CN116910439A - Charging capability estimation method, device, equipment and storage medium - Google Patents

Charging capability estimation method, device, equipment and storage medium Download PDF

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CN116910439A
CN116910439A CN202310828383.0A CN202310828383A CN116910439A CN 116910439 A CN116910439 A CN 116910439A CN 202310828383 A CN202310828383 A CN 202310828383A CN 116910439 A CN116910439 A CN 116910439A
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tobacco leaf
fitting
feeding
feed liquid
fitting model
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葛托
王要飞
韩伟
张兵
郭硕达
崔庆育
张福新
于振江
李晨曦
李高阳
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Shanghai Tobacco Group Co Ltd
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Abstract

The invention provides a feeding capacity prediction method, a device, equipment and a storage medium, wherein the method comprises the steps of acquiring sample data of different types of feed liquid in a tobacco leaf feeding machine in different working stages; respectively fitting sample data in different working stages by taking sample data of the same type of feed liquid as a unit to obtain a first fitting model and a second fitting model, and further determining a flow difference curve; determining an estimated feed flow of the feed pump based on the first fitting model; and determining to adopt a first fitting model or estimate the charging capacity according to the actual measured flow value and the flow difference based on whether the difference between the estimated charging flow and the actual charging flow is within a preset threshold range. According to the method, the feeding capacity of the tobacco leaf feeding machine is estimated, so that the feeding capacity of the tobacco leaf feeding machine meets the requirements of a normal production stage, the stop production is reduced, the times of checking the tobacco leaf feeding machine are reduced, the feeding flow of the production stage is monitored, and the hidden danger of quality risks is reduced.

Description

Charging capability estimation method, device, equipment and storage medium
Technical Field
The invention relates to the technical field of tobacco production, in particular to a method, a device, equipment and a storage medium for estimating charging capability.
Background
At present, a drum-type feeder is adopted in a tobacco shred making workshop to feed tobacco leaves, feed liquid flows out from a feeding drum and is filtered by a filter, flow is controlled by a feeding pump, and finally the feed liquid is atomized and sprayed out through a feeding nozzle and uniformly sprayed onto the tobacco leaves to realize accurate feeding.
The corresponding viscosity of the feed liquid of different types is different, which may cause the unsmooth feeding pipeline or the blockage of the tobacco leaf feeding machine. The feeding pipeline is abnormal, such as breakage, liquid leakage and the like, so that the feeding precision is affected to a certain extent, and the actual feeding flow of the tobacco leaf feeding machine can not meet the actual production requirement. However, in the existing method for estimating the capability of the charging pipeline of the temporary smokeless leaf charging machine, if the charging flow rate in the production process does not meet the charging flow rate actually required, the problem of stopping and checking can be solved.
Therefore, the feeding capacity of the tobacco leaf feeding machine is estimated in advance, and the situation that the feeding flow cannot meet the requirement in the feeding process in the production stage is prevented, so that the technical problem to be solved in the industry is urgently needed.
Disclosure of Invention
Aiming at the technical problems in the prior art, the invention provides a feeding capacity estimating method, a device, equipment and a storage medium.
In a first aspect, the present invention provides a method for estimating charging capability, including:
acquiring sample data of different types of feed liquid in a tobacco leaf feeding machine in different working stages, wherein the sample data comprise the working frequency of a feeding pump and flow values corresponding to the feeding pump when feeding the feed liquid in different types under the working frequency; the different working phases comprise a pre-filling phase and a production phase;
respectively fitting the corresponding relation between the feed pump frequency and the feed liquid flow of the tobacco leaf feeding machine in different working phases by taking sample data corresponding to the feed liquid of the same type as a unit to obtain a first fitting model and a second fitting model;
determining a flow difference curve based on the first fitting model and the second fitting model; the flow difference curve is used for representing the difference value of the feed liquid flow in different working stages of the tobacco leaf feeder under the same feeding pump frequency;
determining the estimated feed liquid flow of a feed pump in the tobacco leaf feeding machine in a pre-filling stage based on the first fitting model;
determining whether the difference value between the estimated feed liquid flow of the feed pump and the actual feed liquid flow of the feed pump is within a preset threshold range;
If the feeding capacity is within the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the working frequency range of a feeding pump in the tobacco leaf feeding machine and the first fitting model;
if the flow difference curve is not in the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the actual feed liquid flow extreme value acquired by the feeding pump in the tobacco leaf feeding machine when the working frequency is limited at the upper and lower limits and the flow difference value corresponding to the flow difference curve when the working frequency is limited at the upper and lower limits.
Optionally, the fitting is performed on the corresponding relationship between the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in different working phases by taking sample data corresponding to the same type of feed liquid as a unit, so as to obtain a first fitting model and a second fitting model, including:
based on linear fitting, respectively determining linear fitting relations of the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in a pre-filling stage and a production stage, and taking the linear fitting relations as a first linear fitting model and a second linear fitting model;
based on a least square method, respectively determining fitting quadratic curves of the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in a pre-filling stage and a production stage, and taking the fitting quadratic curves as a first curve fitting model and a second curve fitting model;
Determining, based on a first rule, the first linear fitting model or the first curve fitting model as a first fitting model at a pre-fill stage;
determining, based on a first rule, the second linear fitting model or the second curve fitting model as a second fitting model at a production stage;
the first rule is to target minimum computational complexity and deviation, and a linear fitting model is preferentially selected.
Optionally, the fitting quadratic curves of the feeding pump frequency and the feed liquid flow rate of the tobacco leaf feeding machine in the pre-filling stage and the production stage are respectively determined based on a least square method and used as a first curve fitting model and a second curve fitting model, and the fitting quadratic curves comprise:
based on a fitting rule, respectively determining a fitting quadratic curve in a pre-filling stage and a fitting quadratic curve in a production stage to serve as a first curve fitting model and a second curve fitting model;
the fitting rule includes:
setting a fitting quadratic curve equation and a fitting objective function;
taking the minimum fitting objective function as a target, and combining sample data corresponding to the feed liquid of the same type, and determining the value of each coefficient of the fitting conic equation under the condition that the derivative of the fitting objective function on each coefficient of the fitting conic equation is zero;
And determining a fitting quadratic curve corresponding to the tobacco leaf feeder based on the values of the coefficients of the fitting quadratic curve equation and the set fitting quadratic equation.
Optionally, the estimating, based on the operating frequency range of the feeding pump in the tobacco feeding machine and the first fitting model, the corresponding feeding capacity of the tobacco feeding machine includes:
and determining the maximum value and the minimum value of the feed liquid flow corresponding to the first fitting model in the working frequency range of the feed pump, and taking the maximum value and the minimum value as the predicted value of the feed capacity corresponding to the tobacco leaf feeding machine.
