Method for extracting cereal aleurone layer, rice milling machine control system and storage medium

Abstract

The present invention discloses a method for extracting cereal aleurone layer, a control system for a rice milling machine and a storage medium, and has established the relationship between the control frequency of the sand roller of a new type of rice milling machine and the single milling depth, as well as the relationship between the opening degree of the new type of rice milling machine and the number of milling times for the same object. By using the method of the present invention, the cereal aleurone layer can be accurately extracted. The present invention controls the frequency quantity of the frequency converter of the rice milling machine, that is, controls the single milling depth by controlling the control frequency of the sand roller. Experiments prove that the present invention can accurately extract the aleurone layer of cereals. The present invention controls the discharge opening degree of the rice milling machine, and further more accurately controls the number of milling times, improving the accuracy and reliability of aleurone layer extraction.

Description

Technical Field

[0001] The present invention relates to grain processing technology, in particular to a method for extracting cereal aleurone layer, a control system for a rice milling machine, and a storage medium. Background Art

[0002] The new type of rice milling machine is different from the general rice milling machine:

[0003] (1) The general rice milling machine adopts a large rice milling chamber, and one rice milling machine is one (or two) large rice milling chambers; while the new type of rice milling machine divides a large rice milling chamber into several small rice milling chambers by using the differential idea.

[0004] (2) The processing method of the general rice milling machine is "grinding" and "shaving" (for the iron roller, it is "grinding" and "rubbing"); while the processing method of the new type of rice milling machine is mainly "shaving", and because the extrusion pressure of the single divided rice milling chamber is weak, and the collision and tumbling are less, the "grinding" is significantly weakened.

[0005] (3) The most important thing is that their control elements are different. The general rice milling machine can directly perform closed-loop control through the rice milling pressure or current feedback. The new type of rice milling machine is different. The rice milling chamber becomes several, and there is no condition or necessity to measure the rice milling pressure. At the same time, on the one hand, it provides frequency conversion control of the sand roller, changes the rotation speed of the sand roller through frequency conversion operation, and the minimum control unit is 0.1 Hz; on the other hand, it also provides precise control of the opening and closing degrees of the feeding and discharging, and the minimum control unit can reach 0.1% of the whole opening and closing process; the change of any control element can bring about the change of the current of the rice milling machine, and more importantly, the change of the corresponding processing technology.

[0006] For the new type of rice milling machine, the change of the current is composed of complex factors. The combined change of multiple control elements can cause the fluctuation of the current, or it can not cause the fluctuation of the current, but it can bring about significant changes in the processing technology, that is:

[0007] (1) There is no corresponding or linear relationship between the current and the processing technology.

[0008] (2) The factors constituting the change of the current are diverse, and the linear relationship between the control elements and the current is also lost.

[0009] Therefore, the intelligent control method and algorithm for online process closed-loop extraction of aleurone layer based on the general rice milling machine are completely inapplicable to the process requirements for extracting aleurone layer of the new type of rice milling machine.

[0010] The aleurone layer has become the most precious raw material for functional and health foods due to its scarce characteristics of functional effectiveness, safety, and naturalness. Therefore, whether from the perspective of food security or the requirements put forward by residents' health, extracting the aleurone layer will become the core demand for future grain processing.

[0011] The new rice milling machine can better meet the precise processing requirements for extracting the aleurone layer due to its processing uniformity. Although its output is only 1 / 4 - 1 / 3 of that of the general rice milling machine, the new rice milling machine will still have a place in the future. Summary of the Invention

[0012] The technical problem to be solved by the present invention is to provide a method for extracting the aleurone layer of grains, a control system for a rice milling machine, and a storage medium, so as to accurately extract the aleurone layer of grains in view of the deficiencies of the prior art.

[0013] To solve the above technical problems, the technical solution adopted by the present invention is: a method for extracting the aleurone layer of grains, which is implemented by a rice milling machine system. The rice milling machine system includes multiple rice milling machines arranged in sequence. The multiple rice milling machines arranged in sequence are divided into four groups, and each group includes M rice milling machines. The method includes:

[0014] In the i-th rice milling process, the amount of inverter frequency ΔMi to be adjusted is expressed as: ΔMi = mzi×ΔZ - myi×ΔYmi; i = 1, 2; ΔZ = Z - Z0, where Z is the percentage of Z type detected in the i-th rice milling process, Z0 is the maximum allowable value of Z type in the i-th rice milling process, mzi is the change amount of Z type with the change of the frequency controlled by the sand roller speed in the i-th rice milling process, my1 is the total change amount of types E, F, G, H, and I with the change of the frequency controlled by the sand roller speed in the first rice milling process, ΔYm1 = the total number of types E, F, G, H, and I in the first rice milling process - Ym10, Ym10 is the maximum allowable value of the total number of types E, F, G, H, and I in the first rice milling process, my2 is the total change amount of types F, G, H, and I with the change of the frequency controlled by the sand roller speed in the second rice milling process, ΔYm2 = the total number of types F, G, H, and I detected in the second rice milling process - Ym20, and Ym20 is the maximum allowable value of the total number of types F, G, H, and I in the second rice milling process;

[0015] In the j-th rice milling process, the amount of inverter frequency ΔMj to be adjusted is expressed as: ΔMj = myj×ΔYmj - mkj×ΔIj; j = 3, 4; my3 is the total change amount of types A, B, and C with the change of the frequency controlled by the sand roller speed in the third rice milling process, my4 is the total change amount of types A, B, C, and D with the change of the frequency controlled by the sand roller speed in the fourth rice milling process, ΔYm3 is the total number of detected values of types A, B, and C in the third rice milling process, ΔYm4 is the total number of detected values of types A, B, C, and D in the fourth rice milling process, mk3 is the change amount of type I with the change of the frequency controlled by the sand roller speed in the third rice milling process, mk4 is the change amount of type I with the change of the frequency controlled by the sand roller speed in the fourth rice milling process, and ΔIj is the detected value of type I in the j-th rice milling process;

[0016] Classes Z, A, B, C, D, E, F, G, H, and I are respectively defined as the outer cortex of the grain not being milled off, the outer cortex being milled by 20%, the outer cortex being milled by 50%, the outer cortex being milled by 80%, the outer cortex being milled by 100%, the aleurone layer being milled by 20%, the aleurone layer being milled by 50%, the aleurone layer being milled by 80%, the aleurone layer being milled by 100%, and being milled to the endosperm.

[0017] The present invention controls the frequency quantity of the frequency converter of the rice milling machine, that is, controls the single milling depth by controlling the frequency of the abrasive roll. Experiments prove that the present invention can accurately extract the aleurone layer of the grain. The control process of the present invention is simple and reliable.

[0018] The method of the present invention further includes:

[0019] Correspondingly superposing the frequency quantity of the frequency converter that needs to be adjusted in the i-th rice milling process and / or the j-th rice milling process onto the frequency converter of the i-th rice milling machine and / or the j-th rice milling machine.

