Feed automated production control system and method

Abstract

This invention discloses an automated feed production control system and method, relating to the technical field of production. The system first uses a component analysis module to accurately assess the component distribution state using characteristic parameters such as resistivity (Dzlz) and eddy current intensity (Wlqd), ensuring that feed mixing reaches a qualified state, thus helping to guarantee feed uniformity and improve animal feeding results. A comprehensive production assessment module uses an agglomeration risk index (Jkfx) to comprehensively consider factors such as the mixing degree coefficient (Jbxs) and component distribution state coefficient (Cfxs), achieving real-time assessment of agglomeration risk, thereby reducing the risk of agglomeration in feed production and improving feed stability. By comparing the risk assessment threshold F with the agglomeration risk index (Jkfx), accurate judgment of the agglomeration level risk is achieved, and corresponding control schemes can be automatically implemented to address potential problems in a timely manner, improving the automation level and safety of production.

Description

Technical Field

[0001] The invention relates to the technical field of production, and in particular to a feed automated production control system and method. Background Art

[0002] In modern industrial automation, the application of intelligent technology has become the key to improving production efficiency and quality, and has brought new development opportunities to the feed processing and production industry. It is a vital part of the agricultural breeding industry, especially in the animal husbandry industry. The quality and production efficiency of feed play a vital role in the growth and health of livestock and poultry. In terms of feed production, the focus is on how to improve the quality of feed through scientific and technological means, ensure the accuracy of the formula, and optimize the production process; therefore, the precise feed production process has become the key to agricultural modernization.

[0003] In the process of feed production, it is inevitable that feed will agglomerate, which may cause uneven mixing of feed, affect the balanced distribution of nutrients, and further affect the feeding effect of animals. Therefore, solving the problem of feed agglomeration has become an important part of improving the quality and efficiency of feed production.

[0004] However, the traditional feed production method has some shortcomings when facing the agglomeration problem. The existing feed production process often relies on manual experience, which cannot comprehensively and accurately solve the agglomeration problem, making it difficult to ensure the uniformity and quality of the feed, and unable to timely judge the mixing state of the feed, which is prone to agglomeration. This will lead to a decrease in production efficiency and increase the quality risk in feed production; in addition, traditional control methods often find it difficult to cope with changes in different raw materials and fluctuations in the production environment through manual experience. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the deficiencies in the prior art, the present invention provides a feed automated production control system and method, which solves the problems in the above-mentioned background technology.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: a feed automated production control system, including a raw material locking module, an automatic collection module, a component analysis module, a comprehensive production evaluation module and a control management module;

[0009] The raw material locking module is used to establish a human-computer interaction interface, from which the composition and proportion of each raw material input by the operator are obtained, and the density status of each component is monitored and registered;

[0010] The automatic collection module is used to collect and record the relevant distribution status data information of each component in the feed by using several groups of sensors after the feed mixing operation, and monitor and collect the relevant mixing status data information of the feed according to the total amount of feed to be produced, and generate the feed data set after dimensionless processing;

[0011] The component analysis module is used to extract features using relevant distribution state data information to obtain resistivity Dzlz and eddy current intensity Wlqd to evaluate the component distribution state coefficient Cfxs, and compare and analyze the component distribution state coefficient Cfxs with a preset state threshold L to determine whether the current feed mixing is in a qualified state;

[0012] The comprehensive production evaluation module is used to summarize the content of each component to obtain the total component content Zhlz, and evaluate the stirring degree coefficient Jbxs according to the total component content Zhlz, and associate the stirring degree coefficient Jbxs with the component distribution state coefficient Cfxs, and after dimensionless processing, fit and calculate the agglomeration risk index Jkfx, and the agglomeration risk index Jkfx is obtained by the following formula:

[0013]

[0014] Wherein, Jbxs represents the stirring degree coefficient, Cfxs represents the component distribution state coefficient, Wdc represents the temperature difference, Sdz represents the humidity value, j, c, w and s represent the preset proportional coefficients of the stirring degree coefficient Jbxs, the component distribution state coefficient Cfxs, the temperature difference Wdc and the humidity value Sdz, respectively, wherein 0.23≤j≤0.34, 0.18≤c≤0.41, 0.05≤w≤0.10, 0.10≤s≤0.15, and 0.60≤j+c+w+s≤1.0, and R represents the first correction constant;

[0015] The control management module is used to pre-set a risk assessment threshold F, and compare and analyze the agglomeration risk index Jkfx with the risk assessment threshold F to obtain an agglomeration level risk result, and adopt a corresponding automatic control plan based on the agglomeration level risk result.

[0016] Preferably, the raw material locking module includes a component information unit and a component summary unit;

[0017] The ingredient information unit is used to store and record detailed information of each raw material ingredient in the feed, including name, origin, content and density, and to identify and track the attributes of each raw material;

[0018] The component summary unit is used to summarize and count the overall information of all raw material components in the feed, including the total content of each component, the humidity of each component and the density value of each component, and marked as the first component density value Cfmd1, the second component density value Cfmd2, ..., the Nth component density value Cfmd N , summary forms include generating reports, providing production statistics, and assisting in recipe adjustments.