Optionally, the method further comprises:
determining an expected feed flow rate of the different types of feed liquids in a tobacco leaf feeder during a production stage;
determining a pre-judging operation adopted for the tobacco leaf feeding machine based on the magnitude relation between the pre-estimated value of the feeding capacity of the tobacco leaf feeding machine and the actual required value; the actual demand value is the product of the expected charging flow and a preset adjustment value; the preset adjustment value is larger than 1 and smaller than 2.
Optionally, the determining the pre-determining operation to be performed on the tobacco leaf feeding machine based on the magnitude relation between the pre-determined value of the feeding capacity of the tobacco leaf feeding machine and the actual required value comprises:
If the predicted value of the feeding capacity of the tobacco leaf feeding machine is larger than or equal to the actual required value, the tobacco leaf feeding machine normally enters a production stage;
and if the predicted value of the feeding capacity of the tobacco leaf feeding machine is smaller than the actual required value, cleaning a feeding pipeline of the tobacco leaf feeding machine.
Optionally, the preset adjustment value is determined according to liquid resistances corresponding to different types of liquid.
Optionally, the flow value corresponding to the feeding of the feed liquid with different types by the feeding pump is obtained by a flowmeter in the feeding pump.
In a second aspect, the present invention also provides a feeding capacity estimating apparatus, including:
the acquisition module is used for acquiring sample data of different types of feed liquid in the tobacco leaf feeding machine in different working stages, wherein the sample data comprise the working frequency of a feeding pump and flow values corresponding to the feeding pump when feeding the feed liquid in different types under the working frequency; the different working phases comprise a pre-filling phase and a production phase;
the fitting module is used for respectively fitting the corresponding relation between the feeding pump frequency of the tobacco leaf feeding machine and the flow of the feed liquid in different working phases by taking sample data corresponding to the feed liquid of the same type as a unit to obtain a first fitting model and a second fitting model;
The difference module is used for determining a flow difference curve based on the first fitting model and the second fitting model; the flow difference curve is used for representing the difference value of the feed liquid flow in different working stages of the tobacco leaf feeder under the same feeding pump frequency;
the first determining module is used for determining the estimated feed liquid flow of the feed pump in the tobacco leaf feeding machine in the pre-filling stage based on the first fitting model;
the second determining module is used for determining whether the difference value between the estimated feed liquid flow of the feed pump and the actual feed liquid flow of the feed pump is within a preset threshold range;
the first estimating module is used for estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the working frequency range of the feeding pump in the tobacco leaf feeding machine and the first fitting model if the first estimating module is in the preset threshold range;
and the second estimating module is used for estimating the corresponding feeding capacity of the tobacco leaf feeder based on the actual feed liquid flow extreme value acquired by the feeding pump in the tobacco leaf feeder when the working frequency is limited at the upper and lower limits and the flow difference value corresponding to the flow difference curve when the working frequency is limited at the upper and lower limits if the flow difference value is not in the preset threshold range.
In a third aspect, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements any of the methods for estimating the charging capability described above when executing the program.
In a fourth aspect, the present invention also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of estimating charging capacity as described in any of the above.
In a fifth aspect, the present invention also provides a computer program product comprising a computer program which, when executed by a processor, implements a method of estimating charging capacity as described in any of the above.
According to the charging capacity estimating method, device, equipment and storage medium, the obtained sample data of the tobacco charging machine in different working stages are fitted, the first fitting model and the second fitting model are determined, the charging capacity of the tobacco charging machine is estimated by using the first fitting model and/or the second fitting model, the charging capacity of the tobacco charging machine is ensured to meet the requirements of a normal production stage, the stop of production is reduced, the times of checking the tobacco charging machine are reduced, the charging flow of the production stage is monitored, and the quality risk hidden danger is reduced.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for estimating charging capacity according to the present invention;
FIG. 2 is a schematic diagram of the workflow of the tobacco leaf feeder provided by the invention;
FIG. 3 is a schematic view of a device for estimating charging capacity according to the present invention;
fig. 4 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The charging capability estimation method, device, equipment and storage medium of the present invention are described below with reference to fig. 1 to 4.
The tobacco leaf feeding process is a technological process of adding different types of feed liquid on tobacco leaf in the cigarette production process, wherein the different feed liquid has different tastes, and the feeding purpose is to improve the flavor characteristics of the cigarette product and cover miscellaneous gases and set off fragrance. The taste of the cigarettes can be enriched and corrected by the treatment of the feeding technology, and the taste of the cigarettes can be kept stable and unchanged. Along with the reduction of cigarette tar and the use of cut stems and slices, the taste of cigarettes needs to be supplemented by feeding. In addition, the feeding material can also endow cigarettes with different aroma styles, and meets the demands of vast consumers. The feeding is an important process for producing cigarettes, and can reduce the components of harmful substances such as tar in cigarettes on the basis of not affecting the original flavor of the cigarettes.
Fig. 1 is a schematic flow chart of a method for estimating charging capability, provided by the invention, as shown in fig. 1, the method can be applied to a tobacco charging machine, and comprises the following steps:
step 101, acquiring sample data of different types of feed liquid in a tobacco leaf feeder in different working stages, wherein the sample data comprise the working frequency of a feed pump and flow values corresponding to the feed pump when feeding the different types of feed liquid is adopted by the feed pump under the working frequency; the different working phases comprise a pre-filling phase and a production phase;
Specifically, the working flow of the tobacco leaf feeding machine specifically comprises a pre-filling stage and a production stage, fig. 2 is a schematic diagram of the working flow of the tobacco leaf feeding machine provided by the invention, as shown in fig. 2, solid arrows represent the flow direction of feed liquid, and dotted arrows represent a control loop. In the pre-filling stage, the smoothness of a feeding pipeline in the tobacco leaf feeder is ensured, the actual feeding flow is monitored, and the feed liquid sequentially passes through a charging tank, a charging tank discharging valve, a filter, a flowmeter, a feeding pump, a pipeline feed back valve and a charging tank feed back valve and returns to the charging tank to finish the pre-filling of the pipeline before production, namely the pre-filling stage is finished. In the production stage, the feed liquid is sprayed on the materials sequentially through a feed tank, a feed tank discharge valve, a filter, a flowmeter, a feed pump and a feed valve-to-feed nozzle. The flowmeter is used for monitoring the corresponding flow value of the feed liquid in real time and controlling the working frequency (pump frequency) of the feed pump through the programmable logic controller. In the production stage, the working frequency (pump frequency) of the charging pump is controlled so as to meet the requirement of production charging.
