Intelligent and precise control method for ozone and ultraviolet combined disinfection of drinking water

Abstract

The present invention provides an intelligent and precise control method for combined ozone and ultraviolet disinfection of drinking water, relating to the fields of water treatment and automated control technology. The method comprises: constructing a three-dimensional dynamic model integrating the pipeline network topology, the volume of the ozone contact tank, and the geometric parameters of the ultraviolet reactor; using sensors to collect the inlet flow rate and the residual ozone concentration in the outlet in real time, and calculating the ozone demand index based on water quality characteristic parameters such as ultraviolet transmittance and chemical oxygen demand; dynamically adjusting the ozone dosage based on the ozone demand index and the residual ozone concentration to ensure a linear proportional relationship with the flow rate; controlling the irradiation power of multiple ultraviolet lamps based on the ultraviolet radiation equivalent to ensure the radiation dose per unit flow rate; and initiating a fault classification program to respond to abnormal pipeline pressure differences or ozone concentrations exceeding safety thresholds. Through intelligent and precise control, the present invention significantly improves the efficiency and safety of direct drinking water disinfection.

Description

Technical Field

[0001] The present invention relates to the technical field of water treatment and automatic control, and in particular to an intelligent and precise control method for ozone-ultraviolet combined disinfection of direct drinking water. Background Art

[0002] In the field of direct drinking water treatment, ozone and ultraviolet combined disinfection technology is widely used to improve water quality safety. However, existing technologies still have significant problems in the implementation process. The determination of ozone dosage usually relies on static empirical formulas, which fail to adapt to the dynamic changes of inlet flow and water quality parameters in real time, resulting in a disconnect between ozone dosage and actual demand, causing insufficient disinfection or waste of chemical agents. The regulation of ultraviolet radiation dose lacks a synergistic optimization mechanism with the ozone residual concentration, and cannot respond quickly when the flow fluctuates or the water quality changes suddenly, making the ultraviolet disinfection efficiency unstable and the radiation dose per unit flow insufficient.

[0003] Detection of abnormal pressure differences and excessive ozone concentrations in pipeline systems primarily relies on threshold alarms, which lack intelligent fault classification and tracing capabilities. This results in delayed responses to abnormal situations and reduced system reliability. The dynamic characteristics of the hydrodynamics are not fully considered, particularly the impact of changes in the Reynolds number on fluid mixing. Existing methods lack dynamic updates of three-dimensional models based on real-time fluid states, resulting in suboptimal ozone contact efficiency and UV radiation uniformity. The ozone attenuation process in water is not precisely modeled, and transmission time parameters are inaccurately obtained, impacting the accuracy of UV dose calculations. This problem is particularly exacerbated in long-distance pipelines.

[0004] The post-verification mechanism for disinfection effectiveness is weak, relying on offline laboratory testing. This leads to long feedback cycles, making it impossible to guide real-time adjustments to disinfection parameters and posing a risk of microbial resurgence. The system's modules exhibit poor coordination, with fragmented control logic for flow monitoring, ozone injection, and UV irradiation. This results in a slow overall response and makes it difficult to achieve truly intelligent and precise control. Summary of the Invention

[0005] In order to solve the technical problems in the existing technology of inaccurate dosage control, slow system response, untimely fault detection and unstable disinfection effect in ozone and ultraviolet combined disinfection, the present invention provides an intelligent and precise control method for direct drinking water ozone and ultraviolet combined disinfection.

[0006] The technical solutions provided by the present invention are as follows:

[0007] The intelligent and precise control method for ozone and ultraviolet combined disinfection of direct drinking water provided by the present invention comprises:

[0008] S1. Construct a three-dimensional dynamic model of the direct drinking water purification system, integrating the pipeline network topology, ozone contact tank volume data, and UV reactor geometry parameters;

[0009] S2. Real-time collection of water inlet flow data through flow sensors , real-time monitoring of residual ozone concentration at the outlet through dissolved ozone probe ;

[0010] S3. Based on the Calculate the ozone demand index based on water quality characteristic parameters ;

[0011] S4. According to the and Real-time calculation of UV radiation equivalent ;

[0012] S5. Dynamically adjust the ozone dosage of the ozone ejector ,make and and The product of is in linear proportion;

[0013] S6. Based on the Control the irradiation power of multi-power flow UV lamp , ensure that the UV radiation dose per unit flow is not less than ;

[0014] S7, when the 3D dynamic model detects abnormal pressure difference at the pipeline node or When safety thresholds are exceeded, a fault classification procedure is initiated and disinfection parameters are adjusted.

