Special meal raw material screening method and system

Abstract

The invention discloses a special meal raw material screening method and system.The method comprises the steps that special meal raw materials are placed on a rotary workbench, and the rotary workbench is made to rotate through an action mechanism so that automatic conveying of the raw materials can be achieved; comprehensive detection is conducted on the special meal raw materials through a multi-parameter collaborative screening module, and the special meal raw materials meeting various indexes are screened out; the multi-parameter collaborative screening module comprises an impurity screening module, a weight screening module, a size screening module, a humidity screening module and a temperature screening module; various parameters in the screening process are recorded in real time, various parameters are analyzed in real time through a neural network, and the screening standard is dynamically adjusted according to the data analysis result. The technical problems that in the prior art, multiple screening dimensions cannot be considered at the same time, and the high-quality standard of special meal beverage production is difficult to ensure are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of raw material screening, and in particular relates to a method and system for screening raw materials for special dietary drinks. Background Art

[0002] The raw material screening technologies for special diet drinks mainly include mechanical screening, manual screening and traditional automated screening. Mechanical screening uses equipment such as drum screens and vibrating screens to perform preliminary screening based on the size or weight differences of the materials. It is suitable for large quantities of materials with relatively uniform shapes. Manual screening relies on manual operation to remove unqualified raw materials through visual inspection and manual classification, and is suitable for small-batch production. Traditional automated screening technology is based on screening with a single parameter (such as weight, humidity, etc.), which can improve screening efficiency. These technologies meet the preliminary screening needs of raw materials for special diet drinks to a certain extent.

[0003] However, existing screening technologies have many limitations. First, the screening accuracy is low, especially for raw materials with irregular shapes or containing impurities, mechanical screening and manual screening are difficult to achieve accurate screening. Secondly, manual screening is inefficient and labor-intensive, and it is difficult to adapt to the high precision and high efficiency requirements of large-scale production. Although traditional mechanical screening has a certain efficiency improvement, it cannot meet the needs of multi-parameter collaborative screening. In addition, the existing technology lacks multi-dimensional collaborative screening capabilities, usually relying only on a single parameter, and cannot combine multiple dimensions such as weight, humidity, size, and impurities for comprehensive screening. At the same time, traditional screening equipment lacks intelligent data analysis and feedback mechanisms, and cannot adjust the screening standards in real time during the production process, which affects the screening accuracy and product consistency. These shortcomings show that the existing screening technology cannot meet the high standards and high efficiency requirements for raw materials in the production of special diet beverages. Summary of the invention

[0004] In order to solve the above technical problems, the present invention proposes a method and system for screening raw materials for special dietary drinks to solve the problems existing in the above-mentioned prior art.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a method for screening raw materials for special dietary drinks, comprising:

[0006] The raw materials of the special meal beverage are placed on a rotating worktable, and the rotating worktable is rotated by an action mechanism to realize automatic conveying of the raw materials;

[0007] Through a multi-parameter collaborative screening module, the special dietary drink raw materials are comprehensively tested to screen out special dietary drink raw materials that meet multiple indicators; the multi-parameter collaborative screening module includes an impurity screening module, a weight screening module, a size screening module and a humidity screening module;

[0008] Record various parameters in the screening process in real time, analyze them in real time through neural networks, and dynamically adjust the screening criteria based on the data analysis results.

[0009] Preferably, the impurity screening module comprises:

[0010] Ultrasonic cleaning of special dietary drink raw materials and setting of ultrasonic frequency;

[0011] Use a constant temperature dryer to dry the cleaned raw materials, or disinfect them with disinfectant.

[0012] Preferably, the weight screening module comprises:

[0013] The raw materials of special dietary drinks are measured by high-precision electronic scales to obtain the measurement results;

[0014] The neural network prediction model in the visual inspection system is used to detect the types of raw materials of the special diet drink in real time, and combined with the measurement results, the ratio between the raw materials and the weight is ensured.

[0015] Preferably, the size screening module comprises:

[0016] The special diet drink raw materials are preliminarily screened through a mechanical card slot mechanism with set size. The motion platform drives the raw materials through the mechanical card slot mechanism. If the special diet drink raw materials can pass through, they will enter the next step, otherwise they will be rejected by the action mechanism.

[0017] Use a CCD industrial camera to take pictures of special meal drink raw materials to obtain image information. By designing an image vision algorithm, the edges of the raw materials are extracted, the edge pixel distribution is calculated, the size of the raw materials is obtained, and it is determined whether the size meets the standards.

