Intelligent control model and method for water balance of filter tank

Abstract

The invention discloses an intelligent control model and method for water balance of a filter tank, and relates to the technical field of beer brewing, and the method comprises the steps: 1, building fitting models for different brand formulas; 2, according to the fitting model, the first wort filtering amount is set in real time by combining the actual saccharified wort input amount and the actual hot coagulum input amount in real time; 3, according to the upper limit and the lower limit of the grain layer height, fitting the feeding amount through historical data to obtain the liquid level after filtering is completed; and 4, in order to ensure that the total filtering amount is unchanged, correspondingly modifying the use amount of the stillage washing water and subtracting the set value to ensure that the total recovery amount is unchanged. According to the invention, automatic deviation rectification is realized through combination of intelligent control of water balance of the filter tank and parameters of the previous process. And manual intervention is not needed, the operation efficiency of the filter tank is improved, and the on-site manual operation frequency is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of beer brewing, and in particular to an intelligent control model and method for water balance in a filter tank. Background Art

[0002] Beer is made by filtering the malt obtained from germinating barley, adding hops and fermenting it with yeast. The beer brewing process is generally divided into brewing procedure, fermentation procedure, pre-brewing treatment, pre-fermentation treatment and other process flows. In the process of making beer, it is necessary to use a model and method for intelligent control of the water balance of the filter tank to control the actual water input of the saccharification filter tank, the input of slop water, the amount of hot coagulant added and the first filtration amount, the second and weak wort recovery and other parameters.

[0003] The existing technology has the following problems: In the operation of the saccharification and filtration tank, the water balance mainly involves: the actual amount of water added in the previous process, the amount of water added to wash the slop, the amount of hot coagulant added, the amount of first-pass filtration, the recovery of the second and weak wort, etc. In the actual operation process, there may be problems such as inaccurate liquid level and hot coagulant addition measurement on site. In the traditional process control, if the water balance cannot be guaranteed, the risk of thin slop or dry slop layer will be reduced. Summary of the invention

[0004] The present invention provides a filter tank water balance intelligent control model and method to solve the problem of reducing the risk of thin slugs or slug layer drying due to failure to ensure water balance in traditional process control.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] An intelligent control model for water balance in a filter tank, which determines the amount of first wort filtered and the amount of slop water input according to the actual amount of water input in the previous process, the amount of hot coagulant input, and the liquid level during the filtration process, comprises the following steps:

[0007] Step 1: Establish fitting models for different brand formulas;

[0008] Among them, the input parameters are: the amount of mashed wort input, the amount of hot coagulant input, and the amount of first wort filtered; the fitting parameter is: the liquid level at the end of the first wort filtration; the first wort filtration amount set by the recipe itself is set aside, and the first wort filtration amount is calculated based on the actual water and material input conditions to form a fitting model;

[0009] Step 2: According to the fitting model, the first wort filtration amount is set in real time in combination with the actual amount of saccharified wort input and the amount of hot coagulant input;

[0010] Step 3: The upper and lower limits of the height of the slag layer can be obtained by fitting the feed amount through historical data to obtain the liquid level after filtration is completed;

[0011] Step 4: In order to ensure that the total filtration volume remains unchanged, the amount of slop washing water should be modified accordingly minus the set value to ensure that the total recovery volume remains unchanged.

[0012] Preferably, the step 1 includes the following:

[0013] A1: Calculate the initial liquid level:

[0014] i: Feed water / 11.3 plus the feed amount converted to the thickness of the slag layer, and then fit according to the liquid level before the first filtration to get a fitting liquid level 1;

[0015] ii: The amount of mash in the saccharification pot is adjusted to obtain a fitting liquid level 2;

[0016] iii: The liquid level at the beginning of filtration in the filter tank is obtained as liquid level 3;

[0017] The initial liquid level of a filter tank is obtained by averaging or medianing the liquid level 1, liquid level 2, and liquid level 3;

[0018] A2: Calculate the amount of first wort filtered;

[0019] Calculation method:

[0020] Where r is the inner diameter of the filter tube.

