CN116820056A - Production process parameter processing method for bag type packaging machine - Google Patents
Production process parameter processing method for bag type packaging machine Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
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- G—PHYSICS
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Abstract
The invention relates to the technical field of data processing, and provides a production process parameter processing method for a bag type packaging machine, which comprises the following steps: acquiring production process parameters of the bag type packaging machine, and acquiring a parameter sequence corresponding to each production process parameter at the moment to be analyzed; acquiring parameter adjustment degrees corresponding to production process parameters; obtaining the prominence concentration degree corresponding to the production process parameters; acquiring parameter adjustment degrees corresponding to production process parameters according to the prominence concentration degree, and acquiring adjustment parameter values of the production process parameters at the moment to be analyzed according to the parameter adjustment degrees; and obtaining the self-adaptive setting value of the production process parameters of the bag type packaging machine according to the adjustment parameter value corresponding to each production process parameter at the moment to be analyzed. The invention aims to solve the problem of abnormal work misjudgment of the bag type packaging machine in the existing production process parameter adjustment process.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a production process parameter processing method for a bag type packaging machine.
Background
The bag type packaging machine is used for automatically packaging products, and an operator only needs to place the packaged bags on the bag taking part of the bag type packaging machine at one time according to requirements, and the bag type packaging machine can automatically complete the procedures of bag taking, date printing, bag opening, signal metering for a metering device, blanking, sealing, outputting and the like. Meanwhile, the automatic packaging machine can be additionally provided with the detailed functions of door opening emergency stop, automatic card feeding, abnormal discharging and the like for the bag type packaging machine according to the product packaging requirements, so that the automation of the packaging process is realized, the production efficiency is improved for enterprises, the labor cost and the management cost are saved, and the cost is reduced. However, before the bag-type packing machine is used to automatically pack the product, the production process parameters of the bag-type packing machine need to be set according to the demand of the product packing.
In the process of setting production process parameters, abnormal detection of the production process parameters of the bag type packaging machine is triggered by repeated adjustment and change of the production process parameters, and fluctuation of the production process parameters caused by adjustment is misjudged as abnormal operation of the bag type packaging machine, so that normal operation of the bag type packaging machine is affected. Therefore, a production process parameter processing method for a bag type packaging machine is needed, the problem of abnormal operation and misjudgment of the bag type packaging machine in the existing production process parameter adjustment process is solved, and automatic adjustment of the production process parameters in the production process of the bag type packaging machine is realized.
Disclosure of Invention
The invention provides a production process parameter processing method for a bag type packaging machine, which aims to solve the problem of abnormal operation and misjudgment of the bag type packaging machine in the existing production process parameter adjustment process, and adopts the following technical scheme:
one embodiment of the present invention provides a production process parameter processing method for a bag-type packaging machine, the method comprising the steps of:
acquiring production process parameters of the bag type packaging machine, and acquiring a parameter sequence corresponding to each production process parameter at the moment to be analyzed;
acquiring parameter adjustment degrees corresponding to production process parameters according to data values contained in each production process parameter sequence at the moment to be analyzed;
acquiring a high-adjustment data value contained in each production process parameter sequence, acquiring the concentration degree of the production process parameters, and acquiring the prominent concentration degree corresponding to the production process parameters according to the parameter adjustment degree, the concentration degree and the high-adjustment data value corresponding to the production process parameters at the moment to be analyzed;
acquiring parameter adjustment degrees corresponding to production process parameters according to the prominence concentration degree, and acquiring adjustment parameter values of the production process parameters at the moment to be analyzed according to the parameter adjustment degrees;
and obtaining the self-adaptive setting value of the production process parameters of the bag type packaging machine according to the adjustment parameter value corresponding to each production process parameter at the moment to be analyzed.
Further, the production process parameters of the bag type packaging machine include, but are not limited to, blanking quality, packaging speed, pressure, sealing temperature, host operating frequency, motor operating frequency, and packaging speed.
