High-purity water hydrogen conductivity analysis system and method based on electric regeneration ion exchange and microelement analysis

Abstract

The present application relates to hydrogen conductivity analysis technical field, specifically, it relates to high-purity water hydrogen conductivity analysis system and method based on electric regeneration ion exchange and microelement analysis. It includes: electric regeneration ion exchange purification unit; Microelement analysis pretreatment unit; Hydrogen conductivity detection unit; Microelement quantitative analysis unit; Correlation data processing unit. The present application relies on the synergistic cooperation of electric regeneration ion exchange purification, microelement analysis pretreatment and double detection unit, through the construction of dynamic molar conductivity traceability correction model based on electrochemical theory, combined with ion exchange resin aging state quantification to improve the model and introduce the conductivity contribution amplification factor to correct the conductivity contribution of characteristic metal cations, the conductivity increment introduced by electric regeneration anode dissolution interference can be quantitatively calculated and mechanism level corrected, and the source of the interference is calculated, so that the high-purity water hydrogen conductivity correction process is consistent with the actual operation state of the resin.

Description

Technical Field

[0001] This invention relates to the field of hydrogen conductivity analysis technology, and more specifically, to a high-purity water hydrogen conductivity analysis system and method based on electroregenerative ion exchange and microelement analysis. Background Technology

[0002] Hydrogen conductivity is a core indicator characterizing the purity of high-purity water, and the accuracy of its detection results is crucial for fields with stringent water quality requirements, such as power, electronics, and pharmaceuticals. Electro-regenerative ion exchange technology, due to its ability to achieve continuous online regeneration of ion exchange resins, significantly improves the efficiency and continuity of online high-purity water purification, making it the mainstream pretreatment technology for high-purity water hydrogen conductivity analysis. However, during the application of this technology, characteristic metal cations inevitably dissolve from the electro-regenerated anode. These cations introduce conductivity increment interference, and the aging state of the ion exchange resin and the real-time operating conditions of electro-regeneration further affect the degree of interference, directly causing distortion of the original hydrogen conductivity detection data. Therefore, achieving accurate correction for this type of interference has become a pressing technical problem to be solved in the field of high-purity water hydrogen conductivity analysis.

[0003] In existing technologies, while basic purification, detection, and simple interference correction operations can be performed for the detection of hydrogen conductivity in high-purity water purified by electro-regeneration ion exchange, the correction effect still falls short of the requirements for high-precision detection. The core defects are reflected in two aspects: First, for conductivity interference caused by cations dissolved from the electro-regeneration anode, existing correction methods mostly lack electrochemical theoretical support, relying solely on empirical numerical adjustments or fixed formulas for simple corrections. They fail to make targeted dynamic adjustments to the interference correction process based on the actual operating and aging state of the ion exchange resin, making it impossible to accurately quantify the conductivity increment introduced by this type of interference and thus difficult to achieve effective correction of interference at the mechanistic level. Second, in existing correction systems, the relevant correction parameters are mostly fixed settings, unable to be adaptively adjusted according to real-time changes in the operating conditions of the electro-regeneration process. At the same time, there is a lack of targeted interference compensation strategies and effective abnormal data identification methods for relevant data such as the concentration of characteristic ions involved in the correction and operating condition monitoring. Fluctuations in the electro-regeneration operating conditions and data anomalies can directly affect the correction results, leading to insufficient accuracy and stability of hydrogen conductivity detection data. In view of this, we propose a high-purity water hydrogen conductivity analysis system and method based on electroregeneration ion exchange and micro-element analysis. Summary of the Invention

[0004] The purpose of this invention is to provide a high-purity water hydrogen conductivity analysis system and method based on electroregeneration ion exchange and micro-element analysis, in order to solve the problems mentioned in the background art, such as the difficulty in accurately quantitatively calculating and mechanistic-level correcting the conductivity interference caused by cations dissolved from the electroregeneration anode, the inability of the correction system to adapt to real-time changes in electroregeneration conditions, and the lack of effective interference compensation and abnormal data verification methods.

[0005] To address the aforementioned technical problems, one objective of this invention is to provide a high-purity water hydrogen conductivity analysis system based on electroregenerative ion exchange and microelement analysis, comprising:

[0006] The electro-regenerative ion exchange purification unit uses electro-regenerative cation exchange technology to purify high-purity water samples online, replacing and removing non-hydrogen cations in the high-purity water samples, realizing continuous online regeneration of ion exchange resins, outputting purified water samples to the micro-element analysis pretreatment unit, and simultaneously collecting real-time regeneration operating data and transmitting it to the associated data processing unit.

[0007] The micro-element analysis pretreatment unit receives the purified water sample output from the electro-regeneration ion exchange purification unit, performs homogeneous branch pretreatment on the purified water sample, one branch removes dissolved interfering gases and outputs the pretreated water sample to the hydrogen conductivity detection unit, and the other branch enriches the characteristic metal cations dissolved from the electro-regeneration anode and outputs the enriched water sample to the micro-element quantitative analysis unit.

[0008] The hydrogen conductivity detection unit receives the pre-treated water sample output by the micro-element analysis pre-processing unit, performs real-time hydrogen conductivity detection on the pre-treated water sample, and outputs the raw hydrogen conductivity detection data to the associated data processing unit.

[0009] The micro-element quantitative analysis unit receives the enriched water sample output by the micro-element analysis preprocessing unit, quantitatively detects the characteristic metal cations dissolved from the electro-regenerated anode in the enriched water sample, and outputs the characteristic metal cation concentration data to the associated data processing unit.

[0010] The associated data processing unit synchronously acquires real-time regeneration operating data from the electro-regeneration ion exchange purification unit, raw hydrogen conductivity detection data from the hydrogen conductivity detection unit, and characteristic metal cation concentration data from the micro-element quantitative analysis unit. It employs a dynamic molar conductivity source correction model based on electrochemical theory, improved by quantifying the aging state of the ion exchange resin, and introduces a conductivity contribution amplification factor to dynamically correct the conductivity contribution calculation of characteristic metal cations. It combines a dynamic update mechanism for compensation parameters linked to electro-regeneration operating conditions, a threshold-triggered interference compensation mechanism, and an abnormal data verification mechanism. It quantitatively calculates and performs mechanistic-level correction on the conductivity increment introduced by electro-regeneration anodic dissolution interference in the raw hydrogen conductivity detection data; completes the source calculation of electro-regeneration anodic dissolution interference; and outputs the final analysis result of high-purity water hydrogen conductivity after source correction.

[0011] As a further improvement to this technical solution, the electroregenerative ion exchange purification unit includes an electroregenerative cation exchange treatment module, an online ion exchange resin regeneration module, and a regeneration condition data acquisition and transmission module, wherein:

[0012] The electro-regenerative cation exchange processing module is based on a high-purity water sample and uses electro-regenerative cation exchange technology to purify the high-purity water sample online, replacing and removing non-hydrogen cations in the high-purity water sample.

[0013] The online regeneration module for ion exchange resin is based on the purification process of the electro-regenerated cation exchange treatment module and uses electric field-driven ion migration technology to achieve continuous online regeneration of ion exchange resin.

[0014] The regeneration operating condition data acquisition and transmission module collects real-time regeneration operating condition data based on the operation process of the electro-regeneration ion exchange purification unit and transmits the real-time regeneration operating condition data to the associated data processing unit.

[0015] As a further improvement to this technical solution, the micro-element analysis pretreatment unit includes a purified water sample receiving and splitting module, a dissolved interfering gas removal module, and a characteristic metal cation enrichment module, wherein:

[0016] The purified water sample receiving and splitting module receives the purified water sample output from the electro-regenerative ion exchange purification unit and performs same-source splitting processing on the purified water sample.

[0017] The dissolved interfering gas removal module removes dissolved interfering gases from one of the purified water samples after the receiving and splitting modules, and outputs the pre-treated water sample to the hydrogen conductivity detection unit.

[0018] The characteristic metal cation enrichment module performs characteristic metal cation enrichment treatment on the purified water sample received and the other purified water sample after being split by the splitting module, and outputs the enriched water sample to the micro-element quantitative analysis unit.

[0019] As a further improvement to this technical solution, the hydrogen conductivity detection unit includes a pretreated water sample receiving module, a real-time hydrogen conductivity detection module, and a raw hydrogen conductivity detection data transmission module, wherein:

[0020] The pre-treated water sample receiving module receives the pre-treated water sample output by the micro-element analysis pre-treatment unit;

[0021] The real-time hydrogen conductivity detection module performs real-time hydrogen conductivity detection on the pre-treated water sample received by the pre-treated water sample receiving module.

[0022] The hydrogen conductivity raw detection data transmission module transmits the hydrogen conductivity raw detection data obtained by the real-time hydrogen conductivity detection module to the associated data processing unit.

[0023] As a further improvement to this technical solution, the micro-element quantitative analysis unit includes a water sample receiving module after enrichment, a characteristic metal cation quantitative detection module, and a characteristic metal cation concentration data transmission module, wherein:

[0024] The enriched water sample receiving module receives the enriched water sample output by the micro-element analysis preprocessing unit;

[0025] The characteristic metal cation quantitative detection module quantitatively detects the characteristic metal cations dissolved from the electro-regenerated anode in the enriched water sample received by the enriched water sample receiving module.

[0026] The characteristic metal cation concentration data transmission module transmits the characteristic metal cation concentration data obtained by the characteristic metal cation quantitative detection module to the associated data processing unit.

[0027] As a further improvement to this technical solution, the associated data processing unit includes a multi-source data synchronous acquisition module, a dynamic molar conductivity traceability correction module, an operating condition linkage compensation and anomaly verification module, and an analysis result output module.

[0028] The multi-source data synchronous acquisition module synchronously acquires the real-time regeneration operating data of the electro-regeneration ion exchange purification unit, the raw hydrogen conductivity detection data of the hydrogen conductivity detection unit, and the characteristic metal cation concentration data of the micro-element quantitative analysis unit.

[0029] The dynamic molar conductivity traceability correction module adopts a dynamic molar conductivity traceability correction model based on electrochemical theory and improves it by combining the aging state quantification of ion exchange resin. It introduces a conductivity contribution amplification factor to dynamically correct the conductivity contribution calculation of characteristic metal cations, and performs quantitative calculation and mechanism-level correction on the conductivity increment introduced by the electro-regenerated anodic dissolution interference in the original hydrogen conductivity detection data, thus completing the calculation of the source of electro-regenerated anodic dissolution interference.

