An ASV heavy metal in-situ detection system and method considering the interference of groundwater environmental factors

Abstract

The present invention discloses an ASV heavy metal in-situ detection system and method that considers interference from groundwater environmental factors. The system includes an ASV sensor measurement module, an environmental factor data collection module, a data transmission module, an error compensation algorithm module, and a data integration intelligent processing module. The present invention utilizes the pH and temperature of nearby groundwater during in-situ measurement by the ASV sensor measurement module. An adaptive intelligent correction algorithm module uses the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module as inputs to an adaptive intelligent correction algorithm model. The adaptive intelligent correction algorithm model predicts the corrected measurement results to obtain a corrected result. This invention can significantly improve the accuracy and reliability of ASV heavy metal detection in groundwater.

Description

Technical Field

[0001] The present invention relates to the field of heavy metal in-situ measurement, and in particular to an ASV heavy metal in-situ detection system and method taking into account the interference of groundwater environmental factors. Background Art

[0002] Anodic stripping voltammetry (ASV), based on electrochemical principles, achieves quantitative analysis of heavy metal ions by precisely controlling electrode potential and current. This method has high sensitivity and low detection limit, and is capable of simultaneous detection of multiple parameters. In addition, ASV is easy to operate, and the entire detection process can usually be completed in a relatively short time. It is commonly used in rapid detection and emergency response of surface water / industrial wastewater. However, since anodic stripping voltammetry involves multiple reaction mechanisms and influencing factors in the electrochemical process, the test results have poor repeatability. In practical applications, not only must experimental conditions such as the state of the electrode, enrichment time, stirring speed and many other parameters be strictly controlled, but the influence of interfering factors in the water environment must also be minimized.

[0003] Typically, the ASV equipment testing process includes an equipment calibration process and target object detection. During the equipment calibration process, it is necessary to use the test results of blank samples and standard samples of specific concentrations to establish a standard curve model, and then use this model to predict the heavy metal concentration of the target sample. During the on-site or in-situ detection of heavy metals in groundwater, the temperature difference between the standard sample during the ground calibration process and the groundwater to be tested may exceed 10°C. It is well known that temperature differences may affect the electrode reaction rate and ion diffusion rate, thereby affecting the ASV measurement results. However, this interference factor is often ignored in the current ASV groundwater detection process. In addition, the supporting electrolyte and buffer solution added during the ASV test are usually fixed volumes. However, the pH of groundwater in contaminated sites usually varies widely. The added electrolytic buffer solution may be difficult to significantly eliminate the interference of coexisting ions, resulting in inaccurate test results. Summary of the Invention

[0004] In response to the above-mentioned deficiencies in the prior art, the present invention provides an ASV heavy metal in-situ detection system and method that takes into account the interference of groundwater environmental factors, which solves the problem that the existing ASV detection method does not consider the impact of temperature data and pH value on heavy metal detection, resulting in inaccurate detection results.

[0005] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0006] Provided is an ASV heavy metal in-situ detection system that takes into account the interference of groundwater environmental factors, which includes: an ASV sensor measurement module, an environmental factor data collection module, a data transmission module, an adaptive intelligent correction algorithm module and a data output module;

[0007] ASV sensor measurement module, including ASV sensor, for in-situ measurement of heavy metals in groundwater;

[0008] The environmental factor data collection module includes a pH sensor and a temperature sensor, which is used to collect pH and temperature data of groundwater near the measurement location when the ASV sensor measurement module performs in-situ measurement of heavy metals in groundwater;

[0009] A data transmission module, used to transmit the data obtained by the ASV sensor measurement module and the environmental factor data collection module to the adaptive intelligent correction algorithm module;

[0010] An adaptive intelligent correction algorithm module, including an adaptive intelligent correction algorithm model, is used to take the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module as input, and predict the corrected measurement results to obtain correction results;

[0011] The data output module is used to output the correction result obtained by the adaptive intelligent correction algorithm module as the final groundwater heavy metal measurement result.