[0020] In order to further, the method of the present invention further includes:

[0021] In the first rice milling process, the change amount ΔN1 of the opening degree of the opening and closing plate that needs to be adjusted for each rice milling machine is expressed as: ΔN1 = na1×ΔA + nb1×ΔB - nc1×ΔC1 - ny1×ΔYn1;

[0022] In the second rice milling process, the change amount ΔN2 of the opening degree of the opening and closing plate that needs to be adjusted for each rice milling machine is expressed as: ΔN2 = n(a + b)2×Δ(A + B) + nc2×ΔC2 + nd2×ΔD2 - ny2×ΔYn2;

[0023] In the third rice milling process, the change amount ΔN3 of the opening degree of the opening and closing plate that needs to be adjusted for each rice milling machine is expressed as: ΔN3 = n(a + b + c)3×Δ(A + B + C) + nd3×ΔD3 + ne3×ΔE + nf3×ΔF - ng3×ΔG3 - nh3×ΔH3;

[0024] In the fourth rice milling process, the change amount ΔN4 of the opening degree of the opening and closing plate that needs to be adjusted for each rice milling machine is expressed as: ΔN4 = ny4×ΔYn4 + ng4×ΔG4 + nh4×ΔH4 - ni4×ΔI4;

[0025] na1 is the variation of Class A during the first rice milling process with the change of the discharge opening degree, nb1 is the variation of Class B during the first rice milling process with the change of the discharge opening degree, nci is the variation of Class C during the i-th rice milling process with the change of the discharge opening degree, ny1 is the variation of the total quantity of Classes D, E, F, G, H, I during the first rice milling process with the change of the discharge opening degree, ny2 is the variation of the total quantity of Classes E, F, G, H, I during the second rice milling process with the change of the discharge opening degree, ny4 is the variation of the total quantity of Classes A, B, C, D, E, F during the fourth rice milling process with the change of the discharge opening degree, n(a + b)2 is the variation of the sum of the quantities of Class A and Class B during the second rice milling process with the change of the discharge opening degree, n(a + b + c)3 is the variation of the sum of the quantities of Classes A, B, C during the third rice milling process with the change of the discharge opening degree, ΔA = the detected value of Class A in the first rice milling process - A0, where A0 is the maximum allowable value of Class A in the first rice milling, ΔB = 100% - the detected value of Class B in the first rice milling process, ΔCi = the detected value of Class C in the i-th rice milling process - C0i, where C0i is the maximum allowable value of Class C in the i-th rice milling process, ΔYn1 = the sum of the detected values of Classes D, E, F, G, H, I in the first rice milling process - Yn10, Δ(A + B) = the sum of the detected values of Class A and Class B in the second rice milling process - the maximum allowable value of Class A and Class B in the second rice milling process, Δ(A + B + C) is the sum of the detected values of Classes A, B, C in the third rice milling process, nd2 and nd3 are respectively the variations of Class D during the second rice milling process and the third rice milling process with the change of the discharge opening degree, ne3, nf3, ng3, nh3 are respectively the variations of Classes E, F, G, H during the third rice milling process with the change of the discharge opening degree, ng4, nh4, ni4 are respectively the variations of Classes G, H, I during the fourth rice milling process with the change of the discharge opening degree, ΔD2 = 100% - the detected value of Class D in the second rice milling process, ΔD3 = the detected value of Class D in the third rice milling process - 5%, ΔYn2 = the sum of the quantities of Classes F, G, H, I in the second rice milling process - (the maximum allowable value of the sum of the quantities of Classes F, G, H, I), ΔE = the detected value of Class E in the third rice milling process - 15%, ΔF = 100% - the detected value of Class F in the third rice milling process, ΔGj = the detected value of Class G in the j-th rice milling process - 10%, ΔH3 is the detected value of Class H in the third rice milling process, ΔH4 = 100% - the detected value of Class H in the fourth rice milling process, ΔYn4 is the sum of the detected values of Classes A, B, C, D, E, F in the fourth rice milling process.

[0026] The present invention further controls the discharge opening degree of the rice milling machine, thereby more precisely controlling the number of milling times, and further improving the accuracy and reliability of aleurone layer extraction.

[0027] In the expressions of ΔN1 to ΔN4, the process of determining the change amount of various data with the change of the discharge opening degree in the s-th rice milling process includes:

[0028] For the s-th rice milling process, adjust the frequency of the sand roller speed variable frequency controller of all rice milling machines in the rice milling process to R Hz, adjust the discharge opening degree to Q%, and keep it for more than T minutes;

[0029] Obtain the first type of detection value L and the second type of detection value Yn for N rounds of each rice milling machine in the rice milling process; s = i, j;

[0030] Calculate the average value of the first type of detection values of the first rice milling machine in N rounds of the rice milling process to obtain L s1-1 ; Calculate the average value of the second type of detection values of the first rice milling machine in N rounds of the rice milling process to obtain Yn s-1 ;

[0031] Combine the first type of detection values of all rounds of the second, third, and fourth rice milling machines in the rice milling process to obtain Ls234; Combine the second type of detection values of all rounds of the second, third, and fourth rice milling machines in the rice milling process to obtain Yns234;

[0032] Adjust the discharge opening degree of the first rice milling machine in the rice milling process to (Q + 0.1)%, keep it for T minutes, calculate the average value of the first type of detection values of the first rice milling machine in N rounds of the rice milling process to obtain L s1-1a ; Calculate the average value of the second type of detection values of the second, third, and fourth rice milling machines in N rounds of the rice milling process to obtain Yn s1-1a ; Combine the first type of detection values of all rounds of the second, third, and fourth rice milling machines in the rice milling process to obtain Ls234a; Combine the second type of detection values of all rounds of the second, third, and fourth rice milling machines in the rice milling process to obtain Yns234a;

[0033] Then: the change amount nt of the t-type data with the change of the discharge opening degree of the k-th rice milling machine in the s-th rice milling process s-k Is expressed as: nt s-k = dM / [(L s1-1a - L s1-1 ) - (Ls234a - Ls234)]; t = a, b, c, d, (a + b), (a + b + c), e, f, g, h, i; dM is a constant;

[0034] The change amount ny of the remaining types of data other than the t-type data with the change of the discharge opening degree of the k-th rice milling machine in the s-th rice milling process s-k Is expressed as: ny s-k = dM / [(Yn s1-1a - Yns-1 )-(Yns234a-Yns234)];

[0035] Adjust the frequency of the sand roller speed variable frequency controller to N different frequency values, and calculate nt at the corresponding frequency value. s-k andny s-k , calculate nt at all frequency values ​​of the kth rice mill in the sth rice milling process s-k The average value of nt corresponding to all rice mills in the sth rice milling process s-k The mean of the average values ​​is taken as nts; calculate the ny of all frequency values ​​of the kth rice mill in the sth rice milling process s-k The average value of ny corresponding to all rice mills in the sth rice milling process s-k The mean of the average values ​​is taken as nys; k=1~M;

[0036] in,

[0037] For the first rice milling process, the second-category test value refers to the sum of the test values ​​of categories D, E, F, G, H, and I, and the first-category test value refers to the test values ​​of all types of data other than the first and second-category test values;

[0038] For the second rice milling process, the second type of test value refers to the sum of the test values ​​of E, F, G, H, and I, and the first type of test value refers to the test values ​​of various types of data other than the first and second type of test values;

[0039] For the fourth rice milling process, the second category test value refers to the sum of the test values ​​of categories A, B, C, D, E, and F, and the first category test value refers to the test values ​​of various types of data other than the first and second category test values.

