Fluorescence sensing-based photoelectric panel wastewater fluorine ion extraction on-line monitoring method and extraction method

Abstract

The invention discloses a photoelectric panel waste water fluorine ion extraction online monitoring method based on fluorescence sensing and an extraction method, and belongs to the field of sewage detection, and the method comprises the following steps: pre-monitoring and calibration, extraction process monitoring and optimization, and reverse extraction process monitoring and optimization. The fluorine ion concentration monitoring sensor is pre-monitored, whether a sensor calibration mechanism is triggered or not is judged based on the pre-monitoring result, the fluorine ion concentration is monitored in real time through the sensor, and then whether dynamic compensation is carried out or not to correct the fluorine ion concentration is judged based on parameters in the monitoring process. Meanwhile, an extraction quality index is obtained, whether extraction process optimization is carried out or not is judged to improve the extraction effect of the fluorine ions, and finally, a reverse extraction reaction is carried out, a reverse extraction quality index is obtained, whether reverse extraction process optimization is carried out or not is judged, so that accumulation of the fluorine ions in an oil phase is prevented, and the online monitoring accuracy of fluorine ion extraction is improved; the problem of low online monitoring accuracy of fluorine ion extraction in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of wastewater detection technology, and in particular to an online monitoring method and extraction method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing. Background Technology

[0002] With the booming development of next-generation information industries such as semiconductors and optoelectronic panels, hydrofluoric acid and its fluorides play an irreplaceable role as key materials in core processes such as chip etching. To achieve green and efficient recovery of fluorine resources, fluoride ion extraction is required. The extractant typically consists of a specific mixture of components such as P204, Cyanex 923, and TBP, dissolved in a diluent such as kerosene or ethyl acetate to form an organic phase. This organic phase is then reacted with fluoride-containing wastewater (aqueous phase) in a stirrer at a specific volume ratio, temperature, and stirring rate to achieve fluoride ion transfer. Subsequently, the fluoride-loaded organic phase undergoes alkaline washing and back-extraction to obtain an ammonium fluoride solution. This solution is then subjected to unit operations such as impurity removal filtration, vacuum evaporation, cooling crystallization, and drying to obtain the ammonium fluoride product. The equipment involved in each step includes stirred tanks, precision filters, multi-effect evaporators, crystallizers, centrifuges, and drying equipment.

[0003] The extraction process is a dynamic equilibrium, and its efficiency and stability are directly affected by the reaction conditions. To ensure optimal process operation, real-time and comprehensive online monitoring of the extraction process is crucial. This monitoring integrates real-time monitoring of physicochemical parameters such as reaction temperature, stirring rate, and pH value. These fundamental parameters are collected by various sensors (such as thermometers, pH meters, and level gauges) and uniformly fed into a central process control system, such as a Programmable Logic Controller (PLC). Based on a preset process curve, the PLC automatically adjusts heating power, stirring motor speed, and other parameters to ensure extraction occurs under optimal conditions.

[0004] Among numerous monitoring parameters, the concentration distribution of fluoride ions in the aqueous and organic phases is the most critical indicator for directly measuring extraction efficiency, determining the reaction endpoint, and assessing the organic phase loading capacity. Online monitoring technology for fluoride ion extraction not only needs to measure the fluoride concentration in the initial wastewater and the final back-extraction solution, but also needs to delve into the extraction reaction itself to track changes in the residual concentration in the aqueous phase and the organic phase loading saturation in real time. For example, ion-selective electrodes in ion-selective electrode methods can continuously track changes in fluoride concentration in water, while fluorescence sensors in optical analysis methods can achieve precise measurement of trace amounts of fluoride in complex samples.

[0005] For example, Chinese invention patent application CN119827593A discloses an online monitoring device and method for high concentration chloride ions in wastewater, comprising: a water supply pump, a filter, an inlet regulating valve, an overflow tank, a mixing tank, a detection tank, a wastewater peristaltic pump, a reagent peristaltic pump, a reagent bottle, a chloride ion concentration detector, and a composite electrode. The outlet pipe of the water supply pump is connected to the inlet of the overflow tank in sequence through the filter and the inlet regulating valve. The inlet end of the wastewater peristaltic pump is connected to the overflow tank, and the outlet end is connected to the mixing tank. The inlet end of the reagent peristaltic pump is connected to the reagent bottle, and the outlet end is connected to the mixing tank. The detection tank is connected to the mixing tank. The composite electrode is installed inside the detection tank, and the signal output end of the composite electrode is connected to the chloride ion concentration detector.

[0006] For example, Chinese invention patent application CN118294609A discloses a general-purpose online fluoride ion monitoring system and its monitoring method, comprising: a PLC controller for executing control logic according to preset control parameters; a buffer pump for quantitatively pumping buffer solution from a buffer tank to a monitoring cup; a raw water pump for quantitatively pumping raw water from a raw water sampler to the monitoring cup; a monitoring cup for mixing raw water and buffer solution to provide detection conditions; a monitoring cup stirrer for stirring the mixture in the monitoring cup until fluoride ion detection is completed; and a laboratory benchtop detector for monitoring... The mixture in the measuring cup is subjected to online fluoride ion detection to obtain the fluoride ion concentration value, and the detection result is reported to the host computer via a touch screen; a clean water solenoid valve is used to add clean water to the monitoring cup; a drain solenoid valve is used to drain the mixture in the monitoring cup after the fluoride ion detection is completed; a buffer pump and a raw water pump are respectively connected to the monitoring cup; the clean water solenoid valve and the drain solenoid valve are respectively located on the monitoring cup; the monitoring cup is located on the monitoring cup stirrer, and the stirring head of the monitoring cup stirrer is located in the monitoring cup; the buffer pump, raw water pump, monitoring cup stirrer, clean water solenoid valve, and drain solenoid valve are respectively electrically connected to the PLC controller.

[0007] Online ion monitoring technology enables real-time, continuous, and automated measurement of the types and concentrations of target ions. Ion-selective electrode method is an analytical technique based on electrochemical principles. It utilizes membrane electrodes that selectively respond to specific ions to convert changes in the activity (or concentration) of ions in solution into measurable potential signals. This method has been widely applied to the measurement of common ions, such as fluoride ions (F...). - ), chloride ions (Cl) - Online monitoring of ions, etc. In addition, optical analysis methods, mainly including spectrophotometry and fluorescence methods, are another important online monitoring technology. These methods involve the chemical reaction between target ions and specific chromogenic agents or fluorescent probes, causing changes in the system's absorbance or fluorescence intensity, and converting this optical signal into concentration information.

[0008] The above-mentioned technology has at least the following technical problems: In existing technologies, existing fluorescence sensors exhibit inherent incompatibility when applied to extraction systems containing organic components such as P2O4, Cyanex 923, TBP, and kerosene. On one hand, organic solvents and extractants themselves have high background absorption or fluorescence quenching effects, severely suppressing the effective signal of target analytes (such as fluoride ion probes). On the other hand, these low surface tension substances readily form stable emulsion systems under process stirring, generating strong light scattering, resulting in drastic fluctuations in signal background and a low signal-to-noise ratio.

[0009] Furthermore, for target ions such as fluoride ions, which lack optical characteristics, existing technologies rely on chemical probes for derivatization detection. However, in complex organic-water mixtures, the performance of the probes is susceptible to negative effects from pH, coexisting ions, and organic solvents, leading to decreased selectivity and sensitivity. This further amplifies measurement errors, making it difficult for the system to accurately determine recovery rates or impurity levels at low concentrations.

[0010] Furthermore, due to factors such as signal background fluctuations and probe performance degradation, the acquired signals are severely distorted. If this distorted signal is used for closed-loop control (such as automatically adjusting the back-extraction liquid flow rate and extraction ratio), the control system will generate "reverse adjustment." For example, after receiving a false signal indicating a low fluoride ion concentration, it may mistakenly judge the extraction as insufficient and take measures such as increasing the back-extraction liquid flow rate. When the actual fluoride ion concentration is high, this will not only fail to stabilize the process but will also exacerbate process fluctuations, resulting in waste of extractant, increased energy consumption, or substandard final products. This indicates a problem with low accuracy in online monitoring of fluoride ion extraction. Summary of the Invention

[0011] To address the low accuracy of online monitoring of fluoride ion extraction in existing technologies, this invention provides an online monitoring method and extraction method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing. The technical solution is as follows: On the one hand, an online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing is provided, including: A1. Pre-monitor the fluoride ion concentration monitoring sensor. Based on the pre-monitoring results, determine whether to trigger the sensor calibration mechanism. If so, monitor the fluoride ion concentration in real time through the calibrated sensor after the sensor is calibrated. Otherwise, continue to monitor the fluoride ion concentration in real time through the sensor. A2. Monitor the fluoride ion concentration during the extraction reaction. Based on the parameters monitored, determine whether to perform dynamic compensation to correct the fluoride ion concentration. At the same time, obtain the extraction quality indicators and determine whether to optimize the extraction process to improve the extraction effect of fluoride ions. If the extraction process is optimized, the optimized alkaline-washed oil phase is back-extracted with ammonia water of a preset back-extraction concentration after the extraction process is optimized. Otherwise, the back-extraction reaction is performed directly. A3 monitors the fluoride ion concentration during the back-extraction reaction, obtains back-extraction quality indicators, and determines whether to optimize the back-extraction process, thereby preventing the accumulation of fluoride ions in the oil phase.

