Activated carbon filter operation optimization method and system for multi-scene water treatment

Abstract

The application belongs to the technical field of water treatment, automatic control and environmental monitoring, and specifically discloses a multi-scene water treatment-oriented activated carbon filter operation optimization method and system, which comprises the following steps: introducing a multi-dimensional real-time sensing and intelligent diagnosis mechanism to realize fine regulation and control of the filter operation state; constructing a dynamic correlation matrix between water quality change and filter layer pressure difference increment, and adopting targeted optimization measures to ensure that the effluent meets the standard; starting low-energy micro-current stimulation to activate adsorption sites first to realize preliminary recovery of filter material activity, and evaluating the operation effect in real time, and starting high-temperature steam regeneration only when the effect is poor; designing non-homogeneous laminated filter material and combining with water source identification technology to achieve adaptive water purification treatment capacity, so that the filter material can flexibly cope with pollution water sources of different sources and different characteristics, identify the type of the water source, select the optimal water flow path, and ensure that each pollutant can be efficiently removed.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of water treatment, automatic control and environmental monitoring, and relates to an activated carbon filter operation optimization method and system for multiple scene water treatment. BACKGROUND

[0002] Water purification and recycling is the core issue of social sustainable development and ecological environment safety. The filter system based on adsorbent materials such as activated carbon is widely used in industrial wastewater treatment, municipal water supply and rainwater recycling, etc. due to its high efficiency in removing various pollutants. However, with the acceleration of industrialization and urbanization, the water quality of the water to be treated is becoming increasingly complex and variable, with many types of pollutants and large fluctuations in concentration, which brings serious challenges to traditional water treatment filter systems.

[0003] Traditional filter operation management relies on empirical fixed parameters and operation procedures, showing significant lag and inaccuracy. For example, backwashing operation is often triggered based on fixed time period or a single physical parameter (such as filter layer pressure difference reaching critical threshold), and adsorption filter material regeneration also adopts periodic planning, with unified high-energy consumption thermal regeneration or chemical regeneration. This management mode can cope with stable water quality when treating stable water sources, but its rigidity and lack of sensing ability are exposed when facing dynamic changes in water quality.

[0004] The drawbacks of traditional solutions lie in the single control logic and lack of diagnosis capability. Specifically, when the filter layer pressure difference increases, simply attributing it to physical clogging is one-sided and inaccurate. In fact, the increase in pressure difference may be due to two completely different mechanisms: one is physical pore clogging caused by suspended particulate matter; the other is the formation of biological or chemical film layer on the surface of adsorbent, which changes the characteristics of water flow channel. Given the essential difference between the two clogging mechanisms, their response strategies should also be different. However, the traditional solution adopts a unified high-speed backwashing mode, which easily causes a large waste of water resources and energy.

[0005] Secondly, the fixed regeneration period setting in the traditional solution also leads to resource waste. Regeneration operation at low concentration of pollutants in the water will consume the filter life prematurely and pay unnecessary energy cost; regeneration operation at high concentration of pollutants will make the filter saturated prematurely; if the regeneration is not found and performed in time, it will lead to the penetration of pollutants through the filter layer, causing the water quality to be seriously out of standard, and thus causing environmental safety accidents.

[0006] In addition, the homogeneous filter material used in traditional filters cannot be flexibly optimized and matched according to the change of water source type, thus limiting the further improvement of the overall treatment efficiency. SUMMARY

[0007] In order to overcome the above-mentioned defects of the prior art, in order to achieve the above-mentioned purpose, the present application proposes the following technical scheme: a method for optimizing the operation of an activated carbon filter for multi-scene water treatment, comprising the following steps: step S1, collecting real-time target signals at the inlet and outlet of the filter and filter layer pressure difference increments, and generating a dynamic water quality-pressure difference matrix.

[0008] Step S2, analyzing the dynamic water quality-pressure difference matrix, generating an integrated blocking signal, and dividing into a physical blocking type or a filter material capacity critical type or a normal operation.

[0009] Step S3, adjusting the water inflow rate according to the integrated blocking signal, and outputting the optimized effluent water quality.

[0010] Step S4, when the integrated blocking signal indicates the filter material capacity critical type and lasts for a preset time, activating a micro-current stimulation device and generating an activity release rate.

[0011] Step S5, triggering hierarchical regeneration based on the activity release rate, and generating a saturation regeneration flag.

[0012] Step S6, identifying the water source type and switching the water flow path of the non-homogeneous laminated filter material, and generating a directional adsorption sequence.

[0013] Step S7, performing hierarchical adsorption according to the directional adsorption sequence, and outputting the final state of purified water.

[0014] The second aspect of the present application provides a system for optimizing the operation of an activated carbon filter for multi-scene water treatment, comprising the following contents: a dynamic water quality-pressure difference matrix generation module, which collects real-time target signals at the inlet and outlet of the filter and filter layer pressure difference increments, and generates a dynamic water quality-pressure difference matrix.

[0015] An integrated blocking signal generation module analyzes the dynamic water quality-pressure difference matrix, generates an integrated blocking signal, and divides into a physical blocking type or a filter material capacity critical type or a normal operation.

