CN117147667A

CN117147667A - Method and system for detecting weak acid soluble heavy metal in soil

Info

Publication number: CN117147667A
Application number: CN202311411391.1A
Authority: CN
Inventors: 刘刚; 刘宁; 叶文帅
Original assignee: China Agricultural University
Current assignee: China Agricultural University
Priority date: 2023-10-30
Filing date: 2023-10-30
Publication date: 2023-12-01
Anticipated expiration: 2043-10-30
Also published as: CN117147667B

Abstract

The invention discloses a method and a system for detecting weak acid soluble heavy metals in soil, and relates to the field of environmental pollutant detection; the method comprises the following steps: obtaining a soil leaching solution; treating the soil leaching solution by adopting a photolysis method to obtain a photolysis solution; the photolytic solution includes: heavy metal ions complexed by soluble organic matters; the heavy metal ions include: lead ions and cadmium ions; carrying out electrochemical analysis on heavy metal ions in the photolysis solution by adopting a stripping voltammetry to obtain a stripping voltammetry curve; determining peak signal information according to the stripping voltammetry curve by adopting a peak signal acquisition algorithm; inputting the peak signal information into an ion concentration calculation model to obtain the concentration of heavy metal ions; the ion concentration calculation model is constructed by adopting a machine learning method; the method can realize rapid and accurate detection of the weak acid soluble heavy metals in the soil.

Description

Method and system for detecting weak acid soluble heavy metal in soil

Technical Field

The invention relates to the field of environmental pollutant detection, in particular to a method and a system for detecting weak acid soluble heavy metals in soil.

Background

Soil heavy metal pollution has become one of the more prominent environmental problems at present. The rapid and accurate acquisition of the soil heavy metal pollution information is a basic requirement for monitoring and controlling the soil heavy metal pollution.

The signal extraction and data analysis performance of the current electrochemical detection device is still to be improved. When the stripping voltammetry potential drifts, the algorithm cannot accurately identify the current peak of the heavy metal. Efficient soluble organic interference suppression methods and efficient multiple metal ion interaction interference suppression methods are also lacking.

In addition, the existing pretreatment method for the soil sample, which is suitable for weak acid soluble heavy metal extraction and stripping voltammetry detection, is tedious, time-consuming and labor-consuming, and needs various equipment, and cannot meet the in-situ, rapid and automatic detection of the soil heavy metal. Therefore, a set of soil heavy metal integrated automatic detection equipment is developed, so that the quick and accurate detection of the soil weak acid soluble lead and cadmium is realized, and the method has important significance for the treatment, prevention and control of soil heavy metal pollution.

Disclosure of Invention

The invention aims to provide a method and a system for detecting weak acid soluble heavy metals in soil, which can realize rapid and accurate detection of weak acid soluble heavy metals in soil.

In order to achieve the above object, the present invention provides the following solutions: a method for detecting weak acid soluble heavy metals in soil, the method comprising: obtaining a soil leaching solution; the soil leaching solution is prepared by mixing a soil sample and leaching solution according to a set solid-to-liquid ratio, performing ultrasonic treatment to obtain a soil mixed solution, and extracting and filtering the soil mixed solution by a suction filtration method to obtain a soil leaching supernatant.

Treating the soil leaching solution by adopting a photolysis method to obtain a photolysis solution; the photolytic solution includes: heavy metal ions complexed by soluble organic matters; the heavy metal ions include: lead ions and cadmium ions.

And carrying out electrochemical analysis on heavy metal ions in the photolysis solution by adopting a stripping voltammetry to obtain a stripping voltammetry curve.

Determining peak signal information according to the stripping voltammetry curve by adopting a peak signal acquisition algorithm; the peak signal information includes: peak height and peak width.

Inputting the peak signal information into an ion concentration calculation model to obtain the concentration of the heavy metal ions; the ion concentration calculation model is constructed by adopting a machine learning method.

According to the specific embodiment provided by the invention, the invention discloses the following technical effects: the invention provides a method and a system for detecting weak acid soluble heavy metals in soil, which are characterized in that soil leaching liquid is obtained; the soil leaching solution is prepared by mixing a soil sample and leaching solution according to a set solid-to-liquid ratio, performing ultrasonic treatment to obtain a soil mixed solution, and extracting and filtering the soil mixed solution by a suction filtration method to obtain a soil leaching supernatant; treating the soil leaching solution by adopting a photolysis method to obtain a photolysis solution; the photolytic solution includes: heavy metal ions complexed by soluble organic matters; the heavy metal ions include: lead ions and cadmium ions; carrying out electrochemical analysis on heavy metal ions in the photolysis solution by adopting a stripping voltammetry to obtain a stripping voltammetry curve; determining peak signal information according to the stripping voltammetry curve by adopting a peak signal acquisition algorithm; inputting the peak signal information into an ion concentration calculation model to obtain the concentration of heavy metal ions; and because the ion concentration calculation model is constructed by adopting a machine learning method, the method can realize the rapid and accurate detection of the weak acid soluble heavy metal in the soil.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a method for detecting weak acid soluble heavy metals in soil.

Fig. 2 is a schematic diagram of the left minimum point.

Fig. 3 is a schematic diagram of the right minimum point.

Fig. 4 is a schematic diagram of peak background currents corresponding to the left minimum point and the right minimum point.

Fig. 5 is a schematic diagram of peak height and width.

Fig. 6 is a schematic diagram of inaccurate peak height and width acquisition.

FIG. 7 is a schematic diagram of accurate peak height and width acquisition.

Fig. 8 is a schematic diagram of a detection device for stripping voltammetry measurement in practical application.

Fig. 9 is a schematic diagram of an electrochemical process for stripping voltammetric measurement.

Fig. 10 is a schematic diagram of a stripping voltammogram.

Fig. 11 is a schematic diagram of an initial stripping voltammogram.

Fig. 12 is a schematic view of a dissolution curve after the smoothing treatment.

Fig. 13 is a schematic graph of the dissolution volts An Dianliu profile collected for a standard reference electrode and a worn reference electrode.

Fig. 14 is a graph showing the peak background current of the heavy metal stripping current in the absence of copper ions.

Fig. 15 is a schematic view of background current of heavy metal stripping current peaks in the presence of copper ions.

FIG. 16 is a graph showing the peak-to-peak distance statistics for the elution current.

FIG. 17 is a graph showing the stripping voltammetric response of a potentiostat.

FIG. 18 shows a potentiostat for Cd at different concentrations ²⁺ Is a schematic of the stripping voltammetric response.

FIG. 19 shows a potentiostat for Pb at different concentrations ²⁺ Is a schematic of the stripping voltammetric response.

FIG. 20 is a Cd detected using a calibration model ²⁺ Concentration results are schematically shown.

FIG. 21 is a diagram of Pb detected using a calibration model ²⁺ Concentration results are schematically shown.

FIG. 22 is a graph of Cd versus modeling set using the H-W-SVR model ²⁺ The results of concentration detection are schematically shown.

FIG. 23 shows the use of the H-W-SVR model to validate set pairs Cd ²⁺ The results of concentration detection are schematically shown.

FIG. 24 is a graph of modeling set versus Pb using the H-W-SVR model ²⁺ The results of concentration detection are schematically shown.

FIG. 25 shows the use of the H-W-SVR model for verification set versus Pb ²⁺ The results of concentration detection are schematically shown.

Detailed Description

In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.

