accommodating the electrical connection lines of the monitoring component 112 and the self-cleaning function module 113.

[0029] Specifically, the monitoring component 112 includes an ultrasonic flow velocity sensor 1121, a pressure and water level module 1122, and a water quality monitoring unit 1123. The ultrasonic flow velocity sensor 1121 includes several pairs of ultrasonic transducers, each pair including a transmitting transducer and a receiving transducer. The transmitting and receiving transducers are arranged diagonally on both sides of the monitoring component installation area, and their detection surfaces are flush with or protrude from the monitoring installation surface 1141, facing the direction of water flow inside the open channel / non-full pipe. The pressure and water level module 1122 is embedded at the geometric center of the monitoring component installation area. The pressure sensing diaphragm of the pressure and water level module 1122 is flush with and sealed to the monitoring installation surface 1141 to directly withstand water pressure. The water quality monitoring unit 1123 is integrated on one side of the monitoring component installation area and includes a turbidity sensing probe, a water temperature sensing probe, and a pollutant type identification probe. The detection ends of each sensing probe are flush with the monitoring installation surface 1141. The self-cleaning module 113 includes a medium-frequency ultrasonic cleaning component 1131 and a high-pressure water flushing component 1132, which are alternately arranged in their respective cleaning function mounting ports 1111. The medium-frequency ultrasonic cleaning component 1131 includes an ultrasonic generator and an ultrasonic transmission block. The ultrasonic generator is fixedly installed in the electrical chamber, and its vibration output end is tightly coupled to the inner end face of the ultrasonic transmission block. The ultrasonic transmission block is sealed and embedded in the self-cleaning function mounting port 1111, and its outer end face is flush with or protrudes from the monitoring mounting surface 1141, with the outer end face of the ultrasonic transmission block facing the monitoring component mounting area. The tilted design focuses the ultrasonic vibration energy onto the detection surface area of ​​the monitoring component 112. The high-pressure water flushing component 1132 includes a high-pressure nozzle, a water delivery channel, and a high-pressure water supply interface. The high-pressure nozzle is sealed and installed in the self-cleaning function mounting port 1111, with its nozzle flush with or protruding from the monitoring mounting surface 1141, and the nozzle tilted towards the monitoring component mounting area. The water delivery channel is located inside the inner support housing 114, connecting the high-pressure nozzle to the high-pressure water supply interface located in the electrical chamber. The high-pressure water supply interface is connected to the external water storage tank 140 or an external water supply system via a flexible high-pressure pipeline.

[0030] The ultrasonic generator and high-pressure nozzle are arranged alternately and evenly around the circumference of the monitoring component installation area, with the central angle θ between adjacent units being 30°-60°, forming a ring-shaped cleaning array around the monitoring component 112. The difference in protrusion height Δh between the outer end face of the ultrasonic transducer and the nozzle of the high-pressure nozzle relative to the monitoring mounting surface 1141 is no greater than 2mm, ensuring that both are in consistent contact with the water. The center line of the outer end face of the ultrasonic transducer and the center line of the nozzle of the high-pressure nozzle intersect spatially at a point 5-15mm in front of the geometric center of the monitoring component installation area, forming an energy convergence point and enhancing the cleaning effect on the detection surface of the monitoring component 112. The monitoring mounting surface 1141 of the inner support shell 114 is provided with an annular guide groove, which is located between the monitoring component installation area and the self-cleaning function installation port. This groove is used to collect the cleaned wastewater and guide it to the outer periphery for discharge, avoiding secondary pollution of the monitoring area.

[0031] The ultrasonic output end of the ultrasonic generator and the water outlet end of the high-pressure nozzle are both facing the monitoring component 112. The self-cleaning function module 113 outputs ultrasonic waves and high-pressure water of corresponding frequency and power according to the control command to clean the monitoring component 112. The 1121 ultrasonic flow velocity sensor features a multi-channel installation design. The number of channels (n) can be flexibly configured according to the cross-sectional width of open channels / partially filled pipes (typically 2-4 channels). The channel spacing is 0.5-1.0m, and the installation angle is 30°-45° to the water flow direction, ensuring comprehensive flow velocity acquisition. The core component of the sensor uses a high-precision ultrasonic transducer with an operating frequency of 1-5MHz, a measurement range of 0.01-10m / s, a measurement error ≤±1.0%, and a response time τ≤10ms, enabling rapid capture of changes in water flow velocity.

[0032] Pressure level module 1122: The appropriate pressure-sensitive element is selected based on the water quality scenario. For clear water channels, a ceramic piezoresistive type is used; for industrial wastewater pipelines, a corrosion-resistant single-crystal silicon resonant type is used; and for rivers with high sediment content, a diffused silicon piezoresistive type is used. The module's measurement range is 0.01-10m, with a measurement error ≤ ±0.5% FS. The sampling interval can be set from 1 to 5 seconds via controller 121. The collected water pressure signal is directly converted into water depth data after A / D conversion.

[0033] Water quality monitoring unit 1123: Turbidity sensor: adopts the principle of light scattering, with a measurement range of 0-1000 NTU, measurement error ≤ ±2% FS, response time ≤ 5s, and real-time output of water turbidity data T; Water temperature sensor: PT100 platinum resistance thermometer is selected, with a measurement range of 0-40℃ and a measurement accuracy of ±0.1℃. The sampling interval is consistent with that of the pressure and water level module 1122. Pollutant type identification module: Based on spectral analysis technology, it integrates visible light and near-infrared spectral sensors. By detecting the absorption and reflection characteristics of water bodies to different wavelengths of light, it identifies pollutant type C (1-sediment, 2-algae, 3-others), with an identification accuracy of ≥90% and a data output cycle of 10s / time.