[0015] Furthermore, the S3 specifically includes:

[0016] S301. Obtaining water quality characteristic parameter ultraviolet transmittance and chemical oxygen demand ;

[0017] S302. Calculate the ozone demand index using the following formula :

[0018] ;

[0019] Where: A is the UV absorption correction factor, ranging from 0.5 to 1.2; B is the organic oxidation coefficient, ranging from 0.15 to 0.35.

[0020] Furthermore, the S4 specifically includes:

[0021] S401, measuring the transmission time t of water from the ozone injection point to the ultraviolet lamp area;

[0022] S402. Calculate the UV radiation equivalent using the following formula: :

[0023] ;

[0024] Where: C is the microbial inactivation constant, ranging from 1.2 to 2.5; D is the ozone decay rate, ranging from 0.05 to 0.2 per minute.

[0025] Furthermore, the updating of the three-dimensional dynamic model in S1 includes:

[0026] S101, based on real-time Calculating the Reynolds number :

[0027] ;

[0028] in is the density, is the flow rate, is the hydraulic diameter, is viscosity;

[0029] S102, when , activates turbulence mode and increases the model update frequency to twice the baseline value.

[0030] Furthermore, the S4 specifically includes:

[0031] S411. Obtaining UV transmittance and ozone synergistic factors , the ozone synergistic factor Values ​​range from 0.05 to 0.15 mg per liter;

[0032] S412. Calculate the UV radiation equivalent using the following formula :

[0033] ;

[0034] in: is the transmittance conversion coefficient, with a value range of 0.8 to 1.2, is the flow suppression constant, ranging from 0.1 to 0.3.

[0035] Furthermore, the S5 specifically includes:

[0036] S501, measuring the water flow rate in the pipeline , ejector pressure drop and water density ;

[0037] S502, control the gas injection amount of the ozone ejector by the following formula :

[0038] ;

[0039] in is the ejector structural constant.

[0040] Furthermore, the S6 specifically includes:

[0041] S601, set the UV lamp base power and minimum radiation equivalent threshold ;

[0042] S602, adjust the UV lamp power by the following formula :

[0043] ;

[0044] in Adjust the gain for power.

[0045] Furthermore, the fault classification procedure in S7 includes:

[0046] S701, collecting pipeline node pressure difference sequence , ozone concentration change rate and UV lamp current fluctuation rate ;

[0047] S702, inputting the collected data into the trained random forest classification model;

[0048] S703: Output the failure probability distribution of leakage, blockage, or sensor failure.

[0049] Furthermore, the fluid dynamics parameters in S102 include:

[0050] Reynolds number Calculated value;

[0051] Turbulence intensity Measured value;

[0052] Model update frequency satisfy:

[0053] ;

[0054] in is the minimum hydraulic unit volume of the system.

[0055] Furthermore, it also includes:

[0056] S8. Detect the adenosine triphosphate (ATP) content of the disinfected water sample by bioluminescence method;

[0057] S9, when the ATP detection value exceeds the preset threshold When The UV absorption correction factor A in the calculation is increased by 20 percent.

[0058] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0059] (1) In this invention, by constructing a three-dimensional dynamic model and integrating fluid parameters in real time, combined with a dual-parameter collaborative control mechanism of ozone demand index (ODI) and ultraviolet radiation equivalent (URE), precise dynamic matching of ozone dosage and ultraviolet radiation dose is achieved. Adaptive adjustment of ozone ejector dosage and UV lamp power based on flow rate and water quality changes solves the problem of disconnection between disinfection dosage and actual demand in traditional static control, significantly improving disinfection efficiency while reducing agent consumption, ensuring that the radiation dosage per unit flow rate meets the standard under different working conditions.