[0012] On the other hand, a method for fluoride ion extraction from optoelectronic panel wastewater based on fluorescence sensing includes: S1, using the photoelectric panel etching wastewater as the aqueous phase, and performing an extraction reaction with the extraction phase according to a preset extraction volume ratio and preset extraction mixing conditions, to obtain the raffinate aqueous phase and the fluorine-loaded oil phase; S2, the obtained fluorine-loaded oil phase is subjected to alkaline washing reaction with ammonia water of a preset alkaline washing concentration according to a preset alkaline washing volume ratio and preset alkaline washing mixing conditions to obtain the alkaline-washed oil phase; S3, the obtained alkaline-washed oil phase is back-extracted with ammonia water of a preset back-extraction concentration according to a preset back-extraction volume ratio and preset back-extraction mixing conditions to obtain a fluorine-containing back-extraction solution and a regenerated oil phase. The regenerated oil phase is then transported to the extract phase storage tank for recycling. The regenerated oil phase is the extract phase that has been restored to its initial form and is used for recycling extraction.

[0013] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: 1. The online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing provided by this invention constructs a comprehensive detection and intelligent decision-making system, encompassing sensor pre-monitoring, calibration, and dynamic optimization adjustment based on parameters during extraction and back-extraction processes. Pre-monitoring determines whether sensor calibration is needed and performs timely calibration, avoiding inaccurate fluoride ion concentration measurements due to sensor errors, thus providing a reliable data foundation for subsequent process control. Then, based on parameters monitored, dynamic compensation is performed to correct reading deviations in fluoride ion concentration caused by various factors, making the measurement results more accurately reflect the actual situation. By acquiring extraction quality indicators and determining whether to optimize the extraction process, problems in the extraction process can be identified and process parameters adjusted in a timely manner, thereby improving the extraction rate of fluoride ions and the purity of fluoride ions in the extracted oil phase. This solves the problem in existing technologies where probe performance is easily affected by pH, coexisting ions, and organic solvents, leading to increased measurement errors in fluoride ion concentration. By acquiring back-extraction quality indicators and determining whether to optimize the back-extraction process, the accumulation of fluoride ions in the oil phase is effectively prevented, avoiding adverse effects on subsequent processes caused by fluoride ion accumulation. The regenerated oil phase is fed back to the extraction step for recycling. Through possible optimization of the back-extraction process, the quality of the regenerated oil phase is guaranteed, preventing fluoride ion accumulation and ensuring the efficiency of the next extraction round. This achieves resource recycling and stable process operation. Compared to existing technologies that may only monitor or control a single step, this approach not only focuses on the accuracy of fluoride ion concentration measurement but also closely links the extraction and back-extraction processes. By acquiring and optimizing their respective parameters, the extraction process is optimized based on the parameters, and its impact on the back-extraction process is considered. Similarly, the back-extraction process is optimized based on the parameters and fed back to the extraction step to ensure the efficiency of the next extraction round. This improves the accuracy of online monitoring of fluoride ion extraction and effectively solves the problem of low accuracy in online monitoring of fluoride ion extraction in existing technologies.

[0014] 2. This invention improves the accuracy and reliability of monitoring by installing a fluorescence sensor and an electrochemical sensor in parallel, leveraging their complementarity. The electrochemical sensor serves as the calibration benchmark for the fluorescence sensor, enabling timely detection and calibration of measurement deviations, ensuring the accuracy of the monitoring data. Furthermore, compared to existing technologies that may use only a single type of sensor for fluoride ion concentration monitoring, dual-sensor monitoring reduces monitoring errors caused by single-sensor failures and improves the stability of fluoride ion monitoring. Then, using the fluoride ion concentration benchmark monitored by the electrochemical sensor as a reference, the absolute value of the relative deviation is calculated and compared with the fluorescence correction threshold to scientifically determine whether the fluorescence sensor needs calibration. This ensures that the fluorescence sensor maintains higher measurement accuracy under different operating conditions, avoiding measurement errors caused by untimely or over-calibrated sensors. Moreover, compared to existing offline calibration or simple periodic calibration methods, the invention uses a recursive least squares method to update the slope and intercept of the fluorescence sensor's calibration curve online, achieving real-time sensor calibration. Finally, the probe measurement state value and its fluctuation value are calculated and compared with the probe measurement... By comparing the fluctuation limits of the sensor's state, it is possible to detect sensor drift in a timely and accurate manner. If sensor drift is detected, the sensor self-test mechanism is immediately triggered, which helps to quickly locate the problem and take corresponding measures to ensure the normal operation of the sensor, thereby improving the reliability of fluoride ion extraction monitoring. Finally, compared with the self-test methods in the prior art that may only perform simple functional checks, the comprehensive sensor self-test mechanism, which includes static stability checks, electronic component checks, and optical path integrity checks, can comprehensively check the sensor from different aspects and quickly and accurately locate the cause of the fault. If the probe measurement state fluctuation value is normal in the standard solution, it indicates that the previous problem may have been caused by the instantaneous interference of the process fluid, avoiding unnecessary maintenance and downtime. By self-testing the microcontroller and reading the sensor parameters and comparing them with the baseline parameters, abnormal working status of the core electronic components inside the sensor can be detected in a timely manner. If the reference peak intensity change rate exceeds the upper limit, it indicates that there may be problems such as contamination or damage in the optical path, which will promptly prompt the designated personnel to handle the problem and ensure the normal optical performance of the sensor, thereby ensuring the accuracy of the measurement results.

[0015] 3. By comparing the fluoride ion concentration in the raffinate with the target concentration, the rotation speed of the extraction phase pump is adjusted to change the balance of the extraction process, thereby controlling the fluoride ion concentration in the raffinate. If the deviation of the fluoride ion concentration in the raffinate exceeds the upper limit, feedforward control is used for adjustment first, followed by further adjustment using a PID controller. Otherwise, the PID controller is used directly. Feedforward control can quickly respond to large deviations and make adjustments in advance, while the PID controller can precisely adjust the rotation speed of the extraction phase pump to stabilize the fluoride ion concentration near the target value, balancing the stability and timeliness of flow control. Then, based on the fluoride ion concentration of the back-extraction solution and the target concentration... Based on the concentration comparison results, the speed of the ammonia pump is adjusted to change the ammonia flow rate, thereby controlling the concentration of fluoride ions in the back-extraction solution to achieve the target value. If the deviation of the fluoride ion concentration in the back-extraction solution exceeds the upper limit, feedforward control is used for adjustment first, followed by further adjustment using a PID controller; otherwise, the PID controller is used directly for adjustment. This allows for faster and more accurate control of the fluoride ion concentration in the back-extraction solution. Addressing the control problem of fluoride ion concentration in the raffinate and back-extraction solution, a closed-loop control system is formed, from concentration detection and deviation handling to control strategy adjustment. This solves the problem of low effectiveness in fluoride ion concentration control in existing technologies. Finally, when the PID controller... When the adjustment response time is too long, it indicates that the performance of the PID controller may not meet the requirements. By combining it with a Smith predictor, the hysteresis effect can be overcome, improving the timeliness of PID control. The fluoride ion concentration change curve of the raffinate phase is recorded, and the gain, time constant, and hysteresis time in the extraction process are identified. A transfer function model is established, which can accurately describe the dynamic relationship between the pump speed change and the fluoride ion concentration change. The model parameters are continuously updated by recursive least squares method, which can adapt to changes in operating conditions. This solves the problem of low accuracy of PID control caused by the use of fixed model parameters in the prior art, and improves the accuracy and precision of PID control. The model output and the hysteresis-free model output are obtained based on the transfer function model and the hysteresis time. By comprehensively considering the actual measured value, the model predicted value, and the hysteresis-free model predicted value, a more accurate synthetic feedback signal is obtained, enabling the PID controller to output a more appropriate control signal according to the real-time status of fluoride ion extraction, further improving the precision and stability of fluoride ion extraction. Compared with the prior art, which may only use a single PID control or other simple control methods, this invention combines feedforward control, PID control, and a Smith predictor, which can better cope with complex operating conditions and improve the control performance of the fluoride ion extraction process. Attached Figure Description

[0016] 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.

[0017] Figure 1 A flowchart of a method for fluoride ion extraction from optoelectronic panel wastewater based on fluorescence sensing, provided in an embodiment of this application; Figure 2 A process flow diagram for producing ammonium fluoride from fluoride-containing wastewater provided in the embodiments of this application; Figure 3 A flowchart illustrating the online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing, provided in an embodiment of this application. Figure 4 A flowchart for pre-monitoring provided in the embodiments of this application; Figure 5 A flowchart for optimizing the extraction process provided in the embodiments of this application. Detailed Implementation

[0018] Embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of the present disclosure are shown in the drawings, it should be understood that embodiments of the present disclosure may be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure.

[0019] It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure. In the description of the embodiments of this disclosure, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "this embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc., may refer to different or the same objects.

[0020] 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.

[0021] like Figure 1 The diagram shown is a flowchart of a method for fluoride ion extraction from optoelectronic panel wastewater based on fluorescence sensing, provided in an embodiment of this application. Figure 2 The diagram shown is a process flow chart for producing ammonium fluoride from fluoride-containing wastewater according to an embodiment of this application. The method includes the following steps: The extractant is prepared by mixing P204, Cyanex923 and TBP in a volume ratio of 2:1:1 at 25-60℃ and then diluting it with kerosene or ethyl acetate solvent.

