A multi-modal self-adaptive flow measurement system and method based on real-time sediment concentration perception

Abstract

The application is suitable for the technical field of hydrological monitoring, and provides a multi-modal adaptive flow measurement system and method based on real-time sensing of sediment concentration, which comprises an optical sediment measurement module, an acoustic flow measurement module, an electromagnetic wave flow measurement module, a mechanical flow measurement module, a signal conditioning and data processing module, and a mode switching control unit. The optical sediment measurement module monitors the sediment concentration in real time. The mode switching control unit is internally provided with a hysteresis threshold comparison logic, two preset threshold values, and a switching mechanism for automatically switching between the acoustic, electromagnetic wave and mechanical flow measurement modes according to the real-time sediment concentration, with a switching response time of less than 0.5s and a 2-5s smooth transition period. The weighted average algorithm is used to realize continuous data transition. Each mode is matched with a dedicated anti-interference algorithm: wavelet threshold denoising for the acoustic mode, Kalman filtering for the electromagnetic wave mode, and temperature drift compensation and sediment concentration density correction for the mechanical mode. The application realizes continuous and stable flow measurement in the full sediment concentration range.

Description

Technical Field

[0001] This invention relates to the field of hydrological monitoring technology, specifically a multimodal adaptive flow measurement system and method based on real-time sediment concentration sensing. Background Technology

[0002] In existing technologies, commonly used flow measurement techniques in hydrological monitoring mainly include acoustic Doppler current profilers (ADCP), non-contact radar / microwave velocimeters, and mechanical rotor current meters. Among these, ADCP utilizes the acoustic Doppler effect to measure the velocity distribution across the entire cross-section, acquiring multi-layer velocity data from the water surface to the riverbed in a single measurement. It is primarily used for routine hydrological monitoring and sediment transport rate measurement, and is the mainstream flow measurement equipment for clear rivers. Non-contact radar / microwave velocimeters utilize the microwave Doppler effect to measure surface velocity, featuring completely non-contact installation and a wide measurement range (0.15~20 m / s), suitable for flow measurement during high-sediment flood seasons and emergency rescue operations. Mechanical rotor current meters utilize water flow to drive a propeller / cup to measure velocity, with a lower velocity limit as low as 0.015 m / s, and can be used in applications with sediment concentrations ≥150 kg / m³. 3 It can operate under short-term extreme conditions and is an important backup plan during periods of extremely high sediment content in rivers.

[0003] However, existing technical solutions each have significant drawbacks. The core flaw of ADCP lies in its effectiveness when the sand content exceeds 10-20 kg / m³. 3 When sound wave energy is absorbed and scattered by suspended sediment particles, it attenuates rapidly, leading to problems such as shortened effective detection distance, bottom tracking failure, or data distortion, and even loss of measurement capability. The core drawback of non-contact radar / microwave velocimeters is that they can only measure the surface velocity of water bodies, requiring the calculation of the cross-sectional average velocity through empirical formulas (such as the velocity distribution exponential law). Under conditions of high sediment content and turbulent flow, the calculation error can exceed 20%, making it difficult to meet the requirements of high-precision hydrological monitoring. Mechanical rotor-type current meters are easily affected by sediment and debris. The propeller / cup is easily jammed or accelerated by coarse particles in high-sediment flow, resulting in high maintenance costs and poor reliability in long-term online operation. In addition, existing systems usually have a fixed installation of one flow measurement device, which cannot automatically switch the flow measurement principle and working mode according to real-time changes in sediment content. Moreover, flow velocity measurement and sediment monitoring often use independent equipment and data links, lacking a collaborative integration mechanism. In summary, existing hydrological monitoring systems generally use a single type of flow measurement equipment and lack an integrated intelligent flow measurement device that can smoothly and seamlessly switch between different flow measurement principles such as acoustic, radar electromagnetic waves, and mechanics based on real-time changes in sediment concentration. This leads to industry problems such as equipment failure, forced shutdown, or reliance on inefficient manual testing when sediment concentration fluctuates significantly.

[0004] Therefore, in view of the above situation, there is an urgent need to provide a multimodal adaptive flow measurement system and method based on real-time sensing of sediment content in order to overcome the shortcomings in current practical applications. Summary of the Invention

[0005] The purpose of this invention is to provide a multimodal adaptive flow measurement system and method based on real-time sensing of sediment content, effectively solving the problems mentioned in the background art.

