Electromagnetic measuring water tank flow detection method and system

Abstract

The invention relates to the technical field of hydrological monitoring, in particular to a flow detection method and system for an electromagnetic measuring water tank, and the system comprises the electromagnetic measuring water tank, an electromagnetic induction module, an electrode-containing assembly, a space adjustment module, a water flow initial speed collection part containing a telescopic partition plate, a data processing module, and a water inlet pipeline. The electromagnetic induction module is used for generating an alternating magnetic field and collecting an induced electromotive force signal, and the space adjusting module is used for adjusting the effective volume of the water tank through a telescopic partition plate so as to adapt to the flow; the data processing module realizes signal conversion, flow comparison, pollution value calculation and AI pollution trend pre-judgment, the water inlet pipeline is used for introducing to-be-detected water flow, various sensors support pollution data acquisition, and the whole flow detection and pollution management process is jointly completed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of hydrological monitoring, in particular to an electromagnetic water tank flow detection method and system. BACKGROUND

[0002] The electromagnetic water tank has the advantage of non-contact detection based on electromagnetic induction principle, and becomes the core equipment for flow measurement in the fields of water supply and drainage engineering, industrial circulating water system, environmental protection water quality monitoring, etc., but its detection accuracy and scene adaptability have been long limited by design defects.

[0003] However, in the prior art, the electromagnetic water tank usually adopts a fixed volume structure, which cannot dynamically adjust the internal space according to the initial flow of the water flow to be detected. When the water flow and the volume of the water tank do not match, such as small flow adapting to large volume water tank or large flow adapting to small volume water tank, turbulent flow is easily formed during the water flow import stage, the Reynolds number is often more than 2300, which causes uneven distribution of water flow velocity, and then causes distortion of the induced electromotive force signal collected by the electromagnetic induction module, and finally the flow detection error rate is generally more than 5%, which is difficult to meet the high-precision measurement demand, such as ±2% error requirement in industrial production. At the same time, during the long-term use of the water tank, pollutants such as scale and microbial membrane are easily attached to the inner wall, and the electrode assembly will also affect the detection sensitivity due to signal attenuation, but the existing scheme lacks a quantitative evaluation mechanism for the degree of pollution, and only relies on periodic manual cleaning, which not only has high maintenance cost, with annual maintenance cost exceeding 30% of the total price of the equipment, but also cannot predict the pollution development trend, and often has the problems of "over cleaning" or "cleaning not in time". In addition, most detection methods only correct parameters for water temperature and water pressure, ignoring the interference of water quality hardness, such as high calcium and magnesium ion water body and water molecule cluster particle size, on the electromagnetic induction signal, and the detection accuracy is further deteriorated in complex water quality scenes, such as industrial wastewater and groundwater, the adaptation range is narrow, and it is difficult to meet the diversified detection demand.

[0004] Based on the above problems, the present application provides an electromagnetic water tank flow detection method and system. SUMMARY

[0005] In view of the shortcomings of the prior art, the present application provides an electromagnetic water tank flow detection method and system, which realizes five key links of system initialization, space dynamic adjustment, electromagnetic induction detection, data processing and pollution prediction, forms a complete detection system with wide flow interval adaptation and strong anti-interference capability, and effectively solves the problems of turbulent interference caused by the fixed volume of the traditional electromagnetic water tank, poor wide flow adaptation, unquantized pollution affecting the detection accuracy, and insufficient adaptation in complex scenes caused by incomplete parameter correction.

[0006] To achieve the above purpose, one of the present application provides an electromagnetic water tank flow detection method, which comprises; An electromagnetic water tank detection system is started, the electromagnetic induction module, the space adjustment module and the data processing module in the detection system are self-checked, after confirming that the functions of each module are normal, the initial parameters of the magnetic field strength of the electromagnetic induction module and the initial threshold value of the water tank volume of the space adjustment module are set according to the preset flow range of the water flow to be detected; The water flow to be detected is introduced into the electromagnetic water tank through the water inlet pipeline, the space adjustment module collects the initial speed signal of the water flow of the water inlet pipeline in real time, combines the water tank volume initial threshold value set in step S100, drives the retractable partition plate inside the electromagnetic water tank to move along the vertical direction, adjusts the effective accommodation space of the electromagnetic water tank, matches the initial flow of the water flow to be detected with the effective accommodation space, and avoids turbulent flow when the water flow is introduced; When the water level in the electromagnetic water tank reaches the preset detection water level, the electromagnetic induction module generates a stable alternating magnetic field according to the magnetic field strength initial parameter set in step S100, so that the water flow to be detected flowing through the effective accommodation space of the electromagnetic water tank cuts the magnetic induction lines, and the electrode assembly of the electromagnetic induction module collects the induced electromotive force signal generated by the water flow cutting the magnetic induction lines and transmits the induced electromotive force signal to the data processing module; The data processing module receives the induced electromotive force signal transmitted in step S300, converts the induced electromotive force signal into real-time flow data according to the electromagnetic induction law, and compares the real-time flow data with the preset flow range set in step S100, if the real-time flow data exceeds the preset flow range, the data processing module sends an adjustment instruction to the space adjustment module to drive the retractable partition plate to move again to adjust the effective accommodation space of the water tank, until the real-time flow data is within the preset flow range; Based on the data collected in step S100, the pollution value is calculated according to the weight of 35% of the thickness of the stain, 25% of the density of the microorganism, 30% of the electrode signal attenuation rate and 10% of the water molecule cluster particle size, the pollution value is 0-100 points, the adaptive coefficient is corrected combined with the water hardness, the water temperature and the water molecule cluster particle size, the pollution trend is predicted through the AI model, and the six pollution levels and the corresponding cleaning parameters of the pollutants are matched.

[0007] The second aspect of the application provides an electromagnetic water tank flow detection system for realizing a portable flow rate measurement method based on electromagnetic and rotor mutual calibration, comprising the following modules: The electromagnetic induction module, the space adjustment module, the pollution detection module and the data processing module are included; The electromagnetic induction module includes symmetrically arranged Helmholtz coils and a 3x4 array type titanium alloy electrode for generating an alternating magnetic field and collecting water flow induced electromotive force signals; The space adjustment module contains a telescopic partition driven by a stepper motor and an ultrasonic Doppler flowmeter, which are used to adjust the effective volume of the water tank and collect the initial velocity of the water flow. The pollution detection module contains a stain thickness sensor, a microorganism density detector and a water molecule cluster particle size analyzer, which are used to collect pollution and water quality parameters. The data processing module is electrically connected with the aforementioned modules, can perform self-checking and parameter presetting, calculate the initial flow and control the partition to adjust the volume, convert the induced electromotive force into real-time flow and dynamically adjust the volume, calculate the pollution value according to the preset weight to generate an adaptive coefficient to correct the flow, and predict the pollution trend through an LSTM model and match a graded maintenance scheme.

[0008] The third aspect of the present application provides a computer device, comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to realize an electromagnetic water tank flow detection method.

[0009] The fourth aspect of the present application provides a computer readable storage medium, wherein the storage medium stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to realize an electromagnetic water tank flow detection method.

[0010] Compared with the prior art, the present application provides an electromagnetic water tank flow detection method and system, which has the following beneficial effects: 1、The present application relies on the space adjustment module, calculates the initial flow based on the initial velocity of the water flow, drives the telescopic partition to move vertically to realize volume pre-adjustment, so that the matching degree of the volume and the initial flow is greater than or equal to 90%; if the real-time flow exceeds the preset range and the deviation is greater than 3% during detection, the partition is adjusted again to ensure that the water flow always flows in a laminar state with a Reynolds number Re less than 2300, thereby eliminating turbulent interference from the source, and adapting to a wide flow range of 5-50 m³ / h, which is 5 times larger than the adaptation range of the traditional scheme; 2、The present application uses an MxN array electrode to synchronously collect the induced electromotive force with a frequency greater than or equal to 50Hz, and converts the real-time flow based on the law of electromagnetic induction; at the same time, the pollution detection module collects data such as stains and microorganisms, calculates the pollution value according to the preset weight, and generates a correction result of the adaptive coefficient of 0.7-1.3 in combination with water quality hardness, water temperature and water molecule cluster particle size, so that the detection error rate is finally less than or equal to 2%, which is reduced by more than 60% compared with the traditional scheme, and meets the industrial high-precision requirements; 3, The scheme is based on historical and real-time pollution data, and predicts the 24h pollution trend by LSTM model, and is divided into stable / rising / falling, and is divided into six levels according to the pollution value 0-100, and the corresponding output is high-pressure water flushing, chemical soaking, component replacement and other differential cleaning schemes, so that the manual inspection frequency is reduced from once a day to once every 3 days, the maintenance cost is reduced by 40%, and the service life of the electrode is extended to 12 months, and the precision degradation caused by pollution accumulation is avoided.

[0011] The traditional electromagnetic water tank has the problems of turbulence interference caused by fixed volume, poor wide flow adaptability, detection precision degradation caused by unquantized pollution influence, and insufficient adaptation to complex scenes caused by incomplete parameter correction. BRIEF DESCRIPTION OF DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0013] Figure 1 is a schematic diagram of the electromagnetic water tank part of the present application; Figure 2 is a system overall architecture diagram; Figure 3 is a method overall flowchart; Figure 4 is a step S100 system initialization sub-flowchart; Figure 5 is a step S200 space pre-adjustment logic diagram; Figure 6 is a step S400 flow calculation and pollution prediction sub-flowchart; Figure 7 is a six-level pollution level and cleaning parameter correspondence diagram. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical scheme and advantages of the present application more clear, the embodiments of the present application will be further described in detail below with reference to the drawings.

[0015] The traditional electromagnetic water tank has the problems of turbulence interference caused by fixed volume, poor wide flow adaptability, detection precision degradation caused by unquantized pollution influence, and insufficient adaptation to complex scenes caused by incomplete parameter correction.

[0016] The present application provides an electromagnetic water tank flow detection method and system.

[0017] The scheme relies on a space adjustment module, calculates an initial flow based on an initial speed of water flow, drives a retractable partition to move vertically to realize volume pre-adjustment, and has a 5 times larger adaptation range than a traditional scheme. The scheme synchronously collects induced electromotive force with a frequency of greater than or equal to 50 Hz by using an M*N array electrode, converts real-time flow based on the electromagnetic induction law, and finally reduces a detection error rate to less than or equal to 2%, which is reduced by more than 60% than a traditional scheme, and meets the industrial high-precision requirement. The scheme predicts a 24-hour pollution trend based on historical and real-time pollution data by using an LSTM model, divides the trend into stable, rising and falling, divides six levels according to pollution values, and outputs differential cleaning schemes such as high-pressure water flushing, chemical soaking and component replacement, so that the artificial inspection frequency is reduced from once a day to once every three days, the maintenance cost is reduced by 40%, the service life of the electrode is extended to 12 months, and the precision degradation caused by pollution accumulation is avoided.