[0019] Preferably, the automatic acquisition module includes a distribution data unit and a stirring data unit;

[0020] The feed data set includes relevant distribution status data information and relevant stirring status data information;

[0021] The distribution data unit is used to collect relevant distribution status data information of each component in the feed, including resistivity Dzlz, eddy current intensity Wlqd, centrifugal force value Lxlz, first component density value Cfmd1, second component density value Cfmd2, ..., Nth component density value Cfmd N And the convection case, wherein the first component density value Cfmd1, the second component density value Cfmd2, ..., the Nth component density value Cfmd N Perform statistical averaging to obtain the average value of the sum of the density values ​​of each component

[0022] The stirring data unit is used to collect relevant stirring condition data information of the feed during the stirring process, including the stirring distance Jqjj, stirring time Jscz, stirring speed Jsdz, number of stirrers, stirrer angle and the distance between the stirrer and the inner wall of the stirring drum in the feed stirring equipment.

[0023] Preferably, the component analysis module includes a first analysis unit, a second analysis unit and an evaluation unit;

[0024] The first analysis unit is used to obtain the density standard deviation value Mdcz by comprehensive analysis according to the number of component species Cfzs and the density value of each component. The density standard deviation value Mdcz is obtained by the following formula:

[0025]

[0026] Cfm i Expressed as the density value of the i-th component, It is expressed as the average value of the sum of the density values ​​of each component, and N is the number of raw material components in the feed.

[0027] Preferably, the second analysis unit is used to associate the resistivity Dzlz with the eddy current intensity Wlqd, and obtain the component distribution state coefficient Cfxs after dimensionless processing, and the component distribution state coefficient Cfxs is obtained by the following formula:

[0028]

[0029] In the formula, Lxlz represents the centrifugal force value, F1, F2, F3 and F4 represent the preset proportional coefficients of resistivity Dzlz, eddy current intensity Wlqd, centrifugal force value Lxlz and density standard deviation value Mdcz, respectively, where 0.11≤F1≤0.21, 0.16≤F2≤0.20, 0.07≤F3≤0.15, 0.10≤F4≤0.44, and 0.50≤F1+F2+F3+F4≤1.0, and B represents the second correction constant.

[0030] Preferably, the evaluation unit is used to pre-set a state threshold L, and compare and analyze the component distribution state coefficient Cfxs with the state threshold L to determine whether the current feed mixing is in a qualified state;

[0031] If the component distribution state coefficient Cfxs is higher than or equal to the state threshold L, that is, Cfxs ≥ L, it means that the current feed mixing is in a qualified state;

[0032] If the component distribution state coefficient Cfxs is lower than the state threshold L, that is, Cfxs<L, it means that the current feed mixing is in an unqualified state.

[0033] Preferably, the total component content Zhlz is associated with the stirrer spacing Jqjj, and after dimensionless processing, the stirring degree coefficient Jbxs is obtained, and the stirring degree coefficient Jbxs is obtained by the following formula:

[0034]

[0035] In the formula, Jscz represents the stirring time, Jsdz represents the stirring speed, a1, a2, a3 and a4 represent the preset proportional coefficients of the total component content Zhlz, the stirrer spacing Jqjj, the stirring time Jscz and the stirring speed Jsdz, respectively, wherein 0.20≤a1≤0.52, 0.04≤a2≤0.16, 0.10≤a3≤0.22, 0.05≤a4≤0.10, and 0.45≤a1+a2+a3+a4≤1.0, and C represents the third correction constant.

[0036] Preferably, the control management module includes a control unit;

[0037] The control unit is used to pre-set a risk assessment threshold F, wherein the risk assessment threshold F includes a first assessment threshold K1 and a second assessment threshold K2, and the first assessment threshold K1 is greater than the second assessment threshold K2, and the agglomeration risk index Jkfx is compared and analyzed with the risk assessment threshold F to obtain an agglomeration level risk result, wherein the specific content of the agglomeration level risk result is as follows:

[0038] If the agglomeration risk index Jkfx ≤ the second evaluation threshold K2, it indicates that the agglomeration situation in the current feed is in an abnormal state, and a first result report is generated;

[0039] If the second evaluation threshold value K2 is less than the agglomeration risk index Jkfx≤K1, it indicates that the agglomeration situation in the current feed is in a normal state, and a second result report is generated;

[0040] If the first evaluation threshold K1 is less than the agglomeration risk index Jkfx, it indicates that the agglomeration situation in the current feed is normal, and a third result report is generated.

[0041] Preferably, the control management module further includes a response unit;

[0042] The response unit is used to adopt corresponding automatic control schemes for the first result report, the second result report and the third result report, and the specific automatic control schemes are as follows:

[0043] If it is the first result report, the response unit will issue a red warning notification to remind the operator that there is a caking problem in the current feed, and control the current feed to enter the next link to avoid rework in the later stage;

[0044] If it is the second result report, the response unit will maintain the current state, but the feed status monitoring needs to be strengthened to ensure that potential abnormal conditions are discovered in time, and the preventive maintenance program is initiated to inspect and maintain the equipment to prevent subsequent agglomeration problems;

[0045] If it is the third result report, the response unit will maintain the current state, strengthen the normal operation monitoring of the feed production process, and ensure production stability.