Further, the method for obtaining the parameter sequence corresponding to each production process parameter at the moment to be analyzed comprises the following specific steps:
acquiring data values of all production process parameters once every first preset threshold time;
respectively marking each time for acquiring the production process parameters as a time to be analyzed, marking the production process parameters of the second preset threshold secondary parameter acquisition time before the time to be analyzed as the production process parameters of the time before the time to be analyzed, and marking the production process parameters of the third preset threshold secondary parameter acquisition time after the time to be analyzed as the production process parameters of the time after the time to be analyzed;
respectively acquiring all data values contained in the previous production process parameters and the later production process parameters corresponding to each production process parameter at the moment to be analyzed, sequencing all the data values corresponding to each production process parameter according to the acquisition time of the data values, and acquiring a time sequence corresponding to each production process parameter;
and recording the time sequence corresponding to the production process parameters into a production process parameter sequence corresponding to the production process parameters.
Further, the method for obtaining the parameter adjustment degree corresponding to the production process parameters according to the data value contained in each production process parameter sequence at the moment to be analyzed comprises the following specific steps:
acquiring information entropy of a production process parameter sequence at a moment to be analyzed;
acquiring the average value of all data values contained in a production process parameter sequence corresponding to the production process parameter at the moment to be analyzed;
the absolute value of the difference value between each data value in the production process parameter sequence at the moment to be analyzed and the average value of all the data values contained in the production process parameter sequence is recorded as the absolute difference value of the data values;
the sum of absolute differences of all data values in the production process parameter sequence is recorded as a first sum value;
the ratio of the absolute difference value of the data value at the moment to be analyzed to the first sum value is recorded as a first ratio;
and recording the product of the first ratio and the information entropy of the production process parameter sequence as the parameter adjustment degree corresponding to the production process parameter at the moment to be analyzed.
Further, the method for obtaining the high-adjustment data value contained in each production process parameter sequence comprises the following specific steps:
performing anomaly detection on all data values contained in the production process parameter sequence to obtain an anomaly value corresponding to each data value;
clustering the abnormal values of all the data values into two clusters by using a clustering algorithm;
and respectively acquiring the average value of all the abnormal values contained in each cluster, and marking the data value corresponding to all the abnormal values contained in the cluster with the largest average value as a high-adjustment data value.
Further, the method for obtaining the concentration of the production process parameters comprises the following specific steps:
judging whether the high-adjustment data value contains the data value at the current moment or not;
when the high-adjustment data value contains the data value at the current moment, counting the total number of all data values continuously adjacent to the acquisition moment of the data value at the current moment in the high-adjustment data value, and recording the counted total number as the concentration degree of the production process parameters corresponding to the data value;
and when the data value of the current moment is not contained in the data value of the high adjustment degree, assigning the concentration degree as a fourth preset threshold value.
Further, the method for obtaining the prominent concentration degree corresponding to the production process parameters according to the parameter adjustment degree, concentration degree and high adjustment degree data value corresponding to the production process parameters at the moment to be analyzed comprises the following specific steps:
the average value of the parameter adjustment degrees corresponding to all the high adjustment degree data values in the production process parameter sequence corresponding to the production process parameters is recorded as a first average value;
recording the ratio of the concentration of the production process parameters to the total number of the high-adjustment data values contained in the production process parameter sequence as a second ratio;
and (3) recording the product of the concentration of the production process parameters, the first average value and the second ratio as the prominent concentration corresponding to the production process parameters.
Further, the method for obtaining the parameter adjustment degree corresponding to the production process parameter according to the prominence concentration degree comprises the following specific steps:
and carrying out linear normalization on the salient concentration degree corresponding to all the production process parameters at the moment to be analyzed, and recording the normalized value of the salient concentration degree as the parameter adjustment degree corresponding to the production process parameters.
Further, the method for obtaining the adjustment parameter value of the production process parameter at the moment to be analyzed according to the parameter adjustment degree comprises the following specific steps:
when the parameter adjustment degree corresponding to the production process parameters is greater than or equal to a fifth preset threshold value, the production process parameters are considered to be unsuitable and need to be adjusted;
when the parameter adjustment degree corresponding to the production process parameters is smaller than a fifth preset threshold value, the process parameters are considered to be proper;
when the production process parameters are unsuitable and need to be adjusted, taking the data value of the production process parameters at the previous time of the time to be analyzed as the input of a prediction model, obtaining the predicted value of the time to be analyzed, and taking the predicted value of the time to be analyzed as the adjustment parameter value of the production process parameters at the time to be analyzed;
when the process parameters are proper, the data value of the moment to be analyzed is used as the adjustment parameter value of the production process parameters of the moment to be analyzed.