[0022] The raw material tank stores fluoride-containing wastewater and is connected to a metering pump via a pipeline; the extraction mixing vessel (stirred vessel) receives fluoride-containing wastewater (aqueous phase) from the raw material tank and extractant organic phase from the organic phase storage tank via a pipeline. The reactor is equipped with a stirrer, level gauge, temperature sensor, and pH meter. A clarification / sedimentation tank is connected to the extraction mixing reactor via pipeline for the static separation of the mixed oil and water phases. An alkali washing reactor receives the fluorinated organic phase from the clarification tank via pipeline and receives the alkali solution from the alkali storage tank. A back-extraction reactor receives the organic phase and back-extraction agent (such as ammonia) from the alkali washing reactor via pipeline. A back-extraction liquid storage tank receives the ammonium fluoride solution (aqueous phase) from the back-extraction reactor via pipeline. A precision filter is connected to the back-extraction liquid storage tank via pipeline to remove impurities from the ammonium fluoride solution. A multi-effect evaporator receives the filtered ammonium fluoride solution via pipeline for concentration. A crystallization tank receives the concentrated solution via pipeline and is equipped with a cooling jacket and stirrer. A centrifuge receives the crystal slurry from the crystallization tank for solid-liquid separation. A drying device receives the wet crystals from the centrifuge and dries them to obtain the ammonium fluoride product. An organic phase regeneration and recycling system purifies the back-extracted oil phase and pumps it back to the organic phase storage tank via pipeline for recycling. All equipment is connected in series via process piping with control valves, forming a continuous or semi-continuous production line. The flow of materials is precisely controlled by starting and stopping the pumps and opening the control valves.

[0023] S1, using the photoelectric panel etching wastewater as the aqueous phase and the extractant as the oil phase (i.e., the extract phase), the extraction reaction is carried out according to a preset extraction volume ratio (i.e., the volume ratio of the aqueous phase to the extract phase, set by the preset personnel based on experience, such as 1:1 or 4:1) and preset extraction mixing conditions (set by the preset personnel, such as mixing for 20 minutes at a temperature of 25-50℃ and a stirring speed of 100-500 rpm) to obtain the raffinate aqueous phase (i.e., the extractant). Figure 2 The process involves separating the aqueous phase (raffinate) from the aqueous phase and the fluorine-loaded oil phase (an extract phase containing fluorine extracted from the aqueous phase). The aqueous raffinate undergoes further treatment (e.g., adding NaOH and CaCl2) before being discharged as wastewater once it meets emission standards. Through this extraction reaction, target substances such as fluorine in optoelectronic panel etching wastewater can be effectively transferred to the extract phase, achieving initial separation of fluorine from the aqueous phase, reducing the fluorine content in the wastewater, alleviating the burden on subsequent treatment, and laying the foundation for fluorine recovery.

[0024] S2, the obtained fluorine-loaded oil phase is mixed with ammonia water of a preset alkaline washing concentration (set by the engineer based on experience, ranging from 1% to 10%) at a preset alkaline washing volume ratio (i.e., the volume ratio of ammonia water to the fluorine-loaded oil phase, set by the engineer based on experience, for example, 4:1) and preset alkaline washing mixing conditions (set by the engineer, for example, mixing at 25°C and 1000 rpm for 10 min) to carry out an alkaline washing reaction, obtaining an alkaline-washed oil phase. The alkaline washing reaction can remove impurities from the fluorine-loaded oil phase, improve the purity of the oil phase, reduce the interference of impurities on the subsequent back-extraction reaction, ensure the smooth progress and effectiveness of the back-extraction reaction, thereby improving the fluorine recovery rate and product quality.

[0025] In step S3, the obtained alkaline-washed oil phase is back-extracted with ammonia water of a preset back-extraction concentration (set by the operator based on experience, ranging from 10% to 30%) at a preset back-extraction volume ratio (set by the operator based on experience, e.g., 5:1) and preset back-extraction mixing conditions (set by the operator, e.g., mixing at 25°C and 1000 rpm for 10 minutes). This yields a fluorine-containing back-extraction solution and a regenerated oil phase. The regenerated oil phase is then transferred to an extractant storage tank for recycling. The regenerated oil phase is the extractant phase restored to its initial state for reuse in cyclic extraction. The back-extraction reaction transfers fluorine from the oil phase back to the aqueous phase, achieving fluorine recovery and extractant phase regeneration. The regenerated oil phase can be recycled, reducing extractant consumption and costs. Simultaneously, the fluorine-containing back-extraction solution provides raw material for subsequent extraction of ammonium fluoride.

[0026] S4. The obtained fluorine-containing back-extraction solution is filtered using a filter to remove solid impurities, yielding a clarified filtrate and a cake. The cake consists of silica, sulfates, borates, etc. Filtration removes solid impurities from the fluorine-containing back-extraction solution, improving its purity and providing higher-quality raw materials for subsequent evaporation and crystallization processes, thus contributing to improved quality and purity of the final product.

[0027] S5. The obtained filtered clear liquid is sent to an evaporator for reduced pressure evaporation for 0.5-2 hours to obtain a concentrated liquid. Reduced pressure evaporation can lower the evaporation temperature, reduce energy consumption, and avoid the decomposition or deterioration of certain substances due to high temperature; through evaporation and concentration, the concentration of solute is increased, creating favorable conditions for the crystallization process.

[0028] S6. The obtained concentrate is cooled and crystallized under preset crystallization conditions (which can be set to -5℃ to 25℃). After centrifugation, ammonium fluoride is obtained. After washing with saturated ammonium fluoride solution, it is dried at a temperature of 55℃ to 85℃ to obtain ammonium fluoride with a purity ≥93%. The crystallization mother liquor and washing liquid are returned to the impurity removal and filtration process for reuse. Cooling crystallization causes ammonium fluoride to precipitate from the concentrate. Through centrifugation, washing, and drying, a high-purity ammonium fluoride product can be obtained, realizing the effective recovery and utilization of fluorine resources. By using a synthetic extractant to perform directional extraction and back-extraction of free fluoride ions in the etching waste liquid of optoelectronic panels, and then using the fluorine-containing solution obtained from the back-extraction as the core raw material for purification, impurity removal, concentration, crystallization, centrifugation, drying, and packaging, ammonium fluoride products are prepared. This not only realizes the efficient reuse of fluorine resources and greatly improves the utilization level of fluorine resources, but also effectively reduces the secondary pollution hazards of fluorine-containing waste residue.

[0029] like Figure 3 The flowchart shown is a process for online monitoring of fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing, as provided in an embodiment of this application. The process includes: A fluoride ion concentration monitoring sensor is installed at the outlet pipe of the extraction mixing vessel to monitor the residual fluoride ion concentration in the aqueous phase after extraction in real time; a fluoride ion concentration monitoring sensor is also installed at the outlet pipe of the back-extraction vessel to monitor the fluoride ion concentration in the aqueous phase (ammonium fluoride solution) after back-extraction in real time.

[0030] A1 performs pre-monitoring on fluoride ion concentration monitoring sensors (including fluorescence sensors and electrochemical sensors). Based on the pre-monitoring results, it determines whether to trigger the sensor calibration mechanism. If so, the fluoride ion concentration is monitored in real time through the calibrated sensor after calibration. Otherwise, the fluoride ion concentration is obtained through real-time monitoring of the sensor. By determining whether the sensor needs calibration through pre-monitoring and calibrating the sensor in a timely manner, the problem of inaccurate fluoride ion concentration measurement caused by sensor error is avoided, and a reliable data foundation is provided for subsequent process control.

[0031] In A2, when monitoring fluoride ion concentration in S1, dynamic compensation is determined based on parameters during the monitoring process. This corrects for deviations in fluoride ion concentration readings caused by various factors, making the measurement results more accurately reflect the actual situation. Simultaneously, extraction quality indicators are obtained, and it is determined whether the extraction process should be optimized to improve the extraction effect of fluoride ions. If extraction process optimization is performed, the optimized alkaline-washed oil phase is back-extracted with ammonia water of a preset back-extraction concentration after optimization; otherwise, the back-extraction reaction is performed directly. By obtaining extraction quality indicators and determining whether the extraction process should be optimized, problems in the extraction process can be identified in a timely manner, and process parameters can be adjusted, thereby improving the extraction rate of fluoride ions and the purity of fluoride ions in the extracted oil phase. The oil phase after alkaline washing and possible extraction process optimization has a composition and properties more conducive to back-extraction with ammonia water, improving the effectiveness of the back-extraction reaction.

[0032] In step A3, during S2, the back-extraction quality index is obtained while monitoring the fluoride ion concentration to determine whether back-extraction process optimization is necessary. This prevents the accumulation of fluoride ions in the oil phase. If back-extraction process optimization is performed, the optimized regenerated oil phase is then transferred to the extract phase storage tank for recycling. Otherwise, the regenerated oil phase is directly transferred to the extract phase storage tank for recycling to ensure the efficiency of the next extraction cycle. A dynamic compensation mechanism based on monitoring parameters is introduced to correct the fluoride ion concentration reading in real time, improving measurement accuracy. Simultaneously, a mechanism to prevent fluoride ion accumulation in the oil phase is established. Back-extraction process optimization ensures long-term stable operation of the process. By obtaining back-extraction quality indexes and determining whether back-extraction process optimization is necessary, the accumulation of fluoride ions in the oil phase is effectively prevented, avoiding adverse effects on subsequent extraction processes due to fluoride ion accumulation. The regenerated oil phase is transferred to the extract phase storage tank for recycling, and the potential back-extraction process optimization ensures the quality of the regenerated oil phase, thereby guaranteeing the efficiency of the next extraction cycle. This achieves resource recycling and stable process operation.

[0033] This application constructs a comprehensive monitoring and intelligent decision-making system that dynamically optimizes and adjusts the extraction and back-extraction processes based on quality indicators, from sensor pre-monitoring and calibration to extraction and back-extraction processes. It can automatically judge and take corresponding measures based on real-time data. It not only focuses on the accuracy of fluoride ion concentration measurement, but also closely links the extraction and back-extraction processes. By obtaining their respective quality indicators for collaborative optimization, it comprehensively improves the accuracy and effectiveness of fluoride ion concentration measurement and each process step in the fluoride ion extraction process.