[0046] A feed automated production control method comprises the following steps:

[0047] Step 1: First, the raw material locking module will establish a human-computer interaction interface to obtain the composition and proportion of each raw material input by the operator, and monitor and register the density status of each component;

[0048] Step 2: After the feed is mixed, the automatic collection module uses several groups of sensors to collect and record the distribution status data of each component in the feed, and monitors and collects the mixing status data of the feed according to the total amount of feed to be produced to generate a feed data set;

[0049] Step 3: The component analysis module is used to evaluate the component distribution state coefficient Cfxs by using the relevant distribution state data information, and compare and analyze the component distribution state coefficient Cfxs with the preset state threshold L to determine whether the current feed mixing is in a qualified state;

[0050] Step 4: In addition, the comprehensive production evaluation module is used to summarize the content of each component to obtain the total component content Zhlz, and evaluate the stirring degree coefficient Jbxs according to the total component content Zhlz, and associate the stirring degree coefficient Jbxs with the component distribution state coefficient Cfxs to fit and calculate the agglomeration risk index Jkfx;

[0051] Step 5: Finally, the control management module compares and analyzes the agglomeration risk index Jkfx with the risk assessment threshold F to obtain the agglomeration level risk result and adopts the corresponding automatic control plan.

[0052] (III) Beneficial effects

[0053] The present invention provides a feed automated production control system and method, which has the following beneficial effects:

[0054] (1) The system first uses characteristic parameters such as resistivity Dzlz and eddy current intensity Wlqd through the component analysis module to accurately evaluate the component distribution state, ensure that the feed mixing reaches the qualified state, help to ensure the uniformity of the feed, and improve the animal feeding effect. The comprehensive production evaluation module comprehensively considers factors such as the mixing degree coefficient Jbxs and the component distribution state coefficient Cfxs through the agglomeration risk index Jkfx, and realizes real-time evaluation of the agglomeration risk, thereby reducing the agglomeration risk in feed production and improving the stability of the feed. By comparing the risk assessment threshold F with the agglomeration risk index Jkfx, the agglomeration level risk is accurately judged, and the corresponding control plan can be automatically adopted to respond to potential problems in a timely manner, thereby improving the automation and safety of production. By establishing a human-computer interaction interface, the system allows operators to easily input the raw material composition and proportion, but reduces the reliance on manual labor in the automatic collection, analysis and evaluation stages, reduces the burden on operators, and improves the level of intelligent production. In short, compared with the existing technology, this system abandons the reliance on manual experience to determine the current feed qualification status. It collects relevant parameters in multiple dimensions and comprehensively and objectively determines the agglomeration status in order to determine the qualification of the feed. It has brought new development opportunities to the agricultural breeding industry, provided a more reliable feeding foundation for livestock and poultry breeding, and helped to promote the entire industry to develop in a more modern direction.

[0055] (2) Through the stirring degree coefficient Jbxs, which comprehensively considers multiple factors such as total ingredient content Zhlz, stirrer spacing Jqjj, stirring time Jscz and stirring speed Jsdz, the stirring degree can be quantitatively evaluated, which helps to fully control the stirring process and improve the accurate measurement of the stirring degree. It provides a scientific basis for the production process, enables the stirring parameters to work better together, optimizes the stirring effect of the feed, and at the same time, helps to better control the stirring process, reduce unnecessary waste, and improve production efficiency.

[0056] (3) According to the different agglomeration level risk results, corresponding automatic control schemes are adopted. Through intelligent response and timely human intervention, the system can minimize the duration of abnormal conditions, reduce production risks and improve production efficiency while ensuring the quality of feed production. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a schematic diagram of a flow chart of a feed automation production control system of the present invention;

[0058] Figure 2 The present invention is a schematic flow chart of the steps of a feed automated production control method. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] In modern industrial automation, the application of intelligent technology has become the key to improving production efficiency and quality, and has brought new development opportunities to the feed processing and production industry. It is a vital part of the agricultural breeding industry, especially in the animal husbandry industry. The quality and production efficiency of feed play a vital role in the growth and health of livestock and poultry. In terms of feed production, the focus is on how to improve the quality of feed through scientific and technological means, ensure the accuracy of the formula, and optimize the production process; therefore, the precise feed production process has become the key to agricultural modernization.

[0061] In the process of feed production, it is inevitable that feed will agglomerate, which may cause uneven mixing of feed, affect the balanced distribution of nutrients, and further affect the feeding effect of animals. Therefore, solving the problem of feed agglomeration has become an important part of improving the quality and efficiency of feed production.