[0016] An inflow rate optimization adjustment module adjusts the water inflow rate according to the integrated blocking signal, and outputs the optimized effluent water quality.

[0017] An activity release rate generation module activates a micro-current stimulation device and generates an activity release rate when the integrated blocking signal indicates the filter material capacity critical type and lasts for a preset time.

[0018] A hierarchical regeneration triggering module triggers hierarchical regeneration based on the activity release rate, and generates a saturation regeneration flag.

[0019] A directional adsorption sequence generation module identifies the water source type and switches the water flow path of the non-homogeneous laminated filter material, and generates a directional adsorption sequence.

[0020] A hierarchical adsorption execution module performs hierarchical adsorption according to the directional adsorption sequence, and outputs the final state of purified water.

[0021] Compared with the prior art, the beneficial effects of the present application are as follows: (1) The present application realizes accurate insight and fine regulation and control of the filter running state by introducing a multi-dimensional real-time perception and intelligent diagnosis mechanism, and by constructing a dynamic correlation matrix between water quality changes and filter layer pressure difference increments, the internal logical relationship between the two over time is deeply analyzed, physical blockage caused by rapid accumulation of suspended solids and performance degradation caused by complete occupation of filter material surface adsorption sites by pollutants can be clearly distinguished, and targeted optimization measures can be taken to help avoid ineffective operation, ensure that the effluent meets the standard, and maximize operational efficiency.

[0022] (2) The present application realizes preliminary recovery of filter material activity by starting low-energy micro-current stimulation and activation of adsorption sites first, and the system will evaluate the effect of this micro-regeneration operation in real time, i.e. the activity release rate, and only when the effect is poor, high-temperature steam regeneration is started. This hierarchical regeneration strategy ensures that energy-intensive operations are only used when absolutely necessary, and in most cases of mild or moderate saturation, the effective operation period of the filter can be extended through low-cost online activation, thereby achieving significant reduction in energy consumption and operating cost while ensuring treatment effect.

[0023] (3) The present application gives the water purification system self-adaptive treatment capacity by designing non-homogeneous laminated filter material and combining with water source identification technology, so that it can flexibly cope with different sources and different characteristics of polluted water sources, and the system can actively identify the type of incoming water source and intelligently select the optimal water flow path. This targeted adsorption strategy dynamically adjusts the contact order of water flow and filter material to ensure that each pollutant can be removed efficiently, so that the system always maintains the best working state and stably outputs high-quality purified water. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. 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.

[0025] Figure 1 The present application is a method implementation step flow diagram.

[0026] Figure 2 The present application is a system module connection diagram. DETAILED DESCRIPTION

[0027] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be clearly and completely described below, obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0028] Embodiment one

[0029] Please refer to Figure 1 The activated carbon filter operation optimization method for multi-scene water treatment provided by the present application includes the following steps: step S1, collecting real-time target signals at the inlet and outlet of the filter and the filter layer pressure difference increment, and generating a dynamic water quality-pressure difference matrix.

[0030] In a preferred embodiment, the step S1 includes: collecting the target information at the inlet and the target information at the outlet by the ultraviolet spectrometer installed at the inlet pipe and the outlet pipe of the filter, and calculating the real-time target signal by formula 1, formula 1: A Wherein, A is the absorbance at the target position, c is the solution concentration, l is the optical path, is the molar absorption coefficient;

[0031] The inlet pressure value and the outlet pressure value are measured by the inlet pressure sensor and the outlet pressure sensor, the filter layer pressure difference is calculated as the inlet pressure value minus the outlet pressure value, and the initial clean state pressure difference value is subtracted to generate the filter layer pressure difference increment. The inlet pressure value is obtained by measuring the inlet pressure sensor; the outlet pressure value is obtained by measuring the outlet pressure sensor; the setting basis of the initial clean state pressure difference value is obtained by experimental measurement under the clean state of the filter (based on the average value of 10 repeated calibrations).

[0032] The real-time target signal and the filter layer pressure difference increment are aligned according to the time stamp, and a dynamic water quality-pressure difference matrix is constructed.

[0033] Specifically, the inlet pressure value and the outlet pressure value are measured in real time by the pressure sensor installed at the inlet and outlet of the filter, the filter layer pressure difference is calculated as the inlet pressure value minus the outlet pressure value, and the initial clean state pressure difference value measured in advance under the clean state of the filter is subtracted to generate the filter layer pressure difference increment.

[0034] The collected real-time target signal and filter layer pressure difference increment are aligned according to the same time stamp, and based on the aligned time stamp sequence, a two-dimensional matrix is constructed, wherein the rows correspond to the time points, and the columns contain the real-time target signal value and the filter layer pressure difference increment value, to generate a dynamic water quality-pressure difference matrix.

[0035] Wherein, the real-time target signal can be selected according to the corresponding index according to the application scene.

[0036] Filter pressure differential increment represents the change of filter pressure loss relative to clean state, unit kilo pascal, set according to pressure sensor industry standard calibration.

[0037] Dynamic water quality-pressure differential matrix is time series data, containing real-time target signal and filter pressure differential increment value.

[0038] Ultraviolet spectrometer is installed at filter inlet and outlet pipeline, set according to standard industry water quality monitoring equipment.

