Method for monitoring trace arsenic in smelting wastewater in real time based on electrochemical sensing array

Abstract

The invention discloses a smelting wastewater trace arsenic real-time monitoring method based on an electrochemical sensing array, and relates to the technical field of electrochemical detection.The method comprises the steps that bypass sample flow is established through a peristaltic pump and pre-filtered, and stable sample flow is obtained; the sample flow is divided into a first passage and a second passage, and a form distinguishing sample flow is obtained after oxidation setting and medium equalization; performing short-time adsorption equilibrium to obtain an interface state parameter set, executing multi-segment coded deposition control based on the parameter set, and collecting a dissolution current curve; a dissolution signal set is obtained by applying single-frequency perturbation signals, characteristic peak parameters are extracted and subjected to correlation calculation with a multi-section response matrix, the total arsenic concentration and the pentavalent arsenic concentration are calculated through a weighted inversion algorithm, and a confidence interval is obtained; and calculating the concentration of the trivalent arsenic and determining an uncertainty range according to the two. According to the method, the quality judgment result is linked with the dynamic adjustment of the sampling flow, the potential amplitude and the deposition duration, so that the self-adaptive optimization control of the detection process is realized.

Description

Technical Field

[0001] This invention relates to the field of electrochemical detection technology, and in particular to a method for real-time monitoring of trace arsenic in smelting wastewater based on an electrochemical sensor array. Background Technology

[0002] With the rapid development of the metallurgical and non-ferrous metal industries, the problem of trace arsenic emissions in smelting wastewater has become increasingly prominent. Arsenic is highly toxic and persistent, and its forms include trivalent arsenic, pentavalent arsenic, and organic arsenic compounds. The toxicological characteristics of different valence states differ significantly. Therefore, real-time monitoring and speciation identification of arsenic have become important research directions in the field of environmental monitoring. Currently, mainstream detection methods include atomic absorption spectrometry, mass spectrometry, and photometry. Although these methods have high sensitivity, they usually rely on complex sample pretreatment and offline experimental conditions, making it difficult to achieve real-time on-site detection. Electrochemical sensing technology, due to its rapid response, low cost, and ease of integration, has gradually become a research hotspot for the monitoring of trace arsenic in smelting wastewater. In particular, electrochemical detection based on multi-electrode arrays provides a new approach for the simultaneous determination of multiple arsenic speciations.

[0003] However, existing electrochemical detection technologies still have two limitations in complex systems of smelting wastewater. First, traditional methods often rely on fixed potentials or single-step dissolution strategies, making it difficult to accurately distinguish between different valence states of arsenic in a single array. They are also susceptible to the influence of associated ions and electrode activation states, leading to drift in detection results or inaccurate speciation identification. Second, existing devices are mostly open-loop operations, lacking real-time feedback control of the sampling fluid state, electrode response, and deposition conditions. They cannot adaptively optimize parameters based on detection errors and signal uncertainties, resulting in poor long-term operational stability. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a real-time monitoring method for trace arsenic in smelting wastewater based on an electrochemical sensor array, which solves the problems of insufficient morphological differentiation accuracy and lack of real-time correction and parameter adaptation capabilities in the existing technology.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: This invention provides a method for real-time monitoring of trace arsenic in smelting wastewater based on an electrochemical sensor array, which includes establishing a bypass sample flow using a peristaltic pump, performing pre-filtration, and obtaining a stable sample flow. The stable sample flow is divided into a first channel and a second channel for oxidation tuning and medium equalization to obtain a morphology-distinguished sample flow. The morphologically differentiated sample streams were subjected to short-term adsorption equilibrium to obtain a set of interface state parameters. Multi-segment coded deposition control is performed based on the interface state parameter set to obtain multi-segment response matrices, dissolution current curves are acquired, and single-frequency perturbation signals are applied to obtain dissolution signal sets. Characteristic peak parameters are extracted from the leaching signal set, and the characteristic peak parameters are correlated with the multi-segment response matrix to obtain the channel response signal vector. The total arsenic concentration and pentavalent arsenic concentration are calculated using a weighted inversion algorithm. The concentration of trivalent arsenic was calculated based on the total arsenic concentration and the concentration of pentavalent arsenic, and the monitoring results were obtained by covariance propagation.

[0007] As a preferred embodiment of the real-time monitoring method for trace arsenic in smelting wastewater based on electrochemical sensor arrays described in this invention, the specific steps for establishing a bypass sample flow using a peristaltic pump, performing pre-filtration, and obtaining a stable sample flow are as follows. A bypass sample flow is established by a peristaltic pump, the pump speed is corrected by a proportional-integral method, a constant negative pressure is maintained by a micro vacuum pump, bubbles and dissolved gases are continuously removed, and a degassed sample flow is obtained. The degassed sample stream is subjected to multi-stage filtration, and the fluid stability index is calculated. The sample stream is then judged based on the fluid stability index to obtain a stable sample stream.

[0008] As a preferred embodiment of the real-time monitoring method for trace arsenic in smelting wastewater based on electrochemical sensor arrays according to the present invention, the steps of dividing the stable sample stream into a first channel and a second channel, performing oxidation tuning and media equalization, and obtaining a speciation-differentiated sample stream are as follows. A stable sample stream is connected to an equal resistance shunt, and the valve position is finely adjusted through the closed loop of the controller to obtain the first and second paths. The pH of the mixture is adjusted in a closed-loop manner using a controller to obtain an acidified second pathway. The acidified second pathway is then oxidized and tuned to obtain an oxidized second pathway. Based on the first pathway and the second pathway after oxidation tuning, a medium equalization operation is performed to obtain a morphology-distinguished sample flow.