[0034] Self-cleaning function module 113: Medium-frequency ultrasonic cleaning component 1131: The ultrasonic generator can output a continuously adjustable frequency signal of 20-80kHz, with a power range of 50-200W. The cleaning wave emission holes (i.e., the mounting port 1111 corresponding to the ultrasonic generator) (diameter 5-8mm) are evenly distributed around the periphery of the monitoring area, and the distance between the ultrasonic flow velocity sensor 1121 and the detection surface of the pressure water level module 1122 is ≤30mm to ensure concentrated cleaning energy. High-pressure water flushing component 1132: It has a built-in micro high-pressure water pump, and the water supply method is a built-in water storage chamber (volume ≥500mL) or an external water pipe. The flushing pressure can be adjusted within the range of 0.5-2.0MPa. The flushing nozzle is a fan-shaped spray design that covers all detection surfaces of the sensor. The nozzle orifice diameter is 1-2mm. Combined cleaning mode: The timing of ultrasonic cleaning and high-pressure water rinsing is coordinated through the preset logic of controller 121. The default interval is 5 seconds, which can be flexibly adjusted through the host computer.

[0035] Ultrasonic generator: It adopts a full-bridge inverter circuit design, supports independent adjustment of frequency and power, and has an output signal distortion of ≤5%. It is connected to the ultrasonic cleaning component and ultrasonic flow sensor 1121 through a shielded cable with a cable length of ≤1.5m to avoid signal interference.

[0036] Communication Module: Employs a 4G / 5G dual-mode transmission module (e.g., Huawei ME909s-821), backward compatible with 2G / 3G networks, supports TCP / IP protocol, data transmission rate ≥1Mbps, and features data encryption (using AES-128 encryption algorithm). The module connects to the self-cleaning flow metering sensor 110 via an RS485 interface and communicates with the host computer via Ethernet or 4G / 5G network. The communication link is stable and reliable; data can be cached during network outages and automatically retransmitted upon network reconnection.

[0037] Storage Unit: Utilizes industrial-grade SD cards (capacity ≥ 32GB) or NAND Flash (capacity ≥ 64GB), supporting at least one year of historical data storage. Stored content includes real-time flow rate, water level, water quality data, pollution level assessment results, self-cleaning parameters, and cleaning records. Data is stored in CSV format, organized into folders by "year-month-day" for easy retrieval and export.

[0038] Computational Unit: Employs an embedded processor based on the ARM Cortex-A9 architecture (e.g., STM32F7 series), with a clock speed ≥1GHz, and floating-point arithmetic capabilities, enabling rapid processing of multi-parameter data calculations and model computations. The computational unit includes a pre-defined cross-sectional fitting parameter library, a cleanliness baseline parameter library, and a multi-parameter self-learning model for "flow rate-turbidity-temperature-biofilm thickness," supporting online parameter updates and iterative model optimization.

[0039] The host computer consists of hardware devices and software systems, and the specific implementation is as follows: Hardware Equipment: The management host can be an industrial-grade server (suitable for centralized management of multiple water intakes), a laptop (suitable for on-site commissioning), or a tablet (suitable for mobile inspection). The minimum configuration requirements are: CPU frequency ≥ 2.0GHz, memory ≥ 8GB, hard disk ≥ 500GB, and it must have an Ethernet interface and 4G / 5G module expansion capabilities. The display unit should be a ≥ 19-inch LCD screen with a resolution ≥ 1920×1080, supporting touch operation.

[0040] Software System: The control software is developed based on the Windows or Linux operating system, written in C++, and has the following functional modules: Data display module: Real-time display of data such as flow rate, water level, flow velocity, turbidity, water temperature, pollutant type, pollution level, and biofilm thickness at each monitoring point, supporting both curve charts and digital panel display modes; Parameter configuration module: Allows remote setting of self-cleaning baseline parameters (baseline frequency f0, baseline power P_c0, baseline pressure P_w0, baseline duration t0), cross-sectional fitting parameters (a_h, b_h, c_h), weighting coefficients (ω1, ω2, ω3), and contamination level thresholds (0.3, 0.7), etc. Control command module: Supports manual sending of cleaning mode switching commands and emergency cleaning commands, and allows setting automatic cleaning trigger conditions; Data management module: Supports historical data query, export (formats include CSV, Excel), and printing, and has a data anomaly alarm function (alarm methods include sound prompts, pop-up prompts, and SMS push notifications); Status monitoring module: Displays the real-time operating status of sensors and controller 121, including power status, communication status, and cleaning component working status, and automatically records fault information when abnormalities occur.

[0041] The self-cleaning flow metering sensor 110 is connected to the controller 121 via a shielded cable (including power supply positive and negative terminals and signal transmission line). The controller 121 is connected to the host computer via a 4G / 5G network or wired Ethernet. The wireless communication distance is unlimited in unobstructed environments, and the maximum wired communication distance is ≤100m (using Cat5e network cable). All connection interfaces use waterproof aviation plugs, which are easy to plug and unplug and have a design to prevent misplugging.

[0042] Overall system workflow: Data acquisition phase: The self-cleaning flow metering sensor 110 synchronously acquires data according to preset parameters, and the ultrasonic flow velocity sensor 1121 acquires data according to the sampling frequency f. s (10-50Hz) Raw flow velocity data is collected through n channels. Pressure level module 1122 collects water level data at 1-5s intervals. Water quality monitoring unit 1123 collects turbidity, water temperature and pollutant type data simultaneously. All raw data are pre-processed (noise reduction and outlier removal) inside the sensor, packaged in a preset data frame format and sent to controller 121 through communication link.

[0043] Data processing and evaluation stage: After receiving the data, the controller 121 first corrects the ultrasonic velocity based on the water temperature data and calibrates the flow velocity data; then, it calculates the cross-sectional area of ​​the water passage by combining the water level data and the cross-sectional fitting parameters, and calculates the flow rate by incorporating the water temperature and turbidity correction coefficients; subsequently, it comprehensively evaluates the degree of pollution by using the ultrasonic signal attenuation rate, flow velocity fluctuation coefficient, and water level fluctuation coefficient, and calculates the biofilm thickness by combining turbidity, flow velocity, and cumulative cleaning time; finally, it dynamically adjusts the self-cleaning parameters (frequency, power, pressure, and duration) based on the water quality data, degree of pollution, and biofilm thickness.