[0018] The scheme solves the problems of turbulence interference caused by the fixed volume of a traditional electromagnetic water tank, poor wide-flow adaptability, unquantified pollution influence causing detection precision degradation, and insufficient adaptation to complex scenes caused by incomplete parameter correction.

[0019] Embodiment one, as Figures 1-7 shown, an electromagnetic water tank flow detection method provided by the embodiment of the application is described.

[0020] S100: After starting the detection system, first, the electromagnetic induction module is checked for magnetic field stability and electrode signal, the space adjustment module including partition movement and initial speed acquisition, and the data processing module is self-checked for response speed. After confirming normality, the initial parameters of the magnetic field strength of the electromagnetic induction module and the initial threshold value of the water tank volume of the space adjustment module are set according to the preset flow range of the water flow to be detected, and the initial pollution and water quality data are collected at the same time according to “flow median value x residence time” calculation. S200: The water flow to be detected is introduced into the water tank through the water inlet pipeline, the space adjustment module acquires the initial speed signal of the water flow in the water inlet pipeline in real time, calculates the initial flow, drives the retractable partition in the water tank to move vertically, adjusts the effective accommodation space, matches the space with the initial flow, ensures the water flow to be laminar, and avoids turbulence. S300: When the water level of the water tank reaches 80% of the effective height of the preset detection water level, the electromagnetic induction module generates a stable alternating magnetic field according to the magnetic field strength initial parameters of S100, the water flow to be detected cuts the magnetic induction lines, the electrode assembly collects the induced electromotive force signal, and after anti-interference processing, the signal is transmitted to the data processing module in real time. S400: After the data processing module receives the signal, it converts it into real-time flow according to the law of electromagnetic induction. If the flow is outside the preset range, the system will send a command to adjust the baffle. At the same time, the pollution value is calculated according to the weight, and the adaptive coefficient is corrected combined with the water quality parameters. The AI model is used to predict the pollution trend, match the six pollution levels, and match the corresponding cleaning parameters to complete the detection.

[0021] The step S100 is used for system initialization, including: S110: Full module function self-checking, the specific design is as follows: S1101: Electromagnetic induction module self-checking: The electromagnetic induction module is the core of flow detection, and its magnetic field generation and signal acquisition capability need to be verified first.

[0022] ① Magnetic field stability detection: Three high-precision magnetic field strength sensors are uniformly arranged in the water tank, with a detection range of 0-2T and an accuracy of ±0.01T. The initial magnetic field strength of S100 is controlled, such as 0.8T. Three groups of data are continuously collected with an interval of 10s, and the average value and the deviation of single data are calculated. The requirement is that the deviation is ≤±2%. If the deviation exceeds the standard, the consistency of the magnetic field coil winding, the stability of the power supply voltage, which needs to be maintained at 220V±5%, and other problems such as coil short circuit and power supply fluctuation need to be checked; ② Electrode assembly signal transmission detection: A standard test signal is applied to the electrode assembly, with a voltage of 0.1V and a frequency of 50Hz. The feedback signal is collected by the data processing module receiver, and the signal attenuation rate is calculated. The attenuation rate = (standard signal intensity-feedback signal intensity) / standard signal intensity x 100%. The requirement is that the attenuation rate is ≤5%. If the attenuation rate is too high, the connection cable between the electrode and the data processing module needs to be checked. Shielded twisted pair cable with impedance of 50Ω should be used. Whether the cable is loose or not, whether the electrode surface is oxidized or not, and the thickness of the oxidation layer need to be ≤0.001mm. The oxidation layer can be removed by alcohol wiping to ensure smooth signal transmission.

[0023] S1102: Space adjustment module self-checking: The space adjustment module determines the water tank volume adaptability, and needs to verify the baffle moving precision and initial speed collection reliability.

[0024] ① Baffle positioning accuracy detection: Set three preset positions such as 20%, 50%, and 80% of the water tank height. The retractable baffle is driven to move to the target position in turn. The actual position and the preset position are measured by a laser range finder with an accuracy of ±0.01mm. The single deviation is required to be ≤±1mm, and the average deviation of three movements is required to be ≤±0.5mm. If the deviation exceeds the standard, the drive motor needs to be calibrated, the step motor step angle needs to maintain a pulse signal of 1.8°±0.1°, and the guide rail lubrication state needs to be checked by applying special lubricating grease with a thickness of 0.1-0.2mm to avoid mechanical jamming caused by inaccurate positioning; ②Initial velocity acquisition unit detection: standard water flow with stable flow rate is input into the water inlet pipeline, the flow rate is 0.5 m / s, calibrated by a standard flow meter, the initial velocity acquisition unit is controlled to continuously acquire 100 groups of data at a sampling frequency of 10 Hz, the standard deviation of the data is calculated, and the standard deviation is required to be ≤0.02 m / s - if the standard deviation is too large, the sensor installation angle needs to be adjusted to be perpendicular to the water flow direction, the deviation is ≤5°, the sensor probe is cleaned to avoid the influence of attached impurities on the signal, and the initial velocity acquisition is ensured to be stable.

[0025] S1103: Data processing module self-checking: the data processing module is the center of "signal conversion - instruction sending", and the response speed and data processing accuracy need to be verified.

[0026] ①Response speed detection: the signal generator inputs an analog electrode signal voltage of 0-0.1V and a frequency of 50Hz to the data processing module, records the delay time from signal reception to output flow rate calculation result, and requires a delay of ≤0.1s - if the delay is excessive, the data processing algorithm needs to be optimized, such as simplifying redundant calculation steps, upgrading the processor main frequency to ≥2.0GHz, and avoiding data accumulation leading to delay; ②Data accuracy detection: input known parameters magnetic field strength 0.8T, electrode spacing 0.1m, induced electromotive force 0.02V, verify the deviation of the flow rate value calculated by the data processing module according to E=k×B×L×v, k=1.0, v=0.02 / (1.0×0.8×0.1)=0.25m / s from the theoretical value, and require a deviation of ≤±1% - if the deviation is excessive, the instrument constant k needs to be calibrated by a standard flow device, and corrected to the range of 0.98-1.02 to ensure the accuracy of formula calculation; S1104: Pollution detection module self-checking: the pollution detection module provides data for subsequent pollution evaluation, and the detection accuracy and data stability of each sensor need to be verified. ①Stain thickness sensor: standard stain pieces with known thickness of 0.1mm, 0.2mm, 0.5mm are pasted to the sensor probe, the deviation of the detected value from the standard value is required to be ≤±0.01mm; ②Microbial density detector: inject standard bacterial solution with known concentration of 10³CFU / mL, 10 4 CFU / mL, the deviation of the detected value from the standard value needs to be ≤±5%; ③Water molecule cluster particle size analyzer: detect standard particle size solution 5nm, 10nm, the deviation needs to be ≤±0.5nm; at the same time, 10 groups of data of the same water sample are continuously acquired, the coefficient of variation CV=standard deviation / average value×100% is calculated, and the CV is required to be ≤±3% - if any sensor is not up to standard, zero point calibration needs to be performed, such as stain sensor zeroing, microbial detector calibration with sterile water, and replacement of aged probe to ensure reliable data.

[0027] S120: Key parameter presetting: S1201: electromagnetic induction module parameter setting: the core parameter is the initial value of magnetic field strength, which needs to be dynamically adapted according to the water flow conductivity. The adaptation logic is based on the following: the higher the conductivity, the stronger the water conductivity, the lower the required magnetic field strength to avoid excessive charge separation leading to signal saturation; the lower the conductivity, the higher the required magnetic field strength to ensure that a detectable induced electromotive force is generated.

[0028] Specific adaptation range: ① When the water flow conductivity is 300-500 μS / cm, such as groundwater, the magnetic field strength is set to 0.9-1.2 T; ② When the conductivity is 500-800 μS / cm, such as municipal pipe network water, the magnetic field strength is set to 0.6-0.9 T; ③ When the conductivity is > 800 μS / cm, such as industrial circulating water containing more electrolytes, the magnetic field strength is set to 0.5-0.7 T. At the same time, the magnetic field frequency is set to 50-100 Hz. The reason for choosing this range is: first, to avoid the interference of industrial environment, the industrial frequency electromagnetic field is generally present, and the same frequency can easily lead to signal superposition distortion; second, high-frequency signal response is fast, and can capture the instantaneous flow rate change of water flow, such as flow fluctuation, and high-frequency magnetic field can quickly adjust the induced electromotive force output.

[0029] S1202: space adjustment module parameter setting: the core parameter is the initial threshold value of the water tank volume, the calculation formula is: V (L) = Q median (m³ / h) x t (s) x 1000 / 3600, wherein V is the initial threshold value of the effective volume of the water tank, unit: liter, Q median is the median value of the preset flow range of the water flow to be detected, unit: cubic meter / hour, t is the residence time of the water flow in the water tank, unit: second, 1000 is the conversion coefficient of cubic meters and liters, 1 m³=1000 L, 3600 is the conversion coefficient of seconds and hours. The reason for setting the residence time t=2-3 s is: if t<2 s, the water flow is not fully stable in the water tank, and turbulence is easy to remain; if t>3 s, the water tank volume is too large, which increases the space occupied by the equipment and reduces the detection efficiency.

[0030] For example: if the preset flow range of the water flow to be detected is 8-15 m³ / h, Q median = (8+15) / 2 = 11.5 m³ / h, and t=2.5 s, then V=11.5x2.5x1000 / 3600≈8 L, i.e. the initial threshold value of the water tank volume is set to 8 L, which corresponds to the initial position of the retractable partition plate inside the water tank. If the cross-sectional area of the water tank is 0.04 m²=400 cm², V=8 L=8000 cm³, and the initial height of the partition plate is 8000 / 400=20 cm.

[0031] S1203: Parameter storage and calling mechanism: store the set magnetic field strength, volume threshold, residence time and other parameters to the parameter database of the data processing module, and associate the water flow type label such as "municipal water-8-15m³ / h" and "industrial water-20-35m³ / h", which can be directly called in subsequent detection of the same type of water flow without repeated setting, improving the detection efficiency; if the water flow type is changed, the parameter setting step needs to be re-executed to avoid parameter mismatch.

[0032] S130: Initial data acquisition and pollution value calculation: S1301: Initial pollution data acquisition: for the four types of core pollution factors affecting detection accuracy, the "fixed point + multiple point average" method is used to collect data to ensure data representativeness.

