Bioreactor-based intelligent treatment of fermentation tail water to meet discharge standards control method and system

Abstract

The application discloses a fermentation tail water intelligent treatment standard control method and system based on a bioreactor, and particularly relates to the technical field of sewage standard control. The method comprises the following steps: multi-source data management, collecting and adjusting the pH, conductivity, temperature, flow rate of the outlet of a regulating pool and the pH of the inlet of a bioreactor, and connecting the CIP start and end, cleaning process identification and valve position state of a cleaning station, completing unified management and time alignment; impact risk grading, jointly evaluating the pH deviation amplitude and change rate and checking the CIP path, generating a CIP impact risk comprehensive quantity and a risk grade; emergency control linkage, executing bypass temporary storage, inlet flow limiting or stopping, acid-alkali segmented dosing and uniform mixing strengthening; gradual recovery release, calculating the recovery release reliability based on the inlet steady state margin, recovery power margin, standard head margin and impact memory decay quantity, and restraining the gradual return of the temporary storage tail water and triggering the rollback loop and event archive.

Description

Technical Field

[0001] This invention relates to the field of wastewater treatment technology, and more specifically, to a method and system for intelligent treatment and control of fermentation effluent from bioreactors. Background Technology

[0002] Fermentation wastewater treatment systems are frequently affected by batch-specific external disturbances during actual operation, with Clean In-Place (CIP) being the most typical and frequent source of such disturbances. Fermentation workshops typically conduct CIP at night or during batch changes, often involving alkaline washing followed by acid washing. Wastewater from the final stage of CIP is discharged into the wastewater system via drains or recycling pipelines. Due to the extreme pH, large instantaneous discharge volume, and distinct phases characteristic of CIP wastewater, if it is not fully mixed with normal wastewater in the equalization tank, or if a high-alkaline or high-acid mass is directly flushed into the equalization tank outlet due to valve misoperation or improper pipeline switching, the pH of the bioreactor influent may deviate significantly within minutes, creating an acid or alkaline shock to the biochemical system.

[0003] Existing fermentation wastewater treatment systems primarily rely on single-point pH monitoring in the equalization tank, employing slow, steady-state acid and alkali addition and closed-loop regulation. However, in scenarios involving concentrated CIP discharges or sudden changes, this control strategy often suffers from insufficient response speed, failing to promptly suppress minute-level abrupt changes. Furthermore, information such as the start and end times of CIP on the production side, the stage of the cleaning process, and valve position signals at the cleaning station are typically not incorporated into the wastewater control system. This results in a lack of feedforward control data on the wastewater side, leading to on-site treatment often relying on manual processes such as pH exceeding alarm limits in the equalization tank, manual confirmation, manual valve shut-off, or temporary storage. This process is prone to delays, misjudgments, or inconsistent operations. In addition, cleaning wastewater may form short-circuit flows or stratified flows within the equalization tank, allowing extreme water masses to bypass thorough mixing and penetrate directly to the outlet or even the bioreactor inlet. Simply relying on single-point pH monitoring in the equalization tank and slow chemical dosing is insufficient to cover such sudden hydraulic and water quality coupling events.

[0004] The aforementioned acid or alkali shocks can inhibit nitrification and cause a short-term increase in effluent ammonia nitrogen. In severe cases, this can lead to sludge floc disintegration and decreased activity, prolonging the recovery period and requiring reprocessing or off-site disposal. This results in a simultaneous increase in operating costs and environmental risks. To address these issues, this invention proposes a solution. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a method and system for intelligent treatment and control of fermentation wastewater based on bioreactors to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for intelligent treatment and control of fermentation effluent from bioreactors to meet standards includes the following steps:

[0008] Collect pH, conductivity, temperature, and flow rate at the outlet of the equalization tank, as well as the pH of the bioreactor influent; access the on-site cleaning CIP start signal, CIP end signal, cleaning process identifier, and the on / off status of valves related to cleaning wastewater or the key valve position status of the cleaning wastewater recovery pipeline at the production-side cleaning station; align the wastewater-side and production-side data in time to form a reliable set of observations.

[0009] Based on a credible set of observations, the deviation magnitude and rate of change of pH at the outlet of the equalization tank are jointly evaluated within a sliding time window, and candidate intervals for suspected shock events are generated by combining the minimum duration constraint. The candidate intervals are cross-validated using cleaning process identifiers and valve position status to confirm CIP shock events or acid-base shock events of unknown origin. A comprehensive CIP shock risk metric is constructed, which is generated by fusing the acid-base shock impulse index, CIP path consistency confidence, and shock transmission factor. The risk level is classified according to the comprehensive CIP shock risk metric and preset thresholds.

[0010] Based on the confirmed type and risk level of the impact event, the system is switched to emergency control mode; when the risk level reaches moderate or severe, a bypass storage operation is performed to isolate the impact water mass, and the influent to the bioreactor is restricted or stopped; at the same time, based on the deviation direction of the pH at the outlet of the equalization tank, the acid metering pump or alkali metering pump is started for staged addition, and the mixing in the equalization tank is enhanced.

[0011] After the impact event subsides, a recovery release confidence level is generated based on the inlet steady-state margin, recovery dynamic margin, compliance margin, and impact memory decay. Based on the recovery release confidence level, the tailwater temporarily stored in the emergency buffer pool or bypass storage unit is subject to gradual return control. During the return process, the return flow rate is dynamically adjusted or the system is triggered to return to the temporary storage mode according to the effluent quality and system status.

[0012] In a preferred embodiment, the wastewater-side and production-side data are time-aligned to form a reliable set of observations. This includes: performing physical boundary and rate-of-change constraint checks on continuous signals and maintaining the most recent valid value when the data is determined to be abnormal. The continuous signals include at least pH at the outlet of the equalization tank, conductivity, temperature, flow rate, and pH of the bioreactor influent; performing jitter removal and state preservation processing on discrete signals. The discrete signals include at least CIP start signal, CIP end signal, cleaning process identifier, and the on / off status of valves related to cleaning wastewater or the critical valve position status of the cleaning wastewater recovery pipeline; and performing time alignment and resampling alignment of the wastewater-side and production-side signals using the receiving time as a unified timescale.

[0013] In a preferred embodiment, the deviation magnitude is the absolute amount of the shift of the smoothed pH at the outlet of the equalization tank relative to the dynamically updated stable baseline, which is obtained by dynamically updating the pH statistics at the outlet of the equalization tank during non-shock and stable operation periods; the rate of change is the change in pH at the outlet of the equalization tank after smoothing at adjacent sampling times, combined with the sampling period, to determine the intensity of change per unit time; the acid-base shock impulse index is generated based on the joint evaluation results of the deviation magnitude and the rate of change within the sliding time window.