[0021] Preferably, the step 2 includes the following:

[0022] B1: During the second wort filtration process, keep the total water flow rate unchanged:

[0023] When adding hot coagulant, the flow rate of the slop water is set to: the original setting value minus the hot coagulant addition rate;

[0024] When the hot coagulant is not added, the flow rate of the slop washing water is set to the original set speed;

[0025] B2: The addition rate of the hot coagulant is approximately 612h1 / h according to the historical data.

[0026] Preferably, if there is a problem with the record of feed water / feed amount, the median of the other two liquid levels is used as the initial liquid level.

[0027] A method for intelligently controlling water balance in a filter tank, according to the liquid level at the beginning of filtering and the set first wort filtering amount, calculates the liquid level after the first wort filtering is completed, thereby adjusting the first wort filtering amount and the amount of slop washing water; if it is judged that the liquid level after the first wort is completed is low, then the first wort filtering amount needs to be reduced accordingly, and the amount of slop washing water input needs to be increased at the same time; the method for intelligently controlling water balance in a filter tank includes the following:

[0028] S1: Record the amount of water dosage set value and actual value of the previous process: When the filter tank starts filtering, the difference between the actual value of the above water volume and the formula set value can be calculated:

[0029] The deviation of water dosage in the previous process is equal to the actual water dosage minus the formula setting value.

[0030] Correction of water dosage deviation in the previous process;

[0031] S2: During the first wort filtration, confirm whether to add heat coagulant;

[0032] S3: First step: confirm the recommended filtration volume;

[0033] S4: first pass end condition;

[0034] S5: Filtration of washed slop wort: confirm the amount of slop water to be added.

[0035] Preferably, the S1 includes the following:

[0036] S11: If the water injection step is repeatedly executed and there are multiple water injection records, the water injection amount deviation of the previous process is set to zero. For the subsequent various filtration amount settings, the model recommended values ​​will follow the system set values;

[0037] S12: If the absolute value is greater than 100, the water dosage deviation of the previous process is equal to zero, and the model recommended value for the subsequent various filtration volume settings will follow the system setting value;

[0038] S13: If the absolute value (deviation of water dosage in the preceding process) is less than five, then the deviation of water dosage in the preceding process is equal to zero.

[0039] Preferably, S2 includes the following:

[0040] S21: Confirm whether to add hot coagulant: When the first wort is filtered and the filtration volume is greater than 260hl, check the sequence chain of the current hot coagulant tank. If it is in the waiting step (EOP3100), add it. If it is not waiting, do not heat the coagulant in this pot to ensure the controllability of the water volume;

[0041] S22: Confirm the amount of thermal coagulant added:

[0042] If according to step 1, when the filter tank starts filtering: it is determined that the thermocoagulant can be added, then the amount of thermocoagulant added is equal to the liquid level of the thermocoagulant tank;

[0043] If according to step 1, when the filtration tank starts filtering: it is determined that no thermocoagulant is to be added, then the amount of thermocoagulant added is equal to zero.

[0044] Preferably, S3 includes the following:

[0045] The model recommended value of the first wort volume is equal to the PLC setting value of the first wort volume plus a relatively large value;

[0046] The deviation value of the washing water volume is equal to the deviation of the water volume in the previous process minus the actual amount of heated coagulant added set in the formula;

[0047] Among them: the actual amount of hot coagulant added will be updated to the actual value after the hot coagulant is added.

[0048] Preferably, S4 includes the following:

[0049] The pressure difference is less than 70mbar and the liquid level is less than 23cm: the first filtration is ended directly;

[0050] The model recommended value for the first wort volume is equal to the current first filter volume.

[0051] Preferably, the S5 includes the following:

[0052] The deviation value of the washing water volume is equal to the deviation of the water volume in the previous process minus the actual amount of hot coagulant added set in the formula; among which, the actual amount of hot coagulant added will be updated to the actual value after the addition of hot coagulant is completed; the model recommended value of the washing water volume is equal to the PLC setting value of the washing water volume minus the deviation value of the washing water volume.