[0039] Pressure sensor is used to measure fluid pressure, installed at filter inlet and outlet, set according to standard industry pressure sensor.

[0040] Timestamp is the time label of data points, unit minute.

[0041] Two-dimensional matrix is a data structure, rows represent time points, real-time COD signal and filter pressure differential increment value are collected.

[0042] Initial clean state pressure differential value is set according to experimental measurement before filter start-up, based on average of 5 groups of independent test data.

[0043] Step S2, analyze dynamic water quality-pressure differential matrix, generate integrated blocking signal, divided into physical blocking type or filter material capacity critical type or normal operation.

[0044] In a preferred embodiment, the step S2 comprises: calculating the percentage increase of filter pressure differential increment and the percentage fluctuation of real-time target signal in dynamic water quality-pressure differential matrix;

[0045] When the filter pressure differential increment increase is greater than or equal to the preset increase threshold and the real-time target signal fluctuation is less than or equal to the preset fluctuation threshold, it is determined as physical blocking type.

[0046] When the real-time target signal increase is greater than or equal to the preset increase threshold and the filter pressure differential increment fluctuation is less than or equal to the preset fluctuation threshold, it is determined as filter material capacity critical type.

[0047] The remaining state is marked as normal operation, and the blocking type code is output as the integrated blocking signal.

[0048] In a further preferred embodiment, the step of calculating the percentage increase comprises: taking the data point sequence of the previous preset time window interval as the window end point for each time point of the dynamic water quality-pressure differential matrix.

[0049] The filter pressure differential increment increase percentage is calculated as the filter pressure differential increment value at the current time point minus the filter pressure differential increment value at the window start point, divided by the filter pressure differential increment value at the window start point multiplied by 100 percentage.

[0050] The real-time target signal amplitude percentage is calculated as the real-time target signal value at the current time minus the real-time target signal value at the window start point, divided by the real-time target signal value at the window start point multiplied by 100%.

[0051] The amplitude percentage calculation is combined with the fluctuation percentage calculation to produce a synergistic effect, which improves the accuracy of the blockage type determination beyond the separate calculation effect, and achieves enhanced filter operation stability by reducing the misjudgment rate.

[0052] Specifically, the dynamic water quality-differential pressure matrix generated in the obtaining step S1 is obtained, which contains time series of real-time target signal values and filter layer differential pressure increment values; for each time point as the window end point, the data point sequence in the previous 10-minute time interval is taken; the amplitude percentage of the filter layer differential pressure increment in the time interval is calculated, which is defined as the filter layer differential pressure increment value at the current time point minus the filter layer differential pressure increment value 10 minutes ago, divided by the filter layer differential pressure increment value 10 minutes ago, multiplied by 100%.

[0053] The fluctuation percentage of the real-time target signal in the time interval is also calculated, which is defined as the maximum value of the real-time target signal values in the interval minus the minimum value, divided by the average value, multiplied by 100%.

[0054] If the filter layer differential pressure increment amplitude percentage is greater than or equal to 30% and the real-time target signal fluctuation percentage is less than or equal to 5%, it is determined to be a physical blockage type; if the real-time target signal amplitude percentage is greater than or equal to 40% and the filter layer differential pressure increment fluctuation percentage is less than or equal to 8%, it is determined to be a filter material capacity critical type; the amplitude percentage calculation method is the same as the filter layer differential pressure increment amplitude percentage; the remaining state is marked as normal operation.

[0055] A blockage type code is generated, where 0 represents normal operation, 1 represents a physical blockage type, and 2 represents a filter material capacity critical type, as an integrated blockage signal output.

[0056] The integrated blockage signal represents the blockage state type, and the code is output as the blockage type code.

[0057] The blockage type code takes values 0, 1 or 2, corresponding to normal operation, physical blockage type and filter material capacity critical type, respectively, and is set based on experimental research on filter blockage mechanism.

[0058] The physical blockage type is a blockage state characterized by accumulation of physical particles in the filter layer, and is set based on filter blockage diagnosis standards.

[0059] The filter material capacity critical type is a blockage state characterized by saturation of the adsorbent material, and is set based on experimental data of adsorption kinetics.

[0060] The time window is fixed at 10 minutes, and the unit is minute. The setting is based on the optimization of the typical response time of industrial filter.

[0061] For example, the example data of the connection step S1 is as follows: the dynamic water quality-differential pressure matrix entry at time point 0 minute is time 0 minute, real-time target signal 1.2, and filter layer differential pressure increment 5 kPa; the extended time point 5 minute entry is time 5 minute, real-time target signal 1.21, and filter layer differential pressure increment 7 kPa; the time point 10 minute entry is time 10 minute, real-time target signal 1.19, and filter layer differential pressure increment 12 kPa; the interval [0, 10] minute data is taken with the time point 10 minute as the window end point; the filter layer differential pressure increment amplitude percentage is calculated as 12 minus 5 divided by 5 multiplied by 100%, which is equal to 140%, and is greater than or equal to 30%; the real-time target signal fluctuation percentage is calculated as 1.21 minus 1.19 divided by 1.20 multiplied by 100%, which is equal to 1.67%, and is less than or equal to 5%; the physical blockage type condition is met, and the blockage type code 1 is output as the integrated blockage signal; this example directly verifies the effectiveness of the amplitude percentage and fluctuation percentage calculation and the blockage type determination logic.

