Dynamic batching adjustment method and system based on online near-infrared detection, and storage medium

Abstract

The invention discloses a dynamic ingredient adjusting method and system based on online near-infrared detection and a storage medium, and the method comprises the following steps: based on a feed formula and the standard content of nutritional ingredients of each feed raw material, obtaining the content of each nutritional ingredient of a prepared feed; the actual nutrient content of each raw material of the feed is detected in real time through a near-infrared sensor; optimizing and adjusting the actual proportion of each raw material in the feed formula according to the actual nutrient content of each raw material and the nutrient content of the prepared feed; according to the actual ratio of the raw materials, the corresponding amount of raw materials are obtained for feed preparation. Based on the near-infrared sensing technology, the actual content of each nutritional ingredient in the feed raw materials is obtained in real time, and the proportioning amount of each raw material in the feed formula is adjusted in time, so that the nutritional ingredient content of the prepared feed can be kept consistent with that of the feed formula; raw material waste is avoided, and meanwhile it is guaranteed that the animals can obtain sufficient nutrition needed by growth.

Description

Technical Field

[0001] The invention belongs to the technical field of feed preparation, and in particular relates to a dynamic ingredient adjustment method, system and storage medium based on online near-infrared detection. Background Art

[0002] With the development of precision feed nutrition technology, targeted feeds need to be developed according to the needs of different animals at different growth stages to ensure on-demand supply. In the feed formula design stage, formulators design feed formulas based on nutritional needs and the standard nutrient content of feed raw materials; in the feed production stage, feed factories produce feed according to feed formulas. However, due to fluctuations in the nutrient content of feed raw materials, there is a large deviation between the nutrient content of the finished feed and the design value. Feed factories configure feed according to nutritional formulas and the standard nutrient content of local feed raw materials, which inevitably leads to fluctuations in the nutrient content of the finished feed. Taking protein as an example, if the content is insufficient, it will affect the growth of animals. If the content is too high, it cannot be fully absorbed, resulting in a waste of protein.

[0003] Therefore, when preparing feed, it is necessary to monitor the nutrient content of feed raw materials so as to adjust the ingredient amount in time according to the nutritional cost requirements in the feed formula to meet the nutritional needs of animals at different stages. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a dynamic batching adjustment method and system based on online near-infrared detection, and a storage medium.

[0005] The technical solution provided by the present invention is as follows:

[0006] A dynamic batching adjustment method based on online near infrared detection comprises the following steps:

[0007] S1. Based on the feed formula and the standard content of the nutrients of the feed raw materials on which it is based, obtain the content of each nutrient component that the formulated feed should have;

[0008] S2, using near infrared sensors to detect the actual nutrient content of each feed raw material during feed preparation in real time;

[0009] S3. Optimize and adjust the actual proportion of each feed raw material in the feed formula according to the actual nutrient content of each feed raw material and the nutrient content of each feed that should be possessed by the formulated feed;

[0010] S4. According to the actual ratio of each feed raw material after optimization and adjustment, obtain the corresponding amount of feed raw materials for feed preparation.

[0011] Further, in step S1, it is assumed that the proportion of each feed raw material in the feed formula is xn represents the formula proportion of the nth raw material; the transfer matrix constructed based on the standard content of nutrients in each feed raw material is A m×n , where a mn represents the standard content of the mth nutrient component of the nth raw material; then the nutrient content of the feed prepared based on the feed formula should be Y m , where y m Indicates the content of the mth nutrient.

[0012] Preferably, the near infrared sensor obtains the actual nutrient content of each feed raw material by detecting the crushed feed raw material.

[0013] Further, in step S3, the actual content of the nutrients in each raw material detected by the near infrared sensor is assumed to be B m×n , where b mn represents the actual content of the mth nutrient component of the nth raw material; then the actual ratio Z of each feed raw material after optimization and adjustment n for:

[0014]

[0015] Among them, z n Indicates the actual ratio of the nth raw material, (Bm × n)- 1 is the matrix Bm × The generalized inverse matrix of n.

[0016] A dynamic batching adjustment system based on the above method comprises: a crusher for crushing feed raw materials, a silo for storing the crushed feed raw materials, a batching scale for obtaining a specified amount of feed raw materials from the silo, a batch bucket for storing the feed raw materials obtained by the batching scale, and a mixer for mixing the feed raw materials in each batch bucket; a near-infrared sensor for real-time detection of the actual content of the nutrient components of the feed raw materials; and a central control system connected to the near-infrared sensor, wherein the central control system is used to input and store feed formulas and standard content of nutrient components of each feed raw material, and is used to optimize and adjust the actual proportion of each feed raw material in the feed formula according to the actual nutrient content of each feed raw material fed back by the near-infrared sensor, and is also used to control the batching scale to obtain a corresponding amount of feed raw materials according to the actual proportion of each feed raw material.

