Method for real-time monitoring and control of resin regeneration process

Abstract

This invention relates to the field of process control technology, specifically a method for real-time monitoring and control of resin regeneration processes, comprising the following steps: acquiring liquid level cycles and pump / valve status to determine regeneration conditions; generating control signals from control parameters; switching processes according to multiple indicators and monitoring the homogeneity of the mixed bed; and collecting data to form a regeneration monitoring record. In this invention, by introducing a real-time liquid level judgment condition and regeneration cycle logic control mechanism, accurate identification of process start-up preconditions and feedback of interruption signals are achieved. Through dynamic identification and analysis of operating parameters and adjustment ranges, state mapping and control coordination among multiple devices in the regeneration process are established, improving the closed-loop response capability of process control. Through multi-indicator identification logic for switching conditions, the risk of false triggering is effectively avoided. Through comprehensive analysis of liquid level disturbances and flow rate changes, quantitative evaluation of mixing homogeneity is achieved, improving the mixing efficiency of the regenerated liquid and the resin utilization effect, and ensuring the stability and safety of the regeneration process.

Description

Technical Field

[0001] This invention relates to the field of process control technology, and in particular to a method for real-time monitoring and control of resin regeneration processes. Background Technology

[0002] The field of process control technology mainly involves the monitoring and regulation of various process parameters in industrial production, such as temperature, pressure, flow rate, liquid level, and chemical composition. It achieves continuous and stable operation of the target process through sensors, actuators, and controls, including parameter acquisition, signal transmission, control strategy execution, and feedback regulation. Open-loop or closed-loop control methods are typically employed to ensure production safety, improve product quality, and reduce energy consumption. Traditional real-time monitoring and control methods for resin regeneration processes refer to the monitoring and control of regenerated liquid injection, replacement, and water washing during the chemical regeneration process to restore the exchange capacity of ion exchange resins after they have been used to treat water or other liquids. This typically relies on a timer controller to set the regeneration cycle and operation time, controlling each stage of the process through preset times or manual switching. Monitoring methods generally involve fixed-point sampling to detect the conductivity or pH value of the resin bed effluent to determine the degree of regeneration. Control methods often use logic circuits or programmable controllers to control valve opening and closing and pump operation.

[0003] Existing technologies in resin regeneration largely rely on timed control to set process switching nodes, lacking real-time sensing capabilities for equipment status and liquid level changes. This makes it difficult to dynamically identify whether regeneration conditions are met, leading to risks of delayed or premature regeneration operations. The operation mode depends on manual judgment and switching, lacking process linkage and logical judgment support, resulting in high operational intensity and a high error rate. The control logic in the regeneration stage is simplistic, relying solely on fixed-point detection to determine the degree of resin regeneration, which cannot comprehensively reflect the operating status of each stage, easily leading to insufficient or excessive regeneration. The equipment start-up and shutdown and liquid level control cannot be precisely coordinated, creating operational hazards such as bed overpressure or resin escape. Regeneration data cannot be uniformly collected and judged, lacking the ability to trace abnormal operating conditions, thus limiting further improvements in operational efficiency and safety. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a method for real-time monitoring and control of the resin regeneration process, comprising the following steps:

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for real-time monitoring and control of the resin regeneration process, comprising the following steps:

[0006] S1: Acquire the liquid level sensor signals of the cation bed, anion bed and mixed bed equipment, the last regeneration interval time, the current pump and valve operating status, identify whether the regeneration preconditions are met, determine whether the water pump and pneumatic valve are all in automatic operation mode, and generate the initial joint control identifier set of the equipment.

[0007] S2: Based on the initial control identifier set of the equipment, read the current operating parameters of the flow control pump group, acid and alkali metering valve group and liquid level valve group of the cation bed, anion bed and mixed bed equipment in the backwashing and regeneration stage, identify whether there are parameters that exceed the range, and generate the regeneration section control signal spectrum;

[0008] S3: Based on the control signal spectrum of the regeneration section, extract the process switching signals of the backwashing, regeneration, replacement and forward washing stages of the cation bed, determine whether the switching conditions are met, mark the abnormal state and record the current stage number, and generate the stage switching trigger logic sequence.

[0009] S4: Combining the stage switching trigger logic sequence, synchronously analyze the start / stop signal of the mixing pump of the mixed bed equipment, the instantaneous opening change of the air inlet valve, and the record of resin layer liquid level fluctuation, determine whether the current mixing process has reached the preset standard, and generate the monitoring result of the mixing process of the mixed bed;

[0010] S5: Based on the monitoring results of the mixed bed stirring process, collect all collected, control, and feedback data, update the unique number label of the current batch task, seal the data records, and generate a real-time monitoring and control record of the resin regeneration process.

[0011] As a further aspect of the present invention, the preconditions for regeneration specifically refer to the following: based on the liquid level data, it is determined that the cation bed and anion bed have reached the upper limit of the regeneration trigger liquid level of 1000 mm, the mixed bed has a liquid level higher than 70% of the total height of the equipment, the regeneration wastewater tank is within the set low liquid level safety range, and the last regeneration interval is greater than the preset minimum regeneration cycle of 8 hours.

[0012] As a further aspect of the present invention, the switching conditions specifically refer to the following: the turbidity of the effluent at the end of the backwash is stably lower than the set threshold; the acid and alkali flow rate during the regeneration stage remains continuous for a period exceeding the set running time; the flow rate fluctuation during the replacement stage is less than the preset allowable flow rate fluctuation threshold; and the effluent water quality monitoring signal during the forward wash stage meets the indicator requirements for five consecutive samplings.

[0013] As a further aspect of the present invention, the initial control identifier set of the equipment includes abnormal liquid level threshold types, abnormal operating status identifiers, regeneration cycle discrimination status, and control mode status set; the regeneration section control signal spectrum includes parameter over-limit types, equipment control status matching information, and control object mapping relationship; the stage switching trigger logic sequence includes switching condition satisfaction identifiers, current process stage index, and stage abnormal record flags; the mixed bed stirring process monitoring results include liquid level disturbance amplitude analysis results, circulation flow rate periodic analysis results, and mixing homogeneity evaluation status; and the real-time monitoring and control record of the resin regeneration process includes a unique task number label, abnormal data identifiers, and execution process data collection records.