Further, according to the adjustment parameter value corresponding to each production process parameter at the moment to be analyzed, the self-adaptive setting value of the production process parameter of the bag type packaging machine is obtained, and the method comprises the following specific steps:
inputting the production process parameter adjustment parameter value at the moment to be analyzed into a fuzzy PID controller, obtaining the correction parameter value at the moment to be analyzed, and recording the correction parameter value at the moment to be analyzed as the self-adaptive setting value of the production process parameter of the bag type packaging machine at the next moment of the moment to be analyzed;
inputting the correction parameter value of the moment to be analyzed and the adjustment parameter value of the moment next to the moment to be analyzed into a fuzzy PID controller, and obtaining the correction parameter value of the moment next to the moment to be analyzed, wherein the correction parameter value of the moment next to the moment to be analyzed is the self-adaptive setting value of the production process parameter of the bag type packaging machine when the correction parameter value of the moment next to the moment to be analyzed is the later two moments of the moment to be analyzed;
and obtaining the self-adaptive set value of the production process parameter of the bag type packaging machine when each moment to be analyzed.
The beneficial effects of the invention are as follows: the invention analyzes the parameter sequence corresponding to each production process parameter of each time to be analyzed of the bag type packaging machine, realizes the automatic adjustment of the production process parameters in the production process of the bag type packaging machine, solves the problem of misjudgment of the working abnormality of the bag type packaging machine in the existing production process parameter adjustment process, and specifically comprises the following steps: firstly, obtaining parameter adjustment degrees corresponding to production process parameters at the moment to be analyzed according to the discrete degree of all data value differences and numerical distribution contained in a production process parameter sequence corresponding to each moment to be analyzed, and primarily evaluating adjustment amplitudes corresponding to the production process parameters; secondly, combining the abnormal degree of the data value in the parameter sequence corresponding to the production process parameter to obtain the concentration degree of the production process parameter, and obtaining the prominence concentration degree corresponding to the production process parameter according to the parameter adjustment degree and the concentration degree corresponding to the production process parameter at the moment to be analyzed to obtain the accurate evaluation of the adjustment amplitude corresponding to the production process parameter; according to the method, the parameter adjustment degree corresponding to the production process parameters is obtained according to the prominence concentration degree, the adjustment parameter values of the production process parameters at the moment to be analyzed are further determined, the self-adaptive setting value of the production process parameters of the bag type packaging machine is obtained according to the adjustment parameter values corresponding to each production process parameter at the moment to be analyzed, the problem of abnormal operation misjudgment of the bag type packaging machine in the existing production process parameter adjustment process is solved, and the automatic adjustment of the production process parameters in the production process of the bag type packaging machine is realized.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for processing production process parameters for a bag-type packaging machine according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a correction parameter value acquisition mode.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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.
Referring to fig. 1, a flowchart of a method for processing production process parameters for a bag-type packaging machine according to an embodiment of the invention is shown, the method includes the following steps:
and S001, acquiring production process parameters of the bag type packaging machine, and acquiring a parameter sequence corresponding to each production process parameter at the moment to be analyzed.
The method comprises the steps of arranging a sensor on the bag type packaging machine and obtaining production process parameters which need to be regulated and detected in the production process of the bag type packaging machine. The production process parameters comprise blanking quality, packaging speed, pressure, sealing temperature, main machine operating frequency, motor operating frequency and packaging speed.
Each intervalData values of all production process parameters are obtained at a time. Respectively marking each time for acquiring the production process parameters as a time to be analyzed, and marking the time to be analyzed as before +.>The production process parameter at the secondary parameter acquisition time is marked as the production process parameter at the previous time of the time to be analyzed, and the time to be analyzed is +.>The production process parameters at the secondary parameter acquisition time are recorded as the production process parameters at the later time of the time to be analyzed. Wherein (1)>The first preset threshold value, the second preset threshold value and the third preset threshold value are respectively adopted, and the empirical values are respectively 10 seconds, 20 and 15.