[0062] Step S3, adjusting the water inflow rate according to the integrated blockage signal, and outputting the optimized effluent water quality.

[0063] In a preferred embodiment, the step S3 comprises: when the integrated blockage signal indicates the physical blockage type, increasing the water inflow rate and triggering the high-speed backwashing mode.

[0064] When the integrated blockage signal indicates the filter material capacity critical type, the water inflow rate is reduced and the slow flow adsorption mode is triggered.

[0065] Real-time monitoring of the target signal, when the target signal is stable at multiple time points for a plurality of time points and is less than or equal to the preset target signal threshold, the optimized effluent water quality is output.

[0066] Specifically, the integrated blockage signal generated by the acquisition step S2 is obtained, which is in the form of a blockage type code representing the current filter running state.

[0067] According to the blockage type code value, the corresponding water inflow rate adjustment operation is performed: if the blockage type code is 1, indicating the physical blockage type, the high-speed backwashing mode is triggered, and the current water inflow rate is increased by 50% for three minutes to flush the filter layer; if the blockage type code is 2, indicating the filter material capacity critical type, the slow flow adsorption mode is triggered, and the current water inflow rate is reduced by 30% to prolong the contact time of water flow and filter material.

[0068] After adjusting the water inflow rate, the outlet target signal value is monitored in real time through the sensor installed in the filter outlet pipeline. During continuous monitoring, it is checked whether the outlet target signal is continuously stable within the preset threshold value, i.e., the outlet target signal value is less than or equal to the preset threshold value. When the target signal value at three consecutive time points is less than or equal to the preset threshold value, it is determined that the water quality is stable and up to standard, and the optimized outlet water quality is output.

[0069] wherein the water inflow rate represents the speed of water flow into the filter, with a unit of cubic meters per hour, and the setting basis is the filter design parameter (based on the manufacturer's specification manual).

[0070] The high-speed backwash mode is used to increase the water inflow rate to flush the filter layer, and the setting basis is the filter backwash industrial standard.

[0071] The slow-flow adsorption mode is used to reduce the water inflow rate to prolong the contact time, and the setting basis is the adsorbent kinetics optimization experiment.

[0072] Specifically, the outlet target signal can be selected according to different application scenarios, for example, in industrial treatment, the outlet COD can be set as the outlet target signal, wherein the outlet COD represents the chemical oxygen demand of the filter outlet water, with a unit of mg / L, measured by an outlet ultraviolet spectrometer, and the setting basis is the international water quality monitoring standard.

[0073] The threshold value represents the standard of up-to-standard water quality, which is defined as 60 mg / L, and the setting basis is the sewage comprehensive discharge standard specification.

[0074] The optimized outlet water quality is the output result, indicating that the adjusted water quality is up to standard, and the setting basis is the real-time monitoring data.

[0075] For example, the example data of the connection step S2 is that the integrated blocking signal is blocking type code 1 at time point 10 minutes, indicating a physical blocking type; the high-speed backwash mode is triggered, assuming that the current water inflow rate is 100 cubic meters per hour, which is increased by 50% to 150 cubic meters per hour, and lasts for three minutes to flush the filter layer; the outlet COD is monitored in real time from time point 10 minutes: the outlet COD is 60 mg / L at time point 11 minutes, 65 mg / L at time point 14 minutes, and 62 mg / L at time point 17 minutes (flushing end point); continue to monitor, the outlet COD is 59 mg / L at time point 20 minutes, 56 mg / L at time point 23 minutes, and 50 mg / L at time point 26 minutes; at this time, the outlet COD at three consecutive time points (20, 23, and 26 minutes) is less than or equal to 60 mg / L, it is determined that the water quality is stable and up to standard, and the optimized outlet water quality is output; this example directly verifies the effectiveness of the water inflow rate adjustment operation and the outlet COD monitoring logic, including the threshold value setting.

[0076] Step S4, when the integrated blocking signal indicates the filter material capacity critical type and lasts for a preset time, activate the micro-current stimulation device and generate the activity release rate.

[0077] In a preferred embodiment, the step S4 comprises: activating the micro-current stimulation device embedded on both sides of the filter tank, inputting a preset voltage direct current and maintaining a preset current density for a preset power-on time.

[0078] The pressure difference increment value before power-on and the pressure difference increment value after power-on are measured, and the pressure difference increment drop amplitude is calculated as the pressure difference increment value before power-on minus the pressure difference increment value after power-on.

[0079] The activity release rate is calculated as the pressure difference increment drop amplitude divided by the pressure difference increment value before power-on multiplied by 100 percent.