Example 1: as shown in fig. 1, the embodiment of the invention provides a method for detecting weak acid soluble heavy metals in soil, which comprises the following steps: step 100: obtaining a soil leaching solution. The soil leaching solution is obtained by mixing a soil sample and leaching solution according to a set solid-to-liquid ratio, performing ultrasonic treatment to obtain a soil mixed solution, and extracting and filtering the soil mixed solution by a suction filtration method to obtain a supernatant.

Step 200: and (3) treating the soil leaching solution by adopting a photolysis method to obtain a photolysis solution. Wherein the photolytic solution comprises: heavy metal ions complexed by soluble organic matters; the heavy metal ions include: lead ions and cadmium ions.

Step 300: and carrying out electrochemical analysis on heavy metal ions in the photodecomposition solution by adopting a stripping voltammetry to obtain a stripping voltammetry curve.

Step 400: and determining peak signal information according to the stripping voltammetry curve by adopting a peak signal acquisition algorithm. Wherein the peak signal information includes: peak height and peak width.

The peak signal information is determined according to the stripping voltammetry curve by adopting a peak signal acquisition algorithm, and the method specifically comprises the following steps: smoothing the stripping voltammetry curve to obtain a stripping curve; determining peak categories corresponding to the current peaks on the dissolution curve based on the peak-to-peak distances; the peak-to-peak distance is a constant value determined from the dissolution potential drift; determining peak peaks according to the dissolution curve; determining a candidate point set based on the peak top points; the candidate point set is a set of peaks of the current peaks adjacent to the peak top point within a set range; the candidate point set includes: a left candidate point set and a right candidate point set; determining a candidate point connecting line set according to the candidate point set; the candidate point connecting line set comprises a plurality of connecting lines; the connecting line is a line segment connected by any current point in the left candidate point set and any current point in the right candidate point set; for any connecting line, determining the connecting point of the vertical line of the peak point and the connecting line; the vertical line is a vertical connecting line between the peak vertex and the abscissa on the dissolution curve; for any connecting point, calculating the distance between the peak top and the connecting point to obtain the initial peak height; comparing all the initial peak heights to obtain the maximum value of the initial peak height, and determining the maximum value of the initial peak height as the peak height; and calculating the length of the line segment according to the connecting line corresponding to the peak height to obtain the peak width.

Wherein, confirm peak point according to the dissolution curve, specifically include: determining a corresponding function expression according to the dissolution curve; performing first-order derivation on the function expression to obtain a derivative function expression; determining a characteristic point set according to the derivative function expression; the feature point set comprises n feature points; the characteristic points are extreme points or zero points; the extreme points include: maximum value points and minimum value points; determining a point set; the point set includes: a maximum point set, a minimum point set and a zero point set; the maximum value point set is a set of maximum value points; the minimum value point set is a set of minimum value points; the zero point set is a zero point set; judging the peak type according to the derivative function expression and the ith characteristic point, and determining a corresponding peak point according to the peak type; the peak points include: a vertex or origin; wherein,。

for the ith feature point, if the ith feature point is in the zero point set and the ith-1 th feature point is in the maximum value point set, and the (i+1) th feature point is in the minimum value point set, the peak type at the ith feature point is a complete peak, and the ith feature point is the peak of the complete peak.

For the ith feature point, if the ith feature point is in the maximum value point set and the (i+1) th feature point is in the minimum value point set, the absolute value of the numerical value of the ith feature point is smaller than the absolute value of the numerical value of the (i+1) th feature point, the peak type at the ith feature point is a right shoulder, and the ith feature point is the starting point of the right shoulder.

Determining the end point of the right acromion according to the right acromion and the start point of the right acromion; calculating a midpoint according to the starting point of the right shoulder and the ending point of the right shoulder to obtain the vertex of the right shoulder; determining peak tops of the stray heavy metal ions according to set conditions according to the peak points of the right shoulder peaks; the stray heavy metal ions include copper ions; and determining the peak top according to the dissolution curve and the peak top of the stray heavy metal ions.

The stripping voltammetry curve is subjected to smoothing treatment to obtain a stripping curve, which specifically comprises the following steps: carrying out initial smoothing treatment on the stripping voltammetric curve to obtain a stripping voltammetric treatment curve; and filtering and smoothing the stripping voltammetry treatment curve by adopting an S-G filtering algorithm to obtain the stripping curve.

Step 500: and inputting the peak signal information into an ion concentration calculation model to obtain the concentration of heavy metal ions. The ion concentration calculation model is constructed by adopting a machine learning method.

The method for determining the ion concentration calculation model specifically comprises the following steps: acquiring training data; the training data includes: training peak signal information and corresponding label data; tag data is the concentration of heavy metal ions; dividing training data into a training set and a verification set; constructing a machine learning neural network; inputting the training set and the corresponding label data into a machine learning neural network, and training the detection parameters in the machine learning neural network by adopting a support vector regression algorithm with the minimum error as a target to obtain a trained machine learning neural network; the detection parameters include: the coefficient and root mean square are detected.

The verification set and the corresponding label data are adopted to adjust the detection parameters of the trained machine learning neural network, and the adjusted machine learning neural network is obtained; and determining the adjusted machine learning neural network as an ion concentration calculation model.

In practical application, the operation steps of determining peak signal information according to the stripping voltammetry curve by adopting a peak signal acquisition algorithm are specifically as follows.

Step 1: and obtaining the peak top point of the heavy metal ion stripping voltammetry curve.

Step 2: determining the minimum point (N) _Left ) Peak and peakMinimum point of right candidate (N _Right ) Is a number of (3).

The range of the left candidate minimum point is from the peak of the dissolution current peak to the peak of the adjacent left dissolution current peak; if the peak is the leftmost dissolution current peak, the left candidate minimum point ranges from the peak of the dissolution current peak to the start of the dissolution current curve.

The right candidate minimum point ranges from the peak of the elution current peak to the peak of the adjacent right elution current peak; if the peak is the rightmost dissolution current peak, the right candidate minimum point ranges from the peak of the dissolution current peak to the end of the dissolution current curve.

Step 3: selecting a right candidate minimum point (P _{R, i} ）（i[1, N _Right ]) And compares it with the left candidate minimum point (P _{L, j} ）（j/>[1, N _Left ]) Is connected to obtain a straight line (L _{i, j} ) As indicated by the dashed lines in fig. 2-3.

Step 4: calculating peak apex to vertical line and straight line L _i,j The distance of the connecting points of (a), i.e. peak height H _i,j The method comprises the steps of carrying out a first treatment on the surface of the The vertical line is the vertical line connecting the peak apex with the abscissa, as shown by the solid lines in fig. 2-3.

Step 5: keeping i=1, from 1 to N _Left Cycle j, find H _{i, j} Maximum value (marked as MH) _i ) And will correspond to P _{L, j} Is denoted as MP _{L, i} (i=1 at this time), as shown in fig. 2.

Step 6: by stepping i from 1 to N _Right Step 5, recording MH _i The value (i)[1，N _Right ]) And will correspond to P _{R, i} Recorded as MP _{R, i} As shown in fig. 3.

Step 7:find MH _i （i[1，N _Right ]) The maximum value of (2) is marked as MH, namely the peak height to be solved; corresponding MP _L,i And MP _R,i Respectively the left Minimum Point (MP) _L ) And right Minimum Point (MP) _R ) As shown in fig. 4.