[0060] (2) In this invention, a fault classification program is linked to a three-dimensional model pressure differential anomaly monitoring mechanism. A random forest model is used to analyze multi-source data such as pipeline pressure differential sequences, ozone concentration gradients, and current fluctuations in real time to accurately identify fault types such as leakage, blockage, or sensor failure. Combined with a fluid state-driven model update strategy (such as Reynolds number-triggered turbulence mode), the system's abnormal response speed and operational reliability are significantly improved, fundamentally overcoming the hysteresis and misjudgment risks of traditional threshold alarms.

[0061] (3) In this invention, biological verification closed-loop control and fluid dynamics optimization are introduced. Real-time adenosine triphosphate (ATP) detection is fed back to the ODI parameter correction, and a three-dimensional model is simultaneously used to optimize ozone contact efficiency and UV radiation uniformity. This forms an intelligent closed-loop of "monitoring-control-verification-re-optimization", completely resolving the potential risks of disinfection effect fluctuations and microbial resurgence, and achieving a comprehensive improvement from device-level control to system-level stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0063] Figure 1 A flow chart of the intelligent and precise control method for ozone and ultraviolet combined disinfection of direct drinking water provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0064] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0065] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as an "exemplary" in the present invention should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner. Furthermore, in the embodiments of the present invention, "and / or" can mean both or either of the two.

[0066] In the embodiments of the present invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, when the distinction is not emphasized, the meanings they convey are the same. The terms "of," "corresponding," and "corresponding" may sometimes be used interchangeably. It should be noted that, when the distinction is not emphasized, the meanings they convey are the same.

[0067] In the embodiment of the present invention, sometimes the subscript is as follows It may be mistakenly written as a non-subscript form such as W1. When the difference is not emphasized, the meaning is the same.

[0068] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0069] Reference Manual Figure 1 , which shows a flow chart of the intelligent and precise control method for ozone and ultraviolet combined disinfection of direct drinking water provided by an embodiment of the present invention.

[0070] The embodiment of the present invention provides an intelligent and precise control method for ozone and ultraviolet combined disinfection of direct drinking water. The processing flow may include the following steps:

[0071] S1. Construct a three-dimensional dynamic model of the direct drinking water purification system, integrating the pipeline network topology, ozone contact tank volume data, and UV reactor geometric parameters.

[0072] In a possible implementation, updating the three-dimensional dynamic model in S1 includes:

[0073] S101, based on real-time Calculating the Reynolds number :

[0074] ;

[0075] in is the density, is the flow rate, is the hydraulic diameter, is viscosity;

[0076] S102, when , activates turbulence mode and increases the model update frequency to twice the baseline value.

[0077] In one possible implementation, the fluid dynamics parameters in S102 include:

[0078] Reynolds number Calculated value;

[0079] Turbulence intensity Measured value;

[0080] Model update frequency satisfy:

[0081] ;

[0082] in is the minimum hydraulic unit volume of the system.

[0083] It should be noted that when constructing the three-dimensional dynamic model in step S1, computer-aided design software is first used to establish an accurate geometric model of the piping system, including the diameter, length and connection method of all pipes. The volume data of the ozone contact tank is calculated by measuring the inner diameter and height of the tank with a laser rangefinder, accurate to the millimeter level. The geometric parameters of the UV reactor include the outer diameter of the quartz sleeve, the effective length of the lamp tube and the spacing between adjacent lamp tubes. These parameters are imported into the model after digitizing the engineering drawings. The model is divided into unstructured tetrahedral grids, and the minimum grid size is controlled within three percent of the volume of the minimum hydraulic unit of the system. The fluid dynamics simulation uses the k-omega turbulence model, and the calculation step size is set to 0.01 seconds.

[0084] Furthermore, when the 3D model is updated, the Reynolds number The parameters required for calculation are obtained as follows: density Real-time measurement using a vibrating tube density meter; flow rate Depend on Divide by the cross-sectional area of ​​the pipe; hydraulic diameter For circular pipes, take the inner diameter; for rectangular pipes, take twice the length and width divided by the length and width; viscosity Obtained by looking up the ASTM standard viscosity table according to the water temperature. When the value is greater than 4000, the turbulence mode is activated when the threshold is exceeded for 10 seconds, and the model update frequency is increased from the baseline 1 Hz to 2 Hz. Need to meet Greater than or equal to 2 times Divide by Constraints, Take the smallest container volume in the system, such as 0.2 liters of sensor bypass tubing.