[0014] In a preferred embodiment, the CIP path consistency confidence is generated based on the cleaning process identifier, valve position status, and temporal correlation with the CIP event; the shock conduction factor is determined based on the shift of the bioreactor influent pH during the shock event, relative to the shift of the equalization tank outlet pH.

[0015] In a preferred embodiment, the risk level is divided into mild, moderate and severe; and when determining the level based on the comprehensive CIP impact risk, a hysteresis fallback strategy is introduced.

[0016] In a preferred embodiment, a candidate interval for a suspected impact event is generated when it meets the constraints of minimum deviation threshold, minimum rate of change threshold, and minimum duration within a continuous sliding time window. Furthermore, after a candidate interval is confirmed as a CIP impact event or an acid-base impact event of unknown origin, an event file is formed, recording the event type, start time, end time, peak value and duration of the comprehensive CIP impact risk, bypass storage activation time, current limiting amplitude and duration, cumulative acid-base dosage, and the evolution of the return flow over time. Based on the event file, the risk classification threshold, fusion weight, retention time, and impact memory decay-related parameters are corrected and updated.

[0017] In a preferred embodiment, after completing the risk level classification, graded alarm information is generated according to the mild, moderate and severe risk levels. The graded alarm information includes at least the event type, risk level and real-time updated CIP impact risk comprehensive quantity, and the graded alarm information is written to the operation log or associated with the event file.

[0018] In a preferred embodiment, the confidence level for resuming release is generated by integrating the inlet steady-state margin, the recovery dynamic margin, the compliance margin, and the impact memory decay. The inlet steady-state margin is determined at least based on the fluctuation, out-of-bounds, and trend of the bioreactor influent pH. The recovery dynamic margin is determined at least based on the state of dissolved oxygen and redox potential in the reaction zone and the consistency of the return control. The compliance margin is determined at least based on the compliance status and trend of effluent pH and ammonia nitrogen. The impact memory decay is determined at least based on the peak value and time decay characteristics of the CIP impact risk composite in this impact event.

[0019] In a preferred embodiment, progressive backflow control of the temporarily stored tailwater is implemented based on the confidence level of the resumption of release, including: starting the backflow flow rate from a low value and increasing it in a gradient, reassessing the system status after each increase; and triggering a backflow and reducing or shutting down the backflow when the confidence level of the resumption of release is lower than a threshold or when water quality deterioration is detected.

[0020] In a preferred embodiment, the following modules are included:

[0021] The multi-source data management module is used to collect pH, conductivity, temperature, and flow rate at the outlet of the equalization tank, as well as pH of the bioreactor influent; it also receives the on-site cleaning CIP start signal, CIP end signal, cleaning process identifier, and the on / off status of valves related to cleaning wastewater or the key valve position status of the cleaning wastewater recovery pipeline from the production-side cleaning station; and it aligns the wastewater-side and production-side data in time to form a reliable set of observations.

[0022] The shock risk classification module is used to jointly evaluate the deviation magnitude and rate of change of pH at the outlet of the equalization tank within a sliding time window based on a set of reliable observations, and generate candidate intervals for suspected shock events by combining minimum duration constraints. The candidate intervals are cross-validated using cleaning process identifiers and valve position status to confirm CIP shock events or acid-base shock events of unknown origin. A comprehensive CIP shock risk quantity is constructed, which is generated by fusing the acid-base shock impulse index, CIP path consistency confidence, and shock transmission factor. Risk levels are classified according to the comprehensive CIP shock risk quantity and preset thresholds.

[0023] The emergency control strategy execution module is used to switch the system to emergency control mode according to the confirmed impact event type and risk level. When the risk level reaches moderate or severe, it performs bypass storage to isolate the impact water mass and restricts or stops the flow of water into the bioreactor. At the same time, according to the deviation direction of the pH at the outlet of the equalization tank, it starts the acid metering pump or alkali metering pump for staged addition and enhances the mixing in the equalization tank.

[0024] The gradual recovery release module is used to generate recovery release confidence based on inlet steady-state margin, recovery dynamic margin, compliance margin, and impact memory decay after the impact event subsides. Based on the recovery release confidence, the module implements gradual return control of the tailwater temporarily stored in the emergency buffer pool or bypass storage unit, and dynamically adjusts the return flow rate or triggers a return to the temporary storage mode according to the effluent quality and system status during the return process.

[0025] The technical effects and advantages of this invention are as follows:

[0026] This invention unifies and aligns the pH, conductivity, temperature, flow rate, and bioreactor influent pH at the equalization tank outlet with the CIP start signal, CIP end signal, cleaning process identifier, and valve position status on the production side, forming a reliable set of observations. This allows for the synchronous perception of sudden changes in wastewater and external disturbances on the production side, providing reliable input for minute-level impact identification. Within a sliding time window, the invention jointly evaluates the deviation magnitude and rate of change of pH at the equalization tank outlet and sets a minimum duration constraint. Combined with cross-validation of cleaning process identifier and valve position status, a comprehensive CIP impact risk quantity is constructed and risk level is classified. This reduces misjudgments and delayed responses caused by relying solely on single-point pH exceedances.

[0027] Following an impact, the system automatically switches to emergency control mode based on the event type and risk level. It uses a bypass to temporarily store the impact water mass and restricts or stops the flow of water to the bioreactor inlet. Simultaneously, it drives acid or alkali metering pumps in the direction of deviation to add water in stages and enhance mixing, achieving rapid damage mitigation and reducing the impact on nitrification and effluent indicators. After the impact subsides, a recovery release confidence level is generated based on inlet steady-state margin, recovery dynamic margin, compliance margin, and impact memory decay. This constrains the gradual return of temporarily stored effluent and triggers a back-loop closed loop when water quality deteriorates, preventing secondary impacts or short-term exceedances caused by a single return. Simultaneously, an operation log and event archive are generated, providing a basis for adjusting parameters such as thresholds, weights, and hold times, improving the system's long-term traceability, adaptability, and stability. Attached Figure Description

[0028] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0029] Figure 1 This is a schematic diagram of the process for the intelligent treatment and control method of fermentation effluent based on a bioreactor according to the present invention.