[0053] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0054] 1. The present invention provides a model and method for intelligent control of water balance in a filter tank. The intelligent control of water balance in the filter tank combines the parameters of the previous process to automatically correct the deviation and ensure water balance. It eliminates abnormalities without manual intervention. It improves the operating efficiency of the filter tank and reduces the frequency of manual operation on site. It solves the problem of reducing the risk of thin slop or drying up the slop layer due to the inability to ensure water balance in traditional process control.

[0055] 2. The present invention provides an intelligent control model and method for water balance in a filter tank, which dynamically monitors the liquid level, sets upper and lower limits, and avoids drying of the slag layer.

[0056] 3. The present invention provides a model and method for intelligent control of water balance in a filter tank to ensure total recovery. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 Schematic diagram of intelligent control of water balance in filter tank according to the present invention Figure 1 ;

[0058] Figure 2 Schematic diagram of intelligent control of water balance in filter tank according to the present invention Figure 2 ;

[0059] Figure 3 It is a schematic diagram of the equipment and step numbers of the present invention;

[0060] Figure 4 This is the liquid level 1 model of the present invention: a schematic diagram of the liquid level fitting of the feed amount converted into liquid level;

[0061] Figure 5 This is a schematic diagram of the liquid level 2 model of the present invention: the liquid level fitting of the mash inlet into the saccharification pot. DETAILED DESCRIPTION

[0062] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0063] like Figure 1 and Figure 2 As shown, a water balance intelligent control model for a filter tank is used to determine the first wort filtration amount and the amount of slop washing water input according to the actual water input amount of the previous process, the amount of hot coagulant input, and the liquid level during the filtration process, including the following steps:

[0064] Step 1: Establish fitting models for different brand recipes: Input parameters: amount of mashed wort, amount of hot coagulant, first wort filtration amount (control variable); Fitting parameter: liquid level at the end of first wort filtration; Ignore the first wort filtration amount set by the recipe itself, and calculate the first wort filtration amount based on the actual water and material input conditions to form a fitting model;

[0065] Step 2: According to the fitting model, the first wort filtration amount is set in real time in combination with the actual saccharification wort input amount and the hot coagulant input amount to ensure that the liquid level does not exceed the upper and lower limits after the first wort is filtered;

[0066] Step 3: The upper and lower limits of the height of the slag layer can be obtained by fitting the feed amount through historical data to obtain the liquid level after filtration is completed;

[0067] Step 4: In order to ensure that the total filtration volume remains unchanged, the amount of slop water used - set value should be modified accordingly to ensure the total recovery volume.

[0068] It should be noted that Figure 4This is the liquid level 1 model of the present invention: a schematic diagram of the liquid level fitting of the feed amount converted into liquid level; Figure 5 This is a schematic diagram of the liquid level 2 model of the present invention: the liquid level fitting of the mash inlet into the saccharification pot.

[0069] Optional, combined Figure 4 and Figure 5 As shown, the above step 1 includes the following:

[0070] A1: Calculate the initial liquid level:

[0071] i: Feed water / 11.3 plus the feed amount converted to the thickness of the slag layer, and then fit according to the liquid level before the first filtration to get a fitting liquid level 1;

[0072] ii: The amount of mash in the saccharification pot is adjusted to obtain a fitting liquid level 2;

[0073] iii: The liquid level at the beginning of filtration in the filter tank is obtained as liquid level 3;

[0074] The initial liquid level of a filter tank is obtained by averaging or medianing the liquid level 1, liquid level 2, and liquid level 3;

[0075] Note: If there is a problem with the feed water / feed amount record, use the median of the other two liquid levels as the initial liquid level;

[0076] A2: Calculate the first wort filtration volume (excluding thermal coagulants)

[0077] Calculation method: (initial liquid level - 4.5cm (false bottom height) - feed amount converted to slag layer height) * 11.3

[0078]

[0079] Where r is the inner diameter of the filter tube.