[0085] In one possible embodiment, the ozone contact efficiency 16 ozone concentration monitoring points are arranged in the contact tank, and the coefficient of variation is obtained by calculating the ratio of the standard deviation of the concentration at each point to the average value. Equal to 1 minus the coefficient of variation. UV radiation uniformity The UV intensity is measured by a UV intensity probe mounted on a moving slide rail, which scans the reactor cross section at a speed of 5 mm per second. It is defined as the ratio of the maximum intensity to the minimum intensity minus 1. When it is lower than 0.92, the regulating valve opening increases in 5% steps; when Above 0.15, the UV lamp array is redistributed into a checkerboard activation pattern.

[0086] It should be noted that the 3D model mesh division setting fault tolerance mechanism: when the finite element calculation residual When the grid of high gradient area is automatically encrypted to 50% of the original size (such as the valve reduction), press Dynamically add artificial viscosity terms; if divergence is still present, activate the simplified turbulence model, switch the k-omega model to the mixing length model, and set the length scale to 1 / 10 of the hydraulic diameter of the pipe.

[0087] S2. Real-time collection of water inlet flow data through flow sensors , real-time monitoring of residual ozone concentration at the outlet through dissolved ozone probe .

[0088] It should be noted that when implementing step S2, the electromagnetic flowmeter is installed in the straight pipe section of the water inlet, and the length of the front straight pipe section is not less than 10 times the pipe diameter, and the length of the rear straight pipe section is not less than 5 times the pipe diameter to ensure the flow measurement accuracy. Data is collected 10 times per second and transmitted via the Modbus RTU protocol. The dissolved ozone probe, a membrane electrode sensor, is installed 2 meters downstream of the water outlet. The probe maintains a surface velocity of at least 0.3 meters per second and outputs a residual ozone concentration (CO3) value every 2 seconds, covering a measurement range of 0 to 5 mg / L.

[0089] S3. Based on the Calculate the ozone demand index based on water quality characteristic parameters .

[0090] In a possible implementation, S3 specifically includes:

[0091] S301. Obtaining water quality characteristic parameter ultraviolet transmittance and chemical oxygen demand ;

[0092] S302. Calculate the ozone demand index using the following formula :

[0093] ;

[0094] Where: A is the UV absorption correction factor, ranging from 0.5 to 1.2; B is the organic oxidation coefficient, ranging from 0.15 to 0.35.

[0095] It should be noted that step S3 executes the ozone demand index Before calculation, it is necessary to obtain water quality characteristic parameters. The chemical oxygen demand was continuously monitored using an online UV spectrophotometer at a wavelength of 254 nm with an optical path length set to 10 mm, and the average value was recorded every 5 minutes. The potassium permanganate index method was used for determination. 50 ml of water sample was collected every 30 minutes by an automatic sampler, and the water sample was reacted under acidic conditions at 120 degrees Celsius for 30 minutes before colorimetric determination. Computing module receives and After the data is received, perform the following operations: first calculate 100 divided by The square root value of is multiplied by the UV absorption correction factor A; at the same time, calculate The natural logarithm of the organic matter oxidation coefficient (B) is multiplied by the organic matter oxidation coefficient (B). The two products are then added together. The A value is dynamically adjusted between 0.5 and 1.2 depending on the raw water type, and the B value is determined to be within the range of 0.15 to 0.35 through regression analysis of historical organic matter removal rate data.

[0096] S4. According to the and Real-time calculation of UV radiation equivalent .

[0097] In a possible implementation, S4 specifically includes:

[0098] S401, measuring the transmission time t of water from the ozone injection point to the ultraviolet lamp area;

[0099] S402. Calculate the UV radiation equivalent using the following formula: :

[0100] ;

[0101] Where: C is the microbial inactivation constant, ranging from 1.2 to 2.5; D is the ozone decay rate, ranging from 0.05 to 0.2 per minute.

