Manufacturing process of brick-shaped aluminum foil with thickness of 6 microns for aseptic packaging

Abstract

The invention discloses a manufacturing process of a brick-shaped aluminum foil for aseptic packaging with the thickness of 6 microns, which comprises the following steps: raw material pretreatment, refining, cast rolling, finish rolling, cleaning and flattening, quality inspection and slitting, the finish rolling step is optimized, a laser thickness gauge is used for measuring the thickness of a cold-rolled multi-layer cast rolling plate blank to obtain a thickness value, and the thickness value of the cold-rolled multi-layer cast rolling plate blank is calculated; according to the obtained thickness value, whether thickness abnormity exists in the multi-layer cast-rolled plate blank in the cold rolling period or not is judged, a thickness abnormity time period is marked, the thickness fluctuation degree in the thickness abnormity time period is analyzed and judged, and a severe fluctuation time period is marked; data processing is carried out on the duration of the thickness abnormal time period and the severe fluctuation time period in the cold rolling period to obtain a cold rolling abnormal value, the abnormal degree in the cold rolling period is judged, a cold rolling abnormal signal or a regulation and control analysis signal is generated, and if the regulation and control analysis signal is generated, whether the thickness abnormal time period in the cold rolling period is periodical or not is evaluated; and the cold rolling mill is regulated and controlled according to the evaluation result, and the aluminum foil manufacturing quality and efficiency are improved.

Description

Technical Field

[0002] The invention relates to the technical field of aluminum foil production, and in particular to a production process of a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns. Background Art

[0004] Aluminum foil is widely used in aseptic packaging. Its moisture-proof, fresh-keeping and sterile properties make it an ideal choice for food packaging. Aluminum foil is particularly widely used in the packaging of dairy products such as milk. In the field of aluminum foil manufacturing, especially in the production process of aluminum foil for brick-shaped aseptic packaging with a thickness of only 6 microns, precise control of the thickness and surface quality of the aluminum foil is the key to ensuring product performance.

[0005] The traditional aluminum foil production process usually includes multiple steps such as raw material pretreatment, refining, casting and rolling, fine rolling, cleaning and leveling, quality inspection and slitting. When producing brick-shaped aseptic packaging aluminum foil with a thickness of only 6 microns, especially in the cold rolling stage, due to the extremely thin thickness of the aluminum foil, any slight thickness change may have a significant impact on the final quality and performance of the product.

[0006] In the prior art, during the cold rolling process, the multi-layer cast-rolled slab is rolled multiple times to achieve the required thickness. However, the cold-rolled aluminum foil often has the problem of uneven thickness. This uneven thickness not only reduces the mechanical properties and barrier properties of the aluminum foil, but may also cause defects such as leakage and rupture in the subsequent packaging process, thereby affecting the overall effect of aseptic packaging. In the prior art, thickness monitoring and control technology often has problems such as slow response speed and insufficient accuracy. It is impossible to accurately identify the abnormal thickness period within the cold rolling cycle, judge the degree of fluctuation, and generate corresponding control analysis signals according to the degree of abnormality. It is difficult to evaluate whether there is periodicity in the abnormal thickness period within the cold rolling cycle, so as to further optimize the rolling process and improve production efficiency and quality stability.

[0007] In view of the above problems, the present invention proposes a manufacturing process of a brick-shaped aluminum foil with a thickness of 6 microns for aseptic packaging. Summary of the invention

[0009] The object of the present invention is to provide a process for manufacturing a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns, so as to solve at least one of the above-mentioned prior art problems.

[0010] In the first aspect, the present invention provides a process for manufacturing a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns, comprising the steps of raw material pretreatment, refining, casting and rolling, finishing rolling, cleaning and leveling, quality inspection and slitting, wherein the finishing rolling step further comprises the following steps:

[0011] The thickness of the multi-layer cast-rolled slab produced by cold rolling is measured by a laser thickness gauge, and the thickness value is determined according to the obtained thickness value, whether the multi-layer cast-rolled slab has thickness abnormality during the cold rolling cycle, and the abnormal thickness period is marked;

[0012] Analyze the marked abnormal thickness period, construct the thickness difference sequence within the abnormal thickness period, perform data processing on the thickness difference sequence to obtain the fluctuation characterization value, judge the thickness fluctuation degree within the abnormal thickness period according to the obtained fluctuation characterization value, and mark the abnormal thickness period with severe fluctuation degree as the severe fluctuation period;

[0013] Obtain the duration of the thickness abnormality period and the severe fluctuation period in the cold rolling cycle, perform data processing on them to obtain the cold rolling abnormality value in the cold rolling cycle, judge the abnormality degree in the cold rolling cycle according to the cold rolling abnormality value, and generate a cold rolling abnormality signal or a control analysis signal;

[0014] Based on the generated control and analysis signal, the thickness change curve and the slope value sequence of the thickness change curve during the thickness abnormality period are constructed, the thickness difference sequence during the thickness abnormality period is obtained, the slope value sequence and the thickness difference sequence are analyzed, and it is evaluated whether there is periodicity in the thickness abnormality period within the cold rolling cycle, and the cold rolling mill is controlled according to the evaluation results.

