Method for advanced treatment of cold rolling acidic wastewater

Abstract

The application discloses a cold-rolling acid wastewater advanced treatment method and relates to the technical field of industrial wastewater treatment, and comprises the following steps: in the process of treating the cold-rolling acid wastewater by the photocatalytic oxidation method, the concentration data of harmful substances in the wastewater are acquired in real time to understand the pollution degree of the wastewater; the harmful substance data information acquired is pretreated, and the data after the pretreatment is collectively managed to establish a data set. The harmful substance concentration in the wastewater is monitored in real time and intelligently evaluated, the system can dynamically adjust the dosing amount of the photocatalyst, the power of the ultraviolet light source and the illumination time, and the photocatalytic reaction can be kept in the optimal state. This not only avoids the excessive load and the active site blockage of the catalyst, but also adjusts the treatment parameters according to the pollution degree of the wastewater, ensures the efficient removal of the harmful substances, improves the wastewater treatment effect, and simultaneously reduces the resource waste and the operation cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial wastewater treatment, and specifically relates to a cold-rolling acidic wastewater advanced treatment method. BACKGROUND

[0002] Cold-rolling acidic wastewater advanced treatment refers to a comprehensive and thorough treatment of acidic wastewater generated in the production process of cold-rolled steel, to remove harmful substances in the wastewater, such as acid, metal ions (Fe 2+ , Fe 3+ , organic matter, etc., to achieve higher purification effect and meet environmental emission standards. Advanced treatment not only includes conventional neutralization or precipitation treatment, but also involves the use of advanced technologies such as membrane separation, Fenton oxidation reaction, acid regeneration, adsorption method, etc., to completely remove or recycle harmful components in wastewater, to realize wastewater resourceization and minimal discharge. Through advanced treatment, environmental pollution can be effectively reduced, resources can be saved, and treatment costs can be reduced, thereby achieving better environmental protection and economic benefits.

[0003] The advanced treatment of cold-rolling acidic wastewater can be carried out by photocatalytic oxidation method. Photocatalytic oxidation method uses photocatalyst (such as titanium dioxide TiO2) to generate strong oxidizing free radicals (such as hydroxyl radical ·OH and superoxide anion O2 ·- ) under ultraviolet light irradiation, which can efficiently degrade harmful substances in wastewater. In cold-rolling acidic wastewater, common pollutants include organic acids, phenolic substances, metal ions (such as Fe 2+ , Fe 3+ , etc. Photocatalytic oxidation method can effectively remove these harmful substances through strong oxidation reaction, reduce the concentration of pollutants in wastewater, and achieve the purpose of advanced treatment. In addition, photocatalytic oxidation method can avoid the problem of generating a large amount of sludge and secondary pollution in traditional treatment methods, and has high energy efficiency and sustainability. Through photocatalytic reaction, harmful substances in wastewater can be completely degraded or converted into harmless substances such as water and carbon dioxide, thereby achieving the goal of purifying water quality and reducing environmental pollution.

[0004] The prior art has the following disadvantages: In the process of treating cold-rolled acidic wastewater by photocatalytic oxidation method, the wastewater may contain a large amount of harmful substances. When the concentration of harmful substances in the wastewater is high, these harmful substances may be adsorbed on the surface of the photocatalyst in large quantities. At this time, the active sites of the photocatalyst may reach a "light saturation" state due to excessive adsorption of pollutants, that is, the active sites on the surface of the catalyst are covered or blocked by pollutants, and cannot effectively react with harmful substances in the wastewater. This phenomenon will lead to a decrease in the catalytic ability of the photocatalyst, a significant decrease in the degradation efficiency of harmful substances in the wastewater, and thus affect the overall treatment effect of the photocatalytic reaction. Specifically, the adsorption of pollutants on the surface of the photocatalyst will reduce its contact opportunities with other harmful substances in the wastewater, resulting in a significant decrease in reaction efficiency, thus failing to meet the requirements of wastewater treatment, and even causing the operation of the treatment system to be interrupted or fail.

[0005] The above information disclosed in the background section is only used to strengthen the understanding of the background of the present disclosure, and therefore it can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0006] The purpose of the present application is to provide a cold-rolled acidic wastewater advanced treatment method, which can dynamically adjust the dosage of photocatalyst, the power of ultraviolet light source and the illumination time by monitoring the concentration of harmful substances in wastewater in real time and intelligently evaluating it, so as to keep the photocatalytic reaction in the optimal state. This not only avoids excessive loading of the catalyst and blockage of the active sites, but also adjusts the treatment parameters according to the pollution degree of the wastewater, ensures efficient removal of harmful substances, improves the wastewater treatment effect, and at the same time reduces resource waste and operating cost, so as to solve the problems in the above background.

[0007] In order to achieve the above purpose, the present application provides the following technical scheme: a cold-rolled acidic wastewater advanced treatment method, comprising the following steps:

[0008] In the process of treating cold-rolled acidic wastewater by photocatalytic oxidation method, the concentration data of harmful substances in the wastewater is obtained in real time to understand the pollution degree of the wastewater;

[0009] The obtained harmful substance data information is preprocessed, and the preprocessed data is collectively managed to establish a data set;

[0010] The decisive variables reflecting the over-standard concentration of pollutants in the wastewater are extracted from the data set, and the extracted decisive variables are comprehensively analyzed to comprehensively evaluate whether the concentration of harmful substances in the current wastewater is over-standard;

[0011] The decisive variables after comprehensive analysis are input into a pre-trained machine learning model, and the current harmful substance concentration in the wastewater is intelligently evaluated by the model to determine whether the harmful substance concentration in the wastewater is over-standard;

[0012] When it is identified that the concentration of harmful substances in wastewater exceeds the standard, based on the pollutant concentration data, the dosage of photocatalyst is dynamically adjusted to provide more active sites; at the same time, according to the intelligent evaluation result, the power and illumination time of the ultraviolet light source are dynamically adjusted to enhance the intensity of the photocatalytic reaction and promote the generation of more free radicals on the surface of the catalyst, thereby ensuring that the harmful substances in the wastewater are fully degraded.

[0013] Preferably, during the treatment of cold-rolled acidic wastewater by the photocatalytic oxidation method, the specific steps for real-time acquisition of the concentration data of harmful substances in wastewater are as follows:

[0014] According to the types of pollutants in wastewater, select the detection equipment that meets the needs to monitor the concentration of harmful substances in real time;

[0015] Through the automatic system, the pollutant concentration data in wastewater is continuously collected to ensure that the changes of pollutants in the treatment process are reflected in real time;

[0016] The collected real-time data is transmitted to the data platform through the network for storage, ensuring the accuracy and integrity of the data, and providing a reliable basis for subsequent analysis and processing.

