Method and system for detecting specific pollutants in printing and dyeing tail water

Abstract

The invention relates to the technical field of water quality on-line monitoring, in particular to a printing and dyeing tail water specific pollutant detection method and system.The method comprises the following steps that optical signal attenuation of a to-be-detected tail water sample under at least two specific wavelengths is obtained, and the at least two specific wavelengths comprise measurement wavelengths, with absorption characteristics, of target soluble pollutants; and a non-absorption characteristic wavelength at which the target soluble contaminant is absorbed little or little; identifying and quantifying whether light scattering interference caused by a non-target substance exists in the tail water sample or not according to the relationship between the light signal attenuation under the measurement wavelength and the light signal attenuation under the non-absorption characteristic wavelength; calculating the measurement confidence of the measurement result according to the identification and quantification result of the light scattering interference; the light scattering interference caused by non-target substances is identified and quantified, and whether the pollutant concentration value is adopted or not is judged according to the measurement confidence, so that the reliability of detection data and the accuracy of wastewater treatment decision making are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of online monitoring of water quality, and in particular to a printing and dyeing tail water characteristic pollutant detection method and system. BACKGROUND

[0002] In industrial production, especially in the textile printing and dyeing industry, in order to ensure that the wastewater meets environmental regulations, factories usually deploy automatic online detection systems to continuously monitor the concentration of characteristic pollutants in tail water. Existing systems are mostly designed based on the law of light absorption, and the concentration of target soluble pollutants is related to the degree of attenuation of light of a specific wavelength. After calibration, the system can reliably operate under the preset conditions of stable tail water composition and provide data support for wastewater treatment.

[0003] However, industrial production often adjusts the process due to market demand. For example, if a cotton / polyester blended fabric order suddenly arises in a cotton fabric active dyeing enterprise, the "one-bath" dyeing process needs to add active dyes and disperse dyes to the same dye vat, resulting in significant changes in the composition of the tail water. Disperse dyes will form fine colloidal particles or micro-suspensions of tens to hundreds of nanometers in the tail water due to their insolubility. The original detection system design does not take this situation into account. When the tail water containing such colloidal particles flows through the detection system, "light scattering" phenomenon occurs. The system originally assumes that the light intensity attenuation is only caused by the light absorption of the target soluble pollutants, but its calculation and calibration logic cannot distinguish between light absorption and light scattering caused by light intensity loss, which will misjudge the light intensity attenuation caused by scattering as an increase in the concentration of target pollutants, and then output an overestimated concentration data. Based on this data, operators will increase the dosage of coagulants, decolorizing agents, and other chemicals, but the situation of rising chemical consumption and operating costs without improving water quality may occur (possibly due to excessive coagulation of particles or excessive chemicals producing undesirable by-products). The factory usually first checks the conventional links such as treatment process and reagent efficiency, and finally suspects the online detection system.

[0004] Therefore, the existing industrial wastewater online detection system based on the principle of light absorption cannot cope with the light scattering interference caused by fine colloidal particles in the tail water due to changes in production processes such as "one-bath" dyeing process, and may misattribute the light intensity attenuation caused by scattering to an increase in the concentration of target pollutants, output inaccurate data, and thus lead to errors in wastewater treatment decisions (such as excessive chemical dosage), resulting in increased costs, poor water quality improvement, and other problems. Therefore, technical improvements are needed for such detection systems.

[0005] In view of the above problems, the existing technology needs to be improved. SUMMARY

[0006] The present application aims to solve the problems in the prior art and provides a printing and dyeing tail water characteristic pollutant detection method and system.

[0007] In a first aspect, the present application provides a method for detecting characteristic pollutants in printing and dyeing tail water, comprising the following steps: obtaining the light signal attenuation of the tail water sample to be detected at at least two specific wavelengths, wherein the at least two specific wavelengths include a measurement wavelength at which a target dissolved pollutant has an absorption characteristic, and a non-absorption characteristic wavelength at which the target dissolved pollutant has little or almost no absorption; identifying and quantifying whether there is light scattering interference caused by non-target substances in the tail water sample according to the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength; calculating a measurement confidence of the measurement result according to the identification and quantification result of the light scattering interference; outputting the measurement confidence together with the pollutant concentration value; judging whether to adopt the pollutant concentration value to adjust the treatment parameters according to the output measurement confidence; when the measurement confidence is lower than a preset threshold, issuing an abnormal state prompt to an operator, and the prompt information indicates that there is light scattering interference.

[0008] In a second aspect, a system for detecting characteristic pollutants in printing and dyeing tail water is provided, comprising: a signal acquisition module, configured to obtain the light signal attenuation of the tail water sample to be detected at at least two specific wavelengths, wherein the at least two specific wavelengths include a measurement wavelength at which a target dissolved pollutant has an absorption characteristic, and a non-absorption characteristic wavelength at which the target dissolved pollutant has little or almost no absorption; an interference analysis module, configured to identify and quantify whether there is light scattering interference caused by non-target substances in the tail water sample according to the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength; a confidence calculation module, configured to calculate a measurement confidence of the measurement result according to the identification and quantification result of the light scattering interference; an output module, configured to output the measurement confidence together with the pollutant concentration value; a decision judgment module, configured to judge whether to adopt the pollutant concentration value to adjust the treatment parameters according to the output measurement confidence; and a prompt module, configured to issue an abnormal state prompt to an operator when the measurement confidence is lower than a preset threshold, and the prompt information indicates that there is light scattering interference.

[0009] Compared with the prior art, the present application has the following beneficial effects: By identifying and quantifying light scattering interference caused by non-target substances, and determining whether to adopt pollutant concentration values ​​based on measurement confidence levels, this method effectively solves the problems in existing technologies where light scattering interference leads to inaccurate measurement results, resulting in excessive addition of treatment agents, increased operating costs, and poor treatment effects. It significantly improves the reliability of detection data and the accuracy of wastewater treatment decisions. Attached Figure Description

[0010] Figure 1 This is a flowchart of the method of the present invention.

[0011] Figure 2 This is a schematic diagram of the system structure of the present invention.

[0012] In the diagram: 201, Signal Acquisition Module; 202, Interference Analysis Module; 203, Confidence Calculation Module; 204, Output Module; 205, Decision Judgment Module; 206, Prompt Module. Detailed Implementation

[0013] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of the present invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0014] Traditional online optical monitoring systems for dyeing and printing wastewater have a problem in calculating the actual concentration of target dissolved pollutants when dealing with non-target substances introduced temporarily from upstream processes that can cause light scattering. This issue stems from the system's interpretation of light signal attenuation, attributing all light attenuation to absorption by the target substance while neglecting the light scattering effects caused by non-target substances. This leads to discrepancies between the system's output concentration data and the actual situation, impacting subsequent wastewater treatment decisions.