All data values contained in the previous production process parameters and the later production process parameters corresponding to each production process parameter at the moment to be analyzed are respectively obtained, all the data values corresponding to each production process parameter are ordered according to the obtaining time of the data values, a time sequence corresponding to each production process parameter is obtained, and the time sequence corresponding to the production process parameter is recorded as a production process parameter sequence corresponding to the production process parameter.
So far, a parameter sequence corresponding to each production process parameter at the moment to be analyzed is obtained.
Step S002, obtaining the parameter adjustment degree corresponding to the production process parameters according to the data value contained in each production process parameter sequence at the moment to be analyzed.
In the process of adjusting the production process parameters, the larger the data value change of the same production process parameters is, the larger the difference between the production process parameters and the target parameters of the working requirements of the current bag type packaging machine is, the larger the adjustment space of the production process parameters is, and the larger the adjustment degree of the production process parameters is.
And acquiring information entropy corresponding to all data values contained in the production process parameter sequence corresponding to the production process parameter, and recording the information entropy of the production process parameter sequence. When the difference of all data values contained in the production process parameter sequence is larger and the numerical distribution is discrete, the information entropy is larger, the difference between the production process parameter and the target parameter of the working requirement of the current bag type packaging machine is larger, the adjustment space of the production process parameter is larger, and the adjustment degree of the production process parameter is larger.
And acquiring the parameter adjustment degree corresponding to each production process parameter at the moment to be analyzed according to the difference of the data values contained in the production process parameter sequence corresponding to each moment to be analyzed.
In the method, in the process of the invention,production process parameters for the moment to be analyzed>Corresponding parameter adjustment degree; />For a second preset threshold, the empirical value is 20; />A third preset threshold value, wherein the empirical value is 15; />Information entropy of the production process parameter sequence; />The production process parameter sequence corresponding to the production process parameter at the moment to be analyzed is +.>A data value, wherein->；/>Is the average of all the data values contained within the sequence of production process parameters.
In the method, in the process of the invention,is the total number of data values contained within the sequence of production process parameters.
When the bag type packaging machine has larger difference of all data values contained in the production process parameter sequence corresponding to the production process parameters at the moment to be analyzed and the numerical distribution is more discrete, the parameter adjustment degree corresponding to the production process parameters is larger, and the production process parameters are more likely to correspond to larger adjustment amplitude.
So far, the parameter adjustment degree corresponding to each production process parameter at the moment to be analyzed is obtained.
Step S003, obtaining high-adjustment data values contained in each production process parameter sequence, obtaining the concentration degree of the production process parameters, and obtaining the prominent concentration degree corresponding to the production process parameters according to the parameter adjustment degree, the concentration degree and the high-adjustment data values corresponding to the production process parameters at the moment to be analyzed.
The parameter adjustment degree is analyzed according to the difference of all the data values and the discrete degree of the numerical distribution contained in the production process parameter sequence, but when the data value of the production process parameter corresponding to the moment to be analyzed is a noise value, the difference of the data value and the discrete degree of the numerical distribution contained in the production process parameter sequence corresponding to the production process parameter also become large, so that the degree of the parameter adjustment is directly determined by the parameter adjustment degree and is influenced by the abnormal noise value, and the influence of the abnormal noise value on the parameter adjustment needs to be eliminated.
And respectively analyzing each production process parameter sequence, carrying out LOF abnormality detection on all data values contained in the production process parameter sequence, obtaining LOF values corresponding to each data value, and recording the LOF values corresponding to the data values as abnormal values of the data values. Clustering the abnormal values of all the data values by using a K-means algorithm, dividing the abnormal values into two clusters, respectively obtaining the average value of all the abnormal values contained in each cluster, and marking the data value corresponding to all the abnormal values contained in the cluster with the largest average value as a high-adjustment data value. The high-adjustment data value is the data value with more prominent variation amplitude of numerical values in the production process parameter sequence.
When the production process parameters are parameters to be regulated, the production process parameters do not accord with the actual production requirements of the bag type packaging machine, and the high regulation data values contained in the production process parameter sequences are concentrated and continuously appear.
