Brown sugar type identification device and method

Abstract

The invention discloses a brown sugar type identification device and method. The brown sugar type identification device comprises a computer and two detection mechanisms, each detection mechanism comprises an electrochemical workstation, a liquid injection module, a magnetic stirrer, a beaker, a three-electrode sensor and a sensor support, the beaker is placed on the magnetic stirrer, a magnetic stirrer of the magnetic stirrer is placed in the beaker, and the three-electrode sensor is arranged on the three-electrode sensor. The three-electrode sensor extends into the beaker, the sensor support is used for fixing the three-electrode sensor, the liquid injection module is used for injecting liquid into the beaker, the three-electrode sensor is electrically connected with the electrochemical workstation, and the computer is electrically connected with the electrochemical workstation, the liquid injection module and the magnetic stirrer. The brown sugar type can be quickly and accurately identified, and the operation is simple.

Description

Technical Field

[0001] The present invention relates to the technical field of brown sugar detection, and in particular to a brown sugar type identification device and method. Background Art

[0002] Traditional brown sugar is made from sugar cane and is crystallized through multiple steps. As a sweet substance with a long history, in addition to having the functions of sugar, it also retains the polyphenols, flavonoids, vitamins and other substances of sugar cane to the maximum extent, so it has a high nutritional value. However, the quality of commercially available brown sugar products varies. Some unscrupulous merchants use other sugars for reprocessing to obtain second-grade brown sugar with similar appearance, impersonating first-grade brown sugar or premium brown sugar, which greatly reduces its nutritional value. Therefore, it is particularly important to distinguish the types of brown sugar.

[0003] The existing methods for detecting the types of brown sugar include instrumental analysis and chemical detection. Although the instrumental analysis method is simple to operate, it has the defects of large equipment size, high cost and low detection accuracy; the chemical detection method has the disadvantages of complicated operation and poor repeatability. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a brown sugar type identification device and method, which can quickly and accurately identify the brown sugar type and is easy to operate.

[0005] In order to solve the above problems, the present invention adopts the following technical solutions:

[0006] The invention discloses a brown sugar type identification device, comprising a computer and two detection mechanisms, wherein the detection mechanism comprises an electrochemical workstation, a liquid injection module, a magnetic stirrer, a beaker, a three-electrode sensor and a sensor bracket, wherein the beaker is placed on the magnetic stirrer, a magnetic stirrer of the magnetic stirrer is placed in the beaker, the three-electrode sensor extends into the beaker, the sensor bracket is used for fixing the three-electrode sensor, the liquid injection module is used for injecting liquid into the beaker, the three-electrode sensor is electrically connected to the electrochemical workstation, and the computer is electrically connected to the electrochemical workstation, the liquid injection module and the magnetic stirrer respectively.

[0007] In this scheme, the brown sugar to be tested is dissolved to obtain a brown sugar solution to be tested, and the brown sugar solution to be tested is mixed with A ml of 0.01 mol / L NaOH solution to obtain two identical mixed solutions, and the two mixed solutions are poured into the beakers of two detection mechanisms respectively. The three-electrode sensor is inserted into the mixed solution of the corresponding beaker, one mixed solution is detected by chronoamperometry, and the other mixed solution is detected by cyclic voltammetry. During the detection process, two liquid injection modules are respectively dripped into the two mixed solutions at an interval of d seconds, and a total of m times are dripped. The magnetic stirrer stirs the mixed solution in the corresponding beaker, and the two electrochemical workstations send the detection current sets I1 and I2 to the computer respectively. The computer normalizes the detection current sets I1 and I2 obtained by the chronoamperometry and cyclic voltammetry detection, and then interleaves and merges them to obtain the merged data set IE, inputs the characteristic display analysis model to obtain the characteristic value EKG, and judges the type of brown sugar according to the characteristic value EKG.