[0034] like Figure 4 The flowchart shown is a pre-monitoring process provided in an embodiment of this application. It is further explained that the pre-monitoring includes dual-sensor parallel monitoring and sensor drift determination. The dual-sensor parallel monitoring is an operation performed periodically, and the sensor drift determination is an operation that needs to be performed before each online monitoring of fluoride ion extraction in optoelectronic panel wastewater.

[0035] Parallel monitoring with dual sensors involves installing both fluorescence and electrochemical sensors at key monitoring points (i.e., the outlet pipes of the extraction mixing vessel and the back-extraction vessel). These sensors simultaneously and continuously sample the fluoride ion concentration at the same monitoring point to achieve more comprehensive and accurate monitoring. Based on a pre-defined sensor calibration cycle (e.g., one week) obtained from a database, calibration is performed using the monitoring data from both the fluorescence and electrochemical sensors to determine if the fluorescence sensor's calibration curve needs correction. Parallel monitoring combines the advantages of both sensors, reducing potential errors from a single sensor and improving the accuracy of the monitoring results.

[0036] The fluorescence sensor employs a ratiometric fluorescent probe that includes a response peak that varies with fluoride ion concentration and a reference peak that does not change with fluoride ion concentration. The ratiometric fluorescent probe reflects the fluoride ion concentration by calculating the ratio of the response peak to the reference peak. Since the reference peak does not change with fluoride ion concentration, it effectively eliminates the influence of external factors (such as temperature and light) on fluorescence intensity, improving the stability and accuracy of the measurement.

[0037] An electrochemical sensor (i.e., a fluoride ion-selective electrode) serves as the calibration benchmark for the fluorescence sensor, used to update the slope and intercept of the calibration curve. The calibration curve represents the relationship between the sensor's output signal (e.g., fluorescence intensity) and the measured physical quantity (e.g., fluoride ion concentration). Through the calibration curve, the raw signal output by the sensor can be converted into the actual value of the measured physical quantity. Data monitored by the electrochemical sensor allows for dynamic updates to the slope and intercept of the fluorescence sensor's calibration curve based on actual conditions, enabling the fluorescence sensor to adapt to measurement needs under different environmental conditions.

[0038] The calibration and judgment are based on monitoring data from fluorescence and electrochemical sensors. The specific process is as follows: The fluoride ion concentrations monitored by the fluorescence sensor and the electrochemical sensor were obtained as benchmarks, representing the measurement results of the fluoride ion concentration at the same monitoring point by different sensors.

[0039] If the absolute value of the relative deviation, reflecting the degree of deviation between the fluoride ion concentration and the fluoride ion concentration reference, is greater than the fluorescence correction threshold, the calibration curve of the fluorescence sensor is corrected. Specifically, this means: using recursive least squares, the slope and intercept of the calibration curve of the fluorescence sensor are updated based on the obtained fluoride ion concentration and the fluoride ion concentration reference, achieving online calibration; the absolute value of the relative deviation, reflecting the degree of deviation between the fluoride ion concentration and the fluoride ion concentration reference, is calculated by dividing the difference between the fluoride ion concentration and the fluoride ion concentration reference by the fluoride ion concentration reference, and the absolute value of the relative deviation is recorded as the absolute value of the relative deviation; recursive least squares... Multiplication is used to dynamically adjust model parameters (in this case, the slope and intercept of the calibration curve) as new data is continuously acquired, so as to minimize the sum of squared errors between the model predictions and the actual observations. In online calibration, the calibration curve can be continuously optimized based on real-time data, enabling the fluorescence sensor to quickly return to an accurate measurement state and ensuring the continuity and accuracy of monitoring data. By calculating the absolute value of the relative deviation between the fluoride ion concentration monitored by the fluorescence sensor and the reference fluoride ion concentration monitored by the electrochemical sensor, deviations between the fluorescence sensor measurement results and the reference values ​​can be detected in a timely manner, improving the accuracy and reliability of fluoride ion concentration monitoring data.

[0040] If the absolute value of the relative deviation, which reflects the degree of deviation between the fluoride ion concentration and the fluoride ion concentration reference, is not greater than the fluorescence correction threshold, then the calibration curve of the fluorescence sensor will not be corrected.

[0041] The fluorescence correction threshold is the maximum allowable deviation between the fluoride ion concentration and the fluoride ion concentration baseline, and is set by a preset user, for example, by setting it to the maximum absolute value of the relative deviation over a historical period.

[0042] Specifically, sensor drift determination is as follows: The probe measurement status value in the fluorescence sensor is obtained at a preset concentration (obtained from a preset database and set by the preset personnel based on experience, for example, the median value of the effective measurement range of the fluorescence sensor). The probe measurement status value is the ratio of the response peak intensity of the probe in the fluorescence sensor to the reference peak intensity at the preset concentration. The response peak intensity represents the fluorescence signal intensity measured at a specific wavelength in the fluorescence sensor after the probe interacts with the target substance. By obtaining this ratio at the preset concentration, basic data is provided for subsequent judgment of whether the sensor has drifted, eliminating the direct influence of some non-target factors (such as changes in light source intensity) on the fluorescence intensity measurement, which can more accurately reflect the interaction state between the probe and the target substance and improve the accuracy of the judgment.

[0043] If the probe measurement status fluctuation value (i.e., the standard deviation obtained by calculating the standard deviation of multiple probe measurement status values ​​within a certain time range) is not less than the probe measurement status fluctuation limit, the sensor is determined to have drifted, and the sensor self-test mechanism is triggered; otherwise, the sensor self-test mechanism is not triggered. The probe measurement status fluctuation limit is the maximum allowable fluctuation of the probe measurement status value, which can be set as the maximum value of the probe measurement status fluctuation value within a historical time period. By setting the fluctuation limit and comparing the fluctuation values, it is possible to quickly and effectively determine whether the sensor has malfunctioned (drifted), avoiding unnecessary self-test operations, improving detection efficiency, and triggering the self-test mechanism in a timely manner when an anomaly occurs, which helps to promptly detect and resolve sensor problems and ensure the normal operation of the sensor.

[0044] Sensor self-testing mechanisms include one or more of the following: static stability checks, electronic component checks, and optical path integrity checks. These checks can determine the specific location or cause of sensor failure.

[0045] The static stability check involves monitoring the probe measurement status of the fluorescence sensor in a standard fluoride ion solution (a fluoride ion solution of known accurate concentration used as a reference environment for static stability testing, providing a standard reference for judging the sensor's measurement status under stable conditions). If the fluctuation value of the probe measurement status is not less than the fluctuation limit of the probe measurement status, an electronic component check is performed to check the working status of the core electronic components inside the sensor; otherwise, the sensor is directly judged to be normal. Checking in a standard solution eliminates the influence of changes in the concentration of the target substance on the measurement results, enabling a more accurate judgment of the sensor's measurement status under stable conditions. If the fluctuation value is within the limit, it indicates that the sensor itself may not be faulty, and the previous abnormality may have been caused by instantaneous interference from the process fluid, avoiding misjudgment. If the fluctuation value exceeds the limit, further in-depth inspection of the electronic components is conducted to gradually investigate the cause of the fault, improving the accuracy of fault diagnosis.

[0046] The electronic component inspection specifically involves: the microcontroller inside the sensor performing a self-test, reading sensor parameters including the light source drive current, photodetector dark current, and temperature sensor readings, and comparing them with the sensor baseline parameters (various parameter values ​​pre-measured and recorded under normal and stable operating conditions, such as light source drive current, photodetector dark current, and temperature sensor readings, serving as a benchmark for comparison with real-time measured parameters during subsequent inspections). If a sensor deviation exists, reflecting the degree of deviation between the sensor parameters and the corresponding sensor baseline parameters (obtained by calculating the difference between the real-time measured parameters and the baseline parameters, used to determine whether the sensor electronic component is normal; if the absolute value of the difference between the real-time measured parameters and the baseline parameters is within the allowable deviation range, the sensor electronic component is considered normal, and there is no sensor deviation; the allowable deviation range is predetermined by designated personnel). Based on experience, the settings (e.g., 5%-10% of the baseline parameters) will prompt the preset personnel to detect electronic component abnormalities; otherwise, an optical path integrity check will be performed. The light source drive current represents the current supplied to the light-emitting element inside the sensor, and the photodetector dark current represents the current generated by the detector when no light shines on it. By automatically reading the key parameters of the sensor and comparing them with the baseline parameters through the microcontroller, the working status of the sensor's electronic components can be detected quickly and accurately. Abnormal light source drive current may affect the light intensity and stability of the light source, abnormal photodetector dark current may affect the sensitivity and accuracy of the detector, and abnormal temperature sensor readings may affect the performance of the entire sensor, thus timely detection of electronic component failures, providing a basis for subsequent repair or replacement. At the same time, if the electronic components are normal, the optical path will be further checked to gradually narrow down the scope of the fault.

[0047] The optical path integrity check is as follows: If the reference peak intensity change rate within a preset time period (obtained by calculating the ratio of the change in reference peak intensity to the time interval, where the change in reference peak intensity is the difference between the reference peak intensity measured at the end of the time interval and the reference peak intensity measured at the beginning of the time interval) is greater than the upper limit of the reference peak intensity change rate, it indicates that there may be a problem with the optical path, such as optical path blockage, optical component damage, or positional misalignment, causing abnormal changes in the reference peak intensity. This indicates an abnormality in the optical path integrity for the preset personnel. Otherwise, it indicates that the optical path is normal. In this case, the sensor abnormality may be caused by other reasons (such as probe damage). Further indicating the sensor abnormality helps to comprehensively troubleshoot the fault. The reference peak intensity change rate reflects the change of reference peak intensity over time. The upper limit of the reference peak intensity change rate is the maximum allowable reference peak intensity change rate, which can be set to the maximum value of the reference peak intensity change rate within a historical time period. This improves the reliability and stability of the sensor, reduces measurement errors and misjudgments caused by sensor failures, and ensures the normal operation of the sensor in various environments.