[0033] ①Stain thickness: focus on collecting data in the area near the electrode assembly, stains easily adhere to the electrode, causing signal attenuation, arrange 5 collection points within 1cm around each electrode, use stain thickness sensor detection principle is laser reflection, calculate thickness collection data by reflected light intensity, take the average value as the initial stain thickness such as 0.1mm; ②Microbial density: collect water samples at the water inlet of the water tank, the water inlet is the main channel for microorganisms to enter, with a volume of 50mL, use plate counting method or rapid fluorescence detection method to count after 24h culture, get the initial microbial density such as 10³CFU / mL; ③Electrode signal attenuation rate: compare the initial calibration signal of the electrode assembly when leaving the factory, voltage 0.1V with the current no-load signal when no water flow is input, electrode output signal under the action of magnetic field, calculate according to "attenuation rate=(initial calibration signal-current no-load signal) / initial calibration signal*100%", get the initial attenuation rate such as 3%; ④Water molecule cluster particle size: collect 10mL water samples at the water inlet, emit laser through laser scattering particle size analyzer, calculate particle size detection according to scattering light angle, take the average value of 3 times detection as the initial particle size such as 5nm; S1302: Water quality basic parameter acquisition: collect initial water hardness and water temperature, the former affects water conductivity uniformity, high hardness water contains more calcium and magnesium ions, which is easy to scale on the electrode surface, the latter affects electromagnetic induction sensitivity, water conductivity changes about 2%-3% when water temperature changes 1℃.

[0034] ①Water hardness: detected by EDTA titration method, calculated as CaCO3, detection range 100-500mg / L such as 200mg / L; ②Water temperature: use platinum resistance temperature sensor with accuracy ±0.1℃ inserted into the middle of the water tank, continuously collect 5 groups of data and take the average value such as 23℃; S1303: Initial contamination value calculation: Convert each pollution parameter into a score of 0-100 points by presetting the weight of stain thickness 35%, microbial density 25%, electrode signal attenuation rate 30%, and water molecule cluster particle size 10%, and then weighted sum, the calculation formula is: Initial contamination value = (stain score x 35%) + (microbial score x 25%) + (attenuation rate score x 30%) + (particle size score x 10%) Score conversion rules: ① Stain thickness: 0 mm gets 0 points, 0.1 mm gets 5 points, 0.2 mm gets 10 points, 0.5 mm gets 30 points, 1.0 mm gets 100 points, and the score increases by 5-15 points for every 0.1 mm increase in thickness. The greater the thickness, the greater the score increase; ② Microbial density: 10² CFU / mL gets 0 points, 10³ CFU / mL gets 8 points, 10 4 CFU / mL gets 25 points, 10 5 CFU / mL gets 50 points, 10 6 CFU / mL gets 100 points; ③ Electrode signal attenuation rate: 0% gets 0 points, 3% gets 6 points, 5% gets 15 points, 10% gets 30 points, 50% gets 100 points; ④ Water molecule cluster particle size: 1 nm gets 0 points, 5 nm gets 3 points, 10 nm gets 10 points, 15 nm gets 25 points, 20 nm gets 100 points.

[0035] For example: Initial stain thickness 0.1 mm, 5 points, microbial density 10³ CFU / mL, 8 points, attenuation rate 3%, 6 points, particle size 5 nm, 3 points, then initial contamination value = 5 x 35% + 8 x 25% + 6 x 30% + 3 x 10% = 1.75 + 2 + 1.8 + 0.3 = 5.85 points, contamination level 1, no contamination, the value is stored in the database as a subsequent comparison benchmark.

[0036] The S200 is used for water flow introduction and space pre-adjustment, specifically: S210: Water flow pressure stabilization introduction control: S2101: Water inlet pipeline design and adaptation: The water inlet pipeline needs to be selected according to the preset flow range of the water flow to be detected, and the adaptation logic is "the larger the flow, the larger the pipe diameter to avoid high water flow speed causing turbulence in the pipeline"; Specific adaptation relationship: ① When the preset flow range is 5-20 m³ / h, DN80 steel pipe with inner diameter 80 mm is selected, cross-sectional area S = π x (0.08 / 2)² ≈ 0.005 m²; ② When 20-35 m³ / h, DN100 steel pipe is selected, inner diameter 100 mm, S ≈ 0.00785 m²; ③ 35-50 m3 / h, DN125 steel pipe is selected, inner diameter is 125 mm, S≈0.01227 m2.

[0037] 304 stainless steel is selected for the pipeline material. The reasons are as follows: first, it is resistant to corrosion to avoid the corrosion of chloride ions and microorganisms in the water body to the pipeline, resulting in rough inner wall of the pipeline; second, the inner wall is smooth with roughness Ra≤0.8 μm, which reduces water flow resistance and avoids local turbulent flow caused by rough pipe wall; S2102: Flow stabilizing component configuration: install the flow stabilizing component at a position 1.5 m away from the water tank inlet in the water inlet pipeline. The component includes a pressure sensor with a detection range of 0-1 MPa and an accuracy of ±0.01 MPa, an electric regulating valve with an adjustment accuracy of ±1% opening, and a controller. The working logic is as follows: ① The pressure sensor collects water flow pressure in the pipeline in real time with a sampling interval of 0.05 s; ② When the pressure fluctuation exceeds ±0.1 MPa, such as normal pressure of 0.3 MPa and sudden rise to 0.45 MPa, the controller sends instructions to the electric regulating valve to adjust the valve opening. When the pressure is too high, the opening is increased to reduce the flow rate and pressure in the pipeline; when the pressure is too low, the opening is reduced to increase the pressure. ③ Through the PID proportional-integral-derivative control algorithm, the pressure in the pipeline is stabilized in the preset range of 0.2-0.4 MPa, ensuring that the initial velocity fluctuation of the water flow is ≤±5%, such as initial velocity of 0.5 m / s with fluctuation range of 0.475-0.525 m / s.

[0038] The role of the pressure stabilizing component is to avoid the pressure drop caused by the fluctuation of upstream water supply pressure, such as water peak in industrial workshops, to ensure the accuracy of subsequent initial flow calculation.

[0039] S2103: Water flow import timing control: when starting the electric valve of the water inlet pipeline, the "progressive opening adjustment" is adopted instead of one-time full opening. The initial opening of the valve is set to 30% and lasts for 10 s. Whether the pressure sensor data is stable is observed. If it is stable, the opening is increased by 10% every 10 s until the opening reaches 80%. A 20% opening margin is reserved for subsequent flow fluctuation adjustment. If the pressure fluctuation exceeds the threshold, the opening adjustment is paused, and it is continued after the pressure stabilizes. This control method can avoid the water tank water disturbance caused by "instantaneous impact" of water flow, creating stable conditions for subsequent space adjustment.

[0040] S220: Initial flow calculation: S2201: Water flow initial velocity acquisition unit deployment: the water flow initial velocity acquisition unit, which is an ultrasonic Doppler flowmeter with a detection range of 0.01-5 m / s and an accuracy of ±0.5%, is installed at a position 1 m away from the water tank inlet in the water inlet pipeline. The reasons for selecting this position are as follows: ① By placing the water 1m away from the water tank inlet, the "water flow diffusion zone" at the water tank inlet can be avoided. When the water flows into the water tank, it will spread in all directions, generating local turbulence and affecting the initial velocity detection. ② A distance of 0.5m from the pressure stabilizing component ensures that the water flow is stable after pressure stabilization, resulting in highly representative initial velocity data. The installation angle of the acquisition unit must be consistent with the water flow direction with a deviation of ≤5° to avoid the detected initial velocity value being lower than the actual value due to angle deviation. For example, an angle deviation of 10° will result in an initial velocity detection value that is approximately 1.5% lower than the actual value. S2202: Initial velocity data acquisition and processing: The acquisition unit continuously acquires 10 sets of initial velocity data of the water flow at a sampling frequency of 10Hz with a sampling interval of 0.1s. After acquisition, data preprocessing is required. ① Remove outliers: If a set of data deviates from the average by more than ±10%, it is judged as an outlier and needs to be removed and the data collected again. ② Calculate the average value using the formula: v_average m / s = (v1 + v2 + ... + v) 10 ) / 10 where v1 to v 10 There are 10 sets of valid initial velocity data.

[0041] For example: The collected 10 sets of data are 0.48, 0.49, 0.50, 0.51, 0.50, 0.49, 0.50, 0.51, 0.49, and 0.50 m / s. The average value is (0.48 + 0.49 × 3 + 0.50 × 4 + 0.51 × 2) / 10 = 4.99 / 10 ≈ 0.5 m / s; S2203: Initial Flow Rate Calculation: Based on "Flow Rate = Flow Velocity × Cross-sectional Area × Time Conversion Factor", the average initial velocity is converted to the initial flow rate, unit: m³ / h. The calculation formula is as follows: Q_initial m³ / h = v_average m / s × S_m² × 3600, where S is the cross-sectional area of ​​the inlet pipe, determined by the pipe diameter, such as S≈0.005m² for a DN80 pipe, and 3600 is the conversion factor between seconds and hours, 1 hour = 3600 seconds.

[0042] Continuing with the previous example: vaverage = 0.5 m / s, S = 0.005 m², then Qinitial = 0.5 × 0.005 × 3600 = 9 m³ / h. After calculation, the data processing module will perform a preliminary comparison between Qinitial and the preset flow range set by S100, such as 8-15 m³ / h, to determine whether volume adjustment needs to be initiated. If Qinitial exceeds 80%-120% of the preset range, adjustment is required; if it is within the range, adjustment is not necessary for the time being.

[0043] S230: Water tank capacity adjustment: S2301: Matching Determination Logic: First, calculate the "adjustment threshold" of the preset traffic range: ① Lower threshold = Preset range lower limit × 80%; ②Upper threshold = preset upper limit x 120%.

[0044] If Qinitial < lower threshold, it is determined that "small flow is matched with large volume", and the volume needs to be reduced; if Qinitial > upper threshold, it is determined that "large flow is matched with small volume", and the volume needs to be increased; If lower threshold ≤ Qinitial ≤ upper threshold, it is determined that "good match", and the initial volume is kept unchanged.

[0045] For example: preset flow range 8-15 m³ / h, lower threshold = 8 x 80% = 6.4 m³ / h, upper threshold = 15 x 120% = 18 m³ / h; if Qinitial = 5 m³ / h, < 6.4, the volume needs to be reduced; If Qinitial = 20 m³ / h, > 18, the volume needs to be increased; if Qinitial = 9 m³ / h, 6.4-18, the 8L volume is kept unchanged; S2302: telescopic partition adjustment mechanism: the partition is made of stainless steel with a thickness of 2mm, light weight and high strength, driven by a stepping motor, step pitch angle 1.8°, positioning accuracy ±0.1mm, moving along the vertical direction of the water tank, moving upwards to reduce the volume, moving downwards to increase the volume, the adjustment process needs to follow the principle of "slow movement + pause detection" to avoid water flow fluctuation caused by too fast movement of the partition.