[0018] Preferably, the humidity screening module comprises:

[0019] Detect the humidity data of special diet drink raw materials through humidity sensors;

[0020] The detected humidity data is saved to the computer center and processed visually in real time. If special meal drink raw materials that do not meet the humidity requirements are detected, the action mechanism will put them back to the starting position of the special meal drink raw material detection and the detection will be cyclical until they meet the standards.

[0021] Preferably, the temperature screening module comprises:

[0022] Detect humidity data of special diet drink raw materials through temperature sensors;

[0023] The detected temperature data is saved in the computer center and processed visually in real time. If special meal drink raw materials that do not meet the temperature requirements are detected, the action mechanism will put them back to the starting position of the special meal drink raw material detection and the detection will be cyclical until they meet the standards.

[0024] In a second aspect, the present invention provides a screening system for raw materials of special dietary drinks, comprising:

[0025] The automatic conveying module is used to place the raw materials of the special meal drink on the rotating worktable, and the rotating worktable is rotated by the action mechanism to realize the automatic conveying of the raw materials;

[0026] A multi-parameter collaborative screening module, used to conduct a comprehensive test on the raw materials of the special diet drink and screen out the raw materials of the special diet drink that meet multiple indicators; the multi-parameter collaborative screening module includes an impurity screening module, a weight screening module, a size screening module, a humidity screening module and a temperature screening module;

[0027] The data analysis module is used to record various parameters in the screening process in real time, analyze various parameters in real time through neural networks, and dynamically adjust the screening criteria according to the data analysis results.

[0028] In a third aspect, the present invention further discloses a computer device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the first aspect.

[0029] In a fourth aspect, the present invention further discloses a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method described in the first aspect when executed by a processor.

[0030] In a fifth aspect, the present invention further discloses a computer program product, including a computer program, which implements the steps of the method described in the first aspect when executed by a processor.

[0031] Compared with the prior art, the present invention has the following advantages and technical effects:

[0032] In view of the problem that existing screening technologies can only perform screening based on a single parameter and cannot accurately handle multi-dimensional screening needs, the present invention uses multi-dimensional collaborative screening technology to combine multiple parameters such as impurities, weight, size, humidity, etc. for comprehensive screening, thereby significantly improving the screening accuracy.

[0033] In view of the problem that traditional screening technology cannot meet high-standard screening requirements, the present invention provides an intelligent screening device that can automatically and efficiently complete screening tasks and adjust screening standards in real time to meet the needs of large-scale production.

[0034] In view of the problem that traditional screening equipment lacks data recording and analysis capabilities and is difficult to make real-time adjustments during the production process, the present invention integrates intelligent data analysis and feedback mechanisms to monitor the screening process in real time and adjust the screening parameters based on the analysis results, thereby ensuring the accuracy and consistency of the screening.

[0035] In view of the fact that the existing technology is often unable to consider multiple screening dimensions at the same time when processing complex raw materials, it is difficult to ensure the high quality standards of special diet beverage production. The present invention uses multi-parameter collaborative screening technology to comprehensively consider various standards of raw materials to ensure that the screened raw materials meet high quality requirements and adapt to the high standards of special diet beverage production. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0037] Figure 1 is a schematic diagram of a device according to an embodiment of the present invention;

[0038] Figure 2 A schematic diagram of a raw material screening workflow according to an embodiment of the present invention;

[0039] Figure 3 A schematic diagram of a mechanical size screening module according to an embodiment of the present invention;

[0040] Figure 4 A schematic diagram of neural network training according to an embodiment of the present invention;

[0041] Among them, 1. Screening module; 2. CCD industrial camera; 3. Rotating working platform; 4. Action mechanism; 5. Upper push rod; 6. Raw materials; 7. Push rod mechanism; 8. Mechanical slot mechanism. DETAILED DESCRIPTION

[0042] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0043] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0044] Embodiment 1

[0045] like Figure 1As shown, the present invention provides a screening device for raw materials of special diet drinks, which aims to accurately screen out high-quality raw materials that meet the production needs of special diet drinks through innovative process flow and optimized technical solutions. The quality of special diet drinks is directly affected by the raw materials. Therefore, ensuring that the raw materials meet the standardization requirements, such as nutritional ingredients, humidity, temperature, size, impurity content, etc., is a crucial link in the production process. The existing technology has problems such as low screening accuracy, low efficiency, and lack of multi-dimensional collaborative screening capabilities. The present invention overcomes these technical limitations through multi-parameter collaborative screening technology and intelligent data analysis methods, and provides a new device and method that can efficiently and accurately screen high-quality raw materials. The implementation of this technical solution will greatly improve the raw material screening accuracy and production efficiency of special diet drink production, and ensure the stability and consistency of product quality.