[0030] The working condition linkage compensation and anomaly verification module combines the dynamic update mechanism of compensation parameters for electric regeneration working condition linkage, the threshold-triggered interference compensation and anomaly data verification mechanism to perform data processing.

[0031] The analysis result output module outputs the final analysis result of the hydrogen conductivity of high-purity water after source correction.

[0032] As a further improvement to this technical solution, the multi-source data synchronization acquisition module includes a unified time-series synchronization acquisition submodule, a resin operating parameter extraction submodule, and a multi-source data normalization submodule, wherein:

[0033] The unified timing synchronous acquisition submodule synchronously acquires real-time regeneration operating condition data, raw hydrogen conductivity detection data, and characteristic metal cation concentration data according to a unified sampling timing sequence.

[0034] The resin operating parameter extraction submodule extracts the cumulative operating time of the ion exchange resin and the average regeneration current intensity from the real-time regeneration operating data.

[0035] The multi-source data normalization submodule normalizes the synchronously collected data and transmits it to the dynamic molar conductivity traceability correction module.

[0036] As a further improvement to this technical solution, the process of dynamic correction of the characteristic metal cation conductivity contribution and quantitative calculation and mechanism-level correction of the dynamic molar conductivity traceability correction module includes the following steps:

[0037] S52.1 Determining the conductivity contribution amplification factor based on the aging state of ion exchange resin ;

[0038] S52.2, Combining conductivity contribution amplification factor Real-time molar conductivity of characteristic metal cations Perform dynamic correction;

[0039] S52.3, Based on the corrected real-time molar conductivity Solving for the conductivity increment introduced by the electro-regenerated anolyte dissolution interference in the raw hydrogen conductivity detection data. ;

[0040] S52.4, Based on Incremental Conductivity Mechanism-level correction was performed on the raw hydrogen conductivity data to obtain source-corrected hydrogen conductivity data. And complete the calculation of the sources of interference from anodic dissolution during electroregeneration.

[0041] As a further improvement to this technical solution, the working condition linkage compensation and anomaly verification module includes a working condition linkage parameter update submodule, a threshold trigger interference compensation submodule, and an anomaly data verification and filtering submodule, wherein:

[0042] The working condition linkage parameter update submodule dynamically updates the compensation parameters of the dynamic molar conductivity traceability correction model based on real-time regeneration working condition data.

[0043] The threshold-triggered interference compensation submodule performs corresponding interference compensation operations based on the characteristic metal cation concentration threshold.

[0044] The abnormal data verification and screening submodule verifies the validity of the characteristic metal cation concentration data and transmits the valid data to the dynamic molar conductivity traceability and correction module.

[0045] The second objective of this invention is to provide a method for analyzing the hydrogen conductivity of high-purity water based on electroregenerative ion exchange and microelement analysis. The high-purity water hydrogen conductivity analysis system based on the aforementioned electroregenerative ion exchange and microelement analysis includes the following steps:

[0046] S1. The high-purity water sample is purified online using electro-regeneration cation exchange technology to replace and remove non-hydrogen cations in the high-purity water sample. At the same time, the ion exchange resin is continuously regenerated online, and the purified water sample is output. Real-time regeneration data is collected and transmitted simultaneously.

[0047] S2. Receive the purified water sample, perform same-source branch pretreatment on the purified water sample, remove dissolved interfering gases from one of the purified water samples and output the pretreated water sample, and enrich the characteristic metal cations dissolved from the electroregenerated anode of the other purified water sample and output the enriched water sample.

[0048] S3. Receive the pretreated water sample, perform real-time hydrogen conductivity detection on the pretreated water sample, output the raw hydrogen conductivity detection data and complete the transmission.

[0049] S4. Receive the enriched water sample, quantitatively detect the characteristic metal cations dissolved from the electro-regenerated anode in the enriched water sample, output the characteristic metal cation concentration data and complete the transmission.

[0050] S5. Simultaneously acquire real-time regeneration operating condition data, raw hydrogen conductivity detection data, and characteristic metal cation concentration data. Collect the above three types of data synchronously according to a unified sampling sequence. Extract the cumulative running time of the ion exchange resin and the average regeneration current intensity from the real-time regeneration operating condition data. Regularize the various types of data after synchronous collection.

[0051] S6. A dynamic molar conductivity source correction model based on electrochemical theory is adopted and improved by combining the aging state quantification of ion exchange resin. A conductivity contribution amplification factor is introduced to dynamically correct the conductivity contribution calculation of characteristic metal cations. First, the conductivity contribution amplification factor is determined based on the aging state quantification of ion exchange resin. Then, the real-time molar conductivity of characteristic metal cations is dynamically corrected based on the conductivity contribution amplification factor. Subsequently, the conductivity increment introduced by the electro-regenerated anodic dissolution interference in the original hydrogen conductivity detection data is calculated based on the corrected real-time molar conductivity. Finally, the original hydrogen conductivity detection data is corrected at the mechanism level based on the conductivity increment to obtain the source-corrected hydrogen conductivity data. At the same time, the source of electro-regenerated anodic dissolution interference is calculated.

[0052] S7. Based on the real-time operating data of regeneration, dynamically update the compensation parameters of the dynamic molar conductivity traceability correction model, perform corresponding interference compensation operations according to the characteristic metal cation concentration threshold, verify the validity of the characteristic metal cation concentration data, and transmit the verified valid data to the dynamic molar conductivity traceability correction model to participate in the correction process.

[0053] S8. Output the final analysis results of the hydrogen conductivity of high-purity water after source correction.

[0054] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0055] 1. This invention relies on the synergistic cooperation of electro-regenerative ion exchange purification, micro-element analysis pretreatment, and dual detection units. By constructing a dynamic molar conductivity source-tracing correction model based on electrochemical theory, and combining the quantification of the aging state of ion exchange resin to improve the model and introduce a conductivity contribution amplification factor to correct the conductivity contribution of characteristic metal cations, it can quantitatively calculate and mechanistic-level correct the conductivity increment introduced by electro-regenerative anodic dissolution interference, and simultaneously complete the calculation of the source of this interference. This allows the high-purity water hydrogen conductivity correction process to closely match the actual operating state of the resin, and is suitable for the correction needs of fields with stringent requirements for high-purity water quality, such as power, electronics, and pharmaceutical industries.

[0056] 2. This invention establishes a dynamic update mechanism for compensation parameters linked to the electroregeneration process, a threshold-triggered interference compensation mechanism, and anomaly data verification mechanism by uniformly collecting and organizing three types of data: real-time regeneration conditions, raw hydrogen conductivity detection, and characteristic metal cation concentration. This mechanism, along with the extraction of key resin operation parameters, enables dynamic updates of correction model compensation parameters based on real-time electroregeneration conditions. It performs targeted interference compensation and verifies the validity of characteristic metal cation concentration data, using only valid data in the correction process to avoid interference from abnormal data. This ensures the accuracy and stability of the hydrogen conductivity correction results for high-purity water, meeting the application requirements for high-precision detection of high-purity water quality in related fields. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the system framework of the present invention;

[0058] The meanings of the labels in the diagram are as follows:

[0059] 1. Electro-regenerative ion exchange purification unit; 11. Electro-regenerative cation exchange treatment module; 12. Online regeneration module for ion exchange resin; 13. Regeneration condition data acquisition and transmission module;

[0060] 2. Microelement analysis pretreatment unit; 21. Purified water sample receiving and splitting module; 22. Dissolved interfering gas removal module; 23. Characteristic metal cation enrichment module;

[0061] 3. Hydrogen conductivity detection unit; 31. Pretreated water sample receiving module; 32. Real-time hydrogen conductivity detection module; 33. Hydrogen conductivity raw detection data transmission module;

[0062] 4. Trace element quantitative analysis unit; 41. Water sample receiving module after enrichment; 42. Characteristic metal cation quantitative detection module; 43. Characteristic metal cation concentration data transmission module;

[0063] 5. Related data processing unit; 51. Multi-source data synchronous acquisition module; 52. Dynamic molar conductivity traceability correction module; 53. Operating condition linkage compensation and anomaly verification module; 54. Analysis result output module. Detailed Implementation

[0064] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0065] like Figure 1 As shown, this embodiment provides a high-purity water hydrogen conductivity analysis system based on electroregenerative ion exchange and microelement analysis, including:

[0066] The electro-regenerative ion exchange purification unit 1 uses electro-regenerative cation exchange technology to purify high-purity water samples online, replacing and removing non-hydrogen cations in the high-purity water samples, realizing continuous online regeneration of ion exchange resins, outputting purified water samples to the micro-element analysis pretreatment unit 2, and simultaneously collecting real-time regeneration operating data and transmitting it to the associated data processing unit 5.

[0067] In this embodiment, the electroregenerative ion exchange purification unit 1 includes an electroregenerative cation exchange treatment module 11, an online ion exchange resin regeneration module 12, and a regeneration condition data acquisition and transmission module 13, wherein:

[0068] The electro-regenerative cation exchange processing module 11 uses electro-regenerative cation exchange technology to purify high-purity water samples online, replacing and removing non-hydrogen cations from the high-purity water samples, and providing a continuous supply of purified water samples for the micro-element analysis pretreatment unit 2. The specific implementation is as follows:

[0069] The electro-regenerated cation exchange treatment module 11 uses a closed electro-regenerated cation exchange column filled with strong acid cation exchange resin as the core purification carrier. High-purity water samples are continuously fed into the inlet of the exchange column in a constant flow manner. The water sample is in full contact with the strong acid cation exchange resin in the column. The hydrogen ions in the resin undergo ion exchange reaction with the non-hydrogen cations in the high-purity water sample, completing the replacement and removal of non-hydrogen cations. The purified water sample is continuously output from the outlet of the exchange column and directly transported to the micro-element analysis pretreatment unit 2. The entire purification process is online and continuous, without offline shutdown processing.