[0017] Preferably, the decisive variables reflecting the over-standard concentration of pollutants in wastewater are extracted from the data set, including the concentration change rate of dissolved ions in wastewater and the concentration of reactive chemical molecules in wastewater. Under the detection window, the extracted concentration change rate of dissolved ions in wastewater and the concentration of reactive chemical molecules in wastewater are comprehensively analyzed to generate dissolved ion concentration change rate reference value and reactive molecule reference value. Through the dissolved ion concentration change rate reference value and the reactive molecule reference value, the concentration of harmful substances in the current wastewater is comprehensively evaluated whether it exceeds the standard.

[0018] Preferably, the specific steps for analyzing the concentration change rate of dissolved ions in wastewater under the detection window to generate the dissolved ion concentration change rate reference value are as follows:

[0019] The change of the concentration of dissolved ions with time is accurately calculated, and the rate of change of the concentration of dissolved ions in wastewater with time is analyzed, that is, the relationship between the increment of the concentration of dissolved ions and time within a time interval, and the calculation expression is as follows:

[0020]

[0021] , wherein, ΔConc i is the concentration change rate of the i-th dissolved ion within the time period Δt, Δt is the time interval, Conc i (t) is the concentration of the i-th dissolved ion at time t, and Conc i (t+Δt) is the concentration of the i-th dissolved ion at time t+Δt.

[0022] After obtaining the concentration change rate of each dissolved ion in wastewater, the obtained concentration change is integrated to generate a dissolved ion concentration change rate reference value, and the calculation expression is as follows:

[0023]

[0024] In the formula, DICCR is the dissolved ion concentration change rate reference value, a i is the weight coefficient of the dissolved ion concentration change rate, indicating the sensitivity of the dissolved ion to the concentration of pollutants in wastewater, and n is the number of dissolved ion species.

[0025] Preferably, the specific steps for analyzing the concentration of reactive chemical molecules in wastewater under the detection window to generate a reactive molecule reference value are as follows:

[0026] The concentration change of reactive chemical molecules in wastewater is monitored by a real-time detection device. Reactive molecules are important intermediates in the degradation process of wastewater pollutants, and the concentration of reactive molecules reflects the degree of activity of redox reactions in wastewater. The concentration data of various types of reactive chemical molecules in wastewater are obtained in real time and converted into numerical values. The initial concentration of reactive chemical molecules is calculated according to the following formula:

[0027]

[0028] In the formula, RCI is the initial reactive chemical molecule concentration index, C j (t) is the concentration of the jth reactive chemical molecule at time t, W j is the weight coefficient of the jth reactive chemical molecule, representing the contribution of the molecule to wastewater degradation, T is the total duration of the detection window, and m is the number of all detected reactive molecules in wastewater.

[0029] After obtaining the initial reactive chemical molecule concentration index RCI, dynamic evaluation is performed to determine whether harmful substances in wastewater exceed the standard. The concentration of pollutants is accurately determined, and a dynamic threshold evaluation model is introduced to compare the initial reactive chemical molecule concentration index with the set over-standard threshold. The formula for the dynamic evaluation process is as follows:

[0030]

[0031] In the formula, RM is the reactive molecule reference value, C threshold is the concentration over-standard threshold, and k is the dynamic adjustment factor, which controls the sensitivity of the index.

[0032] Preferably, the dissolved ion concentration change rate reference value and the reactive molecule reference value after comprehensive analysis are input into the pre-trained machine learning model, the harmful substance concentration change coefficient is generated through the machine learning model, the current wastewater harmful substance concentration is intelligently evaluated through the harmful substance concentration change coefficient, and whether the wastewater harmful substance concentration exceeds the standard is judged.

[0033] Preferably, when the current wastewater harmful substance concentration is intelligently evaluated through the pre-trained machine learning model, the harmful substance concentration change coefficient generated is compared and analyzed with the pre-set harmful substance concentration change coefficient reference threshold value, whether the wastewater harmful substance concentration exceeds the standard is judged, and the judgment logic is as follows:

[0034] If the harmful substance concentration change coefficient is greater than the pre-set harmful substance concentration change coefficient reference threshold value, it is judged that the current wastewater harmful substance concentration exceeds the standard; if the harmful substance concentration change coefficient is less than or equal to the pre-set harmful substance concentration change coefficient reference threshold value, it is judged that the current wastewater harmful substance concentration does not exceed the standard.

[0035] Preferably, when it is identified that the harmful substance concentration in the wastewater exceeds the standard, based on the pollutant concentration data, the dosage of the photocatalyst is dynamically adjusted to provide more active sites; at the same time, according to the intelligent evaluation result, the power and illumination time of the ultraviolet light source are dynamically adjusted to enhance the intensity of the photocatalytic reaction. The specific steps are as follows:

[0036] When it is identified that the harmful substance concentration in the wastewater exceeds the standard, the dosage of the photocatalyst is increased to provide more active sites, thereby enhancing the pollutant degradation effect in the wastewater. The dynamic adjustment calculation expression of the dosage of the photocatalyst is as follows:

[0037]

[0038] , wherein C catalyst is the adjusted dosage of the photocatalyst, C catalyst，base is the basic dosage of the photocatalyst, ΔC catalyst is the increment coefficient of the basic dosage, HSCC is the harmful substance concentration change coefficient, HSCC threshold is the harmful substance concentration change coefficient reference threshold value, and e is the natural base;

[0039] The power of the ultraviolet light source determines the energy input of the photocatalytic reaction. The power of the ultraviolet light source is adjusted to promote the generation of more free radicals on the surface of the catalyst and enhance the intensity of the photocatalytic reaction. The dynamic adjustment calculation expression of the power of the ultraviolet light source is as follows:

[0040]

[0041] , wherein P UVis the adjusted ultraviolet light source power, P UV，base is the basic ultraviolet light source power, and a is the adjustment coefficient.

[0042] Increasing the illumination time provides more time for the reaction, ensuring that the harmful substances in the wastewater are fully reacted. By extending the illumination time, the reaction time between the pollutants and the free radicals generated by the catalyst will be increased, thereby effectively improving the reaction efficiency. The dynamic adjustment calculation expression of the illumination time is as follows:

[0043]

[0044] , wherein t light is the adjusted illumination time, t light，base is the basic illumination time, and g is the illumination time adjustment coefficient.