[0008] Preferably, the sensor bracket includes a frame body and a sensor fixing seat arranged on the frame body, the sensor fixing seat is located directly above the beaker, the sensor fixing seat includes an annular support, three guide rails are arranged radially along the annular support, and the angle between adjacent guide rails is 120 degrees. The guide rail is provided with a slider that can slide along the guide rail and a driving mechanism for driving the slider to slide along the guide rail. A clamping module for clamping / relaxing the electrode is provided at the bottom of the slider. The three-electrode sensor includes a working electrode, a counter electrode, and a reference electrode. The working electrode, the counter electrode, and the reference electrode are clamped by three clamping modules respectively, and the driving mechanism is electrically connected to the computer.

[0009] The detection positions of the working electrode, counter electrode and reference electrode can be adjusted by adjusting the positions of the three sliders on the corresponding guide rails. Before detection, the working electrode and counter electrode of each detection mechanism are adjusted to the same optimal detection position.

[0010] Preferably, the driving mechanism comprises a screw and a stepping motor, the screw passes through the slider and is threadedly connected to the slider, the screw runs in the same direction as the guide rail, and the stepping motor is used to drive the screw to rotate.

[0011] Preferably, the working electrode is a copper sheet electrode, the counter electrode is a platinum electrode, and the reference electrode is a saturated calomel electrode.

[0012] Preferably, the liquid injection module is a microinjection pump.

[0013] A brown sugar type identification method of the present invention is used in the above-mentioned brown sugar type identification device, comprising the following steps:

[0014] S1: Add two identical mixed solutions into the beakers of two detection mechanisms, wherein the mixed solution is a mixture of K ml of the brown sugar solution to be tested and A ml of 0.01 mol / L NaOH solution, and the three-electrode sensor of each detection mechanism is inserted into the mixed solution in the corresponding beaker;

[0015] S2: Adjust the working electrode and counter electrode of each detection mechanism to the same optimal detection position;

[0016] S3: The two mixed solutions are respectively detected by chronoamperometry and cyclic voltammetry to obtain corresponding detection current sets I1 and I2. The two electrochemical workstations send the detection current sets I1 and I2 to the computer respectively. During the whole detection process, the two liquid injection modules simultaneously add h ml of the brown sugar solution to be tested to the two mixed solutions once every d seconds, and add m times in total. The magnetic stirrer stirs the mixed solution in the corresponding beaker;

[0017] S4: the computer normalizes the detection current sets I1 and I2 to obtain corresponding normalized data sets IG1 and IG2;

[0018] S5: The computer interleaves and merges the normalized data sets IG1 and IG2 to obtain a merged data set IE;

[0019] S6: The computer inputs the combined data set IE as an input signal into the feature display analysis model, and the feature display analysis model outputs a feature value EKG;

[0020] S7: The computer determines the type of brown sugar based on the characteristic value EKG.

[0021] In this method, the detection current set I2 obtained by cyclic voltammetry reflects the redox properties of brown sugar. The greater the content of effective ingredients in brown sugar, the more significant the signal of the redox reflection. The detection current set I2 is used to anchor the detection current set I1 obtained by chronoamperometry, which overcomes the errors caused by accidental factors, improves the accuracy of brown sugar type identification, and is simple to operate.

[0022] Preferably, step S2 comprises the following steps:

[0023] The two detection mechanisms are respectively denoted as D1 and D2. The reference electrode of the detection mechanism D1 is adjusted to a preset position, and the working electrode and the counter electrode of the detection mechanism D1 are respectively adjusted to the optimal detection positions; the position of the reference electrode of the detection mechanism D2 is adjusted to the same position as the reference electrode of the detection mechanism D1, the position of the working electrode of the detection mechanism D2 is adjusted to the same position as the working electrode of the detection mechanism D1, and the position of the counter electrode of the detection mechanism D2 is adjusted to the same position as the counter electrode of the detection mechanism D1;

[0024] The method for adjusting the working electrode and the counter electrode of the detection mechanism D1 to the optimal detection position is as follows:

[0025] The working electrode and the counter electrode are adjusted to the initial positions at the outermost sides of the guide rails, and the working electrode is adjusted to different detection positions on the guide rails. When the working electrode moves to a detection position on the guide rails, a detection is performed using cyclic voltammetry to obtain a CV curve, and the reduction peak of the CV curve is recorded. The detection position corresponding to the CV curve with the largest reduction peak is taken as the optimal detection position of the working electrode, and the working electrode is adjusted to the optimal detection position;

[0026] Next, adjust the different detection positions of the counter electrode on the guide rail. When the counter electrode moves to a detection position on the guide rail, perform a detection using cyclic voltammetry to obtain a CV curve. Record the reduction peak of the CV curve, and take the detection position corresponding to the CV curve with the largest reduction peak as the optimal detection position of the counter electrode. Adjust the counter electrode to the optimal detection position.

[0027] Preferably, step S3 comprises the following steps:

[0028] The two mixed solutions were tested simultaneously by chronoamperometry and cyclic voltammetry, respectively, to obtain corresponding detection current sets I1 and I2. The two electrochemical workstations sent the detection current sets I1 and I2 to the computer respectively. During the whole detection process, the two liquid injection modules simultaneously added h ml of the brown sugar solution to be tested to the two mixed solutions once every d seconds, for a total of m times. The magnetic stirrer stirred the mixed solution in the corresponding beaker.

[0029] I1={I1(t1), I1(t2)…I1(t n )}, I2={I2(t1), I2(t2)...I2(t n )},t i is the i-th sampling moment, I1(t i ) is the sampling time t using the chronoamperometry i The absolute value of the detected current value, I2(t i ) is the sampling time t of cyclic voltammetry i The absolute value of the detected current value is 1≤i≤n, where n is the number of sampling times.

[0030] Preferably, S4 comprises the following steps:

[0031] The computer normalizes the detection current set I1 to the interval [1, 5] to obtain the corresponding normalized data set IG1, IG1 = {IG1(t1), IG1(t2)…IG1(tn )},IG1(t i ) is I1(t i ) corresponding normalized value;

[0032] The computer normalizes the detection current set I2 to the interval [1, 5] to obtain the corresponding normalized data set IG2, IG2 = {IG2(t1), IG2(t2)…IG2(t n )}, IG2(t i ) is I2(t i ) corresponding normalized value;

[0033] The merged data set IE in step S5 is:

[0034] IE={IE(1), IE(2)...IE(2n-1), IE(2n)},

[0035] Among them, IG1(t i )=IE(2(i-1)+1),IG2(t i )=IE(2i).

[0036] Preferably, step S6 comprises the following steps:

[0037] The computer inputs the data IE(j) in the combined data set IE as the input signal x(j) into the feature display analysis model, where j=1, 2...2n:

[0038]

[0039] Among them, u(T) is an elastic system, is the excitation signal, ω is the frequency, θ is the initial angle, p is the intensity of the excitation signal, Q, a, and b are all constants;

[0040] Adjust the value of p from small to large, and the characteristic display analysis model approaches the transition condition. When the characteristic display analysis model reaches the transition state, stop adjusting p, record the current value of p as ps, and the characteristic display analysis model outputs the characteristic value EKG.

[0041]

[0042] Preferably, step S7 comprises the following steps:

[0043] When W1≤EKG<W2, the brown sugar to be tested is judged to be industrial brown sugar;

[0044] When W2≤EKG<W3, the brown sugar to be tested is judged to be grade II brown sugar;

[0045] When W3≤EKG<W4, the brown sugar to be tested is judged to be first-grade brown sugar;

[0046] When W4≤EKG≤W5, the brown sugar to be tested is judged to be high-quality brown sugar.

[0047] The beneficial effects of the present invention are that the types of brown sugar can be identified quickly and accurately, and the operation is simple. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of the structure of the testing organization;

[0049] Figure 2 It is a structural schematic diagram of the sensor fixing seat.

[0050] In the figure: 1. electrochemical workstation, 2. liquid injection module, 3. magnetic stirrer, 4. beaker, 5. three-electrode sensor, 6. magnetic stirring bar, 7. frame, 8. sensor fixing seat, 9. annular support, 10. guide rail, 11. slider, 12. screw rod, 13. stepping motor. DETAILED DESCRIPTION

[0051] The technical solution of the present invention is further specifically described below through embodiments and in conjunction with the accompanying drawings.