[0070] The ion exchange resin online regeneration module 12 is based on the purification process of the electro-regeneration cation exchange treatment module 11. It uses electric field-driven ion migration technology to achieve continuous online regeneration of the ion exchange resin, thereby continuously restoring the ion exchange capacity of the resin and ensuring the continuous operation of the online purification process of the electro-regeneration cation exchange treatment module 11. The specific implementation is as follows:

[0071] The online regeneration module 12 for ion exchange resin uses the electro-regenerated cation exchange column in the electro-regenerated cation exchange treatment module 11 as the regeneration carrier. Corrosion-resistant, inert, and conductive cathode and anode electrodes are respectively arranged at the inlet and outlet of the exchange column. The electrodes and the strongly acidic cation exchange resin in the column form an electric field interaction system. While the electro-regenerated cation exchange treatment module 11 is performing online purification, a stable DC electric field is applied to the cathode and anode electrodes. Through electric field-driven ion migration technology, the non-hydrogen cations adsorbed on the resin migrate directionally to the cathode under the action of the electric field force. At the same time, hydrogen ions are replenished to the resin phase, thereby restoring the ion exchange capacity of the ion exchange resin. The regeneration process is synchronized with the purification process of the electro-regenerated cation exchange treatment module 11 and is carried out on the same carrier, without the need for additional offline regeneration steps and regeneration reagents.

[0072] The regeneration operating condition data acquisition and transmission module 13, based on the operation process of the electro-regeneration ion exchange purification unit 1, acquires real-time regeneration operating condition data and transmits it to the associated data processing unit 5, providing raw operating condition data support for the subsequent data correction work of the associated data processing unit 5. The specific implementation is as follows:

[0073] The regeneration operating condition data acquisition and transmission module 13 integrates sensing elements, a data acquisition unit, and an industrial communication module. The sensing elements are correspondingly deployed at key positions in the exchange column of the electro-regeneration cation exchange treatment module 11, the electrodes of the online ion exchange resin regeneration module 12, and the flow path of the electro-regeneration ion exchange purification unit 1, to collect real-time regeneration operating condition data during the operation of the electro-regeneration ion exchange purification unit 1. The data acquisition unit is electrically connected to the sensing elements to complete the real-time acquisition, analog-to-digital conversion, and preliminary standardized encoding of the regeneration operating condition data. The industrial communication module adopts an industrial real-time communication protocol to establish a stable communication link with the multi-source data synchronous acquisition module 51 of the associated data processing unit 5, and transmits the encoded regeneration real-time operating condition data to the associated data processing unit 5 in real time according to a unified sampling sequence.

[0074] The micro-element analysis pretreatment unit 2 receives the purified water sample output from the electro-regeneration ion exchange purification unit 1, performs homogeneous branch pretreatment on the purified water sample, one branch removes dissolved interfering gases and outputs the pretreated water sample to the hydrogen conductivity detection unit 3, and the other branch enriches the characteristic metal cations dissolved from the electro-regeneration anode and outputs the enriched water sample to the micro-element quantitative analysis unit 4.

[0075] In this embodiment, the micro-element analysis pretreatment unit 2 includes a purified water sample receiving and splitting module 21, a dissolved interfering gas removal module 22, and a characteristic metal cation enrichment module 23, wherein:

[0076] The purified water sample receiving and splitting module 21 receives the purified water sample output from the electro-regenerative ion exchange purification unit 1, performs homologous splitting processing on the purified water sample, and provides homologous purified water samples with consistent physicochemical properties to the dissolved interfering gas removal module 22 and the characteristic metal cation enrichment module 23, ensuring the consistency of water samples in the subsequent two processing steps. At the same time, it stably delivers purified water samples to the two modules mentioned above. The specific implementation is as follows:

[0077] The purified water sample receiving and splitting module 21 adopts a closed pressure-resistant receiving channel made of high-purity polytetrafluoroethylene. It is seamlessly connected to the outlet of the electro-regenerative ion exchange purification unit 1 through a flange-type closed joint. An online flow rate sensor is installed in the channel to monitor the water sample flow rate in real time. The outlet of the receiving channel is connected to a precision electromagnetic diversion valve with no dead volume. This diversion valve can achieve precise diversion with equal pressure and velocity, dividing the purified water sample into two paths and connecting them to independent closed high-purity conveying channels. One conveying channel is connected to the inlet of the dissolved interfering gas removal module 22 in a closed manner, and the other is connected to the inlet of the characteristic metal cation enrichment module 23 in a closed manner. The entire process is closed, with no secondary pollution and no water sample retention, maintaining a stable water sample flow.

[0078] The dissolved interfering gas removal module 22 performs dissolved interfering gas removal processing on one of the purified water samples after being split by the purified water sample receiving and splitting module 21, and outputs the pre-treated water sample to the hydrogen conductivity detection unit 3. This removes interfering gases such as dissolved carbon dioxide in the water sample that can cause deviations in hydrogen conductivity detection, eliminates the influence of gas dissociation ions on the detection results, and ensures the accuracy of the original hydrogen conductivity detection data. The specific implementation is as follows:

[0079] The dissolved interfering gas removal module 22 uses a vacuum membrane degasser with a hydrophobic polytetrafluoroethylene degassing membrane as its core as the processing carrier, and is equipped with a vacuum generator and an online dissolved gas monitoring sensor. The water sample delivered by the purified water sample receiving and splitting module 21 enters the water sample channel inside the degassing membrane in a cross-flow manner. The vacuum generator provides a stable vacuum negative pressure to the outside of the degassing membrane. Under the dual action of concentration difference and negative pressure, the dissolved interfering gases in the water sample escape and are extracted and discharged. The online dissolved gas monitoring sensor monitors the dissolved gas content of the effluent water sample in real time. After degassing, the water sample enters a closed buffer channel with an oxygen-barrier design to avoid secondary dissolution. Finally, the pretreated water sample is continuously transported to the hydrogen conductivity detection unit 3 through a high-purity sealed pipeline. No chemical reagents are added and no ions are introduced throughout the entire process.

[0080] The characteristic metal cation enrichment module 23 performs characteristic metal cation enrichment processing on the other purified water sample after being split by the purified water sample receiving and splitting module 21, which is anoly dissolved by electroregeneration. The enriched water sample is then output to the micro-element quantitative analysis unit 4 to increase the concentration of low-concentration characteristic metal cations in the water sample to the quantitative detection limit, providing accurate cation concentration data for subsequent conductivity increment calculation and mechanism-level correction. The specific implementation is as follows:

[0081] The characteristic metal cation enrichment module 23 uses an enrichment column filled with aminophosphonic acid chelating resin as the core enrichment carrier, and is equipped with a low-speed constant flow injection pump, an online flow controller, and a low-concentration dilute nitric acid gradient elution device. The water sample delivered by the purified water sample receiving and splitting module 21 is regulated by the injection pump and flow controller, and then flows through the enrichment column at a low-speed constant flow. The chelating resin specifically adsorbs the characteristic metal cations dissolved by the electro-regenerated anode in the water sample. After the adsorption reaches dynamic equilibrium, the gradient elution device injects quantitative eluent to achieve cation desorption, forming a high-concentration enriched water sample. The enriched water sample enters a closed collection channel and is continuously transported to the micro-element quantitative analysis unit 4 through a high-purity sealed pipeline. The entire process is online and automated, with no impurity ions introduced. The enrichment column can be regenerated online to ensure continuous operation.

[0082] Hydrogen conductivity detection unit 3 receives the pre-treated water sample output by micro-element analysis pre-processing unit 2, performs real-time hydrogen conductivity detection on the pre-treated water sample, and outputs the raw hydrogen conductivity detection data to the associated data processing unit 5.

[0083] In this embodiment, the hydrogen conductivity detection unit 3 includes a pretreated water sample receiving module 31, a real-time hydrogen conductivity detection module 32, and a raw hydrogen conductivity detection data transmission module 33, wherein:

[0084] The pretreated water sample receiving module 31 receives the pretreated water sample output from the micro-element analysis pretreatment unit 2, providing the real-time hydrogen conductivity detection module 32 with a stable flow, stable pressure, and no secondary pollution water sample. This eliminates the impact of water sample flow fluctuations on subsequent hydrogen conductivity detection, ensuring the basic water sample conditions for the detection process. The specific implementation is as follows:

[0085] The pretreated water sample receiving module 31 adopts a closed, stable flow channel made of high-purity polytetrafluoroethylene. It is seamlessly connected to the outlet of the dissolved interfering gas removal module 22 through a flange-type sealed joint. The flow channel is equipped with a flow-limiting and stabilizing structure, and is equipped with an online pressure sensor and an online flow velocity sensor to monitor and regulate the pressure and flow velocity of the water sample in the channel in real time, so as to maintain the flow stability of the water sample entering the subsequent modules. The entire process is a continuous online reception. There is no dead volume or water sample retention in the flow channel, which avoids secondary gas dissolution caused by contact between the water sample and the air. After the pretreated water sample is stabilized and pressure stabilized, it is continuously transported from the closed, stable flow channel to the real-time hydrogen conductivity detection module 32.

[0086] The real-time hydrogen conductivity detection module 32 performs real-time hydrogen conductivity detection on the pretreated water sample received by the pretreated water sample receiving module 31. This is used to accurately obtain the raw hydrogen conductivity data of high-purity water, providing basic detection data for the subsequent calibration work of the associated data processing unit 5. The specific implementation is as follows:

[0087] The real-time hydrogen conductivity detection module 32 uses a dedicated online conductivity electrode for high-purity water and a constant-temperature detection cell as its core detection components, and is equipped with an integrated temperature compensation module. The water sample delivered by the pre-treated water sample receiving module 31 continuously enters the constant-temperature detection cell, which precisely stabilizes the water sample temperature at the standard hydrogen conductivity detection temperature, eliminating the influence of temperature fluctuations on the conductivity detection results. The online conductivity electrode is completely immersed in the water sample in the constant-temperature detection cell and in full contact with the water sample, acquiring the conductivity signal of the water sample in real time. The temperature compensation module simultaneously performs temperature compensation correction on the acquired electrical signal, converting the detection value at a non-standard temperature into the hydrogen conductivity value at a standard temperature, forming continuously updated raw hydrogen conductivity detection data. The entire process is an online real-time detection.

[0088] The raw hydrogen conductivity detection data transmission module 33 transmits the raw hydrogen conductivity detection data obtained by the real-time hydrogen conductivity detection module 32 to the associated data processing unit 5. This ensures the real-time performance, accuracy, and timing consistency of the data transmission, and adapts to the multi-source data synchronization processing requirements of the associated data processing unit 5. The specific implementation is as follows:

[0089] The hydrogen conductivity raw detection data transmission module 33 integrates a data acquisition and conversion submodule and an industrial real-time communication submodule. The data acquisition and conversion submodule is electrically connected to the signal output terminal of the real-time hydrogen conductivity detection module 32, converting the detected analog electrical signal into a digital signal and completing the preliminary standardized encoding of the data. The industrial real-time communication submodule adopts a real-time communication protocol adapted to the industrial site, establishes a stable communication link with the multi-source data synchronous acquisition module 51 of the associated data processing unit 5, and transmits the encoded hydrogen conductivity raw detection data to the associated data processing unit 5 in real time and without delay according to the unified sampling time sequence set by the associated data processing unit 5, ensuring that the data transmission is lossless and without deviation.