[0009] As a preferred embodiment of the real-time monitoring method for trace arsenic in smelting wastewater based on electrochemical sensor arrays according to the present invention, the specific steps for applying a constant potential preprocessing signal to the speciation sample stream and obtaining the interface state parameter set are as follows: The morphology-differentiated sample stream is fed into an electrochemical sensing array, a constant potential preprocessing signal is applied, and the interfacial adsorption stability index is obtained. When the interface adsorption stability index is greater than or equal to the adsorption stability threshold, the electrode baseline potential, the amount of adsorbed charge per unit area, and the background current are recorded to obtain the interface state parameter set.

[0010] As a preferred embodiment of the real-time monitoring method for trace arsenic in smelting wastewater based on electrochemical sensor arrays according to the present invention, the specific steps for obtaining a multi-segment response matrix by performing multi-segment coded deposition control based on an interface state parameter set are as follows. Multi-segment potential encoding calculation is performed based on the interface state parameter set to calculate the instantaneous potential during the deposition stage; Multi-segment coded deposition is performed based on the instantaneous potential of the deposition stage. Key feature values ​​of peak current, steady current and integrated charge of each segment are extracted. The key feature values ​​of all segments are combined in time order to obtain the multi-segment response matrix.

[0011] As a preferred embodiment of the real-time monitoring method for trace arsenic in smelting wastewater based on electrochemical sensor arrays described in this invention, the specific steps for acquiring the dissolution current curve, applying a single-frequency micro-perturbation signal, and obtaining the dissolution signal set are as follows. A linear potential signal is applied, the dissolution current curve is acquired, a single-frequency perturbation signal is applied, and the sensitivity correction coefficient is calculated. The current value corresponding to the highest point of the peak in the dissolution current curve is taken as the dissolution peak current. The dissolution peak current is then calibrated by a sensitivity correction coefficient to obtain the dissolution signal set.

[0012] As a preferred embodiment of the real-time monitoring method for trace arsenic in smelting wastewater based on electrochemical sensor arrays described in this invention, the specific steps for extracting characteristic peak parameters from the leaching signal set and correlating these parameters with a multi-segment response matrix to obtain the channel response signal vector are as follows: Based on the dissolution signal set, characteristic peaks are extracted to identify the positions of the main peak, shoulder peak, and secondary peak in the dissolution curve, and the characteristic peak parameter set is obtained. The characteristic peak parameter set is correlated with the multi-segment response matrix. The dissolution peak signal is matched with the corresponding segment signal in the multi-segment response matrix through a cross-correlation algorithm to obtain the channel response signal vector.

[0013] As a preferred embodiment of the real-time monitoring method for trace arsenic in smelting wastewater based on electrochemical sensor arrays described in this invention, the specific steps for calculating the total arsenic concentration and pentavalent arsenic concentration using a weighted inversion algorithm are as follows. Linear regression was performed on the dissolution peak current to calculate the sensitivity coefficient. The sensitivity coefficients of the three detection cells were combined to obtain a multi-channel sensitivity matrix. The total arsenic concentration and pentavalent arsenic concentration were obtained by weighted inversion calculation of the peak area or peak height of the three detection cells and the multi-channel sensitivity matrix.

[0014] As a preferred embodiment of the real-time monitoring method for trace arsenic in smelting wastewater based on electrochemical sensor arrays described in this invention, the specific steps for calculating the trivalent arsenic concentration based on the total arsenic concentration and pentavalent arsenic concentration, and obtaining the monitoring result set through covariance propagation, are as follows. The difference between the total arsenic concentration and the pentavalent arsenic concentration is taken as the trivalent arsenic concentration, and the uncertainty of the trivalent arsenic concentration is calculated according to the variance propagation principle. Based on the principles of mass conservation and morphological consistency, the total arsenic concentration, pentavalent arsenic concentration, trivalent arsenic concentration, and uncertainty are determined to obtain a set of monitoring results.

[0015] As a preferred embodiment of the real-time monitoring method for trace arsenic in smelting wastewater based on an electrochemical sensor array according to the present invention, the steps for determining the total arsenic concentration, pentavalent arsenic concentration, trivalent arsenic concentration, and uncertainty based on the principles of mass conservation and speciation consistency, and obtaining a monitoring result set, are as follows: The concentrations of trivalent arsenic and pentavalent arsenic are summed and compared with the total arsenic concentration. If the relative deviation does not exceed the acceptable deviation threshold and the uncertainty of the trivalent arsenic concentration is less than the uncertainty threshold of trivalent arsenic, then the quality requirements are deemed to be met. If the relative deviation is greater than the acceptable deviation threshold but less than or equal to the retest deviation threshold, or if the confidence intervals calculated for different forms of arsenic partially overlap numerically, it is determined that a retest is required. If the relative deviation of two consecutive cycles exceeds the acceptable deviation threshold, it is determined to be in-situ regeneration.

[0016] The beneficial effects of this invention are as follows: by calculating the difference between the total arsenic concentration and the pentavalent arsenic concentration as the trivalent arsenic concentration, and by introducing variance propagation to calculate the uncertainty, the accurate differentiation and quantification of multivalent arsenic in a single array is achieved; by setting dual threshold judgment conditions of relative deviation and confidence interval, automatic consistency verification of morphology recognition results is achieved; and by linking the quality judgment results with the dynamic adjustment of sampling flow rate, potential amplitude and deposition duration, adaptive optimization control of the detection process is achieved. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a method for real-time monitoring of trace arsenic in smelting wastewater based on an electrochemical sensor array.

[0019] Figure 2A flowchart for the formation of a stable sample flow and medium equalization.

[0020] Figure 3 A flowchart for morphological differentiation of sample flow preparation and interface state formation.