[0052] Embodiment: A brown sugar type identification device of this embodiment, such as Figure 1 , Figure 2 As shown, it includes a computer and two detection mechanisms, the detection mechanism includes an electrochemical workstation 1, a liquid injection module 2, a magnetic stirrer 3, a beaker 4, a three-electrode sensor 5 and a sensor bracket, the beaker 4 is placed on the magnetic stirrer 3, the magnetic stirrer 6 of the magnetic stirrer 3 is placed in the beaker 4, the three-electrode sensor 5 extends into the beaker 4, the sensor bracket is used to fix the three-electrode sensor 5, the liquid injection module 2 is used to inject liquid into the beaker 4, the three-electrode sensor 5 is electrically connected to the electrochemical workstation 1, and the computer is electrically connected to the electrochemical workstation 1, the liquid injection module 2, and the magnetic stirrer 3 respectively.

[0053] The sensor bracket includes a frame body 7 and a sensor fixing seat 8 arranged on the frame body 7. The sensor fixing seat 8 is located directly above the beaker 4. The sensor fixing seat 8 includes an annular support 9. Three guide rails 10 are arranged radially along the annular support 9 in the annular support 9. The angle between adjacent guide rails 10 is 120 degrees. A slider 11 that can slide along the guide rail 10 and a driving mechanism for driving the slider 11 to slide along the guide rail 10 are provided on the guide rail 10. The driving mechanism includes a screw rod 12 and a stepper motor 13. The screw rod 12 passes through the slider 11 and is threadedly connected to the slider 11. The screw rod 12 and the guide rail 10 are in the same direction. The stepper motor 13 is used to drive the screw rod 12 to rotate. A clamping module for clamping / relaxing electrodes is provided at the bottom of the slider 11. The three-electrode sensor 5 includes a working electrode, a counter electrode, and a reference electrode. The working electrode, the counter electrode, and the reference electrode are clamped by three clamping modules respectively, and the driving mechanism is electrically connected to the computer.

[0054] The working electrode is a copper sheet electrode, the counter electrode is a platinum electrode, and the reference electrode is a saturated calomel electrode. The liquid injection module is a micro-injection pump.

[0055] In this scheme, the brown sugar to be tested is dissolved to obtain a brown sugar solution to be tested, and the brown sugar solution to be tested is mixed with A ml of 0.01 mol / L NaOH solution to obtain two identical mixed solutions, and the two mixed solutions are poured into the beakers of the two detection mechanisms respectively, and the three-electrode sensor is inserted into the mixed solutions in the corresponding beakers. The detection positions of the working electrode, the counter electrode, and the reference electrode can be adjusted by adjusting the positions of the three sliders on the corresponding guide rails. Before detection, the working electrode and the counter electrode of each detection mechanism are adjusted to the same optimal detection position.

[0056] During the detection, one mixed solution is detected by chronoamperometry, and the other mixed solution is detected by cyclic voltammetry. During the detection process, two liquid injection modules simultaneously add h ml of the brown sugar solution to be tested to the two mixed solutions at intervals of d seconds, and a total of m times. The magnetic stirrer stirs the mixed solution in the corresponding beaker, and the two electrochemical workstations send the detection current sets I1 and I2 to the computer respectively. The computer normalizes the detection current sets I1 and I2 obtained by the chronoamperometry and cyclic voltammetry detection, and then interleaves and merges them to obtain the merged data set IE, which is input into the feature display analysis model to obtain the characteristic value EKG, and the type of brown sugar is determined according to the characteristic value EKG.

[0057] A brown sugar type identification method of this embodiment is used in the brown sugar type identification device mentioned above, and includes the following steps:

[0058] S1: Add two identical mixed solutions into the beakers of the two detection mechanisms. The mixed solution is a mixture of K ml of the brown sugar solution to be tested and A ml of 0.01 mol / L NaOH solution. The three-electrode sensor of each detection mechanism is inserted into the mixed solution in the corresponding beaker.