[0102] In a possible implementation, S4 further includes:

[0103] S411. Obtaining UV transmittance and ozone synergistic factors , the ozone synergistic factor Values ​​range from 0.05 to 0.15 mg per liter;

[0104] S412. Calculate the UV radiation equivalent using the following formula :

[0105] ;

[0106] in: is the transmittance conversion coefficient, with a value range of 0.8 to 1.2, is the flow suppression constant, ranging from 0.1 to 0.3.

[0107] It should be noted that the water flow transmission time t in step S4 is measured using the ultrasonic time difference method. A pair of ultrasonic transducers are installed at the ozone injection point and the entrance to the UV lamp area. By measuring the time difference between the downstream and upstream propagation of the sound pulse, the average flow velocity is calculated based on the cross-sectional area of ​​the pipe, and the precise transmission time t is obtained by dividing the pipe length between the two points by the flow velocity. The calculation process is: first Divide by The intermediate variable is multiplied by the microbial inactivation constant, C. Next, calculate e minus D and multiply it by the power of t. Finally, multiply the two results together. The C value is set between 1.2 and 2.5 depending on the target pathogen, with higher values ​​for Bacillus subtilis and lower values ​​for Escherichia coli. The D value is calibrated through laboratory accelerated decay experiments, with a typical value of 0.12 per minute in pure water at 20 degrees Celsius.

[0108] It should be noted that two different technical paths are provided for calculating Ultraviolet Radiation Equivalent (URE). These two calculation methods are complementary solutions for different working conditions. Their application logic and implementation details are as follows:

[0109] The core application scenarios of the calculation methods provided by S401~S402 are applicable to the steady state of water flow (Reynolds number ) or ozone contact time t can be accurately measured. The advantage is that it is directly related to the ozone decay dynamics , suitable for conditions where ozone concentration changes slowly. The microbial inactivation constant C can be customized for the target pathogen (e.g., C=2.2 for Cryptosporidium and C=1.5 for Escherichia coli).

[0110] The implementation steps are as follows: the transmission time t is measured by the ultrasonic time difference method: ultrasonic transducer pairs are installed at the ozone injection point (A) and the UV lamp inlet (B) to measure the downstream propagation time of the sound pulse and countercurrent time , according to the formula Calculate the actual transmission time, where L is the length of the pipe between AB. Dynamic calibration of the ozone decay rate D: When the water temperature changes by more than ±2°C, start the laboratory simulation module, inject the current water sample into the constant temperature water tank, measure the ozone concentration half-life, and reversely calculate the D value.

[0111] The core application scenarios of the calculation methods provided by S411~S412 are applicable to high flow fluctuation conditions ( ) or UV transmittance Significant changes (such as sudden changes in turbidity). Ozone synergistic factors Used to quantify the ozone-UV synergistic disinfection effect. The advantage is that it uses the Sigmoid function Suppress radiation dose fluctuations caused by sudden changes in flow rate. Enhanced UV radiation compensation under high ozone concentrations.

[0112] Implementation steps for flow suppression constant Calibration: During the system debugging phase, the UV dose fluctuation was tested with a step flow rate (0.5, 1.0, 1.5 m³ / h) and fitted. Make the dosage deviation less than ±5%. Verification of synergistic effect: Through comparative experiments, it was determined that when The microbial inactivation rate is improved.

[0113] It should be noted that when the 3D model detects When the confidence level of t measurement is greater than 95%, the formulas provided in S401 and S402 are preferred. or If the value drops by more than 10% for 5 consecutive minutes, switch to the formula provided in S411-S412.

[0114] In one possible implementation, a data fusion strategy is implemented. Two formulas are calculated in parallel. If the difference in the results exceeds 15%, a verification process is triggered. This activates the biometric verification unit to verify whether the ATP test exceeds the standard. If so, the formula results provided by S11-S412 are used and the A value is increased. Otherwise, the formula results provided by S401-S402 are used.

[0115] S5. Dynamically adjust the ozone dosage of the ozone ejector ,make and and The product is in linear proportion.

[0116] In a possible implementation, S5 specifically includes:

[0117] S501, measuring the water flow rate in the pipeline , ejector pressure drop and water density ;

[0118] S502, control the gas injection amount of the ozone ejector by the following formula :

[0119] ;

[0120] in is the ejector structural constant.