[0030] Figure 2 This is a schematic diagram of the intelligent treatment and compliance control system for fermentation wastewater based on a bioreactor, as described in this invention. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] Example 1: The present invention provides a method for intelligent treatment and control of fermentation effluent from a bioreactor to meet emission standards. Figure 1 As shown, it includes the following steps:

[0033] Step 1: Multi-source data governance;

[0034] The purpose of Step 1 is to make the critical state of the fermentation effluent from the equalization tank to the bioreactor inlet section of the wastewater treatment system observable and usable. This involves capturing the acid-base shock, water mass composition changes, and hydraulic shock characteristics caused by CIP cleaning wastewater within minutes, thereby providing a basis for subsequently constructing a comprehensive CIP shock risk assessment. Provides unified and reliable input data; CIP is an abbreviation for Clean In Place, which refers to a cleaning method that achieves online cleaning and removal of residues by circulating or flushing the cleaning medium inside equipment, pipelines and storage tanks according to a predetermined process through preset cleaning pipelines and valve switching without disassembling the production equipment.

[0035] Specifically, the online monitoring unit preferably includes at least the following data collection points: a flow meter is installed at the outlet of the equalization tank effluent pump or on the equalization tank effluent pipeline to obtain the equalization tank effluent flow rate, and a level gauge is installed inside the equalization tank to obtain the equalization tank level; a pH sensor, conductivity sensor, and temperature sensor are installed on the equalization tank outlet pipeline to simultaneously observe the acid-base shock intensity, changes in the composition of the cleaning solution and salt, and the temperature difference characteristics of the cleaning water; a second pH sensor is installed on the bioreactor inlet pipeline to verify the water mass transfer between the equalization tank outlet and the bioreactor inlet, in order to identify the risk of short-circuit flow, stratified flow, or local extreme water mass directly reaching the inlet. Simultaneously, the equalization tank inlet flow rate is also connected to establish an inlet-outlet water volume balance constraint during shocks, assisting in the judgment of whether there are abnormal discharges or short-term hydraulic shocks.

[0036] In addition to online signals from the wastewater side, this step also integrates CIP (Clean Injection) external disturbance information from the production-side cleaning station into the system. This external disturbance information includes at least CIP start signals, CIP end signals, and cleaning process identifiers. Preferably, the cleaning process identifiers distinguish between alkaline washing, acid washing, and rinsing, allowing for greater risk assessment of the alkaline or acid washing stages under the same pH fluctuation conditions. Simultaneously, it is preferable to integrate the on / off status of valves related to cleaning wastewater or the critical valve positions of cleaning wastewater recovery pipelines to determine whether cleaning wastewater is on a possible path to the wastewater system. Through these methods, not only can sudden changes occurring on the wastewater side be detected, but events occurring on the production side can also be used to create prior constraints on shocks, improving the reliability and timeliness of subsequent shock identification from the source.

[0037] After the signal is received, the central control performs unified data management on the aforementioned data streams to prevent false triggering in subsequent calculations due to sensor malfunctions, communication jitter, or short-term noise. The central control sets physical boundaries and rate-of-change constraints for multiple continuous signals such as pH, conductivity, temperature, and effluent flow rate at the regulating tank outlet. Physical boundaries are used to exclude abnormal readings, such as pH exceeding the measurable range, or conductivity or temperature exhibiting extreme values ​​that do not conform to operating conditions. Rate-of-change constraints are used to exclude abnormal jumps within a single sampling period. When a signal exceeds its limits, jumps, drops out, or freezes for an extended period, the data corresponding to that moment is judged as abnormal data. The control input is maintained by holding the most recent valid value, and the abnormal event is stored in the operation log. To avoid frequent triggering caused by minor noise, short-window smoothing of pH, conductivity, temperature, and flow rate signals can be selected to obtain a more stable data sequence for trend judgment; moving average or exponential moving average methods can be selected. Taking exponential moving average as an example, its form can be expressed as:

[0038] ;

[0039] in, These are the original sampled values. The output value is smoothed. The sampling period is The smoothing coefficient is and satisfies , A larger value indicates a higher weighting of historical values ​​and a smoother output; in this embodiment, It can be used to smooth the pH, conductivity, temperature, or effluent flow rate at the outlet of the equalization tank, respectively. It should be noted that the above smoothing is only used to suppress measurement noise and communication jitter, and does not change the detectability of minute-level impact events. The smoothing coefficient and sampling period can be adjusted according to the on-site noise level and impact response requirements.

[0040] For discrete quantities such as CIP signals and valve position signals, this step preferably employs a debouncing and state-holding strategy. Debouncing eliminates potential jitter during switching, preventing short-term repetitions between the start and end points. State holding maintains the most recent valid state during brief communication interruptions or signal packet loss, ensuring consistent event constraints for subsequent steps when determining whether an impact might be related to CIP. Simultaneously, wastewater and production data are time-aligned, preferably using the reception time as a unified timescale, mapping all data to the same sampling time axis. Resampling or interpolation alignment of data from different sampling periods is performed as needed, allowing subsequent feature calculations to be completed within the same time window.

[0041] Step 2: Impact Risk Classification;

[0042] The purpose of step two is to utilize the credible observation set output from step one to promptly and robustly identify and quantify the acid-base shocks introduced by CIP cleaning wastewater on a minute-level timescale, and output the risk level and comprehensive CIP shock risk that can be directly used for subsequent emergency control mode linkage. Unlike methods that rely solely on a single-point threshold of pH at the equalization tank outlet for over-limit alarms, this step involves a joint assessment of the deviation magnitude and rate of change of pH at the equalization tank outlet. It also incorporates cross-validation of the production-side CIP process status and valve position status, further verifying whether the shock penetrates to the bioreactor inlet. This reduces the probability of false alarms and missed alarms, making it particularly suitable for actual operating conditions where the equalization tank experiences short-circuit flow, stratified flow, or localized water masses directly reaching the outlet and inlet.

[0043] Specifically, abrupt changes in pH at the outlet of the equalization tank are assessed within a continuous sliding time window. The deviation magnitude characterizes the degree of shift of the current pH from the stable baseline, while the rate of change characterizes the intensity of pH spikes or dips over a short period. The stable baseline is preferably taken from a historical period without CIP disturbances and during which the system operates smoothly, and is updated using a moving average or moving median to accommodate slow background shifts in raw water without masking minute-level abrupt changes. The filtered pH value at the outlet of the equalization tank is compared with the baseline value, and combined with the differential changes between adjacent sampling times to form a joint judgment on the intensity and rate of change of the abrupt change. When the pH at the outlet of the equalization tank experiences a rapid rise or fall within the sliding time window, and this abrupt change meets the minimum deviation threshold, minimum rate of change threshold, and minimum duration constraints, the corresponding time period is marked as a candidate interval for a suspected shock event. The minimum duration constraint is used to avoid false triggering due to sensor jitter or instantaneous spikes, ensuring that the candidate interval reflects a continuous and real disturbance.