[0048] Furthermore, based on the parameters monitored during the process, it is determined whether dynamic compensation should be performed. The specific process is as follows: The monitoring response time of the fluorescence sensor is obtained during the extraction reaction. By obtaining the monitoring response time, we can understand the working status and response characteristics of the sensor under the current monitoring environment, and provide basic data for subsequent judgment on whether the sensor is working properly.

[0049] If the monitoring response time of the fluorescence sensor exceeds the upper limit, it indicates a sensor monitoring anomaly. Dynamic compensation is then performed to address solvent background interference and improve measurement accuracy. Otherwise, no dynamic compensation is performed. The upper limit is the maximum acceptable monitoring response time, which can be set as the maximum monitoring response time within a historical time period. The monitoring response time is the time required for the fluorescence sensor to reach a stable reading (e.g., fluctuations less than 0.1% concentration change) after contacting the sample. This allows for timely identification of sensor monitoring anomalies. When the monitoring response time exceeds the upper limit, it indicates potential solvent background interference, requiring dynamic compensation to ensure measurement accuracy. If the upper limit is not exceeded, no additional processing is needed, saving computational resources and time.

[0050] Dynamic compensation, specifically: The flow cell is installed on the main process pipeline, allowing online sensors (such as fluorescence sensors, pH meters, etc.) to continuously and in real time measure the flowing liquid without interfering with mainstream production. Taking the extraction mixing vessel outlet pipeline, a key monitoring point, as an example, a bypass is branched off from the main process pipeline connecting the extraction mixing vessel and the clarification tank. The bypass pipeline connects to the inlet of the flow cell, and the outlet of the flow cell returns to the downstream of the main pipeline (usually before the inlet of the clarification tank) through a pipeline. The probe of the fluoride ion concentration monitoring sensor installed on the flow cell is in direct contact with the flowing liquid to perform continuous measurement.

[0051] A fluorine-free blank oil phase (or diluent, such as kerosene or ethyl acetate) is left to stand or circulate at low speed in a flow cell for 1-2 minutes. The sensor will continuously measure for a period of time (e.g., 30 seconds to 1 minute) and record fluorescence intensity data points. The obtained data points are arithmetically averaged to obtain the background intensity, which is recorded as the background fluorescence intensity. This reflects the degree of fluorescence interference caused by background factors such as solvents. By accurately obtaining the background fluorescence intensity, the degree of interference of background factors such as solvents on fluorescence measurement can be clearly identified, providing key data for subsequent background interference elimination.

[0052] The calibrated fluoride ion concentration and background fluorescence intensity at each key monitoring point are processed point by point to obtain the background-compensated fluoride ion concentration, so as to reduce common-mode interference caused by light source fluctuations, temperature changes or detector sensitivity drift; the deviation processing in this application is a difference operation; the calibrated fluoride ion concentration is the fluoride ion concentration obtained after pre-monitoring.

[0053] Multi-parameter fusion compensation is performed on the fluoride ion concentration after background compensation to obtain the compensated fluoride ion concentration. Multi-parameter fusion compensation takes into account a variety of factors that may affect the measurement results, further improving the accuracy and reliability of fluoride ion concentration monitoring, and can more accurately reflect the actual concentration of fluoride ions in the reaction system.

[0054] Specifically, the fluoride ion concentration after background compensation is subjected to multi-parameter fusion compensation. The specific process is as follows: By combining the sensitivity coefficient and background fluorescence intensity, a linear equation is constructed between the probe measurement state value and the fluoride ion concentration, resulting in the fluoride ion correction equation. In the formula, ∆F represents the probe measurement state value. denoted by fluoride ion concentration, b by background fluorescence intensity, and k by sensitivity coefficient; in probe measurement, the sensitivity coefficient reflects the proportional relationship between probe measurement state values ​​(such as changes in fluorescence intensity) and fluoride ion concentration; a preliminary relationship between probe measurement state values ​​and fluoride ion concentration has been established, providing a basic framework for subsequent correction considering various interference factors, thus giving the measurement results a basic quantitative relationship.

[0055] Simultaneous measurements were taken of the corresponding solvent's pH value (obtained via a pH meter), interfering anion concentration (obtained via an online ion chromatograph), and oil phase ratio (obtained via a multiphase flow meter; in oil-water mixed pipelines, the multiphase flow meter can not only measure the total flow rate but also distinguish between the oil and water phases using principles such as conductivity and gamma rays, thereby calculating their respective ratios). pH value affects the chemical state of the fluorescent probe molecules, the interfering anion concentration directly affects the degree of interference to fluoride ion measurement, and the oil phase ratio is related to the solvent's influence on the measurement results. These key parameters affecting fluoride ion measurement were obtained, providing necessary data support for subsequent pH interference correction, solvent correction, and anion interference correction, ensuring a comprehensive consideration of the impact of various factors on the measurement results.

[0056] Since pH affects the dissociation state of fluorescent probe molecules, thus altering the probe's response to fluoride ions, a pH correction factor is obtained by performing pH interference correction processing on the dissociation constant and pH value of the fluorescent sensor probe. In the formula, α(pH) represents the pH correction factor, and pK aThe expression represents the dissociation constant, and pH represents the pH value. The equation is fitted using the Henderson-Hasselbalch equation: , where ∆F max pK represents the saturated fluorescence intensity at a sufficiently high pH, ​​obtained through nonlinear fitting. a The dissociation constant describes the ability of fluorescent probe molecules to release or bind hydrogen ions at a specific pH, thereby eliminating the influence of pH changes on fluoride ion measurement results and making the measurement results more accurately reflect the fluoride ion concentration itself. It eliminates the influence of pH changes on the chemical state of fluorescent probe molecules, and thus eliminates the interference of pH changes on fluoride ion measurement results, making the measurement results more accurate and stable under different pH environments.

[0057] The solvent correction factor is obtained based on the solvent influence coefficient and the oil phase ratio, i.e. In the formula, Let φ represent the solvent correction factor, φ represent the oil phase ratio, and m represent the solvent influence coefficient. Based on the presence of competing anions among the interfering anions, the fluoride ion correction equation is compensated to obtain the compensated fluoride ion. Organic solvents with different oil phase ratios are added to the aqueous phase at a fixed probe concentration. The fluorescence intensity of the probe fluoride ion system corresponding to each oil phase ratio is measured. The fluorescence intensity is compared with the background fluorescence intensity of the pure aqueous phase to obtain the solvent correction factor. A linear fit is plotted on the solvent correction factor against the oil phase ratio, and the absolute value of the slope is denoted as the solvent influence coefficient. Different solvent compositions and volume fractions can affect the measurement environment of the fluorescent probe. For example, the polarity and viscosity of the solvent may change the propagation of the fluorescence signal and the interaction between the probe and fluoride ions. The solvent correction factor can eliminate the interference of solvent factors on the measurement results. This eliminates the influence of solvent factors (such as solvent composition and volume fraction) on the fluorescent probe measurement environment, avoids measurement errors caused by different solvent properties, and improves the reliability of the measurement results under different solvent conditions.

[0058] If competing anions exist among the interfering anions, the compensation process for the fluoride ion correction equation is as follows: A pH correction factor, a solvent correction factor, and anion correction factor are introduced to correct the initial sensitivity (i.e., the pH correction factor, solvent correction factor, anion correction factor, and initial sensitivity are multiplied). The effective sensitivity is then used to replace the sensitivity coefficient, resulting in a new fluoride ion correction equation. This eliminates measurement errors caused by pH changes or interference from coexisting ions, yielding the compensated fluoride ion correction factor. The anion correction factor represents the result obtained by correcting for anion interference by applying anion interference correction to the concentration of each interfering anion and its corresponding site occupancy coefficient. In the formula, c x γ represents the concentration of the x-th interfering anion. xThis represents the site occupancy coefficient of the x-th interfering anion. The site occupancy coefficient describes the ability of a competitive anion to occupy a probe site. In the formula, K x The binding constant between the interfering anion and the probe is represented by the binding constant of the interfering anion to the probe. This binding constant is fitted by measuring the probe's state value as a function of the interfering anion concentration, thus obtaining the site occupancy coefficient. Taking into account various interference factors such as pH changes, solvent effects, and the occupancy of probe sites by competing anions, a new fluoride ion correction equation is obtained by modifying the initial sensitivity. This significantly improves the accuracy of fluoride ion concentration measurement in the presence of competing anions, and more accurately reflects the actual concentration of fluoride ions in the solution.

[0059] At this point, the specific restrictive expression for the fluoride ion correction equation is: ; In the formula, x represents the number of the interfering anion, x=1,2,...,Y, where Y is the total number of interfering anions, and ∆F represents the probe measurement state value. The value represents the fluoride ion concentration, b is the background fluorescence intensity, and k is the concentration of fluoride ions. base This represents the initial sensitivity coefficient when there is no interference.