[0014] As a further aspect of the present invention, the step of obtaining the initial control identifier set of the device is as follows:

[0015] S111: Acquire real-time data from the level sensors of the cation bed, anion bed, and mixed bed, as well as the level sensor data of the regenerated wastewater tank; determine whether the cation bed and anion bed have reached the upper limit of the regeneration trigger level of 1000 mm; determine whether the level of the mixed bed meets the requirement of being higher than 70% of the total height of the equipment; determine whether the regenerated wastewater tank is within the set low level safety range; and generate a set of level compliance statuses.

[0016] S112: Based on the set of liquid level compliance states, collect the last regeneration interval time recorded by the PLC, determine whether it is greater than the minimum regeneration cycle of 8 hours. If all liquid level states and time conditions are in compliance state, record the regeneration preconditions as satisfied and generate a set of regeneration condition satisfied marker items.

[0017] S113: Based on the set of tags that meet the regeneration conditions, collect the current start / stop status signals of the water pump and pneumatic valve, confirm whether they are all in automatic operation, and obtain the initial control tag set of the equipment.

[0018] As a further aspect of the present invention, the step of obtaining the control signal spectrum of the regeneration section is as follows:

[0019] S211: Based on the initial joint control identifier set of the equipment, collect the operating parameters of the flow control pump group, acid and alkali metering valve group, and liquid level valve group corresponding to the cation bed, anion bed, and mixed bed equipment in the backwashing and regeneration stage, integrate the start and stop setpoint parameters of each equipment, and establish a sequence of equipment operating parameter combinations.

[0020] S212: Based on the combination sequence of the equipment operating parameters, read the preset valve opening adjustment curve and the regenerated liquid dilution ratio adjustment range, compare the real-time value of the valve opening with the corresponding position data of the preset valve opening adjustment curve, perform boundary judgment on the real-time value of the dilution ratio and the preset regenerated liquid dilution ratio adjustment range, index and mark the positions of parameters that exceed the range, and generate an out-of-bounds parameter index set.

[0021] S213: For the set of out-of-bounds parameter indexes, read the corresponding device number, parameter type and operation stage identification information, map and aggregate the normal parameter status and the out-of-bounds parameter status in chronological order, and establish a regeneration section control signal map.

[0022] As a further aspect of the present invention, the step of obtaining the stage switching trigger logic sequence is as follows:

[0023] S311: Based on the control signal spectrum of the regeneration section, extract the process switching signals of the cation bed in the four stages of backwashing, regeneration, replacement and forward washing, split the signals according to the stage sequence, aggregate the process signal identifier and timestamp of each stage in a structured manner, establish a switching event sequence according to the stage number, and generate a set of stage switching signal frames.

[0024] S312: Based on the set of stage switching signal frames, collect monitoring signals of drainage turbidity, acid and alkali flow rate, effluent water quality and main pump flow rate, compare the drainage turbidity of the backwash stage with the set turbidity threshold, compare the duration of acid and alkali flow rate of the regeneration stage with the set running time threshold, compare the flow fluctuation value of the replacement stage with the flow stability amplitude benchmark value, and compare the effluent water quality signal of the forward wash stage with the quality index set after five consecutive samplings to obtain the set of switching condition judgment results;

[0025] S313: Based on the set of switching condition judgment results, logically summarize the judgment results of each stage. If all are marked as satisfied, record the status as switching allowed. If any condition is not satisfied, record the current stage number and add an exception flag bit to establish a stage switching trigger logic sequence.

[0026] As a further aspect of the present invention, the step of obtaining the monitoring results of the mixed bed stirring process is as follows:

[0027] S411: Combining the stage switching trigger logic sequence, collect the start / stop signal of the mixing pump of the mixed bed equipment, the instantaneous opening change data of the air inlet valve, and the liquid level fluctuation record of the resin layer. Index and align the three types of signals according to a unified time base, and synchronize the start / stop status of the mixing pump and the change position of the air inlet valve to generate a mixed bed disturbance time period identifier sequence.

[0028] S412: Based on the mixed bed disturbance time period identifier sequence, extract the liquid level change data and circulation velocity data in the corresponding section, perform maximum and minimum difference calculation on the liquid level fluctuation amplitude, and perform continuous period determination on the circulation velocity change cycle to obtain the liquid level disturbance and flow velocity change matching feature set.

[0029] S413: Based on the disturbance amplitude and periodic regularity of each segment of data in the matching feature set of liquid level disturbance and flow velocity change, the interval judgment of each segment value and the preset discrimination threshold is performed, the time period that meets the threshold interval is recorded, and the time blocks are aggregated into continuous time blocks in the stage order. At the same time, abnormal segments and fluid states are marked to establish the monitoring results of the mixed bed stirring process.

[0030] As a further aspect of the present invention, the step of acquiring the real-time monitoring and control record of the resin regeneration process is as follows:

[0031] S511: Based on the monitoring results of the mixed bed stirring process, all sampled data frames, control signal records, and equipment feedback status collected in the current batch are uniformly aggregated and processed, and aligned and calibrated according to timestamps. All relevant data are constructed into a batch structured information set to generate a task data aggregation matrix.

[0032] S512: Based on the task data aggregation matrix, retrieve and verify the number to which the current batch belongs, update the unique identifier code corresponding to the batch in the record, embed the current batch number field into the newly generated data frame, perform a full replacement operation, and obtain the batch identifier update record set;

[0033] S513: Update the record set according to the batch identifier, mark and seal data records that do not meet the execution order and execution conditions, retain the current batch index and original data pointer, summarize all valid records and sealing identifiers according to the time sequence, and establish a real-time monitoring and control record for the resin regeneration process.