[0044] To further reduce false positives, this embodiment introduces cross-validation of candidate intervals for suspected shock events using the CIP process status and valve position status on the production side. Within the candidate interval, the system checks whether the CIP start or end signals and cleaning process identifiers are valid, and whether the valves related to cleaning wastewater are open and leading into the wastewater system. When the candidate interval coincides with the CIP signal in time, and the process identifier indicates a high-risk stage such as alkaline or acidic washing, while the valve position status indicates that the cleaning wastewater pathway is open, the candidate interval is confirmed as a CIP shock event. When the CIP signal is missing or the process identifier is unavailable, but there is a significant pH change at the equalization tank outlet and the duration exceeds the minimum event duration threshold, the candidate interval is confirmed as an acid / alkali shock event of unknown origin, and the system proceeds to the subsequent shock treatment process. Through this cross-validation mechanism, the system can maintain its ability to identify real shocks even when CIP signals are abnormal, communication is unstable, or the production side fails to report completely, while avoiding frequent disturbances caused by triggering emergency response based solely on single-point anomalies on the wastewater side.

[0045] After confirming the impact event, a comprehensive CIP impact risk assessment is further constructed. This is used to quantify impact intensity, CIP path prior, and entry penetration risk in a unified manner, in order to complete risk classification and drive the mode switching in step three. Unlike fusing multiple pieces of evidence one by one, this embodiment preferably uses [the method] to calculate... The comprehensive analysis parameters converge to three: acid-base impact impulse index, etc. CIP path consistency confidence and impact transmission factor .in, Used to characterize the intensity and abruptness of acid-base shocks at the outlet of the equalization tank. This is used to characterize whether the impact is consistent with the path of CIP alkaline washing or acid washing with the valve position open. Used to characterize whether the impact has penetrated to the bioreactor inlet, thereby enabling... It also covers three key dimensions: how severe the impact was, whether it was caused by CIP, and whether it truly threatens the entry point of the biochemical segment.

[0046] Specifically, firstly, the deviation amplitude and rate of change are constructed based on the pH at the outlet of the equalization tank, and then an acid-base shock impulse index is formed. Preferably, the pH deviation amplitude and rate of change at the outlet of the equalization tank are respectively:

[0047] ,

[0048] ;

[0049] in, The pH value at the outlet of the conditioning tank after filtering; To stabilize the baseline pH, it is preferable to obtain the moving mean or moving median from a period of stable operation without CIP disturbances and update it slowly over time. The sampling period is defined as follows. To better reflect the destructive power of impacts with large amplitude and rapid changes, the acid-base impact impulse index is preferably normalized and generated in the following form:

[0050] ;

[0051] in, To deviate from the amplitude reference range, As a reference range for the rate of change, both can be calibrated based on process experience and historical event records; This is a truncation function used to restrict the result to the range of 0 to 1.

[0052] Secondly, construct the CIP path consistency confidence value. This is used to incorporate the CIP process status and valve position status on the production side as external disturbance priors into quantification, making it easier to determine high-risk situations such as alkaline washing or acid washing with valves open under the same pH impact. The preferred method is to generate the following:

[0053] ;

[0054] in, CIP process identifier; To determine the valve position status of the wastewater passage, use 1 for open and 0 for closed. This is an indicator function; it takes the value 1 if the condition is met, and 0 otherwise. The start time of CIP or the process switching time is determined by the start or end signal of CIP accessed in step one; This is a time consistency decay constant, used to indicate that the closer the timing is to the CIP (Continuous Ingress Point) sequence, the higher the path confidence. Based on this definition, the confidence can be automatically reduced when a CIP signal exists but the valve position path is not valid, and false alarms can be suppressed when pH shocks do not match the CIP sequence.

[0055] Next, construct the impact transmission factor. This is used to verify whether abnormal water masses have penetrated to the bioreactor inlet, to adapt to operating conditions such as short-circuit flow, stratified flow, or localized water masses directly reaching the inlet in the equalization tank. Preferably, the pH deviation range of the bioreactor influent is first constructed:

[0056] ;

[0057] in, The pH of the filtered bioreactor influent. To establish a stable baseline. The preferred definition of the impact transmission factor is:

[0058] ;

[0059] in, To prevent extremely small positive numbers with a denominator of 0, a value of 0.01 to 0.05 (pH units) is preferred. When the deviation of the influent pH of the bioreactor is close to the deviation of the outlet pH of the equalization tank, A value close to 1 indicates strong impact penetration and weak buffering effect; when the inlet deviation is significantly smaller than the outlet deviation, A value close to 0 indicates that the impact has been effectively buffered and weakened during transmission.

[0060] Based on the above three comprehensive analysis parameters, a comprehensive CIP impact risk quantity is generated. The preferred method for fusion is as follows:

[0061] ;

[0062] in, , , To integrate weights, satisfy And preferably satisfy .in accordance with The minimum duration constraint is used to classify the severity as mild, moderate, and severe: mild is used to characterize situations where there are fluctuations but the impact on the bioreactor inlet is controllable; moderate is used to characterize situations where bypass storage and flow restriction protection need to be activated; and severe is used to characterize situations where the impact water mass needs to be immediately isolated and stronger flow restriction or short-term shutdown of the bioreactor feedwater needs to be implemented.

[0063] Specifically, setting risk classification thresholds (Mild threshold) (Medium threshold) (Severe threshold), satisfying Simultaneously set the minimum duration. As a preferred embodiment, it is possible to take , , , minute, Minutes. The grading logic is as follows: Mild impact: when And continue to exceed Moderate impact: when And continue to exceed Severe impact: when And continue to exceed To avoid frequent changes in risk levels, this embodiment preferably introduces a hysteresis fallback strategy in the risk level determination process, that is, when... Below the fallback threshold ,For example And continue to maintain the set holding time. Only after this is the risk level allowed to drop, in order to ensure the stability of the execution agency control in step three.

[0064] Step 3: Coordinated execution of emergency control strategies;

[0065] In this embodiment, the purpose of step three is to enable the comprehensive risk assessment after step two confirms the occurrence of a CIP shock event or an acid-base shock event from an unknown source. Driven by the risk level, the system prioritizes blocking the entry of shock water masses into the bioreactor during shock events. At the source, it rapidly stabilizes and enhances the mixing of the effluent from the equalization tank, thereby reducing the impact of the shock on nitrifying bacteria activity and sludge floc structure, and preventing a significant increase in effluent ammonia nitrogen and other indicators within a short period. This step emphasizes the coordinated implementation of three types of actions: isolation and temporary storage, flow restriction protection, and rapid stabilization. This allows the system to move beyond the slow response of a single closed-loop dosing system and achieve controllable loss mitigation even in minute-level shock scenarios.