[0017] Furthermore, the near infrared sensor is arranged after the pulverizer and before the batching scale to detect the nutritional components of the raw materials during the batching process, and then the batching amount is corrected based on the interpolation of the batching amount given in the formula and the actually required batching amount after optimization and adjustment.

[0018] Furthermore, the near infrared sensor is arranged after the pulverizer and before or after the batching scale, and is used to obtain the detection data of the current batch of ingredients to control the next batch of ingredients.

[0019] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the processor executes the optimization control steps of the central control system in the above-mentioned dynamic batching adjustment system.

[0020] Compared with the prior art, the present invention has at least the following beneficial effects:

[0021] The present invention is based on near-infrared sensing technology. By acquiring the actual content of each nutrient in the feed raw materials in real time and timely adjusting the ingredient amount of each raw material in the feed formula, the nutrient content of the prepared feed can be kept consistent with the feed formula, avoiding waste of raw materials while ensuring that animals can obtain sufficient nutrients required for growth. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0023] Figure 1 It is a schematic flow chart of a dynamic batching adjustment method provided by an embodiment of the present invention;

[0024] Figure 2 Schematic diagram A of a dynamic batching adjustment system according to an embodiment of the present invention;

[0025] Figure 3 Schematic diagram B of a dynamic batching adjustment system framework provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, other embodiments obtained by ordinary technicians in this field without making creative work are all within the scope of protection of the present invention.

[0027] Embodiment 1

[0028] This example provides a dynamic batching adjustment method based on online near infrared detection. Figure 1 As shown, it mainly includes:

[0029] (1) Install a near infrared sensor between the daily feed bin and the batch hopper to detect the nutrient content of the main feed ingredients in real time online and transmit the detection data to the batching system.

[0030] An online near-infrared sensor is a device that uses near-infrared (NIR) spectroscopy technology for real-time analysis and measurement. The feed particle size has an important impact on the detection precision and accuracy of the online near-infrared sensor, because uniform fine particles are conducive to reducing light scattering and absorption path inconsistencies, thereby improving the signal-to-noise ratio and the stability of the spectral signal. On the contrary, uneven particle size or larger particles will cause instability and errors in the spectral data, resulting in reduced accuracy and repeatability of the measurement results. Maintaining the consistency and uniformity of the feed sample's particle size is crucial to optimizing the near-infrared detection effect. Therefore, in this embodiment, the online near-infrared sensor is arranged between the daily silo and the batch hopper, such as Figure 2 and Figure 3 As shown, the raw materials have been crushed into smaller particles.

[0031] (2) The batching system optimizes the proportion of the main raw materials in the feed formula based on the standard nutrient content of the main raw materials and the actual nutrient content of the main raw materials detected in real time by the near-infrared sensor.

[0032] Assume that the proportion of n main raw materials in the feed formula is x n represents the formula proportion of the nth raw material; the transfer matrix constructed based on the standard content of m nutrients of n main raw materials in the feed formula is A m×n , where a mn represents the standard content of the mth nutrient component of the nth raw material; then the content of m nutrients in the feed after mixing n main raw materials based on the feed formula should be Y m , where y m Indicates the content of the mth nutrient.

[0033] Assume that the actual content of m nutrients in n main raw materials detected by the online near infrared sensor is B m×n , where b mn Indicates the actual content of the mth nutrient in the nth raw material. In order to obtain a feed with the same nutrient content as in the feed formula, it is only necessary to adjust the actual proportion of the n main raw materials according to the following formula: n Then:

[0034]

[0035] Among them, z n Indicates the actual proportion of the nth raw material, (Bm× n)- 1 is the matrix Bm × The generalized inverse matrix of n, theoretically B m×n There will be countless generalized inverse matrices, and you can just take the one with the lowest raw material cost.

[0036] (3) The batching system feeds back the optimized batching ratio parameters to the central control system, which uses the batching scale to dynamically control the batching, so that the nutritional components of the feed remain stable and consistent with the feed formula. n Substitute X in the recipe n The central control system controls the batching scale to batch the ingredients according to the adjusted raw material proportions.

[0037] Online near infrared sensors can be placed before or after the batching scale. If closed-loop control of the batching is required, the online near infrared sensor needs to be placed before the batching scale, that is, the nutritional components of the raw materials are detected during the batching process, and then the batching amount is corrected based on the interpolation of the standard batching amount and the actual required batching amount. Figure 3 shown.

[0038] If the new batching amount is optimized based on the online near-infrared detection data of the previous batching to control the current batching scale, the online near-infrared sensor can be placed before or after the batching scale. In the continuous production process of feed, the nutrient content of the main raw materials of the feed varies little between batches. Using the detection data of the previous batch of ingredients to control the current batch of ingredients can also meet the requirements of precise nutritional control, and has the following advantages: the online near-infrared sensor has a longer detection time (the average value of multiple detection data after eliminating abnormal data); the optimization algorithm can have more iterations (time).