[0021] Figure 4 This is a flowchart for multi-segment coded deposition and dissolution detection.

[0022] Figure 5 This is a comparison chart of the true and calculated values ​​of trivalent arsenic.

[0023] Figure 6 This is a comparative graph showing the variation of the relative error of trivalent arsenic with the period under different strategies. Detailed Implementation

[0024] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0025] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0026] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0027] Reference Figures 1-6 This is one embodiment of the present invention, which provides a method for real-time monitoring of trace arsenic in smelting wastewater based on an electrochemical sensor array, comprising the following steps: S1. A bypass sample flow is established using a peristaltic pump for pre-filtration to obtain a stable sample flow.

[0028] A bypass interface is opened on the downstream branch of the main discharge pipeline for smelting wastewater. A PTFE (polytetrafluoroethylene) tee connector is used to connect the inert sampling pipeline to the main pipeline. To ensure fluid shear stability, straight pipe sections with a length 15 times the pipe diameter are installed before and after the tee interface to eliminate eddy current interference and inlet disturbance. A precision peristaltic pump is installed in series in the inert sampling pipeline. The output flow rate of the precision peristaltic pump is used as the sampling flow rate. The flow signal is detected in real time by a built-in flow sensor, and closed-loop regulation is performed by a microcontroller. A proportional-integral method is used to correct the pump speed, keeping the output flow rate constant and preventing flow fluctuations. The tolerance exceeds ±1%. To prevent air bubbles from entering during the detection process, a degassing device is installed at the end of the sampling pipeline. A polytetrafluoroethylene (PTFE) microporous membrane is used as the gas-liquid separation medium. An inert negative pressure chamber is connected to the outside of the gas-liquid separation medium. A micro vacuum pump maintains a constant negative pressure to continuously remove air bubbles and dissolved gases, obtaining a degassed sample stream. The degassed sample stream undergoes multi-stage filtration, passing sequentially through a 50μm metal mesh primary filter layer, a 5μm polyethersulfone membrane secondary filter layer, and a 0.45μm PTFE final filter layer to remove suspended particles and solid impurities, ensuring that the liquid is clean, free of particles and air bubbles during electrochemical detection.

[0029] Flow and pressure are detected at the filter outlet. The flow and pressure fluctuations per unit time are calculated by a microcontroller to obtain the fluid stability index, expressed as: ;

[0030] in, Indicates fluid stability index. Indicates the standard deviation of flow rate. Indicates the standard deviation of pressure. Indicates the target traffic. This represents steady-state pressure.

[0031] It should be noted that the target traffic The parameters are determined comprehensively based on pipeline size, sampling length, liquid viscosity, and pump flow rate adjustment accuracy, ensuring that the fluid remains in a laminar flow state within the pipe, pressure fluctuations do not exceed the allowable range, and the fluid stability index is greater than or equal to 0.98; steady-state pressure. The pressure signal is detected in real time by a pressure sensor installed at the end of the sampling pipeline. The average value is obtained after continuous sampling for a period of time under constant flow operation. When the flow rate is maintained at the set value and the pressure fluctuation is less than 5%, the average pressure is taken as the steady-state pressure.

[0032] When the fluid stability index is greater than or equal to 0.98, the flow is considered stable, and a stable sample flow is obtained.

[0033] It should be noted that when the fluid stability index is between 0.95 and 0.98, the baseline drift increases significantly to 3% to 5%, and some channels show false peaks. When the fluid stability index is less than 0.95, the electrode response becomes unstable, the noise exceeds 1 μA, and effective quantification cannot be performed.

[0034] S2. Divide the stable sample flow into a first channel and a second channel, perform oxidation tuning and medium equalization, and obtain a morphology-differentiated sample flow.

[0035] A stable sample flow is connected to an equal resistance splitter. Using a PTFE dual-branch system with matched inner diameter and length, the stable sample flow is divided into two equal paths. Each path is equipped with a miniature mass flow meter and an electric needle valve downstream. The valve position is finely adjusted by the controller in a closed loop to ensure that the flow deviation does not exceed ±1% within 30 seconds, thus obtaining the first and second paths.

[0036] The first pathway does not involve any chemical addition; the sample enters directly into the manifold inlet of the three-cell system via an inert buffer section. A pH sensor and a conductivity sensor are installed on the pathway to monitor the sample matrix state in real time. When the relative fluctuations of pH and conductivity do not exceed 1% within 60 seconds of continuous monitoring, the controller automatically marks the pathway as morphology-ready, indicating that the sample can be directly used for total arsenic determination. The second pathway is equipped with a hydrochloric acid metering pump and an online pH probe. The pH of the mixed sample is adjusted and stabilized at 1.0±0.1 in a closed-loop manner by the controller. After the acid addition point, a static mixer and a short residence period are connected in series to obtain the acidified second pathway.

[0037] A 3wt% hydrogen peroxide micropump, an ORP electrode, and a sulfide ISE were installed in the second pathway section after acidification. The hydrogen peroxide dosing acceleration rate was calculated, and the second pathway after oxidation tuning was obtained. The expression is as follows: ; in, Indicates the acceleration rate of hydrogen peroxide dosing. Indicates the sample flow rate of the second path. Indicates the concentration of hydrogen peroxide solution. This represents the estimated trivalent arsenic concentration from the previous period. Indicates the stoichiometric safety factor. Indicates sulfide concentration. Indicates the rate of change of redox potential. This indicates the decreasing portion of the ORP. This represents the correction factor.

