A water treatment data correlation method based on sample anchor points and treatment events

Abstract

The application provides a water treatment data association method based on sample anchor points and treatment events, and belongs to the technical field of water treatment data. The method takes samples as anchor points to associate the relationships among pollutants, pollution risks and water treatment technologies contained in water treatment multi-source data, realizes effective management of the water treatment multi-source data, is beneficial to analysis and adjustment of water treatment technologies, and is further beneficial to water resource recycling.

Description

Technical Field

[0001] This invention relates to the field of water treatment data technology, and in particular to a method for associating water treatment data based on sample anchor points and treatment events. Background Technology

[0002] Water treatment refers to the process of removing harmful substances from water through a series of treatment methods to meet specific usage standards. Water treatment contributes to the recycling of water resources. Correlating the data generated during the water treatment process is beneficial for analyzing and adjusting water treatment technologies to achieve better treatment results.

[0003] However, existing technologies lack a way to manage the multi-source data generated during the water treatment process, which is not conducive to the analysis and adjustment of water treatment technologies, and thus not conducive to the recycling of water resources. Summary of the Invention

[0004] This invention proposes a water treatment data association method based on sample anchors and treatment events. By using samples as anchors, the method associates pollutants, pollution risks, and water treatment technologies contained in multi-source water treatment data. This enables effective management of multi-source water treatment data, facilitates the analysis and adjustment of water treatment technologies, and ultimately promotes the recycling of water resources.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a water treatment data association method based on sample anchors and treatment events, comprising: acquiring water treatment samples; determining a first association relationship for the samples; the first association relationship including the relationship between any two of the pollutants, pollution risks, and water treatment technologies associated with the samples; and determining a second association relationship based on the first association relationship; the second association relationship indicating the relationship between the pollutants, pollution risks, and water treatment technologies associated with the samples.

[0006] In one implementation, the sample is a sample taken from one of the multiple water treatment stages included in the water treatment process. The first correlation of the sample is determined, including: correlating pollutant detection events and risk detection events corresponding to multiple samples in the sample source chain to obtain the relationship between pollutants and pollution risks; the sample source chain indicates the process by which the original water treatment sample is transformed into a sample stage by stage. Correlating water treatment events and risk detection events corresponding to multiple samples in the sample source chain to obtain the relationship between water treatment technology and pollution risks. Correlating water treatment events and pollutant detection events corresponding to multiple samples sampled in the same water treatment stage to obtain the relationship between water treatment technology and pollutants.

[0007] In one implementation, pollutant detection events are obtained by associating sample anchors with pollutant objects; the sample anchors include the sample source chain, media type, and water quality parameters. Risk detection events are obtained by associating sample anchors with risk detection methods. Water treatment events are obtained by associating sample anchors with water treatment parameters; water treatment events indicate the process by which water treatment technology transforms input samples into output samples.

[0008] In one implementation, the pollutant objects include a first pollutant object whose identity has been determined and a second pollutant object whose identity has not been determined.

[0009] In one implementation, the identity of the second pollutant object is determined.

[0010] In one implementation, a second association is determined based on a first association, including: the relationship between the associated pollutants and pollution risks, the relationship between water treatment technologies and pollution risks, and the relationship between water treatment technologies and pollutants, thus obtaining the second association.

[0011] In one implementation, before determining the second association based on the first association, the method further includes: verifying the first association.

[0012] In one implementation, the above method further includes: analyzing the migration and transformation patterns and potential pollution risks of target pollutants in water treatment based on the second correlation.

[0013] In one implementation, the above method further includes: evaluating the response change pattern and applicability boundary of water treatment to pollution risk based on the second correlation.

[0014] In one implementation, the method further includes: determining candidate water treatment technologies that meet the treatment requirements and / or risk control requirements of the target pollutant based on a second correlation.

[0015] Compared with the prior art, the present invention has the following beneficial effects.