[0040] The determination process of mzi and myj includes:

[0041] The frequency change mzi-k corresponding to the kth rice mill in the i-th rice milling process is expressed as: mzi-k=dM / [(Z 1-ka -Z 1-k )-(Z 234a -Z 234 )]; k = 1 ~ M;

[0042] The change in the aleurone process data corresponding to the kth rice mill in the jth rice milling process as the sand roller speed control frequency changes is expressed as: myj-k=dM / [(Y m1-ka -Y m1-k )-(Y m234a -Y m234 )]; s = i, j;

[0043] dM is a constant;

[0044] Z1-ka , Z 1-k , Z 234a , Z 234 , Y m1-ka , Y m1-k , Y m234a , Y m234 The determination process of

[0045] Adjust the inlet flow opening degree of all rice milling machines to P%; adjust the outlet opening degree position of all rice milling machines in the i-th rice milling process to Q%, adjust the frequency of the sand roller speed variable frequency controller to R Hz, and maintain for T minutes;

[0046] Obtain the online process detection data of N rounds of each rice milling machine in the i-th rice milling process, and respectively count the Z-type data and aleurone layer process data corresponding to each rice milling machine in the i-th rice milling process in each round;

[0047] Calculate the average value of all-round Z-type data corresponding to the k-th rice milling machine in the i-th rice milling process to obtain Z 1-k ; calculate the average value of all-round aleurone layer process data corresponding to the k-th rice milling machine in the i-th rice milling process to obtain Y m1-k ; calculate the average value of all Z-type data obtained by the 2nd, 3rd, and 4th rice milling machines in the i-th rice milling process within T minutes to obtain Z 234 ; calculate the average value of all aleurone layer process data obtained by the 2nd, 3rd, and 4th rice milling machines in the i-th rice milling process within T minutes to obtain Y m234 ;

[0048] Adjust the frequency of the speed variable frequency controller of the k-th rice milling machine in the i-th rice milling process to (R + 0.1) Hz, maintain for T minutes, obtain the Z-type data and aleurone layer process data of N rounds of the k-th rice milling machine in the i-th rice milling process, and calculate the average value of the Z-type data of the 1st rice milling machine in the i-th rice milling process at the frequency of (R + 0.1) Hz to obtain Z 1-ka ; calculate the average value of the aleurone layer process data of the 1st rice milling machine in the i-th rice milling process at the frequency of (R + 0.1) Hz to obtain Y m1-ka ; calculate the average value of the Z-type data of the 2nd, 3rd, and 4th rice milling machines in the i-th rice milling process at the frequency of (R + 0.1) Hz to obtain Z 234a ; calculate the average value of the aleurone layer process data of the 2nd, 3rd, and 4th rice milling machines in the i-th rice milling process at the frequency of (R + 0.1) Hz to obtain Y m234a ;

[0049] Adjust the frequency of the variable frequency controller to N different frequency values respectively, calculate mzi-k and mys-k corresponding to the frequency values, calculate the average value of mzi-k at all frequency values of the k-th rice milling machine in the i-th rice milling process, and take the average value of the average values of mzi-k corresponding to all rice milling machines in the i-th rice milling process as mzi; calculate the average value of mys-k at all frequency values of the k-th rice milling machine in the i-th rice milling process, and take the average value of the average values of mys-k corresponding to all rice milling machines in the i-th rice milling process as mys;

[0050] Among them,

[0051] For the first rice milling process, the aleurone layer process data refers to the sum of the detection values of categories E, F, G, H, and I;

[0052] For the second rice milling process, the aleurone layer process data refers to the sum of the detection values of categories F, G, H, and I;

[0053] For the third rice milling process, the aleurone layer process data refers to the sum of the detection values of categories A, B, and C;

[0054] For the fourth rice milling process, the aleurone layer process data refers to the sum of the detection values of categories A, B, C, and D.

[0055] The N different frequency values are: 41Hz, 45Hz, 39.9Hz, 39Hz, 35Hz.

[0056] P = 80, Q = 60, R = 40, T = 20, N = 5, dM = 0.1.

[0057] M = 4.

[0058] As an inventive concept, the present invention also provides a rice milling machine control system, including a memory, a processor, and a computer program stored on the memory; the processor executes the computer program to implement the steps of the above method.

[0059] As an inventive concept, the present invention also provides a computer-readable storage medium, on which a computer program / instructions are stored; when the computer program / instructions are executed by a processor, the steps of the above method are implemented.

[0060] Compared with the prior art, the beneficial effects of the present invention are: the present invention establishes the relationship between the control frequency of the sand roller of the new rice milling machine and the single milling depth, and the relationship between the opening degree of the new rice milling machine and the number of milling times of the same object, and can accurately extract the aleurone layer of grains. Brief Description of the Drawings

[0061] Figure 1 The aleurone layer obtained in the embodiment of the present invention;

[0062] Figure 2 The rice germ obtained in the embodiment of the present invention;

[0063] Figure 3 The first-grade precious product obtained in the embodiment of the present invention;

[0064] Figure 4 The second-grade precious product obtained in the embodiment of the present invention. Detailed implementation manners

[0065] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0066] In the embodiment of the present invention, the relationship between the control frequency of the sand roller and the single milling depth of the new rice machine is established, the relationship between the opening degree of the new rice machine and the number of milling times of the same object is established, the comprehensive relationship between the grain milling and cutting process and the sand roller frequency conversion and the flow opening degree is searched, and an intelligent controller for extracting the grain aleurone layer by the new rice machine is constructed.

[0067] The traditional production line of the original new rice machine is upgraded to a "rice precious product production line" (Patent No.: ZL202111359213.X), and the "rice precious product" is the "grain aleurone layer" (including part of the rice germ) in the embodiment of the present invention.

[0068] (1) Considering the factor of the small output of the new rice machine, each rice machine is expanded from 1 to 4;

[0069] (2) Considering the processing uniformity characteristics of the new rice machine, the previous and subsequent 6 processes are reduced to 4 processes;

[0070] (3) The first and second rice milling processes are constructed as a "pretreatment process", and its process objective is to remove the outer cortex of the grain, and the third and fourth rice milling processes are constructed as an "aleurone layer extraction process" (including the rice germ);

[0071] (4) Considering that the aleurone layer extracted at the end of the extraction process objectively contains a small amount of endosperm starch, the product from the third process is defined as the "first-grade precious product", and the product from the fourth process is defined as the "second-grade precious product".

[0072] Configure an on - line process detection system for the new production line according to "A Method for On - line Process Detection in Rice Processing" (Patent No.: ZL201911406271.6). Considering the uniformity and controllability of the new rice mill, configure one on - line process detection robot for every two rice mills, and these two rice mills are in the same rice milling process. The on - line detection time for each single - machine round is defined as 2 minutes, that is, one round (for 2 rice mills) of on - line process detection is completed every 4 minutes.

[0073] Train the on - line process detection robot according to the method described in "A Method and System for Processing Instant Rice Bran" (Patent No.: ZL202411296311.7), and define the process detection classifications respectively:

[0074] Class Z, the outer cortex is not removed;

[0075] Class A, the outer cortex is milled by 20%;

[0076] Class B, the outer cortex is milled by 50%;

[0077] Class C, the outer cortex is milled by 80%;

[0078] Class D, the outer cortex is milled by 100%;

[0079] Class E, the aleurone layer is milled by 20%;

[0080] Class F, the aleurone layer is milled by 50%;

[0081] Class G, the aleurone layer is milled by 80%;

[0082] Class H, the aleurone layer is milled by 100%;

[0083] Class I, milled to the endosperm.