[0015] In a second aspect, the present invention provides a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns, which is manufactured by the manufacturing process of the brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns.

[0016] Beneficial effects of the present invention:

[0017] 1. Through the thickness monitoring and abnormality judgment method during the cold rolling cycle described in the present invention, the thickness data of the multi-layer cast-rolled slab during the cold rolling process can be uniformly and accurately obtained. This method not only improves the accuracy and real-time performance of thickness measurement, but also effectively identifies and marks abnormal thickness periods, especially severe fluctuation periods, providing a reliable basis for subsequent regulation. By calculating the cold rolling abnormality value and generating the corresponding signal, accurate monitoring and timely regulation of the cold rolling process are achieved, which significantly improves the thickness uniformity and production quality of the aluminum foil, reduces the defective product rate, and provides a strong guarantee for the production of efficient and stable quality 6-micron brick-type aseptic packaging aluminum foil.

[0018] 2. The present invention constructs a thickness change curve and its slope value sequence, deeply analyzes the characteristics of the abnormal thickness period in the cold rolling cycle, especially its potential periodic law, and can accurately identify and respond to periodic thickness fluctuations through a detailed evaluation of the slope value sequence and the thickness difference sequence, thereby achieving targeted regulation of the cold rolling mill pressure parameters. This innovation not only significantly improves the thickness uniformity and stability of aluminum foil manufacturing, but also effectively reduces quality fluctuations in production, improves overall production efficiency and finished product quality, and provides strong support for lean production in the aluminum foil manufacturing industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 This is a flowchart of the steps of a manufacturing process of a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns provided by an embodiment of the present invention;

[0022] Figure 2 This is a flow chart of the steps for obtaining the fluctuation characterization value in the manufacturing process of a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns provided in the second embodiment of the present invention;

[0023] Figure 3 It is a flow chart of the steps for obtaining an abnormal time period group in a manufacturing process of a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns provided in Example 3 of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] Embodiment 1

[0027] The manufacturing process of a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns provided in an embodiment of the present invention specifically comprises the following steps:

[0028] S1. Raw material pretreatment: Select aluminum ingots with a purity of 99.6%, grind and chemically clean the surface to remove oil and oxide scale, and then put them into a resistance furnace for homogenization annealing at 550°C for 2.5 hours;

[0029] S2. Refining: The annealed aluminum ingot is melted in a melting furnace at 720°C, and a refining agent (composed of fluoride salt and chloride salt) accounting for 0.8% of the weight of the aluminum liquid is added to obtain aluminum liquid through refining;

[0030] S3, casting and rolling: using a continuous casting and rolling machine to cast and roll the aluminum liquid into a 6 mm thick slab, the casting and rolling roll temperature is set to 220° C., the casting and rolling speed is 1.2 m / s, and a cast and rolled slab is obtained;

[0031] S4, finishing rolling: Lubricating oil is evenly coated on both sides of the obtained cast-rolled slab, and multiple cast-rolled slabs are stacked together to obtain a multi-layer cast-rolled slab, and the multi-layer cast-rolled slab is pressed down and cold-rolled by a cold rolling mill, and cold rolling oil is added during cold rolling. The number of cold rolling passes is more than 4, and the amount of each pass is 30-50% of the total thickness before cold rolling, until the thickness of each layer of the multi-layer cast-rolled slab reaches a final thickness of 6 microns, thereby obtaining a multi-layer aluminum foil;

[0032] S5, cleaning and leveling: separating the multi-layer aluminum foil to obtain a single-layer aluminum foil, using an ultrasonic cleaning machine to clean the single-layer aluminum foil, the cleaning liquid is a mixture of deionized water and a special cleaning agent with a mass concentration of 4%, and the cleaned single-layer aluminum foil is leveled at a leveling pressure of 80MPa, and the leveling amount is 0.2%; the leveled single-layer aluminum foil is quality tested to obtain a finished aluminum foil;

[0033] S6. Quality inspection and slitting: The single-layer aluminum foil after cleaning and leveling is subjected to quality inspection to obtain aluminum foil waste and aluminum foil finished products. The finished aluminum foil is slit according to the required dimensions of the brick-shaped aseptic packaging unfolding design drawing. The width error is controlled at ±0.08 mm to obtain aluminum foil for brick-shaped aseptic packaging. The aluminum foil for brick-shaped aseptic packaging produced is packaged with aluminum-plastic composite film in an environment of 35% humidity and 22°C temperature.