[0062] However, the traditional feed production method has some shortcomings when facing the agglomeration problem. The existing feed production process often relies on manual experience, which cannot comprehensively and accurately solve the agglomeration problem, making it difficult to ensure the uniformity and quality of the feed, and unable to timely judge the mixing state of the feed, which is prone to agglomeration. This will lead to a decrease in production efficiency and increase the quality risk in feed production; in addition, traditional control methods often find it difficult to cope with changes in different raw materials and fluctuations in the production environment through manual experience.

[0063] Example 1

[0064] See also Figure 1 , the present invention provides a feed automated production control system, including a raw material locking module, an automatic collection module, a component analysis module, a comprehensive production evaluation module and a control management module;

[0065] The raw material locking module is used to establish a human-computer interaction interface, from which the composition and proportion of each raw material input by the operator are obtained, and the density status of each component is monitored and registered;

[0066] The automatic collection module is used to collect and record the relevant distribution status data information of each component in the feed by using several groups of sensors after the feed mixing operation, and monitor and collect the relevant mixing status data information of the feed according to the total amount of feed to be produced, and generate the feed data set after dimensionless processing;

[0067] The component analysis module is used to extract features using relevant distribution state data information to obtain resistivity Dzlz and eddy current intensity Wlqd to evaluate the component distribution state coefficient Cfxs, and compare and analyze the component distribution state coefficient Cfxs with a preset state threshold L to determine whether the current feed mixing is in a qualified state;

[0068] The comprehensive production evaluation module is used to summarize the content of each component to obtain the total component content Zhlz, and evaluate the stirring degree coefficient Jbxs according to the total component content Zhlz, and associate the stirring degree coefficient Jbxs with the component distribution state coefficient Cfxs, and after dimensionless processing, fit and calculate the agglomeration risk index Jkfx, and the agglomeration risk index Jkfx is obtained by the following formula:

[0069]

[0070] Wherein, Jbxs represents the stirring degree coefficient, Cfxs represents the component distribution state coefficient, Wdc represents the temperature difference, Sdz represents the humidity value, j, c, w and s represent the preset proportional coefficients of the stirring degree coefficient Jbxs, the component distribution state coefficient Cfxs, the temperature difference Wdc and the humidity value Sdz, respectively, wherein 0.23≤j≤0.34, 0.18≤c≤0.41, 0.05≤w≤0.10, 0.10≤s≤0.15, and 0.60≤j+c+w+s≤1.0, and R represents the first correction constant;

[0071] The control management module is used to pre-set a risk assessment threshold F, and compare and analyze the agglomeration risk index Jkfx with the risk assessment threshold F to obtain an agglomeration level risk result, and adopt a corresponding automatic control plan based on the agglomeration level risk result.

[0072] During the operation of this system, the system further realizes real-time monitoring of the mixing state and component distribution by automatically collecting and analyzing key parameters in the feed production process, thereby indirectly optimizing the production process and improving production efficiency and feed quality; the component analysis module uses characteristic parameters such as resistivity Dzlz and eddy current intensity Wlqd to accurately evaluate the component distribution state to ensure that the feed mixing reaches a qualified state. The comprehensive production evaluation module comprehensively considers factors such as the mixing degree coefficient Jbxs and the component distribution state coefficient Cfxs through the agglomeration risk index Jkfx, and realizes real-time evaluation of agglomeration risk. By comparing the risk assessment threshold F with the agglomeration risk index Jkfx, it realizes accurate judgment of the agglomeration level risk, and can automatically adopt corresponding control plans to respond to potential problems in a timely manner, thereby improving the degree of automation and safety of production.

[0073] Example 2

[0074] Please refer to Figure 1 ,Specifically: the raw material locking module includes a component information unit and a component summary unit;

[0075] The ingredient information unit is used to store and record detailed information of each raw material ingredient in the feed, including name, origin, content and density, and to identify and track the attributes of each raw material;

[0076] The component summary unit is used to summarize and count the overall information of all raw material components in the feed, including the total content of each component, the humidity of each component and the density value of each component, and marked as the first component density value Cfmd1, the second component density value Cfmd2, ..., the Nth component density value Cfmd N , provides a comprehensive overview of the ingredients, provides management with an intuitive data overview and comprehensive analysis, which helps to generate production statistical reports and assist in formula adjustments, thereby optimizing the feed production process, improving production efficiency and finished product quality; the summary form includes generating reports, providing production statistics, and assisting in formula adjustments.

[0077] The automatic acquisition module includes a distribution data unit and a stirring data unit;

[0078] The feed data set includes relevant distribution status data information and relevant stirring status data information;

[0079] The distribution data unit is used to collect relevant distribution status data information of each component in the feed, including resistivity Dzlz, eddy current intensity Wlqd, centrifugal force value Lxlz, first component density value Cfmd1, second component density value Cfmd2, ..., Nth component density value Cfmd N And the convection case, wherein the first component density value Cfmd1, the second component density value Cfmd2, ..., the Nth component density value Cfmd N Perform statistical averaging to obtain the average value of the sum of the density values ​​of each component

[0080] The stirring data unit is used to collect relevant stirring condition data information of the feed during the stirring process, including the stirring distance Jqjj, stirring time Jscz, stirring speed Jsdz, number of stirrers, stirrer angle and the distance between the stirrer and the inner wall of the stirring drum in the feed stirring equipment.