[0084] Among the above categories, Class Z and Class I are separate categories in terms of milling depth. The former has not removed the outer cortex, and the latter has reached the endosperm in terms of milling depth; Classes A, B, C, and D have the same milling depth, with part or all of the outer cortex removed, and there are differences in the milling area, but the aleurone layer is intact; Classes E, F, G, and H have the same milling depth, with part or all of the aleurone layer removed, and there are only differences in the milling area, but the endosperm is not milled.

[0085] Define the process objectives and maximum allowable process deviations for each rice - milling process respectively:

[0086] Step 1, that is, Step 1 of the pretreatment process. The core objective of the process is to cluster in Class B. The maximum allowable value for Class A is 10%, the maximum allowable value for Class C is 20%, and the value for (Z + D+E + F+G + H+I) classes is 0;

[0087] The second process, which is the last process of the pretreatment process, the core goal of the process is to cluster into Category D, the allowable value of (Z + A + B) is 0, the maximum allowable value of Category C is 10%, the maximum allowable value of Category E is 10%, and the allowable value of (F + G + H + I) is 0;

[0088] The third process, which is the first process of the aleurone layer extraction process, the core goal of the process is to cluster into Category F, the allowable value of (Z + A + B + C) is 0, the maximum allowable value of Category D is 5%, the maximum allowable value of Category E is 15%, the maximum allowable value of Category G is 10%, and the allowable value of (H + I) is 0;

[0089] The fourth process, which is the second process of the aleurone layer extraction process and also the last process of the production line, the core goal of the process is to cluster into Category H, the allowable value of (Z + A + B + C + D + E + F) is 0, the maximum allowable value of Category G is 10%, the maximum allowable value of Category I is 0, to ensure the purity of the aleurone layer in the second process of the precious rice.

[0090] According to the definition of the target process, a control model is constructed for each rice milling process.

[0091] It is found in the actual production line that there is a linear relationship between the rotation speed of the new rice machine sand roller and the single milling depth - the greater the rotation speed, the deeper the milling, and the smaller the rotation speed, the shallower the milling. Since there is also a good linear relationship between the rotation speed and the frequency of the control motor, therefore, a corresponding linear relationship can be established between the frequency controlling the sand roller rotation speed and the milling depth.

[0092] Insufficient milling depth indicates that the frequency controlling the sand roller rotation speed needs to be increased; excessive milling depth indicates that the control frequency needs to be decreased, and the percentage occupancy of each category after detection can directly reflect whether the control frequency is reasonable.

[0093] At the same time, the research also finds that under the condition of a fixed feed opening degree, the discharge opening degree determines the number of times the processed material is milled in the milling chamber.

[0094] In summary, that is, the milling depth is controlled by adjusting the frequency of the rotation speed, and the milling area is determined by the size of the opening degree. The embodiment of the present invention constructs an intelligent control model based on this.

[0095] Practice has proved that this control model has excellent process effects.

[0096] Example 1

[0097] This embodiment provides a method for extracting the aleurone layer of grains.

[0098] (1) The online intelligent control model for the first rice milling is:

[0099] ΔM1 = mz1×ΔZ - my1×ΔYm1;

[0100] ΔN1 = na1×ΔA + nb1×ΔB - nc1×ΔC - ny1×ΔYn1;

[0101] Wherein, mz1, my1, na1, nb1, nc1, ny1 are parameters;

[0102] ΔZ = Z - Z0, where Z is the currently detected percentage of Z type, Z0 is the maximum allowable value of the maximum Z type for one - pass rice milling, which is 0. Therefore, ΔZ = the currently detected value of Z;

[0103] ΔYm1 = the current (E + F + G + H + I) type - Ym10, Ym10 is the maximum allowable value of the (E + F + G + H + I) type for one - pass rice milling, which is 0. Therefore, ΔYm1 = the detected value of the current (E + F + G + H + I) type; E + F + G + H + I represents the sum of the detected values of types E, F, G, H, and I, and so on;

[0104] ΔA = the currently detected value of type A - A0, A0 is the maximum allowable value of type A for one - pass rice milling, which is 10%;

[0105] ΔB = 100% - (the currently detected value of type B);

[0106] ΔC = the detected value of the current type C - C0, C0 is the maximum allowable value of type C for one - pass rice milling, which is 20%;

[0107] ΔYn1 = the detected value of the current (D + E + F + G + H + I) type - Yn10, Yn10 is 0;

[0108] ΔM1 is the amount of frequency conversion adjustment required according to the current process state;

[0109] ΔN1 is the amount of change in the opening - closing degree required by the system according to the current process state;

[0110] When ΔN1 is greater than 0, it is defined that the opening - closing plate moves in the "closing" direction; when ∆N1 is less than 0, it is defined that the opening - closing plate moves in the "opening" direction.

[0111] (2) Online intelligent control model for two - pass rice milling

[0112] ΔM2 = mz2×ΔZ - my2×ΔYm2;

[0113] ΔN2 = n(a + b)2×Δ(A + B)+nc2×ΔC + nd2×ΔD - ny2×ΔYn2;

[0114] Wherein, mz2, my2, n(a + b)2, nc2, nd2, ny2 are parameters;

[0115] ΔZ = Z - Z0, where Z is the currently detected percentage of Z type, Z0 is 0, that is, ΔZ = Z;

[0116] ΔYm2 = Current value of (F + G + H + I) category - Ym20, where Ym20 is the maximum allowable value of the two - pass rice milling (F + G + H + I) category, which is 0. Therefore, ΔYm2 = Current value of (F + G + H + I) category;

[0117] Δ(A + B) = Current value of (A + B) category - the maximum allowable value of the two - pass rice milling (A + B) category, which is 0. Therefore, Δ(A + B) = Current value of (A + B) category;

[0118] ΔC = Detected value of the current C category - 10%;

[0119] ΔD = 100% - Detected value of the current D category;

[0120] ΔYn2 = Current value of (F + G + H + I) category - the maximum allowable value of the (F + G + H + I) category, that is, ΔYn2 = Detected value of the current (F + G + H + I) category;

[0121] ΔM2 is the frequency adjustment amount of the two - pass sand roller frequency converter of this machine obtained through model calculation;

[0122] ΔN2 is the adjustment amount of the two - pass discharge opening and closing degree of this machine obtained through the algorithm. Its direction is defined as follows: when it is greater than 0, the opening and closing plate moves in the "closing" direction; when it is less than 0, the opening and closing plate moves in the "opening" direction.