[0015] Therefore, this application is as follows Figure 1 The method for detecting characteristic pollutants in dyeing and printing wastewater includes the following steps: S101. Obtain the optical signal attenuation of the tailwater sample to be tested at at least two specific wavelengths, including the measurement wavelength in which the target dissolved pollutant has absorption characteristics, and the non-absorption characteristic wavelength in which the target dissolved pollutant absorbs very little or almost no absorption. In the method, obtaining the light signal attenuation of the tail water sample at at least two specific wavelengths refers to measuring the degree of intensity reduction of light after passing through the tail water sample by an optical detection device. This can be expressed in the form of the logarithm of the ratio of transmitted light intensity to incident light intensity, such as absorbance value. This process can be achieved using a variety of light source and detector combinations, such as using different wavelengths of light-emitting diodes, lasers or wide-spectrum light sources equipped with filters, combined with photodiodes or photomultiplier tubes for light signal reception, which is mainly to provide the basic optical data required for subsequent analysis to distinguish the effects of different substances on the light signal. Among them, the specific wavelengths include the measurement wavelengths of the target dissolved pollutants with absorption characteristics, and the non-absorption characteristic wavelengths with little or almost no absorption of the target dissolved pollutants. The measurement wavelength refers to the wavelength region where the target dissolved pollutants (such as specific dye molecules) can strongly absorb light energy, which can be selected according to the spectral absorption characteristics of the target pollutants, such as the wavelength corresponding to the maximum absorption peak. The non-absorption characteristic wavelength refers to a wavelength at which the target dissolved pollutants have little or almost no absorption of light energy, but which is sensitive to light scattering effects caused by non-target substances (such as colloidal particles). The purpose of selecting these two wavelengths is to simultaneously obtain target pollutant absorption information and non-target substance scattering interference information in the same measurement system, providing a basis for distinguishing and quantifying the interference for subsequent decision-making.

[0016] S102, identifying and quantifying whether there is light scattering interference caused by non-target substances in the tail water sample according to the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength; This refers to determining whether there is light scattering phenomenon caused by non-target substances (such as suspended particles, colloids) in the tail water and determining its influence degree by comparing or calculating the ratio, difference or specific function relationship of the light signal attenuation at the two wavelengths. This process can use pre-established optical response models, calibration curves or empirical thresholds for judgment, which is to separate the non-absorbing part caused by scattering from the total light signal attenuation, so as to more accurately evaluate the true absorption contribution of the target pollutant.

[0017] S103, calculating the measurement confidence of the measurement result according to the identification and quantification results of the light scattering interference; This refers to evaluating the reliability or accuracy of the current pollutant concentration measurement result based on the identified and quantified light scattering interference degree. The measurement confidence can be a percentage value, a score or a level, and its calculation method can use a pre-set function relationship, lookup table or machine learning model, which is to quantify the degree of influence of the measurement result by interference, providing a reliability basis for subsequent decision-making.

[0018] S104, output the measurement confidence together with the pollutant concentration value; This refers to the detection system not only provides traditional pollutant concentration data, but also provides an index reflecting the reliability of the concentration data at the same time. This output can be realized through various industrial communication protocols, such as analog signals (such as 4-20mA current signals), digital communication protocols (such as Modbus TCP / IP, Profibus), the purpose is to provide more comprehensive information to the receiver (such as automation control system or operator), so that it can make intelligent decisions according to the reliability of the data.

[0019] S105, according to the output measurement confidence, judge whether to adopt the pollutant concentration value to adjust the treatment parameter; This refers to the downstream wastewater treatment control system or operator, after receiving the pollutant concentration value and the measurement confidence, according to the height of the confidence, to decide whether to adjust the related parameters (such as chemical agent dosage, pump speed, etc.) in the wastewater treatment process according to the current concentration value. The judgment can be based on the pre-set reliability threshold, the purpose is to avoid blindly adjusting the treatment parameters when the measurement result is unreliable, so as to cause waste of resources or poor treatment effect.

[0020] S106, when the measurement confidence is lower than the pre-set threshold, send an abnormal state prompt to the operator, the prompt information indicates that there is light scattering interference.

[0021] This refers to when the reliability of the measurement result is lower than the acceptable level, the system will actively send alarm information to the artificial operation interface or monitoring system. The pre-set threshold can be set according to the actual application scene and risk tolerance, the prompt information will clearly point out that the reason for the abnormality is light scattering interference, the purpose is to remind the operator to pay attention to the measurement anomaly in time, and provide preliminary diagnosis information, so that the operator can targetedly investigate and intervene, avoid invalid fault diagnosis.

[0022] The core innovation of the present application is that by combining the measurement wavelength of the target dissolved pollutant with the absorption characteristics and the non-absorption characteristic wavelength of the target dissolved pollutant with little or almost no absorption, and based on the light signal attenuation relationship of the two wavelengths, the light scattering interference is recognized and quantified, so as to calculate the measurement confidence of the measurement result, and guide the adjustment of the downstream treatment parameter and the abnormal prompt with the confidence, which effectively avoids the light scattering interference caused by non-target substances leading to false high of the measurement result, and then misleads the effect of wastewater treatment operation.

[0023] Firstly, the system acquires the light signal attenuation of the tail water sample at at least two specific wavelengths. This includes a measurement wavelength, which is characteristic of the target soluble pollutant, for reflecting the concentration of the target pollutant; and a non-absorption characteristic wavelength, which is little or almost not absorbed by the target soluble pollutant, but sensitive to light scattering caused by non-target substances. It is precisely due to the difference in wavelength selection that the system can preliminarily distinguish the part contributed by the absorption of the target pollutant and the part contributed by the scattering of non-target substances from the total light signal attenuation. On this basis, the system identifies and quantifies whether there is light scattering interference caused by non-target substances in the tail water sample according to the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength. This relationship analysis, such as comparing the absorbance ratio or difference at the two wavelengths, can reveal that when non-target substances exist, the light attenuation at the non-absorption characteristic wavelength will abnormally increase, thus explicitly indicating and quantifying the intensity of scattering interference. It is through this accurate identification and quantification of scattering interference that the system can overcome the limitations of traditional detection which only focuses on total attenuation. Further, the system calculates the measurement confidence of the measurement result according to the identification and quantification results of the light scattering interference. This means that the more serious the scattering interference, the lower the reliability of the measurement result, and the lower the confidence score. The introduction of this confidence makes the detection system change from a simple measurement tool to an intelligent unit with self-evaluation capability, which can "honestly" report the reliability of its measurement results. Subsequently, the system outputs the measurement confidence together with the pollutant concentration value. This dual output mechanism ensures that the downstream wastewater treatment control system or operator receives the reliability evaluation of the pollutant concentration data when receiving the pollutant concentration data. This avoids blind decision-making by the downstream system without knowing the data quality. In view of this, the downstream system determines whether to adopt the pollutant concentration value to adjust the treatment parameters according to the output measurement confidence. When the confidence is high, it means that the measurement result is reliable, and the concentration value can be used for automatic adjustment of the treatment parameters; when the confidence is low, it means that the measurement result may be interfered, and the system will actively avoid using the concentration value for automatic adjustment, thereby avoiding resource waste and treatment effect decline caused by false data. Finally, when the measurement confidence is lower than a preset threshold, the system will send an abnormal state prompt to the operator, which explicitly indicates that there is light scattering interference. This accurate abnormal prompt can guide the operator to quickly locate the problem source, avoid wasting time and resources on ineffective troubleshooting, and thus improve the efficiency of fault diagnosis and the stability of the processing flow. Through the above cooperative work, the scheme can effectively cope with the challenges brought by the complex components of printing and dyeing tail water, and ensure the economy and environmental compliance of wastewater treatment.