[0081] In this embodiment, each raw material information is stored in detail through the ingredient information unit and the ingredient summary unit, so that the quality of feed production can be traced and managed, and an accurate ingredient overview can be provided for production, which is helpful to formulate scientific formulas and adjust the ingredient ratio in time, and improve the quality and suitability of feed. The relevant distribution state data information collected by the distribution data unit and the stirring condition data information collected by the stirring data unit realize real-time monitoring of the feed production process, which enables the system to accurately control the stirring state of the feed, improves the automation level of production, and reduces the possibility of uneven stirring. The automatic acquisition module provides a feed data set, including relevant distribution state data information and stirring condition data information. Through the comprehensive analysis of these data by the ingredient analysis module and the comprehensive production evaluation module, the system can realize real-time evaluation of the risk of agglomeration. In short, the system realizes comprehensive monitoring, analysis and control of the entire process of feed production by integrating the raw material locking module and the automatic acquisition module, as well as the corresponding data processing unit, and provides a modern and intelligent solution for the agricultural breeding industry.

[0082] Example 3

[0083] Please refer to Figure 1 ,Specifically: the component analysis module includes a first analysis unit, a second analysis unit and an evaluation unit;

[0084] The first analysis unit is used to obtain the density standard deviation value Mdcz by comprehensive analysis according to the number of component species Cfzs and the density value of each component. The density standard deviation value Mdcz is obtained by the following formula:

[0085]

[0086] Cfm i Expressed as the density value of the i-th component, It is expressed as the average value of the sum of the density values ​​of each component, and N is the number of raw material components in the feed.

[0087] The second analysis unit is used to associate the resistivity Dzlz with the eddy current intensity Wlqd, and obtain the component distribution state coefficient Cfxs after dimensionless processing. The component distribution state coefficient Cfxs is obtained by the following formula:

[0088]

[0089] In the formula, Lxlz represents the centrifugal force value, F1, F2, F3 and F4 represent the preset proportional coefficients of resistivity Dzlz, eddy current intensity Wlqd, centrifugal force value Lxlz and density standard deviation value Mdcz, respectively, where 0.11≤F1≤0.21, 0.16≤F2≤0.20, 0.07≤F3≤0.15, 0.10≤F4≤0.44, and 0.50≤F1+F2+F3+F4≤1.0, and B represents the second correction constant.

[0090] The centrifugal force value Lxlz is monitored and obtained by a rotation speed sensor or an acceleration sensor, etc.;

[0091] The resistivity Dzlz is measured by using a resistance sensor, or a conductivity instrument is used to obtain resistivity related data;

[0092] The eddy current intensity Wlqd is obtained by using an eddy current sensor or an eddy current detection instrument;

[0093] The evaluation unit is used to pre-set a state threshold L, and compare and analyze the component distribution state coefficient Cfxs with the state threshold L to determine whether the current feed mixing is in a qualified state;

[0094] If the component distribution state coefficient Cfxs is higher than or equal to the state threshold L, that is, Cfxs ≥ L, it means that the current feed mixing is in a qualified state;

[0095] If the component distribution state coefficient Cfxs is lower than the state threshold L, that is, Cfxs<L, it means that the current feed mixing is in an unqualified state.

[0096] In this embodiment, by evaluating the density standard deviation value Mdcz, the system can judge the density uniformity of the feed, provide a quantitative reference standard for the mixing quality, and help to achieve accurate control of the mixing process. Through the component distribution state coefficient Cfxs, multiple factors such as resistivity Dzlz, eddy current intensity Wlqd, centrifugal force value Lxlz and density standard deviation value Mdcz are comprehensively considered, which can more comprehensively reflect the feed mixing state, help the system to comprehensively evaluate the mixing uniformity of the feed, and further improve the accurate measurement of the mixing state; the component distribution state coefficient Cfxs is compared and analyzed with the state threshold L to achieve the qualification judgment of the current feed mixing state, which provides a basis for the automatic control module, so that the system can automatically judge whether the mixing state is qualified, and take corresponding automatic control schemes to ensure the stability of the production process.

[0097] Example 4

[0098] Please refer to Figure 1Specifically, the total component content Zhlz is associated with the stirrer spacing Jqjj, and after dimensionless processing, the stirring degree coefficient Jbxs is obtained, and the stirring degree coefficient Jbxs is obtained by the following formula:

[0099]

[0100] In the formula, Jscz represents the stirring time, Jsdz represents the stirring speed, a1, a2, a3 and a4 represent the preset proportional coefficients of the total component content Zhlz, the stirrer spacing Jqjj, the stirring time Jscz and the stirring speed Jsdz, respectively, wherein 0.20≤a1≤0.52, 0.04≤a2≤0.16, 0.10≤a3≤0.22, 0.05≤a4≤0.10, and 0.45≤a1+a2+a3+a4≤1.0, and C represents the third correction constant.