[0045] In the above technical solution, the technical effects and advantages provided by the present application are as follows:

[0046] The present application can dynamically adjust the dosage of the photocatalyst, the power of the ultraviolet light source, and the illumination time by real-time acquisition of the harmful substance concentration data in the wastewater and intelligent evaluation, ensuring that the photocatalytic reaction is always in the optimal state. This not only avoids excessive load and active site blockage of the catalyst, but also intelligently adjusts the treatment parameters according to the degree of wastewater pollution, fully utilizes the degradation capacity of the photocatalytic reaction, and ensures that the harmful substances in the wastewater are fully removed, ultimately achieving efficient and stable wastewater advanced treatment effect, while reducing resource waste and operating cost. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments or prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art based on these drawings.

[0048] Figure 1 The method flowchart of the cold-rolled acid wastewater advanced treatment method of the present application. DETAILED DESCRIPTION

[0049] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations, however, can be implemented in many different forms and should not be construed as limited to the examples set forth herein; rather, these example implementations are provided so that this disclosure will be thorough and complete, and will fully convey the inventive aspects of the example implementations to those skilled in the art.

[0050] The present application provides a cold-rolled acid wastewater advanced treatment method as shown in Figure 1 The present application provides a cold-rolled acid wastewater advanced treatment method as shown in

[0051] During the treatment of cold rolling acidic wastewater by photocatalytic oxidation method, the concentration data of harmful substances in the wastewater is obtained in real time to understand the degree of wastewater pollution.

[0052] The concentration data of harmful substances can be obtained through online sensors, spectral analyzers, chemical analyzers, etc. to ensure that the concentration of various pollutants (such as organic matter, metal ions, etc.) in the wastewater is accurately monitored.

[0053] Real-time acquisition of harmful substance data in wastewater is the basis for ensuring the intelligentization and dynamic adjustment of the treatment process. Sensors can continuously monitor the changing trend of pollutants in wastewater, providing real-time input for subsequent data analysis and processing. This stage is crucial for precise control of the reaction process, especially in the case of high pollution load, which can capture the changes in pollutant concentration in real time to prevent excessive or insufficient treatment. For various pollutants (such as Fe 2+ , Fe 3+ , phenolic substances, phenol sulfonic acid, etc.) that may exist in wastewater, appropriate detection equipment should be selected according to different chemical properties.

[0054] The specific steps for obtaining the concentration data of harmful substances in wastewater in real time during the treatment of cold rolling acidic wastewater by photocatalytic oxidation method are as follows:

[0055] According to the types of pollutants in the wastewater, select the appropriate detection equipment to monitor the concentration of harmful substances in real time;

[0056] When treating cold rolling acidic wastewater by photocatalytic oxidation method, first, appropriate monitoring equipment needs to be selected, which will detect the concentration of pollutants in wastewater in real time. Common monitoring equipment includes chemical sensors, spectral analyzers, ion-selective electrodes, etc. According to the types of pollutants in the wastewater (such as metal ions, phenols, acidic substances, etc.), selecting the corresponding sensors can ensure measurement accuracy. For example, the concentration of metal ions (such as Fe 2+ , Fe 3+ ) can be detected by electrochemical sensors, while organic pollutants can be monitored by spectral analyzers. The equipment should have stability, anti-interference ability and real-time data transmission capability to facilitate subsequent real-time monitoring.

[0057] Through the automatic system, the concentration data of pollutants in the wastewater is continuously collected to ensure real-time reflection of the changes in pollutants during the treatment process;

[0058] The selected monitoring devices will continuously work during the wastewater treatment process, measuring and collecting the concentration data of harmful substances in real time. These data can be collected through an automated system, ensuring that the pollutant concentration at each moment can be accurately recorded. The time interval for data collection can be set according to the frequency of changes in pollutant concentration in wastewater, usually in real-time sampling such as seconds, minutes, etc. The data collection system should have the ability to transmit data to the control center or data processing platform in real time, so as to quickly respond to changes in the treatment system and ensure that the monitoring results can be applied to the optimization and adjustment of wastewater treatment in a timely manner.

[0059] The collected real-time data is transmitted to the data platform through the network for storage, ensuring the accuracy and integrity of the data and providing a reliable basis for subsequent analysis and processing.

[0060] Once the concentration data of harmful substances in wastewater is collected, the next key step is to transmit these data to the central processing system or cloud platform for storage. This process involves real-time data transmission, usually through wireless networks (such as Wi-Fi, LoRa, Bluetooth, etc.) or wired networks (such as Ethernet, optical fiber, etc.) to transmit data to the data center. During data storage, data should be guaranteed for integrity and accuracy to ensure no loss or tampering. At the same time, data should be backed up regularly to prevent data loss due to system failure. The stored data can be used for historical analysis to help identify long-term pollution trends in wastewater, and also provides basic data for the training of machine learning models and real-time intelligent assessment

[0061] The obtained harmful substance data information is preprocessed, and the preprocessed data is collectively managed to establish a data set;

[0062] The real-time data is preprocessed to improve the quality of the data and ensure that it meets the requirements of machine learning algorithms. Preprocessing usually includes the following steps: data denoising (eliminate sensor errors through filtering, smoothing, etc.), missing value filling (use interpolation, mean filling, etc.), and data standardization or normalization (to make the data on the same order of magnitude, to avoid some pollutants affecting the analysis results due to unit differences). This process is crucial to ensure that the subsequent machine learning model can efficiently process data and obtain accurate results.

[0063] The data set is the core of the machine learning process. This set not only includes the concentration data of different pollutants in wastewater, but also records other related variables (such as water temperature, pH value, etc.). These data will be organized in time series to form a complete historical data set. Over time, the data set continues to grow, and the machine learning model can use these historical data to train and optimize, thereby improving its prediction ability. In addition, this data set can also contain the actual effect of each reaction process (such as pollutant degradation rate, etc.), so that the machine learning model can not only evaluate the current situation, but also predict future trends.