[0039] Embodiment 2

[0040] Based on the above dynamic batching adjustment method, this embodiment provides a dynamic batching adjustment system based on online near infrared detection, such as Figure 2 and Figure 3 As shown, including:

[0041] Crusher, used to crush feed raw materials;

[0042] Silos, used to store crushed feed ingredients;

[0043] Batching scale, used to obtain a specified weight of feed ingredients from the silo;

[0044] Batch hopper, used to store feed raw materials obtained from batching scale;

[0045] The mixer is used to mix the feed ingredients in each batch bucket.

[0046] Also includes:

[0047] A near-infrared sensor is arranged behind the pulverizer for real-time detection of the actual content of nutrients in the feed raw materials; and a central control system connected to the near-infrared sensor, wherein the central control system is used to input and store the feed formula, the standard content of nutrients in each feed raw material, and to optimize and adjust the actual ratio of each feed raw material in the feed formula according to the actual content of nutrients in each feed raw material fed back by the near-infrared sensor, and is also used to control the batching scale to obtain the specified weight of feed raw materials according to the actual ratio of each feed raw material.

[0048] Embodiment 3

[0049] According to an embodiment of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the processor executes the optimization control steps of the central control system described in the second embodiment, namely, optimizing and adjusting the actual ratio of each feed raw material in the feed formula according to the actual content of the nutrient components of each feed raw material fed back by a near-infrared sensor, and controlling the batching scale to obtain a specified weight of feed raw materials according to the actual ratio of each feed raw material.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may also be combined, the steps may be implemented in any order, and there are many other changes in different aspects of the present invention as described above, which are not provided in detail for the sake of simplicity. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person of ordinary skill in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A dynamic batching adjustment method based on online near infrared detection, characterized in that: The following steps are involved: S1. Based on the feed formula and the standard content of the nutrients of the feed raw materials on which it is based, obtain the content of each nutrient component that the formulated feed should have; S2, using near infrared sensors to detect the actual nutrient content of each feed raw material during feed preparation in real time; S3. Optimize and adjust the actual proportion of each feed raw material in the feed formula according to the actual nutrient content of each feed raw material and the nutrient content of each feed that should be possessed by the formulated feed; S4. According to the actual ratio of each feed raw material after optimization and adjustment, obtain the corresponding amount of feed raw materials for feed preparation.

2. The dynamic batching adjustment method according to claim 1, characterized in that: In step S1, it is assumed that the proportion of each feed raw material in the feed formula is x n represents the formula proportion of the nth raw material; the transfer matrix constructed based on the standard content of nutrients in each feed raw material is A m×n , where a mn represents the standard content of the mth nutrient component of the nth raw material; then the nutrient content of the feed prepared based on the feed formula should be Y m , where y m Indicates the content of the mth nutrient.

3. The dynamic batching adjustment method according to claim 1, characterized in that: In step S2, the near infrared sensor obtains the actual nutrient content of each feed raw material by detecting the crushed feed raw material.

4. The dynamic batching adjustment method according to claim 2, characterized in that: In step S3, it is assumed that the actual content of the nutrients in each raw material detected by the near infrared sensor is B m×n , where b mn represents the actual content of the mth nutrient component of the nth raw material; then the actual ratio Z of each feed raw material after optimization and adjustment n for: Among them, z n Indicates the actual ratio of the nth raw material, (Bm × n)- 1 is the matrix Bm × The generalized inverse matrix of n.

5. A dynamic batching adjustment system based on the method according to any one of claims 1 to 4, characterized in that: include: A grinder for crushing feed raw materials, a silo for storing the crushed feed raw materials, a batching scale for obtaining a specified amount of feed raw materials from the silo, a batch bucket for storing the feed raw materials obtained by the batching scale, and a mixer for mixing the feed raw materials in each batch bucket; also includes a near-infrared sensor for real-time detection of the actual content of nutrients in the feed raw materials; and a central control system connected to the near-infrared sensor, the central control system is used to input and store feed formulas, standard content of nutrients in each feed raw material, and is used to optimize and adjust the actual ratio of each feed raw material in the feed formula according to the actual nutrient content of each feed raw material fed back by the near-infrared sensor, and is also used to control the batching scale to obtain a corresponding amount of feed raw materials according to the actual ratio of each feed raw material.

6. The dynamic batching adjustment system according to claim 5, characterized in that: The near infrared sensor is arranged after the pulverizer and before the batching scale, detects the nutritional components of the raw materials during the batching process, and then corrects the batching amount based on the interpolation of the batching amount given in the formula and the actually required batching amount after optimization and adjustment.

7. The dynamic batching adjustment system according to claim 5, characterized in that: The near infrared sensor is arranged after the pulverizer and before or after the batching scale, and is used to obtain the detection data of the current batch of ingredients to control the next batch of ingredients.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the processor executes the optimization control steps of the central control system in the dynamic batching adjustment system as claimed in claim 5.

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