[0016] The water treatment data association method based on sample anchors and treatment events provided by this invention first acquires water treatment samples, then pairs pollutants, pollution risks, and water treatment technologies related to the samples to obtain a first association relationship, which includes the relationship between pollutants and pollution risks, the relationship between water treatment technologies and pollution risks, and the relationship between water treatment technologies and pollutants. After obtaining the above three relationships, a second association relationship indicating the relationship between pollutants, pollution risks, and water treatment technologies is obtained. This process uses samples as anchors, introduces pollutants, pollution risks, and water treatment technologies related to the anchors, and gradually associates these pollutants, pollution risks, and water treatment technologies, ultimately achieving the association of the correlation between pollutants, pollution risks, and water treatment technologies. This enables effective management of multi-source data related to water treatment, thereby facilitating the analysis and adjustment of water treatment technologies and ultimately promoting water resource recycling. Attached Figure Description

[0017] Figure 1 This is one of the schematic diagrams of a water treatment data association method based on sample anchor points and treatment events provided in the embodiments of this application; Figure 2 This is a second schematic diagram of a water treatment data association method based on sample anchor points and treatment events provided in this application embodiment; Figure 3 This is the third schematic diagram of a water treatment data association method based on sample anchor points and treatment events provided in this application embodiment; Figure 4 This is the fourth schematic diagram of a water treatment data association method based on sample anchor points and treatment events provided in the embodiments of this application; Figure 5 This is the fifth schematic diagram of a water treatment data association method based on sample anchor points and treatment events provided in the embodiments of this application; Figure 6 This is the sixth schematic diagram of a water treatment data association method based on sample anchor points and treatment events provided in this application embodiment; Figure 7 This is the seventh schematic diagram of a water treatment data association method based on sample anchor points and treatment events provided in the embodiments of this application; Figure 8 This is a schematic diagram of the four-layer coding framework provided in the embodiments of this application; Figure 9 This is a schematic diagram of an encoding example provided in the embodiments of this application; Figure 10 This is a schematic diagram of the associated path query and output of condition constraints provided in the embodiments of this application. Detailed Implementation

[0018] In the specification and claims of this invention, the terms "first" and "second," etc., are used to distinguish different objects, rather than to describe a specific order of objects.

[0019] In the embodiments of this application, "and / or" indicates a relationship between objects. For example, A and / or B can represent the following three situations: A exists alone, B exists alone, and A and B exist simultaneously.

[0020] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0021] In the description of this invention, unless otherwise stated, "a plurality of" means two or more. For example, a plurality of samples means two or more samples.

[0022] The method provided in this application relates to water treatment data management and can be used to correlate water treatment data from the perspectives of pollutants, pollution risks, and water treatment technologies.

[0023] In the field of water treatment, research, monitoring, and engineering operations generate a large amount of pollutant detection data, water quality risk characterization data, and treatment technology and operational data, along with information on sample sources, media characteristics, quality control, and process timing. These data originate from chromatography, mass spectrometry, spectroscopy, risk characterization detection, online instruments, experimental records, and process control systems, exhibiting differences in data granularity, labeling methods, and time scales. Current management methods often rely on piecing together data based on sample name, sampling point, test batch, or manually entered fields, making it difficult to confirm whether different results correspond to the same physical sample, the same treatment event, and the same applicable conditions.

[0024] The embodiments of this application summarize the defects of the prior art into the following six problems.

[0025] 1. After the same original sample is aliquoted, filtered, extracted, concentrated or phase-separated, the pollutant detection results and risk characterization results are prone to mismatch and it is difficult to trace back to the common parent sample.

[0026] 2. The water treatment process involves multiple influent, reflux, chemical dosing, diversion, confluence, backwashing, and byproduct flow. A single "influent-technology-effluent" record cannot reconstruct the true process.

[0027] 3. Pollutants can migrate from the aqueous phase to the organic liquid phase, gas phase, solid phase, or sludge phase. Comparing only the concentration in the aqueous phase may misjudge interphase transfer as degradation or removal.

[0028] 4. The unknown features formed by non-targeted detection will be updated as standards, spectral libraries and structural evidence increase, and static numbering can easily cause historical associations to become invalid.

[0029] 5. Evidence generated under different media and operating conditions cannot be directly reused. When querying, the applicable conditions, evidence level, and data quality must be considered simultaneously.

[0030] 6. Existing sample coding and data tracing methods mainly address unique identification, format mapping, or transfer records, but cannot systematically organize pollutant detection, risk characterization, handling events, and subsequent evidence.