[0064] From the data set, extract the decisive variables that reflect the over-standard concentration of pollutants in wastewater, and comprehensively analyze the extracted decisive variables to assess whether the concentration of harmful substances in the current wastewater is over-standard;

[0065] From the data set, extract the decisive variables that reflect the over-standard concentration of pollutants in wastewater, and the extracted variables include the change rate of dissolved ion concentration in wastewater and the concentration of reactive chemical molecules (such as free radicals, active molecules, etc.) in wastewater. Under the detection window, the change rate of dissolved ion concentration in wastewater and the concentration of reactive chemical molecules (such as free radicals, active molecules, etc.) are comprehensively analyzed to generate dissolved ion concentration change rate reference value and reactive molecule reference value. Through the dissolved ion concentration change rate reference value and the reactive molecule reference value, the concentration of harmful substances in the current wastewater is comprehensively evaluated whether it is over-standard.

[0066] The accelerated change rate of dissolved ion concentration in wastewater indeed indicates that the concentration of harmful substances in the current wastewater is over-standard, especially when the wastewater contains soluble heavy metal ions, organic acids or salts and other pollutants. The change rate of dissolved ion concentration refers to the change rate of dissolved ion concentration in wastewater over time, which is usually closely related to the degree of chemical reaction in wastewater. When the concentration of harmful substances in wastewater is high, pollutants will react with other chemical components in water, causing rapid changes in the concentration of dissolved ions. For example, if the wastewater contains a large amount of metal ions or organic acids, these pollutants will quickly react with other components in water, causing the concentration of dissolved ions to increase rapidly. At this time, the change rate of dissolved ion concentration is accelerated, which usually means that the concentration of harmful substances in water has reached or approached the over-standard level, which may cause more serious pollution or changes in water quality. Therefore, the accelerated change rate of dissolved ion concentration can be an effective indicator of wastewater pollution over-standard, indicating that the concentration of pollutants in wastewater is too high, and further treatment measures need to be taken immediately to avoid environmental pollution or adverse effects on the water ecosystem.

[0067] The specific steps for analyzing the change rate of dissolved ion concentration in wastewater under the detection window to generate the dissolved ion concentration change rate reference value are as follows:

[0068] The change of the dissolved ion concentration over time is accurately calculated, and the rate of change of the concentration of the dissolved ion in the wastewater over time, i.e. the relationship between the increment of the dissolved ion concentration and time within a time interval, is analyzed, and the calculation expression is as follows:

[0069]

[0070] , wherein ΔConc i is the rate of change of the concentration of the i-th dissolved ion within the time period Δt, Δt is the time interval, Conc i (t) is the concentration of the i-th dissolved ion at time t, and Conc i (t+Δt) is the concentration of the i-th dissolved ion at time t+Δt.

[0071] This step reflects the dynamic change of the dissolved ion by calculating the change of the concentration of each dissolved ion in the wastewater within a specified time period (Δt). The greater the concentration change rate (ΔConc i ), the more rapidly the concentration of the dissolved ion changes, which is usually related to the rapid dissolution or reaction of the pollutant, and may indicate that the concentration of the harmful substance in the wastewater exceeds the standard. Through this step, the change rate of each dissolved ion within the time period is obtained, laying the foundation for further index generation.

[0072] After obtaining the concentration change rate of each dissolved ion in the wastewater, the obtained concentration change is integrated to generate a dissolved ion concentration change rate reference value. The generation of the dissolved ion concentration change rate reference value takes into account the concentration change of multiple dissolved ions, and can comprehensively reflect the risk of concentration exceeding the standard of harmful substances in the wastewater, and the calculation expression is as follows:

[0073]

[0074] , wherein DICCR is the dissolved ion concentration change rate reference value, α i is the weight coefficient of the dissolved ion concentration change rate, indicating the sensitivity of the dissolved ion to the concentration exceeding the standard of the pollutant in the wastewater, and n is the number of dissolved ion species.

[0075] The above step integrates the concentration change rate (ΔConc i ) of each dissolved ion into a comprehensive reference value by weighted summation, and the weight coefficient (α i) reflects the contribution of different dissolved ions to the concentration of harmful substances in wastewater exceeding the standard. For example, certain metal ions or chemicals may have a more significant impact on the change in dissolved ion concentration when exceeding the standard, so they will have a higher weight coefficient. The larger the reference value, the faster the concentration of harmful substances in wastewater changes, and the greater the risk of exceeding the standard. Through this index, it can effectively determine whether the pollutants in the wastewater exceed the standard and provide decision-making basis for subsequent dynamic adjustment.

[0076] The larger the dissolved ion concentration rate reference value generated after analyzing the dissolved ion concentration rate in the detection window, the more likely the concentration of harmful substances in wastewater exceeds the standard, and vice versa. The dissolved ion concentration rate reflects the change speed of dissolved substances in wastewater. When the concentration of harmful substances in wastewater is high, these pollutants will quickly dissolve and react with other components in the water, causing the concentration of dissolved ions to change rapidly. For example, when wastewater contains a large amount of metal ions, organic acids or other chemicals, their rapid dissolution will significantly increase the change rate of dissolved ion concentration, so the generated dissolved ion concentration rate reference value will be larger, indicating that the concentration of pollutants exceeds the standard. Conversely, if the concentration of pollutants in wastewater is low or stable, the change rate of dissolved ions is slow, and the reference value is small, indicating that the concentration of pollutants does not exceed the standard.

[0077] The increase in the concentration of reactive chemical molecules (such as free radicals, active molecules, etc.) in wastewater usually indicates that the concentration of harmful substances in wastewater exceeds the standard. Free radicals and active molecules (such as hydroxyl radicals ·OH and superoxide anions O2 ·- , etc.) are key intermediates in the degradation reaction of pollutants in wastewater, and they have strong oxidizing ability and can quickly react with harmful substances in wastewater. When the concentration of harmful substances in wastewater is too high, the concentration of reactive molecules will increase, because the system releases more reactive substances to accelerate the degradation of harmful pollutants, especially in the case of high concentration of pollutants. This increase in reactive molecules is usually due to the production of more free radicals by catalysts (such as TiO2) under ultraviolet light, or the increase in the activity of other redox reactions in wastewater. The increase in the concentration of reactive chemical molecules is a common sign in wastewater treatment, indicating an increase in reaction activity, which may occur when treating high concentrations of harmful substances. In addition, high concentrations of organic pollutants or metal ions (such as Fe 2+ , Fe 3+ ) often exacerbate the generation of such reactive molecules. Therefore, the increase in the concentration of reactive molecules is an important indicator of the concentration of harmful substances in wastewater exceeding the standard, which can help identify the pollution load in wastewater in a timely manner.