[0101] The above-mentioned total component content Zhlz is collected and obtained by a spectrometer or a mass spectrometer;

[0102] The agitator spacing Jqjj is measured by using a laser rangefinder or a photoelectric sensor, etc.; the agitator refers to the agitator support rod in the feed mixing equipment;

[0103] The stirring time Jscz and stirring speed Jsdz can be acquired using sensors on the stirring device, such as a rotation speed sensor and an acceleration sensor;

[0104] In this embodiment, through the stirring degree coefficient Jbxs, which comprehensively considers multiple factors such as total ingredient content Zhlz, stirrer spacing Jqjj, stirring time Jscz and stirring speed Jsdz, the stirring degree can be quantitatively evaluated, which helps to fully control the stirring process, improves the accurate measurement of the stirring degree, provides a scientific basis for the production process, enables the stirring parameters to work better together, optimizes the stirring effect of the feed, and at the same time, helps to better control the stirring process, reduce unnecessary waste, and improve production efficiency.

[0105] Example 5

[0106] Please refer to Figure 1 , specifically: the control management module includes a control unit;

[0107] The control unit is used to pre-set a risk assessment threshold F, wherein the risk assessment threshold F includes a first assessment threshold K1 and a second assessment threshold K2, and the first assessment threshold K1 is greater than the second assessment threshold K2, and the agglomeration risk index Jkfx is compared and analyzed with the risk assessment threshold F to obtain an agglomeration level risk result, wherein the specific content of the agglomeration level risk result is as follows:

[0108] If the agglomeration risk index Jkfx ≤ the second evaluation threshold K2, it indicates that the agglomeration situation in the current feed is in an abnormal state, and a first result report is generated;

[0109] If the second evaluation threshold value K2 is less than the agglomeration risk index Jkfx≤K1, it indicates that the agglomeration situation in the current feed is in a normal state, and a second result report is generated;

[0110] If the first evaluation threshold K1 is less than the agglomeration risk index Jkfx, it indicates that the agglomeration situation in the current feed is normal, and a third result report is generated.

[0111] The control management module also includes a response unit;

[0112] The response unit is used to adopt corresponding automatic control schemes for the first result report, the second result report and the third result report, and the specific automatic control schemes are as follows:

[0113] If it is the first result report, the response unit will issue a red warning notification to remind the operator that there is a caking problem in the current feed, and control the current feed to enter the next link to avoid rework in the later stage, such as the packaging and bag sealing link. The red warning notification is implemented through SMS or email to ensure timely manual intervention;

[0114] If it is the second result report, the response unit will maintain the current state, but the feed status monitoring needs to be strengthened to ensure that potential abnormal conditions are discovered in time, and the preventive maintenance program is initiated to inspect and maintain the equipment to prevent subsequent agglomeration problems;

[0115] If it is the third result report, the response unit will maintain the current state, strengthen the normal operation monitoring of the feed production process, and ensure production stability.

[0116] In this embodiment, by pre-setting the risk assessment threshold F, including the first assessment threshold K1 and the second assessment threshold K2, the system can clearly classify the agglomeration level risk results. According to the analysis results, a clear basis is provided for subsequent control responses, so that the system can respond to different levels of agglomeration risks in a targeted manner; in short, the control management module realizes comprehensive management and optimization of the feed production process by combining risk assessment, intelligent response and automatic control solutions, thereby improving production efficiency, reducing production risks, and ensuring the consistency of feed production.

[0117] Example 6

[0118] Please refer to Figure 1 and Figure 2, specifically: a feed automated production control method, comprising the following steps,

[0119] Step 1: First, the raw material locking module will establish a human-computer interaction interface to obtain the composition and proportion of each raw material input by the operator, and monitor and register the density status of each component;

[0120] Step 2: After the feed is mixed, the automatic collection module uses several groups of sensors to collect and record the distribution status data of each component in the feed, and monitors and collects the mixing status data of the feed according to the total amount of feed to be produced to generate a feed data set;

[0121] Step 3: The component analysis module is used to evaluate the component distribution state coefficient Cfxs by using the relevant distribution state data information, and compare and analyze the component distribution state coefficient Cfxs with the preset state threshold L to determine whether the current feed mixing is in a qualified state;

[0122] Step 4: In addition, the comprehensive production evaluation module is used to summarize the content of each component to obtain the total component content Zhlz, and evaluate the stirring degree coefficient Jbxs according to the total component content Zhlz, and associate the stirring degree coefficient Jbxs with the component distribution state coefficient Cfxs to fit and calculate the agglomeration risk index Jkfx;

[0123] Step 5: Finally, the control management module compares and analyzes the agglomeration risk index Jkfx with the risk assessment threshold F to obtain the agglomeration level risk result and adopts the corresponding automatic control plan.