In order to prolong the service life of the tobacco leaf charging machine, the tobacco leaf charging machine is not usually operated at a limiting frequency, namely a highest or lowest operating frequency, so that the actual charging capacity of the tobacco leaf charging machine, namely the maximum value and the minimum value of charging, is difficult to determine in the pre-filling stage. In the pre-filling stage, sample data of different types of feed liquid in a tobacco leaf feeding machine are firstly obtained, wherein the sample data are grouped by using the same type of feed liquid, and the sample data comprise corresponding flow values when feed liquid feeding pumps in the tobacco leaf feeding machine work at different frequencies.
Step 102, fitting corresponding relations between the feeding pump frequencies of the tobacco leaf feeding machines and the flow rates of the feed liquid in different working phases by taking sample data corresponding to the feed liquid of the same type as a unit to obtain a first fitting model and a second fitting model;
after the sample data corresponding to the different types of feed liquid in the tobacco leaf feeding machine are obtained, fitting the corresponding relation between the feeding pump frequency and the feed liquid flow rate of the tobacco leaf feeding machine in different working phases, and determining the fitting quadratic curve or the linear relation corresponding to the flow rate value and the pump frequency of the tobacco leaf feeding machine. For example, fitting is performed on sample data in a pre-filling stage to obtain a first fitting model, and fitting is performed on sample data in a production stage to obtain a second fitting model. For different types of feed liquid, different fitting quadratic curves or linear relations can be correspondingly achieved, namely when different feed liquids are adopted for processing the material by the same tobacco leaf feeding machine, corresponding maximum feeding values and minimum feeding values can be different and are related to liquid resistance of the feed liquid.
Step 103, determining a flow difference curve based on the first fitting model and the second fitting model; the flow difference curve is used for representing the difference value of the feed liquid flow in different working stages of the tobacco leaf feeder under the same feeding pump frequency;
And determining the difference between the feed liquid flow rate in the pre-filling stage and the feed liquid flow rate in the production stage at any feed pump frequency according to the first fitting model and the second fitting model determined by the method. The flow rate of the feed liquid obtained in the pre-filling stage in the actual production process is mainly reflected, and may be different from that in the actual production stage. The feed liquid flow obtained in the pre-filling stage can be adjusted through the difference value, so that a more accurate estimated value is obtained.
104, determining estimated feed liquid flow of a feed pump in the tobacco leaf feeder in a pre-filling stage based on the first fitting model;
and determining the estimated feed liquid flow of the feed pump based on the first fitting model corresponding to the pre-filling stage and the actually detected current frequency value of the feed pump of the tobacco leaf feeding machine in the pre-filling stage. That is, in an ideal state, the feed liquid flow of the feed pump of the tobacco leaf feeder is at the current frequency.
Step 105, determining whether a difference value between the estimated feed liquid flow of the feed pump and the actual feed liquid flow of the feed pump is within a preset threshold range;
the tobacco leaf feeding machine comprises a tobacco leaf feeding pump, a tobacco leaf feeding machine, a tobacco leaf feeding pump, a tobacco leaf feeding machine and a tobacco leaf feeding system, wherein a flowmeter is arranged in the feeding pump of the tobacco leaf feeding machine and is used for acquiring the actual feed liquid flow of the feeding pump in real time, comparing the actual feed liquid flow with the estimated feed liquid flow determined according to a first fitting model to determine whether the difference value of the actual feed liquid flow and the estimated feed liquid flow is within a preset threshold range, wherein the preset threshold can be set according to actual production requirements or process requirements, and dynamically adjusting in the production process.
Step 106, if the feeding capacity is within the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the working frequency range of the feeding pump in the tobacco leaf feeding machine and the first fitting model;
if the difference value between the actual feed liquid flow and the estimated feed liquid flow determined according to the first fitting model is determined to be within the preset threshold value range, the working state of the tobacco leaf feeding machine can be considered to be normal, and the condition that no obstacle for blocking the feed liquid flow exists in the tobacco leaf feeding machine or a pipeline for the feed liquid flow is smooth can be understood. In this case, the corresponding charging capacity of the tobacco charging machine may be estimated based on the first fitting model, and the extremum (maximum and minimum) of the operating frequency of the charging pump.
And 107, if the flow difference is not in the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the actual feed liquid flow extreme value acquired by the feeding pump in the tobacco leaf feeding machine when the working frequency is limited, and the flow difference value corresponding to the flow difference curve when the working frequency is limited.
If the difference between the actual feed liquid flow and the estimated feed liquid flow determined according to the first fitting model is not within the preset threshold value range, the working state of the tobacco leaf feeding machine can be considered to be abnormal, and the condition that the tobacco leaf feeding machine is provided with an obstacle for blocking the feed liquid flow or a pipeline for the feed liquid flow is not smooth can be understood. In this case, if the feeding capacity of the tobacco leaf feeding machine corresponding to the feeding capacity is estimated to be inaccurate based on the first fitting model and the extreme value (maximum value and minimum value) of the operating frequency of the feeding pump directly, the operating frequency of the feeding pump of the tobacco leaf feeding machine needs to be set to be close to the maximum value and the minimum value, the flow rate of the feed liquid when the operating frequency of the feeding pump is maximum and the flow rate of the feed liquid when the operating frequency of the feeding pump is minimum are obtained through the flowmeter arranged in the feeding pump, the flow rate of the feed liquid when the operating frequency of the feeding pump is maximum is determined based on the flow rate difference curve, the flow rate of the feed liquid corresponding to the maximum value of the operating frequency of the feeding pump and the flow rate of the feed liquid corresponding to the minimum value of the operating frequency are determined, and the maximum value and the minimum value of the feed liquid flow rate through the flow rate and the obtained feed liquid flow rate are corrected, and the estimated value of the feed capacity corresponding to the tobacco leaf feeding machine is obtained. Thereby making the final predicted value more accurate.
Based on the first fitting model, obtaining the distribution of flow values corresponding to the working frequency range of a feeding pump in the tobacco leaf feeding machine, and estimating the corresponding feeding capacity of the tobacco leaf feeding machine. Or according to the actual material flow value obtained by the flowmeter in the feeding pump and the difference value of the tobacco leaf feeding machine in the pre-filling stage and the production stage in the normal production process, the corresponding feeding capacity of the tobacco leaf feeding machine is estimated in advance, the corresponding feeding capacity of the tobacco leaf feeding machine can be flexibly estimated in advance, whether the feeding capacity of the tobacco leaf feeding machine can meet the corresponding requirement in the production stage can be further determined, the feeding capacity of the tobacco leaf feeding machine can be ensured in advance, and the feeding stage entering is smoother.
According to the feeding capacity estimating method provided by the invention, the feeding capacity of the tobacco leaf feeding machine is estimated, so that the feeding capacity of the tobacco leaf feeding machine meets the requirements of a normal production stage, the stop production is reduced, the times of checking the tobacco leaf feeding machine are checked, the feeding flow of the production stage is monitored, and the hidden danger of quality risks is reduced.