Step 8: MP is combined with _L With MP _R Connecting by straight lines to obtain the background current of the peak value; the length of the connection line is the peak width to be solved, as shown in fig. 5.

In addition, in Cu ²⁺ Bi in the presence of acromion ³⁺ And Cu ²⁺ The operation steps of the method for obtaining the peak height and the peak width of the elution current are specifically as follows.

Zn ²⁺ 、Cd ²⁺ And Pb ²⁺ The elution current peaks of (a) are independent peaks, so that their peak top points can be easily obtained. Generally, cu ²⁺ Is ubiquitous in soil and has a content higher than Cd ²⁺ . Therefore, there is a bi—cu overlapping peak on the dissolution curve of the soil leaching solution. When Cu is ²⁺ At higher levels, e.g. greater than 25. Mu.g/L, although Bi ³⁺ And Cu ²⁺ Partial overlap of peaks of (C) is present, but Bi can be easily obtained ³⁺ And Cu ²⁺ Peak apex of elution current peak.

In particular, when Cu ²⁺ When present but at a low level, e.g. below 25. Mu.g/L, intact Cu ²⁺ The peak will become Bi ³⁺ The shoulder to the right of the peak is shown in fig. 6-7. At this time, cu cannot be obtained ²⁺ The peak apex; cu (Cu) ²⁺ The shoulder will be ignored; bi (Bi) ³⁺ The peak height and peak width of the peak may also be miscalculated as shown in fig. 6.

Thus, cu is recognized ²⁺ The shoulder peak and the peak top point are obtained by accurately calculating Bi ³⁺ And Cu ²⁺ The key of the peak height and peak width of the dissolution current. For this purpose, a shoulder recognition algorithm based on the first derivative of the dissolution current is designed. Three first derivative feature points are defined, including a local maximum point, a local minimum point, and a zero point. Then define the right shoulder according to the first derivative characteristic pointsPeaks and complete peaks. The complete peak contains a local maximum point, a local minimum point and a zero point. The right shoulder contains only a maximum point and a minimum point, and the absolute value of the derivative at the maximum point is smaller than the absolute value of the derivative at the minimum point.

Specifically, step 1: calculating the first derivative of the S-G smoothed dissolution current data, and marking the S-G smoothed dissolution current data as f (x) and marking the first derivative as。

Step 2: calculating and storing all first derivative characteristic points, and marking as p _i （i[1,n]) N is the number of all first derivative feature points.

Step 3: obtaining a set of all local maximum points of the first derivative, and marking the set as S _Max The method comprises the steps of carrying out a first treatment on the surface of the The set of all local minimum points of the first derivative is obtained and is marked as S _Min The method comprises the steps of carrying out a first treatment on the surface of the Obtaining the set of all zero points of the first derivative, which is marked as S _Zero 。

Step 4: according to p _i Searching for a peak; if it meets S _Max 、p _i />S _Zero 、p _i+1 />S _Min Under the condition that the peak is a complete peak, p _i Is the peak of the complete peak.

Step 5: according to p _i Find peak if p is satisfied _i S _Max ，p _i+1 />S _Min ，/>Under the condition that the peak is right shoulder peak, p _i Is the origin of the right shoulder.

Step 6: taking p for the right shoulder peak obtained in the step 5 _j J=min (m), p as the endpoint of the right shoulder _m (S _Max />S _Zero )，m>i+1。

Step 7: calculation of p _i And p _j Is the midpoint of the right shoulder peak (denoted as P _Summit ）。

Step 8: calculation of P _Summit To Bi ³⁺ The distance between the peaks of the elution current is 20-70, and the right shoulder is Cu ²⁺ Right shoulder.

Step 9: if step 8 is not satisfied, searching and judging whether the next right shoulder peak is Cu ²⁺ Right shoulder until all the first derivative feature points p are traversed _i 。

Step 10: obtaining Cu ²⁺ After the peak top of the shoulder peak, bi is accurately calculated ³⁺ And Cu ²⁺ The peak height and peak width of the current peak are shown in fig. 7.

Example 2: the embodiment of the invention provides a system for detecting soil weak acid soluble heavy metal, which is realized by applying the method for detecting soil weak acid soluble heavy metal in the embodiment 1, and comprises the following steps: the system comprises a cloud server, a microprocessor, an ultrasonic processor, an extraction and filtration device, an ultraviolet photolysis device and a potentiostat; the ultrasonic processor, the extraction and filtration device, the ultraviolet photolysis device and the potentiostat are all connected with the microprocessor; and the cloud server is connected with the microprocessor.

The microprocessor is used for sending out a control instruction; the ultrasonic processor is used for carrying out ultrasonic treatment on the soil sample and the leaching solution after mixing according to a set solid-liquid ratio according to the control instruction to obtain a soil mixed solution; the extraction and filtration device is used for extracting and filtering the soil leaching liquid in a suction filtration mode according to the control instruction to obtain supernatant, and taking the supernatant as the soil leaching liquid; the ultraviolet photolysis device is used for processing the soil leaching solution according to the control instruction to obtain a photolysis solution; the photolytic solution includes: heavy metal ions complexed by soluble organic matters; the heavy metal ions include: lead ions and cadmium ions.

The potentiostat is used for carrying out electrochemical analysis on heavy metal ions in the photodecomposition solution by adopting a stripping voltammetry according to a control instruction to obtain a stripping voltammetry curve; the electrochemical analysis includes: and outputting a constant negative voltage according to the control instruction, performing electrochemical deposition on heavy metal ions in the photodecomposition solution, outputting an excitation voltage signal according to the control instruction, and performing electrochemical dissolution on the deposited heavy metal to obtain a dissolution voltammetry curve.

The cloud server is used for determining peak signal information according to the stripping voltammetry curve by adopting a peak signal acquisition algorithm; the peak signal information includes: peak height and peak width.

The cloud server is also used for inputting the peak signal information into an ion concentration calculation model to obtain the concentration of heavy metal ions; the ion concentration calculation model is constructed by adopting a machine learning method.

In one embodiment, the system further comprises: a magnetic stirrer; the magnetic stirrer is connected with the microprocessor; the magnetic stirrer is used for stirring the soil leaching liquid according to the control instruction.

As an alternative embodiment, the system further comprises: a quantitative peristaltic pump and an electrochemical analytical cell; the quantitative peristaltic pump is respectively connected with the microprocessor, the ultraviolet photolysis device and the electrochemical analysis tank; the quantitative peristaltic pump is used for quantitatively extracting the photolytic solution to the electrochemical analysis cell according to the control instruction.

In practical application, a soil moisture content detection device is adopted to process a soil sample. Wherein the soil moisture content detection device is formed by a soil sampler such as a cutting ring soil sampling drill, a soil moisture content sensor andand an electronic scale. Soil sampler for collecting a certain volume V ₀ Is a soil of the plant. The soil moisture content detector is used for detecting the soil volume moisture content based on a time domain reflection method. The soil sample water content sensor is inserted into the soil sampler to measure the soil volume water content. The total weight W of the soil in the sampler is then determined using an electronic scale ₀ 。

First, V ₀ Dry weight of volume soil W _d Is thatThe method comprises the steps of carrying out a first treatment on the surface of the Then weighing x g of soil sample, and placing into an ultrasonic extractor, wherein the weight of dry soil is +.>. Assuming that the dry weight of the soil sample is to be kept at 2g, the weight of the actual soil sample to be weighed can be calculated, i.e. the x-value can be calculated.