[0059] S2: Adjust the working electrode and counter electrode of each detection mechanism to the same optimal detection position.

[0060] Step S2 includes the following steps:

[0061] The two detection mechanisms are respectively denoted as D1 and D2. The reference electrode of the detection mechanism D1 is adjusted to a preset position, and the working electrode and the counter electrode of the detection mechanism D1 are respectively adjusted to the optimal detection positions; the position of the reference electrode of the detection mechanism D2 is adjusted to the same position as the reference electrode of the detection mechanism D1, the position of the working electrode of the detection mechanism D2 is adjusted to the same position as the working electrode of the detection mechanism D1, and the position of the counter electrode of the detection mechanism D2 is adjusted to the same position as the counter electrode of the detection mechanism D1;

[0062] The method for adjusting the working electrode and the counter electrode of the detection mechanism D1 to the optimal detection position is as follows:

[0063] The working electrode and the counter electrode are adjusted to the initial positions at the outermost sides of the guide rails, and the working electrode is adjusted to different detection positions on the guide rails. When the working electrode moves to a detection position on the guide rails, a detection is performed using cyclic voltammetry to obtain a CV curve, and the reduction peak of the CV curve is recorded. The detection position corresponding to the CV curve with the largest reduction peak is taken as the optimal detection position of the working electrode, and the working electrode is adjusted to the optimal detection position;

[0064] Next, adjust the different detection positions of the counter electrode on the guide rail. When the counter electrode moves to a detection position on the guide rail, perform a detection using cyclic voltammetry to obtain a CV curve. Record the reduction peak of the CV curve, and take the detection position corresponding to the CV curve with the largest reduction peak as the optimal detection position of the counter electrode. Adjust the counter electrode to the optimal detection position.

[0065] S3: The two mixed solutions are detected simultaneously by chronoamperometry and cyclic voltammetry respectively to obtain corresponding detection current sets I1 and I2. The two electrochemical workstations send the detection current sets I1 and I2 to the computer respectively. During the entire detection process, h ml of the brown sugar solution to be tested is added to the two mixed solutions simultaneously by two liquid injection modules once every d seconds, for a total of m additions. The magnetic stirrer stirs the mixed solutions in the corresponding beakers.

[0066] Step S3 includes the following steps:

[0067] The two mixed solutions were tested simultaneously by chronoamperometry and cyclic voltammetry, respectively, to obtain corresponding detection current sets I1 and I2. The two electrochemical workstations sent the detection current sets I1 and I2 to the computer respectively. During the whole detection process, the two liquid injection modules simultaneously added h ml of the brown sugar solution to be tested to the two mixed solutions once every d seconds, for a total of m times. The magnetic stirrer stirred the mixed solution in the corresponding beaker.

[0068] I1={I1(t1), I1(t2)…I1(t n )}, I2={I2(t1), I2(t2)...I2(t n )},t i is the i-th sampling moment, I1(t i ) is the sampling time t using the chronoamperometry i The absolute value of the detected current value, I2(t i ) is the sampling time t of cyclic voltammetry i The absolute value of the detected current value is 1≤i≤n, where n is the number of sampling times.

[0069] t1 is the 0th second from the start of detection, t n The time is (m+1)*d seconds from the start of the test. The scanning potential of the chronoamperometry is +0.5V constant potential; the scanning range of the cyclic voltammetry is +0.4V~+0.6V, and the scanning rate is 0.10V / s. The magnetic stirrer continuously stirs the mixed solution during the entire test process.

[0070] S4: The computer normalizes the detection current set I1 to the interval [1, 5] to obtain the corresponding normalized data set IG1, IG1 = {IG1(t1), IG1(t2)…IG1(t n )},IG1(t i ) is I1(t i ) corresponding normalized value;

[0071] The computer normalizes the detection current set I2 to the interval [1, 5] to obtain the corresponding normalized data set IG2, IG2 = {IG2(t1), IG2(t2)…IG2(t n )}, IG2(t i ) is I2(t i ) corresponds to the normalized value.