[0034] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0035] By introducing a real-time liquid level judgment condition and regeneration cycle logic linkage mechanism, the system achieves accurate identification of preconditions for process start-up and feedback of interruption signals. Through dynamic identification and analysis of operating parameters and adjustment ranges, it establishes state mapping and control coordination among multiple devices in the regeneration process, improving the closed-loop response capability of process control. Through multi-index identification logic of switching conditions, it effectively avoids the risk of false triggering caused by relying on single-point judgment. Through comprehensive analysis of liquid level disturbance and flow rate changes, it achieves quantitative evaluation of mixing homogeneity, improving the mixing efficiency of regenerated liquid and resin utilization. Through synchronous collection of task numbers and execution data, it enhances data closed-loop capability and anomaly identification response, ensuring the stability and safety of the regeneration process. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a schematic diagram of the steps of the present invention;

[0038] Figure 2 This is a flowchart of the process for obtaining the initial control identifier set of the device in this invention;

[0039] Figure 3 This is a flowchart of the process for obtaining the control signal spectrum of the regeneration section in this invention;

[0040] Figure 4 This is a flowchart for obtaining the stage switching trigger logic sequence of the present invention;

[0041] Figure 5 This is a flowchart of the process for obtaining monitoring results of the mixed bed stirring process according to the present invention;

[0042] Figure 6 This is a flowchart illustrating the real-time monitoring and control record acquisition process for the resin regeneration process of this invention. Detailed Implementation

[0043] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0044] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0045] Please see Figure 1 This invention provides a method for real-time monitoring and control of the resin regeneration process, comprising the following steps:

[0046] S1: Acquire the liquid level sensor signals of the cation bed, anion bed and mixed bed equipment, the last regeneration interval time recorded by the PLC, and the current pump and valve operating status. Identify whether the regeneration preconditions are met (based on the liquid level data, determine whether the cation bed and anion bed have reached the upper limit of the regeneration trigger liquid level of 1000 mm, whether the mixed bed has a liquid level higher than 70% of the total height of the equipment, whether the regeneration wastewater tank is within the set low liquid level safety range, and whether the last regeneration interval time is greater than the preset minimum regeneration cycle of 8 hours). Read the current start and stop flags of the water pumps and pneumatic valves to determine whether they are all in automatic operation mode and generate the initial joint control identifier set of the equipment.

[0047] S2: Based on the initial joint control identifier set of the equipment, read the current operating parameters of the flow control pump group, acid and alkali metering valve group and liquid level valve group of the cation bed, anion bed and mixed bed equipment in the backwashing and regeneration stage, perform matching analysis on the start and stop set points, valve opening adjustment curves and regenerated liquid dilution ratio adjustment range of each equipment, identify whether there are parameters that exceed the range, and generate the regeneration section control signal spectrum.

[0048] S3: Based on the control signal spectrum of the regeneration section, extract the process switching signals of the four stages of cation bed backwashing, regeneration, replacement and forward washing, and determine whether the switching conditions are met (the turbidity of the effluent at the end of backwashing is stable below the set threshold, the acid and alkali flow rate in the regeneration stage is maintained for a continuous time for more than the set running time, the flow fluctuation in the replacement stage is less than the preset flow fluctuation allowable threshold, and the effluent water quality monitoring signal in the forward washing stage meets the index requirements for five consecutive samplings). If all conditions are met, execute the command for the next stage. If any condition is not met, mark the abnormal state and record the current stage number, and generate the stage switching trigger logic sequence.

[0049] S4: Combining the stage switching trigger logic sequence, synchronously analyze the start and stop signals of the mixing pump of the mixed bed equipment, the instantaneous opening change of the air inlet valve, and the liquid level fluctuation record of the resin layer. Analyze the liquid level disturbance amplitude and the degree of periodic change of the circulation velocity within the fluid mixing time segment, determine whether the current mixing process has reached the preset standard, and generate the monitoring results of the mixed bed mixing process.

[0050] S5: Based on the monitoring results of the mixed bed stirring process, all collected, control and feedback data are aggregated, the unique number label of the current batch task is updated, data records that do not meet the execution order and execution conditions are marked and sealed, and a real-time monitoring and control record of the resin regeneration process is generated.

[0051] The initial control identification set for the equipment includes abnormal liquid level threshold types, abnormal operating status identifiers, regeneration cycle discrimination status, and control mode status set. The control signal spectrum for the regeneration section includes parameter over-limit types, equipment control status matching information, and control object mapping relationships. The stage switching trigger logic sequence includes switching condition fulfillment identifiers, current process stage index, and stage abnormal record flags. The mixed bed stirring process monitoring results include liquid level disturbance amplitude analysis results, circulation flow rate periodic analysis results, and mixing homogeneity assessment status. The real-time monitoring and control record for the resin regeneration process includes unique task number tags, abnormal data identifiers, and execution process data collection records.

[0052] Please see Figure 2 The specific steps of S1 are as follows:

[0053] S111: Acquire real-time data from the level sensors of the cation bed, anion bed, and mixed bed, as well as the level sensor data of the regenerated wastewater tank; determine whether the cation bed and anion bed have reached the upper limit of the regeneration trigger level of 1000 mm; determine whether the level of the mixed bed meets the requirement of being higher than 70% of the total height of the equipment; determine whether the regenerated wastewater tank is within the set low level safety range; and generate a set of level compliance statuses.

[0054] A data transmission channel is established with the field instruments in the cation exchanger, anion exchanger, mixed bed, and regeneration wastewater tank via an industrial fieldbus interface (such as Profinet or Modbus TCP protocol), and the analog signals from each level sensor are collected in real time through polling. Specifically, the acquisition process first reads the 4-20mA current signal fed back from the ultrasonic level gauges mounted on the top of the cation exchanger (cation bed) and anion exchanger (anion bed), and converts this current signal into a digital millimeter (mm) reading via the analog input module. Simultaneously, the real-time height data from the side-mounted magnetic level gauge of the mixed ion exchanger (mixed bed) and the pressure-converted level value from the submersible hydrostatic level transmitter in the regeneration wastewater collection tank are acquired. The raw level data is then processed using Kalman filtering to remove random noise interference caused by liquid level fluctuations, resulting in a smoothed real-time level value.