[0031] To address the problem that existing technologies lack management methods for multi-source data generated during water treatment processes, which hinders the analysis and adjustment of water treatment technologies and consequently impedes water resource recycling, this application provides a water treatment data association method based on sample anchors and treatment events. This method uses samples as anchors to associate pollutants, pollution risks, and relationships between water treatment technologies within multi-source water treatment data. This achieves effective management of multi-source water treatment data, facilitating the analysis and adjustment of water treatment technologies and ultimately promoting water resource recycling.

[0032] Understandably, existing water treatment methods often involve multiple water treatment stages. During the water treatment process, samples are often taken at each stage to detect pollutants and pollution risks, and the results of pollutant detection events and pollution risk detection are recorded.

[0033] For example, in order to associate the sampled data with the corresponding pollutant detection events, pollution risk detection results, and water treatment processes, the following describes in detail a water treatment data association method based on sample anchor points and treatment events provided in this application embodiment, taking one water treatment stage as an example. Figure 1 As shown, the above method includes S101-S103.

[0034] S101. Obtain water treatment samples.

[0035] Optionally, the aforementioned water treatment can be implemented in confined space scenarios such as wastewater treatment plants, offshore platforms, or dredging vessels. The aforementioned samples can be sampling samples from one of the multiple water treatment stages included in the water treatment process. Correspondingly, each water treatment stage can include equipment examples, operating parameters, and actual influent and effluent water.

[0036] This application uses a sample as an anchor point (hereinafter referred to as sample anchor point S) to associate pollutants, pollution risks, and water treatment technologies in water treatment with processing events (pollutant detection events, risk detection events, and water treatment events). To achieve this association, the sample anchor point S can include the sample source chain of the corresponding water treatment stage, the medium type, water quality data, and characteristic parameters corresponding to the medium type. In some embodiments, the medium type can be an aqueous phase, oil phase, organic liquid phase, gas phase, solid phase, sludge phase, or mixed phase, etc.; the characteristic parameters can indicate the basic water quality of the water treatment stage, such as physical indicators (e.g., temperature, conductivity), chemical indicators (e.g., pH value, dissolved oxygen), and biological indicators (e.g., total bacterial count); the sample source chain indicates the process of converting the original sample of the water treatment into a sample step by step, and thus the sample source chain can include all sample information (e.g., original sample information, parent sample information, etc.) corresponding to the water treatment stage from the first water treatment stage to the water treatment stage where the sample is located.

[0037] Therefore, it can be seen that the changes in medium type and water quality during the process of transforming the original sample into the sample in the current water treatment process can be clearly identified through the above sample anchor point S.

[0038] S102. Determine the primary correlation of the samples.

[0039] The aforementioned first association includes the relationship between any two of the following: pollutant P, pollution risk B, and water treatment technology T related to the sample. Specifically, the aforementioned first association may include the relationship between pollutant and pollution risk (also known as the PB relationship), the relationship between water treatment technology and pollution risk (also known as the TB relationship), and the relationship between water treatment technology and pollutant (also known as the TP relationship).

[0040] In one implementation, combined with Figure 1 ,like Figure 2 As shown, S102 includes S1021-S1023.

[0041] S1021. By associating multiple pollutant detection events and risk detection events corresponding to samples in the sample source chain where the sample is located, the relationship between pollutants and pollution risks can be obtained.

[0042] In some applications, pollutant P is described using a pollutant object, and the above-mentioned pollutant detection event (also known as P×S event) can be obtained by associating the sample anchor point S with the pollutant object; similarly, when a risk detection method is used to describe a pollution risk B, the above-mentioned risk detection event (also known as S×B event) can be obtained by associating the sample anchor point S with the risk detection method.