Soil samples and leaching solutions were mixed according to 1: and (5) adding the solution to an ultrasonic treatment tank in a solid-liquid ratio of 40, and finishing pretreatment of a soil sample and stripping voltammetry detection of lead and cadmium concentration in the soil leaching solution by using an integrated automatic detection system. Finally, according to 1 again: and the 40 solid-to-liquid ratio converts the detected concentration of the heavy metal solution into the content of weak acid soluble heavy metal in unit dry soil.

In practical application, the detection system can be composed of hardware equipment, smart phone APP software, a cloud server and a communication module.

The hardware equipment is respectively a microprocessor, an ultrasonic processor, an ultraviolet photolysis device, a quantitative peristaltic pump, a magnetic stirrer, a potentiostat, a three-electrode system and a pumping and filtering device which consists of a vacuum pump and a filtering device, wherein the model number of the hardware equipment is STM 32.

The intelligent mobile phone APP software consists of two parts, namely a soil sample pretreatment operation interface and a stripping voltammetry detection operation interface.

The cloud server mainly completes three works, namely smoothing treatment of the dissolved current data and Zn ²⁺ 、Cd ²⁺ 、Pb ²⁺ 、Bi ³⁺ And Cu ²⁺ And (3) obtaining a leaching current signal, and calculating the concentration of lead ions and cadmium ions by a machine learning model.

The intelligent mobile phone APP software sends an instruction to the microprocessor through Bluetooth, and then each hardware device is controlled to work; the dissolved voltammetric data collected by the potentiostat is also sent to the smart phone APP software through Bluetooth. The intelligent mobile phone APP software can also send the dissolved volt-ampere data to the cloud server through the 5G network; and the lead ion concentration and the cadmium ion concentration calculated by the cloud server are returned to the intelligent mobile phone APP software through the 5G network and displayed on an intelligent mobile phone APP software interface.

The ultrasonic treatment module consists of an ultrasonic power supply circuit, an ultrasonic transducer and a stainless steel cup-shaped ultrasonic treatment tank and is used for ultrasonically extracting weak acid soluble heavy metals in soil. The ultrasonic transducer can be selected from CN2550-58HB4.

The intelligent mobile phone APP software is in wireless communication with Bluetooth, and the Bluetooth converts wireless signals into wired signals and sends the wired signals to the microprocessor. After the microprocessor recognizes the instruction for controlling the ultrasonic processing module, the on-off of the ultrasonic power supply circuit and the power supply is controlled by controlling the closing of the relay, so that the work of the ultrasonic transducer is controlled.

The ultrasonic power supply circuit provides power for the ultrasonic transducer, ensures that the power supply is 150W and the voltage is 220V. The function of the ultrasonic transducer is to convert the input electrical power into mechanical power, i.e. ultrasonic waves, to be transmitted out. The stainless steel cup-shaped ultrasonic treatment tank is fixed on the vibrating head of the ultrasonic transducer by using vibrating head glue, and the soil sample and leaching liquid are put into the ultrasonic treatment tank for ultrasonic treatment of soil heavy metals.

For efficiently and rapidly extracting weak acid soluble Cd in soil ²⁺ And Pb ²⁺ The invention optimizes the ultrasonic extraction conditions including ultrasonic power, ultrasonic treatment time and extractant concentration pH5.0. Ultrasonic extraction of weak acid soluble Cd in soil ²⁺ And Pb ²⁺ The optimal conditions of (2) are 150W ultrasonic power, 30min ultrasonic time and 0.3mol/L acetic acid buffer pH5.0.

Therefore, the ultrasonic power supply circuit provides 150W of electric energy for the ultrasonic transducer, the leaching solution is acetic acid buffer solution pH=5.0 of 0.3mol/L, and the microprocessor ensures that the ultrasonic treatment time is 30min by controlling the closing time of the relay. The optimization result is used for guiding the selection and development of the ultrasonic device and the setting of the heavy metal extraction experimental parameters.

The extraction and filtration device consists of a plurality of miniature vacuum liquid pumps with the model number of S15M and the rated voltage of 12V which are mutually cascaded and matched with filters with different apertures, and is used for extracting and filtering the soil mixed liquid after ultrasonic treatment to finally obtain soil leaching liquid; and extracting the soil leaching solution into an ultraviolet photolysis device.

The power supply module provides 12V power for the vacuum pump. The intelligent mobile phone APP software is in wireless communication with Bluetooth, and the Bluetooth converts wireless signals into wired signals and sends the wired signals to the microprocessor. After the microprocessor recognizes the instruction for controlling the vacuum pump device, the microprocessor outputs a high level to the vacuum pump connecting port to control the vacuum pump to work.

Three miniature vacuum liquid pumps are used for mutual cascading and are combined with six filters with different apertures to finish the suction and filtration of the soil leaching liquid. The filter includes a pillar filter and a disc filter. The cylindrical filter is removable and its filter cotton core can be replaced. The filter element is filter cotton with the aperture of 9-11 mu m, and the filter cotton comprises quartz fiber cotton, glass fiber cotton and the like. The diameter of the disc filter was 25mm and the filter pore size comprised of three types of 20 μm, 10 μm and 4 μm. The filtered solution is pumped into a photolysis tank in an ultraviolet photolysis device.

The ultraviolet photolysis device consists of a vacuum ultraviolet lamp, a power supply circuit and a photolysis tank and is used for photolysis of soluble organic matters in the soil leaching liquid and release of heavy metal ions complexed by the soluble organic matters.

The intelligent mobile phone APP software is in wireless communication with Bluetooth, and the Bluetooth converts wireless signals into wired signals and sends the wired signals to the microprocessor. After the microprocessor recognizes the instruction for controlling the ultraviolet photolysis device, a digital switch, such as a PMOS tube, an NMOS tube or a relay, is controlled to be turned on to supply power to the ultraviolet photolysis device. The power supply voltage of the vacuum ultraviolet lamp is 12V, the electric power is 14.4W, and the photolysis time is 20min.

The quantitative peristaltic pump is used for quantitatively extracting the soil leaching liquid after photolysis into the electrochemical analysis cell.

The intelligent mobile phone APP software is in wireless communication with Bluetooth, and the Bluetooth converts wireless signals into wired signals and sends the wired signals to the microprocessor. After the microprocessor recognizes the command for controlling the peristaltic pump, the microprocessor starts to control the peristaltic pump to work. The microprocessor supplies power to the peristaltic pump by controlling the digital switch, and controls the forward rotation, the reverse rotation and the rotating speed of the peristaltic pump by 485 bus. Peristaltic pump quantitatively pumps 40mL of the soil extraction solution after photolysis until 600 mug/L Bi is contained ³⁺ For subsequent stripping voltammetric measurements. The inhalation amount of the peristaltic pump is set to 40mL; the amount of suck back was set to 80mL to empty the remaining solution in the tubing.

The magnetic stirrer consists of a stepping motor and two magnets, and is matched with a magnetic stirrer to stir the soil leaching liquid in the electrochemical deposition process.

The microprocessor controls the magnetic stirrer to work. The output port of the microprocessor supplies power to the stepping motor, and the microprocessor controls the rotating speed of the motor by adjusting the duty ratio of PWM waves output by the port of the stepping motor, so as to control the rotating speed of the magnetic field.