[0090] The micro-element quantitative analysis unit 4 receives the enriched water sample output by the micro-element analysis preprocessing unit 2, performs quantitative detection on the characteristic metal cations dissolved from the electro-regenerated anode in the enriched water sample, and outputs the characteristic metal cation concentration data to the associated data processing unit 5.

[0091] In this embodiment, the micro-element quantitative analysis unit 4 includes a water sample receiving module 41 after enrichment, a characteristic metal cation quantitative detection module 42, and a characteristic metal cation concentration data transmission module 43, wherein:

[0092] The enriched water sample receiving module 41 receives the enriched water sample output from the micro-element analysis preprocessing unit 2; it is used to provide the characteristic metal cation quantitative detection module 42 with a stable flow, no secondary pollution, and stable concentration of analytical water sample, eliminating the influence of water sample flow pattern and concentration fluctuations on subsequent quantitative detection, and ensuring the basic water sample conditions for quantitative detection. The specific implementation is as follows:

[0093] The enriched water sample receiving module 41 adopts a closed, corrosion-resistant flow channel made of high-purity polytetrafluoroethylene. It is seamlessly connected to the outlet of the characteristic metal cation enrichment module 23 through a flange-type sealed joint. A precise flow-limiting structure is set in the flow channel, and it is equipped with an online flow sensor and an online trace metal concentration monitoring sensor to monitor the flow rate and initial concentration of the water sample in real time, maintaining the stability of the flow and concentration of the water sample entering the subsequent modules. The flow channel is designed without dead volume, and the entire process is online and continuous, with no water sample retention and no impurities introduced, avoiding dilution or contamination of the enriched water sample. After the enriched water sample is stabilized, it is continuously transported from the closed, corrosion-resistant flow channel to the characteristic metal cation quantitative detection module 42.

[0094] The characteristic metal cation quantitative detection module 42 quantitatively detects the characteristic metal cations dissolved from the electroregenerated anolyte in the enriched water sample received by the enriched water sample receiving module 41, accurately acquiring the concentration data of each characteristic metal cation. This provides core data support for the conductivity increment calculation, mechanism-level correction, and interference source calculation of the associated data processing unit 5. The specific implementation is as follows:

[0095] The characteristic metal cation quantitative detection module 42 uses an anodic stripping voltammetry detection component adapted for the detection of trace metal cations in high-purity water as its core, and is equipped with a fully automatic sample injection module, a detection signal acquisition submodule, and a quantitative data processing submodule. The water sample delivered by the enriched water sample receiving module 41 is quantitatively and continuously injected through the fully automatic sample injection module. After entering the detection component, the trace quantitative detection of characteristic metal cations such as iron, copper, sodium, calcium, and magnesium anolysed by electroregeneration anodic stripping is completed by anodic stripping voltammetry. The detection signal acquisition submodule collects the electrochemical signals in real time during the detection process, and the quantitative data processing submodule converts the electrochemical signals into specific concentration values ​​of each characteristic metal cation, forming accurate characteristic metal cation concentration data. The detection accuracy is adapted to the low-concentration trace detection requirements of the enriched water sample.

[0096] The characteristic metal cation concentration data transmission module 43 transmits the characteristic metal cation concentration data obtained from the characteristic metal cation quantitative detection module 42 to the associated data processing unit 5 to ensure the real-time performance, accuracy, and consistency of the concentration data transmission, and to achieve synchronous matching with the real-time regeneration operating data and the original hydrogen conductivity detection data. The specific implementation is as follows:

[0097] The characteristic metal cation concentration data transmission module 43 integrates a data extraction submodule, a standardized encoding submodule, and an industrial real-time communication submodule. The data extraction submodule is electrically connected to the data analysis end of the characteristic metal cation quantitative detection module 42, extracting the concentration data and data validity identifiers of each characteristic metal cation in real time. The standardized encoding submodule performs standardized encoding on the extracted concentration data in a unified format to ensure that the data format matches the processing requirements of the associated data processing unit 5. The industrial real-time communication submodule establishes a dedicated communication link with the multi-source data synchronization acquisition module 51 of the associated data processing unit 5, and transmits the encoded characteristic metal cation concentration data and validity identifiers to the associated data processing unit 5 in real time according to the unified sampling sequence of the associated data processing unit 5, ensuring that the data is synchronized with other multi-source data in time and without transmission deviation.

[0098] The associated data processing unit 5 synchronously acquires real-time regeneration operating data from the electro-regeneration ion exchange purification unit 1, raw hydrogen conductivity detection data from the hydrogen conductivity detection unit 3, and characteristic metal cation concentration data from the micro-element quantitative analysis unit 4. It employs a dynamic molar conductivity source correction model based on electrochemical theory, improved by quantifying the aging state of the ion exchange resin, and introduces a conductivity contribution amplification factor to dynamically correct the conductivity contribution calculation of characteristic metal cations. It combines a dynamic update mechanism for compensation parameters linked to electro-regeneration operating conditions, a threshold-triggered interference compensation mechanism, and an abnormal data verification mechanism. It quantitatively calculates and performs mechanistic-level correction on the conductivity increment introduced by electro-regeneration anodic dissolution interference in the raw hydrogen conductivity detection data. It completes the source calculation of electro-regeneration anodic dissolution interference and outputs the final analysis result of high-purity water hydrogen conductivity after source correction.

[0099] It should be added that the associated data processing unit 5 is built on the hardware foundation of an industrial-grade embedded data processing terminal, equipped with a dedicated electrochemical data processing algorithm program and database, and establishes a stable real-time data interaction link with the electro-regenerative ion exchange purification unit 1, the hydrogen conductivity detection unit 3, and the micro-element quantitative analysis unit 4 through an industrial communication interface. At the same time, it has built-in full-process processing logic for data operation, model correction, mechanism compensation, and result output.

[0100] Furthermore, the associated data processing unit 5 includes a multi-source data synchronous acquisition module 51, a dynamic molar conductivity traceability correction module 52, an operating condition linkage compensation and anomaly verification module 53, and an analysis result output module 54.

[0101] In this embodiment, the multi-source data synchronous acquisition module 51 synchronously acquires the real-time regeneration operating condition data of the electro-regeneration ion exchange purification unit 1, the raw hydrogen conductivity detection data of the hydrogen conductivity detection unit 3, and the characteristic metal cation concentration data of the micro-element quantitative analysis unit 4. The multi-source data synchronous acquisition module 51 relies on the industrial-grade embedded data processing terminal hardware resources of the associated data processing unit 5, and is configured with dual industrial communication interfaces of industrial Ethernet and RS485. It establishes point-to-point dedicated real-time data interaction links with the regeneration operating condition data acquisition and transmission module 13, the raw hydrogen conductivity detection data transmission module 33, and the characteristic metal cation concentration data transmission module 43, respectively. The links adopt the industrially common Modbus-RTU communication protocol to ensure the stability and real-time performance of data transmission.

[0102] The multi-source data synchronization acquisition module 51 includes a unified time-series synchronous acquisition submodule, a resin operating parameter extraction submodule, and a multi-source data normalization submodule. These submodules work in a linear workflow of synchronous acquisition, parameter extraction, data normalization, and directional transmission. The output data of the preceding submodule serves as the input data for the following submodule, eliminating data interaction gaps and achieving fully automated and standardized processing of multi-source data. Finally, the normalized structured data is directionally transmitted to the dynamic molar conductivity traceability correction module 52. The data transmission rate is 1.0 to 1.2 times the processing speed of the dynamic molar conductivity traceability correction module 52, matching its processing speed to avoid data accumulation or interruption, and ensuring the continuity of overall data processing in the associated data processing unit 5. Specifically:

[0103] The unified timing synchronization acquisition submodule synchronously acquires real-time regeneration operating data, raw hydrogen conductivity detection data, and characteristic metal cation concentration data according to a unified sampling timing sequence. This establishes a unified time reference for subsequent processing of multi-source data, eliminates data frequency differences and timing misalignments caused by independent acquisition by each unit, and ensures consistency in the time dimension of the three types of data. The specific implementation is as follows:

[0104] The unified time-series synchronous acquisition submodule, based on the real-time requirements of online detection of hydrogen conductivity in high-purity water, presets a unified sampling sequence at the millisecond level. The sampling period can be flexibly configured according to the actual detection requirements of the system, and the sampling period matches the data transmission output frequency of the regeneration working condition data acquisition and transmission module 13, the hydrogen conductivity raw detection data transmission module 33, and the characteristic metal cation concentration data transmission module 43. A high-precision crystal oscillator clock synchronization module is configured for the unified time-series synchronous acquisition submodule, which achieves precise clock synchronization with the electro-regeneration ion exchange purification unit 1, the hydrogen conductivity detection unit 3, and the micro-element quantitative analysis unit 4 through the NTP network time synchronization protocol, ensuring that the clock synchronization error is ≤ 1ms, which is the industrial-grade conventional allowable error in the field of online detection of hydrogen conductivity in high-purity water. The unified time-series synchronous acquisition submodule synchronously pulls and receives the three types of source data according to the preset unified sampling sequence through a dedicated data interaction link. A unique timestamp is added to each set of synchronously acquired data of the three types, and the timestamp is accurate to the smallest time unit of the unified sampling sequence, realizing the time dimension binding of the three types of data.

[0105] Meanwhile, the unified time-series synchronous acquisition submodule is configured with a temporary high-speed data buffer. The buffer adopts a circular storage mechanism, and the storage capacity is adapted to the data flow requirements of the continuous operation of the system. The synchronously acquired multi-source data with timestamps is cached for a short time. During the caching process, the data integrity is checked, and incomplete or garbled data generated during transmission is removed. This ensures that the three types of data in the buffer correspond one-to-one in terms of timestamps, without missing or out-of-order data. In addition, the buffer supports real-time data retrieval by the dynamic molar conductivity traceability and correction module 52.