[0024] As an embodiment of the present application, after the step of calculating the measurement confidence of the measurement result according to the identification and quantification results of the light scattering interference, the method further comprises: After receiving the measurement confidence, the downstream wastewater treatment control system acquires the time series data of the measurement confidence within a preset time window; According to the time series data, the number of times that the measurement confidence crosses a preset reliability limit within the preset time window is calculated; According to the number of crossings, the stability of the measurement confidence signal is judged; According to the stability judgment result, the adoption strategy for the pollutant concentration value is adjusted.

[0025] The downstream wastewater treatment control system refers to an automatic control unit responsible for receiving and processing data from the detection system, and its purpose is to adjust parameters in the wastewater treatment process according to the received information, such as controlling the dosage of chemical agents or the operating state of the treatment equipment. The preset time window refers to a continuous period of time for collecting and analyzing the time series data of the measurement confidence, and its purpose is to provide sufficient data samples for evaluating the dynamic behavior of the measurement confidence signal. The time series data refers to a sequence of measurement confidence values recorded in chronological order within the preset time window, and its purpose is to reflect the trend and fluctuation of the measurement confidence over time. The preset reliability limit refers to a threshold value used to distinguish between reliable and unreliable states of the measurement confidence signal, and its purpose is to serve as a basis for determining whether the measurement confidence has reached an adoptable level. The number of crossings refers to the total number of times that the measurement confidence value changes from below the preset reliability limit to above the limit, or from above the limit to below the limit within the preset time window, and its purpose is to quantify the frequency and instability of the measurement confidence signal. The stability judgment result refers to the evaluation conclusion made according to the number of crossings of the measurement confidence signal, and its purpose is to provide a decision basis for the downstream wastewater treatment control system to adjust the adoption strategy. The adoption strategy refers to the different handling methods adopted by the downstream wastewater treatment control system for the pollutant concentration value according to the stability judgment result of the measurement confidence signal, and its purpose is to avoid misoperation based on unstable or unreliable data, thereby ensuring the stability and economy of wastewater treatment.

[0026] The scheme of the present application can further obtain the time series data of the measurement confidence within a preset time window after receiving the measurement confidence, instead of relying only on the instantaneous confidence value for judgment. Based on these time series data, the system can calculate the number of times the measurement confidence crosses the preset reliability limit within the preset time window. This calculation of the number of crossings can quantify the frequency of switching between reliable and unreliable states of the measurement confidence signal, thereby reflecting its inherent volatility. Subsequently, the system judges the stability of the measurement confidence signal according to the calculated number of crossings. If the number of crossings is frequent, it indicates that the signal is unstable; otherwise, it indicates that the signal is stable. Finally, according to the stability judgment result, the system can intelligently adjust the adoption strategy of the pollutant concentration value. This operating mechanism enables the present scheme to effectively compensate for the shortcomings of relying only on a single instantaneous measurement confidence for judgment. Although the previous scheme can output the measurement confidence to indicate the reliability of the measurement result, it may still lead to frequent and irregular adjustments of the adoption strategy of the pollutant concentration value by the downstream control system when the measurement confidence itself appears frequent fluctuations and temporarily crosses the reliability limit, thereby affecting the stability of the wastewater treatment. The present scheme introduces dynamic evaluation of the stability of the measurement confidence signal, enabling the downstream control system to identify and avoid the misjudgment risk caused by the fluctuation of the confidence signal itself. When the confidence signal is unstable, even if its instantaneous value temporarily crosses the reliability limit, the system can identify this instability through analysis of historical data and adopt a more conservative adoption strategy, such as maintaining the current treatment parameters, thereby avoiding false operation and resource waste caused by false reliable signals. This in-depth understanding and intelligent response to the "behavior pattern" of the measurement confidence signal make the decision-making of the entire wastewater treatment process more stable, significantly improving the reliability and operating efficiency of the system.

[0027] As an embodiment of the present application, when receiving state information indicating that the upstream production process introduces non-target substances with absorption characteristics, the step of calculating the measurement confidence of the measurement result according to the identification and quantification results of the light scattering interference includes: obtaining the light signal attenuation of the tail water sample at another specific wavelength, which is a wavelength at which the non-target substances with absorption characteristics have absorption characteristics and the target dissolved pollutants have little or almost no absorption; determining the light absorption contribution of the non-target substances with absorption characteristics at the non-absorption characteristic wavelength according to the relationship between the light signal attenuation at the non-absorption characteristic wavelength and the light signal attenuation at the other specific wavelength; correcting the light signal attenuation at the non-absorption characteristic wavelength according to the light absorption contribution, thereby obtaining the corrected light scattering interference; calculating the measurement confidence of the measurement result according to the corrected light scattering interference.