[0060] If no competing anion exists among the interfering anions, the compensation process for the fluoride ion correction equation is as follows: A fluorescence quenching compensation term is added to the fluoride ion correction equation. A pH correction factor and a solvent correction factor are introduced to correct the initial sensitivity (i.e., the pH correction factor, solvent correction factor, and initial sensitivity are multiplied together). The effective sensitivity is then used to replace the sensitivity coefficient, resulting in a new fluoride ion correction equation. This reduces chemical interference and achieves accurate measurement of fluoride ion concentration. The fluorescence quenching compensation term represents the result obtained by performing anion quenching compensation processing on the interfering anion concentration and corresponding quenching coefficient of each interfering anion. In the formula, c x k represents the concentration of the x-th interfering anion. x The quenching coefficient of the x-th interfering anion is denoted as . The quenching coefficient describes the ability of the interfering anion to quench the fluorescence signal. A series of solutions with standard concentrations of interfering anions are prepared at a fixed probe concentration, and the fluorescence intensity corresponding to each concentration is measured. The slope is obtained by linearly fitting the fluorescence intensity against the concentration of the interfering anion, and denoted as the quenching coefficient. The study focuses on pH changes, solvent effects, and the quenching effect of interfering anions on the fluorescence signal. By adding a fluorescence quenching compensation term and correcting the initial sensitivity, the influence of chemical interference on the measurement results is reduced, enabling accurate measurement of fluoride ion concentration even in the absence of competing anions but with other interfering factors.

[0061] At this point, the specific restrictive expression for the fluoride ion correction equation is: ; In the formula, x represents the number of the interfering anion, x=1,2,...,Y, where Y is the total number of interfering anions, and ∆F represents the probe measurement state value. The α value represents the fluoride ion concentration, α(pH) represents the pH correction factor, and pH represents the pH value. The solvent correction factor is represented by φ, the oil phase percentage is represented by b, and the background fluorescence intensity is represented by k. base This represents the initial sensitivity coefficient when there is no interference.

[0062] like Figure 5 The diagram shown is a flowchart of the extraction process optimization provided in an embodiment of this application. Further explanation is provided: the specific process for determining whether to perform extraction process optimization is as follows: Extraction quality indicators include turbidity and fluoride ion concentration in the raffinate phase; extraction process optimization includes reducing stirring intensity and adjusting the flow rate of the extract phase.

[0063] If the turbidity measured by the turbidimeter exceeds the upper limit, the stirring intensity of the stirred tank is gradually reduced according to the preset stirring adjustment ratio until the turbidity does not exceed the upper limit, thereby avoiding emulsification and achieving good separation of the oil and water phases. Otherwise, the stirring intensity is not reduced. The upper limit of turbidity is the maximum acceptable turbidity value, which can be set to the maximum turbidity value within a historical time period. The preset stirring adjustment ratio is obtained from the preset database and set by the preset personnel based on experience; for example, it can be set to 10% of the current stirring intensity. When the turbidity exceeds the upper limit, gradually reducing the stirring intensity can effectively avoid emulsification caused by excessive stirring intensity. Emulsification makes it difficult to separate the oil and water phases, reducing extraction efficiency. Reducing the stirring intensity can disrupt the emulsion structure, allowing the oil and water phases to separate well again, improving the separation effect of the extraction process.

[0064] When the turbidity after optimization during the extraction process does not exceed the upper limit of turbidity, the stirring intensity is gradually increased and monitored. Specifically, if the turbidity exceeds the upper limit of turbidity during the gradual increase of stirring intensity, the stirring intensity is returned to the previous level, and the current stirring intensity is recorded as the temporary stirring intensity. At the same time, after the extraction is completed, a notification is sent to the preset personnel indicating an abnormal stirring intensity, and a demulsifier is added during the subsequent preparation of the extractant. Otherwise, the stirring intensity is further reduced. After ensuring that the turbidity meets the requirements, the stirring intensity is gradually increased to explore a suitable stirring intensity range to improve extraction efficiency. Simultaneously, monitoring is performed during the increase. When turbidity exceeds the standard, the stirring intensity is promptly returned to the previous level and the abnormality is recorded. This ensures the stability of the extraction process and provides a reference for subsequent operations, preventing similar abnormalities from recurring. Adding a demulsifier can further prevent the recurrence of emulsification and improve the reliability of the entire fluoride ion extraction process.

[0065] Simultaneously, if the fluoride ion concentration (obtained by a fluoride ion concentration monitoring sensor) of the raffinate aqueous phase (the aqueous phase remaining after extraction with the extractant, containing a certain amount of the target substance, which is fluoride ions in this application) is greater than the target fluoride ion concentration of the raffinate aqueous phase, the speed of the extraction phase pump (equipment used to transport the extraction phase, i.e., the extractant such as organic solvent used in the extraction process) is increased to increase the extraction phase flow rate. If the fluoride ion concentration of the raffinate aqueous phase is less than the target fluoride ion concentration of the raffinate aqueous phase, the speed of the extraction phase pump is decreased to decrease the extraction phase flow rate. If the fluoride ion concentration equals the target fluoride ion concentration in the raffinate aqueous phase, the extraction phase flow rate is not adjusted, thus controlling the fluoride ion concentration in the raffinate aqueous phase. By detecting the fluoride ion concentration in the raffinate aqueous phase and comparing it with the target concentration, the extraction effect can be accurately judged. Adjusting the speed of the extraction phase pump based on the comparison result, and thus adjusting the extraction phase flow rate, allows for precise control of the extraction process. Increasing the flow rate when the fluoride ion concentration is greater than the target concentration can improve extraction efficiency, allowing more target substances to transfer from the aqueous phase to the extraction phase. Reducing the flow rate when the fluoride ion concentration is less than the target concentration can avoid over-extraction and save on extractant costs.

[0066] When the fluoride ion concentration in the raffinate phase is not equal to the target fluoride ion concentration in the raffinate phase, if the deviation in the fluoride ion concentration of the raffinate phase (i.e., the difference between the fluoride ion concentration in the raffinate phase and the corresponding target fluoride ion concentration) is greater than the upper limit of the fluoride ion concentration deviation, feedforward control is used for adjustment, followed by further adjustment using a PID controller to balance the stability and timeliness of flow control. Otherwise, the PID controller is used directly for adjustment. When the deviation in the fluoride ion concentration of the raffinate phase is greater than the upper limit, it indicates a significant disturbance or change. Feedforward control is first used to initially adjust the extraction phase pump to adjust the extraction phase flow rate, thereby adjusting the fluoride ion concentration. This allows for a rapid response to larger deviations. Then, the PID controller is used for further adjustment of the extraction phase pump to adjust the extraction phase flow rate, thereby adjusting the fluoride ion concentration. The PID controller can make precise adjustments based on real-time feedback of the fluoride ion concentration, ensuring the stability and accuracy of flow control, thus balancing the stability and timeliness of flow control and improving the quality and efficiency of the extraction process.

[0067] It should be added that the specific method for obtaining the adjustment amount of the extraction phase flow rate through PID control is as follows: multiply the ratio of the PID output result and 100% with the flow extreme deviation (i.e., the difference between the maximum flow rate and the minimum flow rate), and then sum the product with the minimum flow rate to obtain the actual extraction phase flow rate. Calculate the difference between the actual extraction phase flow rate and the current extraction phase flow rate to obtain the flow adjustment amount. Send a command to the frequency converter to adjust the speed of the extraction phase pump to a frequency that can generate the actual flow rate.

[0068] The adjustment of the extractive phase flow rate is achieved through feedforward control. The specific method for obtaining the adjustment amount is as follows: the current detected concentration deviation (the difference between the new influent fluoride concentration and the target effluent concentration), the current wastewater flow rate, and the safety factor (usually taken as 1.1-1.2 to ensure a certain margin) are multiplied to obtain the actual extractive phase flow rate. The difference between the actual extractive phase flow rate and the current extractive phase flow rate is calculated to obtain the flow adjustment amount. A command is sent to the frequency converter to adjust the speed of the extractive phase pump to a frequency that can generate the actual flow rate.

[0069] Further, determine whether to optimize the back-extraction process. The specific process is as follows: The quality index of back-extraction indicates the fluoride ion concentration of the back-extraction solution. If the fluoride ion concentration of the back-extraction solution (i.e., the aqueous solution obtained after extracting the target substance from the loaded organic phase during the back-extraction process) is greater than the target fluoride ion concentration of the back-extraction solution, the speed of the ammonia pump (equipment used to transport ammonia) is reduced to decrease the ammonia flow rate. If the fluoride ion concentration of the back-extraction solution is less than the target fluoride ion concentration, the speed of the ammonia pump is increased to increase the ammonia flow rate. If the fluoride ion concentration of the back-extraction solution is equal to the target fluoride ion concentration, the ammonia flow rate is not adjusted, thereby controlling the fluoride ion concentration in the back-extraction solution. The specific adjustment amount of the ammonia flow rate is the same as the specific method for obtaining the adjustment amount of the extraction phase flow rate mentioned above.

[0070] It should be added that reducing the ammonia input can alter the chemical environment of the back-extraction system, slowing down certain reactions that promote the entry of fluoride ions into the back-extraction solution, or promoting the precipitation or transfer of fluoride ions from the back-extraction solution to other phases, thereby effectively reducing the fluoride ion concentration in the back-extraction solution and bringing it closer to the target value, ensuring that the quality of the back-extracted product meets the requirements. Increasing the ammonia input can change the reaction conditions, promoting the entry of more fluoride ions into the back-extraction solution, increasing the fluoride ion concentration, meeting the requirements of the production process for the composition of the back-extraction solution, and ensuring the smooth progress of subsequent processes. Not adjusting the ammonia flow rate can avoid unnecessary operations and energy consumption, maintain the stable operation of the back-extraction process, maintain the stability of the back-extraction solution quality, and reduce fluctuations and instabilities that may be caused by excessive adjustments.