[0046] With respect to the screening device, this embodiment provides a method for screening raw materials of special dietary drinks, comprising:

[0047] S1. placing the raw materials of the special diet drink on a rotating worktable, and rotating the rotating worktable through an action mechanism to realize automatic conveying of the raw materials;

[0048] Specifically, the raw materials are placed on the rotating worktable 3 and the process of screening the raw materials is started to ensure their freshness and quality. The raw materials pass through the screening module 1 through the rotating motion of the rotating worktable.

[0049] S2. Through the multi-parameter collaborative screening module, the special dietary drink raw materials are comprehensively tested to screen out the special dietary drink raw materials that meet multiple indicators; the multi-parameter collaborative screening module 1 includes an impurity screening module, a weight screening module, a size screening module and a humidity screening module; the raw material screening workflow, such as Figure 2 As shown;

[0050] Furthermore, the impurity screening module includes:

[0051] Ultrasonic cleaning of special dietary drink raw materials and setting of ultrasonic frequency;

[0052] Use a constant temperature dryer to dry the cleaned raw materials, or disinfect them with disinfectant.

[0053] Specifically, the impurity screening module is mainly used to remove impurities in the raw materials and prevent various contaminants from entering the process of preparing special dietary drinks and causing harm to the human body. It is further explained that the raw materials should be fully cleaned to remove pesticide residues, impurities or other harmful substances that may be attached to the surface to ensure the hygiene and safety of the raw materials. First, the raw materials will pass through the impurity screening module, and the module of the device will clean the raw materials.

[0054] In this embodiment, the cleaning of the raw materials is carried out by ultrasound, and the frequency of the ultrasound is set to F n , which can better ensure that the surface of the raw materials is clean and free of residue. Further explanation: the ultrasonic frequency usually needs to be set according to the surface characteristics, morphology and other features of the raw materials. It is necessary to ensure a clear effect while avoiding damage or changes to the texture and nutritional content of the raw materials. Therefore, the ultrasonic frequency setting will have multiple values, and the value of n is 1, 2, 3... Furthermore, use a constant temperature dryer to dry the cleaned raw materials, or use disinfectant to disinfect them to reduce the risk of bacterial contamination and lay the foundation for subsequent processing steps. It is necessary to ensure that the cleaned raw materials quickly return to a clean and dry state. Furthermore, the set ultrasonic frequency F n Stored as ultrasound information storage n1.

[0055] Furthermore, the weight screening module includes:

[0056] The raw materials of special dietary drinks are measured by high-precision electronic scales to obtain the measurement results;

[0057] The neural network prediction model in the visual inspection system is used to detect the types of raw materials of the special diet drink in real time, and combined with the measurement results, the ratio between the raw materials and the weight is ensured.

[0058] In this embodiment, the weight screening module mainly measures the raw materials by means of a high-precision electronic scale. Further explanation, the automated metering system mainly includes a visual inspection system, a high-precision electronic scale, etc. The visual inspection system is a neural network prediction model, which can detect in real time which type of raw material the current raw material is, and then obtain the weight of the raw material by means of a high-precision electronic scale, thereby ensuring that there is no error in the ratio between the raw materials and the weight.

[0059] The data for training the neural network model comes from the raw materials of the selected manufacturers. This is to avoid the complexity of the raw material sources, which will lead to the difficulty of training the neural network model and increase the probability of recognition errors. This also further ensures the traceability of the raw materials and the consistency of the raw materials, which ensures the efficacy of the special diet drink to a certain extent.

[0060] The construction of the neural network model is based on the pictures collected from the real-time working conditions, and the quality and effect of the final product form a corresponding relationship, such as Figure 4As shown. This is conducive to establishing the relationship between the texture and weight of raw materials and the quality of the final product. After multiple iterations of training, the neural network model can reversely give information such as the ratio of the required raw materials according to the quality and effect of the set product. Furthermore, the model can determine whether the raw materials of the current batch meet the final requirements of the product. If not, the visual system directly gives a reminder, thereby reducing the loss of the enterprise to a certain extent. Furthermore, the raw material image taken by the CCD industrial camera 2 is stored as the image information storage n2, and the weight measured by the metering system is stored as the weight information storage n3.

[0061] Furthermore, the size screening module comprises:

[0062] The special diet drink raw materials are preliminarily screened through a mechanical card slot mechanism with set size. The motion platform drives the raw materials through the mechanical card slot mechanism. If the special diet drink raw materials can pass through, they will enter the next step, otherwise they will be rejected by the action mechanism.

[0063] Use a CCD industrial camera to take pictures of special meal drink raw materials to obtain image information. By designing an image vision algorithm, the edges of the raw materials are extracted, the edge pixel distribution is calculated, the size of the raw materials is obtained, and it is determined whether the size meets the standards.