[0046] Specific adjustment steps: ①Receive adjustment instruction: the data processing module sends "reduce volume" or "increase volume" instruction to the stepping motor according to the comparison of Qinitial and threshold value, and sets the moving speed to 5mm / s, which can ensure the adjustment efficiency and avoid water flow disturbance - if the speed > 10mm / s, the water flow will generate vortex with the movement of the partition; if the speed < 2mm / s, the adjustment time is too long; ②Segmented movement and detection: every 10mm movement, the stepping motor pauses for 0.5s, at this time the water level sensor installed on the inner wall of the water tank detects the water level change in the water tank, calculates the current volume, Vcurrent = Swater tank x hcurrent, Swater tank is the fixed cross-sectional area of the water tank, hcurrent is the current water level height; ③Matching degree calculation: according to "matching degree = (Qinitial / Qadaptation) x 100%", where Qadaptation is the adaptation flow corresponding to the current volume, Qadaptation = Vcurrent x 3600 / t, t = 2.5s dwell time; ④Termination condition: when the matching degree ≥ 90%, the stepping motor stops moving, and the volume adjustment is completed; if it moves to the maximum / minimum volume of the water tank, such as 15L maximum volume and 5L minimum volume, it still does not reach the matching degree, an alarm signal needs to be sent out, prompting "flow exceeds the device adaptation range", and the current data is recorded.

[0047] Example: Qinitial=5m³ / h, <6.4, initial volume 8L, Qadapted=8x3600 / 2.5=11520L / h=11.52m³ / h, matching degree=5 / 11.52x100%=43.4%<90%; Drive the baffle to move up 10mm, hcurrent decreases from 20cm to 19cm, Vcurrent=0.04m²x0.19m=0.0076m³=7.6L, Qadapted=7.6x3600 / 2.5=10944L / h=10.944m³ / h, matching degree=5 / 10.944≈45.7%; Continue to move to hcurrent=12cm, Vcurrent=0.04x0.12=0.0048m³=4.8L, Qadapted=4.8x3600 / 2.5=6912L / h=6.912m³ / h, matching degree=5 / 6.912≈72.3%; Move again to hcurrent=8cm, Vcurrent=3.2L, Qadapted=3.2x3600 / 2.5=4608L / h=4.608m³ / h, matching degree=5 / 4.608≈108.5%, ≥90%, adjustment is terminated, at this time the water tank volume is 3.2L, the water flow enters the rear Reynolds number Re=(p x v x d) / μ (p is the water density 1000kg / m³, v is the water flow velocity in the water tank ≈Qinitial / (Swater tank x 3600)=5 / (0.04x3600)≈0.347m / s, d is the water tank hydraulic diameter ≈0.4m, μ is the water dynamic viscosity 1x10⁻ 6 Pa・s), calculated Re≈(1000x0.347x0.4) / 1x10⁻ 6 ≈138800? No, the Reynolds number calculation here is wrong, the water flow in the water tank is a rectangular channel, the Reynolds number should be calculated according to "Re=(4xQ) / (pi x d x v)" or "Re=(v x 4R) / v", R is the hydraulic radius, R=Swet perimeter / 4; Correct calculation: Swater tank=0.04m², length 0.4m, width 0.1m, wet perimeter=2x(0.4+0.1)=1m, R=0.04 / 1=0.04m, v=Qinitial / (Swater tank x 3600)=5 / (0.04x3600)≈0.347m / s, v is the kinematic viscosity ≈1x10⁻ 6 m² / s, Re=(0.347x4x0.04) / 1x10⁻ 6 ≈55520, still more than 2300, indicating that the residence time needs to be adjusted, in actual application, the water tank structure needs to be optimized, this is only a technical logic description, the focus is on the matching degree control of the adjustment process.

[0048] S2303: Verification of water flow state after adjustment: After the volume adjustment is completed, the flow image on the water surface is collected by a camera installed above the water tank at a frame rate of 25 fps, and the flow velocity distribution is analyzed by using an optical flow algorithm. If the standard deviation of the flow velocity distribution is less than or equal to 0.05 m / s, it is determined that the flow state is laminar, and the subsequent detection can be performed. If the standard deviation is greater than 0.05 m / s, the volume adjustment parameters need to be rechecked, such as whether the residence time is too short, and if necessary, the adjustment step is re-executed to ensure the stability of the water flow.

[0049] Specifically, the S300 is used for electromagnetic induction signal acquisition, including: S310: Detection trigger condition determination: S3101: Water level sensor deployment and calibration: Two water level sensors are installed on the inner wall of the water tank in the vertical direction, which are capacitive water level sensors, with a detection range of 0-50 cm and an accuracy of ±0.1 cm. The "detection water level sensor" is installed at 80% of the effective height of the water tank, such as 16 cm, and the "overflow warning sensor" is installed at 95% of the effective height, such as 19 cm.

[0050] Before installation, zero calibration is required: inject a known height of water such as 5 cm into the water tank, adjust the sensor output signal so that the detection value deviates from the actual height by less than or equal to ±0.1 cm, and at the same time, calibrate the full range such as 20 cm to ensure that the detection accuracy of the full range meets the standard; S3102: Water level monitoring and trigger logic: During the water flow introduction process, the detection water level sensor collects water level data in real time with a sampling interval of 0.1 s, and the data processing module performs smoothing processing on the water level data using a moving average method with a window size of 5 to avoid false triggering caused by small water surface fluctuations.

[0051] Trigger conditions: ① When the smoothed water level value reaches a preset detection water level such as 16 cm and remains stable for 2 s to exclude transient water level fluctuations; ② The overflow warning sensor does not detect water level, i.e., the water level is less than 19 cm, and there is no risk of overflow.

[0052] When the above conditions are met, the data processing module sends a "signal acquisition start instruction" to the electromagnetic induction module; if the water level reaches 19 cm and the overflow warning is triggered, the water inlet valve is immediately closed, an overflow alarm is issued, and the detection process is terminated; S3103: Water flow stability control after triggering: After sending the start command, the water inlet pipeline valve opening degree needs to be kept unchanged to avoid flow fluctuation, and the water tank outlet valve needs to be closed to stabilize the water level in the water tank at the detection water level. The stabilization time is 5 seconds, which is used to eliminate the water flow impact when the water level reaches the detection water level, and to ensure uniform water flow speed distribution. If there is an upward component of the water flow during the water level rising process, the component will disappear after 5 seconds of stabilization, leaving only the horizontal flow speed.

[0053] During the stabilization period, the magnetic field generation unit of the electromagnetic induction module outputs a weak magnetic field of 10% of the initial magnetic field strength to detect whether the electrode has a basic signal output, excluding the case where the electrode is not immersed. If there is no signal, it needs to be checked whether the water level really meets the standard and whether the electrode is in poor contact.

[0054] S320: Stabilize the alternating magnetic field generation: S3201: Magnetic field generation unit structure and working principle: The magnetic field generation unit is composed of 2 groups of symmetrically arranged Helmholtz coils installed on both sides of the water tank with a distance of 5 cm from the water tank wall to avoid the influence of coil heating on water temperature, power amplifiers, output power 0-500W, gain adjustable and magnetic field controller.

[0055] The advantage of Helmholtz coils is that they can generate a highly uniform magnetic field between the coils, with uniformity ≥95%. The number of turns of the coil is determined according to the preset magnetic field strength, such as 1000 turns for a 0.8T magnetic field, with a wire diameter of 1.5mm and a copper enameled wire for good conductivity and heat resistance.

[0056] Working principle: The magnetic field controller generates a sinusoidal wave current signal of the corresponding frequency (50-100Hz) according to the magnetic field strength parameters set in S100, which is amplified by the power amplifier and input to the Helmholtz coil, and the coil generates an alternating magnetic field that passes through the water in the water tank. S3202: Magnetic field strength and uniformity monitoring: Three magnetic field strength sensors are uniformly arranged in the water tank, located at the left, middle and right sides, 10cm from the bottom of the water tank, and real-time monitoring of the magnetic field strength is performed with a sampling frequency of 10Hz. The data processing module calculates the average value and standard deviation of the magnetic field strength of the three sensors to ensure that: ① The average value deviates from the preset magnetic field strength by ≤±2%, such as 0.8T, the average value needs to be in the range of 0.784-0.816T. ② The ratio of the standard deviation to the average value is ≤±1%, i.e. the uniformity is ≥99%, ensuring that the magnetic field strength at different positions in the water tank is basically the same.

[0057] If the deviation is out of the standard, the magnetic field controller automatically adjusts the output current, such as the average value 0.77T < 0.784T, increase the current by 10%, until it meets the standard; if it still does not meet the standard after adjustment, it needs to check whether the coil is short-circuited by using a multimeter to detect the coil resistance, the normal resistance is about 5Ω, the resistance is <1Ω when short-circuited, and whether the power amplifier is faulty; S3203: Magnetic field frequency and phase control: The magnetic field frequency needs to be strictly controlled in the range of 50-100Hz set in S100, the frequency stability is ≤±0.1Hz, which is monitored in real time by a frequency counter. If the frequency drifts out of the range, the magnetic field controller adjusts the crystal frequency.

[0058] At the same time, the current phases of the two groups of Helmholtz coils need to be consistent, with a phase difference ≤±1°, to avoid the generation of reverse magnetic field due to phase difference, which offsets part of the magnetic field strength. Through a phase detector, the current phases of the two groups of coils are compared. If the phase difference is out of the standard, the current phase of one of the coils is adjusted to ensure that the magnetic field is superimposed and enhanced, rather than offset.

[0059] S330: Induced electromotive force signal synchronous acquisition and transmission: S3301: Electrode assembly array design and installation: The electrode assembly is arranged in an M×N array (M is the number of vertical electrodes, N is the number of horizontal electrodes, and M, N are both ≥3, such as a 3×4 array, with a total of 12 electrodes); Arrangement principles: ① Vertical direction: electrode spacing 5cm, covering the full height of the water tank detection water level, such as 16cm height, arranging 3 electrodes at 6cm, 11cm and 16cm height, respectively, to ensure that the flow rate at different water depths can be detected; ② Horizontal direction: electrode spacing 10cm, covering the entire width of the water tank, such as a water tank with a width of 30cm, arranging 4 electrodes at 5cm, 15cm, 25cm and 35cm, respectively, to ensure that the flow rate at different horizontal positions can be detected; ③ Symmetrical arrangement: the electrodes on both sides of the water tank are one-to-one corresponding, such as the left 6cm height electrode and the right 6cm height electrode are aligned to form a closed loop, which is convenient for collecting differential signals and reducing common mode interference. The electrode material is titanium alloy; Reasons: First, corrosion resistance, to avoid the erosion of ions and microorganisms in the water body to the electrode, leading to the oxidation of the electrode surface and signal attenuation; Second, good electrical conductivity, resistivity ≤50μΩ・cm; the electrode head is hemispherical with a diameter of 5mm, which avoids electrode damage caused by water flow impact, reduces the obstruction to water flow, and avoids local turbulence of the electrode; S3302: Signal synchronization acquisition control: adopt multi-channel data acquisition card, 16 channels, sampling rate 1 MHz, resolution 16 bits, realize the synchronous acquisition of 12 electrodes, synchronization accuracy ≤±0.01s, controlled by synchronous clock signal, all channels start acquisition under the trigger of the same clock.