[0124] Example: A feed production plant of a certain company has introduced a feed automation production control system and method. The following is an example of a feed production plant of a certain company:

[0125] Data collection: The density value of the fifth component Cfmd5 is 23; the average value of the sum of the density values ​​of each component is 15; the number of raw materials in the feed is 9; the resistivity Dzlz is 13; the eddy current intensity Wlqd is 24; the centrifugal force value Lxlz is 10; F1 is 0.16; F2 is 0.18; F3 is 0.10; F4 is 0.22; B is 0.91; the total component content Zhlz is 125; the stirrer spacing Jqjj is 6; the stirring time Jscz is 24; the stirring speed Jsdz is 36; a1 is 0.26; a2 is 0.06; a3 is 0.11; a4 is 0.08; C is 0.82; the temperature difference Wdc is 26; the humidity value Sdz is 23; j is 0.25; c is 0.20; w is 0.06; s is 0.12; R is 0.12;

[0126] With the above data, the following calculations can be performed:

[0127] Density standard deviation

[0128] Component distribution state coefficient

[0129] If the state threshold L is 20, the component distribution state coefficient Cfxs is lower than the state threshold L, that is, Cfxs<L, indicating that the current feed mixing is in an unqualified state;

[0130] Agitation coefficient

[0131] Agglomeration risk index

[0132] If the first evaluation threshold K1 is 20 and the second evaluation threshold K2 is 15, when the agglomeration risk index Jkfx ≤ the second evaluation threshold K2, it indicates that the agglomeration situation in the current feed is in an abnormal state, and the first result report is produced; at this time, the response unit will issue a red warning notification to remind the operator that there is a agglomeration problem in the current feed, and control the current feed to enter the next link to avoid rework in the later stage.

[0133] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A feed automated production control system, characterized in that: It includes raw material locking module, automatic collection module, component analysis module, comprehensive production evaluation module and control management module; The raw material locking module is used to establish a human-computer interaction interface, from which the composition and proportion of each raw material input by the operator are obtained, and the density status of each component is monitored and registered; The automatic collection module is used to collect and record the relevant distribution status data information of each component in the feed by using several groups of sensors after the feed mixing operation, and monitor and collect the relevant mixing status data information of the feed according to the total amount of feed to be produced, and generate the feed data set after dimensionless processing; The component analysis module is used to extract features using relevant distribution state data information to obtain resistivity Dzlz and eddy current intensity Wlqd to evaluate the component distribution state coefficient Cfxs, and compare and analyze the component distribution state coefficient Cfxs with a preset state threshold L to determine whether the current feed mixing is in a qualified state; The comprehensive production evaluation module is used to summarize the content of each component to obtain the total component content Zhlz, and evaluate the stirring degree coefficient Jbxs according to the total component content Zhlz, and associate the stirring degree coefficient Jbxs with the component distribution state coefficient Cfxs, and after dimensionless processing, fit and calculate the agglomeration risk index Jkfx; The control management module is used to pre-set a risk assessment threshold F, and compare and analyze the agglomeration risk index Jkfx with the risk assessment threshold F to obtain an agglomeration level risk result, and adopt a corresponding automatic control plan based on the agglomeration level risk result.

2. A feed automated production control system according to claim 1, characterized in that: The raw material locking module includes a component information unit and a component summary unit; The ingredient information unit is used to store and record detailed information of each raw material ingredient in the feed, including name, origin, content and density, and to identify and track the attributes of each raw material; The component summary unit is used to summarize and count the overall information of all raw material components in the feed, including the total content of each component, the humidity of each component and the density value of each component, and marked as the first component density value Cfmd1, the second component density value Cfmd2, ..., the Nth component density value Cfmd N , summary forms include generating reports, providing production statistics, and assisting in recipe adjustments.

3. A feed automated production control system according to claim 2, characterized in that: The automatic acquisition module includes a distribution data unit and a stirring data unit; The feed data set includes relevant distribution status data information and relevant stirring status data information; The distribution data unit is used to collect relevant distribution status data information of each component in the feed, including resistivity Dzlz, eddy current intensity Wlqd, centrifugal force value Lxlz, first component density value Cfmd1, second component density value Cfmd2, ..., Nth component density value Cfmd N And the convection case, wherein the first component density value Cfmd1, the second component density value Cfmd2, ..., the Nth component density value Cfmd N Perform statistical averaging to obtain the average value of the sum of the density values ​​of each component The stirring data unit is used to collect relevant stirring condition data information of the feed during the stirring process, including the stirring distance Jqjj, stirring time Jscz, stirring speed Jsdz, number of stirrers, stirrer angle and the distance between the stirrer and the inner wall of the stirring drum in the feed stirring equipment.

4. A feed automated production control system according to claim 3, characterized in that: The component analysis module includes a first analysis unit, a second analysis unit and an evaluation unit; The first analysis unit is used to obtain the density standard deviation value Mdcz by comprehensive analysis according to the number of component species Cfzs and the density value of each component. The density standard deviation value Mdcz is obtained by the following formula: Cfm i Expressed as the density value of the i-th component, It is expressed as the average value of the sum of the density values ​​of each component, and N is the number of raw material components in the feed.