[0121] It should be noted that step S5 adjusts the ozone dosage When the proportional-integral-derivative controller receives and The product of is used as the set value. The ozone generator adopts dielectric barrier discharge technology, and the power adjustment response time is less than 3 seconds. The control algorithm executes equal Multiply Multiply The relationship, The value is preset between 0.15 and 0.25 depending on the ejector type and is automatically calibrated once a week using outlet ozone concentration feedback.

[0122] Furthermore, the ejector structure constant It needs to be determined by gas-water two-phase flow calibration during the installation phase: select 15 calibration points in the flow rate range of 0.5~3m / s, and adjust the flow rate at each point and measure the actual ozone transfer efficiency ,according to After back-calculation, the median is taken as the final value after eliminating abnormal points that deviate from the mean by ±10%. The calibration process requires that the water temperature fluctuation does not exceed ±0.5℃ and the sampling frequency of the differential pressure sensor is ≥50Hz.

[0123] Furthermore, when the ozone ejector is controlled, the water flow rate in the pipeline The measurement is done by using a time difference ultrasonic flowmeter with an accuracy of 0.5%. The water density is measured using a silicon piezoresistive sensor with a range of -10 to +100 kPa. Online monitoring by nuclear radiation density meter. Gas injection amount When executing a formula calculation, first calculate 1.5 power, and then calculate Divide by The square root value of the ejector is multiplied by the ejector structure constant . It is determined by calibration when the equipment is installed. The calibration process takes 15 calibration points in the flow rate range of 0.5 to 3 meters per second.

[0124] S6. Based on the Control the irradiation power of multi-power flow UV lamp , ensure that the UV radiation dose per unit flow is not less than .

[0125] In a possible implementation, S6 specifically includes:

[0126] S601, set the UV lamp base power and minimum radiation equivalent threshold ;

[0127] S602, adjust the UV lamp power by the following formula :

[0128] ;

[0129] in Adjust the gain for power.

[0130] It should be noted that when controlling the UV lamp power in step S6, the first step is to calculate and minimum radiation equivalent threshold When the difference is less than 5 mJ / cm2, the existing lamp power is changed through pulse width modulation; when the difference is greater than 5 mJ / cm2, the spare lamp module is activated. The lamp array is staggered, and the center distance between adjacent lamps is 1.8 times the diameter of the sleeve. Power adjustment formula equal Plus Multiply reduce The square of the reference power Updated monthly based on the lamp aging curve, The value is optimized in real time through radiation sensor feedback.

[0131] It should be noted that the UV lamp array sets a power fault tolerance strategy: when a single lamp failure causes a power gap When the hydraulic cylinder pushes the spare module into place within 15 seconds; if The adjacent lamps are overloaded to 110% of the rated power. During the overload period, the infrared thermal imager monitors the surface temperature of the lamp in real time, and the power is immediately reduced if it exceeds 90°C.

[0132] S7, when the 3D dynamic model detects abnormal pressure difference at the pipeline node or When safety thresholds are exceeded, a fault classification procedure is initiated and disinfection parameters are adjusted.

[0133] In one possible implementation, the fault classification procedure in S7 includes:

[0134] S701, collecting pipeline node pressure difference sequence , ozone concentration change rate and UV lamp current fluctuation rate ;

[0135] S702, inputting the collected data into the trained random forest classification model;

[0136] S703: Output the failure probability distribution of leakage, blockage, or sensor failure.

[0137] It should be noted that the specific operation for determining the abnormal pressure difference in step S7 is: installing a capacitive differential pressure transmitter at adjacent pipeline nodes with a measurement accuracy of 0.1% of the full scale. When calculating, first take the pressure difference of adjacent nodes and The absolute difference minus 1 is divided by the exact node spacing L extracted from the 3D model. Exceeds the calculated value based on the pipe material When the dissolved ozone probe detects Rate of change When it exceeds 0.3 mg / L per minute, a level 3 alarm response is triggered.

[0138] Furthermore, when the fault classification program is executed, the distributed sensor network first collects To n sequence, the sampling frequency is 10 Hz. Ozone concentration change rate Through nearly 10 The data points are obtained by linear fitting and derivation. UV lamp current fluctuation rate Defined as the percentage deviation between the effective current value and the mean value. The random forest classification model consists of 120 decision trees, each using the Gini impurity criterion as the splitting criterion. Input features include the standard deviation of the differential pressure, the acceleration of ozone variation, and the harmonic distortion rate of the current. The model automatically updates the training dataset every 24 hours, and new fault cases are manually annotated and added to the training database.