[0044] Self-cleaning execution phase: The controller 121 determines the cleaning mode (high-pressure water rinsing, ultrasonic cleaning, combined cleaning) based on the adjusted self-cleaning parameters and the degree of contamination, generates standardized control commands and sends them to the self-cleaning function module 113 of the self-cleaning flow metering sensor 110. The module responds to the commands and starts the corresponding cleaning components to perform the operation, and provides real-time feedback on the working status during the cleaning process.

[0045] Data recording and uploading phase: Controller 121 synchronously records the cleaning start time, end time, actual execution parameters, and monitoring data before and after cleaning. After data integrity verification, it is stored in the local storage unit and simultaneously encrypted and uploaded to the host computer. The host computer completes data display, archiving, and management.

[0046] Figure 4 This is a schematic flowchart illustrating a method according to an embodiment of the present invention. Wherein, Figure 4 The implementing entity can be a flow monitoring system for open channels / partially full pipes with self-cleaning capabilities. Depending on the specific requirements, the order of steps in this flowchart can be changed, and some steps can be omitted.

[0047] like Figure 4 As shown, the method includes: S1. The self-cleaning flow metering sensor collects real-time flow velocity, real-time water level data, and water quality data including turbidity, water temperature, and pollutant type in open channels / non-full pipes through multi-channel synchronous acquisition, and sends the data to the controller in a package. S2. The controller calculates the current ultrasonic velocity based on the real-time water temperature and calibrates the real-time flow velocity data of a single channel by combining the pre-stored standard sound velocity deviation coefficient. S3. The controller calculates the flow rate data of open channel / non-full pipe based on real-time water level data, preset cross-sectional fitting parameters and calibrated weighted average flow velocity, combined with water temperature and turbidity correction coefficients. S4. The controller calculates the ultrasonic signal attenuation rate, flow velocity fluctuation coefficient and water level fluctuation coefficient, dynamically allocates weights according to pollutant type, and comprehensively evaluates the degree of sensor contamination. S5. The controller calculates the biofilm thickness on the sensor by combining turbidity, weighted average flow rate and cumulative time since the last cleaning, and dynamically adjusts the frequency, power, pressure and time parameters of the self-cleaning function module based on the measured flow data of open channel / non-full pipe, pollution level and calculated biofilm thickness. S6. The controller generates adaptive control commands based on dynamically adjusted parameters and sends them to the self-cleaning function module to perform cleaning operations; it also records cleaning parameters, monitoring data before and after cleaning, and uploads them to the host computer.

[0048] To facilitate understanding of the present invention, the following description further illustrates the flow monitoring method for open channels / partially full pipes with self-cleaning function provided by the present invention, based on the principle of the method and the process of monitoring the flow of open channels / partially full pipes using a self-cleaning system in the embodiments.

[0049] First, step S1 includes: S11, Response time of ultrasonic flow velocity sensor based on self-cleaning flow metering sensor Set the data sampling frequency , Simultaneously, the effective water level range for open channels / partially full pipes is preset. ; S12, Ultrasonic flow velocity sensor according to sampling frequency Raw flow velocity data was collected simultaneously through n audio channels. The pressure water level module collects raw water level data at preset time intervals. The water quality monitoring unit simultaneously collects turbidity data. Water temperature and pollutant types (Values: 1 - Sediment, 2 - Algae, 3 - Other); S13. Perform moving average noise reduction processing on the raw flow velocity data: ; in, This is the preprocessed monochannel flow velocity data; N is the sliding window length; data exceeding the limit are removed from the original water level data. After identifying outliers, the average value is calculated as the water level data: ; in, This provides real-time water level data. This is the effective water level data format; S14, after pretreatment Water quality data The data is packaged according to a preset data frame format and sent to the controller via the communication link between the self-cleaning flow metering sensor and the controller.

[0050] Secondly, step S2 includes: S21. The controller extracts the real-time water temperature from the data packaged in step S1. The ultrasonic velocity in the current environment is calculated based on a nonlinear correlation formula between water temperature and ultrasonic velocity. ; in, The ultrasonic velocity corresponding to the current water temperature; S22. The controller retrieves the standard ultrasonic velocity at standard water temperature pre-stored in the storage unit. Calculate the sound speed deviation coefficient to quantify the difference between the current sound speed and the standard sound speed: ; in, The sound velocity deviation coefficient reflects the degree to which changes in water temperature affect the propagation speed of ultrasonic waves. S23. The controller calls the preprocessed mono-channel flow velocity raw data from step S1 and uses the sound velocity deviation coefficient to perform linear calibration, eliminating the flow velocity measurement error caused by water temperature. ; in, This is the calibrated monochannel flow rate data.

[0051] S21 uses a nonlinear correlation formula between water temperature and ultrasonic velocity to calculate the current sound velocity. Compared to a linear approximation formula, this more accurately reflects the change in sound velocity within the commonly monitored water temperature range of 0-40℃, avoiding sound velocity estimation errors caused by water temperature fluctuations and providing reliable basic data for subsequent flow velocity calibration. S22 calculates the deviation coefficient by comparing the current sound velocity with the standard sound velocity, transforming the influence of water temperature on sound velocity into an intuitive and quantifiable parameter. This allows the controller to clearly determine the degree of interference from water temperature changes on flow velocity measurement, providing a clear quantitative basis for flow velocity calibration and avoiding blind corrections. S23 uses the sound velocity deviation coefficient to perform linear calibration on the pre-processed raw flow velocity data, accurately offsetting the impact of differences in ultrasonic propagation speed caused by water temperature changes on flow velocity measurement, effectively correcting flow velocity data deviations, and making the calibrated single-channel flow velocity data more closely match the actual water flow velocity.