[0078] The specific steps for analyzing the concentration of reactive chemical molecules (such as free radicals, active molecules, etc.) in wastewater within the detection window to generate the reference value of reactive molecules are as follows:

[0079] By monitoring the concentration changes of reactive chemical molecules in wastewater through real-time detection equipment (such as online sensors or spectral analyzers), reactive molecules (such as free radicals, active molecules, etc.) are important intermediates in the degradation process of wastewater pollutants, and the concentration of reactive molecules reflects the degree of redox reaction activity in wastewater. When the concentration of harmful substances in wastewater is high, more reactive molecules are generated to promote the degradation of pollutants. Through these devices, the concentration data of various types of reactive chemical molecules in wastewater are obtained in real time and converted into numerical values. The concentration calculation formula of the initial reactive chemical molecules is as follows:

[0080]

[0081] , where RCI is the initial reactive chemical molecule concentration index, C j (t) is the concentration of the jth reactive chemical molecule at time t, W j is the weight coefficient of the jth reactive chemical molecule, representing the contribution of the molecule in wastewater degradation, T is the total duration of the detection window, and m is the number of all detected reactive molecules in wastewater;

[0082] This formula considers the relative contribution of each molecule in pollutant degradation (represented by the weight coefficient W j ) by integrating the concentration of each type of reactive molecule over time. The generated initial reactive chemical molecule concentration index (RCI) provides overall reactive molecule concentration data within the time window for subsequent analysis.

[0083] After obtaining the initial reactive chemical molecule concentration index RCI, dynamic evaluation is performed to determine whether the concentration of harmful substances in wastewater exceeds the standard. The larger the RCI, the higher the concentration of harmful substances in wastewater, indicating the need to strengthen the treatment intensity. Accurate determination of whether the concentration of pollutants exceeds the standard is achieved by introducing a dynamic threshold evaluation model, which compares the initial reactive chemical molecule concentration index with the set over-standard threshold. The formula for the dynamic evaluation process is as follows:

[0084]

[0085] , where RM is the reference value of reactive molecules, C threshold is the concentration over-standard threshold, and k is the dynamic adjustment factor controlling the sensitivity of the index.

[0086] This formula is based on the sigmoid function (S-shaped curve) and is used to map the calculated initial reactive chemical molecule concentration index to a more discriminative value (RCI final). When the reactivity index RCI exceeds a set threshold C threshold , RCI final will tend to 1, indicating that the concentration of harmful substances in the wastewater exceeds the standard; if RCI is lower than the threshold, RCI final is close to 0, indicating that the concentration of pollutants does not exceed the standard.

[0087] The greater the reference value of the reactive molecules generated after analyzing the concentration of reactive chemical molecules (such as free radicals, active molecules, etc.) in the wastewater within the detection window, the more likely it is that the concentration of harmful substances in the wastewater exceeds the standard, and vice versa. The reference value of the reactive molecules reflects the concentration of reactive chemical molecules (such as free radicals, active molecules, etc.) in the wastewater, which play an important role in the wastewater treatment process, mainly by undergoing redox reactions with pollutants to degrade harmful substances. When the concentration of harmful substances in the wastewater is high, more free radicals and active molecules need to be generated to accelerate the reaction process, and the concentration of reactive molecules will increase. The increase in the reference value of the reactive molecules indicates an increase in the concentration of harmful substances in the wastewater, reflecting that the wastewater pollution load is heavy and may exceed the conventional treatment capacity of the treatment system. On the contrary, when the concentration of pollutants in the wastewater is low, the concentration of reactive molecules remains low, and the reference value of the reactive molecules will also be low, indicating that the concentration of harmful substances in the wastewater does not exceed the standard.

[0088] The decisive variables after comprehensive analysis are input into the pre-trained machine learning model, and the current wastewater harmful substance concentration is intelligently evaluated by the model to determine whether the wastewater harmful substance concentration exceeds the standard.

[0089] The reference value of the change rate of the dissolved ion concentration and the reference value of the reactive molecules after comprehensive analysis are input into the pre-trained machine learning model, and the harmful substance concentration change coefficient is generated by the machine learning model. The current wastewater harmful substance concentration is intelligently evaluated by the harmful substance concentration change coefficient to determine whether the wastewater harmful substance concentration exceeds the standard.

[0090] The pre-trained machine learning model refers to an intelligent model that can predict the concentration change of harmful substances in wastewater based on a large amount of historical data and pollutant concentration changes under different conditions in the wastewater treatment system. The model is trained and optimized through machine learning algorithms such as regression models, decision trees, and support vector machines in supervised learning. The training process of the model is based on a historical data set, which includes the concentration changes of different pollutants (such as metal ions and organic matter) in wastewater, environmental variables (such as water temperature, pH value, and flow rate) during wastewater treatment, and the corresponding treatment effects (such as pollutant removal rate). Through machine learning algorithms, the model can analyze and train these data, identify the relationship between pollutant concentration changes and treatment parameters (such as catalyst dosage and ultraviolet light intensity), and learn how to automatically evaluate the trend of pollutant concentration changes in different wastewater treatment scenarios. Therefore, the trained model can receive new input data in real time during actual operation and generate an accurate prediction value, i.e., the harmful substance concentration change coefficient, based on the learning experience in historical data.

[0091] The core function of the pre-trained machine learning model is intelligent evaluation in the wastewater treatment system. By inputting real-time monitored data such as dissolved ion concentration change rate and reactive molecule reference value, the model can automatically calculate the harmful substance concentration change coefficient based on the rules and patterns learned during its training process, and determine whether the harmful substances in the wastewater have reached an excessive concentration. Specifically, the model analyzes the similarity between the current input data and historical data, evaluates the pollution load of the current wastewater, and calculates the change coefficient to represent the rate of change of pollutant concentration. Based on this change coefficient, the system can make real-time decisions and automatically adjust relevant parameters (such as the dosage of photocatalyst and the intensity of ultraviolet light) in the wastewater treatment process, thereby optimizing the wastewater treatment effect, avoiding excessive pollutant concentration, and ensuring that the final wastewater discharge meets environmental protection standards. The automatic evaluation and intelligent adjustment of the machine learning model can significantly improve the automation and accuracy of the wastewater treatment system, thereby improving the efficiency and stability of the entire treatment process.

[0092] The machine learning model is not limited and can achieve comprehensive analysis of the dissolved ion concentration change rate reference value DICCR and the reactive molecule reference value RM to generate the harmful substance concentration change coefficient HSCC. To achieve the technical solution of the present application, a specific implementation method is provided.