[0012] Furthermore, the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module are used as input, and the specific method for predicting the corrected measurement results is as follows:

[0013] The in-situ measurement results of heavy metals obtained by the ASV sensor measurement module and the environmental factor data collection module, and the pH and temperature data of groundwater near the measurement location are used as the input of the trained adaptive intelligent correction algorithm model, and the output of the trained adaptive intelligent correction algorithm model is used as the correction result to complete the correction of the measurement results of the ASV sensor measurement module; the adaptive intelligent correction algorithm model is an MLP multi-layer perceptron regression model.

[0014] Furthermore, the training method of the adaptive intelligent correction algorithm model is:

[0015] Based on the measuring range of the ASV sensor, samples with known heavy metal concentrations at different temperatures and pH values ​​were tested in the laboratory within each measuring range to obtain a number of sample test data. The sample test data, the actual heavy metal concentration, pH value, and temperature data under the same environment were used as a piece of training data to obtain training data sets corresponding to different measuring ranges.

[0016] The training data sets corresponding to different ranges are used as inputs to the adaptive intelligent correction algorithm model, which predicts the corrected measurement results and outputs the corresponding correction results.

[0017] The loss value is calculated based on the real groundwater heavy metal data and the corresponding correction results, and the adaptive intelligent correction algorithm model is optimized through back propagation until the training requirements of the adaptive intelligent correction algorithm model are met, thereby obtaining the trained adaptive intelligent correction algorithm model.

[0018] Furthermore, in the laboratory, samples with known heavy metal concentrations at different temperatures and pH values ​​are selected for each range of detection. The specific method for obtaining test data for several samples is as follows:

[0019] Prepare several standard solutions in high and low concentration ranges within the selected range of the heavy metal to be tested;

[0020] Based on the standard solution, m portions of samples with known concentration values ​​in the pH range of 1 to 12 are prepared;

[0021] All samples were placed in a temperature-controlled box, and n control temperatures were set in sequence, evenly distributed in the conventional groundwater temperature range. The heavy metal concentration value of each sample under each temperature condition was measured according to the ASV sensor standard detection process to obtain several sample test data.

[0022] Furthermore, the concentration value C of the high concentration standard solution H for:

[0023] C H =C min +0.8×(C max -C min )

[0024] Among them C min is the lower limit of the detection range of the selected range; C max is the upper limit of the detection range of the selected range. Further, the concentration value C of the low concentration standard solution L for:

[0025] C L =C min +0.1×(C max -C min )

[0026] Among them C min is the lower limit of the detection range of the selected range; C max It is the upper limit of the detection range of the selected range.

[0027] Furthermore, the values ​​of m and n are both 5 to 10; the conventional groundwater temperature range is 5 to 35°C.

[0028] Provided is an ASV heavy metal in-situ detection method taking into account the interference of groundwater environmental factors, which comprises the following steps:

[0029] S1, in-situ measurement of heavy metals in groundwater using the ASV sensor measurement module;

[0030] S2. When the ASV sensor measurement module performs in-situ measurement of heavy metals in groundwater, the pH and temperature data of groundwater near the measurement location are collected through the environmental factor data collection module;

[0031] S3, transmitting the data obtained by the ASV sensor measurement module and the environmental factor data collection module to the adaptive intelligent correction algorithm module through the data transmission module;

[0032] S4, using the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module as inputs of the adaptive intelligent correction algorithm model through the adaptive intelligent correction algorithm module, and predicting the corrected measurement results through the adaptive intelligent correction algorithm model to obtain a correction result;

[0033] S5. The correction result obtained by the adaptive intelligent correction algorithm module is output as the final groundwater heavy metal measurement result through the data output module.