[0064] Specifically, the size screening module mainly screens the size of raw materials by mechanical means in conjunction with the visual monitoring system. Specifically, the mechanical screening is performed by using a mechanical slot mechanism 8 with a set size, and driving the raw material 6 through a motion platform, so that the raw material 6 slowly passes through the mechanical slot mechanism 8. If the raw material can pass through the mechanical slot mechanism 8, it means that the size of the raw material meets the standard. If it does not meet the standard, the action mechanism will reject it. The working method of the mechanical slot is as follows Figure 3 As shown. Further, when the raw material 6 slowly passes through the mechanical slot mechanism 8, the upper push rod 5 and the push rod mechanism 7 will move slowly, so that the raw material 6 can pass through the mechanical slot mechanism 8 according to the standard size position. The size screening module obtains the size information and stores it as the size information storage n4.

[0065] As an innovative implementation method, the previous process is to perform preliminary size screening of raw materials by mechanical card slots, and the next step is to make judgments through a visual inspection system. Specifically, the raw materials are photographed by a CCD industrial camera 2 to obtain image information, and an image vision algorithm is designed to extract the edges of the raw materials, calculate the distribution of edge pixels, and thus calculate the specific size of the raw materials. This is to further ensure the size of the raw materials, because mechanical screening will inevitably result in various mechanical errors. Furthermore, by visually judging the size, the size error of the raw materials can be minimized.

[0066] Furthermore, the humidity screening module comprises:

[0067] Detect the humidity data of special diet drink raw materials through humidity sensors;

[0068] The detected humidity data is saved to the computer center and processed in real time through visualization. If special meal drink raw materials that do not meet the humidity requirements are detected, the action mechanism puts them back to the starting position of the special meal drink raw material detection and repeats the detection until they meet the standards. The humidity information obtained by the humidity screening module is stored as humidity information storage n5.

[0069] Specifically, the humidity screening module mainly detects the humidity of the raw materials after the above-mentioned process by installing a humidity sensor, in order to ensure that the humidity is just right before the special meal drink is made or before the raw materials are packaged, otherwise it may affect the quality of the raw materials and thus affect the quality of the product.

[0070] Furthermore, the temperature screening module includes:

[0071] Detect the temperature data of special meal drink raw materials through temperature sensors;

[0072] The detected temperature data is saved to the computer center and processed in real time through visualization. If special meal drink raw materials that do not meet the temperature requirements are detected, the action mechanism puts them back to the starting position of the special meal drink raw material detection, and the detection is cyclical until they meet the standards. The temperature screening module obtains the temperature information which is stored as the temperature information storage n6.

[0073] Specifically, the temperature screening module mainly detects the temperature of the raw materials after the above-mentioned process by installing temperature sensors, in order to ensure that the temperature is just right before the special meal preparation or before the packaging of the raw materials, otherwise it may affect the quality of the raw materials and thus affect the quality of the product.

[0074] In this embodiment, the humidity and temperature screening module is the same as other modules. The detected data will be saved to the computer center for real-time visualization processing, which greatly improves the quality traceability of the produced products. Furthermore, if non-compliant raw materials are detected, the action mechanism will put the raw materials back to the starting position of the first step of raw material detection. This will be repeated several times to ensure the quality of the raw materials and prevent system errors of the raw material screening device.

[0075] S3. Record various parameters in the screening process in real time, analyze various parameters in real time through neural network, and dynamically adjust the screening criteria according to the data analysis results.

[0076] Specifically, all real-time stored information can be viewed in real time. If the information of a certain link does not meet the set threshold, the monitoring system will issue an alarm to remind the operator to check. This greatly improves production efficiency and product quality.

[0077] Beneficial effects of this embodiment:

[0078] This embodiment proposes a method for comprehensive screening of raw materials by combining multiple parameters (such as weight, humidity, temperature, size, impurity content, etc.), which can achieve accurate screening of raw materials for special diet drinks and meet the requirements of high-quality and standardized production.

[0079] The screening device of this embodiment is equipped with an intelligent data analysis system, which can record various parameters in the screening process in real time and adjust the screening criteria according to data feedback to ensure screening accuracy and product consistency.

[0080] This embodiment improves screening efficiency and reduces human interference by optimizing traditional screening processes and combining automation and intelligent technologies, and achieves more efficient and accurate screening based on multi-parameter collaborative screening.

[0081] This embodiment also involves the structural design of the screening device, ensuring that the device is easy to operate, efficient and maintain, and is suitable for large-scale production environments.