[0028] wherein receiving state information indicating that the upstream production process introduced a non-target substance with absorption characteristics means that the system perceives, by some means, that a non-target substance that absorbs light can have been introduced in the production process, and the purpose is to trigger subsequent correction logic. This state information can be a pre-defined status code obtained in real-time from the factory's manufacturing execution system (MES) or central programmable logic controller (PLC) through an industrial communication interface, such as Modbus TCP / IP protocol, or obtained by manual input, sensor detecting the presence of a specific chemical, etc. Another specific wavelength means an additional selected light wavelength other than the measurement wavelength and the non-absorption characteristic wavelength, and the purpose is to specifically quantify the light absorption effect of the non-target substance with absorption characteristics. When selecting this wavelength, it is necessary to ensure that the non-target substance has significant absorption characteristics at this wavelength, while the target dissolved contaminant has little or almost no absorption at this wavelength, so that the absorption contributions of different substances can be effectively distinguished. Determining the light absorption contribution of the non-target substance with absorption characteristics at the non-absorption characteristic wavelength means quantifying the actual contribution of the non-target substance to the light signal attenuation at the non-absorption characteristic wavelength by analyzing a specific relationship between the light signal attenuation at the non-absorption characteristic wavelength and the light signal attenuation at another specific wavelength. This relationship can be established in advance through experiments, such as establishing a calibration curve or mathematical model to map the absorption at another specific wavelength to the absorption contribution at the non-absorption characteristic wavelength, and the purpose is to accurately isolate the absorption effect of the non-target substance. Light absorption contribution means the amount of light signal attenuation caused by the non-target substance with absorption characteristics at the non-absorption characteristic wavelength, and the purpose is to serve as a basis for correcting the light scattering interference. The corrected light scattering interference means the amount of attenuation caused purely by light scattering after deducting the light absorption contribution of the non-target substance with absorption characteristics from the light signal attenuation at the non-absorption characteristic wavelength, and the purpose is to provide a more accurate evaluation of light scattering interference, thereby improving the accuracy of measurement confidence calculation.

[0029] Specifically, in the conventional operation, the system identifies and quantifies the light scattering interference caused by non-target substances in the tail water sample according to the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength, and calculates the measurement confidence of the measurement result. However, when the upstream production process introduces non-target substances with absorption characteristics, the original light signal attenuation at the non-absorption characteristic wavelength will contain both light scattering interference and absorption of non-target substances, resulting in inaccurate quantification of light scattering interference, and affecting the reliability of the measurement confidence. In response to this, the present scheme will start a correction process when receiving state information indicating that the upstream production process introduces non-target substances with absorption characteristics. First, the system will obtain the light signal attenuation of the tail water sample at another specific wavelength. This specific wavelength is selected to specifically capture the absorption characteristics of non-target substances with absorption characteristics, while ensuring that the target dissolved pollutants have little or almost no absorption at this wavelength, so as to avoid the interference of the target pollutants on the new wavelength signal. Subsequently, the system will determine the light absorption contribution of the non-target substances with absorption characteristics at the non-absorption characteristic wavelength according to the relationship between the original light signal attenuation at the non-absorption characteristic wavelength and the newly obtained light signal attenuation at the other specific wavelength. This process takes advantage of the difference in absorption characteristics of substances at different wavelengths, and through the established specific relationship model, the specific contribution of non-target substances to light signal attenuation at the non-absorption characteristic wavelength can be accurately calculated. Further, according to this light absorption contribution, the system will correct the original light signal attenuation at the non-absorption characteristic wavelength. By deducting the absorption contribution of non-target substances from the total attenuation, a more pure and accurate corrected light scattering interference can be obtained. This corrected value excludes the confusion caused by the absorption of non-target substances, making the quantification of light scattering interference more accurate. Finally, the system will recalculate the measurement confidence of the measurement result according to the corrected light scattering interference. By using a more accurate light scattering interference, it can ensure that the measurement confidence can truly reflect the reliability of the current measurement result, even in the presence of non-target substances with absorption characteristics, and avoid inaccurate confidence calculation due to misjudgment of the degree of light scattering. This scheme, combined with the basic detection method, makes the system more adaptable and robust when facing complex and variable printing tail water components. It not only can identify and quantify the conventional light scattering interference, but also can intelligently correct the interference quantification when specific absorption non-target substances appear, so as to ensure that the measurement confidence is always a reliable evaluation index. This avoids the distortion of the measurement confidence due to inaccurate quantification of light scattering interference in complex working conditions, and affects the accuracy of the downstream wastewater treatment decision, thereby ensuring the stability and economy of the entire wastewater treatment process.

[0030] As an embodiment of the present application, the step of identifying and quantifying the presence of light scattering interference caused by non-target substances in the effluent sample based on the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorbing characteristic wavelength comprises: obtaining the light signal attenuation at at least one additional wavelength for the effluent sample, the additional wavelength being a wavelength at which the target dissolved contaminant absorbs little or not at all and at which the non-target substances have a different light scattering response than at the non-absorbing characteristic wavelength; determining the physical properties of the non-target substances based on the relationship between the light signal attenuation at the non-absorbing characteristic wavelength and the light signal attenuation at the at least one additional wavelength; adjusting the criteria for determining the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorbing characteristic wavelength based on the physical properties of the non-target substances; identifying and quantifying the presence of light scattering interference caused by non-target substances in the effluent sample based on the adjusted criteria and the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorbing characteristic wavelength.

[0031] wherein the additional wavelength refers to a wavelength that is introduced in addition to the measurement wavelength and the non-absorbing characteristic wavelength. It is selected to capture the difference in scattering behavior of the non-target substances at different wavelengths, thereby providing more information about the scattering behavior of the non-target substances, under the premise that the target dissolved contaminant absorbs little or not at all. It can be implemented by selecting a wavelength that is spectrally spaced from the non-absorbing characteristic wavelength and at which the non-target substances exhibit different scattering intensities or scattering patterns. The physical properties of the non-target substances refer to inherent attributes that affect the light scattering behavior of the non-target substances, such as their particle size, shape, refractive index, or chemical composition. They can be determined by analyzing the optical response characteristics such as the ratio of light signal attenuation at different wavelengths, the shape of the spectral curve, or the scattering angle distribution, and combining them with a pre-established model or database of physical properties and optical responses. The criteria refer to the standards or models used to evaluate the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorbing characteristic wavelength to identify and quantify the light scattering interference. They can be dynamically adjusted using mathematical models, lookup tables, or machine learning algorithms based on the physical properties of the non-target substances, for example, adjusting the scattering coefficient or calibration curve based on particle size.