[0080] Optionally, step 2 includes the following:

[0081] B1: During the second wort filtration process, keep the total water flow rate unchanged:

[0082] When adding hot coagulant, the flow rate of the slop water is set to: the original setting value minus the hot coagulant addition rate;

[0083] When the hot coagulant is not added, the flow rate of the slop washing water is set to the original set speed;

[0084] B2: The addition rate of the hot coagulant is approximately 612h1 / h according to the historical data.

[0085] like Figure 3As shown, a method for intelligently controlling water balance in a filter tank is provided. According to the liquid level at the beginning of filtering and the set filtering amount of the first wort, we can calculate the liquid level after the filtering of the first wort is completed, so as to adjust the filtering amount of the first wort and the amount of water for washing the slops; if it is judged that the liquid level after the first wort is completed is low, then it is necessary to reduce the filtering amount of the first wort accordingly, and at the same time increase the amount of water for washing the slops; the method for intelligently controlling water balance in a filter tank includes the following:

[0086] S1: Record the amount of water dosage set value and actual value of the previous process: When the filter tank starts filtering, the difference between the actual value of the above water volume and the formula set value can be calculated:

[0087] water_diff (deviation of water dosage in the previous process) = water_real (actual water dosage) - water_set (recipe setting value), that is, the difference in water dosage in the previous process can be obtained;

[0088] S2: During the first wort filtration, confirm whether to add heat coagulant;

[0089] S3: First step: confirm the recommended filtration volume;

[0090] S4: first pass end condition;

[0091] S5: Filtration of washed slop wort: confirm the amount of slop water to be added.

[0092] The above S1 specifically includes the following:

[0093] S11: If the water injection step is repeatedly executed and there are multiple water injection records, it is currently considered to be abnormal data. Set water_diff (the amount of water injected in the previous process) = None (zero). For the subsequent various filtration amount settings, the model recommended value will follow the system set value, that is, if the online formula is modified, the model recommended value will follow the modified value;

[0094] S12: abs (absolute value) (water_diff water injection deviation of the previous process) is greater than 100; 100hl is used as the upper and lower limits of protection. If the limit is exceeded, it is considered that a program abnormality has occurred.

[0095] When water_diff (the amount of water added in the previous process) = None (zero), for the subsequent various filtration amount settings, the model recommended values ​​will follow the system set values, that is, if the online formula is modified, the model recommended values ​​will follow the modified values.

[0096] S13: If abs (absolute value) (water_diff, the deviation of water volume in the previous process) is less than 5, then water_diff (the deviation of water volume in the previous process) is equal to 0, which means that no modification is performed by default.

[0097] The above S2 specifically includes the following:

[0098] S21: Confirm whether to add hot coagulant: When the first wort is filtered and the filtration volume is greater than 260hl (the value set in the recipe), check the sequence chain of the current hot coagulant tank. If it is in the wait step (EOP3100), add it. If it is not in the wait step, the coagulant will not be heated in this pot to ensure the controllability of the water volume;

[0099] At this time, the signal of whether to add hot coagulant is given by the box: the instruction of whether to add hot coagulant.

[0100] S22: confirm the amount of thermal coagulant added: trub_add_vol;

[0101] If according to step 1, when the filter tank starts filtering: it is determined that thermocoagulant can be added, then trub_add_vol (thermocoagulant addition amount) is equal to the liquid level of the thermocoagulant tank;

[0102] If according to step 1, when the filtration tank starts filtering: it is determined that no thermocoagulant is to be added, then trub_add_vol (amount of thermocoagulant added) is equal to zero.