[0052] In addition, step S3 includes: S31, The controller retrieves the preset channel flow rate weighting coefficients from the storage unit. Combined with the monochannel flow rate data calibrated in step S2 Calculate the weighted average flow velocity : ; S32. The controller calls the real-time water level data h collected in step S1 and the pre-stored cross-section fitting parameters. The cross-sectional area of ​​the water passage is calculated by integrating the fitting formula for the cross-sectional width: ; ; in, Water level The cross-sectional width at that location; This refers to the cross-sectional area of ​​the water passage. S33. The controller extracts the real-time water temperature θ and turbidity T from step S1 and calculates the flow correction coefficient. To compensate for water temperature and turbidity: ; S34, The controller combines the weighted average flow rate from step S31. The cross-sectional area of ​​the water passage in step S32 and the flow correction coefficient in step S33 Calculate real-time flow data for open channels / non-full pipes : .

[0053] S31 calls the preset weighting coefficients for each channel and combines them with the accurate flow velocity data calibrated in S2 to calculate the weighted average flow velocity. This fully considers the differences in flow velocity distribution across the cross-section for different channels, avoiding the bias of single-channel data. This makes the average flow velocity more closely match the actual water flow conditions of open channels / partially filled pipes, providing reliable core parameters for flow measurement. S32, based on real-time water level data and pre-stored cross-sectional fitting parameters, obtains the cross-sectional area through integration calculations. This eliminates the need for real-time on-site measurement of the cross-sectional width, adapting to different shapes of open channels / partially filled pipes (e.g., rectangular, trapezoidal, irregular cross-sections) while avoiding errors and tedious manual measurement, ensuring a high degree of match between the area data and actual operating conditions. S33 extracts the real-time water temperature and turbidity from S1 and calculates correction coefficients using quantitative formulas. This specifically compensates for the indirect impact of water temperature changes and turbidity on flow measurement, solving the error problem caused by neglecting environmental parameters in traditional flow measurement and further improving the stability of flow data. The S34 system calculates the final flow rate by combining the weighted average flow velocity, cross-sectional area, and flow correction coefficient, forming a complete logical chain of "flow velocity calibration - area calculation - environmental compensation - comprehensive calculation". This ensures that the flow rate data can accurately reflect the actual water flow in open channels / non-full pipes, providing high-quality data support for subsequent sensor pollution assessment and dynamic adjustment of self-cleaning parameters, and guaranteeing the reliability of the core functions of the entire monitoring system.

[0054] Next, step S4 includes: S41. The controller retrieves the initial ultrasonic signal strength of the sensor pre-stored in the storage unit. Extract the current ultrasonic signal intensity in step S1 Monophonic flow rate data after step S2 calibration and the water level sampling data collected in step S1 within the preset time period. Simultaneously, obtain the pollutant types identified in step S1. ; S42. Calculate the ultrasonic signal attenuation rate. To reflect the impact of contaminants adhering to the sensor surface on the signal: ; Calculate the velocity fluctuation coefficient : ; Calculate the water level fluctuation coefficient : ; in, This is the average water level over a preset time period. ; S43. Dynamically allocate the weights of each coefficient according to the type of pollutant. And combined with the ultrasonic signal attenuation rate calculated in step S42 Flow velocity fluctuation coefficient and water level fluctuation coefficient Comprehensive assessment of pollution levels : ; in, Slight pollution. Moderate pollution. It is severely polluted.

[0055] S41 retrieves the initial ultrasonic signal intensity from the sensor, extracts multiple key data points after preprocessing in S1 and calibration in S2, and associates them with the pollutant types identified in S1. This ensures that all data required for pollution assessment comes from the high-quality processing results of previous steps, avoiding data gaps or interference from invalid data, and providing complete data support for accurate assessment. S42 directly reflects the weakening effect of pollutant adhesion on the sensor's detection signal through the ultrasonic signal attenuation rate, and indirectly reflects the decrease in measurement stability caused by pollution through the flow velocity fluctuation coefficient and water level fluctuation coefficient. These three indicators quantify the pollution status from both direct and indirect perspectives, avoiding the one-sidedness of single-indicator assessments and making pollution quantifiable and traceable. S43 dynamically adjusts the weights of the three assessment indicators based on pollutant type (silt, algae, others), fully considering the differences in the impact mechanisms of different pollutants on the sensor (e.g., algae are more likely to cause signal attenuation, while silt may exacerbate flow velocity fluctuations). This ensures that the weight allocation is highly matched to the actual pollution scenario, significantly improving the targeting and accuracy of pollution degree assessment. S43 calculates a quantitative value of the degree of pollution through a comprehensive formula and classifies it into light, moderate and heavy pollution levels. This transforms the abstract state of pollution into a clear classification result, providing an intuitive and actionable basis for subsequent dynamic adjustment of self-cleaning parameters in S5 and selection of cleaning modes in S6. This ensures that cleaning operations are accurately matched with the degree of pollution and avoids insufficient or excessive cleaning.

[0056] Additionally, step 5 includes: S51, The controller extracts the real-time turbidity T from step S1 and the weighted average flow rate from step S3. Flow velocity fluctuation coefficient in step S4 Retrieve the cumulative time since the last cleaning recorded in the storage unit. Preset initial thickness of biofilm and adhesion coefficient Calculate biofilm thickness : ; S52. Real-time flow data of open channels / non-full pipes calculated based on step S3 The pollution level P in step S4 and the biofilm thickness δ in step S51 are determined by a preset reference ultrasonic frequency. Turbidity Influence Coefficient Pollution level influence coefficient Biofilm thickness influence coefficient and thickness threshold Adjust the ultrasonic frequency : ; S53. Combining the pollution level P from step S4, the biofilm thickness δ from step S51, and the real-time water temperature θ from step S1, preset the baseline cleaning power. Pollution level and power coefficient Biofilm thickness power coefficient and water temperature correction factor Adjust the cleaning power of the ultrasonic generator : ; S54. Based on the pollution level P in step S4 and the real-time flow data of the open channel / non-full pipe calculated in step S3. and the weighted average flow rate in step S3 and preset baseline flushing pressure Pollution level and pressure coefficient Turbidity pressure coefficient and flow velocity influence coefficient Adjust the high-pressure water pressure : ; S55. Combining the contamination level P from step S4, the biofilm thickness δ from step S51, and the contaminant type C from step S1, a preset baseline cleaning time is determined. Pollution Degree Duration Coefficient Biofilm thickness duration factor Pollutant type coefficient Define the correction function Adjust cleaning time : .