[0123] (3) Online intelligent control model for three - pass rice milling

[0124] ΔM3 = my3×ΔYm3 - mk3×ΔI;

[0125] ΔN3 = n(a + b + c)3×Δ(A + B + C)+nd3×ΔD+ne3×ΔE+nf3×ΔF - ng3×ΔG - nh3×ΔH;

[0126] Among them, my3, mk3, n(a + b + c)3, nd3, ne3, nf3, ng3, nh3 are parameters;

[0127] ΔYm3 = Detected value of the current (A + B + C) category;

[0128] ΔI = Detected value of the current I category;

[0129] Δ(A + B + C) = Detected value of the current (A + B + C) category;

[0130] ΔD = Detected value of the current D category - 5%;

[0131] ΔE = Detected value of the current E category - 15%;

[0132] ΔF = 100% - Detected value of the current F category;

[0133] ΔG = Current G - type detection value - 10%;

[0134] ΔH = Current H - type detection value;

[0135] ΔM3 and ΔN3 are the frequency conversion adjustment amount and the opening - closing degree adjustment amount obtained through the algorithm and the current process detection values respectively. When ΔN3 > 0, the opening - closing plate moves towards the "closed" direction; when ΔN3 < 0, the opening - closing plate moves towards the "open" direction.

[0136] (4)Online intelligent control model for four - pass rice milling

[0137] ΔM4 = my4×ΔYm4 - mk4×ΔI;

[0138] ΔN4 = ny4×ΔYn4 + ng4×ΔG + nh4×ΔH - ni4×ΔI;

[0139] Where, my4, mk4, ny4, ng4, nh4, ni4 are parameters;

[0140] ΔYm4 = Current (A + B + C + D) - type detection value;

[0141] ΔI = Current I - type detection value;

[0142] ΔYn4 = Current (A + B + C + D + E + F) - type detection value;

[0143] ΔG = Current G - type detection value - 10%;

[0144] ΔH = 100% - Current H - type detection value;

[0145] ΔI = Current I - type detection value;

[0146] ΔM4 and ΔN4 are the frequency adjustment amount and the discharge opening - closing degree adjustment amount calculated according to the model, parameters and current various process detection values respectively. When ΔN4 > 0, the opening - closing plate moves towards the "closed" direction; when ΔN4 < 0, the opening - closing plate moves towards the "open" direction.

[0147] Determine the parameters of each intelligent control model for rice milling

[0148] Parameters of the intelligent control model for one - pass rice milling

[0149] The essence of each parameter is as follows: mz1 is the change amount generated by class Z with the change of the control frequency of the sand roller speed in the first rice milling process. Similarly, my1 is the change amount generated by class (E+F+G+H+I) with the change of the control frequency of the sand roller speed in the first rice milling process; na1 is the change amount generated by class A with the change of the discharge opening degree in the first rice milling process. Similarly, nb1 and nc1 are the change amounts generated by class B and class C with the change of the discharge opening degree respectively, and ny1 is the change amount generated by class (D+E+F+G+H+I) with the change of the opening degree.

[0150] 1. Determine mz1 and my1

[0151] (1) Number the four rice milling machines for the first rice milling process as 1-1, 1-2, 1-3, and 1-4, and respectively match detection robots and intelligent material pickers.

[0152] (2) Adjust the position of the inlet flow opening degree of all equipment to 80% and fix it (Practice has proved that this inlet flow is the optimal processing flow of the equipment, and the inlet flow of all equipment in the whole production line is fixed at this position).

[0153] (3) Adjust the position of the discharge opening degree of 1-1, 1-2, 1-3, and 1-4 to 60% and fix it. At the same time, adjust the frequency of the sand roller speed frequency converter to 40Hz and keep it for 20 minutes to obtain the online process detection data of five rounds for each rice milling machine. Respectively count the Z-class data and the (E+F+G+H+I)-class data (abbreviated as Ym) of 1-1, 1-2, 1-3, and 1-4.

[0154] Take the average value of the Z-class and Ym-class data of the five rounds of 1-1 obtained, and record them as Z 1-1 and Y m1-1 .

[0155] (4) Take the average of all Z-class values obtained by 1-2, 1-3, and 1-4 within these 20 minutes, and record it as Z234; take the average of all Ym-class values of 1-2, 1-3, and 1-4, and record it as Ym234.

[0156] (5) Adjust the frequency of the speed frequency converter of 1-1 to 40.1Hz and keep it for 20 minutes to obtain the process detection data of five rounds of 1-1. Respectively take the average of its Z-class value and Ym-class value, and record them as Z 1-1a and Y m1-1a .

[0157] Take the average of the Z-class values of 1-2, 1-3, and 1-4 at this stage, and record it as Z234a.

[0158] Take the average of the Ym-class values of 1-2, 1-3, and 1-4 at this stage, and record it as Ym234a.

[0159] (6) Calculate the mz value of 1-1:

[0160] mz1-1 = dM / dZ;

[0161] Here, the change value of the frequency is 0.1, so, dM = 0.1;

[0162] The change value of the Z class is (Z 1-1a - Z 1-1 )), but the change of the incoming material objectively needs to be considered, and the change of the incoming material itself brings about the change of the process. Therefore, the offset caused by the change of the incoming material needs to be considered, and this offset is directly reflected in the process changes of 1-2, 1-3, and 1-4, and this offset is equal to (Z234a - Z234). So, dZ = [(Z 1-1a - Z 1-1 ) - (Z234a - Z234)];

[0163] In summary, then mz1-1 = 0.1 / [(Z 1-1a - Z 1-1 ) - (Z234a - Z234)]

[0164] (7) Calculate the my value of 1-1:

[0165] my1-1 = dM / dYm;

[0166] Here, dM = 0.1;

[0167] The change value of Ym is (Y m1-1a - Y m1-1 ), and the offset caused by the change of the incoming material also needs to be considered. Its offset is (Ym234a - Ym234). So, dYm = [(Y m1-1a - Ym 1-1 ) - (Ym234a - Ym234)];

[0168] my1-1 = 0.1 / [(Y m1-1a - Y m1-1 ) - (Ym234a - Ym234)];

[0169] (8) Adjust the frequency of the frequency conversion controller to 41 Hz, and then calculate mz1-1 and my1-1;

[0170] Adjust the frequency of the frequency conversion controller to 45 Hz, and calculate mz1-1 and my1-1;

[0171] Adjust the frequency of the frequency conversion controller to 39.9 Hz, and calculate mz1-1 and my1-1;

[0172] Adjust the frequency of the frequency conversion controller to 39 Hz, and calculate mz1-1 and my1-1;

[0173] Adjust the frequency of the variable-frequency controller to 35 Hz, and calculate mz1-1 and my1-1;

[0174] Take the average values of all the obtained mz1-1 and my1-1, and complete the parameter iteration of mz1-1 and my1-1.

[0175] In the same way, obtain the values of mz1-2 and my1-2, mz1-3 and my1-3, mz1-4 and my1-4.

[0176] (9) Average the iterated mz1-1, mz1-2, mz1-3, and mz1-4 to obtain the value of mz1;

[0177] Average the iterated my1-1, my1-2, my1-3, and my1-4 to obtain the value of my1.

[0178] 2. Determine the values of na1, nb1, nc1, and ny1

[0179] (1) Adjust the frequency of the sand roller speed variable-frequency controller of the 1-1, 1-2, 1-3, and 1-4 rice machines to 40 Hz, and adjust the discharge opening degree to 60%.

[0180] (2) Maintain the above state for 20 minutes, and respectively obtain the Class A values, Class B values, Class C values, and (D+E+F+G+H+I) class values (the total is the Yn value) of five rounds of the 1-1, 1-2, 1-3, and 1-4 rice machines.