[0043] The aforementioned pollutant objects can include a first pollutant object with confirmed identity and a second pollutant object with unconfirmed identity. The aforementioned pollutant detection events can record the concentration, peak area, detection limit, and first quality control information of the pollutant object. The first quality control information describes the data confidence level of the pollutant object, such as spiked recovery rate, parallel sample deviation, standard curve, and limit of quantitation. When the data confidence level is high, the pollutant object corresponding to the pollutant detection event is determined to be the first pollutant object; otherwise, it is determined to be the second pollutant object. The aforementioned risk detection method B can record the pollutant risk detection characterization system, response endpoint, detection method, and method version. The aforementioned risk detection events can record the sample's specific response to risk detection, risk index, risk level, and quality control information. The aforementioned second quality control information can include: negative and positive controls, parallel well or parallel sample deviation, and dose-response fitting quality.

[0044] It should be understood that the above-mentioned correlation process links the pollutant detection events and risk detection events of the samples corresponding to the original samples to the current water treatment process, as indicated by the sample source chain, thereby realizing the correlation between pollutants and pollution risks in the water treatment process from the perspective of pollution tracing.

[0045] S1022. By associating water treatment events and risk detection events corresponding to multiple samples in the sample source chain of the associated sample, the relationship between water treatment technology and pollution risk can be obtained.

[0046] In some embodiments, the aforementioned water treatment event can be obtained by correlating the sample anchor point S with water treatment parameters; the water treatment event indicates that the water treatment technology T will input the sample S. in Converted into output sample S out The process, therefore the above water treatment event can also be called S. in ×T×S out In addition to the above, water treatment events can also record process topology, operating time window, residence time, flow role, and water flow rate. The process topology refers to the connection relationships and spatial structure formed between various water treatment stages according to the process flow. The flow role refers to the role a water flow plays in the water treatment process based on its source, destination, and function, such as influent (raw wastewater), effluent (treated water), return sludge (sludge returned from the secondary sedimentation tank), excess sludge (discharged sludge), or internal recirculation (nitrification liquor recirculation), etc.

[0047] Similarly, the above-mentioned correlation process links the water treatment events and risk detection events of the samples corresponding to the original samples to the current water treatment stage, as indicated by the sample source chain, and realizes the correlation between water treatment technology and pollution risk in the water treatment process from the perspective of pollution backtracking.

[0048] S1023. Correlate water treatment events and pollutant detection events corresponding to multiple samples sampled in the same water treatment process to obtain the relationship between water treatment technology and pollutants.

[0049] Unlike S1021 and S1022 above, the above correlation process links water treatment events and pollutant detection events corresponding to multiple samples sampled in the same water treatment process in parallel, thereby realizing the correlation between water treatment technology and pollutants starting from the same water treatment process.

[0050] S103. Determine the second association relationship based on the first association relationship.

[0051] In this embodiment of the application, the aforementioned second correlation (also known as the PBT relationship) indicates the relationship between pollutants, pollution risks, and water treatment technologies related to the sample. The process of determining the second correlation can be as follows: correlate the PB relationship, TB relationship, and TP relationship to obtain the PBT relationship.

[0052] In the first practical scenario of the above method, combined with Figure 2 ,like Figure 3 As shown, before S103, the above method also includes S104.

[0053] S104. Verify the first association relationship.

[0054] In one implementation, the system performs verification of sample source, time, topology, media conversion, and quality control to verify whether the data recorded in the first correlation belong to the same sample source chain or the same water treatment technology, and records the correlation evidence generated during the verification process; simultaneously, the first correlation that fails verification is retained as a record to be verified. The aforementioned correlation evidence may include PB evidence, TB evidence, TP evidence, sample source chain, processing event, applicable conditions, and verification status, etc.

[0055] Specifically, the candidate is first used to record the first association, and after verification, it is converted to a verified status. Here, "verified" only indicates that the corresponding data belongs to the same physical sample chain or the same treatment event chain, and the associated process is traceable. It does not replace the judgment of the causal relationship between pollutants and risks, nor does it replace the judgment of the removal mechanism of the treatment technology.

[0056] The aforementioned PB evidence can be categorized into co-occurrence in the same sample, statistical association among multiple samples, association after controlling for media conditions, and validation through single-substance spiking or removal. Examples of each type of PB evidence are provided below.

[0057] Co-occurrence in the same sample: Sulfamethoxazole P1 was detected in sample S1 from the secondary sedimentation tank effluent, and the same sample also showed an abnormal morphological response using the fish gill cell high-content imaging method B1. This generates a co-occurrence association between P1 and B1, indicating that both occurred in the same sample.