Optionally, the fitting is performed on the corresponding relationship between the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in different working phases by taking sample data corresponding to the same type of feed liquid as a unit, so as to obtain a first fitting model and a second fitting model, including:
Based on linear fitting, respectively determining linear fitting relations of the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in a pre-filling stage and a production stage, and taking the linear fitting relations as a first linear fitting model and a second linear fitting model;
based on a least square method, respectively determining fitting quadratic curves of the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in a pre-filling stage and a production stage, and taking the fitting quadratic curves as a first curve fitting model and a second curve fitting model;
determining, based on a first rule, the first linear fitting model or the first curve fitting model as a first fitting model at a pre-fill stage;
determining, based on a first rule, the second linear fitting model or the second curve fitting model as a second fitting model at a production stage;
the first rule is to target minimum computational complexity and deviation, and a linear fitting model is preferentially selected.
Specifically, the fitting of sample data of the tobacco leaf feeding machine in a pre-filling stage and a production stage can be performed by adopting two modes of linear fitting or least square fitting. The sample data is data obtained by preprocessing original acquisition data, and the original acquisition data also comprises the working frequency of a charging pump and a flow value corresponding to the charging of the charging pump by adopting different types of feed liquid under the working frequency. The purpose of the preprocessing is mainly to exclude data that are significantly abnormal. For example, in the pre-filling stage, normal distribution statistics is performed on data obtained in different time periods of the same type of feed liquid, the center point of the data is determined under each frequency value, a corresponding fluctuation range is set according to the process requirement, the data meeting the fluctuation range is reserved as sample data, and the data not within the fluctuation range is deleted. And similarly, the same pretreatment method as the pre-filling stage is adopted for the original acquired data of the production stage, so that sample data of the production stage are obtained.
Adopting linear fitting, namely fitting sample data in a pre-filling stage according to a linear relation to determine a corresponding first linear fitting model; and fitting the sample data of the production stage according to a linear relation to determine a corresponding second linear fitting model.
Adopting a least square method, namely fitting sample data in a pre-filling stage according to a quadratic curve relationship, and determining a corresponding first curve fitting model; and fitting the sample data in the production stage according to a quadratic curve relationship, and determining a corresponding second curve fitting model.
By the method, the sample data in the pre-filling stage can be fitted to obtain two models, namely a first linear fitting model and a first curve fitting model, and then the first fitting model corresponding to the sample data in the pre-filling stage with the minimum calculation complexity and the minimum deviation degree is determined according to the calculation complexity corresponding to the two models and the deviation degree between the actual sample data and the fitting model. When the degree of deviation is substantially the same, the first linear fitting model is preferentially selected as the first fitting model.
For the second fitting model of the production phase, screening and determination can be performed in the same manner as for the pre-filling phase.
The first fitting model and the second fitting model obtained in this way are more in line with actual production, and the corresponding calculation complexity is low, so that the processing process is facilitated to be quickened.
Optionally, the fitting quadratic curves of the feeding pump frequency and the feed liquid flow rate of the tobacco leaf feeding machine in the pre-filling stage and the production stage are respectively determined based on a least square method and used as a first curve fitting model and a second curve fitting model, and the fitting quadratic curves comprise:
based on a fitting rule, respectively determining a fitting quadratic curve in a pre-filling stage and a fitting quadratic curve in a production stage to serve as a first curve fitting model and a second curve fitting model;
the fitting rule includes:
setting a fitting quadratic curve equation and a fitting objective function;
taking the minimum fitting objective function as a target, and combining sample data corresponding to the feed liquid of the same type, and determining the value of each coefficient of the fitting conic equation under the condition that the derivative of the fitting objective function on each coefficient of the fitting conic equation is zero;
and determining a fitting quadratic curve corresponding to the tobacco leaf feeder based on the values of the coefficients of the fitting quadratic curve equation and the set fitting quadratic equation.
Specifically, after sample data of the tobacco leaf feeding machine in the pre-filling stage and the production stage are obtained, statistical analysis is performed by taking sample data of the same type of feed liquid as a unit in the pre-filling stage and the production stage respectively. For example, during the pre-fill stage, different types of feed streams include feed stream A, feed stream B, and feed stream C. Firstly, carrying out statistical analysis on sample data corresponding to feed liquid A, and obtaining flow values which are correspondingly collected when a feed pump of the feed liquid A feeds materials in a tobacco leaf feeding machine at different working frequencies, wherein the flow values possibly correspond to a plurality of values at the same working frequency, and for more accurate statistical analysis, determining mathematical expected values of the flow values at the same working frequency to serve as flow values corresponding to the working frequency. Thereby obtaining a feeding flow value set Y for regression fitting i ＝{y i (i=1, 2, …, n) and pump frequency set X i ＝{x i (i=1, 2, …, n), typically requiring n>20, setting a fitting quadratic curve equation corresponding to the tobacco leaf feeding machine to be expressed as:
wherein the coefficients a, b and c are constants, y i At a feed pump frequency x i Corresponding to the feed flow value. Setting a fitting objective function, namely, the residual square sum Q as follows:
Let Q be the minimum to find the above constants a, b and c. From the conditions The method can obtain:
the values of the coefficients a, b and c can be obtained, and a fitting quadratic curve of a certain tobacco leaf feeder taking the feeding flow and the frequency of the feeding pump as variables can be obtained, so that a first curve fitting model is determined, and the corresponding maximum feeding flow estimated value when the working frequency of the feeding pump in the tobacco leaf feeder is maximum can be calculated according to the first curve fitting model. The charging pump has a corresponding rated operating frequency, typically 0Hz to 50Hz, so that the operating frequency of the charging pump does not need to be set to be maximum, and the maximum value of the corresponding charging flow value when the charging pump is at the maximum operating frequency can also be determined by fitting the quadratic curve. Similarly, the minimum value of the feed flow value corresponding to the minimum operating frequency is also determined.
And in the same way, in the production stage, the sample data in the pre-filling stage is fitted in the same way as in the pre-filling stage, so that a corresponding fitting quadratic curve is obtained and is used as a second curve fitting model.
Optionally, the estimating, based on the operating frequency range of the feeding pump in the tobacco feeding machine and the first fitting model, the corresponding feeding capacity of the tobacco feeding machine includes:
And determining the maximum value and the minimum value of the feed liquid flow corresponding to the first fitting model in the working frequency range of the feed pump, and taking the maximum value and the minimum value as the predicted value of the feed capacity corresponding to the tobacco leaf feeding machine.