[0080] Specifically, when the integrated blocking signal output from step S2 indicates the filter material capacity critical type (blocking type code 2) and the state lasts for 120 minutes, the micro-current stimulation device embedded on both sides of the filter tank is activated; the titanium electrode array in the device inputs a 3-volt direct current voltage, the current density is 0.5 ampere per square meter, and the power-on lasts for 5 minutes; after the power-on ends, the current pressure difference increment value is measured in real time through the inlet and outlet pressure sensors; the pressure difference increment drop amplitude is calculated as the pressure difference increment value before power-on minus the pressure difference increment value after power-on; and the activity release rate is calculated as the pressure difference increment drop amplitude divided by the pressure difference increment value before power-on, multiplied by 100 percent; and the activity release rate is generated as output.

[0081] The pressure difference increment drop amplitude is calculated as the pressure difference increment before power-on minus the pressure difference increment after power-on, and the setting basis is real-time measurement data verification.

[0082] The pressure difference increment value before power-on is directly obtained from the pressure difference increment data of step S1, and the setting basis is the pressure sensor calibration standard (based on the industrial filter operation protocol).

[0083] The micro-current stimulation device is used to provide low-intensity current stimulation to promote adsorbent regeneration, and the setting basis is the filter regeneration technology experiment (based on 50 groups of industrial test data optimization).

[0084] The titanium electrode array is a physical structure made of titanium for electrical conduction, and the setting basis is the electrode material durability standard.

[0085] The current density represents the current intensity per unit area, and the setting basis is the adsorbent regeneration efficiency experiment based on the optimal regeneration effect parameters, 0.5 ampere per square meter.

[0086] The pressure difference increment drop amplitude represents the pressure difference reduction, and the setting basis is the pressure sensor accuracy standard, with an error of less than 1 kilopascal.

[0087] The activity release rate represents the degree of activity recovery of the adsorbent. The setting basis is the regeneration performance evaluation criterion, and the target range is 20% to 60%.

[0088] For example, the example of the connection step S3 assumes that at the time point 136 minutes, the integrated blocking signal continuously reaches the filter capacity critical type code 2 for 120 minutes, for example, continuously detected as code 2 from the time point 16 minutes; the micro-current stimulation device is activated, a direct current of 3 volts is input, the current density is 0.5 amperes per square meter, and the duration is 5 minutes; the pressure difference increment is measured to be 20 kilopascals (initial increment) before power-on; the pressure difference increment is measured to be 15 kilopascals after power-on; the pressure difference increment drop is calculated to be 20 minus 15 equal to 5 kilopascals; the activity release rate is calculated to be 5 divided by 20 multiplied by 100 percent equal to 25 percent; the activity release rate 25 percent is generated; this example directly verifies the effectiveness of the micro-current stimulation operation parameter and the activity release rate calculation logic.

[0089] Step S5, based on the activity release rate, triggers the staged regeneration, and generates a saturated regeneration flag.

[0090] In a preferred embodiment, the step S5 includes: when the activity release rate is greater than or equal to a preset release threshold, generating a delayed regeneration instruction and resetting the adsorption saturation timer.

[0091] When the activity release rate is less than the preset release threshold, a high-temperature steam regeneration program is activated, and a preset temperature high-temperature steam is input for a preset regeneration period.

[0092] After the regeneration program is completed, a saturated regeneration flag is output.

[0093] Specifically, the activity release rate generated by the obtaining step S4 is obtained; it is judged whether the activity release rate is greater than or equal to 40 percent; when the activity release rate is greater than or equal to 40 percent, a delayed regeneration instruction is generated, and the adsorption saturation timer is reset to zero; when the activity release rate is less than 40 percent, a 380-degree Celsius high-temperature steam regeneration program is activated, which controls the steam generator to input 380-degree Celsius high-temperature steam to the filter layer for a preset regeneration period; after the regeneration program is executed, a saturated regeneration flag signal is output.

[0094] The staged regeneration is intended to select different regeneration modes according to the activity release rate, and the setting basis is the filter economic operation criterion based on the energy efficiency ratio optimization experiment.

[0095] The delayed regeneration instruction is used to suspend the deep regeneration operation, and the setting basis is the adsorbent self-recovery characteristic research (50 groups of industrial test verification).

[0096] The saturated regeneration flag is used to identify that the deep regeneration has been completed, and the setting basis is the filter maintenance protocol.

[0097] The adsorption saturation timer is used to accumulate the critical type duration of filter capacity, in minutes, and the setting basis is the connection (120-minute duration threshold) of the triggering condition in step S4.

[0098] The high-temperature steam regeneration program is a 380-degree Celsius steam treatment, and the setting basis is the industrial standard for activated carbon regeneration. The 380-degree Celsius is the steam temperature set point, and the setting basis is the optimal temperature experiment for adsorbent thermal regeneration (300 groups of thermogravimetric analysis).

[0099] For example, case one: in the example of connecting step S4, the activity release rate is 25%, which is less than 40%, triggering the 380-degree Celsius high-temperature steam regeneration program; after the steam is introduced into the filter layer for a preset period of 30 minutes, the program is completed, and the saturated regeneration flag (the flag value is set to 1) is output.

[0100] Case two: in another operating scenario, the activity release rate output by step S4 is 45%, which is greater than or equal to 40%, generating a delayed regeneration instruction (such as the instruction code "DELAY"), and resetting the adsorption saturation timer to zero. The two examples respectively verify the effectiveness of the two branch execution logics of the hierarchical regeneration strategy.