[0071] When the fluoride ion concentration in the back-extraction solution is not equal to the target fluoride ion concentration, if the deviation in fluoride ion concentration (i.e., the difference between the fluoride ion concentration in the back-extraction solution and the corresponding target fluoride ion concentration) exceeds the upper limit of the fluoride ion concentration deviation (set by the pre-set personnel based on experience, for example, the maximum value of the fluoride ion concentration deviation in the back-extraction solution within a historical time period), then feedforward control is used to adjust the ammonia flow rate, followed by further adjustment using a PID controller. Otherwise, the PID controller is used directly to adjust the ammonia flow rate. Feedforward control can make a rough adjustment of the ammonia flow rate in advance, quickly responding to large deviations and creating a more favorable initial condition for subsequent PID control, reducing the adjustment time and difficulty of PID control. PID control then makes fine adjustments based on this, eliminating possible errors in feedforward control, making the fluoride ion concentration in the back-extraction solution more accurately stabilized at the target value, and improving the response speed and control accuracy of process control.

[0072] Furthermore, adjustments using a PID controller also include: If the adjustment response time of the PID controller (the time required from the start of the input to the output reaching and maintaining within a certain allowable error range near the setpoint, or the time for the PID controller to adjust the fluoride ion concentration in the raffinate phase to the target value) is greater than the upper limit of the adjustment response time, then the PID controller is optimized; otherwise, the PID controller is not optimized. The upper limit of the adjustment response time is the maximum acceptable adjustment response time, for example, it can be set to the maximum adjustment response time. PID is an abbreviation for Proportional, Integral, and Derivative. The PID controller generates a control signal to adjust the controlled object by performing proportional, integral, and derivative operations on the error signal (the difference between the setpoint and the actual value), so that the system output reaches and maintains the setpoint. By setting an upper limit of the adjustment response time, unnecessary optimization operations are avoided, saving computational resources and time. At the same time, it ensures that optimization is performed in a timely manner when the controller performance does not meet the requirements, thus guaranteeing the control quality of the PID controller.

[0073] Optimizing the PID controller means combining it with a Smith predictor to optimize the PID control, thereby adapting to changes in operating conditions and improving the timeliness of PID control. The Smith predictor is a compensator used to solve the control problem of large time delay systems. By establishing a mathematical model of the controlled object, it estimates the output flow in advance, thereby compensating for the time delay in PID control and improving the control performance and stability of the PID controller.

[0074] The PID controller is optimized as follows: Taking the raffinate aqueous phase as an example, the same principle applies when replacing it with the back-extraction solution. Record the pump speed and the fluoride ion concentration in the raffinate aqueous phase. Export the recorded time-series data (timestamp, pump speed, fluoride ion concentration) to analysis software (such as MATLAB or Python). Plot a curve with time on the x-axis and fluoride ion concentration in the raffinate aqueous phase on the y-axis to obtain the change curve of fluoride ion concentration in the raffinate aqueous phase. Identify the gain, time constant, and lag time during the extraction process. Based on this, establish a transfer function model describing the relationship between the pump speed change and the fluoride ion concentration change. The gain represents the ratio of the output change to the input change, reflecting the amplification of the input signal. The time constant is a parameter describing the dynamic response characteristics of the system, representing the time required for the output to reach 63.2% of the steady-state value after a step input. The lag time refers to the time interval from the start of the input signal to the point where the output shows a significant change. The transfer function model is a mathematical model that describes the dynamic relationship between the system's input and output, usually expressed in the form of a Laplace transform, reflecting the system's response characteristics at different frequencies. The transfer function model accurately describes the dynamic relationship between the pump speed (input) and the fluoride ion concentration (output), providing a foundation for subsequent optimization and control. By identifying parameters such as gain, time constant, and lag time, it helps to control the fluoride ion concentration more precisely.

[0075] After each control cycle, the calibrated fluoride ion concentration and control signal from the historical control cycles are used to re-obtain the transfer function model parameters using the recursive least squares method, and the transfer function model in the Smith predictor is updated. Since the operating conditions of the extraction process may change over time, the parameters of the transfer function model may also change. By periodically updating the model parameters using the recursive least squares method, the transfer function model can always maintain a good match with the actual PID controller, improving the accuracy and adaptability of the model, thereby ensuring the compensation effect of the Smith predictor and the control performance of the PID controller.

[0076] In each control cycle, based on the transfer function model and lag time, the model output and the lag-free model output are obtained. The current control signal, which is the output value calculated by the previous PID controller, is acquired. This current control signal is then input into the ideal transfer function model (in which the lag time is 0, and the gain and time constant remain unchanged). By solving the model's differential equation (or difference equation), the lag-free model output (i.e., the prediction of the actual process output value at the current moment) is obtained. The current control signal is then input into the transfer function model (identifying the gain, time constant, and lag time in the extraction process). By solving the model's differential equation (or difference equation), the control signal from a previous time period (lag time) is output, denoted as the lag control signal. This lag control signal is then input into the ideal transfer function model. In this process, the output of the hysteresis model is obtained by solving the differential equation (or difference equation) of the model. Then, a synthetic feedback signal is obtained based on the calibrated fluoride ion concentration, the model output, and the output of the hysteresis-free model. This is achieved by summing the calibrated fluoride ion concentration and the model output, and then subtracting the result from the output of the hysteresis-free model. The synthetic feedback signal is then input into the PID controller to obtain a new control signal. The synthetic feedback signal is a signal obtained by comprehensively processing the model output obtained from the transfer function model and the hysteresis time, the output of the hysteresis-free model, and the actual measured calibrated fluoride ion concentration. This signal is used to input the PID controller to generate a more suitable control signal, further improving the control accuracy and stability of the PID controller for the extraction process, so that the fluoride ion concentration can reach the set value faster and more accurately.

[0077] Through the above description of the implementation methods, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the above functions can be divided into different functional modules to complete all or part of the functions described above.

[0078] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are merely illustrative; for instance, the division of modules or 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 device, 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, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0079] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units, located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0080] Furthermore, 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. The integrated unit can be implemented in hardware or as a software functional unit.

[0081] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the solution, or all or part of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0082] 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 within the technical scope 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. An online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing, characterized in that: Includes the following steps: A1. Pre-monitor the fluoride ion concentration monitoring sensor. Based on the pre-monitoring results, determine whether to trigger the sensor calibration mechanism. If so, monitor the fluoride ion concentration in real time through the calibrated sensor after the sensor is calibrated. Otherwise, continue to monitor the fluoride ion concentration in real time through the sensor. A2. Monitor the fluoride ion concentration during the extraction reaction. Based on the parameters monitored, determine whether to perform dynamic compensation to correct the fluoride ion concentration. At the same time, obtain the extraction quality indicators and determine whether to optimize the extraction process to improve the extraction effect of fluoride ions. If the extraction process is optimized, the optimized alkaline-washed oil phase is back-extracted with ammonia water of a preset back-extraction concentration after the extraction process is optimized. Otherwise, the back-extraction reaction is performed directly. A3 monitors the fluoride ion concentration during the back-extraction reaction, obtains back-extraction quality indicators, and determines whether to optimize the back-extraction process, thereby preventing the accumulation of fluoride ions in the oil phase.

2. The online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing as described in claim 1, characterized in that: The pre-monitoring includes parallel monitoring with dual sensors and sensor drift determination; The dual-sensor parallel monitoring means that a fluorescence sensor and an electrochemical sensor are installed in parallel at key monitoring points, and calibration judgment is made based on the monitoring data of the fluorescence sensor and the electrochemical sensor according to the set sensor calibration cycle. The fluorescence sensor employs a ratiometric fluorescent probe that includes a response peak that varies with fluoride ion concentration and a reference peak that does not vary with fluoride ion concentration. The electrochemical sensor serves as a calibration benchmark for the fluorescence sensor, used to update the slope and intercept of the calibration curve. The sensor drift determination is specifically as follows: Obtain the probe measurement status value in the fluorescence sensor at a preset concentration. The probe measurement status value is the ratio of the response peak intensity of the probe in the fluorescence sensor to the reference peak intensity at the preset concentration. If the probe measurement status fluctuation value, which reflects the fluctuation of the probe measurement status value, is not less than the probe measurement status fluctuation limit, then the sensor is determined to have drifted and the sensor self-test mechanism is triggered; otherwise, the sensor self-test mechanism is not triggered. The probe measurement status fluctuation limit is the maximum allowable fluctuation of the probe measurement status value.

3. The online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing as described in claim 2, characterized in that: The calibration and judgment based on monitoring data from fluorescence and electrochemical sensors follows the specific procedure as follows: Obtain the fluoride ion concentration benchmarks monitored by the fluorescence sensor and the electrochemical sensor; If the absolute value of the relative deviation, which reflects the degree of deviation between the fluoride ion concentration and the fluoride ion concentration reference, is greater than the fluorescence correction threshold, then the calibration curve of the fluorescence sensor is corrected. Specifically, the slope and intercept of the calibration curve of the fluorescence sensor are updated based on the obtained fluoride ion concentration and the fluoride ion concentration reference using the recursive least squares method. Otherwise, the calibration curve of the fluorescence sensor is not corrected; The fluorescence correction threshold is the maximum allowable deviation between the fluoride ion concentration and the fluoride ion concentration baseline.