Specifically, the first fitting model corresponding to the tobacco leaf feeding machine can be expressed as a quadratic curve equation or a linear equation taking the working frequency of the feeding pump and the flow value corresponding to the working frequency as variables, and can be expressed as a quadratic curve or a linear relation taking the working frequency of the feeding pump as a horizontal axis and the flow value corresponding to the working frequency as a vertical axis, or a quadratic curve or a linear relation taking the working frequency of the feeding pump as a vertical axis and the flow value corresponding to the working frequency as a horizontal axis. And the corresponding working frequency ranges of different tobacco leaf feeding machines can be different, and the corresponding maximum value and minimum value of the corresponding feeding flow can be determined as the pre-estimated value of the corresponding feeding capacity of the tobacco leaf feeding machines by correspondingly cutting the quadratic curve or the linear relation according to the working frequency ranges.
Optionally, the method further comprises:
determining an expected feed flow rate of the different types of feed liquids in a tobacco leaf feeder during a production stage;
Determining a pre-judging operation adopted for the tobacco leaf feeding machine based on the magnitude relation between the pre-estimated value of the feeding capacity of the tobacco leaf feeding machine and the actual required value; the actual demand value is the product of the expected charging flow and a preset adjustment value; the preset adjustment value is larger than 1 and smaller than 2.
Specifically, when the tobacco leaf feeding machine enters the production stage, the theoretical feeding flow, namely the expected feeding flow, is calculated according to the material set flow and the feeding proportion. The material is usually tobacco, and the material set flow rate refers to the flow rate of the tobacco when the tobacco passes through a feeding nozzle in a tobacco feeding machine, for example, the material set flow rate is 2700, the corresponding feeding proportion is 1%, and then the corresponding expected feeding flow rate is 27. The present invention is not limited to the above-described embodiments, and may be modified in any manner.
According to the method, the corresponding feeding capacity of the tobacco leaf feeding machine is determined, and in order to prolong the service life of the feeding machine, the tobacco leaf feeding machine is usually not allowed to work at the maximum working frequency, therefore, an actual required value is usually determined by the product of the expected feeding flow and a preset adjusting value, the preset adjusting value is usually a value which is larger than 1 and smaller than 2, and can be determined according to the liquid resistance of the feed liquid, for example, the larger the liquid resistance of the feed liquid is, the smaller the preset adjusting value is, because the larger the liquid resistance of the feed liquid is, the higher the possibility that the feed liquid is higher in viscosity, the feeding flow which can be actually achieved by the tobacco leaf feeding machine in the production process is possibly smaller than the theoretical value, and in this way, the larger the preset adjusting value is set, the actual flow value which can be provided by the tobacco leaf feeding machine can meet the expected feeding flow for a longer time.
Of course, the preset adjustment values may also be values within a certain range according to the liquid resistances corresponding to different types of liquid medicines, for example, the first range and the second range have a one-to-one correspondence, where the first range represents the value range of the liquid resistance, and the second range represents the range of the preset adjustment value, so that the liquid medicines with different liquid resistances may be corresponding to the same first range, and then the corresponding preset adjustment values may be the same value.
Further, according to the magnitude relation between the predicted value of the feeding capacity of the tobacco leaf feeding machine and the actual required value, determining the pre-judging operation adopted for the tobacco leaf feeding machine; the prejudging operation comprises the following steps: the tobacco leaf feeding machine normally enters the production stage and a feeding pipeline of the tobacco leaf feeding machine is cleaned.
Optionally, the determining the pre-determining operation to be performed on the tobacco leaf feeding machine based on the magnitude relation between the pre-determined value of the feeding capacity of the tobacco leaf feeding machine and the actual required value comprises:
if the predicted value of the feeding capacity of the tobacco leaf feeding machine is larger than or equal to the actual required value, the tobacco leaf feeding machine normally enters a production stage;
and if the predicted value of the feeding capacity of the tobacco leaf feeding machine is smaller than the actual required value, cleaning a feeding pipeline of the tobacco leaf feeding machine.
Specifically, the predicted value S of the feeding capacity of the tobacco leaf feeding machine is compared with the product T of the maximum value of the corresponding feeding capacity of the tobacco leaf feeding machine and a preset adjustment value.
If the estimated value S of the charging capacity is greater than or equal to the product T, it is indicated that the tobacco charging machine is capable of carrying the charging tasks of these materials, and after the pre-filling phase, the production phase can be directly accessed.
If the estimated value S of the feeding capacity is smaller than the product T, the tobacco leaf feeding machine is indicated to bear no feeding tasks of the materials, and after the pre-filling stage, the feeding pipeline of the tobacco leaf feeding machine is cleaned so as to ensure that the tobacco leaf feeding machine does not bear the feeding tasks of the materials because of blockage of the feeding pipeline. And determining a fitting quadratic curve corresponding to the tobacco leaf feeder again, and repeating the comparison process after determining the estimated value of the feeding capacity of the tobacco leaf feeder again.
According to the feeding capacity estimating method provided by the invention, the feeding capacity of the tobacco leaf feeding machine is estimated by utilizing the least square method, so that the feeding capacity of the tobacco leaf feeding machine is ensured to meet the requirements of a normal production stage, the stop production is reduced, the times of checking the tobacco leaf feeding machine are reduced, the feeding flow of the production stage is monitored, and the quality risk hidden danger is reduced.
The feeding capacity estimating apparatus provided by the invention is described below, and the feeding capacity estimating apparatus described below and the feeding capacity estimating method described above can be referred to correspondingly.
Fig. 3 is a schematic structural diagram of a device for estimating charging capacity according to the present invention, as shown in fig. 3, the device includes: an acquisition module 301, a fitting module 302, a difference module 303, a first determination module 304, a second determination module 305, a first estimation module 306 and a second estimation module 307. Wherein:
the obtaining module 301 is configured to obtain sample data of different types of feed liquids in a tobacco leaf feeding machine in different working phases, where the sample data includes a working frequency of a feeding pump and a flow value corresponding to when the feeding pump uses different types of feed liquids for feeding at the working frequency; the different working phases comprise a pre-filling phase and a production phase;
the fitting module 302 is configured to fit corresponding relations between the feed pump frequencies and the feed liquid flows of the tobacco leaf feeding machines in different working phases respectively by using sample data corresponding to the same type of feed liquid as a unit, so as to obtain a first fitting model and a second fitting model;
a difference module 303, configured to determine a flow difference curve based on the first fitting model and the second fitting model; the flow difference curve is used for representing the difference value of the feed liquid flow in different working stages of the tobacco leaf feeder under the same feeding pump frequency;
A first determining module 304, configured to determine, based on the first fitting model, a predicted feed liquid flow rate of a feed pump in the tobacco leaf feeding machine during a pre-filling stage;
a second determining module 305, configured to determine whether a difference between the estimated feed liquid flow rate of the feed pump and the actual feed liquid flow rate of the feed pump is within a preset threshold range;
a first estimating module 306, configured to estimate, if the estimated feeding capacity is within a preset threshold range, a corresponding feeding capacity of the tobacco leaf feeding machine based on a working frequency range of a feeding pump in the tobacco leaf feeding machine and the first fitting model;
and the second estimating module 307 is configured to estimate a charging capability corresponding to the tobacco charging machine based on an actual feed liquid flow extremum acquired by the charging pump in the tobacco charging machine when the working frequency is upper and lower and a flow difference value corresponding to the flow difference curve when the working frequency is upper and lower.