[0072] S5: The computer interleaves and merges the normalized data sets IG1 and IG2 to obtain a merged data set IE, where IE = {IE(1), IE(2) ... IE(2n-1), IE(2n)}, where IG1(ti )=IE(2(i-1)+1),IG2(t i )=IE(2i).

[0073] The method for interlaced merging of normalized data sets IG1 and IG2 is: generate an empty merged data set IE, first put the first element of the normalized data set IG1 into the merged data set IE, then put the first element of the normalized data set IG2 into the merged data set IE, then put the second element of the normalized data set IG1 into the merged data set IE, then put the second element of the normalized data set IG2 into the merged data set IE, and repeat this cycle until all elements in the normalized data sets IG1 and IG2 are put into the merged data set IE.

[0074] For example: IG1={IG1(t1), IG1(t2), IG1(t3)},

[0075] IG2={IG2(t1), IG2(t2), IG2(t3)],

[0076] The normalized data sets IG1 and IG2 are interleaved and merged to obtain a merged data set IE={IG1(t1), IG2(t1), IG1(t2), IG2(t2), IG1(t3), IG2(t3)}.

[0077] S6: The computer inputs the combined data set IE as an input signal into the feature display analysis model, and the feature display analysis model outputs a feature value EKG.

[0078] Step S6 includes the following steps:

[0079] The computer inputs the data IE(j) in the combined data set IE as the input signal x(j) into the feature display analysis model, where j=1, 2...2n:

[0080]

[0081] Among them, u(T) is an elastic system, is the excitation signal, ω is the frequency, θ is the initial angle, p is the intensity of the excitation signal, Q, a, and b are all constants, cos(ωj+θ) is the cosine frequency component of the input signal, and sin(ωj+θ) is the sine frequency component of the input signal;

[0082] Adjust the value of p from small to large, and the characteristic display analysis model approaches the transition condition. When the characteristic display analysis model reaches the transition state, stop adjusting p, record the current value of p as ps, and the characteristic display analysis model outputs the characteristic value EKG.

[0083]

[0084] S7: When W1≤EKG<W2, the brown sugar to be tested is judged to be industrial brown sugar;

[0085] When W2≤EKG<W3, the brown sugar to be tested is judged to be grade II brown sugar;

[0086] When W3≤EKG<W4, the brown sugar to be tested is judged to be first-grade brown sugar;

[0087] When W4≤EKG≤W5, the brown sugar to be tested is judged to be high-quality brown sugar.

[0088] In this scheme, the brown sugar to be tested is dissolved to obtain a brown sugar solution to be tested, and the brown sugar solution to be tested is mixed with A ml of 0.01 mol / L NaOH solution to obtain two identical mixed solutions. The detection current sets I1 and I2 obtained by chronoamperometry and cyclic voltammetry are normalized and then interlaced to obtain a combined data set IE, which is input into the feature display analysis model to obtain the eigenvalue EKG, and the type of brown sugar is determined according to the eigenvalue EKG.

[0089] In this method, the detection current set I2 obtained by cyclic voltammetry reflects the redox properties of brown sugar. The greater the content of effective ingredients in brown sugar, the more significant the signal of the redox reflection. The detection current set I2 is used to anchor the detection current set I1 obtained by chronoamperometry, which overcomes the errors caused by accidental factors, improves the accuracy of brown sugar type identification, and is simple to operate.

[0090] In this embodiment, the initially configured mixed solution is formed by mixing 100 ml of a 20 g / L brown sugar solution to be tested and 20 ml of a 0.01 mol / L NaOH solution. During the entire detection process, 50 μL of the brown sugar solution to be tested is added to the two mixed solutions at the same time every 25 seconds and stirred, for a total of 20 additions.