[0101] Step S6, identifying the water source type and switching the water flow path of the heterogeneous stacked filter material, generates a directional adsorption sequence.

[0102] In a preferred embodiment, the step S6 includes: identifying, by an external water source monitoring unit, that the water source type is industrial wastewater or rainwater purification.

[0103] When the water source type is industrial wastewater, the rotating water inlet distributor is controlled to rotate to a first preset angle, so that the water flow preferentially flows through the first layer of high-porosity carbon particle area of the heterogeneous stacked filter material, and a first layer priority instruction is generated as the directional adsorption sequence.

[0104] When the water source type is rainwater purification, the rotating water inlet distributor is controlled to rotate to a second preset angle, so that the water flow preferentially flows through the second layer of microporous carbon layer area of the heterogeneous stacked filter material, and a second layer priority instruction is generated as the directional adsorption sequence.

[0105] Specifically, the water source type is identified by an external water source monitoring unit as industrial wastewater or rainwater purification, the industrial wastewater includes but is not limited to municipal sewage, and the rainwater purification includes but is not limited to municipal water supply; when it is identified as an industrial wastewater type, the rotating water inlet distributor at the filter inlet is controlled to rotate to a 30-degree angle position, so that the water flow preferentially flows through the first layer of high-porosity carbon particle area of the heterogeneous stacked filter material; when it is identified as a rainwater purification type, the rotating water inlet distributor is controlled to rotate to a 60-degree angle position, so that the water flow preferentially flows through the second layer of microporous carbon layer area of the heterogeneous stacked filter material.

[0106] After the water flow path is switched, the carbon layer use order instruction is generated according to the carbon particle use priority, the industrial wastewater scenario generates the "first layer→second layer" instruction, and the rainwater purification scenario generates the "second layer→first layer" instruction; and finally the carbon layer use order instruction is output as the directional adsorption sequence.

[0107] The water source type is divided into industrial wastewater and rainwater purification, and the setting basis is a water source water quality characteristic library (based on 100 water source spectrum analyses).

[0108] The rotating water inlet distributor is used to adjust the initial water flow path, and the angular position control precision is ±1 degree, and the setting basis is an industrial hydraulic transmission standard.

[0109] The heterogeneous stacked filter material is a filter material structure, including a first layer and a second layer of activated carbon with different pore characteristics.

[0110] The high-porosity carbon particle has a porosity greater than or equal to 60% and an average pore diameter of 50 microns, and the setting basis is an industrial activated carbon specification.

[0111] The microporous carbon layer is an activated carbon material with a pore diameter less than or equal to 2 nanometers and a specific surface area greater than or equal to 1000 m2 / g, and the setting basis is an international standard for microporous adsorbents.

[0112] The directional adsorption sequence indicates the carbon layer use priority order, such as the character instruction "first layer→second layer", and the setting basis is an adsorption path optimization experiment (based on 200 efficiency comparison data groups).

[0113] For example, case one: the external water source monitoring unit identifies industrial wastewater with a COD value of 380 mg / L, the rotating water inlet distributor is turned to an angle of 30 degrees, the water flow first passes through the first layer of high-porosity carbon particles (porosity 65%) and then passes through the second layer of microporous carbon layers (pore diameter 1.8 nanometers), and the directional adsorption sequence "first layer→second layer" is generated.

[0114] Case two: rainwater with a suspended solid concentration of 25 mg / L is identified, the rotating water inlet distributor is turned to an angle of 60 degrees, the water flow first passes through the second layer of microporous carbon layers (specific surface area 1100 m2 / g) and then passes through the first layer of high-porosity carbon particles, and the directional adsorption sequence "second layer→first layer" is generated. The two examples respectively verify the effectiveness of the water source type identification and the carbon layer path switching logic.

[0115] Step S7: Perform layered adsorption according to the directional adsorption sequence, and output the final state of purified water.

[0116] In a preferred embodiment, the step S7 includes: controlling the water flow to sequentially pass through the first layer of high-porosity carbon particles and the second layer of microporous carbon layers of the heterogeneous stacked filter material according to the directional adsorption sequence.

[0117] Monitor the COD of the water discharged from each layer.

[0118] Monitor the COD of the final water. When the COD of the final water is less than or equal to the preset purification threshold for a preset number of consecutive time points, output the final purified water.

[0119] Specifically, the directional adsorption sequence instruction generated in step S6 is obtained; the order of water flow through the non-homogeneous stacked filter material is controlled according to the instruction content: if the instruction is "first layer→second layer", the water flow first passes through the first layer of high porosity carbon particle area, and then passes through the second layer of microporous carbon layer area; if the instruction is "second layer→first layer", the water flow first passes through the second layer of microporous carbon layer area, and then passes through the first layer of high porosity carbon particle area; install an ultraviolet spectrometer at the outlet of each filtration area, monitor the water quality at the outlet of the current carbon layer immediately after the water flow passes through the carbon layer, and record it as the COD of the water discharged from each layer; after all the specified carbon layers are filtered, the COD of the final water is continuously monitored; when the COD of the final water is less than or equal to 50 mg / L for sixty consecutive time points, output the final purified water.