[0038] It should be noted that, The sample flow is measured blank without the addition of an oxidant. An approximate initial concentration value is derived from the electrode baseline current and the standard curve. At the end of each test, the trivalent arsenic concentration result calculated in this cycle is read to replace the old value of the previous cycle. It automatically corrects the theoretical stoichiometric equivalent based on real-time detected changes in the concentration of reducing substances and redox potential, thereby dynamically determining the stoichiometric safety factor for the current period, with a value range of [1.1, 1.3]. When the concentration is less than 1.1, the added oxidizing agent is lower than the stoichiometric amount required for complete reaction. This means that some trivalent arsenic cannot be completely oxidized to pentavalent arsenic, leaving a residual reducing component in the system. This can distort the subsequent determination of the arsenic valence ratio, leading to an underestimation of total arsenic or incorrect valence state identification. When the value is greater than 1.3, the oxidant is added in excess. In addition to wasting the reagent, it will also make the redox potential of the system too high, produce peroxidation side reactions or oxidation by-products, resulting in an increase in background current and noise in electrochemical detection, and may corrode the electrode surface or damage the composition of the solution matrix.

[0039] It should be noted that, This method records real-time potential values ​​at a fixed sampling period (e.g., 1 second). The instantaneous rate of change is obtained by dividing the potential difference between two adjacent samples by the time interval. The moving average of the rate of change over multiple consecutive points is taken as the current redox potential change rate. A positive result indicates increased oxidizing power of the system, while a negative result indicates that the oxidant is consumed and the reducing component increases. Only the negative value is taken as the redox potential change rate. Input; correction factor The value range is [0.1, 0.3]. When the value is less than 0.1, the response to changes in redox potential is too sluggish, failing to promptly correct the acceleration rate of hydrogen peroxide addition, resulting in a prolonged period of low ORP, incomplete oxidation of trivalent arsenic, and a tendency to produce residual or cumulative errors over time. When the value is greater than 0.3, the system overreacts to small fluctuations in ORP, and the dosage changes frequently, which can easily lead to over-adjustment, resulting in drastic potential fluctuations, excessive consumption of oxidant, and may enhance the peroxidation side reaction of the system, thereby increasing detection noise and damaging the electrode surface.

[0040] To ensure uniform mixing of acid and oxidant within a small volume flow channel, a static mixer and an isochoric residence section are connected in series after the oxidation dosing point. The static mixing tube is equipped with spiral baffles to allow the acid and oxidant to be split and recombined multiple times within a short period, achieving thorough mixing within a very small volume. After entering the isochoric residence section, the sample flow is maintained for 5–10 seconds to ensure the oxidation reaction proceeds fully. Real-time changes in acidity and conductivity are simultaneously collected using an online pH electrode and conductivity sensor, and their fluctuation range within a fixed time window is calculated. When the fluctuations in real-time acidity and conductivity are minimal and stable, the mixing process is considered to have reached a media equilibrium state, with a media equilibrium coefficient close to 1, indicating that acidity and ion concentration are sufficiently uniform in the fluid. If significant fluctuations in acidity or conductivity are still detected, the residence time is automatically extended or the flow rate is fine-tuned until the media equilibrium coefficient stabilizes above the equilibrium release threshold before release, allowing for the acquisition of morphologically differentiated sample flows.

[0041] It should be noted that the equilibrium release threshold is determined by continuously collecting pH and conductivity data over a period of time and calculating the correlation between the fluctuation amplitude and the stability of the subsequent electrochemical signal. When the relative fluctuation amplitude of acidity and conductivity is less than 1% and the relative standard deviation of the corresponding detection signal is less than 2%, the medium is considered to be sufficiently homogeneous. At this time, the medium equilibrium coefficient is approximately 0.95, which is used as the equilibrium release threshold.

[0042] S3. Perform short-term adsorption equilibrium on the morphologically differentiated sample streams to obtain the interface state parameter set.

[0043] The morphology-differentiated sample stream is fed into an electrochemical sensing array, which consists of three independent detection cells, each equipped with a flow electrode assembly. The flow rates of the three detection cells are precisely adjusted to 2.0 mL / min using a mass flow control valve, and the temperature is maintained at 25 ± 0.2 °C to ensure consistent flow conditions between the cells. Detection cell 1 uses a gold-modified glassy carbon electrode for the total arsenic response; detection cell 2 uses a bismuth oxide nanofilm-modified electrode for the As(III) selective response; and detection cell 3 uses a tin oxide composite film-modified electrode for the As(V) response.

[0044] A constant potential pretreatment signal was applied to the three sets of electrodes in sequence to form an adsorption activation layer on the electrode surface. The function of the constant potential pretreatment signal is to remove residual oxides on the surface and induce trace amounts of arsenic ions or matrix anions to form an initial adsorption film at the active site, thereby establishing a stable interface state.

[0045] To determine if the electrode surface has reached a stable state, current-time curves are recorded during the constant potential phase, the rate of change of the adsorption process is calculated, and the interfacial adsorption stability index is obtained, expressed as: ; in, Indicates the adsorption stability index. Indicates the preprocessing duration. This represents the instantaneous current during the constant potential phase, obtained by sampling from the constant potential controller. This represents the steady-state current, specifically the average current over the last 5 seconds of the constant potential phase. The time independent variable represents continuous integration.

[0046] It should be noted that the preprocessing duration The method detects that the rate of change of current continuously decreases and tends to stabilize over several consecutive sampling periods (e.g., 5 seconds). The time interval before and after the stabilization point is used as the candidate duration interval, and the upper limit of the candidate duration interval is selected as the threshold. .