[0181] Take the average of the Class A values of five rounds of the 1-1 and denote it as A 1-1 ;

[0182] Take the average of the Class B values of five rounds of the 1-1 and denote it as B 1-1 ;

[0183] Take the average of the Class C values of five rounds of the 1-1 and denote it as C 1-1 ;

[0184] Take the average of the Yn values of five rounds of the 1-1 and denote it as Yn 1-1 .

[0185] Merge the data of five rounds of the 1-2, 1-3, and 1-4 to respectively obtain A234, B234, C234, and Yn234.

[0186] (3) Adjust the opening degree of the 1-1 to 60.1% and maintain it for 20 minutes. In the same way, obtain A 1-1a , B 1-1a , C 1-1a , Y n1-1a; A234a, B234a, C234a, and Yn234a within this time period are also obtained.

[0187] (4) Calculate the values of na, nb, nc, and ny for 1-1 respectively.

[0188] (a) na1-1 = dN / dA, where dN is 0.1%;

[0189] The value of dA is (A 1-1a - A 1-1 ). The offset caused by the change in the incoming material needs to be considered and corrected with the change values of 1-2, 1-3, and 1-4. The offset is (A234a - A234). Therefore, dA = [(A 1-1a - A 1-1 ) - (A234a - A234)].

[0190] Thus, na1-1 = 0.1% / [(A 1-1a - A 1-1 ) - (A234a - A234)];

[0191] (b) nb1-1 = dN / dB, here, dN is 0.1%;

[0192] dB = [(B 1-1a - B 1-1 ) - (B234a - B234)];

[0193] nb1-1 = 0.1% / [(B 1-1a - B 1-1 ) - (B234a - B234)].

[0194] (c) Similarly:

[0195] nc1-1 = 0.1% / [(B 1-1a - B 1-1 ) - (B234a - B234)];

[0196] Ny1-1 = 0.1% / [(Y n1-1a - Y n1-1 ) - (Yn234a - Yn234)].

[0197] According to the same iterative and correction method to obtain mz1 and my1, the determined values of na1, nb1, nc1, and ny1 are obtained.

[0198] Obtain and determine all other parameters in the same way.

[0199] Parameters of the two-pass rice milling intelligent control model: mz2, my2, n(a + b)2, nc2, nd2, ny2;

[0200] The parameters of the intelligent control model for three-pass rice milling: my3, mk3, n(a+b+c)3, nd3, ne3, nf3, ng3, nh3;

[0201] The parameters of the intelligent control model for four-pass rice milling: my4, mk4, ny4, ng4, nh4, ni4.

[0202] Substitute the parameters into the intelligent control models for each pass of rice milling.

[0203] Different processing varieties have different outer cortexes, different aleurone layer thicknesses, and different processing attributes. With different processing varieties, the parameters in the model also vary accordingly.

[0204] Therefore, although the intelligent control model remains unchanged, for different processing varieties, it is necessary to determine their respective parameters separately according to the described method.

[0205] Application example:

[0206] There are 16 new rice milling machines on the original production line, used for processing traditional polished rice; upgrade the original production line to a rice germ production line for extracting the aleurone layer (and rice germ):

[0207] Each sub-process is designed with 4 rice milling machines;

[0208] The first and second passes are used as pre-treatment processes;

[0209] The third and fourth passes are used as extraction processes. The product from the third pass is the first-grade rice germ, and the product from the fourth pass is the second-grade rice germ;

[0210] A total of 8 online process detection robots are configured. An online process detection system for the production line is constructed through the detection robots, online intelligent material pickers, material pipes, and industrial Internet;

[0211] Construct a complete rice germ production line through the industrial Internet with rice milling machines, online process detection systems, pre-intelligent controllers, and private cloud (intelligent control) platforms.

[0212] Construct an intelligent control model based on real-time online process detection data according to the method of the embodiment of the present invention, and determine the respective parameters (processing variety: Datingchang No. 1) according to the method of the embodiment of the present invention as follows:

[0213]

[0214] Substitute the respective parameters into the intelligent control model, and perform aleurone layer extraction processing on Datingchang No. 1. The obtained aleurone layer and rice germ are as Figure 1 and Figure 2 shown. Visible to the naked eye, the purity of the aleurone layer and rice germ is very high. After staining with a staining agent and observing under a thousand-fold microscope, the first-grade rice germ and the second-grade rice germ are respectively as Figure 3 andFigure 4 As shown. At the microscopic level, the first-class precious product is mainly composed of the cell walls of the aleurone layer, while in the second-class precious product, the aleurone grains account for a larger proportion, and even in the microscopic state, it is a pure aleurone layer without visible impurities.

[0215] Example 2

[0216] Example 2 of the present invention provides a control system corresponding to Example 1 above, including a memory, a processor, and a computer program stored on the memory; the processor executes the computer program on the memory to implement the steps of the method in Example 1 above.

[0217] In some implementations, the memory can be a high-speed random access memory (RAM: Random Access Memory), and may also include non-volatile memory, such as at least one disk memory.

[0218] In other implementations, the processor can be various types of general-purpose processors such as a central processing unit (CPU), a digital signal processor (DSP), etc., which are not limited here.

[0219] Example 3

[0220] Example 3 of the present invention provides a computer-readable storage medium corresponding to Example 1 above, on which a computer program / instructions are stored. When the computer program / instructions are executed by a processor, the steps of the method in Example 1 above are implemented.

[0221] A computer-readable storage medium can be a tangible device that holds and stores instructions used by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination of the above.

[0222] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0223] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices produce a means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0224] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0225] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0226] Obviously, those skilled in the art can make various changes and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

Claims

1. A method for extracting cereal aleurone layer, which is realized by a rice milling machine system. The rice milling machine system includes multiple rice milling machines arranged in sequence. The multiple rice milling machines arranged in sequence are divided into four groups, and each group includes M rice milling machines; it is characterized in that, The method includes: In the i-th rice milling process, the variable frequency quantity ∆Mi to be adjusted is expressed as: ∆Mi = mzi×∆Z - myi×∆Ymi; i = 1, 2; ∆Z = Z - Z0, where Z is the percentage of the detected quantity of type Z in the i-th rice milling process, Z0 is the maximum allowable percentage of the detected quantity of type Z in the i-th rice milling process, mzi is the change amount of type Z with the change of the frequency controlled by the sand roller speed in the i-th rice milling process, my1 is the change amount of the total quantity of types E, F, G, H, I with the change of the frequency controlled by the sand roller speed in the first rice milling process, ∆Ym1 = the sum of the detected quantity percentages of types E, F, G, H, I in the first rice milling process - Ym10, Ym10 is the maximum allowable percentage of the total detected quantity of types E, F, G, H, I in the first rice milling process, my2 is the change amount of the total quantity of types F, G, H, I with the change of the frequency controlled by the sand roller speed in the second rice milling process, ∆Ym2 = the sum of the detected quantity percentages of types F, G, H, I in the second rice milling process - Ym20, Ym20 is the maximum allowable percentage of the total detected quantity of types F, G, H, I in the second rice milling process; In the j-th rice milling process, the variable frequency quantity ∆Mj to be adjusted is expressed as: ∆Mj = myj×∆Ymj - mkj×∆Ij; j = 3, 4; my3 is the change amount of the total quantity of types A, B, C with the change of the frequency controlled by the sand roller speed in the third rice milling process, my4 is the change amount of the total quantity of types A, B, C, D with the change of the frequency controlled by the sand roller speed in the fourth rice milling process, ∆Ym3 is the sum of the detected quantity percentages of types A, B, C in the third rice milling process, ∆Ym4 is the sum of the detected quantity percentages of types A, B, C, D in the fourth rice milling process, mk3 is the change amount of type I with the change of the frequency controlled by the sand roller speed in the third rice milling process, mk4 is the change amount of type I with the change of the frequency controlled by the sand roller speed in the fourth rice milling process, and ∆Ij is the detected quantity percentage of type I in the j-th rice milling process; Types Z, A, B, C, D, E, F, G, H, I are respectively defined as the unhusked outer cortex of the grain, 20% of the outer cortex ground off, 50% of the outer cortex ground off, 80% of the outer cortex ground off, 100% of the outer cortex ground off, 20% of the aleurone layer ground off, 50% of the aleurone layer ground off, 80% of the aleurone layer ground off, 100% of the aleurone layer ground off, and ground to the endosperm.