The stripping voltammetry measuring device is a device for electrochemical analysis and mainly comprises a self-made potentiostat and a three-electrode system. The self-made potentiostat mainly comprises a first microprocessor, a potentiostat circuit and an I/V conversion circuit, wherein the first microprocessor is internally provided with an ADC and DAC module.

The three electrode system consists of a working electrode (working electrode, WE), a reference electrode (reference electrode, RE) and a counter electrode (counter electrode, CE). The reference electrode is an Ag/AgCl electrode, the counter electrode is a platinum wire electrode, and the working electrode is a glassy carbon electrode (Bi/GCE) modified by in-situ plating bismuth film. The potentiostat is connected to the three-electrode system for performing stripping voltammetry measurements of the soil leaching solution.

The principle of stripping voltammetry measurement is shown in fig. 8-10. Firstly, heavy metal ions are deposited, namely pre-enriched, on the surface of a working electrode under the action of reduction potential, and the process is called electrochemical deposition; thereafter, the reduced heavy metal dissolves out from the electrode surface into the electrolyte solution under the action of the oxidation potential to obtain a dissolution current, a process called electrochemical dissolution. The elution potential of different heavy metal ions is different, and the elution current is related to the concentration of heavy metal.

The microprocessor integrates a 16-channel analog-to-digital converter and a 2-channel digital-to-analog converter, and can realize the generation of an excitation voltage signal on a constant potential circuit and the acquisition of a response signal of a stripping voltage An Dianliu on an I/V converter.

The primary function of the potentiostatic circuit is to maintain a constant potential between the reference electrode and the working electrode. In order to ensure that no current flows through the reference electrode, a high input impedance operational amplifier OPAI24 is adopted to form a voltage follower, and a closed-loop negative feedback regulation system is formed by the voltage follower and the counter electrode. When the electrochemical reaction produces a current in the electrolytic cell, any deviation in the potential of the reference electrode from the potential of the working electrode is corrected by the negative feedback system to obtain a constant potential. The output voltage range of the constant potential circuit is-2.0V, and the voltage resolution is 1mV.

The I/V conversion circuit consists of an ultralow input bias current operational amplifier with the model number of AD8628, an analog switch with the model number of 700-MAX308EUE and a feedback resistor with the range of 1kW-10 MW. The dissolved current output by the working electrode is converted into a voltage signal through an I/V converter, the range of the voltage signal is 0V-2.0V, the resolution is 1mV, the voltage signal is filtered by a low-pass filter circuit, and then the voltage signal is converted into a digital signal through an ADC (analog to digital converter), and then the digital signal is received and stored by a microprocessor. The detection range of the elution current was.+ -.500. Mu.A, and the detection resolution was 0.1. Mu.A.

The intelligent mobile phone APP software is in wireless communication with Bluetooth, and the Bluetooth converts wireless signals into wired signals and sends the wired signals to the microprocessor. After the microprocessor recognizes the stripping voltammetry measurement instruction, the constant potential rectifier and the three-electrode system are controlled to execute the stripping voltammetry measurement.

In the electrochemical deposition step, the first microprocessor generates a precise time series of constant negative voltage signals, for example, 180s of-1.2V voltage, using an internal DAC and timer, for depositing heavy metals onto the working electrode surface. In the electrochemical dissolution step, an accurate time-series square wave excitation voltage signal is generated using an internal DAC and timer. The exciting voltage signal is converted and shaped by the constant potential circuit and then applied to the working electrode to cause the electrochemical reaction of heavy metal, and the current generated by the electrochemical reaction is converted and amplified by the I/V converter to obtain the dissolved current.

After the leaching current is received, firstly, the leaching current is stored in a text format in a cloud server, then, the cloud server controls a microprocessor to carry out SG smoothing treatment on the leaching volt current, then, a designed leaching current peak signal acquisition algorithm is applied to extract leaching current peak height and peak width signals of each heavy metal ion, and finally, the extracted peak height and peak width signals are substituted into a trained machine learning model to calculate the concentration of lead ions and cadmium ions.

In addition, in practical application, the detection system further comprises: a waste liquid recovery device; the waste liquid recovery device consists of a waste liquid recovery tank and a miniature vacuum liquid pump. And the waste liquid recovery device pumps the soil leaching liquid after the stripping voltammetry detection into a waste liquid recovery tank from the electrochemical analysis tank.

After the detection is completed, deionized water is added into the ultrasonic treatment tank, and all filters connected with the vacuum pump are removed. Then, the intelligent mobile phone APP software is operated to carry out wireless communication with Bluetooth, and the Bluetooth converts wireless signals into wired signals and sends the wired signals to a microprocessor.

After receiving a cleaning instruction, the STM32 microprocessor firstly controls the potentiostat to apply a constant potential of 0.35V to the working electrode so as to remove residual heavy metals on the surface of the electrode; then, controlling all vacuum pumps and quantitative peristaltic pumps to work, cleaning all containers and pipelines in the equipment, sequentially cleaning an ultrasonic treatment tank, a vacuum pump pipeline, a photolysis tank, a peristaltic pump pipeline and an electrochemical analysis tank, and then enabling waste liquid to flow into a waste liquid recovery tank.

The original dissolution current curve is subject to high frequency noise due to parasitic parameters and high frequency oscillations in the homemade potentiostat circuit, as shown in fig. 11. For this purpose, the original dissolution current curve is smoothed using a Savitzky-Golay (SG) filter algorithm. As shown in FIG. 12, the SG is smoothed to remove the dissolved electricity High frequency noise in the stream. SG smoothing treatment helps Zn ²⁺ 、Cd ² ⁺ 、Pb ²⁺ 、Bi ³⁺ And Cu ²⁺ The peak height and the peak width of the dissolved current are accurately obtained. Thus, the SG smoothed dissolution current curve was used for subsequent data analysis.

For automatic and accurate acquisition of Zn ²⁺ 、Cd ²⁺ 、Pb ²⁺ 、Cu ²⁺ And Bi (Bi) ³⁺ Peak height and peak width of the dissolved current are designed into a peak signal acquisition algorithm. The peak information acquisition algorithm is implemented in the Python programming language. The peak signal acquisition algorithm mainly comprises the steps of acquiring peak peaks, identifying peaks of heavy metal ions, solving background currents of the peaks, and calculating peak heights and peak widths.

For the collection of peak heights and peak widths described above, accurate acquisition of peak peaks is the first step. After the dissolution current curve is smoothed by using the S-G algorithm, the find_peaks function, i.e. the embedded function in the SciPy library, is applied to find the peak-to-peak point on the dissolution current curve. Scipy is an open source library of Python algorithms. To avoid some small noise peaks, the peak threshold is set to a minimum peak height of 0.25 and a minimum peak width of 18. Nonetheless, some peaks without information such as noise will be retained. Therefore, it is necessary to accurately identify the category of each retention peak, i.e., identify Zn ²⁺ 、Cd ²⁺ 、Pb ²⁺ 、Cu ²⁺ And Bi (Bi) ³⁺ Is a dissolution current peak of (a).

As shown in fig. 13, the dissolution potential of the dissolution current profile acquired using the worn reference electrode was subject to negative drift compared to the dissolution current profile acquired using the standard reference electrode. Drift in the elution potential results in failure of the method of identifying peak categories using the elution potential. However, the extent of drift of the dissolution potential is relatively stable for the same reference electrode, i.e. all current peaks on the dissolution current curve have the same extent of drift, which ensures that the peak-to-peak distances of dissolution currents acquired by different reference electrodes are constant. Thus, the present invention seeks to establish a reference peak, bi ³⁺ Peak and then identifying Zn based on peak-to-peak distance ²⁺ 、Cd ²⁺ 、Pb ²⁺ And Cu ²⁺ Is a peak of (2).