[0047] When the adsorption stability index is greater than or equal to the adsorption stability threshold of 0.98, it indicates that the electrochemical state of the electrode surface is stable. The electrode baseline potential, adsorbed charge per unit area, and background current are recorded to obtain the interface state parameter set. The electrode baseline potential is obtained by stopping the constant potential signal when the electrode surface reaches a stable adsorption state, and immediately switching to an open-circuit state after disconnecting the constant potential. Electrode potential signals are continuously acquired for 5 seconds in the open-circuit state, and the acquired signals are averaged to obtain the electrode baseline potential. The adsorbed charge per unit area is obtained by recording the current-time curve during the constant potential pretreatment and analyzing the current-time curve throughout the pretreatment process. The total adsorbed charge was obtained by integrating over time, and the ratio of the total adsorbed charge to the effective reaction area of ​​the electrode was taken as the adsorbed charge per unit area. The background current was obtained after the electrode reached adsorption equilibrium, the sample flow was switched to an inert carrier liquid (without arsenic ions), and the constant potential condition was maintained for about 10 seconds. The average steady-state current at this time was recorded as the background current. The adsorption stability threshold was defined as 0.98, when the current fluctuation amplitude was less than 2%, the electrode surface was in a stable adsorption state, and the repeatability of the subsequent detection signal was better than 2%. Further increasing the adsorption stability threshold had limited improvement but would significantly increase the pretreatment time. Therefore, 0.98 was taken as the release standard for adsorption stability.

[0048] S4. Perform multi-segment coded deposition control based on the interface state parameter set, obtain multi-segment response matrices, acquire dissolution current curves, apply single-frequency micro-perturbation signals, and acquire dissolution signal sets.

[0049] Multi-segment coded deposition control was performed on the three sets of detection cells. Using the electrode baseline potential from the interface state parameter set as the reference potential, a potential sequence containing multiple segments of variable polarity was generated, expressed as follows: ; in, Indicates the instantaneous potential during the deposition stage. Indicates the electrode baseline potential. Indicates the potential amplitude. Indicates the duration of deposition. This indicates the phase encoding angle.

[0050] It should be noted that the potential amplitude The amplitude is automatically calculated based on the current response intensity and signal stability of the previous cycle. When the detection signal is weak or the noise is high, the amplitude is automatically increased to enhance the deposition driving force; when the signal is too strong or current fluctuations occur, the amplitude is automatically decreased to prevent side reactions. The deposition duration is also calculated automatically. By analyzing the current change curve in real time, when the deposition current tends to stabilize within a continuous sampling period and the rate of change is less than 2%, the deposition process is determined to have reached equilibrium, and this duration is taken as the deposition duration of this segment; phase encoding angle When the three detection cells are running in parallel, the main controller first uses the signal sequence of the first detection cell as the phase reference, and then staggers the phases of the second and third detection cells by a fixed angle, so that the potential changes of the three cells are staggered in time, avoiding electrochemical noise coupling and improving signal resolution. If the correlation coefficient of the current waveforms of any two cells is found to be higher than 0.8 during operation, the phase angle is reallocated to keep the cross-correlation interference between adjacent channels to a minimum. The correlation coefficient of the current waveforms of any two cells is obtained by synchronously collecting the current signals of each detection cell within the same time window and performing normalization processing, and calculating the similarity of their changing trends.

[0051] During the control process, the sample flow in each detection cell is maintained at a constant flow rate (2 mL / min) and a constant temperature (25 °C). Three to five deposition potentials with different polarities and amplitudes are applied sequentially. The potentials are switched in sequence according to the coding sequence, so that arsenic in different valence states and accompanying metal ions in the sample flow are selectively deposited on different electrode materials according to the differences in the interface activation layer. During each deposition process, the current change signal is recorded in real time, and key feature values, including peak current, steady current and integrated charge, are extracted at the end of the deposition. The feature signals of all segments are combined in time sequence to form a multi-segment response matrix.

[0052] It should be noted that the peak current is a current time series recorded at a fixed sampling frequency. When the current rises to its maximum value, it is taken as the peak current. The average value is calculated as the steady current during the period when the current fluctuation is less than 2% in the later stage of deposition. The current curve is integrated over the entire deposition time to obtain the integrated charge.

[0053] After completing the multi-segment coded deposition, dissolution voltammetry scanning was immediately performed on each detection cell. The three detection cells maintained the same flow rate and temperature conditions. Simultaneously, using the baseline potential of each electrode as the starting potential, a linear potential signal was applied from the negative to the positive potential range at a fixed scan rate (e.g., 100 mV / s), and dissolution current curves were acquired synchronously. During the scanning process, a single-frequency perturbation signal was superimposed within the same potential range to obtain the electrode impedance characteristics. By measuring the phase difference and amplitude of the perturbation response current, the double-layer capacitance and charge transfer resistance of the electrode were calculated to reflect the activation state and interfacial transport capability of the electrode surface. The expressions are as follows: ; in, This represents the sensitivity correction coefficient. This represents the corrected dissolution peak current. This represents the original dissolution peak current. Indicates the electrode structure correction factor. Represents charge transfer resistance. Indicates double-layer capacitance. This represents the angular frequency of the perturbation signal.

[0054] It should be noted that, The sensitivity correction coefficient is calculated by synchronously acquiring the real-time values ​​of the electric double-layer capacitance and charge transfer resistance. The product of the original dissolution peak current and the sensitivity correction coefficient is then used as the... ; The current response curve of the working electrode is recorded in real time using high-frequency sampling (e.g., 1 kHz), and the current peak point in the curve is identified by a signal analysis algorithm. The current peak point corresponds to the maximum current generated when arsenic dissolves from the electrode surface, and the current value at the current peak point is used as the original dissolution peak current; electrode structure correction factor. This is achieved by reading the electrode's geometric dimensions (including electrode radius, surface roughness coefficient, and active area ratio) and the effective volume of the fluid channel. Then, using a standard electrolyte (e.g., 1 mol / L KCl), the reference impedance of the electrode under standard conditions is measured. This reference impedance is then compared to the theoretical impedance of an ideal planar electrode to obtain the required impedance. .