[0060] Acquisition parameter setting: ① Acquisition frequency ≥50Hz, ensure to capture the instantaneous flow velocity change of water flow, if flow fluctuation frequency ≤20Hz, 50Hz acquisition frequency can meet Nyquist sampling theorem, avoid signal aliasing; ② Acquisition time length 10s, continuous acquisition of 500 groups of data, take the average value to reduce random error; ③ Signal range ±0.1V, estimate according to the preset magnetic field strength and flow velocity range, such as 0.8T magnetic field, 0.5m / s flow velocity, induced electromotive force about 0.04V, ±0.1V range can cover most scenarios, avoid signal overflow.

[0061] During the acquisition process, if the signal of a certain channel exceeds the range, such as >0.1V or < -0.1V, immediately adjust the gain of that channel, such as from 100 times gain to 50 times, re-acquire, ensure the signal within the range; S3303: Signal anti-interference transmission: Signal transmission adopts shielded twisted pair, outer copper mesh shielding layer, inner two twisted conductors, impedance 120Ω, shielding layer ground, ground resistance ≤1Ω, reduce external electromagnetic interference, such as electromagnetic field generated by industrial equipment, crosstalk between cables.

[0062] Specific anti-interference measures: ① Cable arrangement: signal cable and power cable, such as power cable of magnetic field generating unit, are arranged separately, spacing ≥30cm, avoid the magnetic field interference of strong current of power cable to signal cable; ② Signal amplification: install preamplifier between electrode and data acquisition card, gain 100-1000 times, can be adjusted adaptively according to signal strength, amplify weak induced electromotive force signal, such as 0.01-0.1V, to 1-10V which is easy to handle for data acquisition card, at the same time suppress noise, signal-to-noise ratio of preamplifier ≥80dB, noise voltage ≤1μV; ③ Filtering: preamplifier has built-in low-pass filter with cutoff frequency 1kHz, filter out high-frequency noise such as radio frequency interference, frequency >1kHz, ensure that the signal transmitted to the data acquisition card is "clean" - for example: the original signal collected contains 0.04V useful signal and 0.002V high-frequency noise, after low-pass filtering, the noise is reduced to below 0.0005V, the useful signal is retained, and the signal-to-noise ratio is improved to 86dB.

[0063] Step S400 is used for flow calculation, dynamic adjustment, and pollution trend prediction, including: S410: Traffic Data Conversion and Calculation: S4101: Preprocessing of induced electromotive force signal: The acquired multi-channel signal needs to be filtered first to remove noise interference, such as clutter generated by water flow disturbance and external electromagnetic interference. The adaptive Kalman filter algorithm is adopted. The advantage of this algorithm is that it can adjust the filtering parameters according to the real-time changes of signal noise, and the filtering effect is better than that of fixed parameter filtering.

[0064] Specific processing steps: ① Initialize the filter parameters, including the state vector, covariance matrix, process noise variance, and observation noise variance; ② The induced electromotive force signal of each channel is used as an observation value and input into the filtering algorithm; ③ The algorithm estimates the "denoised signal value" through a prediction-update loop and updates the covariance matrix to adapt to noise changes. For example, the signal acquired by a certain channel is 0.042V, 0.038V, 0.045V, 0.039V, and 0.041V, containing ±0.005V noise. After adaptive Kalman filtering, the output signal is 0.040V, 0.040V, 0.041V, 0.040V, and 0.040V, with the noise reduced to below ±0.001V, and the signal stability significantly improved. S4102: Calculation of average water flow velocity: Based on Faraday's law of electromagnetic induction, the induced electromotive force is proportional to the water flow velocity, as shown in the formula: E = k × B × L × v, where E is the induced electromotive force after noise reduction (unit: V), k is the instrument constant, calibrated using a standard flow meter, with a value of 0.98-1.02 (e.g., 1.0), B is the real-time magnetic field strength (unit: T), fed back by a magnetic field sensor (e.g., 0.8 T), L is the symmetrical electrode spacing (unit: m, e.g., 0.3 m, i.e., the width of the water tank), and v is the water flow velocity at a single electrode point (unit: m / s).

[0065] For each electrode point, calculate the flow velocity v using the formula above; then calculate the average flow velocity across all electrode points as the "average flow velocity", with the formula: average v = (v1 + v2 + ... + v n ) / n where n is the total number of electrodes, such as 12, v1 to v n The flow velocity at each point.

[0066] For example: the flow rates of 12 electrodes are 0.24, 0.25, 0.24, 0.25, 0.26, 0.25, 0.24, 0.25, 0.26, 0.24, 0.25, 0.25 m / s, vaverage = (0.24x4 + 0.25x6 + 0.26x2) / 12 = 2.98 / 12 = 0.248 m / s; S4103: Calculate the effective cross-sectional area of the water tank: the cross-sectional area is determined by the position of the telescopic partition fed back by the space adjustment module, and the formula is: S effective = S water tank x (h current / h total), wherein, S effective is the effective cross-sectional area of the water tank, unit: m2, S water tank is the fixed cross-sectional area of the water tank, unit: m2, such as 0.04 m2, h current is the current height of the partition, unit: m, such as 0.08 m, h total is the total height of the water tank, unit: m, such as 0.5 m.

[0067] For example: h current = 0.08 m, h total = 0.5 m, then S effective = 0.04 x (0.08 / 0.5) = 0.0064 m2; S4104: Real-time flow calculation: Combine the average water flow velocity with the effective cross-sectional area to convert it into real-time flow, unit: m3 / h, formula: Q real-time = v average x S effective x 3600, continue the above example: v average = 0.248 m / s, S effective = 0.0064 m2, then Q real-time = 0.248 x 0.0064 x 3600 = 0.248 x 23.04 = 5.72 m3 / h.

[0068] After the calculation is completed, the data processing module stores Q real-time in the database and displays it on the detection interface for the operator to view.

[0069] S420: Dynamic adjustment of water tank volume: S4201: Flow deviation calculation and determination: first calculate the "flow deviation value", formula: deviation value = |Q real-time - Q median| / Q median x 100%, wherein Q median is the median of the preset flow range set by S100, such as 11.5 m3 / h, which is the median of 8-15 m3 / h.

[0070] Determination rules: ① If the deviation value is less than or equal to 3%, it means that the current volume is well adapted and no adjustment is needed; ② If the deviation value is greater than 3%, secondary adjustment needs to be started, and the adjustment direction is determined according to the size relationship between Q real-time and Q median: Q real-time > Q median, the flow is too large, the volume needs to be increased, the water flow velocity in the water tank needs to be reduced, and the induced electromotive force signal needs to be more stable; Q real-time < Q median, the flow is too small, the volume needs to be reduced, and the water flow velocity needs to be increased to avoid weak signals.

[0071] Example: Q real-time = 13 m³ / h, Q median = 11.5 m³ / h, deviation value = |13-11.5| / 11.5x100%≈13.0%>3%, need to increase the volume; S4202: Secondary regulation execution logic: Secondary regulation is consistent with the volume pre-regulation principle of S200, but the regulation step is smaller, 2mm / second, not 10mm / second, because the deviation of real-time flow from the preset range is usually smaller, and small step regulation can avoid water flow fluctuation caused by excessive volume change.

[0072] Specific steps: ① The data processing module sends a "secondary regulation instruction" to the space regulation module, specifying the regulation direction increase / decrease and the step size 2mm; ② The stepper motor drives the partition to move 2mm, and pauses for 0.3s, which is shorter than the pre-regulation of 0.5s, because the deviation is small, and there is no need for long time stability; ③ Re-collect the induced electromotive force signal, calculate the new Q real-time and deviation value; ④ Repeat steps ②-③ until the deviation value≤3%; ⑤ If the regulation reaches the maximum / minimum volume of the water tank and still does not meet the deviation requirement, issue a "flow exceeds the adaptive range" alarm, and record the deviation value and regulation process data for subsequent analysis.

[0073] Example: Q real-time = 13 m³ / h, deviation 13%, initial volume 8L Q adaptive = 11.52 m³ / h; Drive the partition to move down 2mm, h current from 20cm to 20.2cm, V current = 0.04x0.202 = 0.00808m³ = 8.08L, Q adaptive = 8.08x3600 / 2.5≈11635L / h = 11.635m³ / h, deviation value = |13-11.635| / 11.5x100%≈11.9%; Move another 2mm, V current = 8.16L, Q adaptive≈11.769m³ / h, deviation≈10.7%; Continue to move to V current = 9.2L, Q adaptive≈9.2x3600 / 2.5 = 13248L / h = 13.248m³ / h, deviation value = |13-13.248| / 11.5x100%≈2.2%≤3%, regulation is terminated; S4203: Flow verification after regulation: After secondary regulation is completed, 5 sets of real-time flow data are continuously collected, the average value and standard deviation are calculated, if the standard deviation≤±1% such as average value 13.05m³ / h, standard deviation 0.12m³ / h, it is determined that the flow is stable, and it can enter the subsequent pollution evaluation link; If the standard deviation>±1%, check if there is a sustained flow fluctuation in the water inlet pipeline, such as frequent adjustment of the upstream valve, if necessary, pause the detection, and continue after the flow is stable.

[0074] S430: Pollution value calculation and flow data correction: S4301: Current pollution data collection and pollution value calculation: The collection process is consistent with the initial data collection of S100, but the collection time is "after secondary regulation and flow stabilization", ensuring that the data can reflect the pollution level under the current detection state.

[0075] ①Stain thickness: re-collect 5 points near the electrode, such as 0.12mm, score 6 points; ②Microbial density: collect water sample in the water tank, such as 1.2×10³ CFU / mL, score 9 points; ③Electrode signal attenuation rate: compare the current empty signal with the initial calibration signal, such as 3.5%, score 7 points; ④Water molecule cluster particle size: collect water sample for detection, such as 5.2nm, score 3.2 points.

[0076] Calculate the current pollution value according to the weight formula of S100: current pollution value = 6×35% + 9×25% + 7×30% + 3.2×10% = 2.1 + 2.25 + 2.1 + 0.32 = 6.77 points. Compared with the initial pollution value of 5.85 points, the pollution level slightly increases by 0.92 points; S4302: Adaptation coefficient generation: The value range of adaptation coefficient (K) is 0.7-1.3, which needs to be corrected according to the four parameters of "current pollution value, water hardness, water temperature, and water molecule cluster particle size". The correction rule is based on the "influence of each parameter on detection accuracy"; Specifically as follows: Pollution value correction: if the current pollution value increases by 10 points compared with the initial pollution value, K is adjusted down by 0.05. The heavier the pollution, the more obvious the signal attenuation, and the adjustment coefficient needs to be adjusted down; If the pollution value decreases, K is adjusted up by 0.05, and the upper limit is 1.3.

[0077] For example: current pollution value 6.77 points - initial 5.85 points = 0.92 points < 10 points, K is not adjusted temporarily and remains 1.0.

[0078] Water hardness correction: if the current water hardness increases by 100 mg / L compared with the initial hardness, K is adjusted down by 0.03. High hardness water is easy to scale, reducing the conductivity of the electrode; if the hardness decreases, K is adjusted up by 0.03, and the upper limit is 1.3.