[0057] S51 integrates the turbidity of S1, the weighted average flow rate of S3, the flow rate fluctuation coefficient of S4, and the stored cumulative cleaning time. It calculates the biofilm thickness using a quantitative formula, transforming the abstract state of contamination adhesion into a concrete and measurable physical quantity. This avoids the problems of insufficient or excessive cleaning caused by traditional cleaning strategies' inability to perceive biofilm thickness, providing a core basis for subsequent cleaning parameter adjustments. S52 to S55 establish logical connections between the four core cleaning parameters—ultrasonic frequency, cleaning power, high-pressure water pressure, and cleaning time—and key data from previous steps. Ultrasonic frequency is correlated with turbidity, contamination level, and biofilm thickness; cleaning power is correlated with contamination level, biofilm thickness, and water temperature; high-pressure water pressure is correlated with contamination level, turbidity, and flow rate; and cleaning time is correlated with contamination level, biofilm thickness, and contaminant type. Adjustments to each parameter are based on multi-dimensional actual operating data, avoiding poor cleaning effects caused by single parameters or fixed values, ensuring a high degree of matching between cleaning parameters and contamination status and water quality environment. The S5's parameter adjustment logic fully considers the differences in pollutant type, water quality conditions, and water flow state: for the characteristic of significant biofilm adhesion in algal pollution, the adjustment of ultrasonic frequency and cleaning time is enhanced by the biofilm thickness coefficient; for the characteristic of flow velocity affecting deposition in silt pollution, the flow velocity parameter is incorporated into the high-pressure water pressure adjustment; and the cleaning power is optimized by combining the influence of water temperature on cleaning efficiency, so that the cleaning strategy can flexibly adapt to different complex scenarios such as high turbidity, algal growth, and silt deposition, thereby improving the system's environmental adaptability.

[0058] By precisely quantifying the degree of contamination and biofilm thickness, S5 dynamically adjusts the intensity and duration of cleaning parameters—reducing cleaning power and shortening time for light contamination, and specifically increasing key parameters for heavy contamination. This avoids the ineffective energy consumption waste of traditional fixed-parameter cleaning modes, while reducing unnecessary wear and tear caused by excessive equipment operation. It extends the lifespan of cleaning components and reduces system operating costs while ensuring cleaning effectiveness. The ultrasonic frequency, cleaning power, high-pressure water pressure, and cleaning duration output by S5 directly serve as the core basis for executing the S6 cleaning mode; their accuracy determines the effectiveness of the cleaning operation. Through scientific parameter adjustment, it ensures that contaminants (silt, algae, biofilm) on the sensor detection surface are fully removed, avoiding a decrease in measurement accuracy due to residual contaminants. This, in turn, ensures the long-term stable operation of the entire monitoring system's core functions such as flow measurement and contamination assessment.

[0059] Finally, step 6 includes: S61, The controller retrieves the contamination level P from step S4 and the ultrasonic frequency f and cleaning power after dynamic adjustment in step S5. Flushing pressure and cleaning time Determine the cleaning mode based on the degree of contamination: If Then select the high-pressure water flushing mode. Then select the single mode according to the pollutant type in step S1. Then select the combination mode; S62. The controller encapsulates the cleaning mode, adjusted self-cleaning parameters and execution timing into standardized control instructions. The instruction format meets the communication protocol requirements between the self-cleaning flow metering sensor and the controller. S63. The controller sends standardized control commands to the self-cleaning function module of the self-cleaning flow metering sensor through its 4G / 5G dual-mode communication module (backward compatible with 2G / 3G). The module responds to the command and starts the corresponding cleaning component (ultrasonic generator or high-pressure water device) to perform the cleaning operation. S64. During the cleaning process, the controller synchronously records the cleaning start time. End time Actual execution parameters ( , The data includes real-time monitoring data before and after cleaning, verified using a data integrity verification formula. Validate the data validity, among which, To effectively record the number of data entries, This represents the total number of records to be recorded. S65. After the verification is successful, the controller stores the above-mentioned recorded data in its storage unit and simultaneously uploads it to the host computer via the communication module with encryption. The host computer's display unit displays the data, and the storage and forwarding unit archives and manages it.

[0060] Data Retrieval and Verification: The controller retrieves the quantified pollution level value P (range 0-1) calculated in step S4 from the computing unit cache via the internal data bus. Simultaneously, it extracts the complete set of self-cleaning parameters dynamically adjusted in step S5, including ultrasonic frequency f (20-80kHz), cleaning power P_c (50-200W), high-pressure water flushing pressure P_w (0.5-2.0MPa), and cleaning duration t (10-120s). Simultaneously, it reads the pollutant type C (1-silt, 2-algae, 3-others) identified and stored in step S1 from the storage unit and verifies the integrity of all retrieved data (no missing data, no outliers outside reasonable ranges) through data verification logic, ensuring the reliability of the decision-making basis.

[0061] Pollution level classification: The controller has built-in classification logic, which determines the pollution level by comparing P with preset thresholds (0.3, 0.7). When P < 0.3, it is judged as slightly contaminated. At this time, the contaminants on the sensor surface are mainly a small amount of floating dust and slight mud and sand, and no high-intensity cleaning is required. When 0.3≤P<0.7, it is judged as moderate pollution, with obvious pollutant deposits or initial biofilm adhesion on the sensor surface, requiring a specific single cleaning mode; When P ≥ 0.7, it is judged as heavily polluted, and a thick layer of pollutants or a dense biofilm has formed on the sensor detection surface. The cleaning effect of a single mode is limited, and a combination of modes is required to enhance cleaning.