[0139] In one possible implementation, the input features of the random forest classification model are expanded to 42 dimensions: the pressure difference sequence is extracted through fast Fourier transform (FFT) to extract the 0-50 Hz main frequency amplitude and harmonic energy ratio; the ozone concentration change rate is calculated by Lyapunov exponent and sample entropy as nonlinear features; the 0-40th harmonic components are collected from the ultraviolet lamp discharge current fluctuations, and the total harmonic distortion (THD) is calculated according to the IEC 61000-4-7 standard; the model automatically downloads new fault cases at 2:00 a.m. every day, updates the leaf node weights through semi-supervised learning, and uses SMOTE oversampling technology to address the class imbalance problem for the newly added data.

[0140] In a possible implementation, the method provided in this embodiment further includes:

[0141] S8. Detect the adenosine triphosphate (ATP) content in the disinfected water sample using bioluminescence.

[0142] It should be noted that during the Adenosine Triphosphate test, the automatic sampling valve collects 100 ml of water sample every 2 hours and injects the reagent kit containing luciferase. After the mixture is kept at 37 degrees Celsius for 10 minutes, the relative light unit value is measured using a photomultiplier tube. When the test value exceeds 50 for two consecutive times When the ozone demand index The calculated UV absorption correction factor A is immediately increased by 20% and remains in effect until the next test is passed.

[0143] S9, when the ATP detection value exceeds the preset threshold When The UV absorption correction factor A in the calculation is increased by 20 percent.

[0144] It should be noted that the correction factor linkage mechanism when ATP detection exceeds the standard is: When the UV absorption correction factor A is increased by 20% and lasts for 24 hours, the ozone dosage ratio coefficient is automatically increased. To 1.2 times of the original value; if the test exceeds the standard for three consecutive times, the UV lamp enhanced disinfection mode will be started, and the reference power Temporarily increases the minimum radiation equivalent by 15% Increase to .

[0145] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0146] (1) In the present invention, by constructing a three-dimensional dynamic model and integrating fluid parameters in real time, combined with the ozone demand index (ODI) and ultraviolet radiation equivalent (URE) dual-parameter collaborative control mechanism, a precise dynamic matching of ozone dosage and ultraviolet radiation dose is achieved. The ozone ejector dosage and ultraviolet lamp power are adaptively adjusted based on flow rate and water quality changes, solving the problem of the disconnection between disinfection dosage and actual demand in traditional static control, significantly improving disinfection efficiency while reducing agent consumption, and ensuring that the radiation dosage per unit flow rate meets the standard under different working conditions.

[0147] (2) In this invention, a fault classification program is linked to a three-dimensional model pressure differential anomaly monitoring mechanism. A random forest model is used to analyze multi-source data such as pipeline pressure differential sequences, ozone concentration gradients, and current fluctuations in real time to accurately identify fault types such as leakage, blockage, or sensor failure. Combined with a fluid state-driven model update strategy (such as Reynolds number-triggered turbulence mode), the system's abnormal response speed and operational reliability are significantly improved, fundamentally overcoming the hysteresis and misjudgment risks of traditional threshold alarms.

[0148] (3) In this invention, biological verification closed-loop control and fluid dynamics optimization are introduced. Real-time adenosine triphosphate (ATP) detection is fed back to the ODI parameter correction, and a three-dimensional model is simultaneously used to optimize ozone contact efficiency and UV radiation uniformity. This forms an intelligent closed-loop of "monitoring-control-verification-re-optimization", completely resolving the potential risks of disinfection effect fluctuations and microbial resurgence, and achieving a comprehensive improvement from device-level control to system-level stability.

[0149] The above content is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

[0150] There are a few points to note:

[0151] (1) The drawings of the embodiments of the present invention only relate to the structures related to the embodiments of the present invention. Other structures may refer to conventional designs.