[0058] Statistical correlation across multiple samples: In multiple influent and effluent water samples, the concentration of P1 and the response of B1 showed a statistical correlation with changes in the samples. This result can serve as a basis for prioritizing spiked or single-substance validation.

[0059] Correlation after controlling media conditions: Analyze the relationship between pollutants and water quality risk in sample subsets with similar pH, conductivity and TOC to reduce interference caused by differences in baseline water quality.

[0060] Single-substance spiking or removal verification: Add a known concentration of P1 to the original sample or use selective treatment to reduce P1, and then test the B1 response; if the response changes reproducibly with P1, a higher confidence experimental record can be formed.

[0061] Furthermore, the aforementioned TP evidence is based on changes in contaminant detection in input and output samples during the same treatment event. The aforementioned TB evidence is based on changes in risk response before and after the same treatment event. The physical meaning and main uses of the aforementioned PB, TB, and TP evidence are shown in Table 1 below.

[0062] Table 1

[0063] Optionally, each piece of evidence may record the technology type, equipment example, input and output samples, medium, basic water quality or medium profile, operating conditions, calibration results, and applicable scope. When the same pollutant is detected in different output media, it is recorded as a phase migration clue to be verified for subsequent analysis.

[0064] In the second practical scenario of the above method, combined with Figure 3 ,like Figure 4 As shown, after S103, the above method also includes S105.

[0065] S105. Identify the second pollutant.

[0066] It should be noted that for unidentified second contaminant objects (also known as unknown contaminants), unknown contaminants mainly refer to contaminants identified but not confirmed during non-targeted mass spectrometry analysis (since the confidence level of non-targeted identification is divided into 5 levels, there will be a large number of suspected contaminants). For example, a temporary identification code (P-LX) method can be used to record unknown contaminants. If the identity of an unknown contaminant is confirmed, and the aforementioned unknown contaminant belongs to a new contaminant, it is recorded as a new first contaminant object; otherwise, the data related to the aforementioned unknown contaminant is merged into the record of the first contaminant object with the same identity.

[0067] In the third practical scenario of the above method, combined with Figure 3 ,like Figure 5 As shown, after S103, the above method also includes S106.

[0068] S106. Based on the second correlation, analyze the migration and transformation patterns and potential pollution risks of target pollutants in water treatment.

[0069] In one implementation, a second correlation relationship corresponding to the target pollutant is obtained. Based on the sample source chain and treatment events recorded in the second correlation relationship, the input and output samples corresponding to the target pollutant are determined according to the water treatment process. The pollutant detection events and risk detection events corresponding to the input and output samples are also obtained. The detection results of the target pollutant in different samples before and after the same treatment event are compared. Based on the changes in the detection results of the target pollutant in different treatment stages and different media, the migration and change of the target pollutant during the water treatment process are determined. Combining the process topology and time sequence of the treatment events, the migration and change situations corresponding to multiple treatment events are correlated to obtain the migration and transformation law of the target pollutant during the water treatment process.

[0070] Furthermore, based on the relationship between pollutants associated with the target pollutant and pollution risk, the risk detection results corresponding to the input and output samples are obtained. By comparing the changes in risk response, risk index, and / or risk level before and after the treatment event, the changes in the pollution risk associated with the target pollutant during the water treatment process can be determined, thus revealing the potential pollution risk of the target pollutant in water treatment.

[0071] In the fourth practical scenario described above, combined with... Figure 3 ,like Figure 6 As shown, after S103, the above method also includes S107.

[0072] S107. Based on the second correlation, evaluate the response change pattern and applicability boundary of water treatment to pollution risks.

[0073] In one implementation, a second correlation corresponding to the target water treatment technology and the treatment event corresponding to the second correlation are obtained. Input and output samples are determined based on the treatment events, and risk detection events corresponding to the input and output samples are obtained respectively. The risk response, risk index, and / or risk level before and after the treatment events are compared to determine the change in risk response corresponding to the water treatment technology. The change in risk response includes at least one of the following: a decrease in risk response, no significant change, or an increase in risk response.