[0034] The beneficial effects of the present invention are as follows: the present invention utilizes the ASV sensor measurement module to perform in-situ measurement of the pH and temperature of nearby groundwater, and uses the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module as inputs of the adaptive intelligent correction algorithm model through the adaptive intelligent correction algorithm module. The corrected measurement results are predicted by the adaptive intelligent correction algorithm model to obtain the correction results. The present invention can significantly improve the accuracy and reliability of ASV detection of heavy metals in groundwater. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is the structural diagram of the system;

[0036] Figure 2 The figures show the performance of the training data set and test data of the adaptive intelligent correction algorithm model for ASV detection of heavy metal Pb in the range of 0-100 ppb in the embodiment of the present invention; (a) shows the comparison of the errors before and after correction under different pH conditions when the true concentration in the training set is 10 ppb; (b) shows the comparison of the errors before and after correction under different temperature conditions when the true concentration in the training set is 10 ppb; (c) shows the comparison of the errors before and after correction under different pH conditions when the true concentration in the training set is 80 ppb; (d) shows the comparison of the errors before and after correction under different temperature conditions when the true concentration in the training set is 80 ppb; and (e) shows the comparison of the errors of the measured values ​​of the training set and the validation set before and after correction. DETAILED DESCRIPTION

[0037] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0038] Example 1:

[0039] like Figure 1 As shown, the ASV heavy metal in-situ detection system considering the interference of groundwater environmental factors includes: an ASV sensor measurement module, an environmental factor data collection module, a data transmission module, an adaptive intelligent correction algorithm module and a data output module;

[0040] ASV sensor measurement module, including ASV sensor, for in-situ measurement of heavy metals in groundwater;

[0041] The environmental factor data collection module includes a pH sensor and a temperature sensor, which is used to collect pH and temperature data of groundwater near the measurement location when the ASV sensor measurement module performs in-situ measurement of heavy metals in groundwater;

[0042] A data transmission module, used to transmit the data obtained by the ASV sensor measurement module and the environmental factor data collection module to the adaptive intelligent correction algorithm module;

[0043] An adaptive intelligent correction algorithm module, including an adaptive intelligent correction algorithm model, is used to take the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module as input, and predict the corrected measurement results to obtain correction results;

[0044] The data output module is used to output the correction result obtained by the adaptive intelligent correction algorithm module as the final groundwater heavy metal measurement result.

[0045] The specific method of using the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module as input and predicting the corrected measurement results is as follows:

[0046] The in-situ measurement results of heavy metals obtained by the ASV sensor measurement module and the environmental factor data collection module, and the pH and temperature data of groundwater near the measurement location are used as the input of the trained adaptive intelligent correction algorithm model, and the output of the trained adaptive intelligent correction algorithm model is used as the correction result to complete the correction of the measurement results of the ASV sensor measurement module; the adaptive intelligent correction algorithm model is an MLP multi-layer perceptron regression model.

[0047] The training method of the adaptive intelligent correction algorithm model is:

[0048] Based on the measuring range of the ASV sensor, samples with known heavy metal concentrations at different temperatures and pH values ​​were tested in the laboratory within each measuring range to obtain a number of sample test data. The sample test data, the actual heavy metal concentration, pH value, and temperature data under the same environment were used as a piece of training data to obtain training data sets corresponding to different measuring ranges.

[0049] The training data sets corresponding to different ranges are used as inputs to the adaptive intelligent correction algorithm model, which predicts the corrected measurement results and outputs the corresponding correction results.

[0050] The loss value is calculated based on the real groundwater heavy metal data and the corresponding correction results, and the adaptive intelligent correction algorithm model is optimized through back propagation until the training requirements of the adaptive intelligent correction algorithm model are met, thereby obtaining the trained adaptive intelligent correction algorithm model.