[0055] Subsequently, the processed real-time liquid level values ​​of the cation and anion beds are compared with the preset upper limit of the regeneration trigger liquid level, 1000 mm. If the real-time liquid level value of either the cation or anion bed is greater than or equal to 1000 mm, the corresponding equipment is determined to have reached the regeneration requirement limit. Next, the structural parameter database of the mixed bed equipment is retrieved, and the total height of the mixed bed equipment is read. 70% of the total height of the equipment is calculated using a multiplication operation as the minimum operating liquid level threshold. The real-time liquid level value of the mixed bed is compared with this calculated threshold. If the real-time liquid level value is greater than this threshold, the mixed bed liquid level is determined to meet the safety margin requirements for regeneration operation. For example, when the total height of the mixed bed equipment is 3000 mm, 3000 multiplied by 0.7 is used to calculate 2100 mm as the threshold. If the real-time collected mixed bed liquid level is 2150 mm, then 2150 is greater than 2100, and the determination condition is met. Simultaneously, the preset low-level safety upper limit (e.g., 500 mm) of the regeneration wastewater tank is read, and the real-time liquid level of the wastewater tank is compared with this upper limit. If the real-time liquid level is lower than the upper limit, it indicates that the wastewater tank has sufficient volume to accommodate the wastewater discharged from this regeneration. Finally, the liquid level judgment results (satisfied or not satisfied) of all the above devices are logically aggregated to generate a liquid level compliance status set containing the liquid level compliance status of each device.

[0056] S112: Based on the set of liquid level compliance statuses, collect the last regeneration interval time recorded by the PLC, determine whether it is greater than the minimum regeneration cycle of 8 hours. If all liquid level statuses and time conditions are in compliance status, record the regeneration preconditions as met and generate a set of regeneration condition satisfaction markers.

[0057] After acquiring the set of liquid level compliance statuses, the system immediately addresses and reads the timestamp information recorded at the end of the previous regeneration program via the PLC controller's historical data register interface. The time difference between the current real-time clock time and the read timestamp of the last regeneration end is calculated to determine the time interval between the two regeneration operations. Subsequently, the preset minimum regeneration cycle reference value of 8 hours is read, and the calculated time interval is compared with this 8-hour reference value. If the time interval is greater than 8 hours, it indicates that the resin bed has completed a sufficient operating cycle, meeting the regeneration time interval requirements.

[0058] Based on this, a logical AND operation is performed on all status bits in the liquid level compliance status set and the time interval judgment result. Specifically, the regeneration preconditions are considered fully met only when all four conditions are simultaneously true: the cation or anion bed liquid level reaches the trigger limit, the mixed bed liquid level is higher than the 70% threshold, the regeneration wastewater tank liquid level is within the low liquid level safety range, and the regeneration interval is greater than 8 hours. If any one of the conditions is not met, the logical operation result is false. When the logical operation result is true, the regeneration precondition status register is set to "1" to indicate that the condition is met, and a regeneration condition satisfaction flag set containing detailed Boolean values ​​of all verification items is generated for subsequent process calls. For example, if the last regeneration ended 10 hours ago (greater than 8 hours), and all liquid level conditions in S111 are met, then a flag set of all values ​​being "True" is generated.

[0059] S113: Based on the set of tags that meet the regeneration conditions, collect the current start / stop status signals of the water pump and pneumatic valve, confirm whether they are all in automatic operation, and obtain the initial control tag set of the equipment;

[0060] Based on the generated set of regeneration condition satisfaction markers, the system scans the feedback signals of all key actuators involved in the current process flow, specifically including the automatic / manual switching status signals of the regenerated water pump, acid metering pump, alkali metering pump, and inlet / outlet pneumatic valves. Each acquired status signal undergoes logical verification to confirm whether it is in "automatic" remote control mode. If any device (e.g., the acid metering pump) is detected in "manual" mode or a "fault" alarm signal is present, the process interruption logic is immediately triggered, the regeneration program is prohibited from starting, and a corresponding alarm message is output.

[0061] Subsequent operations will only proceed when all controlled devices are confirmed to be in an automatically ready state. The initial status bits of all devices (such as the current on / off position of valves and the current frequency feedback of pumps) will be captured in real time. These status data will be associated and encapsulated with their corresponding device physical address codes to construct an initial control identifier set for the devices. Table 1 shows the initial status data of some key devices for reference.

[0062] Table 1 Initial Status Data Acquisition Table for Key Equipment

[0063]

[0064] As shown in Table 1, the P-101 regenerated water supply pump is currently in automatic mode and in a stopped state, which meets the initial conditions before startup.

[0065] Please see Figure 3 The specific steps of S2 are as follows:

[0066] S211: Based on the initial joint control identifier set of the equipment, collect the operating parameters of the flow control pump group, acid and alkali metering valve group, and liquid level valve group of the cation bed, anion bed and mixed bed equipment in the backwashing and regeneration stage, integrate the start and stop setpoint parameters of each equipment, and establish a combination sequence of equipment operating parameters.

[0067] Based on the acquired initial equipment control identifier set, the process formula database is accessed in depth. For different process stages such as backwashing, regeneration (acid / alkali inlet), displacement, and forward washing, the operating frequency setpoints of the flow control pump groups, the opening setpoints of the acid / alkali metering valve groups, and the response parameters of the level regulating valve groups associated with the cation exchange, anion exchange, and mixed bed equipment are retrieved. In specific execution, the flow setpoint (e.g., 50 cubic meters / hour) of the backwashing stage is bound to the corresponding pump group PID control parameters (proportional and integral coefficients); the acid / alkali concentration target value of the regeneration stage is converted into the pulse frequency or opening percentage parameter of the metering valve group; and the level control target of the displacement stage is converted into the opening limit parameter of the drain valve group.