2. The method for extracting cereal aleurone layer according to claim 1, wherein It further includes: Correspondingly superimposing the variable frequency quantity of the inverter to be adjusted in the i-th rice milling process and / or the j-th rice milling process onto the inverter frequency of the i-th rice milling machine and / or the j-th rice milling machine.

3. The method for extracting cereal aleurone layer according to claim 1, characterized in that It further includes: In the first rice milling process, the change amount ∆N1 of the opening degree of the opening and closing plate to be adjusted for each rice milling machine is expressed as: ∆N1 = na1×∆A + nb1×∆B - nc1×∆C1 - ny1×∆Yn1; In the second rice milling process, the change amount ∆N2 of the opening degree of the opening and closing plates that need to be adjusted for each rice milling machine is expressed as: ∆N2 = n(a + b)2 × ∆(A + B) + nc2 × ∆C2 + nd2 × ∆D2 - ny2 × ∆Yn2; In the third rice milling process, the change amount ∆N3 of the opening degree of the opening and closing plates that need to be adjusted for each rice milling machine is expressed as: ∆N3 = n(a + b + c)3 × ∆(A + B + C) + nd3 × ∆D3 + ne3 × ∆E + nf3 × ∆F - ng3 × ∆G3 - nh3 × ∆H3; In the fourth rice milling process, the change amount ∆N4 of the opening degree of the opening and closing plates that need to be adjusted for each rice milling machine is expressed as: ∆N4 = ny4 × ∆Yn4 + ng4 × ∆G4 + nh4 × ∆H4 - ni4 × ∆I4; na1 is the change amount of Class A with the change of the discharge opening degree in the first rice milling process, nb1 is the change amount of Class B with the change of the discharge opening degree in the first rice milling process, nci is the change amount of Class C with the change of the discharge opening degree in the i-th rice milling process, ny1 is the change amount of the total quantity of Classes D, E, F, G, H, I with the change of the discharge opening degree in the first rice milling process, ny2 is the change amount of the total quantity of Classes E, F, G, H, I with the change of the discharge opening degree in the second rice milling process, ny4 is the change amount of the total quantity of Classes A, B, C, D, E, F with the change of the discharge opening degree in the fourth rice milling process, n(a + b)2 is the change amount of the sum of the quantities of Class A and Class B with the change of the discharge opening degree in the second rice milling process, n(a + b + c)3 is the change amount of the sum of the quantities of Classes A, B, C with the change of the discharge opening degree in the third rice milling process, ∆A = the percentage of the detected quantity of Class A in the first rice milling process - A0, where A0 is the maximum allowable percentage of Class A in the first rice milling process, ∆B = 100% - the percentage of the detected quantity of Class B in the first rice milling process, ∆Ci = the percentage of the detected quantity of Class C in the i-th rice milling process - C0i, where C0i is the maximum allowable percentage of the detected quantity of Class C in the i-th rice milling process, ∆Yn1 is the sum of the percentages of the detected quantities of Classes D, E, F, G, H, I in the first rice milling process - Yn10, where Yn10 is 0, ∆(A + B) = the sum of the percentages of the detected quantities of Class A and Class B in the second rice milling process - the maximum allowable percentage of the detected quantities of Class A and Class B in the second rice milling process, ∆(A + B + C) is the sum of the percentages of the detected quantities of Classes A, B, C in the third rice milling process, nd2 and nd3 are respectively the change amounts of the detected quantity of Class D with the change of the discharge opening degree in the second rice milling process and the third rice milling process, ne3, nf3, ng3, nh3 are respectively the change amounts of the detected quantities of Classes E, F, G, H with the change of the discharge opening degree in the third rice milling process, ng4, nh4, ni4 are respectively the change amounts of the detected quantities of Classes G, H, I with the change of the discharge opening degree in the fourth rice milling process, ∆D2 = 100% - the percentage of the detected quantity of Class D in the second rice milling process, ∆D3 = the percentage of the detected quantity of Class D in the third rice milling process - 5%, ∆Yn2 = the sum of the percentages of the detected quantities of Classes F, G, H, I in the second rice milling process - the maximum allowable percentage of the sum of the detected quantities of F, G, H, I, ∆E = the percentage of the detected quantity of Class E in the third rice milling process - 15%, ∆F = 100% - the percentage of the detected quantity of Class F in the third rice milling process, ∆Gj = the percentage of the detected quantity of Class G in the j-th rice milling process - 10%, ∆H3 is the percentage of the detected quantity of Class H in the third rice milling process, ∆H4 = 100% - the percentage of the detected quantity of Class H in the fourth rice milling process, ∆Yn4 is the sum of the percentages of the detected quantities of Classes A, B, C, D, E, F in the fourth rice milling process.