[0091] In this embodiment, W1=0.2, W2=0.38, W3=0.46, W4=0.54, W5=0.61, that is:

[0092] When 0.2≤EKG<0.38, the brown sugar to be tested is judged to be industrial brown sugar;

[0093] When 0.38≤EKG<0.46, the brown sugar to be tested is judged to be grade II brown sugar;

[0094] When 0.46≤EKG<0.54, the brown sugar to be tested is judged to be first-grade brown sugar;

[0095] When 0.54≤EKG≤0.61, the brown sugar to be tested is judged to be high-quality brown sugar.

Claims

1. A brown sugar type identification device, characterized in that: The invention comprises a computer and two detection mechanisms, wherein the detection mechanism comprises an electrochemical workstation (1), a liquid injection module (2), a magnetic stirrer (3), a beaker (4), a three-electrode sensor (5) and a sensor bracket, wherein the beaker (4) is placed on the magnetic stirrer (3), a magnetic stirrer (6) of the magnetic stirrer (3) is placed in the beaker (4), the three-electrode sensor (5) extends into the beaker (4), the sensor bracket is used to fix the three-electrode sensor (5), the liquid injection module (2) is used to inject liquid into the beaker (4), the three-electrode sensor (5) is electrically connected to the electrochemical workstation (1), and the computer is electrically connected to the electrochemical workstation (1), the liquid injection module (2) and the magnetic stirrer (3) respectively.

2. A brown sugar type identification device according to claim 1, characterized in that: The sensor bracket comprises a frame body (7) and a sensor fixing seat (8) arranged on the frame body (7), the sensor fixing seat (8) is located directly above the beaker (4), the sensor fixing seat (8) comprises an annular support (9), three guide rails (10) are arranged radially along the annular support (9), the angle between adjacent guide rails (10) is 120 degrees, a slider (11) which can slide along the guide rail (10) and a driving mechanism for driving the slider (11) to slide along the guide rail (10) are provided on the guide rail (10), a clamping module for clamping / relaxing electrodes is provided at the bottom of the slider (11), the three-electrode sensor (5) comprises a working electrode, a counter electrode and a reference electrode, the working electrode, the counter electrode and the reference electrode are clamped by three clamping modules respectively, and the driving mechanism is electrically connected to a computer.

3. A brown sugar type identification device according to claim 2, characterized in that: The driving mechanism comprises a screw rod (12) and a stepping motor (13); the screw rod (12) passes through the slider (11) and is threadedly connected to the slider (11); the screw rod (12) and the guide rail (10) are aligned in direction; and the stepping motor (13) is used to drive the screw rod (12) to rotate.

4. A brown sugar type identification device according to claim 2, characterized in that: The working electrode is a copper sheet electrode, the counter electrode is a platinum electrode, and the reference electrode is a saturated calomel electrode.

5. The brown sugar type identification device according to claim 1, characterized in that: The liquid injection module (2) is a microinjection pump.

6. A method for identifying brown sugar types, used in a brown sugar type identification device according to claim 2, characterized in that: The following steps are involved: S1: Add two identical mixed solutions into the beakers of two detection mechanisms, wherein the mixed solution is a mixture of K ml of the brown sugar solution to be tested and A ml of 0.01 mol / L NaOH solution, and the three-electrode sensor of each detection mechanism is inserted into the mixed solution in the corresponding beaker; S2: Adjust the working electrode and counter electrode of each detection mechanism to the same optimal detection position; S3: The two mixed solutions are respectively detected by chronoamperometry and cyclic voltammetry to obtain corresponding detection current sets I1 and I2. The two electrochemical workstations send the detection current sets I1 and I2 to the computer respectively. During the whole detection process, the two liquid injection modules simultaneously add h ml of the brown sugar solution to be tested to the two mixed solutions once every d seconds, and add m times in total. The magnetic stirrer stirs the mixed solution in the corresponding beaker; S4: the computer normalizes the detection current sets I1 and I2 to obtain corresponding normalized data sets IG1 and IG2; S5: The computer interleaves and merges the normalized data sets IG1 and IG2 to obtain a merged data set IE; S6: The computer inputs the combined data set IE as an input signal into the feature display analysis model, and the feature display analysis model outputs a feature value EKG; S7: The computer determines the type of brown sugar based on the characteristic value EKG.