[0152] (2) For the sake of clarity, the thickness of layers or regions in the drawings used to describe the embodiments of the present invention are exaggerated or reduced, that is, these drawings are not drawn to scale. It is understood that when an element such as a layer, film, region, or substrate is referred to as being "on" or "under" another element, the element may be "directly on" or "under" the other element or intervening elements may be present.

[0153] (3) In the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other to form new embodiments.

[0154] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. Intelligent and precise control method for ozone and ultraviolet disinfection of drinking water, characterized by: include: S1. Construct a three-dimensional dynamic model of the direct drinking water purification system, integrating the pipeline network topology, ozone contact tank volume data, and UV reactor geometry parameters; S2. Real-time collection of water inlet flow data through flow sensors , real-time monitoring of residual ozone concentration at the outlet through dissolved ozone probe ; S3. Based on the Calculate the ozone demand index based on water quality characteristic parameters ; S4. According to the and Real-time calculation of UV radiation equivalent ; S5. Dynamically adjust the ozone dosage of the ozone ejector ,make and and The product of is in linear proportion; S6. Based on the Control the irradiation power of multi-power flow UV lamp , ensure that the UV radiation dose per unit flow is not less than ; S7, when the 3D dynamic model detects abnormal pressure difference at the pipeline node or When safety thresholds are exceeded, the fault classification procedure is initiated and disinfection parameters are adjusted The S3 specifically includes: S301. Obtaining water quality characteristic parameter ultraviolet transmittance and chemical oxygen demand ; S302. Calculate the ozone demand index using the following formula : ； Where: A is the UV absorption correction factor, the value range is 0.5 to 1.2, B is the organic oxidation coefficient, the value range is 0.15 to 0.35; The S4 specifically includes: S401, measuring the transmission time t of water from the ozone injection point to the ultraviolet lamp area; S402. Calculate the UV radiation equivalent using the following formula: : ； Where: C is the microbial inactivation constant, ranging from 1.2 to 2.5; D is the ozone decay rate, ranging from 0.05 to 0.2 per minute; The S4 specifically includes: S411. Obtaining UV transmittance and ozone synergistic factors , the ozone synergistic factor Values ​​range from 0.05 to 0.15 mg per liter; S412. Calculate the UV radiation equivalent using the following formula : ； in: is the transmittance conversion coefficient, with a value range of 0.8 to 1.2, is the flow suppression constant, with a value range of 0.1 to 0.3; The S5 specifically includes: S501, measuring the flow rate of water in the pipeline , ejector pressure drop and water density ; S502, control the gas injection amount of the ozone ejector by the following formula : ； in is the ejector structural constant; The S6 specifically includes: S601, set the UV lamp base power and minimum radiation equivalent threshold ; S602, adjust the UV lamp power by the following formula : ； in Adjust the gain for power.

2. The intelligent and precise control method for ozone and ultraviolet combined disinfection of direct drinking water according to claim 1 is characterized in that: The updating of the three-dimensional dynamic model in S1 includes: S101, based on real-time Calculating the Reynolds number : ； in is the density, is the flow rate, is the hydraulic diameter, is viscosity; S102, when , activates turbulence mode and increases the model update frequency to twice the baseline value.

3. The intelligent and precise control method for ozone and ultraviolet combined disinfection of direct drinking water according to claim 1 is characterized in that: The fault classification procedure in S7 includes: S701, collecting pipeline node pressure difference sequence , ozone concentration change rate and UV lamp current fluctuation rate ; S702, inputting the collected data into the trained random forest classification model; S703: Output the failure probability distribution of leakage, blockage, or sensor failure.

4. The intelligent and precise control method for ozone and ultraviolet combined disinfection of direct drinking water according to claim 2 is characterized in that: The fluid dynamics parameters in S102 include: Reynolds number Calculated value; Turbulence intensity Measured value; Model update frequency satisfy: ； in is the minimum hydraulic unit volume of the system.

5. The intelligent and precise control method for ozone and ultraviolet combined disinfection of direct drinking water according to claim 1 is characterized in that: Also includes: S8. Detect the adenosine triphosphate (ATP) content of the disinfected water sample by bioluminescence method; S9, when the ATP detection value exceeds the preset threshold When The UV absorption correction factor A in the calculation is increased by 20 percent.

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