[0074] Furthermore, the media type, water quality parameters, water treatment parameters, and quality control information corresponding to the formation of the second correlation are obtained, and the second correlation that meets the preset treatment requirements is screened based on the treatment results of the target pollutant and / or the changes in pollution risk; the media type, water quality parameter range, and water treatment parameter range corresponding to the second correlation that meets the preset treatment requirements are statistically analyzed to determine the applicability boundary of the water treatment technology.

[0075] In the fifth practical scenario of the above method, combined with Figure 3 ,like Figure 7 As shown, after S103, the above method also includes S108.

[0076] S108. Based on the second correlation, identify candidate water treatment technologies that meet the treatment requirements and / or risk control requirements of the target pollutant.

[0077] In one implementation, the treatment requirements for the target pollutant (hereinafter referred to as the target water treatment requirements) are obtained. The target water treatment requirements may include at least one of the target pollutant, the target pollution risk, and the target treatment conditions. The target treatment conditions may include at least one of the media type, water quality parameters, water treatment parameters, and time range.

[0078] Based on the target water treatment requirements, water treatment technologies and corresponding treatment events associated with the target pollutant and / or the target pollution risk are retrieved from the second association. The retrieved second association is then filtered based on at least one of the following: sample source chain, media type, water quality parameters, water treatment parameters, quality control information, and verification status, excluding associations that do not match the target treatment conditions.

[0079] The input and output samples corresponding to the second correlation after screening are compared. When the detection result of the target pollutant meets the preset pollutant treatment requirements and / or the risk detection result of the pollution risk meets the preset pollution risk control requirements, the corresponding water treatment technology is determined as a candidate water treatment technology.

[0080] Optionally, it can also output at least one of the following: target pollutant corresponding to the candidate water treatment technology, input sample, treatment event, output sample, risk detection results, media information, water quality parameters, water treatment parameters, calibration status, and data source.

[0081] In a practical application scenario of the water treatment data association method based on sample anchors and processing events, a four-layer coding framework for water treatment multi-media sample data association can be constructed according to the aforementioned water treatment data association method. This four-layer coding framework can achieve water treatment data association based on object-anchor-event-evidence. For example... Figure 8 As shown, the above four-layer coding framework includes the research object layer, the observation anchor layer, the event outcome layer, and the evidence layer. (Reference) Figure 8 The research object layer uses P-codes to represent pollutant objects, B-codes to represent risk testing methods, and T-codes to represent water treatment technologies. The observation anchor layer uses S-codes as sample codes to store corresponding sample anchors. The event outcome layer can link the research object layer and the observation anchor layer to obtain pollutant detection events represented by S×P codes, risk testing events represented by S×B codes, and events represented by S×P codes. in ×T×S out The entire process of the event is represented by a code; and a pollutant detection result table is derived based on the pollutant detection event, a risk test result table is derived based on the risk test event, and a unit influent and effluent correlation table is derived based on the entire process of the event. The evidence layer, based on the established basic water quality table, correlates the above event result layers to obtain the PB evidence table, TB evidence table, and TP evidence table. The specific data content stored in the research object layer, observation anchor point layer, event result layer, and evidence layer can be referred to the above content in the embodiments of this application, and will not be repeated here.

[0082] It should be noted that, in engineering applications, the method provided in this application preferably constructs a multi-media sample data association database for water treatment. This association database is the main implementation carrier of this method and is used to continuously store object master data, sample source chains, media profiles, detection and characterization events, processing events, associated evidence, verification records, and version history. One-time data analysis can also be performed in memory or file environments, but this is not conducive to continuous updates, historical traceability, and multi-user queries.

[0083] Figure 9 Taking a water treatment process as an example, this paper describes the recording process of S-code, P-code, B-code, and T-code in a multi-media sample data association database for water treatment. (Reference) Figure 9The S code consists of the platform / laboratory, date, process node, medium, and parallel sample code. The P code corresponds to the contaminant object; for the first contaminant object, the P code includes the contaminant's CAS number; for the second contaminant object, the P code uses LX to indicate unconfirmed identity. The B code consists of cell, subcellular morphology, high-content imaging, and method serial number. The T code consists of the water treatment technology category, subcategory, and related technology number. These S, P, B, and T codes serve as unique identifiers to ensure accurate recording of water treatment data.