7. A method for identifying brown sugar types according to claim 6, characterized in that: The step S2 comprises the following steps: The two detection mechanisms are respectively denoted as D1 and D2. The reference electrode of the detection mechanism D1 is adjusted to a preset position, and the working electrode and the counter electrode of the detection mechanism D1 are respectively adjusted to the optimal detection positions; the position of the reference electrode of the detection mechanism D2 is adjusted to the same position as the reference electrode of the detection mechanism D1, the position of the working electrode of the detection mechanism D2 is adjusted to the same position as the working electrode of the detection mechanism D1, and the position of the counter electrode of the detection mechanism D2 is adjusted to the same position as the counter electrode of the detection mechanism D1; The method for adjusting the working electrode and the counter electrode of the detection mechanism D1 to the optimal detection position is as follows: The working electrode and the counter electrode are adjusted to the initial positions at the outermost sides of the guide rails, and the working electrode is adjusted to different detection positions on the guide rails. When the working electrode moves to a detection position on the guide rails, a detection is performed using cyclic voltammetry to obtain a CV curve, and the reduction peak of the CV curve is recorded. The detection position corresponding to the CV curve with the largest reduction peak is taken as the optimal detection position of the working electrode, and the working electrode is adjusted to the optimal detection position; Next, adjust the different detection positions of the counter electrode on the guide rail. When the counter electrode moves to a detection position on the guide rail, perform a detection using cyclic voltammetry to obtain a CV curve. Record the reduction peak of the CV curve, and take the detection position corresponding to the CV curve with the largest reduction peak as the optimal detection position of the counter electrode. Adjust the counter electrode to the optimal detection position.

8. A method for identifying brown sugar types according to claim 6, characterized in that: The step S3 comprises the following steps: The two mixed solutions are detected simultaneously by chronoamperometry and cyclic voltammetry, respectively, to obtain corresponding detection current sets I1 and I2. The two electrochemical workstations send the detection current sets I1 and I2 to the computer respectively. During the whole detection process, the two liquid injection modules simultaneously add h milliliters of the brown sugar solution to be tested to the two mixed solutions once every d seconds, and add m times in total. The magnetic stirrer stirs the mixed solution in the corresponding beaker, I1={I1(t1), I1(t2)…I1(t n )], I2={I2(t1), I2(t2)...I2(t n )},t i is the i-th sampling moment, I1(t i ) is the sampling time t using the chronoamperometry i The absolute value of the detected current value, I2(t i ) is the sampling time t of cyclic voltammetry i The absolute value of the detected current value is 1≤i≤n, where n is the number of sampling times.

9. A method for identifying brown sugar types according to claim 8, characterized in that: The S4 comprises the following steps: The computer normalizes the detection current set I1 to the interval [1, 5] to obtain the corresponding normalized data set IG1, IG1 = {IG1(t1), IG1(t2)…IG1(t n )],IG1(t i ) is I1(t i ) corresponding normalized value; The computer normalizes the detection current set I2 to the interval [1, 5] to obtain the corresponding normalized data set IG2, IG2 = {IG2(t1), IG2(t2)…IG2(t n )},IG2(t i ) is I2(t i ) corresponding normalized value; The merged data set IE in step S5 is: IE={IE(1), IE(2)...IE(2n-1), IE(2n)}, Among them, IG1(t i )=IE(2(i-1)+1), IG2(t i ) = IE(2i).

10. A method for identifying brown sugar types according to claim 9, characterized in that: The step S6 comprises the following steps: The computer inputs the data IE(j) in the combined data set IE as the input signal x(j) into the feature display analysis model, where j=1, 2...2n: Among them, u(T) is an elastic system, is the excitation signal, ω is the frequency, θ is the initial angle, p is the intensity of the excitation signal, Q, a, and b are all constants; Adjust the value of p from small to large, and the characteristic display analysis model approaches the transition condition. When the characteristic display analysis model reaches the transition state, stop adjusting p, record the current value of p as ps, and the characteristic display analysis model outputs the characteristic value EKG.

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