As a Bi/GCE electrode modification material, 600. Mu.g/L Bi ³⁺ Is added to the solution to be measured. If the solution to be measured contains a small amount or no Cu ²⁺ Bi is then ³⁺ Is large in the peak of the elution current and Bi ³⁺ The background current slope of the current peak is close to zero as shown in fig. 14. Under this condition, bi ³⁺ The peak is the first peak from the right to exceed 30 muA in height, so it can be easily identified. Cu in solution to be tested ²⁺ Bi at higher concentration ³⁺ And Cu ²⁺ The peaks of (2) overlap to form a Bi-Cu overlapping peak, as shown in fig. 15. Under this condition, bi ³⁺ And Cu ²⁺ The background current slope of the current peak is greater than and less than zero, respectively. Thus, in Cu ²⁺ When present, can be based on Bi ³⁺ And Cu ²⁺ Identifying Bi by peak background current of (c) ³⁺ A peak. Bi is adopted in the invention ³⁺ The slope threshold of the peak background current was set to 0.01, cu ²⁺ The slope threshold of the peak background current is set to-0.01. By this method, bi can be accurately identified ³⁺ A peak. Notably, no matter what Cu ²⁺ Whether or not Zn exists ²⁺ 、Cd ²⁺ And Pb ²⁺ The background current slope of the current peaks is close to zero.

Determination of Bi ³⁺ After the peak, zn can be calculated ²⁺ 、Cu ²⁺ And Pb ²⁺ Peak and Bi ³⁺ The distance between the peaks identifies their elution current peaks. The peak-to-peak distance refers to the distance from the peak of one heavy metal elution current peak to the peak of another heavy metal elution current peak. As shown in FIG. 16, zn is counted ²⁺ 、Cd ²⁺ 、Pb ²⁺ And Cu ²⁺ Peak of elution current to Bi ³⁺ Distance between elution current peaks, different heavy metal elution peaks to Bi ³⁺ The distance of the elution peak has a clear limit. According to the statistical result of FIG. 16, zn ²⁺ 、Cd ²⁺ And Pb ²⁺ Peak to Bi elution ³⁺ The distance thresholds of the elution peaks are set to 156-230, 96-155 and 60-95, respectively. Notably, zn ²⁺ 、Cd ²⁺ And Pb ²⁺ The peak of the elution current is located at Bi ³⁺ Left side of the dissolution current peak; cu (Cu) ²⁺ The peak of the elution current is located at Bi ³⁺ The peak distance of Cu-Bi is negative, and the threshold value of the absolute value of the peak distance of Cu-Bi is set to 20-70.

In the identification of Zn ²⁺ 、Cd ²⁺ 、Pb ²⁺ 、Bi ³⁺ And Cu ²⁺ After the peak value of the leaching current of the heavy metal ions, calculating the peak height and the peak width of the leaching current of the heavy metal ions is another key task. Therefore, the key to this step is to find the background current of the elution peak. Assuming that the background current is 0, the peak height is the vertical distance from the peak apex to the abscissa, and the peak width is the vertical projection width of the peak on the abscissa. However, background current is typically present and is typically a ramp signal. Therefore, the peak height and peak width of each heavy metal ion elution current peak need to be accurately calculated.

When the digestion current peak signal acquisition algorithm is operated, according to the peaks of all current peaks, zn is identified ² ⁺ 、Cd ²⁺ 、Pb ²⁺ 、Cu ²⁺ And Bi (Bi) ³⁺ Obtaining Zn by the elution current peak of (2) ²⁺ 、Cd ²⁺ 、Pb ²⁺ 、Cu ²⁺ And Bi (Bi) ³⁺ Finally judging whether Cu exists in the dissolution current data or not according to the peak height and peak width signals of the dissolution current ²⁺ Right shoulder.

If Cu is present ²⁺ Right shoulder, determination of Cu ²⁺ The apex of the right shoulder peak, and then accurately obtaining Cu ²⁺ And Bi (Bi) ³⁺ Peak height and peak width signals of the dissolution current. If Cu is not present ²⁺ Right shoulder, zn is directly obtained ²⁺ 、Cd ²⁺ 、Pb ²⁺ 、Cu ²⁺ And Bi (Bi) ³⁺ The peak height and peak width signals of the dissolved current are accurate.

The invention uses self-made potentiostat to collect Cd with different concentrations ²⁺ And Pb ²⁺ Is described. Cd (cadmium sulfide) ²⁺ And Pb ²⁺ The concentration ranges of (C) are 1. Mu.g/L, 5. Mu.g/L, 10. Mu.g/L, 20. Mu.g/L, 30. Mu.g/L, 40. Mu.g/L, 50. Mu.g/L, 60. Mu.g/L, 80. Mu.g/L, 100. Mu.g/L and 120. Mu.g/L, respectively. Cd (cadmium sulfide) ²⁺ And Pb ²⁺ The stripping voltammetric response curves of (2) are shown in FIGS. 17-19. Self-made potentiostat pair Cd ²⁺ And Pb ²⁺ Respectively, detection sensitivity of (a)0.4467 mu A× (μg/L) ⁻¹ And 0.2293. Mu.A× (μg/L) ⁻¹ The method comprises the steps of carrying out a first treatment on the surface of the Self-made potentiostat pair Cd ²⁺ And Pb ²⁺ The detection limits of (1) are 0.329. Mu.g/L and 0.697. Mu.g/L (S/N=3), respectively. And obtain Cd ²⁺ And Pb ²⁺ Peak height of elution current and Cd ²⁺ And Pb ²⁺ The direct correction models between the concentrations are y= 0.4467x-3.1779 and y= 0.2293x-1.6877 respectively, (y: the peak height of the dissolution current is shown in mu A, x: the concentration of the heavy metal ions is shown in mu g/L), and the concentration of the heavy metal ions can be calculated according to the peak height of the dissolution current of the heavy metal by using the direct correction models.

Detection of Cd for analysis by stripping voltammetry ²⁺ And Pb ²⁺ The invention designs 64 groups of orthogonal experiments, as shown in Table 1, by utilizing self-made potentiostat to collect Zn ²⁺ 、Cd ²⁺ 、Pb ²⁺ 、Cu ²⁺ Dissolution current under cross-talk.

TABLE 1 Zn for 64 orthogonal tests ²⁺ 、Cd ²⁺ 、Pb ²⁺ 、Cu ²⁺ Concentration meter.