Optionally, the fitting module 302 is configured to fit the corresponding relationship between the feed pump frequency and the feed liquid flow of the tobacco leaf feeding machine in different working phases, respectively, with the sample data corresponding to the feed liquid of the same type as a unit, so as to obtain a first fitting model and a second fitting model, where the fitting module is specifically configured to:
Based on linear fitting, respectively determining linear fitting relations of the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in a pre-filling stage and a production stage, and taking the linear fitting relations as a first linear fitting model and a second linear fitting model;
based on a least square method, respectively determining fitting quadratic curves of the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in a pre-filling stage and a production stage, and taking the fitting quadratic curves as a first curve fitting model and a second curve fitting model;
determining, based on a first rule, the first linear fitting model or the first curve fitting model as a first fitting model at a pre-fill stage;
determining, based on a first rule, the second linear fitting model or the second curve fitting model as a second fitting model at a production stage;
the first rule is to target minimum computational complexity and deviation, and a linear fitting model is preferentially selected.
The fitting quadratic curves of the feeding pump frequency and the feed liquid flow rate of the tobacco leaf feeding machine in the pre-filling stage and the production stage are respectively determined based on a least square method and used as a first curve fitting model and a second curve fitting model, and the fitting quadratic curves comprise:
based on a fitting rule, respectively determining a fitting quadratic curve in a pre-filling stage and a fitting quadratic curve in a production stage to serve as a first curve fitting model and a second curve fitting model;
The fitting rule includes:
setting a fitting quadratic curve equation and a fitting objective function;
taking the minimum fitting objective function as a target, and combining sample data corresponding to the feed liquid of the same type, and determining the value of each coefficient of the fitting conic equation under the condition that the derivative of the fitting objective function on each coefficient of the fitting conic equation is zero;
and determining a fitting quadratic curve corresponding to the tobacco leaf feeder based on the values of the coefficients of the fitting quadratic curve equation and the set fitting quadratic equation.
Optionally, the first estimating module 306 is specifically configured to, in estimating, based on the operating frequency range of the feeding pump in the tobacco feeding machine and the first fitting model, a corresponding feeding capacity of the tobacco feeding machine:
and determining the maximum value and the minimum value of the feed liquid flow corresponding to the first fitting model in the working frequency range of the feed pump, and taking the maximum value and the minimum value as the predicted value of the feed capacity corresponding to the tobacco leaf feeding machine.
Optionally, the apparatus further comprises:
a first determining module for determining an expected feed flow rate of the different types of feed liquids in the tobacco leaf feeding machine in a production stage;
The second determining module is used for determining the pre-judging operation adopted by the tobacco leaf feeding machine based on the magnitude relation between the pre-estimated value of the feeding capacity of the tobacco leaf feeding machine and the actual required value; the actual demand value is the product of the expected charging flow and a preset adjustment value; the preset adjustment value is larger than 1 and smaller than 2.
Optionally, the second determining module is specifically configured to, in a process of determining the pre-determining operation to be performed on the tobacco leaf feeding machine based on a magnitude relation between a pre-determined value of the feeding capacity and an actual required value of the tobacco leaf feeding machine:
if the predicted value of the feeding capacity of the tobacco leaf feeding machine is larger than or equal to the actual required value, the tobacco leaf feeding machine normally enters a production stage;
and if the predicted value of the feeding capacity of the tobacco leaf feeding machine is smaller than the actual required value, cleaning a feeding pipeline of the tobacco leaf feeding machine.
Optionally, the preset adjustment value is determined according to liquid resistances corresponding to different types of liquid.
Optionally, the flow value corresponding to the feeding of the feed liquid with different types by the feeding pump is obtained by a flowmeter in the feeding pump.
The method and the device provided by the invention are based on the same application conception, and because the principle of solving the problems by the method and the device is similar, the implementation of the device and the method can be mutually referred to, and the repetition is not repeated.
Fig. 4 is a schematic structural diagram of an electronic device according to the present invention, as shown in fig. 4, the electronic device may include: processor 410, communication interface (Communications Interface) 420, memory 430 and communication bus 440, wherein processor 410, communication interface 420 and memory 430 communicate with each other via communication bus 440. The processor 410 may invoke logic instructions in the memory 430 to perform a loading capacity estimation method comprising: acquiring sample data of different types of feed liquid in a tobacco leaf feeding machine in different working stages, wherein the sample data comprise the working frequency of a feeding pump and flow values corresponding to the feeding pump when feeding the feed liquid in different types under the working frequency; the different working phases comprise a pre-filling phase and a production phase;
respectively fitting the corresponding relation between the feed pump frequency and the feed liquid flow of the tobacco leaf feeding machine in different working phases by taking sample data corresponding to the feed liquid of the same type as a unit to obtain a first fitting model and a second fitting model;
determining a flow difference curve based on the first fitting model and the second fitting model; the flow difference curve is used for representing the difference value of the feed liquid flow in different working stages of the tobacco leaf feeder under the same feeding pump frequency;
Determining the estimated feed liquid flow of a feed pump in the tobacco leaf feeding machine in a pre-filling stage based on the first fitting model;
determining whether the difference value between the estimated feed liquid flow of the feed pump and the actual feed liquid flow of the feed pump is within a preset threshold range;
if the feeding capacity is within the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the working frequency range of a feeding pump in the tobacco leaf feeding machine and the first fitting model;
if the flow difference curve is not in the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the actual feed liquid flow extreme value acquired by the feeding pump in the tobacco leaf feeding machine when the working frequency is limited at the upper and lower limits and the flow difference value corresponding to the flow difference curve when the working frequency is limited at the upper and lower limits.
Optionally, the fitting is performed on the corresponding relationship between the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in different working phases by taking sample data corresponding to the same type of feed liquid as a unit, so as to obtain a first fitting model and a second fitting model, including:
based on linear fitting, respectively determining linear fitting relations of the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in a pre-filling stage and a production stage, and taking the linear fitting relations as a first linear fitting model and a second linear fitting model;
Based on a least square method, respectively determining fitting quadratic curves of the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in a pre-filling stage and a production stage, and taking the fitting quadratic curves as a first curve fitting model and a second curve fitting model;
determining, based on a first rule, the first linear fitting model or the first curve fitting model as a first fitting model at a pre-fill stage;
determining, based on a first rule, the second linear fitting model or the second curve fitting model as a second fitting model at a production stage;
the first rule is to target minimum computational complexity and deviation, and a linear fitting model is preferentially selected.