[0006] This invention is implemented as follows: a multimodal adaptive flow measurement system based on real-time sediment concentration sensing, comprising: An optical sand measurement module is used to monitor the sand content of water bodies in real time. An acoustic flow measurement module is used to measure flow velocity when the sand content is below a first threshold. The electromagnetic wave flow measurement module is used to measure the surface velocity of water in a non-contact manner and convert it into the cross-sectional average velocity through a flow velocity profile model. The mechanical flow measurement module is used for flow velocity measurement in extreme environments with extremely high sediment content. The signal conditioning and data processing module is connected to the optical sand measurement module, acoustic flow measurement module, electromagnetic wave flow measurement module and mechanical flow measurement module respectively, and is used to complete signal amplification, filtering and analog-to-digital conversion. The mode switching control unit is signal-connected to the signal conditioning and data processing module, and is also control-connected to the acoustic flow measurement module, the electromagnetic wave flow measurement module, and the mechanical flow measurement module, respectively. The mode switching control unit has built-in hysteresis threshold comparison logic and presets two levels of boundary thresholds: the first threshold C1 = 20 kg / m 3 The second threshold C2 = 150 kg / m 3 Based on the real-time sediment concentration, the corresponding flow measurement mode is automatically activated, while the non-working mode is put into dormancy or reduced in weight.

[0007] As a further aspect of the present invention: the mode switching response time of the mode switching control unit is less than 0.5s; The modality switching control unit has a built-in data smoothing transition module, which is used to perform weighted fusion of the flow rate output data before and after the mode switching during a smoothing transition period of 2 to 5 seconds after the mode switching occurs.

[0008] As a further aspect of the present invention: the weighted average algorithm executed by the data smoothing transition module is as follows: ; In the formula, To output flow rate, The original modal velocity, For the new modal flow velocity, It grows linearly from 0 to 1.

[0009] As a further aspect of the present invention, the optical sand measuring module employs a near-infrared transmission or scattering optical sensor.

[0010] As a further aspect of the present invention, the optical sand measurement module is also equipped with a dual-frequency ultrasonic particle size identification module, which is used to obtain the median particle size d50 and assist in flow pattern discrimination and parameter correction.

[0011] As a further aspect of the present invention: the acoustic flow measurement module adopts a 300kHz~600kHz low-frequency acoustic Doppler velocity profiler or a multi-path ultrasonic time-of-flight flow measurement unit.

[0012] As a further aspect of the present invention: the electromagnetic wave flow measurement module uses a 24GHz or 35GHz radar surface velocity meter, and combines a logarithmic flow velocity profile model to convert the surface flow velocity into the cross-sectional average flow velocity.

[0013] As a further aspect of the present invention: the mechanical flow measurement module adopts a strain gauge flow measurement rod or a differential pressure sensor, and the mechanical flow measurement module has no optical window and no high-frequency acoustic components.

[0014] This invention also provides a multimodal adaptive flow measurement method based on real-time sediment concentration sensing, employing the system described above, and including the following steps: Step S1: The optical sand measurement module collects the sand content C in real time; Step S2: The mode switching control unit compares C with the threshold C1 = 20 kg / m 3 C2 = 150 kg / m 3 ; Step S3: If C < 20 kg / m 3 Activate the acoustic flow measurement module; if 20kg / m 3 ≤C<150kg / m 3 Activate the electromagnetic wave current measurement module; if C ≥ 150 kg / m 3 Activate the mechanical flow measurement module; Step S4: During the mode switching transition period of 2-5 seconds, apply the weighted formula. Output, Incrementing linearly from 0 to 1; Step S5: Enable the anti-interference algorithm for the corresponding mode; Step S6: Upload the data to the big data center.

[0015] As a further aspect of the present invention: in step S5, wavelet threshold denoising is used for acoustic modes, Kalman filtering is used for electromagnetic modes, and temperature drift compensation and sand content density correction are used for mechanical modes.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention integrates three modes: acoustic, electromagnetic wave, and mechanical, covering the entire scenario from clear water to floods with extremely high sediment content. It solves the problem of failure of single flow measurement equipment under high sediment content conditions and realizes continuous measurement of the entire sediment content range.

[0017] The real-time monitoring and automatic switching of the sediment measurement module and the control unit have a response time of less than 0.5 seconds, which replaces the outdated mode of "manual measurement or equipment replacement for high sediment content" at hydrological stations and realizes fully automatic unattended adaptive switching.