[0084] Specifically, it adopts "preprocessing-A" 2 Taking a wastewater treatment plant using the "O biological treatment—secondary sedimentation tank—ozone—biological activated carbon" process as an example, in the influent, A 2 Aqueous phase sampling points were set up for the influent (O2), effluent (secondary sedimentation tank), effluent (ozone), effluent (biological activated carbon), and total effluent. Return sludge and excess sludge sampling points were set up in the secondary sedimentation tank. Exhaust gas sampling points were set up in the ozone contact unit. Conventional water quality data were recorded for pH, COD, TOC, ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, total nitrogen, total phosphorus, conductivity, dissolved oxygen, suspended solids, and flow rate. The correlation recording method for the above data in the water treatment multi-media sample data association database is shown in Table 2 below.

[0085] Table 2

[0086] Taking a secondary sedimentation tank as an example, create a processing event E-SEC-20260715-01, with input A. 2 The / O terminal mixed liquor output includes secondary sedimentation tank effluent, returned sludge, and excess sludge; the returned sludge serves as input for subsequent biological treatment events. The laboratory extracts pollutant detection samples and risk characterization samples from the secondary sedimentation tank effluent, each registered as S, and pointing to a common parent sample via parent_sample_id. Since the two samples share the same parent sample, a PB relationship is generated accordingly.

[0087] Taking the ozone contact unit as an example, a treatment event E-O3-20260715-01 is established, with the secondary sedimentation tank effluent as the input and ozone effluent and tail gas as the output. Pollutant detection events on the input sample and pollutant detection events on the output sample are associated through the same treatment event, thereby generating a TP relationship (a candidate relationship between detection and treatment events). Similarly, B characterization events on the input sample and B characterization events on the output sample generate a TB relationship (a candidate relationship between treatment technology and risk characterization events). The biological activated carbon unit associates influent, effluent, activated carbon samples, and backwash water with the same event to distinguish the destination of pollutants in different output media.

[0088] Users submit a query for "techniques with treatment records for P-723-46-6 under aqueous phase and pH 6.5-8.0 conditions, and with risk characterization results after treatment". The query service excludes paths where the medium or operating conditions do not meet the requirements, and returns the complete chain of "target pollutant - input sample - treatment event / technology - output sample - risk characterization", along with operating parameters, medium information, changes before and after treatment, applicable conditions, calibration status, and original data source.

[0089] refer to Figure 10 The application process of the aforementioned multi-media sample data association database for water treatment may include querying corresponding association paths under constraints. The query request may include at least one of the target pollutant, risk characterization characteristics, or treatment technology, and may also include media type, pH, COD, TOC, ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, total nitrogen, total phosphorus, conductivity, dissolved oxygen, salinity, oil content, solids content, operating parameters, and time range. The system searches for candidate paths in the association structure composed of objects, samples, treatment events, and evidence, eliminating paths that do not match in terms of media, time, operating conditions, quality control, or sample source. The output includes the target object, sample source chain, treatment event, media information, changes in detection before and after treatment, applicable conditions, verification status, and data source. The association status only indicates the data chain verification result and does not replace causal or mechanistic judgments.

[0090] Compared with existing water sample coding methods, the method provided in this application has the following advantages.

[0091] 1. Reduce mismatches in the sample sourcing chain. Sample S and its source chain trace the pollutant detection sampling, risk characterization sampling, and treatment records back to the original physical sample. When there is a source conflict or the derivative chain is incomplete, the candidate association is put into a pending verification state, thereby reducing the risk of sample mismatch in the three types of data. The P-LX temporary identity and identity history maintain the original characteristics, sample, event, and evidence relationship, and there is no need to reconstruct the entire historical association after the pollutant identity is updated.

[0092] 2. Maintain the integrity of the event handling process chain. Multi-input, multi-output processing event recording includes splitting, merging, reflux, phase separation, backwashing, and byproduct streams, maintaining connectivity between processing technologies, equipment instances, and input / output samples, and improving the recording integrity of complex processing chains.