[0106] The resin operating parameter extraction submodule extracts the cumulative operating time and average regeneration current intensity of the ion exchange resin from the real-time regeneration data. These two parameters are key foundational data for the dynamic molar conductivity traceability and correction module 52 to quantify the aging state of the ion exchange resin and determine the conductivity contribution amplification factor, ensuring the accuracy and real-time performance of parameter extraction and calculation. The specific implementation is as follows:

[0107] The resin operation parameter extraction submodule analyzes and extracts the real-time regeneration condition dataset of the electro-regeneration ion exchange purification unit 1 from the timestamped multi-source data output by the unified time-series synchronous acquisition submodule. From this dataset, it selects two basic data items: cumulative ion exchange resin operation time and real-time regeneration current intensity. The cumulative ion exchange resin operation time is the total continuous operation time of the online ion exchange resin regeneration module 12 from commissioning to the current sampling time. This cumulative value is directly extracted from the real-time regeneration condition dataset and denoted as... During the extraction process, the validity of parameter values ​​is verified, and abnormal values ​​that clearly exceed the reasonable range are removed; the real-time regeneration current intensity is the real-time current detection value of the electric field applied by the ion exchange resin online regeneration module 12, denoted as... The resin operating parameter extraction submodule defines a time window according to the preset sampling time sequence of the synchronous acquisition submodule. The regeneration real-time current intensity collected within the time window is then calculated using a moving average to obtain the regeneration average current intensity. The calculation formula is as follows:

[0108] ;

[0109] in:

[0110] Indicates the average regenerated current intensity;

[0111] This represents the number of real-time regenerative current intensity sampling points within the time window of the unified sampling timing sequence.

[0112] Indicates the first time within the time window The regenerated real-time current intensity at each sampling point.

[0113] Meanwhile, the resin operating parameter extraction submodule extracts the cumulative operating time of the ion exchange resin. With the calculated average regenerative current intensity Individually label the two parameters and add timestamp identifiers consistent with the original operating condition data. Establish an association mapping with the original real-time regeneration operating condition dataset to form a set of key parameters for resin operation. Transmit this parameter set together with the full amount of timestamped multi-source data output by the unified time-series synchronous acquisition submodule to the multi-source data regularization submodule.

[0114] Furthermore, when verifying the validity of parameter values ​​during the extraction process, the core judgment principle for parameter validity verification is: regenerative real-time current intensity. The reasonable range is ±20% of the rated operating current of the ion exchange resin during electric regeneration. Values ​​exceeding this range are considered abnormal and should be discarded. The cumulative operating time of the ion exchange resin... Only data continuity is verified, invalid data with gaps or jumps are removed, and there is no anomaly judgment for numerical range, to ensure the authenticity of the cumulative duration.

[0115] The multi-source data normalization submodule normalizes the synchronously collected data and transmits it to the dynamic molar conductivity traceability and correction module 52. This submodule performs format standardization, data structuring, and time-series consistency verification on the timestamped real-time regeneration operating data, raw hydrogen conductivity detection data, characteristic metal cation concentration data, and key resin operation parameter sets. This completes the integration and normalization of multi-source data, ensuring that the data transmitted to the dynamic molar conductivity traceability and correction module 52 has a unified format, dimension matching, and time-series consistency, allowing it to be directly used by the module for subsequent model calculations. The specific implementation is as follows:

[0116] The multi-source data normalization submodule first presets a standardized data format adapted to electrochemical data operations. It standardizes the character and symbolic descriptive data in the regeneration real-time operating data, hydrogen conductivity raw detection data, characteristic metal cation concentration data, and key resin operation parameters into numerical codes, converting all data items into numerical data that can be directly used in calculations, thus eliminating the computational obstacles caused by different data types. Subsequently, it performs a strict time sequence consistency check on the received full volume of timestamped multi-source data. Using the timestamp as the sole verification benchmark, it removes invalid data with mismatched or missing timestamps. For a small number of missing data items with a single data type ratio of ≤5%, it simply marks them blank without manual value filling. If the proportion of missing data items with a single data type ratio is >5%, the data frame is determined to be invalid and removed, thus preserving the originality and authenticity of the data while ensuring data integrity.

[0117] After verification, the real-time regeneration data, raw hydrogen conductivity data, and characteristic metal cation concentration data are integrated one-to-one using the timestamp as an index. At the same time, the key parameters of the resin operation are embedded into the real-time regeneration data with the corresponding timestamp, forming a standardized multi-source structured data frame. Each data frame contains core computational data such as timestamp, cumulative operating time of ion exchange resin, average regeneration current intensity, full parameters of real-time regeneration, raw hydrogen conductivity value, and concentration values ​​of each characteristic metal cation.

[0118] Finally, the multi-source data regularization submodule transmits the completed multi-source structured data frames sequentially and directionally to the dynamic molar conductivity traceability correction module 52 through the internal high-speed data bus of the associated data processing unit 5. During the data transmission process, a unique data transmission identifier is added to ensure that the data is not lost or out of order, and the transmission rate can be dynamically adapted according to the computing load of the dynamic molar conductivity traceability correction module 52 to avoid data accumulation.

[0119] In this embodiment, the dynamic molar conductivity source correction module 52 adopts a dynamic molar conductivity source correction model based on electrochemical theory and improves it by combining the aging state quantification of ion exchange resin. It introduces a conductivity contribution amplification factor to dynamically correct the conductivity contribution calculation of characteristic metal cations, quantitatively solves and corrects the conductivity increment introduced by the electro-regenerated anodic dissolution interference in the original hydrogen conductivity detection data, completes the solution of the source of electro-regenerated anodic dissolution interference, and outputs a standardized correction result dataset to provide core correction data for the operating condition linkage compensation and anomaly verification module 53. At the same time, it receives the dynamically updated model compensation parameters from the operating condition linkage compensation and anomaly verification module 53 to adapt the correction model to the real-time operating conditions of the system and ensure the accuracy of the correction throughout the process.

[0120] Meanwhile, the dynamic molar conductivity traceability correction module 52 relies on the industrial-grade embedded data processing terminal hardware resources of the associated data processing unit 5, and has a built-in electrochemical basic parameter database. It pre-stores well-known constants in the field of electrochemistry, such as the theoretical molar conductivity of characteristic metal cations, to provide basic parameter support for model calculation. The dynamic molar conductivity traceability correction module 52 establishes a one-way data receiving link with the multi-source data synchronous acquisition module 51 through an internal high-speed data bus, and receives the multi-source structured data frames transmitted by it. It also establishes a two-way data interaction link with the operating condition linkage compensation and anomaly verification module 53, and receives the dynamically updated model compensation parameters such as the resin aging conductivity contribution correction coefficient and the theoretical molar conductivity of characteristic metal cations, while outputting the correction result dataset to it. Data transmission adopts an internal high-speed synchronous transmission protocol to ensure data consistency, no loss, and no delay.

[0121] The process of dynamic correction of the characteristic metal cation conductivity contribution and quantitative calculation and mechanism-level correction of conductivity increment in the dynamic molar conductivity traceability correction module 52 includes the following steps:

[0122] S52.1 Determining the conductivity contribution amplification factor based on the aging state of ion exchange resin This provides core correction parameters for the dynamic correction of the real-time molar conductivity of characteristic metal cations, eliminating the influence of ion exchange resin aging on the conductivity contribution calculation. The specific implementation is as follows:

[0123] The dynamic molar conductivity traceability correction module 52 extracts the cumulative running time of the ion exchange resin from the multi-source structured data frames transmitted by the multi-source data synchronization acquisition module 51. With average regeneration current intensity ;by and Using ion exchange resin aging state coefficient as the core quantitative indicator, an aging state coefficient was constructed. , Characterizing the aging degree of ion exchange resins, The higher the value, the higher the degree of resin aging. The calculation formula is as follows:

[0124] ;

[0125] in:

[0126] The aging factor represents the cumulative operating time of the resin, and is derived from... The fitting yielded that, with The increase is monotonically increasing;

[0127] The aging coefficient represents the average regeneration current intensity, derived from... The fitting yielded that, with The increase is monotonically increasing.

[0128] Understandable, and The fitting relationship is determined based on the electro-regeneration operation characteristics of the ion exchange resin. The fitting function is a linear piecewise function that adapts to the aging patterns of the resin at different operating stages. The fitting parameters are well-known parameters in the field of electrochemistry and can be determined by those skilled in the art based on the actual resin model used.

[0129] In this embodiment, Cation exchange resins are classified into three stages based on their rated service life: low aging, medium aging, and high aging. Each stage represents a linear function with an increasing slope. For example, styrene-based strong acid cation exchange resins have a rated service life of 8000 hours. For low aging stage, For the middle and old age stage, This is the high aging stage; The resin electroregeneration process is divided into two stages based on the rated operating current: rated current and overload current. Each stage is a linear function with a fixed slope. For example, when the resin's rated operating current is 5A... For the rated current stage, For the overload current stage, the slope of the linear function in each stage is a conventional value used in the electrochemical field to adapt to the electroregeneration process.

[0130] Furthermore, based on the quantified resin aging state coefficient Determine the conductance contribution amplification factor , The formula used to correct the bias in conductivity contribution of characteristic metal cations to hydrogen conductivity detection after resin aging is as follows:

[0131] ;

[0132] in:

[0133] Indicates the amplification factor contributed by conductivity;

[0134] This represents the correction coefficient for the contribution of resin aging conductivity. It is a constant determined experimentally and is suitable for the application scenarios of electro-regeneration cation exchange technology.

[0135] Specifically, The experimental principle is as follows: by measuring the deviation between the actual and theoretical conductivity contributions of characteristic metal cations in the same type of ion exchange resin under different aging conditions, the deviation value is fitted to the resin aging state coefficient. The linear relationship is determined by taking the slope of the linear fitting equation as... The fixed value; this invention is suitable for conventional electroregenerated cation exchange resins based on styrene and acrylic. The typical value range is 0.02 to 0.05, and those skilled in the art can fine-tune it according to the specific resin model.

[0136] S52.2, Combining conductivity contribution amplification factor Real-time molar conductivity of characteristic metal cations Dynamic correction is performed to obtain the real-time molar conductivity that adapts to the aging state of the resin. This provides accurate molar conductivity parameters for subsequent incremental conductivity calculations. The specific implementation is as follows:

[0137] The dynamic molar conductivity traceability and correction module 52 extracts the theoretical molar conductivity of each characteristic metal cation from the built-in database. (A well-known constant in the field of electrochemistry, for different cations) (A fixed value); combined with the conductance contribution amplification factor determined in step S52.1. The real-time molar conductivity of each characteristic metal cation is dynamically corrected to obtain the corrected real-time molar conductivity. The calculation formula is as follows:

[0138] ;

[0139] in:

[0140] Indicates the first Real-time molar conductivity after correction for characteristic metal cations;

[0141] Indicates the amplification factor contributed by conductivity;

[0142] Indicates the first The theoretical molar conductivity of a characteristic metal cation.