[0018] Furthermore, by employing a short-time weighted smoothing algorithm, the fluctuation range of mode switching data is less than 3%, ensuring the integrity and availability of hydrological data compilation and achieving continuous data without jumps during the switching process. Simultaneously, the mechanical mode directly measures fluid dynamic pressure, unaffected by acoustic attenuation or optical window contamination, and utilizes real-time sediment concentration to correct fluid density, maintaining good accuracy even in high sediment concentration environments.

[0019] Furthermore, the present invention enables a single device to simultaneously perform flow measurement, sand measurement, and particle size monitoring, eliminating the need for multiple sets of monitoring equipment. Compared to separate deployment schemes, the overall cost is reduced by 30% to 40%, achieving integrated flow and sand measurement and reducing construction and maintenance costs. Attached Figure Description

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 This is a system architecture block diagram of the present invention.

[0022] Figure 2 This is a schematic diagram of the system installation structure of the present invention.

[0023] Figure 3 This is a flowchart of the method of the present invention. Detailed Implementation

[0024] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] The present invention will be further explained below with reference to specific embodiments.

[0026] Example 1: As Figure 1 As shown, the present invention provides a multimodal adaptive flow measurement system based on real-time sediment concentration sensing, comprising an optical sediment measurement module, an acoustic flow measurement module, an electromagnetic flow measurement module, a mechanical flow measurement module, a signal conditioning and data processing module, a mode switching control unit, and a data storage and remote transmission module. The optical sediment measurement module, acoustic flow measurement module, electromagnetic flow measurement module, and mechanical flow measurement module are each signal-connected to the signal conditioning and data processing module; the signal conditioning and data processing module is signal-connected to the mode switching control unit; the mode switching control unit is control-connected to the acoustic flow measurement module, electromagnetic flow measurement module, and mechanical flow measurement module, and is used to send activation, sleep, or deweighting control commands to each flow measurement module based on real-time sediment concentration data; the data storage and remote transmission module is data-connected to the signal conditioning and data processing module and the mode switching control unit.

[0027] The optical sand measurement module uses near-infrared transmission or scattering optical sensors (such as OBS) to monitor the sand content of the water body in real time, providing a basis for mode switching.

[0028] Optionally, the optical sand measurement module is also equipped with a dual-frequency ultrasonic particle size identification module, which is used to obtain the median particle size d50 of sediment in the water body to assist in flow pattern identification and flow velocity parameter correction.

[0029] The acoustic flow measurement module employs a 300kHz~600kHz low-frequency acoustic Doppler current profiler (ADCP) or a multi-path ultrasonic time-of-flight flow measurement unit, used when the sediment content is below the first threshold (C1=20kg / m³). 3 High-precision flow velocity measurement was performed under low sand content conditions. When the sand content exceeded 20 kg / m³... 3 When this happens, the system will automatically reduce its data weight or turn it off.

[0030] The electromagnetic wave flow measurement module uses a 24GHz or 35GHz radar surface velocity meter to measure the surface velocity of water in a non-contact manner. It is largely unaffected by sediment concentration and is suitable for sediment concentrations between the first and second thresholds (20kg / m³). 3 ≤C<150kg / m 3 The electromagnetic wave flow measurement module is designed for medium to high sand content conditions. It has a built-in velocity profile model conversion unit that converts the measured surface velocity into the cross-sectional average velocity based on the logarithmic velocity profile model. The error under normal working conditions can be controlled within ±10%.

[0031] The mechanical flow measurement module employs a strain gauge flow meter or a differential pressure velocity sensor. This module is specifically designed for applications where the sand content exceeds a second threshold (C ≥ 150 kg / m³). 3Designed for extreme environments with extremely high sand content, it has no optical windows or high-frequency acoustic components, and features anti-siltation and wear-resistant properties, with errors controllable within ±5%.