[0120] Among them, the layered adsorption is through different carbon layers in sequence according to the sequence instruction, and the setting basis is the adsorption kinetics optimization experiment (based on 300 groups of flux test).

[0121] The COD of the water discharged from each layer represents the water quality after single-layer filtration, with a unit of mg / L, measured by an interlayer sensor, and the setting basis is the international water quality monitoring standard.

[0122] The final purified water represents the final qualified water quality, and the setting basis is the continuous and stable qualified condition.

[0123] The sixty consecutive time points are time conditions, each time point is one minute apart, and the total duration is sixty minutes, and the setting basis is the industrial water treatment stability verification protocol (200 groups of operation data analysis).

[0124] For example, under the premise that the target signal is set as the COD of the water discharged, case one: the directional adsorption sequence "first layer→second layer" of step S6 industrial wastewater scene is connected; the COD of the water discharged from each layer after the water flow passes through the first layer of high porosity carbon particles is 58 mg / L; the COD of the final water after the water flow passes through the second layer of microporous carbon layer is 53 mg / L at time point 0 minute; the COD of the final water is continuously monitored to be 38 mg / L at time point 59 minute and 32 mg / L at time point 60 minute; the COD of the final water is less than or equal to 50 mg / L for sixty consecutive time points (actually qualified from time point 5 minute), and the final purified water is output.

[0125] Case two: the sequence of rainwater purification scenarios "second layer → first layer"; the water first passes through the second layer of microporous carbon layer, and then the layered water COD is 60 mg / L; then it passes through the first layer of carbon particles, and finally the effluent COD is 48 mg / L from time point 0 to 35 mg / L at time point 60; it is up to standard for 60 consecutive time points, and the final state of the purified water is output. The two examples directly verify the effectiveness of the carbon layer sequence execution and the continuous monitoring mechanism.

[0126] Example two

[0127] Please refer to Figure 2 As shown in the figure, based on the basis of example one, the second aspect of the present application provides an activated carbon filter operation optimization system for multiple scene water treatment, which includes: a dynamic water quality-differential pressure matrix generation module, an integrated blocking signal generation module, an influent rate optimization adjustment module, an activity release rate generation module, a hierarchical regeneration triggering module, a directional adsorption sequence generation module and a hierarchical adsorption execution module.

[0128] The dynamic water quality-differential pressure matrix generation module, the integrated blocking signal generation module, the influent rate optimization adjustment module, the activity release rate generation module, the hierarchical regeneration triggering module, the directional adsorption sequence generation module and the hierarchical adsorption execution module are connected in sequence.

[0129] The dynamic water quality-differential pressure matrix generation module collects real-time COD signals and filter layer differential pressure increments at the inlet and outlet of the filter, and generates a dynamic water quality-differential pressure matrix.

[0130] The integrated blocking signal generation module analyzes the dynamic water quality-differential pressure matrix and generates an integrated blocking signal, which is divided into a physical blocking type or a filter material capacity critical type or a normal operation.

[0131] The influent rate optimization adjustment module adjusts the influent rate according to the integrated blocking signal, and outputs the optimized effluent water quality.

[0132] The activity release rate generation module activates the micro-current stimulation device and generates the activity release rate when the integrated blocking signal indicates the filter material capacity critical type and lasts for a preset time.

[0133] The hierarchical regeneration triggering module triggers hierarchical regeneration based on the activity release rate and generates a saturated regeneration flag.

[0134] The directional adsorption sequence generation module identifies the water source type and switches the water flow path of the non-homogeneous laminated filter material, and generates a directional adsorption sequence.

[0135] The hierarchical adsorption execution module executes hierarchical adsorption according to the directional adsorption sequence, and outputs the final state of the purified water.

[0136] The above merely illustrates and describes the concept of the present application, and those skilled in the art can make various modifications or supplements to the described specific embodiments or adopt similar ways to replace, as long as the modifications or supplements do not deviate from the concept of the present application or exceed the defined scope of the present application, and should belong to the protection scope of the present application.