[0143] Simultaneously, the dynamic molar conductivity traceability correction module 52 will correct the real-time molar conductivity of each characteristic metal cation. Store it as the core input parameter for step S52.3.

[0144] S52.3, Based on the corrected real-time molar conductivity Solving for the conductivity increment introduced by the electro-regenerated anolyte dissolution interference in the raw hydrogen conductivity detection data. This step is based on the corrected real-time molar conductivity. Combined with the concentration values ​​of each characteristic metal cation Quantitatively calculate the total conductivity increment introduced by the electro-regenerated anolyte dissolution interference in the original hydrogen conductivity detection data. Simultaneously, the individual conductivity increments of each characteristic metal cation are calculated. This provides core data for subsequent mechanism-level correction and interference source calculation. The specific implementation is as follows:

[0145] The dynamic molar conductivity traceability correction module 52 extracts the concentration values ​​of each characteristic metal cation from the multi-source structured data frame transmitted by the multi-source data synchronization acquisition module 51. Based on the quantitative relationship between ion concentration, molar conductivity, and conductivity contribution in electrochemistry, combined with the corrected real-time molar conductivity... Concentration values ​​of each characteristic metal cation Quantitatively calculate the total conductivity increment introduced by the electro-regenerated anolyte dissolution interference in the original hydrogen conductivity detection data. The calculation formula is as follows:

[0146] ;

[0147] in:

[0148] This represents the total conductivity increment introduced by the interference of anodic dissolution during electro-regeneration;

[0149] This indicates the number of characteristic metal cations dissolved from the electro-regenerated anode; in this embodiment, the characteristic metal cations dissolved from the electro-regenerated anode are the most common types in the high-purity water electro-regeneration ion exchange purification process, typically including... , , , ,Right now The typical value is 4. Those skilled in the art can supplement other types of leached cations based on the on-site water quality and anode material.

[0150] Indicates the first Concentration values ​​of characteristic metal cations;

[0151] Indicates the first Real-time molar conductivity corrected for characteristic metal cations.

[0152] Simultaneously, the dynamic molar conductivity traceability correction module 52 calculates the individual conductivity increment introduced by each characteristic metal cation. The calculation formula is as follows:

[0153] ;

[0154] in:

[0155] Indicates the first The individual conductivity increment introduced by a characteristic metal cation;

[0156] The dynamic molar conductivity traceability correction module 52 will calculate the total conductivity increment. Individual conductivity increments of each characteristic metal cation Store it as the core input parameter for step S52.4.

[0157] S52.4, Based on Incremental Conductivity Mechanism-level correction was performed on the raw hydrogen conductivity data to obtain source-corrected hydrogen conductivity data. And complete the calculation of the sources of interference from anodic dissolution during electro-regeneration, specifically as follows:

[0158] The dynamic molar conductivity traceability and correction module 52 extracts the original detection value of hydrogen conductivity from the multi-source structured data frame transmitted by the multi-source data synchronization acquisition module 51. The difference correction method is used to calculate the total conductance increment obtained in step S52.3. From the raw measured value of hydrogen conductivity After subtraction, the hydrogen conductivity data after source correction is obtained. This achieves mechanistic-level correction of the raw hydrogen conductivity detection data, and its calculation formula is as follows:

[0159] ;

[0160] Meanwhile, the dynamic molar conductivity traceability correction module 52 is based on the total conductivity increment. Individual conductivity increments of each characteristic metal cation Calculate the conductivity contribution percentage of each characteristic metal cation. ,pass The magnitude of the interference determines the main source of interference from anodic dissolution during electro-regeneration, enabling accurate calculation of the interference sources. The calculation formula is as follows:

[0161] ;

[0162] in:

[0163] Indicates the first The percentage of conductivity contribution of each characteristic metal cation.

[0164] The dynamic molar conductivity traceability correction module 52 will trace and correct the hydrogen conductivity data. The proportion of conductivity contribution of each characteristic metal cation The relevant calculation parameters are integrated into a correction result dataset and transmitted to the working condition linkage compensation and anomaly verification module 53 for further processing.

[0165] In this embodiment, the operating condition linkage compensation and anomaly verification module 53 performs data processing by combining the dynamic update mechanism of compensation parameters for electroregeneration operating condition linkage, the threshold-triggered interference compensation mechanism, and the anomaly data verification mechanism. Specifically, it performs full-process processing of system data by combining the dynamic update mechanism of compensation parameters for electroregeneration operating condition linkage, the threshold-triggered interference compensation mechanism, and the anomaly data verification mechanism: dynamically updating the compensation parameters of the dynamic molar conductivity traceability correction module 52 to adapt to real-time operating conditions; performing graded interference compensation based on the characteristic metal cation concentration threshold to optimize the correction results; verifying the validity of the characteristic metal cation concentration data, eliminating abnormal data, providing reliable input for the dynamic molar conductivity traceability correction module 52, and ultimately ensuring the accuracy and stability of the hydrogen conductivity analysis results. The working condition linkage compensation and anomaly verification module 53 includes a working condition linkage parameter update submodule, a threshold trigger interference compensation submodule, and an anomaly data verification and filtering submodule. The working condition linkage compensation and anomaly verification module 53 relies on the industrial-grade embedded data processing terminal of the associated data processing unit 5. It establishes a bidirectional data interaction link through an internal high-speed data bus, a multi-source data synchronization acquisition module 51, a dynamic molar conductivity traceability correction module 52, and an analysis result output module 54.

[0166] The operating condition linkage parameter update submodule dynamically updates the compensation parameters of the dynamic molar conductivity traceability correction model based on real-time regeneration operating condition data. This ensures that the dynamic molar conductivity traceability correction model always adapts to the real-time operating status of the electro-regeneration ion exchange purification unit 1, eliminating the impact of operating condition fluctuations on the model's calculation accuracy and guaranteeing the dynamic accuracy of the correction results. The specific implementation is as follows:

[0167] Preset regeneration operating condition change thresholds: The operating condition linkage parameter update submodule presets the change rate thresholds for three types of core operating condition parameters: electric field voltage change threshold, electric field current change threshold, and water sample flow rate change threshold. The thresholds are industry-standard values ​​adapted to electro-regeneration cation exchange technology, and those skilled in the art can adjust them according to the system operation requirements.

[0168] Real-time extraction of operating condition data: The operating condition linkage parameter update submodule extracts real-time operating condition data of regeneration from the multi-source structured data frames transmitted by the multi-source data synchronization acquisition module 51, including parameters such as electric field voltage, electric field current, and water sample flow rate.

[0169] Calculating the rate of change of operating conditions: The operating condition linkage parameter update submodule calculates the relative rate of change of the operating condition parameters at the current sampling time compared to the operating condition parameters at the previous sampling time. The calculation formula is as follows:

[0170] ;

[0171] in:

[0172] Indicates the rate of change of operating parameters;

[0173] This represents the operating condition parameter value at the current sampling time;

[0174] This represents the operating condition parameter value at the previous sampling time.

[0175] Threshold Comparison and Parameter Update: The operating condition linkage parameter update submodule compares the calculated rate of change with a preset threshold. If the rate of change does not exceed the threshold, the compensation parameters of the dynamic molar conductivity traceability correction module 52 remain unchanged. If the rate of change exceeds the threshold, the operating condition linkage parameter update submodule updates the parameters based on the magnitude of the change in operating condition parameters using linear interpolation (the linear interpolation method uses the rated operating condition parameters of resin electroregeneration as a benchmark and the relative rate of change of operating condition parameters as the benchmark). As variables, Larger compensation parameters , The larger the adjustment range, the more limited the adjustment range of all compensation parameters is to ±10% of the value corresponding to the rated operating condition, in order to adapt to fluctuations in operating conditions and not exceed the reasonable range of the process. This is the correction coefficient for the contribution of resin aging conductivity in the model. Theoretical molar conductivity of characteristic metal cations The compensation parameters are dynamically adjusted.

[0176] Parameter feedback and recording: The working condition linkage parameter update submodule feeds back the adjusted compensation parameters to the dynamic molar conductivity traceability correction module 52 in real time, updates the model calculation parameters, and logs the time of each parameter update, the reason for the change in working condition, and the parameter adjustment range, so as to realize full traceability of parameter updates.

[0177] The threshold-triggered interference compensation submodule performs corresponding interference compensation operations based on the characteristic metal cation concentration threshold. Specifically, it classifies the interference from electro-regenerated anolyte dissolution into different levels according to the characteristic metal cation concentration threshold, and performs targeted compensation operations for different levels of interference. This further optimizes the traceability-corrected hydrogen conductivity value output by the dynamic molar conductivity traceability correction module 52, improving the accuracy of the final analysis results. The specific implementation is as follows:

[0178] Preset concentration grading thresholds: Based on the accuracy requirements of high-purity water hydrogen conductivity detection, the threshold-triggered interference compensation submodule presets a grading threshold for the total concentration of characteristic metal cations, classifying interference into three levels: low interference (total concentration < threshold 1), medium interference (threshold 1 ≤ total concentration < threshold 2), and high interference (total concentration ≥ threshold 2). Different levels correspond to different compensation coefficients. ;

[0179] Calculation of total concentration of characteristic metal cations: The threshold-triggered interference compensation submodule extracts the concentration values ​​of each characteristic metal cation from the correction result dataset output by the dynamic molar conductivity traceability correction module 52. Calculate the total concentration The calculation formula is:

[0180] ;

[0181] in:

[0182] Indicates the total concentration of characteristic metal cations;

[0183] This indicates the number of characteristic metal cations dissolved from the electro-regenerated anode;

[0184] Determine the interference level and compensation coefficient: The threshold triggers the interference compensation submodule to... The current interference level is determined by comparing it with the classification threshold, and the corresponding compensation coefficient is applied. (Low interference) Interference High interference , (A constant determined experimentally to accommodate compensation requirements for different levels of interference).