The fitting quadratic curves of the feeding pump frequency and the feed liquid flow rate of the tobacco leaf feeding machine in the pre-filling stage and the production stage are respectively determined based on a least square method and used as a first curve fitting model and a second curve fitting model, and the fitting quadratic curves comprise:
based on a fitting rule, respectively determining a fitting quadratic curve in a pre-filling stage and a fitting quadratic curve in a production stage to serve as a first curve fitting model and a second curve fitting model;
the fitting rule includes:
setting a fitting quadratic curve equation and a fitting objective function;
Taking the minimum fitting objective function as a target, and combining sample data corresponding to the feed liquid of the same type, and determining the value of each coefficient of the fitting conic equation under the condition that the derivative of the fitting objective function on each coefficient of the fitting conic equation is zero;
and determining a fitting quadratic curve corresponding to the tobacco leaf feeder based on the values of the coefficients of the fitting quadratic curve equation and the set fitting quadratic equation.
Optionally, the estimating, based on the operating frequency range of the feeding pump in the tobacco feeding machine and the first fitting model, the corresponding feeding capacity of the tobacco feeding machine includes:
and determining the maximum value and the minimum value of the feed liquid flow corresponding to the first fitting model in the working frequency range of the feed pump, and taking the maximum value and the minimum value as the predicted value of the feed capacity corresponding to the tobacco leaf feeding machine.
Optionally, the method further comprises:
determining an expected feed flow rate of the different types of feed liquids in a tobacco leaf feeder during a production stage;
determining a pre-judging operation adopted for the tobacco leaf feeding machine based on the magnitude relation between the pre-estimated value of the feeding capacity of the tobacco leaf feeding machine and the actual required value; the actual demand value is the product of the expected charging flow and a preset adjustment value; the preset adjustment value is larger than 1 and smaller than 2.
Optionally, the determining the pre-determining operation to be performed on the tobacco leaf feeding machine based on the magnitude relation between the pre-determined value of the feeding capacity of the tobacco leaf feeding machine and the actual required value comprises:
if the predicted value of the feeding capacity of the tobacco leaf feeding machine is larger than or equal to the actual required value, the tobacco leaf feeding machine normally enters a production stage;
and if the predicted value of the feeding capacity of the tobacco leaf feeding machine is smaller than the actual required value, cleaning a feeding pipeline of the tobacco leaf feeding machine.
Optionally, the preset adjustment value is determined according to liquid resistances corresponding to different types of liquid.
Optionally, the flow value corresponding to the feeding of the feed liquid with different types by the feeding pump is obtained by a flowmeter in the feeding pump.
Further, the logic instructions in the memory 430 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product comprising a computer program, the computer program being storable on a non-transitory computer readable storage medium, the computer program, when executed by a processor, being capable of performing the method of estimating charging capability provided by the above methods, the method comprising:
acquiring sample data of different types of feed liquid in a tobacco leaf feeding machine in different working stages, wherein the sample data comprise the working frequency of a feeding pump and flow values corresponding to the feeding pump when feeding the feed liquid in different types under the working frequency; the different working phases comprise a pre-filling phase and a production phase;
respectively fitting the corresponding relation between the feed pump frequency and the feed liquid flow of the tobacco leaf feeding machine in different working phases by taking sample data corresponding to the feed liquid of the same type as a unit to obtain a first fitting model and a second fitting model;
determining a flow difference curve based on the first fitting model and the second fitting model; the flow difference curve is used for representing the difference value of the feed liquid flow in different working stages of the tobacco leaf feeder under the same feeding pump frequency;
Determining the estimated feed liquid flow of a feed pump in the tobacco leaf feeding machine in a pre-filling stage based on the first fitting model;
determining whether the difference value between the estimated feed liquid flow of the feed pump and the actual feed liquid flow of the feed pump is within a preset threshold range;
if the feeding capacity is within the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the working frequency range of a feeding pump in the tobacco leaf feeding machine and the first fitting model;
if the flow difference curve is not in the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the actual feed liquid flow extreme value acquired by the feeding pump in the tobacco leaf feeding machine when the working frequency is limited at the upper and lower limits and the flow difference value corresponding to the flow difference curve when the working frequency is limited at the upper and lower limits.
In yet another aspect, the present invention provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the method of estimating charging capacity provided by the above methods, the method comprising:
acquiring sample data of different types of feed liquid in a tobacco leaf feeding machine in different working stages, wherein the sample data comprise the working frequency of a feeding pump and flow values corresponding to the feeding pump when feeding the feed liquid in different types under the working frequency; the different working phases comprise a pre-filling phase and a production phase;
Respectively fitting the corresponding relation between the feed pump frequency and the feed liquid flow of the tobacco leaf feeding machine in different working phases by taking sample data corresponding to the feed liquid of the same type as a unit to obtain a first fitting model and a second fitting model;
determining a flow difference curve based on the first fitting model and the second fitting model; the flow difference curve is used for representing the difference value of the feed liquid flow in different working stages of the tobacco leaf feeder under the same feeding pump frequency;
determining the estimated feed liquid flow of a feed pump in the tobacco leaf feeding machine in a pre-filling stage based on the first fitting model;
determining whether the difference value between the estimated feed liquid flow of the feed pump and the actual feed liquid flow of the feed pump is within a preset threshold range;
if the feeding capacity is within the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the working frequency range of a feeding pump in the tobacco leaf feeding machine and the first fitting model;
if the flow difference curve is not in the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the actual feed liquid flow extreme value acquired by the feeding pump in the tobacco leaf feeding machine when the working frequency is limited at the upper and lower limits and the flow difference value corresponding to the flow difference curve when the working frequency is limited at the upper and lower limits.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A method for estimating charging capacity, comprising:
acquiring sample data of different types of feed liquid in a tobacco leaf feeding machine in different working stages, wherein the sample data comprise the working frequency of a feeding pump and flow values corresponding to the feeding pump when feeding the feed liquid in different types under the working frequency; the different working phases comprise a pre-filling phase and a production phase;
respectively fitting the corresponding relation between the feed pump frequency and the feed liquid flow of the tobacco leaf feeding machine in different working phases by taking sample data corresponding to the feed liquid of the same type as a unit to obtain a first fitting model and a second fitting model;
Determining a flow difference curve based on the first fitting model and the second fitting model; the flow difference curve is used for representing the difference value of the feed liquid flow in different working stages of the tobacco leaf feeder under the same feeding pump frequency;
determining the estimated feed liquid flow of a feed pump in the tobacco leaf feeding machine in a pre-filling stage based on the first fitting model;
determining whether the difference value between the estimated feed liquid flow of the feed pump and the actual feed liquid flow of the feed pump is within a preset threshold range;
if the feeding capacity is within the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the working frequency range of a feeding pump in the tobacco leaf feeding machine and the first fitting model;
if the flow difference curve is not in the preset threshold range, estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the actual feed liquid flow extreme value acquired by the feeding pump in the tobacco leaf feeding machine when the working frequency is limited at the upper and lower limits and the flow difference value corresponding to the flow difference curve when the working frequency is limited at the upper and lower limits.