Test number	Cd ²⁺ (μg/L)	Pb ²⁺ (μg/L)	Cu ²⁺ (μg/L)	Zn ²⁺ (μg/L)
					1	1	50	25	250
2	1	5	0	0
					3	1	150	100	150
4	1	250	150	300
					5	1	100	75	400
6	1	200	125	100
					7	1	75	50	50
8	1	25	10	200
					9	5	75	25	0
10	5	50	50	200
					11	5	200	150	150
12	5	250	125	400
					13	5	150	75	100
14	5	100	100	300
					15	5	5	10	50
16	5	25	0	250
					17	10	150	150	50
18	10	200	75	0
					19	10	250	100	200
20	10	75	10	150
					21	10	50	0	400
22	10	5	25	100
					23	10	25	50	300
24	10	100	125	250
					25	15	50	10	300
26	15	5	50	150
					27	15	150	125	0
28	15	100	150	200
					29	15	250	75	250
30	15	25	25	400
					31	15	75	0	100
32	15	200	100	50
					33	20	250	50	100
34	20	5	75	200
					35	20	100	0	150
36	20	25	100	0
					37	20	50	125	50
38	20	75	150	250
					39	20	150	10	400
40	20	200	25	300
					41	25	5	100	250
42	25	200	50	400
					43	25	100	10	100
44	25	150	0	300
					45	25	25	75	50
46	25	50	150	0
					47	25	75	125	200
48	25	250	25	150
					49	30	5	125	300
50	30	25	150	100
					51	30	75	100	400
52	30	50	75	150
					53	30	150	50	250
54	30	100	25	50
					55	30	200	0	200
56	30	250	10	0
					57	40	75	75	300
58	40	150	25	200
					59	40	50	100	100
60	40	5	150	400
					61	40	200	10	250
62	40	25	125	150
					63	40	250	0	50
64	40	100	50	0

The 64 samples were first tested for Zn using the direct calibration model shown in FIGS. 17-19 ²⁺ 、Cd ²⁺ 、Pb ²⁺ And Cu ²⁺ Co-existence of Cd ²⁺ And Pb ²⁺ Is a concentration of (3). Cd is processed ²⁺ And Pb ²⁺ Substituting the peak height of the dissolved current into a corresponding direct calibration model, and calculating to obtain Cd ²⁺ And Pb ²⁺ The concentration of (2) and the detection results are shown in FIG. 20 and FIG. 21. Cd (cadmium sulfide) ²⁺ R of the detected concentration and the actual concentration ² The value was 0.385, cd ²⁺ Root-mean-square error (RMSE) of 10.395 μg/L; pb ²⁺ R of (2) ² And RMSE was 0.870 and 37.874. Mu.g/L, respectively. Cd (cadmium sulfide) ²⁺ And Pb ²⁺ The RMSE value of (2) is larger, which indicates that the direct calibration model between the eluting current peak height and the heavy metal concentration can not accurately detect Cd under the condition of the interaction interference of a plurality of heavy metal ions ²⁺ And Pb ²⁺ Is a concentration of (3).

To improve Cd under multi-ion interaction interference ²⁺ And Pb ²⁺ The invention utilizes Zn to realize the stripping voltammetry detection precision ²⁺ 、Cd ² ⁺ 、Pb ²⁺ 、Cu ²⁺ And Bi (Bi) ³⁺ The peak height and peak width of the dissolved current are used as input variables to build a machine learning model. Support vector regression (support vector regression, SVR) algorithm as a machine learning modeling algorithm for characterizing Zn ²⁺ 、Cd ²⁺ 、Pb ²⁺ 、Bi ³⁺ And Cu ²⁺ Peak height and peak width of dissolution current and Cd ²⁺ And Pb ²⁺ Is a non-linear mathematical relationship between the concentrations of (a). The SVR detection model established by using the peak height and the peak width as input variables is marked as H-W-SVR. And respectively optimizing parameters of the H-W-SVR detection model by using a grid optimizing algorithm.

Prior to model training, 64 samples were randomly divided into 44 samples for the modeling set and 20 samples for the validation set. The former is used to train the H-W-SVR model, and the latter is used to verify the detection performance of the H-W-SVR model. Determining coefficients using a validation set (R _v ² ) And verification set Root mean square error (Root-mean-square error of validation dataset, RMSEV) evaluation model pair Cd ²⁺ And Pb ²⁺ Concentration detection performance.

。

Wherein,and->The actual and detected Cd of the ith sample respectively ²⁺ Or Pb ²⁺ Concentration of->Is the actual Cd of n samples in the verification set ²⁺ Or Pb ²⁺ Average value of concentration. In the present invention n=20.

In detecting Cd ²⁺ When the modeling set of the H-W-SVR model determines coefficients (R _v ² ) And modeling set Root Mean Square Error (RMSEC) of 0.874 μg/L and 4.441 μg/L, respectively; r of H-W-SVR model _v ² And RMSEV of 0.815 μg/L and 5.069 μg/L, respectively, as shown in FIGS. 22-23. In detecting Pb ²⁺ R of H-W-SVR model _c ² And RMSEC values of 0.991 μg/L and 8.099 μg/L, respectively; r of H-W-SVR model _v ² And RMSEV of 0.935. Mu.g/L and 17.732. Mu.g/L, respectively, as shown in FIGS. 24-25.

Compared with a direct correction model, the H-W-SVR model uses Cd ²⁺ The root mean square error of the concentration is reduced from 10.395 mug/L to 5.069 mug/L; pb was modeled by H-W-SVR ²⁺ The root mean square error of the concentration was reduced from 37.874. Mu.g/L to 17.732. Mu.g/L. The result shows that the SVR model established by taking the peak height and the peak width of the heavy metal leaching current as input variables can improve the Cd resistance of the leaching voltammetry under the interaction interference of various metal ions ²⁺ And Pb ²⁺ Is provided.

According to the method of the present invention, it takes approximately 75 minutes to analyze a soil sample.

8 heavy metal contaminated soil samples were used to verify the detection performance of the system. Absorbance at 254nm of 8 parts of the soil extract after photolysis treatment (A ₂₅₄ ) All the organic matters are obviously reduced, which indicates that the ultraviolet light degrades the soluble organic matters in the soil leaching liquid. Soluble organic compoundsThe degradation of the substance converts the heavy metal complexed with the soluble organic matters in the soil leaching solution into free heavy metal ions which can be detected by the stripping voltammetry, thereby improving the stripping voltammetry on the weak acid soluble Cd in the soil ²⁺ And Pb ²⁺ Is provided.

The present invention compares the detection results of the detection system and the BCR-ICP-MS by the t-test method as shown in table 2. Cd (cadmium sulfide) ²⁺ And Pb ²⁺ The t-test values of the concentrations are 1.3965 and 0.0399 respectively, and all t-test values are less than t _0.05 (14) A threshold value (1.7613) for the test indicating Cd detected by the integrated automation device ²⁺ And Pb ²⁺ Concentration and Cd detected by BCR-ICP-MS ²⁺ And Pb ²⁺ There was no significant difference in concentration. The results show that the integrated automatic detection equipment developed by the invention can accurately detect the content of weak acid soluble lead and cadmium in soil.

。

Wherein t is _0.05 (14) Is 1.7613.

The invention designs a stable and accurate stripping voltammetry signal acquisition algorithm which is not influenced by potential drift, improves the automation degree of electrochemical detection equipment and ensures the stripping voltammetry detection precision of heavy metal ions. Under the coexistence of multiple metal ions, analyzing the response of the peak height and the peak width of the stripping voltammetry current; analyzing the interference rule of the multi-ion interaction on the multi-element stripping voltammetry signal; the method takes a multielement leaching voltammetric signal as input, establishes a machine learning model to inhibit interaction interference of multiple metal ions, and realizes high-precision detection of lead ions and cadmium ions in the soil weak acid leaching solution.