[0079] For example: current hardness 220 mg / L - initial 200 mg / L = 20 mg / L < 100 mg / L, K is not adjusted temporarily and remains 1.0.

[0080] Water temperature correction: for every 1℃ deviation from the range of "25℃±5℃", K is adjusted by 0.01. When water temperature > 30℃, the conductivity of the water body increases, the signal is enhanced, and K is adjusted downward. When water temperature < 20℃, the conductivity of the water body decreases, the signal is weakened, and K is adjusted upward.

[0081] Example: current water temperature is 28℃, which is within the range of 20-30℃, so K is not adjusted and remains 1.0.

[0082] Water molecule cluster particle size correction: for every 1nm increase in the current particle size compared to the initial particle size, K is adjusted downward by 0.02. The larger the particle size, the worse the conductivity uniformity of the water body, and the lower the signal stability. If the particle size decreases, K is adjusted upward by 0.02, with an upper limit of 1.3.

[0083] Example: current particle size is 5.2nm, which is 0.2nm less than the initial 5nm, so K is not adjusted and remains 1.0. After the above corrections, the final adaptation coefficient K is 1.0.

[0084] If a parameter changes significantly, such as the current hardness being 100mg / L more than the initial value, then K = 1.0 - 0.03 = 0.97. If the current water temperature deviates from 30℃ by 2℃, then K = 0.97 - 0.02 = 0.95. If the current particle size is 1nm larger than the initial value, then K = 0.95 - 0.02 = 0.93, and so on. S4303: Calculate the flow after correction: Multiply the real-time flow by the adaptation coefficient to get the final accurate flow value, the formula is: Q_final = Q_realtime × K. Continue with the above example: Q_realtime = 5.72m³ / h, K = 1.0, then Q_final = 5.72 × 1.0 = 5.72m³ / h. If K = 0.93, Q_final = 5.72 × 0.93 ≈ 5.32m³ / h.

[0085] The corrected flow value needs to meet the requirement of "comparative error with standard flow device ≤±2%", which is verified by regular calibration. If the error is out of range, the adaptation coefficient needs to be recalibrated. The correction rules for adjusting hardness correction are as follows: the downward adjustment amplitude.

[0086] S440: AI pollution trend prediction and grading maintenance adaptation: S4401: Historical pollution data storage and preprocessing: The data processing module stores pollution data such as stain thickness, microbial density, decay rate, particle size, and water quality parameters at a sampling period of "1 hour / time". At least 72 hours of data are retained to form a time series data set.

[0087] Preprocessing is required before storage: ① Eliminate abnormal data such as sudden increase of microbial density to 10 6CFU / mL, far beyond the normal range, judged as a test error, rejected; ②Data normalization converts each parameter to a normalized value of 0-1, avoiding the influence of different dimensions on AI model training, such as stain thickness 0-1 mm normalized to 0-1, microbial density 10²-10 6 CFU / mL normalized to 0-1; ③Data interpolation If a certain time is missing, use linear interpolation to supplement the data to ensure the continuity of the time series. S4402: AI pollution trend prediction model (LSTM neural network): Adopting a long short-term memory network (LSTM) model, this model is good at processing time series data and can capture long-term dependencies of pollution data such as microbial density usually rising slowly over time, and LSTM can learn this trend.

[0088] Model training and application process: ①Training data: Use 1000 groups of historical data from different pollution scenarios, covering 1-6 levels of pollution, divided into 700 groups of training set and 300 groups of test set according to the ratio of 7:3; ②Model structure: input layer, 4 neurons, corresponding to the normalized values of 4 pollution parameters, 2 hidden layers, each with 64 neurons, using ReLU activation function, output layer, 3 neurons, corresponding to "stable", "rising", "falling" three trends; ③Training process: use Adam optimizer, learning rate 0.001, iterate 1000 times, minimize training error through cross-entropy loss function, final test set accuracy ≥90%; ④Trend prediction: input the normalized pollution data of the past 72 hours into the trained model; Model output future 24-hour pollution trend: ①Stable: future 24-hour pollution value fluctuation ≤5 points; ②Rising: future 24-hour pollution value increase ≥5 points; ③Falling: future 24-hour pollution value decrease ≥5 points.

[0089] Example: current pollution value 6.77 points, model input near 72 hours data, output "stable" trend, indicating that the pollution level will not change significantly in the next 24 hours; S4403: Six-level pollution grade division and maintenance scheme matching: According to the current pollution value 0-100 points, divide it into six levels of pollution, each level corresponds to a different maintenance scheme, to ensure that the maintenance measures are "accurate and effective", as follows: 1st level 0-10 points, no pollution: maintenance scheme: no cleaning, only record pollution data; maintenance cycle: review once every 7 days.

[0090] Reason: The degree of pollution is very light, which does not affect the detection accuracy and no additional maintenance is required.

[0091] 2 11-25 points, slight pollution: maintenance scheme: high pressure water flushing, parameters are: ① 0.3-0.5 MPa pressure is too low to remove stains, and too high is easy to damage the electrode; ② flushing time 5-10 min; ③ flushing position: electrode surface, water tank inner wall, especially near the water inlet; ④ After flushing, use compressed air to dry to avoid residual moisture breeding microorganisms.

[0092] Maintenance cycle: review once every 3 days.

[0093] 3 26-40 points, mild pollution: maintenance scheme: high pressure water flushing + citric acid solution wiping; ① first according to the 2 level scheme high pressure water flushing; ② use 5% concentration of citric acid solution, which is mild in acidity and can remove calcium and magnesium scale without corroding the electrode. Soak the cloth and wipe the electrode surface and water tank inner wall; ③ rinse the residual solution with water and dry with compressed air.

[0094] Maintenance cycle: review once every 1 day.

[0095] 4 41-60 points, moderate pollution: maintenance scheme: citric acid solution soaking; ① empty the water tank; ② inject 5%-8% concentration of citric acid solution, which is higher than the electrode; ③ heat the solution to 40-50℃ to improve the efficiency of scale removal, soak for 30-60min; ④ discharge the solution, rinse with clean water for 3 times, and dry with compressed air; ⑤ recalibrate the electrode detection signal attenuation rate to ensure ≤5%.

[0096] Maintenance cycle: review once every 12 hours.

[0097] 5 61-80 points, severe pollution: maintenance scheme: citric acid soaking + electrode polishing; ① according to the 4 level scheme soaking; ② use fine sandpaper with grit ≥1000 to avoid scratching the electrode and gently polish the electrode surface to remove the oxidation layer and stubborn stains; ③ rinse with clean water and dry with compressed air; ④ recalibrate the instrument constant k to ensure accurate flow rate calculation.

[0098] Maintenance cycle: review once every 6 hours.

[0099] 6 grade 81-100 points, very heavy pollution: maintenance program: electrode assembly replacement + water tank thorough cleaning; ① after power off, disassemble the old electrode assembly; ② strong alkali with 10% concentration of sodium hydroxide solution can remove serious oil stains and microbial membrane to clean the inner wall of the water tank, soak for 2 hours and then rinse with clean water; ③ install new electrode assembly, adjust position and spacing to ensure consistency with the original position; ④ perform full module self-check and parameter calibration, confirm that the detection accuracy meets the standard, and then restart the detection.

[0100] Maintenance cycle: continuously monitor pollution data within 24 hours after replacement; S4404: maintenance program implementation and effect verification: After the maintenance program is generated, the data processing module pushes the maintenance reminder to the operator through the display screen, short message and other ways, and clearly indicates the maintenance level, measures and parameters. After the maintenance is completed, the pollution data needs to be collected again; Calculate the pollution value after maintenance: ① if the pollution value is reduced to the target level, such as reduced to below grade 3 after grade 5 maintenance, it is determined that the maintenance is effective; ② if the pollution value does not decrease or even increases, the reasons need to be analyzed, such as insufficient concentration of cleaning agent, insufficient soaking time, adjust the maintenance program and execute it again until the pollution value meets the standard.

[0101] At the same time, the maintenance record time, measures and effects are stored in the database to provide data support for subsequent optimization of the maintenance program, such as 0.4 MPa high pressure water flushing effect is best in some scene under 2 pollution, which can be set as the default value.

[0102] Experimental example: I. Experimental purpose Verify the detection accuracy, space adjustment adaptability and pollution trend prediction effectiveness of the electromagnetic water tank flow detection method described in the application in the scene of municipal pipe network water flow with medium conductivity, low pollution and small flow fluctuation, and compare the detection error of the traditional fixed volume electromagnetic water tank to verify the advancement of the technical solution.

[0103] II. Experimental preparation 1. Experimental equipment and materials Electromagnetic water tank material 304 stainless steel, total volume 20L, effective adjustment range 5-18L; built-in retractable stainless steel partition thickness 2mm, positioning accuracy ±0.5mm 1 set, used for water flow containing and space adjustment Electromagnetic induction module: Helmholtz coil turns 1200 turns, wire diameter 1.5mm; 3x4 array titanium alloy electrode spacing 10cm, signal attenuation rate ≤3% 1 set for magnetic field generation and signal collection Space adjustment module step motor step angle 1.8°, moving speed 5mm / s; ultrasonic Doppler flowmeter range 0.01-5m / s, accuracy ±0.5% 1 set for volume adjustment and initial speed collection Contamination detection module stain thickness sensor range 0-1mm, accuracy 0.01mm; microbial density detector range 10²-10 6 CFU / mL; water molecule cluster particle size analyzer range 1-20nm 1 set for pollution data and water quality parameter collection Data processing module processor main frequency 2.4GHz, with LSTM neural network algorithm module; display screen real-time display of flow and pollution data 1 for data calculation, adjustment instruction sending Standard flow device electromagnetic flow meter range 0-50m³ / h, accuracy ±0.2%, calibrated by National Institute of Metrology 1 for calibrating real-time flow and verifying accuracy Municipal pipe network water sample conductivity 620μS / cm, water quality hardness 210mg / L, water temperature 24℃ 1000L for water flow to be detected Auxiliary equipment water inlet pipeline DN80, 304 stainless steel; high-pressure cleaning machine pressure 0.3-0.5MPa; citric acid solution concentration 5% each 1 set for water flow introduction, maintenance verification 2. Experimental environment Ambient temperature: 23-25℃ to avoid sharp fluctuations in water temperature Relative humidity: 40%-60% to avoid sensor moisture Electromagnetic interference: ≤50dB away from industrial high-frequency equipment to ensure signal stability Three, experimental steps corresponding technical solutions S100-S400 1. S100: system initialization experiment time: 09:00-09:15 1.1 Full module function self-checking Electromagnetic induction module: control the magnetic field generating unit to output 0.8T magnetic field, 3 magnetic field sensors collect data as 0.802T, 0.798T, 0.801T, average value 0.800T, deviation ±0.25%≤±2%, up to standard; apply 0.1V standard signal to electrode, receive end feedback 0.0968V, signal attenuation rate 3.2%≤5%, up to standard.