5. A feed automated production control system according to claim 4, characterized in that: The second analysis unit is used to associate the resistivity Dzlz with the eddy current intensity Wlqd, and obtain the component distribution state coefficient Cfxs after dimensionless processing. The component distribution state coefficient Cfxs is obtained by the following formula: In the formula, Lxlz represents the centrifugal force value, F1, F2, F3 and F4 represent the preset proportional coefficients of resistivity Dzlz, eddy current intensity Wlqd, centrifugal force value Lxlz and density standard deviation value Mdcz respectively, and B represents the second correction constant.

6. A feed automated production control system according to claim 5, characterized in that: The evaluation unit is used to pre-set a state threshold L, and compare and analyze the component distribution state coefficient Cfxs with the state threshold L to determine whether the current feed mixing is in a qualified state; If the component distribution state coefficient Cfxs is higher than or equal to the state threshold L, that is, Cfxs ≥ L, it means that the current feed mixing is in a qualified state; If the component distribution state coefficient Cfxs is lower than the state threshold L, that is, Cfxs<L, it means that the current feed mixing is in an unqualified state.

7. The feed automated production control system according to claim 3, characterized in that: The total component content Zhlz is associated with the stirrer spacing Jqjj, and after dimensionless processing, the stirring degree coefficient Jbxs is obtained, and the stirring degree coefficient Jbxs is obtained by the following formula: In the formula, Jscz represents the stirring time, Jsdz represents the stirring speed, a1, a2, a3 and a4 represent the preset proportional coefficients of the total component content Zhlz, the stirrer spacing Jqjj, the stirring time Jscz and the stirring speed Jsdz respectively, and C represents the third correction constant.

8. The feed automated production control system according to claim 7, characterized in that: The agglomeration risk index Jkfx is obtained by the following formula: Wherein, Jbxs represents the stirring degree coefficient, Cfxs represents the component distribution state coefficient, Wdc represents the temperature difference, Sdz represents the humidity value, j, c, w and s represent the preset proportional coefficients of the stirring degree coefficient Jbxs, the component distribution state coefficient Cfxs, the temperature difference Wdc and the humidity value Sdz, respectively, and R represents the first correction constant; The control management module includes a control unit; The control unit is used to pre-set a risk assessment threshold F, wherein the risk assessment threshold F includes a first assessment threshold K1 and a second assessment threshold K2, and the first assessment threshold K1 is greater than the second assessment threshold K2, and the agglomeration risk index Jkfx is compared and analyzed with the risk assessment threshold F to obtain an agglomeration level risk result, wherein the specific content of the agglomeration level risk result is as follows: If the agglomeration risk index Jkfx ≤ the second evaluation threshold K2, it indicates that the agglomeration situation in the current feed is in an abnormal state, and a first result report is generated; If the second evaluation threshold value K2 is less than the agglomeration risk index Jkfx≤K1, it indicates that the agglomeration situation in the current feed is in a normal state, and a second result report is generated; If the first evaluation threshold K1 is less than the agglomeration risk index Jkfx, it indicates that the agglomeration situation in the current feed is normal, and a third result report is generated.

9. A feed automated production control system according to claim 8, characterized in that: The control management module also includes a response unit; The response unit is used to adopt corresponding automatic control schemes for the first result report, the second result report and the third result report, and the specific automatic control schemes are as follows: If it is the first result report, the response unit will issue a red warning notification to remind the operator that there is a caking problem in the current feed, and control the current feed to enter the next link to avoid rework in the later stage; If it is the second result report, the response unit will maintain the current state, but the feed status monitoring needs to be strengthened to ensure that potential abnormal conditions are discovered in time, and the preventive maintenance program is initiated to inspect and maintain the equipment to prevent subsequent agglomeration problems; If it is the third result report, the response unit will maintain the current state, strengthen the normal operation monitoring of the feed production process, and ensure production stability.

10. A feed automation production control method, comprising a feed automation production control system according to any one of claims 1 to 9, characterized in that: The following steps are included: Step 1: First, the raw material locking module will establish a human-computer interaction interface to obtain the composition and proportion of each raw material input by the operator, and monitor and register the density status of each component; Step 2: After the feed is mixed, the automatic collection module uses several groups of sensors to collect and record the distribution status data of each component in the feed, and monitors and collects the mixing status data of the feed according to the total amount of feed to be produced to generate a feed data set; Step 3: The component analysis module is used to evaluate the component distribution state coefficient Cfxs by using the relevant distribution state data information, and compare and analyze the component distribution state coefficient Cfxs with the preset state threshold L to determine whether the current feed mixing is in a qualified state; Step 4: In addition, the comprehensive production evaluation module is used to summarize the content of each component to obtain the total component content Zhlz, and evaluate the stirring degree coefficient Jbxs according to the total component content Zhlz, and associate the stirring degree coefficient Jbxs with the component distribution state coefficient Cfxs to fit and calculate the agglomeration risk index Jkfx; Step 5: Finally, the control management module compares and analyzes the agglomeration risk index Jkfx with the risk assessment threshold F to obtain the agglomeration level risk result and adopts the corresponding automatic control plan.

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