4. The online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing as described in claim 2, characterized in that: The sensor self-testing mechanism includes one or more of the following: static stability check, electronic component check, and optical path integrity check; The static stability check specifically involves monitoring the probe measurement status in the fluorescence sensor in a standard fluoride ion solution. If the fluctuation value of the probe measurement status is not less than the fluctuation limit of the probe measurement status, an electronic component check is performed to check the working status of the core electronic components inside the sensor; otherwise, the sensor is directly determined to be normal. The electronic component inspection specifically involves: reading sensor parameters including the light source drive current, the photodetector dark current, and the temperature sensor readings, and comparing them with the sensor baseline parameters. If there is a sensor deviation that reflects the degree of deviation between the sensor parameters and the corresponding sensor baseline parameters, a pre-set personnel is prompted that the electronic component is abnormal; otherwise, an optical path integrity check is performed. The light source drive current represents the current supplied to the light-emitting element inside the sensor, and the photodetector dark current represents the current generated by the detector when no light shines on it. The optical path integrity check specifically involves: if the rate of change of reference peak intensity within a preset time period is greater than the upper limit of the rate of change of reference peak intensity, then a preset personnel optical path integrity abnormality is indicated; otherwise, a preset personnel sensor abnormality is indicated. The rate of change of reference peak intensity reflects the change of reference peak intensity over time, and the upper limit of the rate of change of reference peak intensity is the maximum allowable rate of change of reference peak intensity.

5. The online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing as described in claim 1, characterized in that: The specific process for determining whether to perform dynamic compensation based on parameters during the monitoring process is as follows: The monitoring response time of the fluorescence sensor was obtained during the extraction reaction; If the monitoring response time of the fluorescence sensor is greater than the upper limit of the monitoring response, it indicates that the sensor is monitoring abnormal and dynamic compensation is performed; otherwise, no dynamic compensation is performed. The upper limit of the monitoring response is the maximum value of the acceptable monitoring response. The dynamic compensation specifically refers to: Measurement signals from a fluorine-free blank oil phase were collected to obtain the background fluorescence intensity; The calibrated fluoride ion concentration and background fluorescence intensity at each key monitoring point were processed point by point to obtain the background-compensated fluoride ion concentration, so as to reduce common-mode interference caused by light source fluctuations, temperature changes or detector sensitivity drift. The fluoride ion concentration after background compensation is subjected to multi-parameter fusion compensation to obtain the compensated fluoride ion concentration. The calibrated fluoride ion concentration is the fluoride ion concentration obtained after pre-monitoring.

6. The online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing as described in claim 1, characterized in that: The specific process for determining whether to optimize the extraction process is as follows: If the turbidity obtained by the turbidity meter is greater than the upper limit of turbidity, the stirring intensity is gradually reduced according to the preset stirring adjustment ratio until the turbidity is no greater than the upper limit of turbidity, so as to avoid emulsification; otherwise, the stirring intensity is not reduced. The upper limit of turbidity is the maximum acceptable turbidity. When the turbidity after the extraction process is optimized is not greater than the upper limit of turbidity, the stirring intensity is gradually increased and monitored. Specifically, if the turbidity is greater than the upper limit of turbidity during the gradual increase of stirring intensity, the stirring intensity is returned to the previous level, the current stirring intensity is recorded as the temporary stirring intensity, and the preset personnel are notified of the abnormal stirring intensity after the extraction is completed and the demulsifier is added in the subsequent preparation of the extractant. Otherwise, the stirring intensity is reduced. Meanwhile, if the fluoride ion concentration in the raffinate is greater than the target fluoride ion concentration in the raffinate, the speed of the extraction phase pump is increased to increase the extraction phase flow rate. If the fluoride ion concentration in the raffinate is less than the target fluoride ion concentration in the raffinate, the speed of the extraction phase pump is decreased to decrease the extraction phase flow rate. If the fluoride ion concentration in the raffinate is equal to the target fluoride ion concentration in the raffinate, the extraction phase flow rate is not adjusted, thereby controlling the fluoride ion concentration in the raffinate. When the fluoride ion concentration in the raffinate phase is not equal to the target fluoride ion concentration in the raffinate phase, if the deviation of the fluoride ion concentration in the raffinate phase is greater than the upper limit of the fluoride ion concentration deviation, then the feedforward control is used for adjustment and then the PID controller is used for adjustment to balance the stability and timeliness of the flow control; otherwise, the PID controller is used directly for adjustment. The extraction process optimization includes reducing the stirring intensity and adjusting the flow rate of the extractant phase.

7. The online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing as described in claim 1, characterized in that: The specific process for determining whether to optimize the back-extraction process is as follows: If the fluoride ion concentration in the back-extraction solution is greater than the target fluoride ion concentration, the speed of the ammonia pump is reduced to reduce the ammonia flow rate. If the fluoride ion concentration in the back-extraction solution is less than the target fluoride ion concentration, the speed of the ammonia pump is increased to increase the ammonia flow rate. If the fluoride ion concentration in the back-extraction solution is equal to the target fluoride ion concentration, the ammonia flow rate is not adjusted, thereby controlling the fluoride ion concentration in the back-extraction solution. When the fluoride ion concentration of the back-extraction solution is not equal to the target fluoride ion concentration of the back-extraction solution, if the deviation of the fluoride ion concentration of the back-extraction solution is greater than the upper limit of the deviation of the fluoride ion concentration, then the feedforward control is used for adjustment and then the PID controller is used for adjustment; otherwise, the PID controller is used directly for adjustment.

8. The online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing as described in claim 6, characterized in that: The adjustment using a PID controller also includes: If the adjustment response time of the PID controller is greater than the upper limit of the adjustment response time, the PID controller is optimized; otherwise, the PID controller is not optimized. The upper limit of the adjustment response time is the maximum acceptable adjustment response time. The optimization of the PID controller refers to combining the Smith predictor to optimize the PID control, thereby adapting to changes in operating conditions and improving the timeliness of PID control. The optimization of the PID controller specifically includes: Record the change curve of fluoride ion concentration in the raffinate aqueous phase, identify the gain, time constant and lag time in the extraction process, and establish a transfer function model describing the change in pump speed and fluoride ion concentration. After each control cycle ends, the calibrated fluoride ion concentration and control signal from the historical control cycles are used to re-obtain the transfer function model parameters using the recursive least squares method, and the transfer function model in the Smith predictor is updated. In each control cycle, the model output and the lag-free model output are obtained based on the transfer function model and the lag time. Then, a synthetic feedback signal is obtained based on the calibrated fluoride ion concentration, the model output, and the lag-free model output. The synthetic feedback signal is then input into the PID controller to obtain a new control signal.

9. The online monitoring method for fluoride ion extraction in optoelectronic panel wastewater based on fluorescence sensing as described in claim 5, characterized in that: The specific process for multi-parameter fusion compensation of the fluoride ion concentration after background compensation is as follows: By combining the sensitivity coefficient and background fluorescence intensity, a linear equation between the probe measurement state value and the fluoride ion concentration is constructed, resulting in the fluoride ion correction equation. Simultaneously measure the pH value, interfering anion concentration, and oil phase ratio of the corresponding solvent; The dissociation constant and pH value of the fluorescent sensor probe are subjected to pH interference correction processing to obtain a pH correction factor. The dissociation constant is used to describe the ability of the fluorescent probe molecule to release or bind hydrogen ions at a specific pH. The solvent correction factor is obtained based on the solvent influence coefficient and the proportion of oil phase. The fluoride ion correction equation is compensated based on whether there are competing anions among the interfering anions, so as to obtain the compensated fluoride ions. If there are competing anions among the interfering anions, the process of compensating for the fluoride ion correction equation is as follows: introduce a pH correction factor, a solvent correction factor, and an anion correction factor to correct the initial sensitivity, obtain an effective sensitivity to replace the sensitivity coefficient, and obtain a new fluoride ion correction equation, thereby eliminating the measurement error caused by pH changes or interference from coexisting ions. The anion correction factor represents the result obtained by performing anion interference correction processing on the interfering anion concentration and the corresponding site occupancy coefficient of each interfering anion. The site occupancy coefficient is used to describe the ability of competing anions to occupy probe sites. If there are no competing anions among the interfering anions, the compensation process for the fluoride ion correction equation is as follows: a fluorescence quenching compensation term is added to the fluoride ion correction equation, a pH correction factor and a solvent correction factor are introduced, the initial sensitivity is corrected, and an effective sensitivity is obtained to replace the sensitivity coefficient, resulting in a new fluoride ion correction equation, thereby reducing chemical interference. The fluorescence quenching compensation term represents the result obtained by anion quenching compensation processing of the interfering anion concentration and the corresponding quenching coefficient of each interfering anion. The quenching coefficient is used to describe the ability of interfering anions to quench fluorescence signals.

10. A method for fluoride ion extraction from optoelectronic panel wastewater based on fluorescence sensing, used to implement the online monitoring method for fluoride ion extraction from optoelectronic panel wastewater based on fluorescence sensing as described in claims 1-9, characterized in that, Includes the following steps: S1, using the photoelectric panel etching wastewater as the aqueous phase, and performing an extraction reaction with the extraction phase according to a preset extraction volume ratio and preset extraction mixing conditions, to obtain the raffinate aqueous phase and the fluorine-loaded oil phase; S2, the obtained fluorine-loaded oil phase is subjected to alkaline washing reaction with ammonia water of a preset alkaline washing concentration according to a preset alkaline washing volume ratio and preset alkaline washing mixing conditions to obtain the alkaline-washed oil phase. S3, the obtained alkaline-washed oil phase is back-extracted with ammonia water of a preset back-extraction concentration according to a preset back-extraction volume ratio and preset back-extraction mixing conditions to obtain a fluorine-containing back-extraction solution and a regenerated oil phase. The regenerated oil phase is then transported to an extraction phase storage tank for recycling. The regenerated oil phase is the extraction phase that is restored to its initial form and used for cyclic extraction.

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