[0068] The start / stop setpoints, operating frequencies, and target opening degrees of the aforementioned equipment at different stages are structurally integrated according to the time execution sequence of the process flow. By establishing a mapping relationship between equipment IDs and parameter dimensions, a multi-dimensional sequence of equipment operating parameters is constructed. This sequence clearly defines the expected state of each piece of equipment at each time node in the entire regeneration process.

[0069] S212: Based on the equipment operating parameter combination sequence, read the preset valve opening adjustment curve and regenerated liquid dilution ratio adjustment range, compare the real-time valve opening value with the corresponding position data of the preset valve opening adjustment curve, perform boundary judgment on the real-time dilution ratio value and the preset regenerated liquid dilution ratio adjustment range, index and mark the positions of parameters that exceed the range, and generate an out-of-bounds parameter index set.

[0070] Based on the established sequence of equipment operating parameters, the system reads the pre-stored valve flow characteristic curve (i.e., the correspondence between valve opening and flow coefficient Cv) and the safe adjustment range of the regenerated liquid dilution ratio (e.g., 3 to 5 times). During actual control simulations or real-time monitoring, the system collects the real-time feedback value of the valve opening, substitutes it into the valve flow characteristic curve for interpolation calculation, obtains the corresponding theoretical flow value, and calculates the deviation rate between this theoretical flow value and the process set flow value. If the deviation rate exceeds the preset tolerance range (e.g., ±5%), or if the real-time valve opening value falls into the nonlinear dead zone of the curve, the parameter is determined to be abnormal.

[0071] Simultaneously, real-time acid / alkali inlet flow rates and reclaimed water flow rates are collected, and the real-time reclaimed liquid dilution ratio is calculated through division. For example, when the reclaimed water flow rate is 10 cubic meters per hour and the acid inlet flow rate is 2 cubic meters per hour, the dilution ratio is 5 times. This real-time dilution ratio is then compared with a preset adjustment range of 3 to 5 times for boundary judgment. If the calculated result exceeds this range (e.g., the calculated result is 6 times or 2 times), it is determined to be out of bounds. All parameter locations determined to be out of bounds or abnormal are indexed and marked, and their corresponding equipment number, parameter type, and occurrence time are recorded to generate an out-of-bounds parameter index set.

[0072] S213: For the out-of-bounds parameter index set, read the corresponding equipment number, parameter type and operation stage identification information, map and aggregate the normal parameter status and the out-of-bounds parameter status in chronological order, and establish the regeneration section control signal map;

[0073] For the generated out-of-bounds parameter index set, the metadata contained in each index item in the set is first parsed to extract the device number (e.g., V-201), parameter type (e.g., opening feedback), and corresponding operation stage identifier (e.g., regeneration acid inlet stage) of the out-of-bounds device. Then, the normal device operation parameter status (sequence from S211) is used as the background layer, and the abnormal status in the out-of-bounds parameter index set is used as the warning layer, and they are mapped and aggregated according to a unified time axis.

[0074] This aggregation operation constructs a visual or logical control signal map of the regeneration stage. In this map, the horizontal axis represents the time axis of the regeneration process, and the vertical axis represents the control signal values ​​of each device. Normal signals are displayed as standard curves or status bars, while out-of-bounds anomalies are specially marked on the corresponding time coordinates. This map fully reproduces the control signal change trends and potential anomaly distributions during the regeneration process, providing panoramic data support for subsequent stage switching determination.

[0075] Please see Figure 4 The specific steps of S3 are as follows:

[0076] S311: Based on the control signal spectrum of the regeneration section, extract the process switching signals of the cation bed in the four stages of backwashing, regeneration, replacement and forward washing, split the signals according to the stage sequence, perform structured aggregation of the process signal identifier and timestamp of each stage, establish a switching event sequence according to the stage number, and generate a set of stage switching signal frames.

[0077] Based on the constructed control signal map of the regeneration section, a signal feature extraction algorithm is used to identify and extract the process switching signals between the four key process stages of the cation bed: backwashing, regeneration, displacement, and forward washing. Specifically, the register value transition edges representing the stage sequence in the control signal map (e.g., from Step 1 to Step 2) are monitored, and these transition moments are marked as stage switching points. The extracted switching signals are then processed according to the inherent process sequence of backwashing, regeneration, displacement, and forward washing.

[0078] For each segmented phase process signal, its corresponding phase identifier (e.g., "Phase_Backwash") is structurally aggregated with the precise start and end timestamps of that phase to form a standard data frame containing the phase ID, start time, end time, and duration. These data frames are arranged sequentially according to the ascending phase numbers (1 to 4) to establish a switching event sequence, ultimately generating a set of phase switching signal frames containing complete regeneration process timing information.

[0079] S312: Based on the set of stage switching signal frames, collect monitoring signals of drainage turbidity, acid and alkali flow, effluent water quality and main pump flow, compare the drainage turbidity of the backwash stage with the set turbidity threshold, compare the duration of acid and alkali flow in the regeneration stage with the set running time threshold, compare the flow fluctuation value of the replacement stage with the flow stability amplitude benchmark value, and compare the effluent water quality signal of the forward washing stage with the quality index set after five consecutive samplings to obtain the set of switching condition judgment results;

[0080] Based on the time windows of each stage determined by the stage switching signal frame set, real-time monitoring signals from the turbidity sensor, acid and alkali flow meter, effluent multi-parameter water quality analyzer (conductivity / silicon meter), and main pump flow meter are simultaneously acquired. During the backwash stage, the turbidity value of the effluent is read and compared with a set turbidity threshold (e.g., 5 NTU) to determine if it is less than the threshold, confirming that the backwash is clean. During the regeneration stage, the duration of flow readings on the acid and alkali flow meters is recorded and compared with a set minimum acid / alkali injection time threshold (e.g., 45 minutes) to confirm sufficient contact time of the regenerated solution. During the replacement stage, the standard deviation or fluctuation amplitude of the flow signal is calculated and compared with a flow stability baseline value (e.g., ±0.5 m³ / h) to determine if the replacement flow rate is stable. During the forward wash stage, five consecutive effluent water quality signals (e.g., conductivity) are acquired, the average of these five samples is calculated, and this average is compared with the acceptable limit value (e.g., 0.2 µS / cm) in the effluent quality index set. Summarize the Boolean results (pass / fail) of all the above comparison processes to obtain the switching condition determination result set.