[0062] Cleaning mode adaptive selection: For lightly contaminated scenarios (P < 0.3): the high-pressure water rinsing mode is always selected because this mode has high cleaning efficiency and low energy consumption for lightly loose contaminants, and can avoid unnecessary wear from ultrasonic cleaning. In this case, the high-pressure water rinsing pressure is the same as the P_w adjusted in step S5, and the cleaning time is shortened by 30% according to the light contamination rule (t_light = t × 0.7). Moderate pollution scenario (0.3 ≤ P < 0.7): Dynamically select a single mode based on pollutant type C: When C=1 (sediment), select the high-pressure water flushing mode to quickly remove the deposited sediment using the impact force of the water flow, which is suitable for the characteristics of large sediment particles and weak adhesion. When C=2 (algae), select the ultrasonic cleaning mode. The medium-frequency ultrasonic vibration will destroy the cell wall and biofilm adhesion of algae, which is suitable for the strong adhesiveness and easy adhesion of algae. When C=3 (other), a random number generation algorithm is used to select one of the two single modes to ensure adaptability to unknown types of pollutants; In heavily polluted scenarios (P≥0.7): The "ultrasonic cleaning + high-pressure water rinsing" combination mode is always selected. The execution sequence is as follows: first, ultrasonic cleaning is started (the parameters f, P_c, t are used as adjusted in step S5). After cleaning, there is a 5-second interval (a preset fixed interval to ensure that there is a buffer time after the pollutants are removed). Then, high-pressure water rinsing is started. At this time, the rinsing pressure is increased by 20% based on P_w adjusted in step S5 (P_w,high=P_w×1.2) to enhance the flushing effect on residual stubborn pollutants.

[0063] Mode and parameter association storage: The controller associates and stores the final determined cleaning mode, the corresponding execution parameters and selection logic (P value, C value) in the storage unit to form a cleaning decision log, which provides data support for subsequent multi-parameter self-learning model optimization.

[0064] Taking the flow monitoring scenario of a city's drainage pipe network as an example, the network is mainly polluted by sediment during the flood season (C=1), and prone to algae growth during the non-flood season (C=2). The system configuration is as follows: Preset pollution level thresholds: 0.3 (light / moderate boundary), 0.7 (moderate / heavy boundary); Combination mode interval: 5s; Correction factor for duration of light pollution: 0.7; The pressure increase coefficient for severe pollution is 1.2.

[0065] The specific execution scenarios are as follows: Scenario 1 (Light pollution during the flood season): Step S4 calculates P=0.25 (<0.3), and step S1 identifies C=1 (silt). The controller determined that the contamination was minor and selected the high-pressure water flushing mode. The flushing pressure P_w=1.0MPa and cleaning time t=30s adjusted in step S5 are called. The time is shortened to 21s according to the rules. High-pressure water flushing is started to quickly remove a small amount of mud and sand.

[0066] Scenario 2 (Moderate pollution outside the flood season): Step S4 calculates P=0.5 (0.3≤P<0.7), and step S1 identifies C=2 (algae). The controller determines that the contamination is moderate and selects the ultrasonic cleaning mode. The ultrasonic cleaning process was initiated by calling the ultrasonic frequency f=55kHz, cleaning power P_c=150W, and cleaning duration t=40s adjusted in step S5, which effectively removed the algae biofilm.

[0067] Scenario 3 (Severe pollution after heavy rain): Step S4 calculates P=0.8 (≥0.7), and step S1 identifies C=3 (mixed pollutants: silt + algae). The controller determines the pollution level to be heavy and selects the combined mode; First, adjust the parameters (f=60kHz, P_c=180W, t=50s) according to step S5 and perform ultrasonic cleaning. After a 5s interval, increase the rinsing pressure from 1.2MPa adjusted in step S5 to 1.44MPa and perform high-pressure water rinsing to thoroughly remove mixed stubborn contaminants.

[0068] Cleaning levels are determined by a quantitative value P indicating the degree of contamination, and a targeted mode is selected based on the type of contaminant C. This avoids the problem of traditional fixed modes being insufficiently adaptable to different contamination scenarios. For light contamination, low-pressure, short-duration rinsing saves energy; for moderate contamination, a single mode is selected based on the characteristics of the contaminant to improve efficiency; and for heavy contamination, a combination mode is used to enhance the effect, thus achieving "cleaning on demand".

[0069] By selecting a tiered mode, the system avoids equipment wear caused by using high-intensity ultrasonic cleaning when the contamination is mild, and also reduces the ineffective energy consumption of repeated cleaning in a single mode when the contamination is severe. This extends the service life of the self-cleaning function modules (ultrasonic generator, high-pressure water pump) and reduces system operating costs.

[0070] Different cleaning modes are matched to the physicochemical characteristics of different types of pollutants such as silt and algae, which solves the problem that traditional single cleaning modes cannot completely remove specific pollutants; the timing design of the combined mode realizes the synergistic effect of "vibration stripping + high pressure flushing", which greatly improves the removal effect of stubborn pollutants.

[0071] Although the present invention has been described in detail with reference to the accompanying drawings and preferred embodiments, the present invention is not limited thereto. Various equivalent modifications or substitutions can be made to the embodiments of the present invention by those skilled in the art without departing from the spirit and essence of the invention, and such modifications or substitutions should all be within the scope of the present invention. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should also be covered within the protection scope of the present invention.

Claims

1. A flow monitoring system for open channels / partially full pipes with self-cleaning function, characterized in that, The system includes a self-cleaning flow metering sensor (110), a controller (121), and a host computer. The self-cleaning flow metering sensor (110) is connected to the controller (121) via communication, and the controller (121) is connected to the host computer via communication. The self-cleaning flow metering sensor (110) is used to collect real-time flow velocity data, real-time water level data, and real-time water quality data in open channels / non-full pipes, and to perform self-cleaning operations in response to control commands. The controller (121) includes a communication module, a storage unit, and a computing unit, which are used to receive real-time data, calculate flow data, assess the degree of pollution, dynamically adjust self-cleaning parameters, and generate control commands through the computing unit. The host computer is used to display various types of data, configure self-cleaning reference parameters, receive operating status information uploaded by the controller (121), and support remote control.