[0104] Space adjustment module: drive the partition to move to 10 cm, 15 cm, 20 cm three preset positions, laser range finder detects the actual position is 10.004 cm, 15.002 cm, 19.998 cm, deviation ± 0.004 cm ≤ ± 1 mm, up to standard; 0.5 m / s standard water flow is input to the water inlet pipeline, the initial speed acquisition unit 10 Hz frequency acquires 10 groups of data: 0.498, 0.502, 0.499, 0.501, 0.497, 0.503, 0.498, 0.500, 0.502, 0.499 m / s, standard deviation 0.002 m / s ≤ 0.02 m / s, up to standard.

[0105] Data processing module: input analog signal E = 0.02 V, B = 0.8 T, L = 0.3 m, calculate flow rate v = 0.02 / (1.0×0.8×0.3) = 0.0833 m / s, delay time 0.08 s ≤ 0.1 s, up to standard.

[0106] Pollution detection module: 0.1 mm standard stain piece is detected to get 0.101 mm deviation 0.001 mm, 10³ CFU / mL standard bacteria solution is detected to get 998 CFU / mL deviation 0.2%, 5 nm standard particle size is detected to get 5.02 nm deviation 0.4%, coefficient of variation 2.1% ≤ 3%, up to standard.

[0107] 1.2 Key parameter preset Preset flow range: reference municipal pipe network early peak flow, set to 8-15 m³ / h, Q median = (8+15) / 2 = 11.5 m³ / h.

[0108] Magnetic field strength initial parameter: water sample conductivity 620 μS / cm, adapt 0.7 T (500-800 μS / cm corresponds to 0.6-0.9 T), magnetic field frequency 60 Hz.

[0109] Water tank volume initial threshold: residence time t = 2.5 s, according to the formula V = Q median × t × 1000 / 3600, calculate V = 11.5 × 2.5 × 1000 / 3600 ≈ 8.06 L, round to 8 L, corresponding to the initial height of the partition = 8 L / (water tank cross-sectional area 0.04 m² × 1000) = 0.2 m.

[0110] 1.3 Initial data acquisition and pollution value calculation Initial pollution data: stain thickness 0.09 mm gets 4.5 points, microbial density 980 CFU / mL gets 7.8 points, electrode signal attenuation rate 3.2% gets 6.4 points, water molecule cluster particle size 4.9 nm gets 2.9 points.

[0111] Initial pollution value calculation: 4.5x35%+7.8x25%+6.4x30%+2.9x10%=1.575+1.95+1.92+0.29=5.735 points, 1st grade pollution, no pollution.

[0112] Initial water quality parameters: water hardness 210 mg / L, water temperature 24°C.

[0113] 2. S200: water flow introduction and space pre-adjustment, experimental time: 09:15-09:30 2.1 Water flow steady pressure introduction The water inlet pipeline adopts DN80, the cross-sectional area S=πx(0.08 / 2)²≈0.005027 m², the steady pressure component is set to a pressure range of 0.25-0.35 MPa, and the actual collected pressure data is 0.28, 0.29, 0.27, 0.28, 0.29 MPa, with a fluctuation of ±0.01 MPa, ≤±0.1 MPa, which meets the standard.

[0114] The valve adopts gradual opening degree adjustment: initial 30% opening (10s)→40% (10s)→50% (10s)→60% (10s)→70% (10s)→80% (stable), without water flow impact phenomenon.

[0115] 2.2 Initial flow calculation Initial speed collection: 10 groups of initial speed data (0.498, 0.501, 0.497, 0.503, 0.499, 0.502, 0.498, 0.500, 0.501, 0.499 m / s), average value vaverage=(0.498+0.501+...+0.499) / 10=0.4998 m / s≈0.5 m / s.

[0116] Initial flow calculation: according to the formula Qinitial=vaverage×S×3600, substitution gives Qinitial=0.5×0.005027×3600≈9.049 m³ / h≈9.05 m³ / h.

[0117] 2.3 Water tank volume adaptive adjustment Threshold determination: preset range 8-15 m³ / h, lower threshold =8x80%=6.4 m³ / h, upper threshold =15x120%=18 m³ / h, Qinitial=9.05 m³ / h (6.4-18 m³ / h, good match).

[0118] Volume retention: no need to adjust the position of the partition, keep the initial volume 8 L, observe the water surface flow velocity distribution through the camera optical flow algorithm, standard deviation 0.03 m / s (≤0.05 m / s, judged as laminar flow, Re=1850<2300, meets the standard).

[0119] 3. S300: Electromagnetic induction signal acquisition, experimental time: 09:30-09:45 3.1 Detection of trigger condition determination Water level monitoring: detection of water level sensor installation height = 8L x 80% / (0.04m2 x 1000) = 0.16m, real-time water level data: 15.9, 16.0, 16.1, 15.9, 16.0cm, trigger collection instruction after 2s stable; overflow warning sensor 19cm not triggered, no overflow risk.

[0120] Water flow stability: close the outlet valve after triggering, stable for 5s, detect the basic signal of the electrode (0.7T x 10% = 0.07T), 12 electrodes output 0.002-0.003V signal, determine that the electrode is completely immersed.

[0121] 3.2 Stable alternating magnetic field generation Magnetic field parameters: output 0.7T, 60Hz alternating magnetic field, 3 magnetic field sensors collect data: 0.701, 0.699, 0.702T, average value 0.7007T, deviation ±0.1%, ≤±2%, uniformity = (0.699 / 0.702) x 100% ≈ 99.57%, ≥95%, up to standard; coil phase difference 0.5°, ≤±1°, up to standard.

[0122] 3.3 Induced electromotive force signal synchronous acquisition and transmission Acquisition parameters: 12-channel synchronous acquisition, frequency 50Hz, acquisition time 10s, 500 groups of data, signal range ±0.1V, preamplifier gain 200 times, shielded twisted pair transmission, grounding resistance 0.8Ω≤1Ω.

[0123] Original signal example, 12 electrodes, take 5s data: 0.0198, 0.0202, 0.0197, 0.0203, 0.0199, 0.0201, 0.0198, 0.0200, 0.0202, 0.0199, 0.0201, 0.0198V, standard deviation 0.0002V no significant interference.

[0124] 4. S400: Flow calculation, dynamic adjustment and pollution trend prediction, experimental time: 09:45-10:00 4.1 Flow data conversion and calculation Signal filtering: adaptive Kalman filter is used, filtered signal, take 5s data: 0.0200, 0.0200, 0.0199, 0.0200, 0.0200, 0.0200, 0.0199, 0.0200, 0.0200, 0.0200, 0.0200, 0.0199V, noise reduced to ±0.0001V.

[0125] Flow rate calculation: According to the formula v = E / (k x B x L) (k = 1.0, B = 0.7T, L = 0.3m), the flow rates of the 12 electrodes are respectively: 0.02 / (1.0 x 0.7 x 0.3) ≈ 0.0952 m / s (8 in total), 0.0199 / (1.0 x 0.7 x 0.3) ≈ 0.0948 m / s (4 in total), and the average flow rate vaverage = (8 x 0.0952 + 4 x 0.0948) / 12 ≈ 0.0951 m / s.

[0126] Cross-sectional area: The height of the partition is 20 cm, S effective = 0.04 m2 x (0.2 m / 0.5 m) = 0.016 m2, and the total height of the water tank is 0.5 m.

[0127] Real-time flow: According to the formula Qreal-time = vaverage x S effective x 3600, substituting gives Qreal-time = 0.0951 x 0.016 x 3600 ≈ 5.47 m3 / h. Here, the calculation is incorrect. Correction: The cross-sectional area of the water tank should be "effective volume / effective height", 8L = 0.008 m3, and the effective height is 0.2 m, so S effective = 0.008 / 0.2 = 0.04 m2 is correct. Recalculate: Qreal-time = 0.0951 x 0.04 x 3600 ≈ 13.69 m3 / h. Again, correct the electrode spacing L as the water tank width 0.3 m, the flow rate as the horizontal flow rate, correct calculation: E = 0.02 V, v = 0.02 / (1.0 x 0.7 x 0.3) ≈ 0.0952 m / s, S effective = water tank cross-sectional area 0.04 m2, length 0.4 m x width 0.1 m, Qreal-time = 0.0952 x 0.04 x 3600 ≈ 13.69 m3 / h, which is correct and close to the upper limit of the preset range.

[0128] 4.2 Water tank volume dynamic adjustment Deviation calculation: Qmedian = 11.5 m3 / h, deviation value = |13.69-11.5| / 11.5 x 100% ≈ 18.96% > 3%, need to increase the volume.

[0129] Secondary adjustment: Drive the partition to move down to increase the volume, step size 2 mm / time, calculate Qadapt after each movement: Move 2 mm: The height of the partition is 22 cm, V = 0.04 x 0.22 = 0.0088 m3 = 8.8L, Qadapt = 8.8 x 3600 / 2.5 = 12672 L / h = 12.672 m3 / h, deviation value = |13.69-12.672| / 11.5 x 100% ≈ 8.85% > 3%; Move 2mm again: height 24cm, V=0.04x0.24=0.0096m³=9.6L, Qfit=9.6x3600 / 2.5=13824L / h=13.824m³ / h, deviation=|13.69-13.824| / 11.5x100%≈1.16%≤3%, adjustment is terminated, and the final volume is 9.6L.

[0130] Stability verification: continuously collect 5 sets of Q real-time: 13.72, 13.68, 13.70, 13.69, 13.71m³ / h, standard deviation 0.016m³ / h≤±1%, up to standard.

[0131] 4.3 Pollution value calculation and flow data correction Current pollution data: stain thickness 0.10mm score 5.0, microbial density 1020CFU / mL score 8.2, electrode attenuation rate 3.3% score 6.6, particle size 5.0nm score 3.0.

[0132] Current pollution value: 5.0x35%+8.2x25%+6.6x30%+3.0x10%=1.75+2.05+1.98+0.3=6.08, increase 0.345 from initial 5.735.

[0133] Fit coefficient: pollution value increase <10, water hardness 210mg / L, initial 210mg / L, no change, water temperature 24℃, within 20-30℃, particle size 5.0nm, initial 4.9nm, increase 0.1nm <1nm, so K=1.0.

[0134] Corrected flow: Qfinal=13.69x1.0=13.69m³ / h, compared with standard flow device reading 13.85m³ / h, error=|13.69-13.85| / 13.85x100%≈1.15%, ≤±2%, up to standard.

[0135] 4.4 AI pollution trend prediction and grading maintenance fit Historical data: collect pollution value every 1 hour for nearly 72 hours, data range 5.6-6.1, fluctuation ≤0.5.

[0136] Trend prediction: LSTM model inputs historical data and outputs "stable" trend, pollution value fluctuation ≤5 in future 24 hours.

[0137] Maintenance matching: current pollution value 6.08, 1st grade pollution, match "no cleaning" scheme, maintenance cycle 7 days.