First, it is determined whether the high-adjustment data value includes a data value at the current time. When the high-adjustment data value contains the data value at the current moment, counting the total number of all data values continuously adjacent to the acquisition moment of the data value at the current moment in the high-adjustment data value, and recording the counted total number as the concentration degree of the production process parameters corresponding to the data value. For example, the current time is recorded as 0 time, and the time before the time to be analyzed is recordedThe respective moments are marked +.>Before the moment to be analyzed +.>The time points are respectively marked as the sequence of the acquisition time pointsWhen the high-adjustment data value contains the current time data value, if the time corresponding to the high-adjustment data value isStatistics of data values within the high-adjustment data value and at the current timeThe time of acquiring all data values whose time is consecutive is +.>I.e. a concentration of 6. And when the data value of the current moment is not contained in the data value of the high adjustment degree, assigning the concentration degree as a fourth preset threshold value. Wherein the empirical value of the fourth preset threshold is 1.
When the concentration is larger, the degree of the high-adjustment data value concentration is larger, and the probability that the production process parameter is the parameter needing to be adjusted is larger, and the adjustment amplitude is larger.
And obtaining the prominent concentration degree corresponding to the production process parameters according to the parameter adjustment degree, concentration degree and high adjustment degree data value corresponding to the production process parameters at the moment to be analyzed.
In the method, in the process of the invention,production process parameters for the moment to be analyzed>Corresponding prominence concentration; />For the production process parameters->The total number of high-adjustment data values contained in the corresponding production process parameter sequences; />For the production process parameters->Concentration of (3); />For the production process parameters->The corresponding production process parameter sequence is +.>Parameter adjustment corresponding to the high adjustment data value, wherein +.>。
In the method, in the process of the invention,for the production process parameters->Average value of parameter adjustment corresponding to all high adjustment data values contained in corresponding production process parameter sequences, < ->The ratio of the concentration ratio to the number of the data values of the high adjustment degree.
When the concentration degree of the production process parameters is larger, the average value of the parameter adjustment degrees corresponding to all the high adjustment degree data values contained in the production process parameter sequence is larger, and the ratio of the concentration degree to the number of the high adjustment degree data values is larger, the concentration degree is larger, namely the production process parameters are more likely to correspond to the production process parameters with larger adjustment amplitude.
So far, the salient concentration degree corresponding to all production process parameters at the moment to be analyzed is obtained.
And S004, acquiring parameter adjustment degrees corresponding to the production process parameters according to the prominence concentration degree, and acquiring adjustment parameter values of the production process parameters at the moment to be analyzed according to the parameter adjustment degrees.
And carrying out linear normalization on the salient concentration degree corresponding to all the production process parameters at the moment to be analyzed, and recording the normalized value as the parameter adjustment degree corresponding to the production process parameters.
When the parameter adjustment degree corresponding to the production process parameter is larger than or equal to a fifth preset threshold value, the production process parameter is considered unsuitable, larger adjustment is needed, and otherwise, the process parameter is considered suitable. Wherein the empirical value of the fifth preset threshold is 0.7.
When the production process parameters are unsuitable and larger adjustment is needed, the ARIMA time sequence model is used to makeAnd taking the data value of the production process parameter at the previous time of the time to be analyzed as the input of the model, obtaining the predicted value of the time to be analyzed, and taking the predicted value as the adjustment parameter value of the production process parameter at the time to be analyzed. When the process parameters are proper, the data value of the moment to be analyzed is used as the adjustment parameter value of the production process parameters of the moment to be analyzed. The prediction of the data using the ARIMA time series model is a well-known technique, and will not be described in detail.
So far, the adjustment parameter value of the production process parameter at the moment to be analyzed is obtained.
And S005, obtaining the self-adaptive set value of the production process parameters of the bag type packaging machine according to the adjustment parameter value corresponding to each production process parameter at the moment to be analyzed.
And inputting the production process parameter adjustment parameter value at the moment to be analyzed into a fuzzy PID controller, and obtaining the correction parameter value at the moment to be analyzed, wherein the correction parameter value at the moment to be analyzed is the self-adaptive setting value of the production process parameter of the bag type packaging machine at the next moment of the moment to be analyzed. The process of obtaining correction parameter values by a fuzzy PID controller is shown in fig. 2.