[0032] The scheme of the present application enhances the perception of the light scattering characteristics of non-target substances by introducing the acquisition of the amount of light signal attenuation of the tail water sample at at least one additional wavelength. The additional wavelength is selected to be poorly or almost not absorbed by the target dissolved pollutants, and the light scattering response of the non-target substances differs from that at the non-absorption characteristic wavelength. In this way, the system can obtain more abundant optical information than using only the measurement wavelength and the non-absorption characteristic wavelength, especially about the differences in scattering behavior of non-target substances at different wavelengths. On this basis, the system further determines the physical characteristics of the non-target substances according to the relationship between the amount of light signal attenuation at the non-absorption characteristic wavelength and the amount of light signal attenuation at at least one additional wavelength. This is because the scattering response patterns of non-target substances with different physical characteristics at different wavelengths are unique. By analyzing the attenuation relationship between these wavelengths, the system can infer the key physical properties of the non-target substances in the current tail water, such as particle size, shape or refractive index. Subsequently, the system dynamically adjusts the judgment basis for the relationship between the amount of light signal attenuation at the measurement wavelength and the amount of light signal attenuation at the non-absorption characteristic wavelength according to the determined physical characteristics of the non-target substances. This adjustment is crucial, as it enables the system to optimize its recognition logic for light scattering interference according to the type of non-target substance actually present and its scattering characteristics, avoiding the bias that can result from using a single fixed judgment standard. For example, if the non-target substance is identified as a certain particle size of colloids, the system can load a more accurate judgment model for scattering characteristics of that particle size. Finally, the system identifies and quantifies whether there is light scattering interference caused by non-target substances in the tail water sample according to the adjusted judgment basis and the relationship between the amount of light signal attenuation at the measurement wavelength and the amount of light signal attenuation at the non-absorption characteristic wavelength. This identification and quantification process calibrated by physical characteristics significantly improves the accuracy of light scattering interference judgment. Through the above scheme, the present application further refines the interference recognition mechanism on the basis of the original recognition of light scattering interference according to the measurement wavelength and the non-absorption characteristic wavelength. When the light scattering response of the non-target substance is close to the non-absorption characteristic wavelength, making it difficult for the original method to accurately distinguish, the introduction of the additional wavelength and the dynamic adjustment of the judgment basis according to the physical characteristics of the non-target substance enable the system to more accurately strip the influence of light scattering interference. This more accurate interference recognition and quantification result can directly improve the reliability of subsequent measurement confidence calculation, and thus ensure the effectiveness of pollutant concentration value adoption judgment and processing parameter adjustment based on the confidence, avoiding incorrect decisions due to inaccurate interference recognition, thereby making the entire detection method of characteristic pollutants in dyeing tail water more adaptable and robust in complex and variable working conditions.

[0033] As an embodiment of the present application, the step of determining the physical characteristics of the non-target substances according to the relationship between the amount of light signal attenuation at the non-absorption characteristic wavelength and the amount of light signal attenuation at at least one additional wavelength comprises: obtaining a specific relationship between the light signal attenuation at the non-absorption characteristic wavelength and the light signal attenuation at the at least one additional wavelength of a plurality of non-target substances with different physical properties in advance, and establishing an optical response characteristic library of the specific relationship; comparing the current relationship between the light signal attenuation at the non-absorption characteristic wavelength and the light signal attenuation at the at least one additional wavelength of the tail water sample with the optical response characteristic library; According to the comparison result, the physical properties of the non-target substance corresponding to the specific relationship that best matches the current relationship are identified and determined as the physical properties of the non-target substance.

[0034] The optical response characteristic library refers to a set of specific relationships between the light signal attenuation at the non-absorption characteristic wavelength and the light signal attenuation at the at least one additional wavelength of a plurality of non-target substances with different physical properties, which can be a pre-established database, a lookup table or a multidimensional array, and its purpose is to provide a reference standard for subsequent identification of the physical properties of the non-target substance. The comparison refers to comparing the current relationship between the light signal attenuation at the non-absorption characteristic wavelength and the light signal attenuation at the at least one additional wavelength of the tail water sample with the specific relationship stored in the optical response characteristic library, which can be implemented by similarity calculation, pattern recognition algorithm or rule-based matching logic, and its purpose is to determine which known substance is closest to the optical response of the non-target substance in the current tail water sample. The identification and determination refer to finding the specific relationship that best matches the current relationship from the optical response characteristic library according to the comparison result, and obtaining the physical properties of the non-target substance corresponding to the specific relationship, which can be achieved by finding the data entry with the highest similarity or by the output result of the classifier, and its purpose is to accurately obtain the physical properties of the non-target substance in the tail water, and to provide accurate input for subsequent quantification of light scattering interference.

[0035] Specifically, first, specific relationships between the light signal attenuation at the non-absorption characteristic wavelength and the light signal attenuation at at least one additional wavelength of a plurality of non-target substances with different physical characteristics are obtained in advance, and an optical response characteristic library of these specific relationships is established. This step is the key to building an accurate identification basis, because the physical characteristics of different non-target substances, such as particle size, shape or refractive index, determine their light scattering and absorption behavior at different wavelength combinations, thereby forming a unique optical "fingerprint". By measuring and storing these "fingerprints" in advance, the system has a comprehensive reference system. On this basis, the current relationship between the light signal attenuation at the non-absorption characteristic wavelength and the light signal attenuation at at least one additional wavelength of the tail water sample is compared with the optical response characteristic library. This comparison process is the core step to achieve accurate identification, which allows the system to match the real-time measured optical response of the tail water sample with the "fingerprint" of the known non-target substance, thereby determining the type of non-target substance in the tail water. Finally, according to the comparison result, the physical characteristics of the non-target substance corresponding to the specific relationship that best matches the current relationship are identified and determined as the physical characteristics of the non-target substance in the tail water sample. In this way, instead of relying on a simplified single function model, the present scheme uses multi-dimensional optical response characteristics for pattern matching, significantly improving the accuracy of determining the physical characteristics of non-target substances. This accurate physical characteristic information further provides a more reliable basis for subsequent identification and quantification of the light scattering interference caused by non-target substances in the tail water sample. For example, when the physical characteristics of the non-target substance are accurately determined, the system can adjust the judgment basis of the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength, thereby more accurately identifying and quantifying the light scattering interference, avoiding the deviation of the interference quantification caused by inaccurate physical characteristics judgment, and thereby improving the overall accuracy of the detection of the characteristic pollutants in the printing and dyeing tail water.

[0036] As an embodiment of the present application, the step of adjusting the judgment basis of the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength according to the physical characteristics of the non-target substance comprises: pre-establishing the association information between the physical characteristics of the non-target substance and the judgment basis of the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength; According to the physical characteristics of the non-target substance, the adjusted judgment basis of the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength is obtained from the association information.

[0037] The judgment basis refers to a standard or rule for identifying and quantifying light scattering interference, and can be a ratio threshold, a difference threshold between light signal attenuation amounts, or a classification model based on a multi-wavelength attenuation mode, and aims to distinguish the influence of target substance absorption and non-target substance scattering according to light signal characteristics; the association information refers to a data set that pre-stores physical characteristics of different non-target substances and corresponding judgment basis, which can be in the form of a lookup table, a database, or a machine learning model, and aims to provide a knowledge base for the system to dynamically select appropriate judgment standards according to non-target substance types.