2. The method for estimating charging capacity according to claim 1, wherein said fitting the corresponding relation between the charging pump frequency and the flow rate of the material liquid of the tobacco charging machine in different working phases with the sample data corresponding to the material liquid of the same type as a unit, respectively, to obtain a first fitting model and a second fitting model, includes:
Based on linear fitting, respectively determining linear fitting relations of the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in a pre-filling stage and a production stage, and taking the linear fitting relations as a first linear fitting model and a second linear fitting model;
based on a least square method, respectively determining fitting quadratic curves of the feeding pump frequency and the feed liquid flow of the tobacco leaf feeding machine in a pre-filling stage and a production stage, and taking the fitting quadratic curves as a first curve fitting model and a second curve fitting model;
determining, based on a first rule, the first linear fitting model or the first curve fitting model as a first fitting model at a pre-fill stage;
determining, based on a first rule, the second linear fitting model or the second curve fitting model as a second fitting model at a production stage;
the first rule is to target minimum computational complexity and deviation, and a linear fitting model is preferentially selected.
3. The method according to claim 2, wherein determining fitting quadratic curves of the feed pump frequency and the feed liquid flow rate of the tobacco leaf feeder in the pre-filling stage and the production stage, respectively, based on the least square method, as the first curve fitting model and the second curve fitting model, comprises:
Based on a fitting rule, respectively determining a fitting quadratic curve in a pre-filling stage and a fitting quadratic curve in a production stage to serve as a first curve fitting model and a second curve fitting model;
the fitting rule includes:
setting a fitting quadratic curve equation and a fitting objective function;
taking the minimum fitting objective function as a target, and combining sample data corresponding to the feed liquid of the same type, and determining the value of each coefficient of the fitting conic equation under the condition that the derivative of the fitting objective function on each coefficient of the fitting conic equation is zero;
and determining a fitting quadratic curve corresponding to the tobacco leaf feeder based on the values of the coefficients of the fitting quadratic curve equation and the set fitting quadratic equation.
4. The feeding capacity estimating method according to claim 3, wherein the estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the operating frequency range of the feeding pump in the tobacco leaf feeding machine and the first fitting model includes:
and determining the maximum value and the minimum value of the feed liquid flow corresponding to the first fitting model in the working frequency range of the feed pump, and taking the maximum value and the minimum value as the predicted value of the feed capacity corresponding to the tobacco leaf feeding machine.
5. The feed capacity estimation method of claim 4, further comprising:
determining an expected feed flow rate of the different types of feed liquids in a tobacco leaf feeder during a production stage;
determining a pre-judging operation adopted for the tobacco leaf feeding machine based on the magnitude relation between the pre-estimated value of the feeding capacity of the tobacco leaf feeding machine and the actual required value; the actual demand value is the product of the expected charging flow and a preset adjustment value; the preset adjustment value is larger than 1 and smaller than 2.
6. The feeding capacity estimating method according to claim 5, wherein said determining a pre-determination operation to be performed on said tobacco leaf feeding machine based on a magnitude relation between a pre-determined value of feeding capacity of said tobacco leaf feeding machine and an actual demand value includes:
if the predicted value of the feeding capacity of the tobacco leaf feeding machine is larger than or equal to the actual required value, the tobacco leaf feeding machine normally enters a production stage;
and if the predicted value of the feeding capacity of the tobacco leaf feeding machine is smaller than the actual required value, cleaning a feeding pipeline of the tobacco leaf feeding machine.
7. The method according to claim 5 or 6, wherein the preset adjustment value is determined according to the liquid resistances corresponding to different types of liquid.
8. A charging capacity estimation device, the device comprising:
the acquisition module is used for acquiring sample data of different types of feed liquid in the tobacco leaf feeding machine in different working stages, wherein the sample data comprise the working frequency of a feeding pump and flow values corresponding to the feeding pump when feeding the feed liquid in different types under the working frequency; the different working phases comprise a pre-filling phase and a production phase;
the fitting module is used for respectively fitting the corresponding relation between the feeding pump frequency of the tobacco leaf feeding machine and the flow of the feed liquid in different working phases by taking sample data corresponding to the feed liquid of the same type as a unit to obtain a first fitting model and a second fitting model;
the difference module is used for determining a flow difference curve based on the first fitting model and the second fitting model; the flow difference curve is used for representing the difference value of the feed liquid flow in different working stages of the tobacco leaf feeder under the same feeding pump frequency;
the first determining module is used for determining the estimated feed liquid flow of the feed pump in the tobacco leaf feeding machine in the pre-filling stage based on the first fitting model;
The second determining module is used for determining whether the difference value between the estimated feed liquid flow of the feed pump and the actual feed liquid flow of the feed pump is within a preset threshold range;
the first estimating module is used for estimating the corresponding feeding capacity of the tobacco leaf feeding machine based on the working frequency range of the feeding pump in the tobacco leaf feeding machine and the first fitting model if the first estimating module is in the preset threshold range;
and the second estimating module is used for estimating the corresponding feeding capacity of the tobacco leaf feeder based on the actual feed liquid flow extreme value acquired by the feeding pump in the tobacco leaf feeder when the working frequency is limited at the upper and lower limits and the flow difference value corresponding to the flow difference curve when the working frequency is limited at the upper and lower limits if the flow difference value is not in the preset threshold range.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the feeding capability estimation method according to any one of claims 1 to 7 when executing the program.
10. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the feeding capacity estimation method according to any one of claims 1 to 7.
CN202310828383.0A 2023-07-06 2023-07-06 Charging capability estimation method, device, equipment and storage medium Pending CN116910439A (en)

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CN202310828383.0A CN116910439A (en) 2023-07-06 2023-07-06 Charging capability estimation method, device, equipment and storage medium

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Application Number Priority Date Filing Date Title
CN202310828383.0A CN116910439A (en) 2023-07-06 2023-07-06 Charging capability estimation method, device, equipment and storage medium

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CN116910439A true CN116910439A (en) 2023-10-20

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