[0055] After the dissolution scan is completed in each detection cell, the dissolution peak signal is calibrated for sensitivity to obtain the impedance-compensated dissolution signal value. The calibrated dissolution signals from all detection cells are arranged in potential order to form a dissolution signal set.

[0056] S5. Extract characteristic peak parameters from the leaching signal set, correlate the characteristic peak parameters with the multi-segment response matrix to obtain the channel response signal vector, and use a weighted inversion algorithm to calculate the total arsenic concentration and pentavalent arsenic concentration.

[0057] Based on the dissolution signal set, characteristic peak extraction is performed on the dissolution curve of each detection cell to identify the positions of the main peak, shoulder peak, and secondary peak in the dissolution curve. Characteristic parameters such as peak potential, peak height, half-maximum width, and peak area are recorded to obtain a characteristic peak parameter set. This characteristic peak parameter set is then correlated with a multi-segment response matrix. A cross-correlation algorithm is used to match the dissolution peak signal with the corresponding segment signal in the multi-segment response matrix to obtain the purified channel response signal vector, expressed as: ; in, This represents the purified channel response signal vector. This represents the transpose of a multi-segment response matrix. This represents the relevant weight vector.

[0058] It should be noted that, The process involves reading the time and phase parameters of each deposition segment recorded in the previous cycle, realigning the time axis of the dissolution curve in the current cycle to the encoding time axis, calculating the cross-correlation coefficient between the response signal and the encoded waveform of each segment to obtain the correlation intensity value of each segment, standardizing these correlation coefficients into a weighted sequence of 0 to 1, and arranging them in chronological order to construct a correlation weight vector.

[0059] After obtaining the purified channel response signal, the peak area or peak height of each detection cell is weighted and inverted with the multi-channel sensitivity matrix to obtain the total arsenic concentration and pentavalent arsenic concentration, expressed as: ; in, Indicates the total arsenic concentration. Indicates the concentration of pentavalent arsenic. This represents the multi-channel sensitivity matrix.

[0060] It should be noted that, The method involves injecting trivalent and pentavalent arsenic standard solutions of known concentrations into each detection cell. While maintaining constant flow rate, temperature, and potential, a stripping voltammetry scan is performed to collect the stripping peak current after impedance correction. Linear regression is then performed on the concentration of each set of standard solutions and the corresponding current signal to calculate the sensitivity coefficient of each detection cell. The sensitivity coefficients of the three sets of detection cells are arranged according to the response type (total arsenic, trivalent arsenic, pentavalent arsenic) to form a multi-channel sensitivity matrix.

[0061] By leveraging the relationship between the fluctuation of peak parameters and the uncertainty propagation of impedance measurements, a corresponding confidence interval is generated, expressed as: ; in, Indicates the confidence interval. This represents the standard normal distribution coefficient, corresponding to the boundary values ​​of the two intervals at a 95% confidence level. This represents the variance of the total arsenic concentration, i.e., the uncertainty of the total arsenic concentration. This represents the variance of pentavalent arsenic concentration, i.e., the uncertainty of pentavalent arsenic concentration.

[0062] S6. Calculate the trivalent arsenic concentration based on the total arsenic concentration and the pentavalent arsenic concentration, and perform covariance propagation to obtain the monitoring result set.

[0063] The difference between the total arsenic concentration and the pentavalent arsenic concentration is taken as the trivalent arsenic concentration. The statistical variance of the trivalent arsenic concentration is calculated using the variance propagation principle, and the uncertainty of the trivalent arsenic concentration is obtained, expressed as: ; in, Indicates the concentration of trivalent arsenic. This represents the covariance between the total arsenic concentration and the pentavalent arsenic concentration. This indicates the uncertainty of the trivalent arsenic concentration.

[0064] like Figure 5 The results show that under different trivalent arsenic ratios, the calculated trivalent arsenic concentration exhibits an approximately linear relationship with the actual trivalent arsenic concentration. The data points are generally distributed near the ideal consistency reference line, indicating that it is feasible to invert the trivalent arsenic concentration using the difference between the total arsenic channel and the pentavalent arsenic channel. Error bars represent confidence intervals obtained through variance propagation. It can be seen that in most samples, the actual concentration falls within the confidence interval, indicating that the present invention reasonably characterizes measurement errors and the correlation between channels. A magnified view shows that under different trivalent arsenic ratios, the data points are distributed in a narrow band around the consistency reference line, indicating that the array can still maintain good linear response and discrimination ability under various valence ratios. The magnified view also shows that under different trivalent arsenic ratios, the data points are distributed in a narrow band around the consistency reference line, indicating that the array can still maintain good linear response and discrimination ability under various valence ratios.

[0065] Based on the principles of mass conservation and consistency of arsenic forms, the total arsenic concentration, pentavalent arsenic concentration, trivalent arsenic concentration, and uncertainty are determined. The trivalent arsenic concentration and pentavalent arsenic concentration are summed and compared with the total arsenic concentration. If the relative deviation does not exceed the acceptable deviation threshold and the uncertainty of the trivalent arsenic concentration is less than the trivalent arsenic uncertainty threshold, then the quality requirements are met. If the relative deviation is greater than the acceptable deviation threshold but less than or equal to the retest deviation threshold, or if the confidence intervals calculated for different forms of arsenic (such as trivalent and pentavalent arsenic) partially overlap numerically, it indicates insufficient differentiation between the two forms of concentration, making it impossible to determine that the difference between the two forms of concentration is statistically significant, and a retest is required. If the relative deviation exceeds the acceptable deviation threshold for two consecutive periods, or if an interfacial impedance change exceeding 10% is detected in the same period, in-situ regeneration is performed, and the working electrode surface is reactivated.