Claims

1. A method for optimizing the operation of an activated carbon filter for multi-scenario water treatment, characterized in that, The method comprises the following steps: Step S1, collecting real-time target signals of the filter inlet and outlet and filter layer pressure difference increments to generate a dynamic water quality-pressure difference matrix; Step S2, analyzing the dynamic water quality-pressure difference matrix to generate an integrated blocking signal, which is divided into a physical blocking type, a filter material capacity critical type, or a normal operation; Step S3, adjusting the water inflow rate according to the integrated blocking signal, and outputting the optimized effluent water quality; Step S4, when the integrated blocking signal indicates the filter material capacity critical type and lasts for a preset time, activating a micro-current stimulation device and generating an activity release rate; Step S5, triggering hierarchical regeneration based on the activity release rate, and generating a saturated regeneration flag; Step S6, identifying the water source type and switching the water flow path of the non-homogeneous layered filter material to generate a directional adsorption sequence; Step S7, performing layered adsorption according to the directional adsorption sequence, and outputting the final purified water; The step S2 comprises: calculating the amplitude percentage of the filter layer pressure difference increment and the fluctuation percentage of the real-time target signal in the dynamic water quality-pressure difference matrix; when the filter layer pressure difference increment amplitude is greater than or equal to the preset amplitude threshold and the real-time target signal fluctuation is less than or equal to the preset fluctuation threshold, it is determined as the physical blocking type; when the real-time target signal amplitude is greater than or equal to the preset amplitude threshold and the filter layer pressure difference increment fluctuation is less than or equal to the preset fluctuation threshold, it is determined as the filter material capacity critical type; the remaining state is marked as normal operation, and the blocking type code is output as the integrated blocking signal; The step S3 comprises: when the integrated blocking signal indicates the physical blocking type, the water inflow rate is increased and the high-speed backwashing mode is triggered; when the integrated blocking signal indicates the filter material capacity critical type, the water inflow rate is reduced and the slow-flow adsorption mode is triggered; real-time monitoring of the target signal, when the target signal is continuously stable at multiple time points and less than or equal to the preset COD threshold, the optimized effluent water quality is output; The step S6 comprises: identifying the water source type as industrial wastewater or rainwater purification through an external water source monitoring unit; when the water source type is industrial wastewater, the rotating water inflow distributor is controlled to rotate to a first preset angle, so that the water flow preferentially flows through the first layer of high-porosity carbon particle area of the non-homogeneous layered filter material, and a first layer priority instruction is generated as the directional adsorption sequence; when the water source type is rainwater purification, the rotating water inflow distributor is controlled to rotate to a second preset angle, so that the water flow preferentially flows through the second layer of microporous carbon layer area of the non-homogeneous layered filter material, and a second layer priority instruction is generated as the directional adsorption sequence.

2. The method for activated carbon filter operation optimization for multi-scenario water treatment according to claim 1, characterized in that, The step S1 comprises: collecting target data information through the ultraviolet spectrometer installed on the filter inlet pipe and outlet pipe, and creating real-time target signals based on the target data information; measuring the inlet pressure value and outlet pressure value through the inlet pressure sensor and outlet pressure sensor, calculating the filter layer pressure difference as the inlet pressure value minus the outlet pressure value, and subtracting the initial clean state pressure difference value to generate the filter layer pressure difference increment; aligning the real-time target signals and the filter layer pressure difference increments by time stamp, and constructing the dynamic water quality-pressure difference matrix.

3. The multi-scenario water treatment-oriented activated carbon filter operation optimization method according to claim 1, characterized in that, The step S4 comprises: activating the micro-current stimulation device embedded on both sides of the filter, inputting a preset voltage direct current and maintaining a preset current density for a preset power-on time; The pressure difference increment value before power-on and the pressure difference increment value after power-on are measured, and the pressure difference increment decrease amplitude is calculated as the pressure difference increment value before power-on minus the pressure difference increment value after power-on; The activity release rate is calculated as the pressure difference increment decrease amplitude divided by the pressure difference increment value before power-on multiplied by 100 percent.

4. The multi-scenario water treatment-oriented activated carbon filter operation optimization method according to claim 1, characterized in that, The step S5 comprises: When the activity release rate is greater than or equal to the preset release threshold, a delay regeneration instruction is generated and the adsorption saturation timer is reset; When the activity release rate is less than the preset release threshold, a high-temperature steam regeneration program is activated and the preset temperature high-temperature steam is input for a preset regeneration period; After the regeneration program is completed, a saturation regeneration flag is output.

5. The multi-scenario water treatment oriented activated carbon filter operation optimization method according to claim 1, characterized in that, The step S7 comprises: According to the directional adsorption sequence, the water flow sequentially passes through the first layer of high porosity carbon particle area and the second layer of microporous carbon layer area of the non-homogeneous stacked filter material; The layered effluent COD is monitored at the outlet of each filtration area; The final effluent COD is monitored at the final effluent pipeline, and when the final effluent COD is less than or equal to the preset purification threshold at a continuous preset number of time points, a final state purified water is output.

6. The activated carbon filter operation optimization system for multi-scenario water treatment, characterized in that, The operation optimization system uses the operation optimization method as claimed in claim 1, and the operation optimization system comprises: A dynamic water quality-pressure difference matrix generation module acquires real-time target signals at the filter tank inlet and outlet and filter layer pressure difference increments, and generates a dynamic water quality-pressure difference matrix; An integrated blocking signal generation module analyzes the dynamic water quality-pressure difference matrix, generates an integrated blocking signal, and is divided into a physical blocking type, a filter material capacity critical type, or a normal operation; An inlet water rate optimization adjustment module adjusts the inlet water rate according to the integrated blocking signal and outputs an optimized effluent water quality; An activity release rate generation module activates a micro-current stimulation device and generates an activity release rate when the integrated blocking signal indicates the filter material capacity critical type and lasts for a preset time; A hierarchical regeneration triggering module triggers hierarchical regeneration based on the activity release rate and generates a saturation regeneration flag; A directional adsorption sequence generation module identifies the water source type and switches the water flow path of the non-homogeneous stacked filter material, and generates a directional adsorption sequence; A hierarchical adsorption execution module executes hierarchical adsorption according to the directional adsorption sequence and outputs a final state purified water.

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