[0066] Specifically, the event type, risk level, and real-time updates output from step two are received. Subsequently, the system is preferably switched to emergency control mode. This emergency control mode, at the actuator level, includes bypass valves, an emergency buffer tank or bypass storage unit, frequency conversion control of the equalization tank effluent pump, frequency conversion control of the influent valve or influent pump entering the bioreactor, acid and alkali metering pumps, and an equalization tank agitator or circulating return pump. The intensity of the action is selected based on the risk level: when the risk level is moderate or severe, it is preferable to control the switching of the bypass valves, allowing the effluent from the equalization tank outlet to preferentially enter the emergency buffer tank or bypass storage unit, thus isolating and temporarily storing the shock mass; simultaneously, flow restriction or short-term shutdown of the influent entering the bioreactor is implemented to maintain the inlet pH of the bioreactor within an acceptable range, preventing the shock from being directly conducted into the reaction zone. If the risk level is mild, bypass storage may not be activated, but flow restriction and increased monitoring are still preferred to prevent mild shocks from rapidly escalating into moderate to severe shocks due to short-circuit flow in the equalization tank or subsequent CIP process switching.

[0067] To ensure the control strategy is implementable and explainable, this embodiment preferably combines influent flow restriction with... Establish a correlation so that the flow restriction intensity changes continuously with shock risk, rather than being restricted at a fixed ratio. As an optional implementation, set a target allowable influent flow rate for the bioreactor. Set as risk normalization quantity Monotonically decreasing forms, for example:

[0068] ;

[0069] in, This represents the target influent flow rate of the bioreactor at time t; This indicates the design influent flow rate during normal system operation; This is the current limiting intensity coefficient, with a value ranging from 0 to 1, used to limit the maximum current limiting amplitude; For the reason The risk normalization value obtained by mapping ranges from 0 to 1. The larger the value, the stronger the impact, and the smaller the allowable influent. The purpose of this expression is that when the impact approaches the severe threshold, the system can automatically reduce the influent to a low level or even close to a complete shutdown; when the impact subsides, the influent can smoothly recover as the risk decreases, thus avoiding secondary disturbances caused by frequent valve opening and closing or frequent pump raising and lowering. It should be noted that even when performing a short-term shutdown, it is preferable to maintain the minimum operating conditions of internal stirring and basic aeration in the bioreactor to maintain sludge suspension and microbial activity, avoiding recovery difficulties caused by hypoxia or sedimentation.

[0070] During the parallel implementation of isolation, temporary storage, and flow restriction, rapid and stable control of the water quality at the outlet of the equalization tank is simultaneously performed to shorten the duration of shocks and reduce the temporary storage load. Specifically, when the pH at the outlet of the equalization tank is higher than the preset upper limit or significantly higher than the target range, the acid metering pump is activated for segmented addition; when the pH at the outlet of the equalization tank is lower than the preset lower limit or significantly lower than the target range, the alkali metering pump is activated for segmented addition. The segmented addition preferably adopts a small-dose, multiple, and rapid iterative approach, that is, after each addition, a short evaluation period is waited, and the addition requirement is recalculated based on the latest trends in pH, conductivity, and temperature at the outlet of the equalization tank, and then a decision is made on whether to continue adding or adjust the addition rate, thereby avoiding reverse overrush caused by a large-dose addition at once. To further improve stability and address the issue of localized extreme water masses reaching the outlet caused by short-circuit flow and stratified flow in the equalization tank, it is preferable to increase the stirring intensity of the equalization tank or activate the circulating return pump during the impact period. This allows the water in the equalization tank to be quickly mixed, reducing the continuous output of localized extreme water masses. Simultaneously, the conductivity and temperature signals at the equalization tank outlet can be used to assist in judging whether the residual cleaning solution or temperature difference water masses have been significantly reduced. This allows for a more accurate understanding of the impact attenuation process, avoiding relying solely on pH recovery as the sole basis for exiting the emergency mode.

[0071] For shock tailwater entering the emergency buffer pool or bypass storage unit, this embodiment preferably uses an online monitoring unit to collect the liquid level and pH of the storage pool, and accordingly coordinates and controls the inlet and outlet valves of the storage pool: during the rising phase of the shock, priority is given to ensuring that the storage capacity is not quickly depleted, and during the stabilizing or falling phase of the shock, the storage pool is kept within a safe liquid level range to avoid bypass failure due to the storage pool being full.

[0072] Through the aforementioned coordinated control, this step outputs two key results: First, the bioreactor influent state is constrained within safe boundaries, preventing significant deviations in the bioreactor inlet pH, thus ensuring the stability of the nitrifying bacteria and sludge flocs; second, the shock effluent is isolated and rapidly stabilized at the equalization tank, reducing the duration and scope of the shock. This output directly correlates with the reliability of the gradual resumption of feed and release in step four. The computational and rollback closed loop provides a stable premise, thereby forming an implementable, controllable, and traceable emergency response chain for CIP impact scenarios.

[0073] Step 4: Gradually restore passage;

[0074] The purpose of step four is to implement controlled, gradual reinjection of the temporarily stored effluent after step three has completed the isolation and temporary storage of the impact effluent and brought the bioreactor influent state back to the safety boundary. During the recovery phase, unified constraints are placed on the reinjection intensity, effluent release, and re-treatment of the recirculated effluent, thereby avoiding secondary acid / alkali shocks or short-term excessive discharges caused by a single reinjection. This step establishes the credibility of the recovery release. By quantifying the recovery conditions, the recovery process is equipped with calculable safety boundaries, interpretable decision-making basis, and self-protection capabilities that can be rolled back, ultimately achieving continuous and stable compliance of the fermentation wastewater treatment system under CIP impact scenarios.

[0075] Specifically, after the impact event enters the subsidence phase, the pH at the outlet of the equalization tank, the pH of the bioreactor influent, and the liquid level and temporary storage pH of the storage unit are continuously monitored. Ideally, these signals should be maintained within a stable range for a continuous period to avoid premature recirculation due to a sudden drop. Upon entering the recovery phase, the stored effluent is not immediately recirculated to the equalization tank or the front end of the bioreactor. Instead, the recirculation process is defined as a gradual process, starting with a low flow rate and increasing it step by step according to a preset gradient. After each recirculation segment is completed, the stability trend of the inlet and effluent is reassessed, and the confidence level for recovery is updated. Based on this, a decision can be made on whether to continue increasing the return flow, maintain the current return flow, or trigger a reversal. Through the above-mentioned gradual return flow, secondary shocks can be effectively suppressed when residual acidity or alkalinity or compositional fluctuations still exist in the temporarily stored effluent, reducing the risk of nitrifying bacteria in the bioreactor being suppressed again during the recovery period.