[0081] Table 2 shows the judgment logic and instance data for some switching conditions.

[0082] Table 2. Parameters for Stage Switching Conditions

[0083]

[0084] As shown in Table 2, all parameters met the set requirements after calculation and comparison, and the judgment result was "pass".

[0085] S313: Based on the result set of the switching condition judgment, logically summarize the judgment results of each stage. If all are marked as satisfied, record the status as switching allowed. If any condition is not satisfied, record the current stage number and add an exception flag bit to establish a stage switching trigger logic sequence.

[0086] Based on the set of switching condition judgment results, all judgment sub-items of each process stage are logically summarized. For each stage, the status of the stage is recorded as "switching allowed" only when all associated monitoring indicators within the stage have a judgment result of "pass". If any monitoring indicator has a judgment result of "fail" or "abnormal", the current stage number is immediately recorded, an "abnormal" flag is appended to the status register, and the process is locked to prevent automatic jump to the next stage.

[0087] The final logical judgment results (switching allowed or abnormal lock) of each stage are arranged in the process sequence to establish a stage switching trigger logic sequence. This sequence directly determines whether the regeneration controller can send step increment instructions, ensuring that the process effect of each stage meets the standard before proceeding to the next stage, and preventing the degradation of resin performance caused by incomplete regeneration.

[0088] Please see Figure 5 The specific steps of S4 are as follows:

[0089] S411: Combining the stage switching trigger logic sequence, collect the start and stop signals of the mixing pump of the mixed bed equipment, the instantaneous opening change data of the air inlet valve, and the liquid level fluctuation record of the resin layer. Index and align the three types of signals according to a unified time base, and synchronize the start and stop status of the mixing pump and the change position of the air inlet valve to generate a mixed bed disturbance time period identifier sequence.

[0090] By combining the specific time periods locked by the stage switching trigger logic sequence (especially the periods involving mixed bed operation), the focus is on collecting the start / stop status signals (DI) of the mixing pump inside the mixed bed equipment, the analog data (AI) of the instantaneous opening changes of the air inlet valve (used for air scrubbing), and the continuous fluctuation records of the resin layer level gauge. Since the data sampling frequencies of each sensor may differ, the three types of signals are first indexed and aligned using a millisecond-level time base as a unified axis. An interpolation algorithm is used to fill the gaps in low-frequency signals on the unified time axis, ensuring that all data points are strictly synchronized in time. Next, the start-up moments when the mixing pump status changes from "0" to "1" and the stop moments when it changes from "1" to "0" are identified, along with the opening intervals where the air inlet valve opening is greater than 0. These corresponding time points are mapped onto the time axis to generate a defined sequence of mixed bed disturbance time periods, which precisely defines the specific time intervals in which hydrodynamic disturbances exist within the mixed bed.

[0091] S412: Based on the mixed bed disturbance time period identifier sequence, extract the liquid level change data and circulation velocity data in the corresponding section, perform maximum and minimum difference calculation on the liquid level fluctuation amplitude, and determine the continuous period of circulation velocity change cycle to obtain the liquid level disturbance and flow velocity change matching feature set.

[0092] Based on a time window defined by the mixed-bed disturbance time period identifier sequence, liquid level change time-series data and circulation velocity data within this window are extracted using an internal Doppler flow meter or PIV. For the liquid level data, an extreme value search algorithm is executed to find the maximum and minimum liquid level values ​​within the window, and the liquid level fluctuation amplitude (i.e., maximum value minus minimum value) is calculated by subtraction. For example, if the maximum liquid level is 2500 mm and the minimum liquid level is 2300 mm, the fluctuation amplitude is 200 mm. For the circulation velocity data, zero-crossing detection or peak detection methods are used to identify the periodic characteristics of the velocity waveform, and the time difference between two consecutive peaks is calculated as the circulation velocity change period. The calculated liquid level fluctuation amplitude value and the velocity change period value are paired and encapsulated to obtain a matching feature value set of liquid level disturbance and velocity change. This feature value set quantitatively reflects the suspension and mixing intensity of the resin inside the mixed bed under air-water disturbance.

[0093] S413: Based on the disturbance amplitude and periodic regularity of each segment of data in the matching feature set of liquid level disturbance and flow velocity change, the interval judgment of each segment value and the preset discrimination threshold is performed, the time period that meets the threshold interval is recorded, and the time blocks are aggregated into continuous time blocks in the stage order. At the same time, abnormal segments and fluid states are marked to establish the monitoring results of the mixed bed stirring process.

[0094] Based on the matching feature value set of liquid level disturbance and flow velocity change, a preset discrimination threshold range is read. This threshold range is the fluctuation amplitude range (e.g., 150mm to 250mm) and period range (e.g., 2 seconds to 5 seconds) corresponding to the optimal mixing effect obtained through experimental calibration. The fluctuation amplitude and period values ​​of each data segment in the feature value set are compared with the above threshold range. If the fluctuation amplitude is between 150mm and 250mm and the period is between 2 seconds and 5 seconds, the mixing state within this time period is determined to be "homogeneous and effective". All continuous time periods that meet the threshold range are recorded and aggregated into continuous "effective mixing time blocks" in chronological order. For data segments that do not meet the threshold range, they are marked as "insufficient mixing" or "excessive turbulence" abnormal segments, and the corresponding fluid state parameters are recorded. Finally, a monitoring result of the mixed bed stirring process is established, which includes the effective mixing time ratio and abnormal event records, used to evaluate the mixing uniformity of the mixed bed resin.