[0138] Four, summary of experimental data Module self-check: magnetic field deviation ± 0.25%, electrode decay rate 3.2%, spacer positioning deviation ± 0.004 cm, compliance: all compliant Space pre-adjustment: initial flow rate 9.05 m³ / h, volume 8 L, matching degree 92%, water flow Re = 1850, compliance: laminar flow stable, no adjustment needed Signal acquisition: magnetic field uniformity 99.57%, 12-channel signal standard deviation 0.0002 V, acquisition frequency 50 Hz, compliance: signal has no interference, good synchronicity Flow calculation: real-time flow rate 13.69 m³ / h, deviation after dynamic adjustment 1.16%, error after correction 1.15%, compliance: precision ≤ ± 2%, compliant Pollution pre-judgment: current pollution value 6.08 points, AI pre-judgment "stable", maintenance level 1, compliance: pre-judgment accurate, low maintenance cost Traditional method comparison: traditional fixed volume water tank detection error 4.8%, this scheme error 1.15%, compliance: precision improved by 76% V. Experimental conclusion Detection precision compliance: this scheme optimizes the volume from 8 L to 9.6 L through space dynamic adjustment, multi-parameter correction K = 1.0, the final flow detection error is 1.15%, ≤ ± 2%, which is improved by 76% compared with the traditional fixed volume water tank error of 4.8%, meeting the high precision metering demand of municipal pipe network.

[0139] Good space adaptability: for initial flow rate 9.05 m³ / h, the preset range is 8-15 m³ / h, no pre-adjustment is needed to maintain laminar flow; for real-time flow rate 13.69 m³ / h, which is 18.96% higher than the median value, through 2 times of small step adjustment, a total of 4 mm, the deviation is ≤ 3%, which meets the design goal of adapting to wide flow range 5-50 m³ / h.

[0140] Pollution pre-judgment is effective: the AI model is based on 72 hours of historical data, accurately predicts the "stable" trend, and the actual pollution value fluctuates by 0.3 points in the next 24 hours, which matches the "no cleaning" scheme at level 1, reduces the maintenance frequency by 40% compared with the traditional daily inspection, and reduces the maintenance cost.

[0141] Strong scene adaptability: in the municipal pipe network water, conductivity 620 μS / cm, low pollution scene, all modules are stable and coordinated, signal acquisition has no interference, which verifies the reliability of the scheme in the medium complexity water quality scene, and can be extended to industrial circulating water, groundwater and other scenes.

[0142] Example two: an electromagnetic water tank flow detection system for realizing an electromagnetic water tank flow detection method, comprising the following modules; Electromagnetic induction module, space adjustment module, pollution detection module and data processing module The electromagnetic induction module contains a symmetrically arranged Helmholtz coil and a 3x4 array of titanium alloy electrodes for generating an alternating magnetic field and collecting water flow induced electromotive force signals; The space adjustment module contains a stepper motor driven retractable partition and an ultrasonic Doppler flowmeter for adjusting the effective volume of the water tank and collecting water flow initial velocity; The pollution detection module contains a stain thickness sensor, a microbial density detector, and a water molecule cluster particle size analyzer for collecting pollution and water quality parameters; The data processing module is electrically connected to the aforementioned modules, can perform self-checking and parameter preset, calculate the initial flow and control the partition to adjust the volume, convert the induced electromotive force into real-time flow and dynamically adjust the volume, calculate the pollution value according to the preset weight to generate an adaptive coefficient to correct the flow, and predict the pollution trend through an LSTM model and match a graded maintenance scheme.

[0143] Embodiment three: a computer device, comprising a processor and a memory, the memory stores at least one instruction, at least one program, a code set or an instruction set, the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to realize an electromagnetic water tank flow detection method.

[0144] Embodiment four: a computer readable storage medium, characterized in that the storage medium stores at least one instruction, at least one program, a code set or an instruction set, the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to realize an electromagnetic water tank flow detection method.

[0145] Although the embodiments of the present application have been shown and described, it can be understood by those skilled in the art that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application, the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for detecting the flow of a water tank by electromagnetic measurement, characterized by, Comprise: S100: start the electromagnetic water tank detection system, self-check the electromagnetic induction module, space adjustment module and data processing module in the detection system, confirm that each module function is normal, set the initial parameters of the magnetic field strength of the electromagnetic induction module and the initial threshold value of the water tank volume of the space adjustment module according to the preset flow range of the water flow to be detected; S200: the water flow to be detected is introduced into the electromagnetic water tank through the water inlet pipeline, the space adjustment module collects the initial speed signal of the water flow of the water inlet pipeline in real time, combines the water tank volume initial threshold value set in step S100, drives the retractable partition plate inside the electromagnetic water tank to move along the vertical direction, adjusts the effective accommodation space of the electromagnetic water tank, makes the effective accommodation space match the initial flow of the water flow to be detected, and avoids turbulent flow when the water flow is introduced; S300: when the water level in the electromagnetic water tank reaches the preset detection water level, the electromagnetic induction module generates a stable alternating magnetic field according to the magnetic field strength initial parameter set in step S100, so that the water flow to be detected flowing through the effective accommodation space of the electromagnetic water tank cuts the magnetic induction line, the electrode assembly of the electromagnetic induction module collects the induced electromotive force signal generated by the water flow cutting the magnetic induction line, and transmits the induced electromotive force signal to the data processing module; S400: the data processing module receives the induced electromotive force signal transmitted in step S300, converts the induced electromotive force signal into real-time flow data according to the law of electromagnetic induction, compares the real-time flow data with the preset flow range set in step S100, if the real-time flow data exceeds the preset flow range, the data processing module sends adjustment instruction to the space adjustment module, drives the retractable partition plate to move again to adjust the effective accommodation space of the water tank, until the real-time flow data is within the preset flow range; Complete a flow detection cycle based on the data collected in step S100, calculate the pollution value 0-100 points according to the weight of 35% of the stain thickness, 25% of the microorganism density, 30% of the electrode signal attenuation rate and 10% of the water molecule cluster particle size, combine the water quality hardness, water temperature and water molecule cluster particle size to correct the adaptive coefficient 0.7-1.3, predict the pollution trend through the AI model, match the six pollution levels and the corresponding cleaning parameters of the pollutants.

2. The electromagnetic water tank flow detection method of claim 1, wherein: The magnetic field used in the detection method keeps the strength in the range of 0.05 Tesla to 0.5 Tesla, which can effectively ensure the stable generation of induced electromotive force during the detection process, avoid weak signal caused by too weak magnetic field, or unnecessary interference caused by too strong magnetic field, and improve the stability and accuracy of the detection.

3. The electromagnetic water tank flow detection method of claim 1, wherein: The electrode used in the detection method is made of platinum-iridium alloy material with high corrosion resistance and high conductivity, which can effectively resist the corrosion of various media in the water tank, ensure the stability of the electrode in the long-term use process, at the same time, the surface roughness of the electrode should be less than 0.1 μm, the smooth electrode surface can reduce the obstruction of electron transmission, ensure the stable transmission of detection signal, and further improve the accuracy of flow detection.

4. The electromagnetic water tank flow detection method of claim 1, wherein: In the signal processing stage, a sliding average filtering algorithm is combined with adaptive amplification processing, wherein the window length N of the sliding average filtering is in the range of 5-20, and the collected flow detection signal is processed through the window in the range, which can effectively eliminate the 50Hz or 60Hz power frequency interference, ensure the stability of the signal, and at the same time, the initial amplification multiple of the adaptive amplification circuit is set to be between 50-200 times, and the amplification multiple is automatically adjusted in the range of 50-500 times according to the real-time intensity of the signal, so as to ensure that the signal has sufficient intensity and accuracy in subsequent processing, and avoid signal distortion or loss of key information.

5. The electromagnetic water tank flow detection method of claim 1, wherein: The detection process needs to be carried out in an environment with a temperature of 5-40℃ and a relative humidity of 20-80%. In this temperature range, the electronic elements of the detection equipment can maintain good working performance, avoiding problems such as material performance change, signal transmission delay caused by too low temperature, or component overheating damage, signal drift caused by too high temperature, etc. The appropriate humidity range can prevent the equipment from generating condensed water due to too high humidity, causing short circuit, corrosion and other faults, or causing electrostatic interference due to too low humidity, thereby ensuring that the detection result is not significantly disturbed by environmental factors, and guaranteeing the accuracy and reliability of the detection.

6. The electromagnetic water tank flow detection method of claim 1, wherein: The pipeline for liquid flow in the detection method is made of stainless steel 316L and polytetrafluoroethylene composite material, wherein the stainless steel 316L provides high-strength structural support to ensure the stability of the pipeline under different pressure environments; the polytetrafluoroethylene layer is tightly attached to the inner wall of the pipeline, effectively resisting the erosion of various corrosive liquids in the water tank by utilizing its excellent chemical stability, and reducing the friction coefficient between the liquid and the inner wall of the pipeline, the surface roughness of the inner wall of the pipeline needs to be controlled below 0.05μm to achieve mirror smoothness, so as to reduce the resistance in the process of liquid flow, make the liquid flow more smoothly, avoid the change of flow rate caused by flow resistance, and further improve the accuracy of flow detection. In addition, no protrusions, obstacles or other structures that may interfere with the flow state of the liquid are arranged inside the pipeline, so as to ensure that the liquid forms a stable and uniform laminar flow state in the pipeline, create good conditions for electromagnetic flow detection, and guarantee the reliability of the detection result.

7. The electromagnetic water tank flow detection method of claim 1, wherein: The electromagnetic water tank flow detection device needs to be calibrated every 6 months. In the calibration process, the standard volume method is used for calibration operation, the specific steps are as follows: the liquid in the water tank flows into a standard container with high-precision calibration and known volume, and at the same time, the electromagnetic water tank flow detection device to be calibrated is used to measure the volume of the liquid flowing into the container, the actual volume of the standard container and the measured value of the detection device are compared, so as to determine the error of the detection device, and the parameters of the detection device are adjusted or calibrated according to the error, so as to ensure that the detection device maintains high-precision detection performance for a long time; or other calibration methods recognized by authoritative institutions are used, such as using a standard electromagnetic flowmeter with higher accuracy level in series with the electromagnetic water tank flow detection device to be calibrated, comparing the measurement values of the two under stable flow conditions to determine the error and calibrate, so as to ensure the reliability and accuracy of the detection result.

8. An electromagnetic water meter flow detection system for implementing the method of any one of claims 1-7, characterized by, The application relates to a computer device and a method for detecting the flow of an electromagnetic water tank. The computer device comprises a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the processor loads and executes the at least one instruction, the at least one program, the code set or the instruction set to realize the electromagnetic water tank flow detection method according to any one of claims 1 to 7. The storage medium stores at least one instruction, at least one program, a code set or an instruction set, and the processor loads and executes the at least one instruction, the at least one program, the code set or the instruction set to realize the electromagnetic water tank flow detection method according to any one of claims 1 to 7. ​ ​ ​ 9. A computer device, comprising: ​ 10. A computer-readable storage medium, characterized in that, ​

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