[0076] To ensure that the recovery decision has a quantifiable basis for implementation, this embodiment preferably generates the recovery release confidence level based solely on four normalized parameters. This value is set to reflect the relationship between recovery reliability and release risk. As an implementable example, recovery release reliability... It can be calculated in the following form: ;

[0077] in, To restore the credibility of release, a larger value indicates a more reliable restoration and a lower risk of release; to To integrate the weighting coefficients, satisfy the following conditions: And preferably satisfying The four normalization parameters are all limited to the range of 0 to 1 and are evaluated within the same evaluation time window. Internal update, the The sampling period can be set from several minutes to tens of minutes depending on the system inertia, thereby enabling... It reflects stable trends rather than instantaneous fluctuations.

[0078] in, This is the inlet steady-state margin, used to characterize the bioreactor inlet's ability to withstand and suppress acid-base shocks. The calculation steps are as follows: within the evaluation time window... Obtain the pH sequence of the bioreactor influent; calculate the fluctuation factor. ,in It is a function of standard deviation. Calculate the maximum permissible standard deviation of fluctuation (e.g., 0.2 pH units); calculate the out-of-bounds factor. This means that the statistical pH value exceeds the preset safe range. Points ratio ,but ; Calculate trend factor Linear regression was performed on the pH sequence to obtain the slope k. (For example And if the most recent sampling points all fall within the safe range, then Otherwise, it is 0.5; finally, a comprehensive calculation is performed. ,in , , The weighting coefficients are and satisfy the following conditions: As an example, it is acceptable , .

[0079] To restore kinetic margin, this method characterizes the controllable recovery capacity of a bioreactor during the recovery phase. The calculations are based on dissolved oxygen (DO) and redox potential (ORP) in the reaction zone: within the evaluation time window. Obtain the DO and ORP sequences; calculate the deviation factors of DO and ORP relative to their defined intervals, respectively. and Taking DO as an example, ,in This is the average value. For setting value, To determine the maximum allowable deviation, calculate the trend stabilization factors for DO and ORP. If the absolute values ​​of the linear regression slopes of both sequences are less than a set threshold, then Otherwise, it is 0.5; calculate the control consistency factor. Compare the average relative error e between the setpoint and the actual feedback flow rate. Finally, a comprehensive calculation was performed. Weighting coefficient satisfy For example, an equal weight of 0.25 can be used; i is the index, which can be 1, 2, 3, or 4.

[0080] To establish compliance margins, used to quantify the safety margin for effluent compliance, its calculation is based on effluent pH and ammonia nitrogen: calculating the pH compliance factor. If the pH of the effluent within the assessment window is entirely within the discharge standard range, then Otherwise, it is 0; calculate the ammonia nitrogen safety factor. ,in For ammonia nitrogen emission limits, To evaluate the average value within the window, Calculate the ammonia nitrogen trend factor for the set safety threshold (e.g., 80% of the limit). For linear regression of the ammonia nitrogen sequence, if the slope or ,but Otherwise, it is 0.5; finally, a comprehensive calculation is performed. Weighting coefficient , , satisfy + + =1, which can be used as an example. , , .

[0081] The impact memory decay factor is used to introduce a conservative constraint that the severity of the impact decays over time but does not immediately disappear, thus making the recovery process after a severe impact more cautious. As an implementable example, the impact memory decay factor can be: ;

[0082] in, The comprehensive CIP shock risk during this shock event The peak value; The threshold for severe impact; This refers to the moment when the peak occurs; The memory decay time constant is preferably several minutes to tens of minutes; It is an exponentially decaying function; This is a cutoff function, restricting the result to between 0 and 1. Therefore, the greater the impact or the closer to the impact peak, the... The smaller, the more it inhibits The rapid rise in temperature should be avoided to prevent excessively rapid return and release under surface recovery, which could cause secondary shocks or short-term exceedances.

[0083] exist Under the constraints, the return of temporarily stored tailwater and the release of effluent are subject to graded control. Preferably, when When the high reliability threshold is reached and the set holding time is continuously met, the return flow rate is allowed to increase stepwise according to the preset gradient, and the effluent is allowed to enter the normal discharge state when the effluent pH meets the discharge range and the effluent ammonia nitrogen is within the safety margin; when When in the middle range, maintain the feedback at a low level or increase it slowly, and recalculate after each feedback phase. To confirm that the steady-state margin, recovery momentum margin, and target position margin have not been weakened; when If the pH of the bioreactor influent falls below the low confidence threshold, or if abnormal deviations occur in the reaction zone's DO or ORP during the refeeding process, or if the effluent ammonia nitrogen shows a continuous upward trend, or if the consistency between the refeeding execution feedback and control commands significantly decreases, a back-loop is triggered. This reduces the refeeding flow rate or shuts down the refeeding channel and switches back to temporary storage mode. Simultaneously, the flow restriction and rapid stabilization strategy from step three is restored until... The system recovers to a range where further recovery is possible. This fallback mechanism automatically suppresses secondary shocks and short-term overshoot risks during the recovery process, preventing repeated instability caused by overly rapid recovery.

[0084] In addition, to ensure long-term traceability and optimization, step four also involves creating an event archive to record the impact event. Peak value and duration, bypass storage activation time, current limiting range and duration, cumulative acid / alkali dosage, and evolution of return flow over time. The evolution patterns and effluent compliance results are used to correct and update subsequent thresholds, weights, retention times, and memory decay time constants, ensuring stable compliance control under different batches, CIP intensities, and raw water conditions. Through the above gradual feedback, reliability constraints, and backtracking closed loop, controllable recovery delivery results, interpretable effluent release decisions, and traceable event archives are ultimately formed, completing the full closed-loop intelligent compliance control for CIP impacts.

[0085] Example 2: The design of the intelligent treatment and compliance control system for fermentation effluent from a bioreactor, based on the method in Example 1, is as follows: Figure 2 The following modules are shown:

[0086] The multi-source data management module is used to make the key states of fermentation effluent from the equalization tank to the bioreactor inlet section observable and usable after it enters the wastewater treatment system. This module consists of an online monitoring unit that collects data from multiple points and a central control unit that performs unified data management. The online monitoring unit preferably collects at least the equalization tank effluent flow rate, equalization tank level, equalization tank outlet pH, conductivity, and temperature, as well as the bioreactor influent pH, and inputs the equalization tank influent flow rate to form an influent-effluent flow balance constraint. Simultaneously, it inputs external disturbance information from the production-side cleaning station's CIP (Clean Injection Process) system, including at least the CIP start signal, CIP end signal, and cleaning process identifier, and inputs the on / off status or key valve position status of the cleaning wastewater-related valves. The central control sets physical boundaries and rate of change constraints for continuous signals, retains the most recent valid value for abnormal data and writes it to the operation log, and performs short-window smoothing for pH, conductivity, temperature and flow signals. For discrete quantities such as CIP signals and valve position signals, it adopts de-jittering and state preservation strategies, and performs time alignment and resampling alignment for wastewater and production data, thereby outputting a set of reliable observations required for subsequent calculations.