[0103] The above S3 includes the following:

[0104] first_wort_qty_RCMD (first wort quantity model recommended value) is equal to first_wort_qty_set (first wort quantity PLC set value) plus 40 (relatively large value);

[0105] diff_vol (the deviation of the washing water volume) is equal to water_diff (the deviation of the water volume in the previous process) minus 80 (the amount of hot coagulant added set in the formula) plus trub_add_vol (the actual amount of hot coagulant added);

[0106] Ps: trub_add_vol (actual amount of hot coagulant added) will be updated to the actual value after the hot coagulant is added.

[0107] The above S4 includes the following:

[0108] The pressure difference is less than 70mbar and the liquid level is less than 23cm: the first filtration is ended directly;

[0109] first_wort_qty_RCMD (first wort quantity model recommended value) is equal to the current first filtration volume.

[0110] The above S5 includes the following:

[0111] diff_vol (the deviation of the washing water volume) is equal to water_diff (the deviation of the water volume in the previous process) minus 80 (the amount of hot coagulant added set in the formula) plus trub_add_vol (the actual amount of hot coagulant added);

[0112] Ps: trub_add_vol will be updated to the actual value after the addition of hot coagulant is completed;

[0113] second_wort_qty_RCMD (model recommended value for the amount of wash water) is equal to second_wort_qty_set (PLC set value for the amount of wash water) minus diff_vol (deviation value for the amount of wash water).

[0114] The intelligent control of the water balance of the filter tank is combined with the parameters of the previous process to automatically correct deviations, ensure water balance, and eliminate abnormalities without manual intervention. It improves the operating efficiency of the filter tank and reduces the frequency of on-site manual operations, thereby solving the problem of reducing the risk of thinning the mash or drying up the mash layer due to the inability to ensure water balance in traditional process control. According to the liquid level at the beginning of filtration and the set first wort filtration volume, the liquid level after the first wort filtration is completed can be calculated, so as to adjust the first wort filtration volume and the mash washing water volume. If it is judged that the liquid level after the first wort is completed is low, then it is necessary to reduce the first wort filtration volume accordingly and increase the mash washing water input at the same time.

[0115] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An intelligent control model for water balance in a filter tank, which determines the amount of first wort filtered and the amount of slop water input according to the actual amount of water input in the previous process, the amount of hot coagulant input, and the liquid level during the filtration process, and is characterized in that: The following steps are involved: Step 1: Establish fitting models for different brand formulas; Among them, the input parameters are: the amount of mashed wort input, the amount of hot coagulant input, and the amount of first wort filtered; the fitting parameter is: the liquid level at the end of the first wort filtration; the first wort filtration amount set by the recipe itself is set aside, and the first wort filtration amount is calculated based on the actual water and material input conditions to form a fitting model; Step 2: According to the fitting model, the first wort filtration amount is set in real time in combination with the actual amount of saccharified wort input and the amount of hot coagulant input; Step 3: According to the upper and lower limits of the slag layer height, the liquid level after filtration can be obtained by fitting the feed amount through historical data; Step 4: In order to ensure that the total filtration volume remains unchanged, the amount of slop washing water should be modified accordingly minus the set value to ensure that the total recovery volume remains unchanged.

2. The intelligent control model for water balance in a filter tank according to claim 1, characterized in that: The step 1 includes the following: A1: Calculate the initial liquid level: i: Feed water / 11.3 plus the feed amount converted to the thickness of the slag layer, and then fit according to the liquid level before the first filtration to get a fitting liquid level 1; ii: The amount of mash in the saccharification pot is adjusted to obtain a fitting liquid level 2; iii: the liquid level at the beginning of filtration in the filter tank, and then the liquid level 3 is obtained; The initial liquid level of a filter tank is obtained by averaging or medianing the liquid level 1, liquid level 2, and liquid level 3; A2: Calculate the amount of first wort filtered; Calculation method: Where r is the inner diameter of the filter tube.

3. The intelligent control model for water balance in a filter tank according to claim 1, characterized in that: The second step includes the following: B1: During the second wort filtration process, keep the total water flow rate unchanged: When adding hot coagulant, the flow rate of the slop water is set to: the original setting value minus the hot coagulant addition rate; When the hot coagulant is not added, the flow rate of the slop washing water is set to the original set speed; B2： The addition rate of the hot coagulant is fitted according to historical data and is 612hl / h.