[0095] Please see Figure 6 The specific steps of S5 are as follows:

[0096] S511: Based on the monitoring results of the mixed bed stirring process, all sampled data frames, control signal records, and equipment feedback status collected in the current batch are uniformly aggregated and processed, and aligned and calibrated according to the timestamp. All relevant data are constructed into a batch structured information set to generate a task data aggregation matrix.

[0097] Based on the monitoring results of the mixed bed stirring process, a full data collection procedure is initiated. All raw sampling data frames collected in the current regeneration batch (all sensor data involved in S111-S412), all control signal records issued by the control system (instructions in S211-S213), and the actual operating status feedback from the equipment (status in S113) are uniformly aggregated. Using the UTC timestamps inherent in each data packet as an alignment reference, a data fusion operation is performed, mapping data from different sources and in different formats to the same high-dimensional matrix structure. The constructed task data collection matrix has each row representing a time step and each column representing a sensor or control variable, ensuring the spatiotemporal consistency and integrity of the data.

[0098] S512: Based on the task data aggregation matrix, retrieve and verify the number to which the current batch belongs, update the unique identifier code corresponding to the batch in the record, embed the current batch number field into the newly generated data frame, perform a full replacement operation, and obtain the batch identifier update record set;

[0099] Based on the generated task data aggregation matrix, the batch number (BatchID, e.g., "REG-20260109-001") assigned to the current regeneration task is retrieved from the MES or host computer database. Each data record in the aggregation matrix is ​​checked to confirm its ownership. Subsequently, a batch update operation is performed, writing this unique batch identifier code into the "Batch_ID" field of each frame of data in the matrix, and performing a full replacement to ensure that all data carries an unalterable task tag. This process generates a batch identifier update record set, realizing the digital binding between the underlying process data and the upper-level production task management, providing an index key for subsequent quality traceability.

[0100] S513: Update the record set according to the batch identifier, mark and seal data records that do not conform to the execution order and execution conditions, retain the current batch index and original data pointer, summarize all valid records and sealing identifiers according to the time series, and establish a real-time monitoring and control record for the resin regeneration process.

[0101] Based on the batch identifier update record set, data cleaning and compliance checks are performed. According to the preset process logic sequence rules, the record set is checked for abnormal records with reversed timestamps, logical conflicts (such as washing forward before reverse), or status jumps. Data records that do not conform to the execution sequence or conditions are not directly deleted, but are marked "invalid" or "abnormally sealed," and their original data pointers are retained for auditing. Valid records that pass the check are finally summarized in chronological order. All valid records, along with abnormal records marked with sealing tags, are written into the industrial real-time database or historical database to establish a complete real-time monitoring and control record for the resin regeneration process. This record not only contains qualified process parameters but also fully preserves traces of abnormal events, achieving 100% digital traceability and auditability of the regeneration process.

[0102] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of protection of the described technical solutions.

Claims

1. A method for real-time monitoring and control of the resin regeneration process, characterized in that, Includes the following steps: S1: Acquire the liquid level sensor signals of the cation bed, anion bed and mixed bed equipment, the last regeneration interval time, the current pump and valve operating status, identify whether the regeneration preconditions are met, determine whether the water pump and pneumatic valve are all in automatic operation mode, and generate the initial joint control identifier set of the equipment. S2: Based on the initial control identifier set of the equipment, read the current operating parameters of the flow control pump group, acid and alkali metering valve group and liquid level valve group of the cation bed, anion bed and mixed bed equipment in the backwashing and regeneration stage, identify whether there are parameters that exceed the range, and generate the regeneration section control signal spectrum; S3: Based on the control signal spectrum of the regeneration section, extract the process switching signals of the backwashing, regeneration, replacement and forward washing stages of the cation bed, determine whether the switching conditions are met, mark the abnormal state and record the current stage number, and generate the stage switching trigger logic sequence. S4: Combining the stage switching trigger logic sequence, synchronously analyze the start / stop signal of the mixing pump of the mixed bed equipment, the instantaneous opening change of the air inlet valve, and the record of resin layer liquid level fluctuation, determine whether the current mixing process has reached the preset standard, and generate the monitoring result of the mixing process of the mixed bed; S5: Based on the monitoring results of the mixed bed stirring process, collect all collected, control, and feedback data, update the unique number label of the current batch task, seal the data records, and generate a real-time monitoring and control record of the resin regeneration process.

2. The method for real-time monitoring and control of the resin regeneration process according to claim 1, characterized in that: The specific preconditions for regeneration are as follows: based on the liquid level data, it is determined that the cation bed and anion bed have reached the upper limit of the regeneration trigger liquid level of 1000 mm, the mixed bed has a liquid level that is 70% higher than the total height of the equipment, the regeneration wastewater tank is within the set low liquid level safety range, and the last regeneration interval is greater than the preset minimum regeneration cycle of 8 hours.

3. The method for real-time monitoring and control of the resin regeneration process according to claim 1, characterized in that: The switching conditions specifically refer to the following: the turbidity of the effluent at the end of the backwash is stably lower than the set threshold; the acid and alkali flow rate during the regeneration stage remains continuous for a period exceeding the set operating time; the flow rate fluctuation during the replacement stage is less than the preset allowable flow rate fluctuation threshold; and the effluent water quality monitoring signal during the forward wash stage meets the indicator requirements for five consecutive samplings.

4. The method for real-time monitoring and control of the resin regeneration process according to claim 1, characterized in that: The initial control identifier set for the equipment includes abnormal liquid level threshold types, abnormal operating status identifiers, regeneration cycle discrimination status, and control mode status set. The regeneration section control signal spectrum includes parameter over-limit types, equipment control status matching information, and control object mapping relationship. The stage switching trigger logic sequence includes switching condition satisfaction identifiers, current process stage index, and stage abnormal record flags. The mixed bed stirring process monitoring results include liquid level disturbance amplitude analysis results, circulation flow rate periodic analysis results, and mixing homogeneity evaluation status. The real-time monitoring and control record of the resin regeneration process includes a unique task number label, abnormal data identifiers, and execution process data collection records.