[0093] The harmful substance concentration change coefficient HSCC is generated according to the following formula: HSCC = k1·DICCR + k2RM, where k1 and k2 are preset proportionality coefficients for the dissolved ion concentration change rate reference value DICCR and the reactive molecule reference value RM, respectively, and both k1 and k2 are greater than 0.

[0094] The preset proportionality coefficients refer to coefficients used in the machine learning model to represent the degree of influence of each parameter on the target output. In this case, the generation formula of HSCC (Harmful Substance Concentration Change Coefficient) contains two proportionality coefficients k1 and k2, which correspond to two input parameters: DICCR (Dissolved Ion Concentration Change Rate) and RM (Reactive Molecules). These proportionality coefficients are preset to adjust the contribution of different input parameters to the calculation of HSCC.

[0095] Specifically, the values of k1 and k2 determine the relative importance of the dissolved ion concentration change rate and the reactive molecule reference value in calculating the harmful substance concentration change coefficient. k1 and k2 are usually determined through the training process of the machine learning model, which learns the optimal coefficient values through a large amount of data, so that the prediction results are closest to the actual wastewater treatment results. In this formula, the values of k1 and k2 must be greater than 0, indicating that the influence of both parameters on HSCC is positive, i.e., as the dissolved ion concentration change rate and the concentration of reactive molecules change, the change in the concentration of harmful substances in wastewater will also change accordingly.

[0096] From the harmful substance concentration change coefficient, it can be seen that the greater the dissolved ion concentration change rate reference value generated by analyzing the dissolved ion concentration change rate in the wastewater in the detection window, and the greater the reactive molecule reference value generated by analyzing the concentration of reactive chemical molecules (such as free radicals, active molecules, etc.) in the wastewater in the detection window, the greater the harmful substance concentration change coefficient generated by the intelligent evaluation of the current wastewater harmful substance concentration by the pre-trained machine learning model, indicating that the probability of the current wastewater harmful substance concentration exceeding the standard is greater, and vice versa.

[0097] The harmful substance concentration change coefficient generated by the intelligent evaluation of the current wastewater harmful substance concentration by the pre-trained machine learning model is compared and analyzed with the pre-set harmful substance concentration change coefficient reference threshold to determine whether the wastewater harmful substance concentration exceeds the standard, and the judgment logic is as follows:

[0098] If the harmful substance concentration change coefficient is greater than the pre-set harmful substance concentration change coefficient reference threshold, it is determined that the current wastewater harmful substance concentration exceeds the standard; if the harmful substance concentration change coefficient is less than or equal to the pre-set harmful substance concentration change coefficient reference threshold, it is determined that the current wastewater harmful substance concentration does not exceed the standard.

[0099] When it is identified that the concentration of harmful substances in wastewater exceeds the standard, based on the pollutant concentration data, the dosage of photocatalyst is dynamically adjusted to provide more active sites; at the same time, according to the intelligent evaluation result, the power and illumination time of the ultraviolet light source are dynamically adjusted to enhance the intensity of the photocatalytic reaction, promote the generation of more free radicals on the surface of the catalyst, and thus ensure that the harmful substances in the wastewater are fully degraded;

[0100] By dynamically adjusting the key operating parameters of the photocatalytic oxidation method based on real-time wastewater pollutant concentration data and intelligent evaluation results, it is ensured that the harmful substances in the wastewater can be efficiently and fully degraded. Specifically, when the system detects that the concentration of harmful substances in the wastewater exceeds the standard, first, the dosage of photocatalyst is dynamically adjusted to provide more active sites, ensuring that the catalyst can adsorb more pollutants and promote the reaction. The surface active sites of the catalyst play a key role in the catalytic reaction, and increasing the amount of catalyst can effectively make up for the problem of insufficient surface active sites of the catalyst due to too high concentration of pollutants, thereby ensuring the smooth progress of the photocatalytic reaction.

[0101] In addition, dynamically adjusting the power and illumination time of the ultraviolet light source can further enhance the intensity of the photocatalytic reaction. The ultraviolet light source is an important energy source for exciting the photocatalyst, and the increase of its power can enhance the number of free radicals (such as hydroxyl radicals ·OH and superoxide anions O2 ·- ) generated on the surface of the catalyst, thereby improving the reaction rate and removal efficiency. Increasing the illumination time helps to prolong the contact time between pollutants and catalyst, further promoting the degradation of pollutants. By adjusting these parameters in real time, the reaction process can be automatically optimized according to the actual pollution degree of the wastewater, thereby ensuring the maximum reaction efficiency and avoiding resource waste, while ensuring the efficiency and stability of the wastewater treatment process.

[0102] The core of this process is to achieve intelligent adjustment, responding to changes in wastewater pollutant concentration through precise control strategies to ensure that the system always maintains the best operating state, ultimately achieving the goal of fully degrading harmful substances in wastewater. This dynamic adjustment mechanism not only improves the efficiency of wastewater treatment, but also enhances the adaptability and stability of the system, especially in the face of large fluctuations in pollutant concentration.

[0103] When it is identified that the concentration of harmful substances in wastewater exceeds the standard, based on the pollutant concentration data, the dosage of photocatalyst is dynamically adjusted to provide more active sites; at the same time, according to the intelligent evaluation result, the power and illumination time of the ultraviolet light source are dynamically adjusted to enhance the intensity of the photocatalytic reaction, the specific steps are as follows:

[0104] When it is identified that the concentration of harmful substances in wastewater exceeds the standard, the dosage of photocatalyst is increased to increase more active sites, thereby enhancing the degradation effect of pollutants in wastewater. Increasing the amount of photocatalyst can ensure that harmful substances in wastewater are fully reacted, especially when the concentration of pollutants is high, which can effectively avoid the deficiency of the reaction. The dynamic adjustment calculation expression of the dosage of photocatalyst is as follows:

[0105]

[0106] , wherein C catalyst is the adjusted dosage of photocatalyst, C catalyst，base is the basic dosage of photocatalyst, ΔC catalyst is the increment coefficient of the basic dosage, indicating the increase proportion of photocatalyst per unit change, HSCC is the harmful substance concentration change coefficient, and HSCC threshold is the reference threshold value of the harmful substance concentration change coefficient, and e is the natural base;

[0107] When the harmful substance concentration change coefficient HSCC exceeds the reference threshold value, the dosage of catalyst is adjusted in the form of an exponential function to enhance the response to the change in pollutant concentration. The characteristic of exponential growth can rapidly increase the amount of photocatalyst when the concentration of pollutants fluctuates greatly, thereby compensating for the possible loss of active sites on the catalyst surface and ensuring the reaction efficiency.