[0185] Perform interference compensation: The threshold-triggered interference compensation submodule uses a compensation coefficient. The traceability-corrected hydrogen conductivity value output by the dynamic molar conductivity traceability correction module 52 A second compensation is performed to obtain the optimized hydrogen conductivity value. The calculation formula is:

[0186] ;

[0187] in:

[0188] This represents the traceability-corrected hydrogen conductivity value output by the dynamic molar conductivity traceability correction module 52.

[0189] Results Integration: The threshold-triggered interference compensation submodule will compensate the optimized results. The optimized calibration result dataset is integrated with the original calibration result dataset and then transmitted to the analysis result output module 54.

[0190] Furthermore, The principle for determining the value is as follows: it is determined based on the experimental correlation between the total concentration of characteristic metal cations and the correction deviation of hydrogen conductivity, under low interference conditions. A value of 0.95~0.99 is used to compensate for minor deviations in the detection system caused by low concentrations of dissolved ions; under high interference... A value of 1.01~1.05 is used to compensate for the superposition bias of the conductivity contribution from high-concentration dissolved ions. The specific value can be fine-tuned according to the detection accuracy requirements of hydrogen conductivity in high-purity water.

[0191] The abnormal data verification and screening submodule verifies the validity of the characteristic metal cation concentration data, removes abnormal data generated during transmission or detection, marks suspicious data, and transmits valid data to the dynamic molar conductivity traceability and correction module 52 to prevent abnormal data from interfering with the calculation accuracy of the correction model. The specific implementation is as follows:

[0192] Selecting the verification method: The abnormal data verification and screening submodule adopts the Grubbs test, which is commonly used in the field of high-purity water detection, as the core verification method, with a preset significance level (e.g., 0.05, a common value in this field).

[0193] Extracting Data to be Verified: The abnormal data verification and filtering submodule extracts the characteristic metal cation concentration data sequence from the multi-source structured data frames transmitted by the multi-source data synchronization acquisition module 51. ;

[0194] Statistical Analysis and Threshold Calculation: The outlier detection and filtering submodule calculates the average value of the concentration data sequence. and standard deviation The critical value of the Grubbs test is determined by combining the significance level. ;

[0195] Abnormal data detection: The abnormal data verification and filtering submodule checks each concentration data point. Calculate the Grubbs statistic The calculation formula is:

[0196] ;

[0197] like ,determination This is abnormal data; if near ,determination Data deemed suspicious;

[0198] Data processing and transmission: The abnormal data verification and screening submodule directly removes data that is determined to be abnormal, marks suspicious data separately, and organizes the remaining valid data into a valid concentration dataset according to the original time sequence. It is then transmitted to the dynamic molar conductivity traceability and correction module 52 through the internal data bus. At the same time, the removed abnormal data and marked suspicious data are logged, and the reasons for the abnormality / suspicion are marked to provide a basis for system operation and maintenance.

[0199] In this embodiment, the analysis result output module 54 outputs the final analysis result of the hydrogen conductivity of high-purity water after source traceability correction. The purpose of the analysis result output module 54 is to receive the effective correction results from the operating condition linkage compensation and anomaly verification module 53, integrate and output the final analysis result of the hydrogen conductivity of high-purity water after source traceability correction, and simultaneously realize the storage and traceability of full-process data, providing support for industrial site monitoring and operation and maintenance. The specific implementation is as follows:

[0200] Data reception and structured integration: The analysis result output module 54 receives the valid correction result dataset transmitted by the operating condition linkage compensation and anomaly verification module 53, and uses the timestamp as an index to display the compensated and optimized hydrogen conductivity value. Resin aging state coefficient Interference conductance increment The proportion of each cation's contribution to conductivity Information such as data quality identifiers is structured and integrated to form a standardized final analysis dataset.

[0201] Final result verification: The optimized hydrogen conductivity value will be compensated. The final analysis results of hydrogen conductivity in high-purity water after traceability correction were verified. For data with suspicious markers, a unique identifier was added to the results to clearly distinguish them from normal and valid results.

[0202] Multiple output formats:

[0203] Local real-time display: The final analysis results, resin aging status, main interfering ions and their contribution percentages are displayed in real time on an industrial display screen, and suspicious results are highlighted.

[0204] Remote data transmission: The final analysis dataset and results are transmitted in real time to the host computer, control system or cloud platform via industrial communication interface and common protocol;

[0205] Automated Reports: Automatically generate analysis reports according to preset cycles, including statistical results, trends, and data quality within the cycle, and support export and printing.

[0206] Data storage and traceability: It adopts a local + cloud dual storage mode, and stores data in categories such as raw data, correction process, final result, and abnormal log. All data is timestamped and device identified, and supports accurate query and full-chain traceability by keywords such as time, value, and operating condition.

[0207] Operation and maintenance coordination support: Real-time analysis of suspicious data identification and abnormal data removal logs in the effective correction result dataset. If suspicious / abnormal data is detected, maintenance prompts are issued via local display pop-ups, device indicator lights, and remote maintenance terminal message pushes, noting the time of the suspicious / abnormal data, the corresponding detection value, and possible causes; simultaneously, the aging state coefficient of the ion exchange resin is... Data such as the types of interfering ions from the main electro-regenerated anode are linked with the system operation and maintenance management module to provide accurate data support for online regeneration optimization of ion exchange resin, replacement cycle determination, and system interference source investigation, thereby achieving integrated linkage between high-purity water hydrogen conductivity detection and system operation and maintenance.

[0208] This embodiment also provides a method for analyzing the hydrogen conductivity of high-purity water based on electroregenerative ion exchange and microelement analysis. Based on the aforementioned high-purity water hydrogen conductivity analysis system based on electroregenerative ion exchange and microelement analysis, the method includes the following steps:

[0209] S1. The high-purity water sample is purified online using electro-regeneration cation exchange technology to replace and remove non-hydrogen cations in the high-purity water sample. At the same time, the ion exchange resin is continuously regenerated online, and the purified water sample is output. Real-time regeneration data is collected and transmitted simultaneously.

[0210] S2. Receive the purified water sample, perform same-source branch pretreatment on the purified water sample, remove dissolved interfering gases from one of the purified water samples and output the pretreated water sample, and enrich the characteristic metal cations dissolved from the electroregenerated anode of the other purified water sample and output the enriched water sample.

[0211] S3. Receive the pretreated water sample, perform real-time hydrogen conductivity detection on the pretreated water sample, output the raw hydrogen conductivity detection data and complete the transmission.

[0212] S4. Receive the enriched water sample, quantitatively detect the characteristic metal cations dissolved from the electro-regenerated anode in the enriched water sample, output the characteristic metal cation concentration data and complete the transmission.

[0213] S5. Simultaneously acquire real-time regeneration operating condition data, raw hydrogen conductivity detection data, and characteristic metal cation concentration data. Collect the above three types of data synchronously according to a unified sampling sequence. Extract the cumulative running time of the ion exchange resin and the average regeneration current intensity from the real-time regeneration operating condition data. Regularize the various types of data after synchronous collection.

[0214] S6. A dynamic molar conductivity source correction model based on electrochemical theory is adopted and improved by combining the aging state quantification of ion exchange resin. A conductivity contribution amplification factor is introduced to dynamically correct the conductivity contribution calculation of characteristic metal cations. First, the conductivity contribution amplification factor is determined based on the aging state quantification of ion exchange resin. Then, the real-time molar conductivity of characteristic metal cations is dynamically corrected based on the conductivity contribution amplification factor. Subsequently, the conductivity increment introduced by the electro-regenerated anodic dissolution interference in the original hydrogen conductivity detection data is calculated based on the corrected real-time molar conductivity. Finally, the original hydrogen conductivity detection data is corrected at the mechanism level based on the conductivity increment to obtain the source-corrected hydrogen conductivity data. At the same time, the source of electro-regenerated anodic dissolution interference is calculated.

[0215] S7. Based on the real-time operating data of regeneration, dynamically update the compensation parameters of the dynamic molar conductivity traceability correction model, perform corresponding interference compensation operations according to the characteristic metal cation concentration threshold, verify the validity of the characteristic metal cation concentration data, and transmit the verified valid data to the dynamic molar conductivity traceability correction model to participate in the correction process.

[0216] S8. Output the final analysis results of the hydrogen conductivity of high-purity water after source correction.

[0217] Those skilled in the art will understand that the process of implementing all or part of the steps of the above embodiments can be carried out by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0218] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A high-purity water hydrogen conductivity analysis system based on electroregenerative ion exchange and micro-element analysis, characterized in that, include: The electro-regenerated ion exchange purification unit (1) uses electro-regenerated cation exchange technology to purify high-purity water samples online, replaces and removes non-hydrogen cations in the high-purity water samples, realizes continuous online regeneration of ion exchange resin, outputs purified water samples to micro-element analysis pretreatment unit (2), and synchronously collects real-time regeneration operating data and transmits it to the associated data processing unit (5). The micro-element analysis pretreatment unit (2) receives the purified water sample output from the electro-regeneration ion exchange purification unit (1), performs homogeneous branch pretreatment on the purified water sample, removes dissolved interfering gases in one branch and outputs the pretreated water sample to the hydrogen conductivity detection unit (3), and enriches the characteristic metal cations dissolved from the electro-regeneration anode and outputs the enriched water sample to the micro-element quantitative analysis unit (4). Hydrogen conductivity detection unit (3) receives the pre-treated water sample output by the micro-element analysis pre-processing unit (2), performs real-time hydrogen conductivity detection on the pre-treated water sample, and outputs the original hydrogen conductivity detection data to the associated data processing unit (5). The micro-element quantitative analysis unit (4) receives the enriched water sample output by the micro-element analysis pretreatment unit (2), performs quantitative detection on the characteristic metal cations dissolved by the electro-regenerated anode in the enriched water sample, and outputs the characteristic metal cation concentration data to the associated data processing unit (5). The associated data processing unit (5) synchronously acquires the real-time regeneration operating data of the electro-regeneration ion exchange purification unit (1), the original hydrogen conductivity detection data of the hydrogen conductivity detection unit (3), and the characteristic metal cation concentration data of the micro-element quantitative analysis unit (4); adopts a dynamic molar conductivity traceability correction model based on electrochemical theory, and improves it by combining the aging state quantification of ion exchange resin, and introduces a conductivity contribution amplification factor to dynamically correct the conductivity contribution calculation of characteristic metal cations; combines the compensation parameter dynamic update mechanism of electro-regeneration operating condition linkage, threshold trigger interference compensation and abnormal data verification mechanism; performs quantitative calculation and mechanism-level correction on the conductivity increment introduced by electro-regeneration anode dissolution interference in the original hydrogen conductivity detection data; completes the calculation of the source of electro-regeneration anode dissolution interference; and outputs the final analysis result of high-purity water hydrogen conductivity after traceability correction.