[0066] It should be noted that the acceptable deviation threshold is formed by continuously recording the differences between the total arsenic concentration and the concentrations of trivalent and pentavalent arsenic under long-term stable operating conditions, resulting in a relative deviation distribution. The mean and standard deviation of the deviation distribution are calculated. When the relative deviation distribution exhibits a stable normal distribution, the upper bound of the relative deviation distribution is determined as the acceptable deviation threshold based on the principle of three times the standard deviation. The retest deviation threshold is determined by selecting a high quantile (such as the 95th or 97.5th percentile of the deviation distribution) in the relative deviation distribution and setting the relative deviation value corresponding to the high quantile as the retest deviation threshold. The trivalent arsenic uncertainty threshold uses the background noise amplitude of the electrode under steady-state conditions as the lower limit of uncertainty, and refers to the concentration fluctuation range formed by the electrode in multiple repeated measurements to ensure that the trivalent arsenic uncertainty threshold includes normal instrument internal fluctuations. Combined with the slight interface changes that may occur during the long-term operation of the electrode, the maximum allowable fluctuation range is used as the upper limit of uncertainty, thus obtaining the trivalent arsenic uncertainty threshold.

[0067] The total arsenic concentration, trivalent arsenic concentration, pentavalent arsenic concentration, and confidence interval were combined to obtain the monitoring result set.

[0068] When the determination result indicates that retesting is required, resampling and a stripping voltammetry scan sequence are performed; when the determination result indicates in-situ regeneration, an electrode regeneration sequence is initiated, including reverse polarization rinsing, short-time oxidation potential pulse application, and inert solution circulation to restore electrode surface activity; if the determination meets quality requirements, adaptive parameter optimization is performed, dynamically adjusting the sampling flow rate, potential amplitude, and deposition duration, as expressed by: ; in, This indicates optimizing the objective function value. Indicates the sampling flow rate. This represents the half-width of the concentration confidence interval. This represents the average concentration value of the corresponding morphology. This represents the difference in concentration between trivalent and pentavalent arsenic. Indicates the energy consumption of the periodic electrode. This indicates the reference energy consumption.

[0069] It should be noted that, It is calculated from the concentration variance of the dissolution curve in multiple repeated samplings, and corrected by taking the standard normal distribution coefficient of 1.96 at a 95% confidence level; It is obtained by integrating the current-potential data of the dissolution curve; It is obtained by integrating the product of electrode current and potential during the deposition process over time; It is obtained by performing a complete deposition process under no-load or standard solution conditions during the device setup phase, and is calculated based on the time integral of the product of potential and current as a reference energy consumption.

[0070] After each cycle, the sampling flow rate, potential amplitude, and deposition duration are fine-tuned based on the optimization objective function value to minimize the optimization objective function value for the next cycle, thereby achieving adaptive optimization of the monitoring process.

[0071] like Figure 6 The relative error changes of trivalent arsenic in continuous detection cycles were compared between the fixed strategy and the adaptive strategy. Figure 6 The upper and middle figures show the complete time series. The fixed strategy exhibits significant error fluctuations, with the deviation intensifying in several periods. In contrast, the adaptive strategy, through real-time parameter linkage based on the quality judgment results, keeps the overall error within a narrow range. Figure 6 The lower part of the figure shows local details of a typical range. The local figure shows that the adaptive strategy has stronger error convergence in the fluctuation range and the peak amplitude is significantly lower than that of the fixed strategy. This indicates that when quality anomalies or uncertainty increase, the adaptive mechanism can effectively suppress error accumulation and improve long-term monitoring stability by increasing the deposition time or adjusting the sampling conditions.

[0072] In summary, this invention achieves accurate differentiation and quantification of multivalent arsenic in a single array by: calculating the difference between total arsenic concentration and pentavalent arsenic concentration as trivalent arsenic concentration and introducing variance propagation to calculate uncertainty; automatically verifying the consistency of morphology recognition results by setting dual threshold judgment conditions of relative deviation and confidence interval; and achieving adaptive optimization control of the detection process by linking the quality judgment results with the dynamic adjustment of sampling flow rate, potential amplitude, and deposition duration.

[0073] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for real-time monitoring of trace arsenic in smelting wastewater based on electrochemical sensor array, characterized in that: The method comprises the following steps: A bypass sample flow is established by a peristaltic pump, pre-filtering is performed, and a stable sample flow is obtained; The stable sample flow is divided into a first channel and a second channel, oxidation setting and medium balancing are performed, and a morphological separation sample flow is obtained; The morphological separation sample flow is subjected to short-time adsorption equilibrium, and an interface state parameter set is obtained; Based on the interface state parameter set, multi-segment coding deposition control is performed, a multi-segment response matrix is obtained, a dissolution current curve is collected, a single-frequency perturbation signal is applied, and a dissolution signal set is obtained; Feature peak parameters are extracted from the dissolution signal set, the feature peak parameters are associated with the multi-segment response matrix for calculation, a channel response signal vector is obtained, and a total arsenic concentration and a pentavalent arsenic concentration are calculated by using a weighted inversion algorithm; The trivalent arsenic concentration is calculated according to the total arsenic concentration and the pentavalent arsenic concentration, and a monitoring result set is obtained through covariance propagation.

2. The real time monitoring of trace arsenic in smelting wastewater based on electrochemical sensor array as claimed in claim 1 wherein: The bypass sample flow is established by the peristaltic pump, pre-filtering is performed, and a stable sample flow is obtained, and the specific steps are as follows: A bypass sample flow is established by a peristaltic pump, a proportional integral method is used to correct the pump speed, a constant negative pressure is maintained by a micro vacuum pump, air bubbles and dissolved gas are continuously removed, and a degassed sample flow is obtained; The degassed sample flow is subjected to multi-stage filtering, fluid stability indexes are calculated, the sample flow is judged based on the fluid stability indexes, and a stable sample flow is obtained.