[0038] The scheme of the present application establishes the association information between the judgment basis of the relationship between the physical characteristics of non-target substances and the light signal attenuation amount in advance, so that the system can store and manage specific judgment standards corresponding to different non-target substance types. The establishment of such association information, for example through experimental calibration or historical data analysis, maps the light scattering characteristics of various non-target substances (such as colloidal particles of different particle sizes, shapes or compositions) and the judgment basis (such as a specific attenuation ratio threshold or attenuation mode) required to identify their scattering interference. It is precisely due to this pre-knowledge reserve that when the system determines the physical characteristics of the non-target substance in the current tail water sample according to the relationship between the light signal attenuation amount at the non-absorption characteristic wavelength and the light signal attenuation amount at at least one additional wavelength, it can accurately obtain the adjusted judgment basis matching the current non-target substance type from the pre-established association information using these known physical characteristics. This mechanism of dynamically obtaining and applying judgment basis makes the system no longer rely on a single fixed judgment standard, but can automatically switch to the most suitable strategy for identifying and quantifying light scattering interference according to the actual detected non-target substance type. In this way, the system can more accurately separate the light scattering interference caused by non-target substances from the total light signal attenuation, thereby providing a more reliable basis for subsequent target dissolved pollutant concentration calculation.

[0039] As an embodiment of the present application, according to the output measurement confidence, the step of determining whether to adopt the pollutant concentration value to adjust the treatment parameter includes: comparing the output measurement confidence with a preset reliability limit; According to the comparison result, if the measurement confidence is higher than the reliability limit, the pollutant concentration value is adopted to adjust the treatment parameter; According to the comparison result, if the measurement confidence is not higher than the reliability limit, the pollutant concentration value is not adopted to adjust the treatment parameter.

[0040] The measurement confidence refers to a quantitative evaluation of the reliability of the current pollutant concentration measurement result, which can be expressed in the form of percentage, score or grade, etc. The preset reliability limit refers to a preset numerical value or range, which is used to determine whether the measurement confidence reaches the minimum standard of reliability, which can be realized by fixed numerical value, threshold value based on expert experience or critical point determined by system calibration. The pollutant concentration value is adopted to adjust the treatment parameter refers to taking the current measured pollutant concentration data as an effective basis for modifying the relevant control variables in the wastewater treatment process. The pollutant concentration value is not adopted to adjust the treatment parameter refers to not taking the measured pollutant concentration data as a direct basis to modify the wastewater treatment parameters under the current circumstances.

[0041] The scheme can make the wastewater treatment process more reasonably respond to the online detection data by introducing an intelligent judgment mechanism for measurement confidence. In the detection of printing and dyeing tail water, the system first obtains the light signal attenuation of the tail water sample to be detected at the measurement wavelength and the non-absorption characteristic wavelength. Based on the relationship between the light signal attenuation at the two wavelengths, the system can identify and quantify whether there is light scattering interference caused by non-target substances in the tail water sample. Subsequently, according to the identification and quantification results of the light scattering interference, the system calculates the measurement confidence of the measurement results, and outputs the confidence together with the pollutant concentration value. On this basis, the scheme further refines how to use this measurement confidence to guide the actual wastewater treatment process. Specifically, the system compares the output measurement confidence with a preset reliability limit. The reliability limit is the minimum requirement set by the system for the reliability of the measurement results. Through this comparison, the system can determine whether the current measurement results are reliable enough to provide a clear basis for subsequent decision-making. According to the comparison result, if the measurement confidence is higher than the preset reliability limit, it means that the current measurement results are reliable and can be used as the basis for adjusting the treatment parameters. At this time, the system will adopt the pollutant concentration value and adjust the wastewater treatment parameters, such as increasing or decreasing the dosage of chemical agents, to achieve optimal control of the wastewater treatment process. On the contrary, if the measurement confidence is not higher than the preset reliability limit, it means that the current measurement results may be interfered and should not be directly used to adjust the treatment parameters, otherwise it may lead to treatment failure. In this case, the system will not adopt the pollutant concentration value to adjust the treatment parameters, but maintain the current dosage of chemical agents or keep the treatment parameters unchanged. This strategy can effectively avoid making decisions based on false information, thereby ensuring the stability of the wastewater treatment process. This mechanism is a beneficial combination with the previous scheme of only outputting confidence. The previous scheme provides an evaluation of data reliability, while the present scheme provides a specific path for intelligent decision-making based on this evaluation. Due to the hierarchical judgment and differentiated processing strategy of the measurement confidence, the entire wastewater treatment system can avoid blindly adopting unreliable concentration values when facing complex and variable tail water components, thereby ensuring the effectiveness of wastewater treatment while effectively avoiding resource waste and environmental risks caused by measurement errors.

[0042] As an embodiment of the present application, the determination method of the preset reliability limit includes: obtaining the type information or the concentration range information of the target dissolved pollutant in the current tail water; pre-establishing the association information between the type or the concentration range of the target dissolved pollutant and the corresponding reliability limit; According to the type information or the concentration range information, the matching reliability limit is obtained from the association information as the preset reliability limit.

[0043] The association information refers to a data set or a logical rule that is pre-established to describe the correspondence between the type of the target dissolved pollutant or the concentration range thereof and the corresponding reliability limit. It can be implemented in the form of a database table, a lookup table, a mapping function, or a machine learning model, and its purpose is to provide a basis for dynamically determining the reliability limit according to the actual situation.

[0044] Firstly, the system obtains the type information or the concentration range information of the target dissolved pollutant in the current tail water. This is because the influence degree of the measurement confidence on the subsequent processing parameter adjustment is different for different pollutant types or concentration ranges, so it is necessary to determine the reliability limit accordingly. For example, for a pollutant with high toxicity but low concentration, even if the measurement confidence decreases slightly, a stricter reliability limit may be needed to ensure the safety of the treatment; while for a pollutant with lower toxicity but high concentration, a slightly lower confidence may be allowed. On this basis, the system pre-establishes the association information between the type of the target dissolved pollutant or the concentration range thereof and the corresponding reliability limit. This association information can be a structured database, which stores the best reliability limit determined through experimental verification or expert experience under different pollutant types or concentration ranges. The establishment of this association information enables the system to quickly and automatically find and apply the most suitable reliability limit according to the actual changes in the tail water quality. Subsequently, the system retrieves and obtains the reliability limit that matches the current situation from the pre-established association information according to the obtained type information or concentration range information of the target dissolved pollutant in the current tail water, and uses it as the preset reliability limit for judgment. In this way, the system no longer relies on a fixed and unchanging reliability limit, but can adaptively adjust the judgment standard according to the dynamic characteristics of the tail water quality. It is precisely because of this mechanism of dynamically determining the reliability limit that when the output measurement confidence is compared with this adaptively adjusted reliability limit, the judgment result can more accurately reflect the true reliability of the current pollutant concentration value. When the measurement confidence is higher than this dynamically adjusted reliability limit, the system can more confidently adopt the pollutant concentration value to adjust the processing parameters, thereby ensuring the treatment effect; when the measurement confidence is not higher than this limit, the system can more cautiously not adopt the value to avoid resource waste or treatment failure caused by inaccurate data. This ability to dynamically adjust the reliability limit enables the entire detection and processing decision-making process to exhibit higher adaptability and robustness when facing complex and variable printing tail water quality, effectively avoiding the misjudgment that may be caused by a fixed limit, thereby improving the efficiency and economy of wastewater treatment.