4. The intelligent control model for water balance in a filter tank according to claim 2, characterized in that: If there is a problem with the record of feed water / feed amount, use the median of the other two liquid levels as the initial liquid level.

5. A method for intelligent control of water balance in a filter tank, based on an intelligent control model for water balance in a filter tank as described in any one of claims 1 to 4: according to the liquid level at the beginning of filtration and the set first wort filtration volume, the liquid level after the first wort filtration is completed is calculated, so as to adjust the first wort filtration volume and the amount of slop water; if it is judged that the liquid level after the first wort is completed is low, then it is necessary to reduce the first wort filtration volume accordingly, and at the same time increase the amount of slop water input; it is characterized in that The intelligent control method for filter tank water balance includes the following: S1: Record the amount of water dosage set value and actual value of the previous process: When the filter tank starts filtering, the difference between the actual value of the above water volume and the formula set value can be calculated: The deviation of water dosage in the previous process is equal to the actual water dosage minus the formula setting value. Correction of water dosage deviation in the previous process; S2: During the first wort filtration, confirm whether to add hot coagulant; S3: First step: confirm the recommended filtration volume; S4: first pass end condition; S5: Filtration of washed slop wort: confirm the amount of slop water to be added.

6. The method for intelligent control of water balance in a filter tank according to claim 5, characterized in that: The S1 includes the following: S11: If the water injection step is repeatedly executed and there are multiple water injection records, the water injection amount deviation of the previous process is set to zero. For the subsequent various filtration amount settings, the model recommended values ​​will follow the system set values; S12: If the absolute value is greater than 100, the water dosage deviation of the previous process is equal to zero, and the model recommended value for the subsequent various filtration volume settings will follow the system setting value; S13: If the absolute value is less than five, then the water dosage deviation of the previous process is equal to zero.

7. The intelligent control method for water balance in a filter tank according to claim 5, characterized in that: The S2 includes the following: S21: Confirm whether to add hot coagulant: When the first wort is filtered and the filtration volume is greater than 260hl, check the sequence chain of the current hot coagulant tank. If it is in the waiting step, add it. If it is not waiting, do not heat the coagulant in this pot to ensure the controllability of the water volume; S22: Confirm the amount of thermal coagulant added: If according to step 1, when the filter tank starts filtering: it is determined that the thermocoagulant can be added, then the amount of thermocoagulant added is equal to the liquid level of the thermocoagulant tank; If according to step 1, when the filtration tank starts filtering: it is determined that no thermocoagulant is to be added, then the amount of thermocoagulant added is equal to zero.

8. The intelligent control method for water balance in a filter tank according to claim 5, characterized in that: The S3 includes the following: The model recommended value of the first wort volume is equal to the PLC setting value of the first wort volume plus a relatively large value; The deviation value of the washing water volume is equal to the deviation of the water volume in the previous process minus the actual amount of heated coagulant added set in the formula; The actual amount of the thermal coagulant added will be updated to the actual value after the addition of the thermal coagulant is completed.

9. The intelligent control method for water balance in a filter tank according to claim 5, characterized in that: The S4 includes the following: The pressure difference is less than 70mbar and the liquid level is less than 23cm: the first filtration is ended directly; The model recommended value for the first wort volume is equal to the current first filter volume.

10. The intelligent control method for water balance in a filter tank according to claim 5, characterized in that: The S5 includes the following: The deviation value of the washing water volume is equal to the deviation of the water volume in the previous process minus the actual amount of heated coagulant added set in the formula; Among them, the actual amount of hot coagulant added will be updated to the actual value after the addition of the hot coagulant is completed; the model recommended value of the washing trough water volume is equal to the washing trough water volume PLC setting value minus the washing trough water volume deviation value.

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