[0108] The power of the ultraviolet light source determines the energy input of the photocatalytic reaction. Adjusting the power of the ultraviolet light source can promote the generation of more free radicals on the catalyst surface and enhance the strength of the photocatalytic reaction. When the concentration of harmful substances is high, the power of the ultraviolet light source needs to be appropriately increased to provide sufficient energy to support the reaction. The dynamic adjustment calculation expression of the power of the ultraviolet light source is as follows:

[0109]

[0110] , wherein P UV is the adjusted power of the ultraviolet light source, P UV，base is the basic power of the ultraviolet light source, and α is the adjustment coefficient, indicating the relationship between the power of the ultraviolet light source and the harmful substance concentration change coefficient.

[0111] The increase in the power of the ultraviolet light source is dynamically adjusted based on the harmful substance concentration change coefficient HSCC. When the concentration of harmful substances in wastewater changes beyond the reference threshold value, the increase in power will accelerate in the form of a power function to ensure that sufficient energy is provided during the reaction process. This process can accelerate the generation of free radicals and enhance the reaction intensity, thereby ensuring the effective degradation of pollutants.

[0112] The increase of light duration provides more time for the reaction, ensures that the harmful substances in the wastewater are fully reacted, and by prolonging the light duration, the reaction time between the pollutants and the free radicals generated by the catalyst will be increased, thereby effectively improving the reaction efficiency, and the dynamic adjustment calculation expression of the light duration is as follows:

[0113]

[0114] In the formula, t light is the adjusted light duration, t light，base is the basic light duration, and gamma is the light duration adjustment coefficient, which is used to control the increase of the light duration.

[0115] The increase of the light duration is realized by two parts of adjustment. The linear part ensures that the light duration is appropriately prolonged with the change of the pollutant concentration, and the logarithmic part avoids excessive prolongation, so that the increase of the light duration is more smooth, and the light duration will not be excessively prolonged when the pollutant concentration changes sharply. This makes the reaction more flexible, and avoids unnecessary energy waste.

[0116] The present application can dynamically adjust the dosage of the photocatalyst, the power of the ultraviolet light source and the light duration by real-time acquisition of the harmful substance concentration data in the wastewater and intelligent evaluation, so that the photocatalytic reaction is always in the optimal state. In this way, not only the excessive load and active site blockage of the catalyst can be avoided, but also the treatment parameters can be intelligently adjusted according to the pollution degree of the wastewater, the degradation capacity of the photocatalytic reaction can be fully utilized, and the harmful substances in the wastewater can be fully removed, so that the effect of efficient and stable wastewater advanced treatment is achieved, and the resource waste and operation cost are reduced.

[0117] The above formulas are dimensionless values, and the formulas are obtained by software simulation of a large amount of data to obtain a formula of the most recent real situation, and the preset parameters in the formula are set by the person skilled in the art according to the actual situation.

[0118] The above only describes some exemplary embodiments of the present application by way of illustration, and it is needless to say that the described embodiments can be modified in various ways without departing from the spirit and scope of the present application for those skilled in the art. Therefore, the above figures and descriptions are illustrative in nature and should not be understood as limiting the scope of protection of the claims of the present application.

[0119] It should be noted that, in the present document, relational terms are used to convey a relationship of one entity or action to another entity or action. For example, without necessarily implying any actual relationship or order between entities or actions, the terms "first," "second," "top" and "bottom" are used to name different entities and actions, and are used to distinguish one element from another. Furthermore, the terms "comprise," "include," and "have," and variations thereof, do not preclude the presence or addition of one or more other elements or steps, unless the context clearly indicates otherwise. The term "including" as used herein, means "comprising" in the sense of the transition word "comprising," and not by way of limitation. The use of "including" and "including" and "have" and variations thereof herein, does not imply that there are no additional elements or steps. The term "coupled" as used herein, means the joining of two members together such that the members together and / or one or both members can function together.

[0120] It should be understood that the sequence numbers of the processes described above do not mean execution sequence, and the execution sequence of the processes should be determined according to their functions and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0121] Those skilled in the art can clearly understand that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0122] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0123] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e. they can be located in one place or distributed on multiple network units. Part or all of the units can be selected to achieve the purpose of the embodiments according to actual needs.

[0124] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present alone, or two or more units can be integrated in one unit.

[0125] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present application, which should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0126] The foregoing merely illustrates some exemplary embodiments of the present application, and it is obvious to those skilled in the art that the described embodiments can be modified in various ways without departing from the spirit and scope of the present application. Therefore, the above drawings and descriptions are illustrative in nature, and should not be construed as limiting the scope of the claims of the present application.

Claims

1. A method for advanced treatment of cold rolling acidic wastewater, characterized by, Includes the following steps: During the treatment of cold rolling acidic wastewater by photocatalytic oxidation, the concentration data of harmful substances in the wastewater are obtained in real time to understand the degree of wastewater pollution. The acquired data on hazardous substances is preprocessed, and the preprocessed data is then aggregated and managed to establish a data set. The decisive variables reflecting the excessive concentration of pollutants in wastewater are extracted from the dataset, and the extracted decisive variables are comprehensively analyzed to fully assess whether the concentration of harmful substances in the current wastewater exceeds the standard. The decisive variables after comprehensive analysis are input into a pre-trained machine learning model. The model then intelligently assesses the concentration of harmful substances in the current wastewater and determines whether the concentration exceeds the standard. When the concentration of harmful substances in wastewater exceeds the standard, the dosage of photocatalyst is dynamically adjusted based on pollutant concentration data to provide more active sites. Meanwhile, based on the intelligent evaluation results, the power and duration of the ultraviolet light source are dynamically adjusted to enhance the intensity of the photocatalytic reaction and promote the generation of more free radicals on the catalyst surface, thereby ensuring that harmful substances in the wastewater are fully degraded. Reactive molecular reference values ​​comprehensively assess whether the concentration of harmful substances in the current wastewater exceeds the standard; The specific steps for analyzing the concentration of reactive chemical molecules in wastewater under a detection window to generate reference values ​​for reactive molecules are as follows: The concentration changes of reactive chemical molecules in wastewater are monitored in real time using detection equipment. Reactive molecules are important intermediates in the degradation process of wastewater pollutants, and their concentration reflects the activity of redox reactions in the wastewater. The concentration data of various reactive chemical molecules in wastewater are acquired in real time and converted into numerical values. The initial concentration of reactive chemical molecules is calculated using the following formula: , wherein, is the initial reactivity chemical molecule concentration index, is the concentration of the th reactivity chemical molecule at time , is the weight coefficient of the th reactivity chemical molecule, representing the contribution degree of the molecule in wastewater degradation, is the total length of the detection window, is the number of species of all detected reactivity molecules in wastewater; Obtaining initial reactivity chemical molecule concentration index After that, dynamic evaluation is carried out to determine whether the harmful substances in the wastewater exceed the standard, accurately determine whether the pollutant concentration exceeds the standard, introduce a dynamic threshold evaluation model, compare the initial reactivity chemical molecule concentration index with the set exceeding threshold, and the formula of the dynamic evaluation process is as follows: , wherein, is the reference value of the reactive molecule, is the threshold of concentration exceeding, is the dynamic adjustment factor, controlling the sensitivity of the index.