[0045] As an embodiment of the present application, the step of identifying and quantifying the presence of light scattering interference caused by non-target substances in the tail water sample according to the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength comprises: comparing the light signal difference or the light signal ratio between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength; determining the presence of light scattering interference and calculating its value according to the light signal difference or the light signal ratio and the pre-set optical response characteristics or calibration data.

[0046] Wherein, the light signal difference refers to the numerical difference between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength, which can be obtained by direct subtraction. The light signal ratio refers to the ratio between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength, which can be obtained by division. The purpose is to establish a preliminary basis for judgment to reflect the degree of light scattering interference. Wherein, the pre-set optical response characteristics refer to the pre-determined regularity data of the light scattering or absorption behavior of different types of non-target substances (such as particles of different particle sizes and different refractive indices) at a specific wavelength, which can be obtained by experimental measurement, theoretical modeling or simulation analysis. The calibration data refers to the data set obtained by calibrating the system under controlled conditions using known concentrations of non-target substances or simulated interference substances, which can be determined by pre-calibration in laboratory conditions using known concentrations of target pollutants solution and different turbidity of colloidal particle suspension. The purpose is to provide an accurate reference benchmark to improve the accuracy of light scattering interference identification and quantification.

[0047] Specifically, the system first obtains the light signal attenuation of the tail water sample to be measured at the measurement wavelength and the non-absorption characteristic wavelength. Subsequently, it compares the light signal difference or the light signal ratio between the light signal attenuation at the two wavelengths. This comparison step establishes a preliminary judgment basis, because the attenuation at the measurement wavelength reflects the combined influence of the target dissolved pollutants and non-target substances, while the attenuation at the non-absorption characteristic wavelength mainly reflects the influence of non-target substances. Therefore, the difference or ratio between the two can preliminarily indicate the existence and approximate degree of light scattering interference. Further, based on this preliminary judgment, the present scheme introduces a basis for pre-set optical response characteristics or calibration data. This means that the system does not simply rely on a fixed threshold or ratio for judgment, but combines a pre-established data model reflecting the optical characteristics of different types of non-target substances. For example, these data can include the relationship between the light signal difference or ratio and the scattering intensity corresponding to particles of different sizes and different refractive indices. When the system calculates the current light signal difference or ratio, it compares or looks up with these pre-set data. It is precisely due to this judgment mechanism combined with prior knowledge that the system can more accurately determine whether light scattering interference exists and accurately calculate its value. This way can effectively distinguish different types of light scattering interference and reduce the influence of measurement error and environmental factors on the accuracy of identification and quantification. Through this refined identification and quantification process, the present scheme can provide more reliable input for subsequent measurement confidence calculation. When the light scattering interference is accurately identified and quantified, the system can more accurately assess the reliability of the current pollutant concentration measurement result, thereby avoiding misleading downstream wastewater treatment operations due to interference-induced false high concentration data. This makes the entire detection method provide more meaningful judgments when facing light scattering interference caused by non-target substances, thereby improving the overall accuracy and reliability of the detection of characteristic pollutants in dyeing tail water.

[0048] As shown in Figure 2 a system for detecting characteristic pollutants in dyeing tail water, the system comprises: a signal acquisition module 201, configured to obtain the light signal attenuation of the tail water sample to be measured at at least two specific wavelengths, the at least two specific wavelengths including a measurement wavelength at which the target dissolved pollutants have absorption characteristics, and a non-absorption characteristic wavelength at which the target dissolved pollutants absorb little or almost no light; an interference analysis module 202, configured to identify and quantify whether light scattering interference caused by non-target substances exists in the tail water sample according to the relationship between the light signal attenuation at the measurement wavelength and the light signal attenuation at the non-absorption characteristic wavelength; a confidence calculation module 203, configured to calculate the measurement confidence of the measurement result according to the identification and quantification result of the light scattering interference; The output module 204 is configured to output the measurement confidence together with the pollutant concentration value; The decision judgment module 205 is configured to judge whether to adopt the pollutant concentration value to adjust the processing parameter according to the output measurement confidence. The prompt module 206 is configured to issue an abnormal state prompt to the operator when the measurement confidence is lower than a preset threshold, and the prompt information indicates that there is light scattering interference.

[0049] The above shows and describes the basic principles, main features and advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above embodiments, and the above embodiments and descriptions are only the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application.

Claims

1. A method for detecting characteristic pollutants in dyeing and printing wastewater, characterized in that, The method includes the following steps: The optical signal attenuation of the tailwater sample to be tested is obtained at at least two specific wavelengths, wherein the at least two specific wavelengths include the measurement wavelength in which the target dissolved pollutant has absorption characteristics, and the non-absorption characteristic wavelength in which the target dissolved pollutant absorbs very little or almost no absorption. Based on the relationship between the light signal attenuation at the measured wavelength and the light signal attenuation at the non-absorption characteristic wavelength, the presence of light scattering interference caused by non-target substances in the tailwater sample is identified and quantified. Based on the identification and quantification results of light scattering interference, the measurement confidence level of the measurement results is calculated; The measurement confidence level and the pollutant concentration value are output together; Based on the output measurement confidence level, determine whether to adopt the pollutant concentration value to adjust the processing parameters; When the measurement confidence level is lower than a preset threshold, an abnormal status prompt is issued to the operator, indicating the presence of light scattering interference.

2. The method for detecting characteristic pollutants in dyeing and printing wastewater according to claim 1, characterized in that, After performing the step of calculating the measurement confidence level of the measurement result based on the identification and quantification results of light scattering interference, the method further includes: After receiving the measurement confidence level, the downstream wastewater treatment control system acquires the time-series data of the measurement confidence level within a preset time window; Based on the time series data, calculate the number of times the measurement confidence level crosses a preset reliability limit within the preset time window; The stability of the measured confidence signal is determined based on the number of crossings. Based on the stability assessment results, the strategy for adopting the pollutant concentration values ​​will be adjusted.