[0087] The shock risk classification module utilizes the aforementioned set of reliable observations to jointly assess the deviation magnitude and rate of change of the pH at the outlet of the equalization tank within a continuous sliding time window. It generates candidate intervals for suspected shock events by combining minimum deviation thresholds, minimum rate of change thresholds, and minimum duration constraints. The module then cross-validates these candidate intervals using the CIP process status and valve position status on the production side to confirm CIP shock events or acid-base shock events of unknown origin. Further, the module constructs and outputs a comprehensive CIP shock risk quantity, preferably generated by fusing the acid-base shock impulse index, CIP path consistency confidence, and shock transmission factor. Based on risk classification thresholds, it classifies the impact as mild, moderate, or severe, while incorporating a hysteresis fallback strategy to suppress frequent risk level jumps. The module's output includes at least the event type, risk level, and a real-time updated comprehensive CIP shock risk quantity, driving subsequent emergency control mode linkage.

[0088] The emergency control strategy execution module is used to switch the system to emergency control mode and execute linkage control after the impact risk classification module confirms the occurrence of a CIP impact event or an acid-base impact event of unknown origin, based on the event type, risk level, and comprehensive CIP impact risk. The emergency control mode preferably includes, at the actuator level, a bypass valve, an emergency buffer tank or bypass storage unit, frequency converter control of the equalization tank effluent pump, frequency converter control of the influent valve or influent pump entering the bioreactor, acid and alkali metering pumps, and an equalization tank agitator or circulating return pump. When the risk level is moderate or severe, the bypass valve is switched to allow the effluent from the equalization tank outlet to preferentially enter the emergency buffer tank or bypass storage unit for isolation and temporary storage, and the influent entering the bioreactor is subject to flow restriction or short-term shutdown. When the risk level is mild, flow restriction and increased monitoring are preferred. Meanwhile, the module performs rapid and stable control of the outlet water quality of the equalization tank during the parallel isolation, temporary storage, and flow restriction: when the pH of the outlet water of the equalization tank is too high, the acid metering pump is started to add acid in stages; when the pH of the outlet water of the equalization tank is too low, the alkali metering pump is started to add alkali in stages. During the shock, the stirring intensity of the equalization tank is increased or the circulation return pump is turned on to enhance the mixing. For the shock tailwater entering the emergency buffer tank or the bypass temporary storage unit, it is preferable to have the online monitoring unit collect the liquid level and temporary storage pH of the temporary storage tank and coordinate the temporary storage inlet and outlet valves accordingly to avoid the bypass failure due to the temporary storage tank being full.

[0089] The gradual recovery and release module is used to implement controlled, gradual return of the temporarily stored effluent after the shock effluent isolation and temporary storage have been completed in step three and the bioreactor influent state has returned to the safety boundary. During the recovery phase, the module uniformly constrains the return intensity, effluent release, and recirculation retreatment. After the shock event enters the subsidence phase, the module continuously monitors the pH at the equalization tank outlet, the pH of the bioreactor influent, and the liquid level and temporary storage pH in the temporary storage unit. After confirming stability for a continuous holding period, it enters the recovery phase. During the recovery phase, the return process is defined as a gradual delivery process, starting the return flow rate from a low value and gradually increasing it according to a preset gradient. After each segment of return is completed, the stability trend of the inlet and effluent is reassessed, and the recovery and release confidence is updated, based on which a decision is made to continue increasing, maintain the current level, or trigger a reversal. The recovery release confidence level is preferably generated based solely on four normalized parameters: inlet steady-state margin, recovery dynamic margin, compliance margin, and shock memory decay. Under the constraint of the recovery release confidence level, graded control is implemented for the temporary effluent return and effluent release. When the recovery release confidence level falls below the low confidence threshold, or when inlet boundary violations, abnormal deviations in DO or ORP in the reaction zone, continuous increases in effluent ammonia nitrogen, or a significant decrease in the consistency between return execution feedback and control commands occur during the return process, a backtracking closed loop is triggered. This reduces the return flow rate or closes the return channel and switches back to temporary storage mode, while simultaneously restoring the flow limiting and rapid stabilization strategies of the emergency control strategy execution module. Furthermore, to achieve long-term traceability and optimization, the module also generates an event archive, recording the peak value and duration of shock events, the bypass temporary storage activation time, the flow limiting amplitude and duration, the cumulative acid and alkali dosage, the evolution of the return flow rate over time, and the effluent compliance results, for subsequent correction and updates of thresholds, weights, and time constants.

[0090] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0092] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0093] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0094] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for intelligent treatment and control of fermentation effluent from a bioreactor to meet emission standards, characterized in that, Includes the following steps: Collect pH, conductivity, temperature, and flow rate at the outlet of the equalization tank, as well as the pH of the influent to the bioreactor; Access the on-site cleaning CIP start signal, CIP end signal, cleaning process identifier, and the on / off status of valves related to cleaning wastewater or the key valve position status of cleaning wastewater recovery pipelines at the production-side cleaning station; align the wastewater-side and production-side data in time to form a reliable set of observations; Based on a credible set of observations, the deviation magnitude and rate of change of pH at the outlet of the equalization tank are jointly evaluated within a sliding time window, and candidate intervals for suspected shock events are generated by combining the minimum duration constraint. The candidate intervals are cross-validated using cleaning process identifiers and valve position status to confirm CIP shock events or acid-base shock events of unknown origin. A comprehensive CIP shock risk metric is constructed, which is generated by fusing the acid-base shock impulse index, CIP path consistency confidence, and shock transmission factor. The risk level is classified according to the comprehensive CIP shock risk metric and preset thresholds. Based on the confirmed type and risk level of the impact event, the system is switched to emergency control mode; when the risk level reaches moderate or severe, a bypass storage operation is performed to isolate the impact water mass, and the influent to the bioreactor is restricted or stopped; at the same time, based on the deviation direction of the pH at the outlet of the equalization tank, the acid metering pump or alkali metering pump is started for staged addition, and the mixing in the equalization tank is enhanced. After the impact event subsides, a recovery release confidence level is generated based on the inlet steady-state margin, recovery dynamic margin, compliance margin, and impact memory decay. Based on the recovery release confidence level, the tailwater temporarily stored in the emergency buffer pool or bypass storage unit is subject to gradual return control. During the return process, the return flow rate is dynamically adjusted or the system is triggered to return to the temporary storage mode according to the effluent quality and system status.