2. The flow monitoring system for open channels / partially full pipes with self-cleaning function according to claim 1, characterized in that, The self-cleaning flow metering sensor (110) includes an outer protective housing (111), an inner support housing (114), a monitoring component (112), and a self-cleaning functional module (113). The outer protective housing (111) is a cylindrical structure with a flange connection at one axial end for sealing and fixing to the side wall of the open channel / non-full pipe to be monitored. The other axial end of the outer protective housing (111) is an open end with an internal thread connection on the inner side. The inner support housing (114) is a disc-shaped structure with an external thread connection on its outer periphery that mates with the internal thread connection. The inner support housing (114) is sealed by threaded engagement. The sealing device is installed at the open end of the outer protective shell (111) to form a detachable sealed connection; the end face of the inner support shell (114) facing the inside of the open channel / non-full pipe is defined as the monitoring installation surface (1141), the central area of ​​the monitoring installation surface (1141) is the monitoring component installation area, and a number of self-cleaning function installation ports (1111) are evenly distributed around the outer protective shell (111) on the outer periphery of the monitoring component installation area; the outer protective shell (111) and the inner support shell (114) together form a sealed electrical chamber for accommodating the electrical connection lines of the monitoring component (112) and the self-cleaning function module (113).

3. The flow monitoring system for open channels / partially full pipes with self-cleaning function according to claim 2, characterized in that, The monitoring component (112) includes an ultrasonic flow velocity sensor (1121), a pressure level module (1122), and a water quality monitoring unit (1123). The ultrasonic flow velocity sensor (1121) includes several sets of ultrasonic transducer pairs. Each set of ultrasonic transducer pairs includes a transmitting transducer and a receiving transducer. The transmitting transducer and the receiving transducer are arranged diagonally on both sides of the monitoring component installation area. Their detection surfaces are flush with or protrude from the monitoring installation surface (1141) and face the direction of water flow inside the open channel / non-full pipe. The pressure level module (1122) is embedded in the geometric center of the monitoring component installation area. The pressure sensing diaphragm of the pressure level module (1122) is flush with and sealed to the monitoring installation surface (1141) to directly withstand water pressure. The water quality monitoring unit (1123) is integrated on one side of the monitoring component installation area, including a turbidity sensor probe, a water temperature sensor probe and a pollutant type identification probe. The detection end of each sensor probe is flush with the monitoring installation surface (1141). The self-cleaning function module (113) includes a medium-frequency ultrasonic cleaning component (1131) and a high-pressure water flushing component (1132), which are alternately arranged in their respective cleaning function installation ports (1111); The medium-frequency ultrasonic cleaning assembly (1131) includes an ultrasonic generator and an ultrasonic transmission block; the ultrasonic generator is fixedly installed in the electrical chamber, and its vibration output end is tightly coupled to the inner end face of the ultrasonic transmission block; the ultrasonic transmission block is sealed and embedded in the self-cleaning function installation port (1111), and its outer end face is flush with or protrudes from the monitoring installation surface (1141), and the outer end face of the ultrasonic transmission block is tilted towards the monitoring assembly installation area, so that the ultrasonic vibration energy is focused on the detection surface area of ​​the monitoring assembly (112); The high-pressure water flushing assembly (1132) includes a high-pressure nozzle, a water delivery channel, and a high-pressure water supply interface; the high-pressure nozzle is sealed and installed in the self-cleaning function installation port (1111), and its spray nozzle is flush with or protrudes from the monitoring installation surface (1141), and the spray nozzle is inclined toward the monitoring assembly installation area; the water delivery channel is opened inside the inner support shell (114) and connects the high-pressure nozzle with the high-pressure water supply interface located in the electrical chamber; the high-pressure water supply interface is connected to an external water storage tank or an external water supply system through a flexible high-pressure pipeline.

4. A method for monitoring flow in open channels / partially full pipes with self-cleaning function, characterized in that, The method applicable to the open channel flow monitoring system with self-cleaning function according to any one of claims 1-3 includes: S1. The self-cleaning flow metering sensor collects real-time flow velocity, real-time water level data, and water quality data including turbidity, water temperature, and pollutant type in open channels / non-full pipes through multi-channel synchronous acquisition, and sends the data to the controller in a package. S2. The controller calculates the current ultrasonic velocity based on the real-time water temperature and calibrates the real-time flow velocity data of a single channel by combining the pre-stored standard velocity deviation coefficient. S3. The controller calculates the flow rate data of open channel / non-full pipe based on real-time water level data, preset cross-sectional fitting parameters and calibrated weighted average flow velocity, combined with water temperature and turbidity correction coefficients. S4. The controller calculates the ultrasonic signal attenuation rate, flow velocity fluctuation coefficient and water level fluctuation coefficient, dynamically allocates weights according to pollutant type, and comprehensively evaluates the degree of sensor contamination. S5. The controller calculates the biofilm thickness on the sensor by combining turbidity, weighted average flow rate and cumulative time since the last cleaning, and dynamically adjusts the frequency, power, pressure and time parameters of the self-cleaning function module based on the measured flow data of open channel / non-full pipe, pollution level and calculated biofilm thickness. S6. The controller generates adaptive control commands based on dynamically adjusted parameters and sends them to the self-cleaning function module to perform cleaning operations; it also records cleaning parameters, monitoring data before and after cleaning, and uploads them to the host computer.

5. The method for monitoring flow in open channels / partially full pipes with self-cleaning function according to claim 4, characterized in that, Step S1 includes: S11, Response time of ultrasonic flow velocity sensor based on self-cleaning flow metering sensor Set the data sampling frequency , Simultaneously, the effective water level range for open channels / partially full pipes is preset. ; S12, Ultrasonic flow velocity sensor according to sampling frequency Raw flow velocity data was collected simultaneously through n audio channels. The pressure water level module collects raw water level data at preset time intervals. The water quality monitoring unit simultaneously collects turbidity data. Water temperature and pollutant types ; S13. Perform moving average noise reduction processing on the raw flow velocity data: ； in, This is the preprocessed monochannel flow velocity data; N is the sliding window length; data exceeding the limit are removed from the original water level data. After identifying outliers, the average value is calculated as the water level data: ； in, This provides real-time water level data. This is the effective water level data format; S14, after pretreatment Water quality data The data is packaged according to a preset data frame format and sent to the controller via the communication link between the self-cleaning flow metering sensor and the controller.