The fuzzy PID controller can utilize fuzzy logic to optimize parameters in real time according to fuzzy rules, and the process of acquiring correction parameter values at the moment to be analyzed by using the fuzzy PID controller is a known technology and will not be repeated.
And inputting the correction parameter value of the moment to be analyzed and the adjustment parameter value of the moment next to the moment to be analyzed into a fuzzy PID controller, and obtaining the correction parameter value of the moment next to the moment to be analyzed, wherein the correction parameter value of the moment next to the moment to be analyzed is the self-adaptive setting value of the production process parameter of the bag type packaging machine when the two moments after the moment to be analyzed. And repeating the steps to obtain the self-adaptive set value of the production process parameters of the bag type packaging machine at each moment to be analyzed.
Thus, the processing of the production process parameters of the bag type packaging machine is completed.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (10)
1. A method for processing production process parameters for a bag-type packaging machine, characterized in that the method comprises the steps of:
acquiring production process parameters of the bag type packaging machine, and acquiring a parameter sequence corresponding to each production process parameter at the moment to be analyzed;
acquiring parameter adjustment degrees corresponding to production process parameters according to data values contained in each production process parameter sequence at the moment to be analyzed;
acquiring a high-adjustment data value contained in each production process parameter sequence, acquiring the concentration degree of the production process parameters, and acquiring the prominent concentration degree corresponding to the production process parameters according to the parameter adjustment degree, the concentration degree and the high-adjustment data value corresponding to the production process parameters at the moment to be analyzed;
acquiring parameter adjustment degrees corresponding to production process parameters according to the prominence concentration degree, and acquiring adjustment parameter values of the production process parameters at the moment to be analyzed according to the parameter adjustment degrees;
and obtaining the self-adaptive setting value of the production process parameters of the bag type packaging machine according to the adjustment parameter value corresponding to each production process parameter at the moment to be analyzed.
2. The method of claim 1, wherein the process parameters include, but are not limited to, blanking quality, pressure, sealing temperature, host operating frequency, motor operating frequency, and packaging speed.
3. The method for processing parameters of bag-type packaging machine according to claim 1, wherein the step of obtaining the parameter sequence corresponding to each production parameter at the moment to be analyzed comprises the following specific steps:
acquiring data values of all production process parameters once every first preset threshold time;
respectively marking each time for acquiring the production process parameters as a time to be analyzed, marking the production process parameters of the second preset threshold secondary parameter acquisition time before the time to be analyzed as the production process parameters of the time before the time to be analyzed, and marking the production process parameters of the third preset threshold secondary parameter acquisition time after the time to be analyzed as the production process parameters of the time after the time to be analyzed;
respectively acquiring all data values contained in the previous production process parameters and the later production process parameters corresponding to each production process parameter at the moment to be analyzed, sequencing all the data values corresponding to each production process parameter according to the acquisition time of the data values, and acquiring a time sequence corresponding to each production process parameter;
and recording the time sequence corresponding to the production process parameters into a production process parameter sequence corresponding to the production process parameters.
4. The method for processing the production process parameters of the bag-type packaging machine according to claim 1, wherein the step of obtaining the parameter adjustment degree corresponding to the production process parameters according to the data value included in each production process parameter sequence at the time to be analyzed comprises the following specific steps:
acquiring information entropy of a production process parameter sequence at a moment to be analyzed;
acquiring the average value of all data values contained in a production process parameter sequence corresponding to the production process parameter at the moment to be analyzed;
the absolute value of the difference value between each data value in the production process parameter sequence at the moment to be analyzed and the average value of all the data values contained in the production process parameter sequence is recorded as the absolute difference value of the data values;
the sum of absolute differences of all data values in the production process parameter sequence is recorded as a first sum value;
the ratio of the absolute difference value of the data value at the moment to be analyzed to the first sum value is recorded as a first ratio;
and recording the product of the first ratio and the information entropy of the production process parameter sequence as the parameter adjustment degree corresponding to the production process parameter at the moment to be analyzed.