2. The intelligent treatment and control method for fermentation effluent based on a bioreactor to meet standards as described in claim 1, characterized in that: The wastewater and production data are time-aligned to form a reliable set of observations. This includes: checking continuous signals for physical boundaries and rate of change constraints, and using the most recent valid value to preserve data that is deemed abnormal. Continuous signals include at least pH, conductivity, temperature, flow rate at the equalization tank outlet, and pH of the bioreactor influent; de-jittering and state preservation processing is performed on discrete signals, which include at least CIP start signal, CIP end signal, cleaning process identifier, and the on / off status of valves related to cleaning wastewater or the critical valve position status of the cleaning wastewater recovery pipeline; and time alignment and resampling alignment of wastewater and production signals using the receiving time as a unified timescale.

3. The intelligent treatment and control method for fermentation effluent based on a bioreactor to meet standards as described in claim 1, characterized in that: The deviation magnitude is the absolute amount of the shift of the smoothed pH at the outlet of the equalization tank relative to the dynamically updated stable baseline, which is obtained by dynamically updating the pH statistics at the outlet of the equalization tank during non-shock and stable operation periods; the rate of change is the change in the smoothed pH at the outlet of the equalization tank at adjacent sampling times, combined with the sampling period, to determine the intensity of change per unit time; the acid-base shock impulse index is generated based on the joint evaluation results of the deviation magnitude and the rate of change within the sliding time window.

4. The intelligent treatment and control method for fermentation effluent based on a bioreactor to meet standards, as described in claim 1, is characterized in that: The CIP path consistency confidence is generated based on the cleaning process identifier, valve position status, and temporal correlation with the CIP event; the shock conduction factor is determined based on the shift of the bioreactor influent pH during the shock event, relative to the shift of the equalization tank outlet pH.

5. The intelligent treatment and control method for fermentation effluent based on a bioreactor to meet standards as described in claim 1, characterized in that: The risk levels are divided into mild, moderate and severe; and a hysteresis fallback strategy is introduced when determining the level based on the comprehensive amount of CIP impact risk.

6. The intelligent treatment and control method for fermentation effluent based on a bioreactor to meet standards as described in claim 1, characterized in that: Candidate intervals for suspected impact events are generated when they meet the constraints of minimum deviation threshold, minimum rate of change threshold, and minimum duration within a continuous sliding time window. Furthermore, after a candidate interval is confirmed as a CIP impact event or an acid-base impact event of unknown origin, an event file is formed, recording the event type, start time, end time, peak value and duration of the comprehensive CIP impact risk, bypass storage activation time, current limiting amplitude and duration, cumulative acid-base dosage, and the evolution of the return flow over time. Based on the event file, the risk classification threshold, fusion weight, retention time, and impact memory decay-related parameters are corrected and updated.

7. The intelligent treatment and control method for fermentation effluent based on a bioreactor to meet standards as described in claim 1, characterized in that: After completing the risk level classification, generate graded alarm information according to the mild, moderate and severe risk levels. The graded alarm information shall include at least the event type, risk level and real-time updated CIP impact risk comprehensive quantity, and write the graded alarm information to the operation log or associate it with the event file.

8. The intelligent treatment and control method for fermentation effluent based on a bioreactor to meet standards as described in claim 1, characterized in that: The confidence level for resuming release is generated by integrating the inlet steady-state margin, recovery dynamic margin, compliance margin, and shock memory decay. The inlet steady-state margin is determined at least based on the fluctuation, out-of-bounds, and trend of the bioreactor influent pH. The recovery dynamic margin is determined at least based on the state of dissolved oxygen and redox potential in the reaction zone and the consistency of the return control. The compliance margin is determined at least based on the compliance status and trend of effluent pH and ammonia nitrogen. The shock memory decay is determined at least based on the peak value and time decay characteristics of the CIP shock risk composite in this shock event.

9. The intelligent treatment and control method for fermentation effluent based on a bioreactor to meet standards, as described in claim 1, is characterized in that: Based on the confidence level of resuming release, a gradual control of the return of temporarily stored tailwater is implemented, including: starting the return flow rate from a low value and increasing it in a gradient, and reassessing the system status after each increase; when the confidence level of resuming release is lower than the threshold or water quality deterioration is detected, a backtracking is triggered and the return is reduced or shut down.

10. A smart control system for treating and controlling fermentation wastewater from a bioreactor to meet emission standards, characterized in that: The control system is used to implement the method according to any one of claims 1-9, and includes the following modules: The multi-source data management module is used to collect pH, conductivity, temperature, and flow rate at the outlet of the equalization tank, as well as the pH of the bioreactor influent. Access the on-site cleaning CIP start signal, CIP end signal, cleaning process identifier, and the on / off status of valves related to cleaning wastewater or the key valve position status of cleaning wastewater recovery pipelines at the production-side cleaning station; align the wastewater-side and production-side data in time to form a reliable set of observations; The shock risk classification module is used to jointly evaluate the deviation magnitude and rate of change of pH at the outlet of the equalization tank within a sliding time window based on a set of reliable observations, and generate candidate intervals for suspected shock events by combining minimum duration constraints. The candidate intervals are cross-validated using cleaning process identifiers and valve position status to confirm CIP shock events or acid-base shock events of unknown origin. A comprehensive CIP shock risk quantity is constructed, which is generated by fusing the acid-base shock impulse index, CIP path consistency confidence, and shock transmission factor. Risk levels are classified according to the comprehensive CIP shock risk quantity and preset thresholds. The emergency control strategy execution module is used to switch the system to emergency control mode according to the confirmed impact event type and risk level. When the risk level reaches moderate or severe, it performs bypass storage to isolate the impact water mass and restricts or stops the flow of water into the bioreactor. At the same time, according to the deviation direction of the pH at the outlet of the equalization tank, it starts the acid metering pump or alkali metering pump for staged addition and enhances the mixing in the equalization tank. The gradual recovery release module is used to generate recovery release confidence based on inlet steady-state margin, recovery dynamic margin, compliance margin, and impact memory decay after the impact event subsides. Based on the recovery release confidence, the module implements gradual return control of the tailwater temporarily stored in the emergency buffer pool or bypass storage unit, and dynamically adjusts the return flow rate or triggers a return to the temporary storage mode according to the effluent quality and system status during the return process.

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