[0082] Embodiment 2

[0083] Based on the same inventive concept, this embodiment also provides a screening system for special dietary drink raw materials, including:

[0084] The automatic conveying module is used to place the raw materials of the special meal drink on the rotating worktable, and the rotating worktable is rotated by the action mechanism to realize the automatic conveying of the raw materials;

[0085] A multi-parameter collaborative screening module, used to conduct a comprehensive test on the raw materials of the special diet drink and screen out the raw materials of the special diet drink that meet multiple indicators; the multi-parameter collaborative screening module includes an impurity screening module, a weight screening module, a size screening module, a humidity screening module and a temperature screening module;

[0086] The data analysis module is used to record various parameters in the screening process in real time, analyze various parameters in real time through neural networks, and dynamically adjust the screening criteria according to the data analysis results.

[0087] The screening system for special dietary drink raw materials provided in this embodiment has all the advantages of the screening method for special dietary drink raw materials provided in the first embodiment.

[0088] Embodiment 3

[0089] This embodiment further discloses a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the first embodiment.

[0090] Embodiment 4

[0091] This embodiment further discloses a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in the first embodiment are implemented.

[0092] Embodiment 5

[0093] This embodiment also discloses a computer program product, including a computer program, which implements the steps of the method described in the first embodiment when executed by a processor.

[0094] The above are only preferred specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for screening raw materials for special dietary drinks, characterized in that: The following steps are involved: The raw materials of the special meal beverage are placed on a rotating worktable, and the rotating worktable is rotated by an action mechanism to realize automatic conveying of the raw materials; Through a multi-parameter collaborative screening module, the special dietary drink raw materials are comprehensively tested to screen out the special dietary drink raw materials that meet multiple indicators; the multi-parameter collaborative screening module includes an impurity screening module, a weight screening module, a size screening module, a humidity screening module and a temperature screening module; Record various parameters in the screening process in real time, analyze them in real time through neural networks, and dynamically adjust the screening criteria based on the data analysis results.

2. The method according to claim 1, characterized in that The impurity screening module comprises: Ultrasonic cleaning of special dietary drink raw materials and setting of ultrasonic frequency; Use a constant temperature dryer to dry the cleaned raw materials, or disinfect them with disinfectant.

3. The method according to claim 1, characterized in that The weight screening module comprises: The raw materials of special dietary drinks are measured by high-precision electronic scales to obtain the measurement results; The neural network prediction model in the visual inspection system is used to detect the types of raw materials of the special diet drink in real time, and combined with the measurement results, the ratio between the raw materials and the weight is ensured.

4. The method according to claim 1, characterized in that: The size screening module comprises: The special diet drink raw materials are preliminarily screened through a mechanical card slot mechanism with set size. The motion platform drives the raw materials through the mechanical card slot mechanism. If the special diet drink raw materials can pass through, they will enter the next step, otherwise they will be rejected by the action mechanism. Use a CCD industrial camera to take pictures of special meal drink raw materials to obtain image information. By designing an image vision algorithm, the edges of the raw materials are extracted, the edge pixel distribution is calculated, the size of the raw materials is obtained, and it is determined whether the size meets the standards.

5. The method according to claim 1, characterized in that The humidity screening module comprises: Detect the humidity data of special diet drink raw materials through humidity sensors; The detected humidity data is saved to the computer center and processed visually in real time. If special meal drink raw materials that do not meet the humidity requirements are detected, the action mechanism will put them back to the starting position of the special meal drink raw material detection and the detection will be cyclical until they meet the standards.

6. The method according to claim 1, characterized in that The temperature screening module comprises: Detect humidity data of special diet drink raw materials through temperature sensors; The detected temperature data is saved in the computer center and processed visually in real time. If special meal drink raw materials that do not meet the temperature requirements are detected, the action mechanism will put them back to the starting position of the special meal drink raw material detection and the detection will be cyclical until they meet the standards.

7. A screening system for raw materials of special dietary drinks, characterized in that: include: The automatic conveying module is used to place the raw materials of the special meal drink on the rotating worktable, and the rotating worktable is rotated by the action mechanism to realize the automatic conveying of the raw materials; A multi-parameter collaborative screening module, used to conduct a comprehensive test on the raw materials of the special diet drink and screen out the raw materials of the special diet drink that meet multiple indicators; the multi-parameter collaborative screening module includes an impurity screening module, a weight screening module, a size screening module and a humidity screening module; The data analysis module is used to record various parameters in the screening process in real time, analyze various parameters in real time through neural networks, and dynamically adjust the screening criteria according to the data analysis results.

8. A computer device comprising a memory, a processor and a computer program stored in 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 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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