6. The method for monitoring flow in open channels / partially full pipes with self-cleaning function according to claim 5, characterized in that, Step S2 includes: S21. The controller extracts the real-time water temperature from the data packaged in step S1. The ultrasonic velocity in the current environment is calculated based on a nonlinear correlation formula between water temperature and ultrasonic velocity. ； in, The ultrasonic velocity corresponding to the current water temperature; S22. The controller retrieves the standard ultrasonic velocity at standard water temperature pre-stored in the storage unit. Calculate the sound speed deviation coefficient to quantify the difference between the current sound speed and the standard sound speed: ； in, This is the sound speed deviation coefficient; S23. The controller calls the preprocessed monochannel flow velocity raw data from step S1 and performs linear calibration on it using the sound velocity deviation coefficient: ； in, This is the calibrated monochannel flow rate data.

7. The method for monitoring flow in open channels / partially full pipes with self-cleaning function according to claim 6, characterized in that, Step S3 includes: S31, The controller retrieves the preset channel flow rate weighting coefficients from the storage unit. Combined with the monochannel flow rate data calibrated in step S2 Calculate the weighted average flow velocity : ； S32. The controller calls the real-time water level data h collected in step S1 and the pre-stored cross-section fitting parameters. The cross-sectional area of ​​the water passage is calculated by integrating the fitting formula for the cross-sectional width: ； ； in, Water level The cross-sectional width at that location; This refers to the cross-sectional area of ​​the water passage. S33. The controller extracts the real-time water temperature θ and turbidity T from step S1 and calculates the flow correction coefficient. : ； S34, The controller combines the weighted average flow rate from step S31. The cross-sectional area of ​​the water passage in step S32 and the flow correction coefficient in step S33 Calculate real-time flow data for open channels / non-full pipes : 。 8. The method for monitoring flow in open channels / partially full pipes with self-cleaning function according to claim 7, characterized in that, Step S4 includes: S41. The controller retrieves the initial ultrasonic signal strength of the sensor pre-stored in the storage unit. Extract the current ultrasonic signal intensity in step S1 Monoflow velocity data after step S2 calibration and the water level sampling data collected in step S1 within the preset time period. Simultaneously, obtain the pollutant types identified in step S1. ; S42. Calculate the ultrasonic signal attenuation rate. : ； Calculate the flow velocity fluctuation coefficient : ； Calculate the water level fluctuation coefficient : ； in, This is the average water level over a preset time period. ; S43. Dynamically allocate the weights of each coefficient according to the type of pollutant. And combined with the ultrasonic signal attenuation rate calculated in step S42 Flow velocity fluctuation coefficient and water level fluctuation coefficient Comprehensive assessment of pollution levels : ； in, Slight pollution. Moderate pollution. It is severely polluted.

9. The method for monitoring flow in open channels / partially full pipes with self-cleaning function according to claim 8, characterized in that, Step 5 includes: S51, The controller extracts the real-time turbidity T from step S1 and the weighted average flow rate from step S3. Flow velocity fluctuation coefficient in step S4 Retrieve the cumulative time since the last cleaning recorded in the storage unit. Preset initial thickness of biofilm and adhesion coefficient Calculate biofilm thickness : ； S52. Real-time flow data of open channels / non-full pipes calculated based on step S3 The pollution level P in step S4 and the biofilm thickness δ in step S51 are determined by a preset reference ultrasonic frequency. Turbidity Influence Coefficient Pollution level influence coefficient Biofilm thickness influence coefficient and thickness threshold Adjust the ultrasonic frequency : ； S53. Combining the pollution level P from step S4, the biofilm thickness δ from step S51, and the real-time water temperature θ from step S1, preset the baseline cleaning power. Pollution level and power coefficient Biofilm thickness power coefficient and water temperature correction factor Adjust the cleaning power of the ultrasonic generator : ； S54. Based on the pollution level P in step S4 and the real-time flow data of the open channel / non-full pipe calculated in step S3. and the weighted average flow rate in step S3 and preset baseline flushing pressure Pollution level and pressure coefficient Turbidity pressure coefficient and flow velocity influence coefficient Adjust the high-pressure water pressure : ； S55. Combining the contamination level P from step S4, the biofilm thickness δ from step S51, and the contaminant type C from step S1, a preset baseline cleaning time is determined. Pollution Degree Duration Coefficient Biofilm thickness duration factor Pollutant type coefficient Define the correction function Adjust cleaning time : 。 10. The method for monitoring flow in open channels / partially full pipes with self-cleaning function according to claim 9, characterized in that, Step 6 includes: S61, The controller retrieves the contamination level P from step S4 and the ultrasonic frequency f and cleaning power after dynamic adjustment in step S5. Flushing pressure and cleaning time Determine the cleaning mode based on the degree of contamination: If Then select the high-pressure water flushing mode. Then select the single mode according to the pollutant type in step S1. Then select the combination mode; S62. The controller encapsulates the cleaning mode, adjusted self-cleaning parameters, and execution timing into standardized control instructions. S63. The controller sends standardized control commands to the self-cleaning function module of the self-cleaning flow metering sensor through its 4G / 5G dual-mode communication module. The module responds to the command and starts the corresponding cleaning component to perform the cleaning operation. S64. During the cleaning process, the controller synchronously records the cleaning start time. End time The actual execution parameters and real-time monitoring data before and after cleaning are verified using the data integrity verification formula. Validate the data validity, among which, To effectively record the number of data entries, This represents the total number of records to be kept. S65. After the verification is successful, the controller stores the above-mentioned recorded data in its storage unit and simultaneously uploads it to the host computer via the communication module with encryption. The host computer's display unit displays the data, and the storage and forwarding unit archives and manages it.

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