[0051] In the laboratory, the specific method for testing samples with known heavy metal concentrations at different temperatures and pH values ​​within each range of the detection range is as follows:

[0052] Prepare several standard solutions in high and low concentration ranges within the selected range of the heavy metal to be tested;

[0053] Based on the standard solution, m portions of samples with known concentration values ​​in the pH range of 1 to 12 are prepared;

[0054] All samples were placed in a temperature-controlled box, and n control temperatures were set in sequence, evenly distributed in the conventional groundwater temperature range. The heavy metal concentration value of each sample under each temperature condition was measured according to the ASV sensor standard detection process to obtain several sample test data.

[0055] The concentration value C of the high concentration standard solution H for:

[0056] C H =C min +0.8×(C max -C min )

[0057] Among them C min is the lower limit of the detection range of the selected range; C max The concentration value C of the low concentration standard solution is L for:

[0058] C L =Cmin +0.1×(C max -C min )

[0059] Among them C min is the lower limit of the detection range of the selected range; C max It is the upper limit of the detection range of the selected range.

[0060] In the specific implementation process, the values ​​of m and n are both 5 to 10; the conventional groundwater temperature range is 5 to 35°C.

[0061] Example 2:

[0062] This example further expands upon Example 1. In this example, lead (Pb) was measured as a heavy metal element in groundwater. The high-concentration and low-concentration standard solutions in the training set were 80 ppb and 10 ppb, respectively. The values ​​of m and n corresponding to the pH and temperature in the training set were both 5; the pH values ​​were 1, 5, 7, 10, and 12, and the temperatures were 10, 15, 20, 25, and 30°C. The validation set consisted of 50 simulated real groundwater samples.

[0063] The ASV heavy metal in-situ detection method considering the interference of groundwater environmental factors includes the following steps:

[0064] S0, training the adaptive intelligent correction algorithm module through the training set;

[0065] S1, in situ measurement of heavy metals in the validation set using the ASV sensor measurement module;

[0066] S2. When the ASV sensor measurement module performs in-situ measurement of heavy metals in the validation set through the environmental factor data collection module, pH and temperature data near the measurement location are collected;

[0067] S3, transmitting the data obtained by the ASV sensor measurement module and the environmental factor data collection module to the adaptive intelligent correction algorithm module through the data transmission module;

[0068] S4, using the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module as inputs of the adaptive intelligent correction algorithm model through the adaptive intelligent correction algorithm module, and predicting the corrected measurement results through the adaptive intelligent correction algorithm model to obtain a correction result;

[0069] S5. The correction result obtained by the adaptive intelligent correction algorithm module is output as the final heavy metal measurement result in the verification set through the data output module.

[0070] The RMSE of the ASV measurement value of the real groundwater samples in the validation set used in this example is 9.65 ppb. Figure 2 As shown in the figure, after correction using this method, the RMSE was reduced to 5.8 ppb; the mean error before correction was 4.21 ppb, and the mean error after correction was 1.69 ppb. Overall, the error reduction after correction using this method significantly improved the accuracy and reliability of ASV detection of heavy metals in groundwater.

[0071] In summary, the present invention utilizes the pH and temperature of nearby groundwater during in-situ measurement by the ASV sensor measurement module, and uses the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module as inputs of the adaptive intelligent correction algorithm model through the adaptive intelligent correction algorithm module. The corrected measurement results are predicted by the adaptive intelligent correction algorithm model to obtain the correction results. The present invention can significantly improve the accuracy and reliability of ASV detection of heavy metals in groundwater.