2. The high-purity water hydrogen conductivity analysis system based on electroregenerative ion exchange and micro-element analysis according to claim 1, characterized in that, The electro-regenerative ion exchange purification unit (1) includes an electro-regenerative cation exchange treatment module (11), an online ion exchange resin regeneration module (12), and a regeneration condition data acquisition and transmission module (13), wherein: The electro-regenerative cation exchange processing module (11) uses electro-regenerative cation exchange technology to purify high-purity water samples online, replacing and removing non-hydrogen cations in the high-purity water samples. The online regeneration module (12) of the ion exchange resin is based on the purification process of the electro-regenerated cation exchange treatment module (11) and uses electric field driven ion migration technology to realize the continuous online regeneration of the ion exchange resin. The regeneration operating condition data acquisition and transmission module (13) collects real-time regeneration operating condition data based on the operation process of the electro-regeneration ion exchange purification unit (1) and transmits the real-time regeneration operating condition data to the associated data processing unit (5).

3. The high-purity water hydrogen conductivity analysis system based on electroregenerative ion exchange and micro-element analysis according to claim 2, characterized in that, The micro-element analysis pretreatment unit (2) includes a purified water sample receiving and splitting module (21), a dissolved interfering gas removal module (22), and a characteristic metal cation enrichment module (23), wherein: The purified water sample receiving and splitting module (21) receives the purified water sample output from the electro-regenerated ion exchange purification unit (1) and performs same-source splitting processing on the purified water sample. The dissolved interfering gas removal module (22) performs dissolved interfering gas removal processing on one of the purified water samples after being split by the purified water sample receiving and splitting module (21), and outputs the pre-treated water sample to the hydrogen conductivity detection unit (3). The characteristic metal cation enrichment module (23) performs characteristic metal cation enrichment treatment on the other purified water sample after being split by the purified water sample receiving and splitting module (21) through electro-regeneration anodic dissolution, and outputs the enriched water sample to the micro-element quantitative analysis unit (4).

4. The high-purity water hydrogen conductivity analysis system based on electroregenerative ion exchange and micro-element analysis according to claim 3, characterized in that, The hydrogen conductivity detection unit (3) includes a pretreated water sample receiving module (31), a real-time hydrogen conductivity detection module (32), and a hydrogen conductivity raw detection data transmission module (33), wherein: The pretreated water sample receiving module (31) receives the pretreated water sample output by the micro-element analysis pretreatment unit (2); The real-time hydrogen conductivity detection module (32) performs real-time hydrogen conductivity detection on the pretreated water sample received by the pretreated water sample receiving module (31). The hydrogen conductivity raw detection data transmission module (33) transmits the hydrogen conductivity raw detection data obtained by the real-time hydrogen conductivity detection module (32) to the associated data processing unit (5).

5. The high-purity water hydrogen conductivity analysis system based on electroregenerative ion exchange and micro-element analysis according to claim 4, characterized in that, The micro-element quantitative analysis unit (4) includes a water sample receiving module (41) after enrichment, a characteristic metal cation quantitative detection module (42), and a characteristic metal cation concentration data transmission module (43), wherein: The enriched water sample receiving module (41) receives the enriched water sample output by the micro-element analysis preprocessing unit (2); The characteristic metal cation quantitative detection module (42) performs quantitative detection on the characteristic metal cations dissolved from the electro-regenerated anode in the enriched water sample received by the enriched water sample receiving module (41). The characteristic metal cation concentration data transmission module (43) transmits the characteristic metal cation concentration data obtained by the characteristic metal cation quantitative detection module (42) to the associated data processing unit (5).

6. The high-purity water hydrogen conductivity analysis system based on electroregenerative ion exchange and micro-element analysis according to claim 5, characterized in that, The associated data processing unit (5) includes a multi-source data synchronous acquisition module (51), a dynamic molar conductivity traceability correction module (52), an operating condition linkage compensation and anomaly verification module (53), and an analysis result output module (54). The multi-source data synchronous acquisition module (51) synchronously acquires the real-time regeneration operating data of the electro-regeneration ion exchange purification unit (1), the original detection data of hydrogen conductivity of the hydrogen conductivity detection unit (3), and the characteristic metal cation concentration data of the micro-element quantitative analysis unit (4). The dynamic molar conductivity traceability correction module (52) adopts a dynamic molar conductivity traceability correction model based on electrochemical theory and improves it by combining the aging state quantification of ion exchange resin. It introduces a conductivity contribution amplification factor to dynamically correct the conductivity contribution calculation of characteristic metal cations, and performs quantitative calculation and mechanism-level correction on the conductivity increment introduced by the electro-regenerated anodic dissolution interference in the original hydrogen conductivity detection data, thus completing the calculation of the source of electro-regenerated anodic dissolution interference. The working condition linkage compensation and anomaly verification module (53) performs data processing by combining the dynamic update mechanism of compensation parameters of electric regeneration working condition linkage, threshold-triggered interference compensation and anomaly data verification mechanism. The analysis result output module (54) outputs the final analysis result of the hydrogen conductivity of high-purity water after source correction.

7. The high-purity water hydrogen conductivity analysis system based on electroregenerative ion exchange and micro-element analysis according to claim 6, characterized in that, The multi-source data synchronization acquisition module (51) includes a unified time-series synchronization acquisition submodule, a resin operating parameter extraction submodule, and a multi-source data regularization submodule, wherein: The unified timing synchronous acquisition submodule synchronously acquires real-time regeneration operating condition data, raw hydrogen conductivity detection data, and characteristic metal cation concentration data according to a unified sampling timing sequence. The resin operating parameter extraction submodule extracts the cumulative operating time of the ion exchange resin and the average regeneration current intensity from the real-time regeneration operating data. The multi-source data normalization submodule normalizes the synchronously collected data and transmits it to the dynamic molar conductivity traceability correction module (52).

8. The high-purity water hydrogen conductivity analysis system based on electroregeneration ion exchange and micro-element analysis according to claim 7, characterized in that, The dynamic molar conductivity traceability correction module (52) includes the following steps for dynamic correction of the characteristic metal cation conductivity contribution and quantitative calculation and mechanism-level correction of conductivity increment: S52.1 Determining the conductivity contribution amplification factor based on the aging state of ion exchange resin ; S52.2, Combining conductivity contribution amplification factor Real-time molar conductivity of characteristic metal cations Perform dynamic correction; S52.3, Based on the corrected real-time molar conductivity Solving for the conductivity increment introduced by the electro-regenerated anolyte dissolution interference in the raw hydrogen conductivity detection data. ; S52.4, Based on Incremental Conductivity Mechanism-level correction was performed on the raw hydrogen conductivity data to obtain source-corrected hydrogen conductivity data. And complete the calculation of the sources of interference from anodic dissolution during electroregeneration.

9. The high-purity water hydrogen conductivity analysis system based on electroregeneration ion exchange and micro-element analysis according to claim 8, characterized in that, The working condition linkage compensation and anomaly verification module (53) includes a working condition linkage parameter update submodule, a threshold trigger interference compensation submodule, and an anomaly data verification and filtering submodule, wherein: The working condition linkage parameter update submodule dynamically updates the compensation parameters of the dynamic molar conductivity traceability correction model based on real-time regeneration working condition data. The threshold-triggered interference compensation submodule performs corresponding interference compensation operations based on the characteristic metal cation concentration threshold. The abnormal data verification and screening submodule verifies the validity of the characteristic metal cation concentration data and transmits the valid data to the dynamic molar conductivity traceability and correction module (52).

10. A method for analyzing the hydrogen conductivity of high-purity water based on electroregenerative ion exchange and microelement analysis, based on the high-purity water hydrogen conductivity analysis system based on electroregenerative ion exchange and microelement analysis as described in any one of claims 1-9, characterized in that, Includes the following steps: S1. The high-purity water sample is purified online using electro-regeneration cation exchange technology to replace and remove non-hydrogen cations in the high-purity water sample. At the same time, the ion exchange resin is continuously regenerated online, and the purified water sample is output. Real-time regeneration data is collected and transmitted simultaneously. S2. Receive the purified water sample, perform same-source branch pretreatment on the purified water sample, remove dissolved interfering gases from one of the purified water samples and output the pretreated water sample, and enrich the characteristic metal cations dissolved from the electroregenerated anode of the other purified water sample and output the enriched water sample. S3. Receive the pretreated water sample, perform real-time hydrogen conductivity detection on the pretreated water sample, output the raw hydrogen conductivity detection data and complete the transmission. S4. Receive the enriched water sample, quantitatively detect the characteristic metal cations dissolved from the electro-regenerated anode in the enriched water sample, output the characteristic metal cation concentration data and complete the transmission. S5. Simultaneously acquire real-time regeneration operating condition data, raw hydrogen conductivity detection data, and characteristic metal cation concentration data. Collect the above three types of data synchronously according to a unified sampling sequence. Extract the cumulative running time of the ion exchange resin and the average regeneration current intensity from the real-time regeneration operating condition data. Regularize the various types of data after synchronous collection. S6. A dynamic molar conductivity source correction model based on electrochemical theory is adopted and improved by combining the aging state quantification of ion exchange resin. A conductivity contribution amplification factor is introduced to dynamically correct the conductivity contribution calculation of characteristic metal cations. First, the conductivity contribution amplification factor is determined based on the aging state quantification of ion exchange resin. Then, the real-time molar conductivity of characteristic metal cations is dynamically corrected based on the conductivity contribution amplification factor. Subsequently, the conductivity increment introduced by the electro-regenerated anodic dissolution interference in the original hydrogen conductivity detection data is calculated based on the corrected real-time molar conductivity. Finally, the original hydrogen conductivity detection data is corrected at the mechanism level based on the conductivity increment to obtain the source-corrected hydrogen conductivity data. At the same time, the source of electro-regenerated anodic dissolution interference is calculated. S7. Based on the real-time operating data of regeneration, dynamically update the compensation parameters of the dynamic molar conductivity traceability correction model, perform corresponding interference compensation operations according to the characteristic metal cation concentration threshold, verify the validity of the characteristic metal cation concentration data, and transmit the verified valid data to the dynamic molar conductivity traceability correction model to participate in the correction process. S8. Output the final analysis results of the hydrogen conductivity of high-purity water after source correction.

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