[0093] 3. Conditional constraints reduce error reuse. Media profiling, basic water quality, operating conditions, and quality control work together to perform correlation verification and query filtering, ensuring that the applicable conditions at the time of formation are retained in the correlation records. This provides data support for identifying the distribution and destination of pollutants in different output media and reduces direct extrapolation across media and operating conditions.

[0094] 4. Continuous traceability through database association The database uniformly stores objects, samples, events, associations, verification status, and identity history; during queries, it synchronously returns the sample source chain, processing events, changes in detection before and after processing, verification status, and data source, facilitating technical screening and anomaly review; newly added detection data and identity confirmation results can be continuously integrated into the existing data chain, supporting the accumulation of research data and long-term engineering operation.

[0095] In summary, the water treatment data association method based on sample anchors and treatment events provided in this application first acquires water treatment samples, then pairs pollutants, pollution risks, and water treatment technologies related to the samples to obtain a first association relationship, which includes the relationship between pollutants and pollution risks, the relationship between water treatment technologies and pollution risks, and the relationship between water treatment technologies and pollutants. After obtaining the above three relationships, the above three relationships are further linked to obtain a second association relationship indicating the relationship between pollutants, pollution risks, and water treatment technologies. The above process uses samples as anchors, introduces pollutants, pollution risks, and water treatment technologies related to the anchors, and gradually associates the above pollutants, pollution risks, and water treatment technologies, ultimately realizing the association of the correlation between pollutants, pollution risks, and water treatment technologies. This enables effective management of multi-source data related to water treatment, which is beneficial for the analysis and adjustment of water treatment technologies, and thus for the recycling of water resources.

[0096] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A water treatment data association method based on sample anchor points and treatment events, characterized in that, include: Obtain water treatment samples; Determine the first association relationship of the samples; The first association includes the relationship between any two of the pollutants, pollution risks, and water treatment technologies associated with the sample; Based on the first association, a second association is determined; the second association indicates the relationship between pollutants, pollution risks, and water treatment technologies related to the sample.

2. The method as described in claim 1, characterized in that, The sample is a sample taken from one of the multiple water treatment steps included in the water treatment process; then determining the first correlation of the sample includes: By associating pollutant detection events and risk detection events corresponding to multiple samples in the sample source chain of the sample, the relationship between pollutants and pollution risks is obtained; the sample source chain indicates the process by which the original sample of the water treatment is transformed into the sample at each stage. By associating water treatment events and risk detection events corresponding to multiple samples in the sample source chain of the sample, the relationship between water treatment technology and pollution risk can be obtained. By associating water treatment events and pollutant detection events corresponding to multiple samples collected in the same water treatment process, the relationship between water treatment technology and pollutants can be obtained.

3. The method as described in claim 2, characterized in that, The pollutant detection event is obtained by associating sample anchor points with pollutant objects; the sample anchor points include the sample source chain, media type, and water quality parameters. The risk detection events are obtained by associating sample anchor points with risk detection methods; The water treatment event is obtained by associating sample anchor points with water treatment parameters; the water treatment event indicates the process by which the water treatment technology transforms the input sample into the output sample.

4. The method as described in claim 3, characterized in that, The pollutant objects include a first pollutant object whose identity has been determined and a second pollutant object whose identity has not been determined.

5. The method as described in claim 4, characterized in that, The method further includes: Identify the second pollutant object.

6. The method as described in claim 1 or 2, characterized in that, The step of determining the second association relationship based on the first association relationship includes: The second correlation is obtained by relating pollutants to pollution risks, water treatment technologies to pollution risks, and water treatment technologies to pollutants.

7. The method as described in claim 1, characterized in that, Before determining the second association relationship based on the first association relationship, the method further includes: Verify the first association relationship.

8. The method as described in claim 1, characterized in that, The method further includes: Based on the second correlation, the migration and transformation patterns and potential pollution risks of the target pollutants in the water treatment process are analyzed.

9. The method as described in claim 1, characterized in that, The method further includes: Based on the second correlation, the response change pattern and applicability boundary of the water treatment to pollution risk are evaluated.

10. The method as described in claim 1, characterized in that, The method further includes: Based on the second correlation, candidate water treatment technologies that meet the treatment requirements and / or risk control requirements of the target pollutant are identified.

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