Claims

1. A method for detecting weak acid soluble heavy metals in soil, the method comprising:

obtaining a soil leaching solution; the soil leaching solution is obtained by mixing a soil sample and leaching solution according to a set solid-to-liquid ratio, performing ultrasonic treatment to obtain a soil mixed solution, and extracting and filtering the soil mixed solution by a suction filtration method to obtain a supernatant;

treating the soil leaching solution by adopting a photolysis method to obtain a photolysis solution; the photolytic solution includes: heavy metal ions complexed by soluble organic matters; the heavy metal ions include: lead ions and cadmium ions;

carrying out electrochemical analysis on heavy metal ions in the photolysis solution by adopting a stripping voltammetry to obtain a stripping voltammetry curve;

determining peak signal information according to the stripping voltammetry curve by adopting a peak signal acquisition algorithm; the peak signal information includes: peak height and peak width;

2. The method for detecting the weak acid soluble heavy metal in the soil according to claim 1, wherein peak signal information is determined according to the stripping voltammetry curve by adopting a peak signal acquisition algorithm, and the method specifically comprises the following steps:

Smoothing the stripping voltammetry curve to obtain a stripping curve;

determining peak categories corresponding to the current peaks on the dissolution curve based on the peak-to-peak distances; the peak-to-peak distance is a constant value determined from the dissolution potential drift;

determining peak peaks according to the dissolution curve;

determining a set of candidate points based on the peak top points; the candidate point set is a set of peaks of the current peaks adjacent to the peak peaks in a set range; the candidate point set includes: a left candidate point set and a right candidate point set;

determining a candidate point connecting line set according to the candidate point set; the candidate point connecting line set comprises a plurality of connecting lines; the connecting line is a line segment connected by any current point in the left candidate point set and any current point in the right candidate point set;

for any connecting line, determining a connecting point of the perpendicular line of the peak point and the connecting line; the vertical line is a vertical connecting line between the peak top point and the abscissa on the dissolution curve;

calculating the distance between the peak top point and the connecting point for any connecting point to obtain an initial peak height;

comparing all the initial peak heights to obtain the maximum value of the initial peak height, and determining the maximum value of the initial peak height as the peak height;

And calculating the length of the line segment according to the connecting line corresponding to the peak height to obtain the peak width.

3. The method for detecting a weak acid-soluble heavy metal in soil according to claim 2, wherein determining peak peaks according to the dissolution curve comprises:

determining a corresponding function expression according to the dissolution curve;

performing first-order derivation on the function expression to obtain a derivative function expression;

determining a characteristic point set according to the derivative function expression; the feature point set comprises n feature points; the characteristic points are extreme points or zero points; the extreme points include: maximum value points and minimum value points;

determining a point set; the set of points includes: a maximum point set, a minimum point set and a zero point set; the maximum value point set is a set of maximum value points; the minimum value point set is a set of minimum value points; the zero point set is a zero point set;

judging a peak type according to the derivative function expression and the ith characteristic point, and determining a corresponding peak point according to the peak type; the peak points include: a vertex or origin; wherein,；

for the ith feature point, if the ith feature point is in the zero point set and the ith-1 th feature point is in the maximum point set, and the (i+1) th feature point is in the minimum point set, the peak type at the ith feature point is a complete peak, and the ith feature point is the peak of the complete peak;

For the ith feature point, if the ith feature point is in the maximum value point set and the (i+1) th feature point is in the minimum value point set, the absolute value of the numerical value of the ith feature point is smaller than the absolute value of the numerical value of the (i+1) th feature point, the peak type at the ith feature point is a right shoulder, and the ith feature point is the starting point of the right shoulder;

determining a right acromion end point according to the right acromion and the start point of the right acromion;

calculating a midpoint according to the starting point of the right shoulder and the ending point of the right shoulder to obtain the vertex of the right shoulder;

determining peak tops of the stray heavy metal ions according to set conditions according to the peak points of the right shoulder peaks; the stray heavy metal ions include copper ions;

and determining peak tops according to the dissolution curve and the peak tops of the stray heavy metal ions.

4. The method for detecting the weak acid soluble heavy metal in soil according to claim 2, wherein the stripping voltammetry curve is smoothed to obtain a stripping curve, and the method specifically comprises the following steps:

carrying out initial smoothing treatment on the stripping voltammetric curve to obtain a stripping voltammetric treatment curve;

and filtering and smoothing the stripping voltammetry treatment curve by adopting an S-G filtering algorithm to obtain the stripping curve.

5. The method for detecting the weak acid soluble heavy metal in soil according to claim 1, wherein the method for determining the ion concentration calculation model specifically comprises the following steps:

acquiring training data; the training data includes: training peak signal information and corresponding label data; the tag data is the concentration of heavy metal ions;

dividing the training data into a training set and a verification set;

constructing a machine learning neural network;

inputting the training set and the corresponding label data into the machine learning neural network, and training the detection parameters in the machine learning neural network by adopting a support vector regression algorithm with the minimum error as a target to obtain a trained machine learning neural network; the detection parameters include: detecting the coefficient and root mean square;

adjusting the detection parameters of the trained machine learning neural network by adopting the verification set and the corresponding label data to obtain an adjusted machine learning neural network;

and determining the adjusted machine learning neural network as the ion concentration calculation model.

6. A system for detecting a weak acid-soluble heavy metal in soil, wherein the system is implemented by using the weak acid-soluble heavy metal detection method according to any one of claims 1 to 5, and the system comprises: the system comprises a cloud server, a microprocessor, an ultrasonic processor, an extraction and filtration device, an ultraviolet photolysis device and a potentiostat;

The ultrasonic processor, the extraction and filtration device, the ultraviolet photolysis device and the potentiostat are all connected with the microprocessor; the cloud server is connected with the microprocessor;

the microprocessor is used for sending out a control instruction;

the ultrasonic processor is used for mixing a soil sample and the leaching solution according to the control instruction and then carrying out ultrasonic treatment according to a set solid-liquid ratio to obtain a soil mixed solution;

the extraction and filtration device is used for extracting and filtering the soil mixed solution in a suction filtration mode according to the control instruction to obtain a supernatant, and taking the supernatant as a soil leaching solution;

the ultraviolet photolysis device is used for processing the soil leaching solution according to the control instruction to obtain a photolysis solution; the photolytic solution includes: heavy metal ions complexed by soluble organic matters; the heavy metal ions include: lead ions and cadmium ions;

the potentiostat is used for carrying out electrochemical analysis on heavy metal ions in the photolysis solution by adopting a stripping voltammetry according to the control instruction to obtain a stripping voltammetry curve; the electrochemical analysis includes: outputting constant negative voltage according to the control instruction, performing electrochemical deposition on heavy metal ions in the photolysis solution, outputting an excitation voltage signal according to the control instruction, and performing electrochemical dissolution on deposited heavy metal to obtain a dissolution voltammetry curve;

The cloud server is used for:

7. The soil weak acid soluble heavy metal detection system of claim 6, further comprising: a magnetic stirrer;

the magnetic stirrer is connected with the microprocessor;

the magnetic stirrer is used for stirring the soil leaching liquid according to the control instruction.

8. The soil weak acid soluble heavy metal detection system of claim 6, further comprising: a quantitative peristaltic pump and an electrochemical analytical cell;

the quantitative peristaltic pump is respectively connected with the microprocessor, the ultraviolet photolysis device and the electrochemical analysis cell;

and the quantitative peristaltic pump is used for quantitatively extracting the photolytic solution to the electrochemical analysis cell according to the control instruction.