3. The real time monitoring of trace arsenic in smelting wastewater based on electrochemical sensor array as claimed in claim 2 wherein: The stable sample flow is divided into a first channel and a second channel, oxidation setting and medium balancing are performed, and a morphological separation sample flow is obtained, and the specific steps are as follows: The stable sample flow is connected to an equal-resistance flow divider, a first channel and a second channel are obtained by closed-loop fine adjustment of the valve position of the controller; The pH after mixing is adjusted in a closed loop mode by the controller, the second channel after acidification is obtained, the second channel after acidification is subjected to oxidation setting, and the second channel after oxidation setting is obtained; Medium balancing is performed based on the first channel and the second channel after oxidation setting, and a morphological separation sample flow is obtained.

4. The real time monitoring of trace arsenic in smelting wastewater based on electrochemical sensor array as claimed in claim 3 wherein: The morphological separation sample flow is subjected to short-time adsorption equilibrium, and an interface state parameter set is obtained, and the specific steps are as follows: The morphological separation sample flow is sent into an electrochemical sensing array, a constant potential pretreatment signal is applied, and an interface adsorption stability index is obtained; When the interface adsorption stability index is greater than or equal to an adsorption stability threshold value, an electrode baseline potential, a unit area adsorption charge quantity, and a background current are recorded, and an interface state parameter set is obtained.

5. The real time monitoring of trace arsenic in smelting wastewater based on electrochemical sensor array as claimed in claim 4 wherein: Based on the interface state parameter set, multi-segment coding deposition control is performed, and a multi-segment response matrix is obtained, and the specific steps are as follows: Based on the interface state parameter set, multi-segment potential coding calculation is performed, and a deposition stage instantaneous potential is calculated; Based on the deposition stage instantaneous potential, multi-segment coding deposition is performed, key characteristic values of peak current, stable current, and integral charge quantity of each segment are extracted, all the key characteristic values are combined in time sequence, and a multi-segment response matrix is obtained.

6. The real time monitoring of trace arsenic in smelting wastewater based on electrochemical sensor array as claimed in claim 5 wherein: The dissolution current curve is collected, a single-frequency perturbation signal is applied, and a dissolution signal set is obtained, and the specific steps are as follows: A linear potential signal is applied, the dissolution current curve is collected, a single-frequency perturbation signal is applied, and a sensitivity correction coefficient is calculated; The current value corresponding to the highest point of the peak shape in the dissolution current curve is taken as a dissolution peak current, the dissolution peak current is subjected to sensitivity correction through the sensitivity correction coefficient, and a dissolution signal set is obtained.

7. The real time monitoring of trace arsenic in smelting wastewater based on electrochemical sensor array as claimed in claim 6 wherein: The characteristic peak parameters are extracted from the dissolution signal set, and the characteristic peak parameters are associated with the multi-segment response matrix for correlation calculation to obtain a channel response signal vector. Based on the dissolution signal set, characteristic peak extraction is performed to identify the positions of the main peak, shoulder peak and secondary peak in the dissolution curve to obtain a characteristic peak parameter set. The characteristic peak parameter set is associated with the multi-segment response matrix for correlation calculation, and the dissolution peak signal is matched with the corresponding segment signal in the multi-segment response matrix through cross-correlation algorithm to obtain a channel response signal vector.

8. The real time monitoring of trace arsenic in smelting wastewater based on electrochemical sensor array method as claimed in claim 7, wherein: The total arsenic concentration and the pentavalent arsenic concentration are calculated by using a weighted inversion algorithm, and the specific steps are as follows, The sensitivity coefficients of the three groups of detection cells are combined to obtain a multi-channel sensitivity matrix. The peak area or peak height of the three groups of detection cells is weighted and inversely calculated with the multi-channel sensitivity matrix to obtain the total arsenic concentration and the pentavalent arsenic concentration.

9. The real time monitoring of trace arsenic in smelting wastewater based on electrochemical sensor array as claimed in claim 8 wherein: The trivalent arsenic concentration is calculated according to the total arsenic concentration and the pentavalent arsenic concentration, and the monitoring result set is obtained through covariance propagation, and the specific steps are as follows, The difference between the total arsenic concentration and the pentavalent arsenic concentration is taken as the trivalent arsenic concentration, and the uncertainty of the trivalent arsenic concentration is calculated according to the principle of variance propagation; According to the principles of mass conservation and morphological consistency, the total arsenic concentration, the pentavalent arsenic concentration, the trivalent arsenic concentration and the uncertainty are determined to obtain the monitoring result set.

10. The real-time monitoring of trace arsenic in smelting wastewater based on electrochemical sensor array as claimed in claim 9 wherein: According to the principles of mass conservation and morphological consistency, the total arsenic concentration, the pentavalent arsenic concentration, the trivalent arsenic concentration and the uncertainty are determined to obtain the monitoring result set, and the specific steps are as follows, The trivalent arsenic concentration and the pentavalent arsenic concentration are summed and compared with the total arsenic concentration, if the relative deviation is not more than the qualified deviation threshold, and the uncertainty of the trivalent arsenic concentration is less than the trivalent arsenic uncertainty threshold, it is determined to meet the quality requirements; If the relative deviation is greater than the qualified deviation threshold and less than or equal to the retest deviation threshold, or when the confidence intervals calculated for different forms of arsenic partially overlap in value, it is determined to be retested; If the relative deviation of two consecutive periods exceeds the qualified deviation threshold, it is determined to be in-situ regeneration.

Images