2. The method for deep treatment of cold-rolling acidic wastewater according to claim 1, characterized in that, The specific steps for obtaining real-time concentration data of harmful substances in the wastewater during the photocatalytic oxidation process for treating acidic wastewater from cold rolling are as follows: Based on the types of pollutants in the wastewater, select appropriate detection equipment to monitor the concentration of harmful substances in real time; The system continuously collects pollutant concentration data in wastewater through an automated system to ensure that changes in pollutants during the treatment process are reflected in real time. The collected real-time data is transmitted to the data platform via the network for storage, ensuring the accuracy and integrity of the data and providing a reliable foundation for subsequent analysis and processing.

3. The cold rolling acidic wastewater advanced treatment method according to claim 1, characterized in that, The decisive variables reflecting the excessive concentration of pollutants in wastewater are extracted from the dataset. The extracted variables include the rate of change of dissolved ion concentration and the concentration of reactive chemical molecules in wastewater. Under the detection window, the extracted rate of change of dissolved ion concentration and the concentration of reactive chemical molecules in wastewater are comprehensively analyzed to generate reference values ​​for the rate of change of dissolved ion concentration and reference values ​​for reactive molecules.

4. The cold rolling acidic wastewater advanced treatment method according to claim 3, characterized in that, The specific steps for analyzing the rate of change of dissolved ion concentration in wastewater under a detection window to generate a reference value for the rate of change of dissolved ion concentration are as follows: The change in dissolved ion concentration over time is precisely calculated to analyze the rate of change of dissolved ion concentration in wastewater over time, i.e., the relationship between the increase in dissolved ion concentration and time within a time interval. The calculation expression is as follows: wherein is the rate of change of the concentration of the dissolved ions of the first species over the time period , is the time interval, is the concentration of the dissolved ions of the first species at time , is the concentration of the dissolved ions of the first species at time ; After obtaining the concentration change rate of each dissolved ion in the wastewater, the obtained concentration changes are combined to generate a reference value for the dissolved ion concentration change rate. The calculation expression is as follows: , wherein, is a reference value of the rate of change of the concentration of the dissolved ion, is a weight coefficient of the rate of change of the concentration of the dissolved ion, indicating the sensitivity of the dissolved ion to the concentration of the pollutants in the wastewater, is the number of types of dissolved ions.

5. The method for deep treatment of cold-rolling acidic wastewater according to claim 3, characterized in that, The reference values ​​for the rate of change of dissolved ion concentration and the reference values ​​for reactive molecules, after comprehensive analysis, are input into a pre-trained machine learning model. The machine learning model generates a coefficient for the change of hazardous substance concentration, and the current concentration of hazardous substances in the wastewater is intelligently assessed based on the coefficient for change of hazardous substance concentration to determine whether the concentration of hazardous substances in the wastewater exceeds the standard.

6. The method for deep treatment of cold-rolling acidic wastewater according to claim 5, characterized in that, The concentration change coefficient of hazardous substances generated by the pre-trained machine learning model when intelligently assessing the concentration of hazardous substances in the current wastewater is compared with a pre-set reference threshold for the concentration change coefficient of hazardous substances to determine whether the concentration of hazardous substances in the wastewater exceeds the standard. The judgment logic is as follows: If the coefficient of change of hazardous substance concentration is greater than the preset reference threshold for the coefficient of change of hazardous substance concentration, it is determined that the current concentration of hazardous substances in the wastewater exceeds the standard; if the coefficient of change of hazardous substance concentration is less than or equal to the preset reference threshold for the coefficient of change of hazardous substance concentration, it is determined that the current concentration of hazardous substances in the wastewater does not exceed the standard.

7. The method for deep treatment of cold-rolling acidic wastewater according to claim 6, characterized in that, When the concentration of harmful substances in wastewater exceeds the standard, the dosage of photocatalyst is dynamically adjusted based on pollutant concentration data to provide more active sites. Simultaneously, based on intelligent assessment results, the power and duration of the ultraviolet light source are dynamically adjusted to enhance the intensity of the photocatalytic reaction. The specific steps are as follows: When the concentration of harmful substances in wastewater exceeds the standard, the dosage of photocatalyst is increased to increase the number of active sites, thereby enhancing the degradation effect of pollutants in the wastewater. The dynamic adjustment calculation expression for the dosage of photocatalyst is as follows: In the formula, This is the adjusted photocatalyst dosage. This is the basic photocatalyst dosage. It is the incremental coefficient of the basic dosage. It is the coefficient of change of concentration of harmful substances. It is a reference threshold for the coefficient of change of concentration of harmful substances. It is the natural base; The power of the ultraviolet light source determines the energy input of the photocatalytic reaction. Adjusting the power of the ultraviolet light source can promote the generation of more free radicals on the catalyst surface and enhance the intensity of the photocatalytic reaction. The dynamic adjustment formula for the power of the ultraviolet light source is as follows: In the formula, This is the adjusted power of the ultraviolet light source. This is the basic ultraviolet light source power. It is the adjustment coefficient; Increasing the duration of illumination provides more time for the reaction, ensuring that harmful substances in the wastewater react fully. By extending the illumination duration, the reaction time between pollutants and free radicals generated by the catalyst is increased, thereby effectively improving the reaction efficiency. The dynamic adjustment formula for illumination duration is as follows: In the formula, This is the adjusted duration of illumination. This is the basic duration of illumination. It is the light duration adjustment coefficient.

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