[0032] The mode switching control unit has built-in hysteresis threshold comparison logic and presets two levels of boundary thresholds: the first threshold C1 = 20 kg / m 3 The second threshold C2 = 150 kg / m 3 The mode switching control unit automatically switches operating modes according to the following rules based on the real-time sand concentration data transmitted by the optical sand concentration module: when the real-time sand concentration C < C1, the acoustic flow measurement module is activated as the main operating mode, and a sleep or deweighting command is sent to the electromagnetic flow measurement module and the mechanical flow measurement module; when the real-time sand concentration C1 ≤ C < C2, the electromagnetic flow measurement module is activated as the main operating mode, and a sleep or deweighting command is sent to the acoustic flow measurement module and the mechanical flow measurement module; when the real-time sand concentration C ≥ C2, the mechanical flow measurement module is activated as the main operating mode, and a sleep or deweighting command is sent to the acoustic flow measurement module and the electromagnetic flow measurement module. The mode switching control unit has a built-in hysteresis comparator to prevent frequent mode switching caused by small fluctuations in sand concentration near the threshold. The mode switching response time of the mode switching control unit is less than 0.5 seconds.

[0033] The mode switching control unit also incorporates a data smoothing transition module, which performs weighted fusion processing on the flow rate output data before and after the mode switching occurs within a preset transition time. The data smoothing transition module executes the following weighted average algorithm: In the formula: To output flow rate, The original modal velocity, For the new modal flow velocity; These are the weighting coefficients. It linearly increases from 0 to 1 within a preset transition time (2 to 5 seconds).

[0034] Meanwhile, this invention configures dedicated anti-interference algorithms and compensation models for each working mode: the acoustic flow measurement module is equipped with a wavelet threshold denoising algorithm to suppress environmental noise and multipath interference in the acoustic signal; the electromagnetic wave flow measurement module is equipped with a Kalman filter denoising algorithm to smooth random noise in the radar echo signal; the mechanical flow measurement module is equipped with a temperature drift compensation algorithm and a sediment concentration density correction algorithm. The sediment concentration density correction algorithm corrects the fluid density in real time based on the sediment concentration data fed back by the optical sediment measurement module, so as to eliminate the influence of high sediment concentration water density changes on the accuracy of mechanical flow measurement.

[0035] The structure of each component in this system is as follows: Figure 2 As shown.

[0036] The core of this invention is the overall architecture of real-time sensing of sediment content and at least two flow measurement units based on different physical principles, as well as automatic threshold switching. It is not limited to specific sensor and algorithm types, and all equivalent substitutions fall within the protection scope of this invention.

[0037] Specifically, alternatives to the sediment concentration sensing module include: The method of indirect inversion of sand content using ultrasonic attenuation, gamma-ray transmission, and vibrating tube density meter can be used to replace near-infrared OBS optical sensors. It is suitable for scenarios with extremely high sand content, strong light interference, and easy contamination of optical windows.

[0038] Alternatives to acoustic flow measurement units include: the use of fixed multi-path ultrasonic time-of-flight method and horizontal H-ADCP to replace the mobile ADCP, in order to adapt to online monitoring of river channels with stable cross sections.

[0039] Alternatives to electromagnetic wave flow measurement units include: using video surface velocimetry (LSPIV), laser Doppler velocimetry, and microwave array radar to replace traditional single-point radar.

[0040] Alternatives to the mechanical flow measurement unit include: using differential pressure velocity sensors, sealed wear-resistant rotor velocity meters, and pipeline electromagnetic flow meters as equivalent replacements for strain gauge flow measurement rods.

[0041] Alternatives to the switching and smoothing algorithms include: threshold decision can use hysteresis comparison or dynamic threshold; data smoothing can use exponential smoothing, confidence-weighted fusion, or Kalman multi-source fusion algorithms, all of which can achieve the same continuous transition effect.

[0042] Example 2: Figure 3 As shown, this embodiment of the invention also provides a multimodal adaptive flow measurement method based on real-time sediment concentration sensing, employing the system described in Embodiment 1, and including the following steps: Step S1: The sand measurement module collects real-time information on the sediment content (C) and particle size of the water body; Step S2: After the signal conditioning and data processing module completes signal amplification, filtering, and analog-to-digital conversion, the mode switching control unit compares C with the threshold C1 = 20 kg / m 3 C2 = 150 kg / m 3 ; Step S3: The mode switching control unit automatically matches the optimal flow measurement mode according to the preset threshold. If C < 20 kg / m 3 Activate the acoustic unit; if 20kg / m 3 ≤C<150kg / m 3 Activate the electromagnetic wave unit; if C ≥ 150 kg / m 3 Activate the mechanical unit; Step S4: During the handover transition period (2 Within 5 seconds, according to the weighted formula Output, The flow rate increases linearly from 0 to 1 to avoid abrupt changes in the flow process line and ensure smooth and continuous data. Step S5: Enable the anti-interference algorithm for the corresponding mode. Wavelet threshold denoising is used for acoustic mode, Kalman filtering is used for radar electromagnetic wave mode, and temperature drift compensation and sand content density correction are used for mechanical mode. Step S6: Upload the data to the big data center.