5. The method for processing the production process parameters for the bag-type packaging machine according to claim 1, wherein the step of obtaining the high-adjustment data value included in each production process parameter sequence comprises the following specific steps:
performing anomaly detection on all data values contained in the production process parameter sequence to obtain an anomaly value corresponding to each data value;
clustering the abnormal values of all the data values into two clusters by using a clustering algorithm;
and respectively acquiring the average value of all the abnormal values contained in each cluster, and marking the data value corresponding to all the abnormal values contained in the cluster with the largest average value as a high-adjustment data value.
6. The method for processing production process parameters for a bag-type packaging machine according to claim 1, wherein the obtaining the concentration of the production process parameters comprises the following specific steps:
judging whether the high-adjustment data value contains the data value at the current moment or not;
when the high-adjustment data value contains the data value at the current moment, counting the total number of all data values continuously adjacent to the acquisition moment of the data value at the current moment in the high-adjustment data value, and recording the counted total number as the concentration degree of the production process parameters corresponding to the data value;
and when the data value of the current moment is not contained in the data value of the high adjustment degree, assigning the concentration degree as a fourth preset threshold value.
7. The method for processing production process parameters of a bag-type packaging machine according to claim 1, wherein the obtaining the prominent concentration degree corresponding to the production process parameters according to the parameter adjustment degree, concentration degree and high adjustment degree data value corresponding to the production process parameters at the moment to be analyzed comprises the following specific steps:
the average value of the parameter adjustment degrees corresponding to all the high adjustment degree data values in the production process parameter sequence corresponding to the production process parameters is recorded as a first average value;
recording the ratio of the concentration of the production process parameters to the total number of the high-adjustment data values contained in the production process parameter sequence as a second ratio;
and (3) recording the product of the concentration of the production process parameters, the first average value and the second ratio as the prominent concentration corresponding to the production process parameters.
8. The method for processing production process parameters for a bag-type packaging machine according to claim 1, wherein the obtaining the parameter adjustment degree corresponding to the production process parameters according to the prominence concentration degree comprises the following specific steps:
and carrying out linear normalization on the salient concentration degree corresponding to all the production process parameters at the moment to be analyzed, and recording the normalized value of the salient concentration degree as the parameter adjustment degree corresponding to the production process parameters.
9. The method for processing parameters of bag-type packaging machine according to claim 1, wherein the step of obtaining the adjustment parameter value of the process parameter at the moment to be analyzed according to the parameter adjustment degree comprises the following specific steps:
when the parameter adjustment degree corresponding to the production process parameters is greater than or equal to a fifth preset threshold value, the production process parameters are considered to be unsuitable and need to be adjusted;
when the parameter adjustment degree corresponding to the production process parameters is smaller than a fifth preset threshold value, the process parameters are considered to be proper;
when the production process parameters are unsuitable and need to be adjusted, taking the data value of the production process parameters at the previous time of the time to be analyzed as the input of a prediction model, obtaining the predicted value of the time to be analyzed, and taking the predicted value of the time to be analyzed as the adjustment parameter value of the production process parameters at the time to be analyzed;
when the process parameters are proper, the data value of the moment to be analyzed is used as the adjustment parameter value of the production process parameters of the moment to be analyzed.
10. The method for processing production process parameters of a bag-type packaging machine according to claim 1, wherein the obtaining the self-adaptive setting value of the production process parameters of the bag-type packaging machine according to the adjustment parameter value corresponding to each production process parameter at the moment to be analyzed comprises the following specific steps:
inputting the production process parameter adjustment parameter value at the moment to be analyzed into a fuzzy PID controller, obtaining the correction parameter value at the moment to be analyzed, and recording the correction parameter value at the moment to be analyzed as the self-adaptive setting value of the production process parameter of the bag type packaging machine at the next moment of the moment to be analyzed;
inputting the correction parameter value of the moment to be analyzed and the adjustment parameter value of the moment next to the moment to be analyzed into a fuzzy PID controller, and obtaining the correction parameter value of the moment next to the moment to be analyzed, wherein the correction parameter value of the moment next to the moment to be analyzed is the self-adaptive setting value of the production process parameter of the bag type packaging machine when the correction parameter value of the moment next to the moment to be analyzed is the later two moments of the moment to be analyzed;
and obtaining the self-adaptive set value of the production process parameter of the bag type packaging machine when each moment to be analyzed.
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