3. The method for detecting characteristic pollutants in dyeing and printing wastewater according to claim 1, characterized in that, When receiving state information indicating the introduction of a non-target substance with absorption characteristics into the upstream production process, the step of calculating the measurement confidence level of the measurement result based on the identification and quantification results of light scattering interference includes: The light signal attenuation of the tailwater sample at another specific wavelength is obtained. The other specific wavelength is the wavelength at which the non-target substance with absorption characteristics has absorption characteristics and the target dissolved pollutant absorbs very little or almost no absorption. Based on the relationship between the light signal attenuation at the non-absorption characteristic wavelength and the light signal attenuation at another specific wavelength, the light absorption contribution of the non-target substance with absorption properties at the non-absorption characteristic wavelength is determined. Based on the light absorption contribution, the attenuation of the optical signal at the non-absorption characteristic wavelength is corrected to obtain the corrected light scattering interference. The measurement confidence level of the measurement result is calculated based on the corrected light scattering interference.

4. The method for detecting characteristic pollutants in dyeing and printing wastewater according to claim 1, characterized in that, The step of identifying and quantifying whether there is light scattering interference caused by non-target substances in the tailwater sample based on the relationship between the light signal attenuation at the measured wavelength and the light signal attenuation at the non-absorption characteristic wavelength includes: The light signal attenuation of the tailwater sample at at least one additional wavelength is obtained. The additional wavelength is the wavelength in which the target dissolved pollutant absorbs very little or almost no light, and the light scattering response of the non-target substance differs from the non-absorption characteristic wavelength. The physical properties of the non-target substance are determined based on the relationship between the optical signal attenuation at the non-absorption characteristic wavelength and the optical signal attenuation at the at least one additional wavelength. The basis for determining the relationship between the optical signal attenuation at the measurement wavelength and the optical signal attenuation at the non-absorption characteristic wavelength is based on the physical properties of the non-target substance. Based on the adjusted judgment criteria and the relationship between the light signal attenuation at the measured wavelength and the light signal attenuation at the non-absorption characteristic wavelength, the presence of light scattering interference caused by non-target substances in the tailwater sample is identified and quantified.

5. The method for detecting characteristic pollutants in dyeing and printing wastewater according to claim 4, characterized in that, The step of determining the physical properties of the non-target substance based on the relationship between the optical signal attenuation at the non-absorption characteristic wavelength and the optical signal attenuation at the at least one additional wavelength includes: A specific relationship is obtained in advance between the optical signal attenuation of various non-target substances with different physical properties at the non-absorption characteristic wavelength and the optical signal attenuation at at least one additional wavelength, and an optical response feature library of the specific relationship is established. The current relationship between the optical signal attenuation of the tailwater sample at the non-absorption characteristic wavelength and the optical signal attenuation at the at least one additional wavelength is compared with the optical response feature library. Based on the comparison results, the physical properties of the non-target substance corresponding to the specific relationship that best matches the current relationship are identified and determined as the physical properties of the non-target substance.

6. The method for detecting characteristic pollutants in dyeing and printing wastewater according to claim 4, characterized in that, The step of determining the relationship between the optical signal attenuation at the measurement wavelength and the optical signal attenuation at the non-absorption characteristic wavelength based on the physical properties of the non-target substance includes: The correlation information between the physical properties of the non-target substance and the judgment criteria for the relationship between the attenuation of the optical signal at the measurement wavelength and the attenuation of the optical signal at the non-absorption characteristic wavelength is established in advance; Based on the physical properties of the non-target substance, the basis for determining the relationship between the optical signal attenuation at the adjusted measurement wavelength and the optical signal attenuation at the non-absorption characteristic wavelength is obtained from the associated information.

7. The method for detecting characteristic pollutants in dyeing and printing wastewater according to claim 1, characterized in that, The step of determining whether to adopt the pollutant concentration value to adjust the treatment parameters based on the output measurement confidence level includes: The measurement confidence level of the output is compared with a preset reliability limit; Based on the comparison results, if the measurement confidence level is higher than the reliability limit, the pollutant concentration value is adopted to adjust the processing parameters; Based on the comparison results, if the measurement confidence level is not higher than the reliability limit, the pollutant concentration value will not be adopted to adjust the treatment parameters.

8. The method for detecting characteristic pollutants in dyeing and printing wastewater according to claim 7, characterized in that, The methods for determining the preset reliability limits include: Obtain information on the type or concentration range of the target dissolved pollutants in the current effluent; Establish in advance the correlation information between the type or concentration range of the target soluble pollutant and the corresponding reliability limits; Based on the type information or the concentration range information, a reliability limit matching the current situation is obtained from the associated information and used as the preset reliability limit.

9. The method for detecting characteristic pollutants in dyeing and printing wastewater according to claim 4, characterized in that, The step of identifying and quantifying whether light scattering interference caused by non-target substances exists in the tailwater sample based on the relationship between the light signal attenuation at the measured wavelength and the light signal attenuation at the non-absorption characteristic wavelength includes: Compare the optical signal attenuation at the measured wavelength with the optical signal attenuation at the non-absorption characteristic wavelength to determine the difference or ratio of optical signals. Based on the difference or ratio of the optical signal, and according to the preset optical response characteristics or calibration data, the existence of the light scattering interference is determined and its magnitude is calculated.

10. A system for detecting characteristic pollutants in dyeing and printing wastewater, characterized in that, The system includes: The signal acquisition module is used to acquire the optical signal attenuation of the tailwater sample under test at at least two specific wavelengths, wherein the at least two specific wavelengths include the measurement wavelength in which the target dissolved pollutant has absorption characteristics, and the non-absorption characteristic wavelength in which the target dissolved pollutant absorbs very little or almost no absorption. The interference analysis module is used to identify and quantify whether there is light scattering interference caused by non-target substances in the tailwater sample based on the relationship between the light signal attenuation at the measured wavelength and the light signal attenuation at the non-absorption characteristic wavelength. The confidence calculation module is used to calculate the measurement confidence of the measurement results based on the identification and quantification results of light scattering interference. The output module is used to output the measurement confidence level and the pollutant concentration value together; The decision-making module is used to determine, based on the output measurement confidence level, whether to adopt the pollutant concentration value to adjust the processing parameters; and The prompting module is used to issue an abnormal status prompt to the operator when the measurement confidence level is lower than a preset threshold. The prompt message indicates the presence of light scattering interference.

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