Claims

1. An ASV heavy metal in-situ detection system considering the interference of groundwater environmental factors, characterized in that: include: ASV sensor measurement module, environmental factor data collection module, data transmission module, adaptive intelligent correction algorithm module and data output module; ASV sensor measurement module, including ASV sensor, for in-situ measurement of heavy metals in groundwater; The environmental factor data collection module includes a pH sensor and a temperature sensor, which is used to collect pH and temperature data of groundwater near the measurement location when the ASV sensor measurement module performs in-situ measurement of heavy metals in groundwater; A data transmission module, used to transmit the data obtained by the ASV sensor measurement module and the environmental factor data collection module to the adaptive intelligent correction algorithm module; An adaptive intelligent correction algorithm module, including an adaptive intelligent correction algorithm model, is used to take the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module as input, and predict the corrected measurement results to obtain correction results; A data output module is used to output the correction result obtained by the adaptive intelligent correction algorithm module as the final groundwater heavy metal measurement result; The training method of the adaptive intelligent correction algorithm model is: Based on the measuring range of the ASV sensor, samples with known heavy metal concentrations at different temperatures and pH values ​​were tested in the laboratory within each measuring range to obtain a number of sample test data. The sample test data, the actual heavy metal concentrations, pH values, and temperature data under the same environment were used as a set of training data to obtain multiple sets of training data corresponding to different measuring ranges. The training data sets corresponding to different ranges are used as inputs to the adaptive intelligent correction algorithm model, which predicts the corrected measurement results and outputs the corresponding correction results. The loss value is calculated based on the real groundwater heavy metal data and the corresponding correction results, and the adaptive intelligent correction algorithm model is optimized through back propagation until the training requirements of the adaptive intelligent correction algorithm model are met, thereby obtaining the trained adaptive intelligent correction algorithm model; The specific method of using the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module as input and predicting the corrected measurement results is as follows: The in-situ heavy metal measurement results obtained by the ASV sensor measurement module and the environmental factor data collection module, as well as the pH and temperature data of the groundwater near the measurement location, are used as the input of the trained adaptive intelligent correction algorithm model. The output of the trained adaptive intelligent correction algorithm model is used as the correction result to complete the correction of the measurement results of the ASV sensor measurement module. The adaptive intelligent correction algorithm model is the MLP multi-layer perceptron regression model; In the laboratory, the specific method for testing samples with known heavy metal concentrations at different temperatures and pH values ​​within each range of the detection range is as follows: Prepare several standard solutions in high and low concentration ranges within the selected range of the heavy metal to be tested; Based on the standard solution, m portions of samples with known concentration values ​​in the pH range of 1 to 12 are prepared; All samples were placed in a temperature-controlled box, and n control temperatures were set in sequence, evenly distributed in the conventional groundwater temperature range. The heavy metal concentration of each sample under each temperature condition was measured according to the ASV sensor standard detection process. Several sample test data were obtained, with the values ​​of m and n both ranging from 5 to 10. The conventional groundwater temperature range is 5 to 35°C. The concentration value C of the high concentration standard solution H for: C H =C min +0.8×(C max -C min ) Among them C min is the lower limit of the detection range of the selected range; C max The upper limit of the detection range of the selected range; The concentration value C of the low concentration standard solution L for: C L =C min +0.1×(C max -C min ) Among them C min is the lower limit of the detection range of the selected range; C max It is the upper limit of the detection range of the selected range.

2. The ASV heavy metal in-situ detection method considering the interference of groundwater environmental factors according to the ASV heavy metal in-situ detection system considering the interference of groundwater environmental factors according to claim 1 is characterized in that: The following steps are involved: S1, in-situ measurement of heavy metals in groundwater using the ASV sensor measurement module; S2. When the ASV sensor measurement module performs in-situ measurement of heavy metals in groundwater, the pH and temperature data of groundwater near the measurement location are collected through the environmental factor data collection module; S3, transmitting the data obtained by the ASV sensor measurement module and the environmental factor data collection module to the adaptive intelligent correction algorithm module through the data transmission module; S4, using the data obtained by the environmental factor data collection module and the measurement results of the ASV sensor measurement module as inputs of the adaptive intelligent correction algorithm model through the adaptive intelligent correction algorithm module, and predicting the corrected measurement results through the adaptive intelligent correction algorithm model to obtain a correction result; S5. The correction result obtained by the adaptive intelligent correction algorithm module is output as the final groundwater heavy metal measurement result through the data output module.

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