[0043] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multimodal adaptive flow measurement system based on real-time sediment concentration sensing, characterized in that, include: An optical sand measurement module is used to monitor the sand content of water bodies in real time. An acoustic flow measurement module is used to measure flow velocity when the sand content is below a first threshold. The electromagnetic wave flow measurement module is used to measure the surface velocity of water in a non-contact manner and convert it into the cross-sectional average velocity through a flow velocity profile model. The mechanical flow measurement module is used for flow velocity measurement in extreme environments with extremely high sediment content. The signal conditioning and data processing module is connected to the optical sand measurement module, acoustic flow measurement module, electromagnetic wave flow measurement module and mechanical flow measurement module respectively, and is used to complete signal amplification, filtering and analog-to-digital conversion. The mode switching control unit is signal-connected to the signal conditioning and data processing module, and is also control-connected to the acoustic flow measurement module, the electromagnetic wave flow measurement module, and the mechanical flow measurement module, respectively. The mode switching control unit has built-in hysteresis threshold comparison logic and presets two levels of boundary thresholds: the first threshold C1 = 20 kg / m 3 The second threshold C2 = 150 kg / m 3 Based on the real-time sediment concentration, the corresponding flow measurement mode is automatically activated, while the non-working mode is either put into dormancy or downweighted.

2. The system according to claim 1, characterized in that, The mode switching response time of the mode switching control unit is less than 0.5s; The modality switching control unit has a built-in data smoothing transition module, which is used to perform weighted fusion of the flow rate output data before and after the mode switching during a smoothing transition period of 2 to 5 seconds after the mode switching occurs.

3. The system according to claim 2, characterized in that, The weighted average algorithm executed by the data smoothing transition module is as follows: ； In the formula, To output flow rate, The original modal velocity, For the new modal flow velocity, It grows linearly from 0 to 1.

4. The system according to claim 1, characterized in that, The optical sand measurement module uses a near-infrared transmission or scattering optical sensor.

5. The system according to claim 1, characterized in that, The optical sand measurement module is also equipped with a dual-frequency ultrasonic particle size identification module, which is used to obtain the median particle size d50 and assist in flow pattern discrimination and parameter correction.

6. The system according to claim 1, characterized in that, The acoustic flow measurement module uses a 300kHz~600kHz low-frequency acoustic Doppler velocity profiler or a multi-path ultrasonic time-of-flight flow measurement unit.

7. The system according to claim 1, characterized in that, The electromagnetic wave flow measurement module uses a 24GHz or 35GHz radar surface velocity meter, and combines a logarithmic velocity profile model to convert the surface velocity into the cross-sectional average velocity.

8. The system according to claim 1, characterized in that, The mechanical flow measurement module uses a strain gauge flow measurement rod or a differential pressure sensor, and the mechanical flow measurement module has no optical window or high-frequency acoustic components.

9. A multimodal adaptive flow measurement method based on real-time sediment concentration sensing, employing the system described in any one of claims 1 to 8, characterized in that, Includes the following steps: Step S1: The optical sand measurement module collects the sand content C in real time; Step S2: The mode switching control unit compares C with the threshold C1 = 20 kg / m 3 C2 = 150 kg / m 3 ; Step S3: If C < 20 kg / m 3 Activate the acoustic flow measurement module; if 20kg / m 3 ≤C<150kg / m 3 Activate the electromagnetic wave current measurement module; if C ≥ 150 kg / m 3 Activate the mechanical flow measurement module; Step S4: During the mode switching transition period of 2-5 seconds, apply the weighted formula. Output, Incrementing linearly from 0 to 1; Step S5: Enable the anti-interference algorithm for the corresponding mode; Step S6: Upload the data to the big data center.

10. The method according to claim 9, characterized in that, In step S5, wavelet thresholding is used for denoising acoustic modes, Kalman filtering is used for denoising electromagnetic modes, and temperature drift compensation and sand content density correction are used for mechanical modes.

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