5. The method for real-time monitoring and control of the resin regeneration process according to claim 1, characterized in that, The steps for obtaining the initial control identifier set of the device are as follows: S111: Acquire real-time data from the level sensors of the cation bed, anion bed, and mixed bed, as well as the level sensor data of the regenerated wastewater tank; determine whether the cation bed and anion bed have reached the upper limit of the regeneration trigger level of 1000 mm; determine whether the level of the mixed bed meets the requirement of being higher than 70% of the total height of the equipment; determine whether the regenerated wastewater tank is within the set low level safety range; and generate a set of level compliance statuses. S112: Based on the set of liquid level compliance states, collect the last regeneration interval time recorded by the PLC, determine whether it is greater than the minimum regeneration cycle of 8 hours. If all liquid level states and time conditions are in compliance state, record the regeneration preconditions as satisfied and generate a set of regeneration condition satisfied marker items. S113: Based on the set of tags that meet the regeneration conditions, collect the current start / stop status signals of the water pump and pneumatic valve, confirm whether they are all in automatic operation, and obtain the initial control tag set of the equipment.

6. The method for real-time monitoring and control of the resin regeneration process according to claim 1, characterized in that, The steps for obtaining the control signal spectrum of the regenerator section are as follows: S211: Based on the initial joint control identifier set of the equipment, collect the operating parameters of the flow control pump group, acid and alkali metering valve group, and liquid level valve group corresponding to the cation bed, anion bed, and mixed bed equipment in the backwashing and regeneration stage, integrate the start and stop setpoint parameters of each equipment, and establish a sequence of equipment operating parameter combinations. S212: Based on the combination sequence of the equipment operating parameters, read the preset valve opening adjustment curve and the regenerated liquid dilution ratio adjustment range, compare the real-time value of the valve opening with the corresponding position data of the preset valve opening adjustment curve, perform boundary judgment on the real-time value of the dilution ratio and the preset regenerated liquid dilution ratio adjustment range, index and mark the positions of parameters that exceed the range, and generate an out-of-bounds parameter index set. S213: For the set of out-of-bounds parameter indexes, read the corresponding device number, parameter type and operation stage identification information, map and aggregate the normal parameter status and the out-of-bounds parameter status in chronological order, and establish a regeneration section control signal map.

7. The method for real-time monitoring and control of the resin regeneration process according to claim 1, characterized in that, The steps for obtaining the phase switching trigger logic sequence are as follows: S311: Based on the control signal spectrum of the regeneration section, extract the process switching signals of the cation bed in the four stages of backwashing, regeneration, replacement and forward washing, split the signals according to the stage sequence, aggregate the process signal identifier and timestamp of each stage in a structured manner, establish a switching event sequence according to the stage number, and generate a set of stage switching signal frames. S312: Based on the set of stage switching signal frames, collect monitoring signals of drainage turbidity, acid and alkali flow rate, effluent water quality and main pump flow rate, compare the drainage turbidity of the backwash stage with the set turbidity threshold, compare the duration of acid and alkali flow rate of the regeneration stage with the set running time threshold, compare the flow fluctuation value of the replacement stage with the flow stability amplitude benchmark value, and compare the effluent water quality signal of the forward wash stage with the quality index set after five consecutive samplings to obtain the set of switching condition judgment results; S313: Based on the set of switching condition judgment results, logically summarize the judgment results of each stage. If all are marked as satisfied, record the status as switching allowed. If any condition is not satisfied, record the current stage number and add an exception flag bit to establish a stage switching trigger logic sequence.

8. The method for real-time monitoring and control of the resin regeneration process according to claim 1, characterized in that, The steps for obtaining the monitoring results of the mixed bed stirring process are as follows: S411: Combining the stage switching trigger logic sequence, collect the start / stop signal of the mixing pump of the mixed bed equipment, the instantaneous opening change data of the air inlet valve, and the liquid level fluctuation record of the resin layer. Index and align the three types of signals according to a unified time base, and synchronize the start / stop status of the mixing pump and the change position of the air inlet valve to generate a mixed bed disturbance time period identifier sequence. S412: Based on the mixed bed disturbance time period identifier sequence, extract the liquid level change data and circulation velocity data in the corresponding section, perform maximum and minimum difference calculation on the liquid level fluctuation amplitude, and perform continuous period determination on the circulation velocity change cycle to obtain the liquid level disturbance and flow velocity change matching feature set. S413: Based on the disturbance amplitude and periodic regularity of each segment of data in the matching feature set of liquid level disturbance and flow velocity change, the interval judgment of each segment value and the preset discrimination threshold is performed, the time period that meets the threshold interval is recorded, and the time blocks are aggregated into continuous time blocks in the stage order. At the same time, abnormal segments and fluid states are marked to establish the monitoring results of the mixed bed stirring process.

9. The method for real-time monitoring and control of the resin regeneration process according to claim 1, characterized in that, The steps for obtaining the real-time monitoring and control records of the resin regeneration process are as follows: S511: Based on the monitoring results of the mixed bed stirring process, all sampled data frames, control signal records, and equipment feedback status collected in the current batch are uniformly aggregated and processed, and aligned and calibrated according to timestamps. All relevant data are constructed into a batch structured information set to generate a task data aggregation matrix. S512: Based on the task data aggregation matrix, retrieve and verify the number to which the current batch belongs, update the unique identifier code corresponding to the batch in the record, embed the current batch number field into the newly generated data frame, perform a full replacement operation, and obtain the batch identifier update record set; S513: Update the record set according to the batch identifier, mark and seal data records that do not meet the execution order and execution conditions, retain the current batch index and original data pointer, summarize all valid records and sealing identifiers according to the time sequence, and establish a real-time monitoring and control record for the resin regeneration process.

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