4. The method for extracting cereal aleurone layer according to claim 3, wherein In the expressions of ∆N1 to ∆N4, the process of determining the variation of various data with the change of the discharge opening degree in the s-th rice milling process includes: For the s-th rice milling process, adjust the frequency of the sand roll speed variable frequency controller of all rice mills in the rice milling process to R Hz, adjust the discharge opening degree to Q%, and maintain for more than T minutes; Obtain the first type of detection quantity percentage L and the second type of detection quantity percentage Yn of N rounds of each rice mill in the rice milling process; s = i, j; Calculate the average value of the percentage of the first type of detection quantity in N rounds of the first rice milling machine in the rice milling process to obtain L s1-1 ; Calculate the average value of the percentage of the second type of detection quantity in N rounds of the first rice milling machine in the rice milling process to obtain Yn s-1 ; Combine the first type of detection quantity percentages of all rounds of the 2nd, 3rd, and 4th rice mills in the rice milling process to obtain Ls234; combine the second type of detection quantity percentages of all rounds of the 2nd, 3rd, and 4th rice mills in the rice milling process to obtain Yns234; Adjust the discharge opening degree of the first rice milling machine in the rice milling process to (Q + 0.1)%, and maintain it for T minutes. Calculate the average value of the percentage of the first type of detection quantity in N rounds of the first rice milling machine in the rice milling process to obtain L s1-1 a; Calculate the average value of the percentage of the second type of detection quantity in N rounds of the second, third, and fourth rice milling machines in the rice milling process to obtain Yn s1-1a ; Combine the percentages of the first type of detection quantity in all rounds of the second, third, and fourth rice milling machines in the rice milling process to obtain Ls234a; Combine the percentages of the second type of detection quantity in all rounds of the second, third, and fourth rice milling machines in the rice milling process to obtain Yns234a; Then: the change amount nt of t - type data generated with the change of the discharge opening degree of the k - th rice milling machine in the s - th rice milling process s-k Is expressed as: nt s-k =dM / [(L s1-1a - L s1-1 )-(Ls234a - Ls234)]; t = a, b, c, d, (a + b), (a + b + c), e, f, g, h, i; a, b, c, d, (a + b), (a + b + c), e, f, g, h, i respectively correspond to the percentage of the detection quantity of type A, the percentage of the detection quantity of type B, the percentage of the detection quantity of type C, the percentage of the detection quantity of type D, the sum of the detection quantity percentages of type A and type B, the sum of the detection quantity percentages of type A, B, and C, the percentage of the detection quantity of type E, the percentage of the detection quantity of type F, the percentage of the detection quantity of type G, the percentage of the detection quantity of type H, and the percentage of the detection quantity of type I; dM is a constant; The variation amount ny of the remaining types of data other than the t-type data generated with the change of the discharge opening degree of the k-th rice milling machine in the s-th rice milling process s-k Expressed as: ny s-k =dM / [(Yn s1-1a -Yn s-1 )-(Yns234a - Yns234)]; Adjust the frequency of the sand roller speed variable frequency controller to N different frequency values respectively, and calculate nt corresponding to the frequency values s-k and ny s-k , calculate the average value of nt at all frequency values of the k-th rice milling machine in the s-th rice milling process, and take the average value of the average values of nt corresponding to all rice milling machines in the s-th rice milling process as nts; calculate the average value of ny at all frequency values of the k-th rice milling machine in the s-th rice milling process, and take the average value of the average values of ny corresponding to all rice milling machines in the s-th rice milling process as nys; k = 1 to M; s-k s-k s-k s-k ​​​​ Among them, For the first rice milling process, the second type of detection quantity refers to the sum of the detection quantity percentages of types D, E, F, G, H, and I, and the first type of detection quantity refers to the detection quantity percentage of various data other than the second type of detection quantity; For the second rice milling process, the second type of detection quantity refers to the sum of the detection quantity percentages of types E, F, G, H, and I, and the first type of detection quantity refers to the detection quantity percentage of various data other than the second type of detection quantity; For the fourth rice milling process, the second type of detection quantity refers to the sum of the detection quantity percentages of types A, B, C, D, E, and F, and the first type of detection quantity refers to the detection quantity percentage of various data other than the second type of detection quantity.

5. The method for extracting cereal aleurone layer according to claim 1, wherein The process of determining mzi and myj includes: The frequency change amount mzi-k corresponding to the k-th rice milling machine in the i-th rice milling process is expressed as: mzi-k = dM / [(Z 1-ka - Z 1-k ) - (Z 234a - Z 234 )]; k = 1 to M; The change amount myj-k of the aleurone layer process data corresponding to the k-th rice milling machine in the j-th rice milling process generated with the change of the control frequency of the sand roller speed is expressed as: myj-k = dM / [(Y m1-ka - Y m1-k ) - (Y m234a - Y m234 )]; dM is a constant; Z 1-ka 、Z 1-k 、Z 234a 、Z 234 、Y m1-ka 、Y m1-k 、Y m234a 、Y m234 The determination process of Adjust the inlet flow opening degree of all rice mills to P%; adjust the discharge opening degree position of all rice mills in the i-th rice milling process to Q%, adjust the frequency of the sand roll speed variable frequency controller to R Hz, and maintain for T minutes; Obtain the on-line process detection data of each rice mill in the i-th rice milling process for N rounds, and respectively count the Z-type data and aleurone layer process data corresponding to each rice mill in the i-th rice milling process in each round; Calculate the average value of all round Z - type data corresponding to the k - th rice milling machine in the i - th rice milling process to obtain Z 1-k ; Calculate the average value of all round aleurone layer process data corresponding to the k - th rice milling machine in the j - th rice milling process to obtain Y m1-k ; Calculate the average value of all Z - type data obtained by the 2nd, 3rd, and 4th rice milling machines within T minutes in the i - th rice milling process to obtain Z 234 ; Calculate the average value of all aleurone layer process data obtained by the 2nd, 3rd, and 4th rice milling machines within T minutes in the j - th rice milling process to obtain Y m234 ; Adjust the frequency of the variable frequency controller of the k-th rice milling machine in the i-th rice milling process to (R + 0.1) Hz, and maintain it for T minutes to obtain the Z-type data and aleurone layer process data of N rounds of the k-th rice milling machine in the i-th rice milling process. Calculate the average value of the Z-type data of the first rice milling machine in the i-th rice milling process at the frequency of (R + 0.1) Hz to obtain Z 1-ka ; Calculate the average value of the aleurone layer process data of the first rice milling machine in the j-th rice milling process at the frequency of (R + 0.1) Hz to obtain Y m1-ka ; Calculate the average value of the Z-type data of the 2nd, 3rd, and 4th rice milling machines in the i-th rice milling process at the frequency of (R + 0.1) Hz to obtain Z 234a ; Calculate the average value of the aleurone layer process data of the 2nd, 3rd, and 4th rice milling machines in the j-th rice milling process at the frequency of (R + 0.1) Hz to obtain Y m234a ; Adjust the frequency of the variable frequency controller to N different frequency values respectively, calculate mzi-k and myj-k corresponding to the frequency values, calculate the average value of mzi-k of the k-th rice mill in the i-th rice milling process at all frequency values, and take the average value of the average values of mzi-k corresponding to all rice mills in the i-th rice milling process as mzi; calculate the average value of myj-k of the k-th rice mill in the j-th rice milling process at all frequency values, and take the average value of the average values of myj-k corresponding to all rice mills in the j-th rice milling process as myj; Among them, For the first rice milling process, the aleurone layer process data refers to the sum of the detection quantity percentages of types E, F, G, H, and I; For the second rice milling process, the aleurone layer process data refers to the sum of the detection quantity percentages of types F, G, H, and I; For the third rice milling process, the aleurone layer process data refers to the sum of the percentages of the detection quantities of types A, B, and C; For the fourth rice milling process, the aleurone layer process data refers to the sum of the detection quantity percentages of types A, B, C, and D.

6. The method for extracting cereal aleurone layer according to claim 5, characterized in that, The N different frequency values are respectively: 41 Hz, 45 Hz, 39.9 Hz, 39 Hz, 35 Hz.

7. The method for extracting cereal aleurone layer according to claim 5 or 6, characterized in that, P = 80, Q = 60, R = 40, T = 20, N = 5, dM = 0.

1.

8. The method for extracting cereal aleurone layer according to any one of claims 1 to 6, characterized in that, M=4。 9. A rice milling machine control system includes a memory, a processor, and a computer program stored on the memory; characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program / instructions stored thereon; characterized in that, When the computer program / instructions are executed by the processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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