[0034] Embodiment 2

[0035] like Figure 1 As shown, the manufacturing process of a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns provided in the embodiment of the present invention optimizes the finishing step described in the first embodiment, and specifically includes the following steps:

[0036] Step 1, evenly taking a number of detection time points with the same distance in the cold rolling cycle, measuring the thickness of the cold-rolled multi-layer cast-rolled slab by a laser thickness gauge, obtaining the thickness value at each detection time point, judging whether the multi-layer cast-rolled slab has thickness abnormality in the cold rolling cycle according to the obtained thickness value, and marking the period when the thickness abnormality occurs as the thickness abnormality period;

[0037] In some embodiments, lubricating oil is evenly coated on both sides of the obtained cast-rolled slab, and multiple cast-rolled slabs are stacked together to obtain a multi-layer cast-rolled slab. The cold rolling mill is started and allowed to rotate without load for 5-10 minutes to ensure that the machine runs smoothly. The multi-layer cast-rolled slab is placed on the conveying roller to ensure that the placement position is correct.

[0038] A laser thickness gauge is installed at the exit of the cold rolling mill, and several thickness detection points are set in the width direction of the multi-layer cast-rolled slab. The thickness detection points are composed of a laser transmitter and a receiving head, and are evenly and symmetrically distributed along the center line of the multi-layer cast-rolled slab. The positions of the laser transmitter and the receiving head are adjusted so that the laser beam is perpendicular to the surface of the multi-layer cast-rolled slab;

[0039] The cold rolling mill is turned on to start cold rolling of the multi-layer cast slab;

[0040] At the same time, the measuring program of the laser thickness gauge is started, the time required for one cold rolling pass of the multi-layer cast-rolled slab is marked as the cold rolling cycle, a number of detection time points are evenly taken in the cold rolling cycle, the intervals between the adjacent detection time points are the same, and at each detection time point, the thickness of the cold-rolled multi-layer cast-rolled slab is measured in real time through the thickness detection point of the laser thickness gauge;

[0041] Based on any detection time point, the thickness values ​​measured at all thickness detection points within the detection time point are summed and averaged to obtain the thickness value of the cold-rolled multi-layer cast-rolled slab at the detection time point, the thickness value is subtracted from the thickness standard value and the absolute value is taken to obtain the absolute thickness difference, and the obtained absolute thickness difference is compared with the absolute thickness difference threshold;

[0042] If the absolute thickness difference is less than or equal to the absolute thickness difference threshold, it means that the thickness of the multi-layer cast slab produced by cold rolling is normal, and a normal thickness signal is generated;

[0043] If the absolute thickness difference is greater than the absolute thickness difference threshold, it means that the thickness value of the multi-layer cast slab produced by cold rolling is abnormal, and a thickness abnormality signal is generated;

[0044] Take a Flag value and assign its initial value to 0. Based on any detection time point, if a thickness abnormality signal is generated and the Flag value is 0, the Flag value is set to 1. If a thickness normal signal is generated, the Flag value is set to 0. The period when the Flag is 1 is marked as the thickness abnormality period.

[0045] It should be noted that the purpose of setting the Flag value is to mark the start and end of the thickness abnormality period;

[0046] Analyze all thickness abnormality periods in the cold rolling cycle to obtain the duration of the interval period between adjacent thickness abnormality periods, where the interval period represents the interval period between the end point of the previous thickness abnormality period and the starting point of the next thickness abnormality period;

[0047] Comparing the duration of the interval period with the interval duration threshold;

[0048] If the duration of the interval between adjacent thickness abnormality periods is greater than or equal to the interval duration threshold, it is determined that the thickness value changes smoothly between the two thickness abnormality periods;

[0049] If the duration of the interval between adjacent thickness abnormal time periods is less than the interval duration threshold, it is determined that the thickness value changes dramatically between the two thickness abnormal time periods, and the two thickness abnormal time periods and the interval period are combined into one thickness abnormal time period;

[0050] The above operation is performed on all adjacent abnormal thickness time periods in the cold rolling cycle until the duration of the interval between no adjacent abnormal time periods is less than the interval duration threshold;

[0051] Step 2: Analyze the marked abnormal thickness period, construct a thickness difference sequence within the abnormal thickness period, perform data processing on the thickness difference sequence to obtain a fluctuation characterization value, judge the thickness fluctuation degree within the abnormal thickness period according to the obtained fluctuation characterization value, and mark the abnormal thickness period with severe fluctuation as a severe fluctuation period;

[0052] like Figure 2 As shown, the specific steps for obtaining the fluctuation characterization value are:

[0053] In some embodiments, based on any thickness abnormality period, the absolute thickness differences within the thickness abnormality period are arranged in the time sequence of the detection time points to construct a thickness difference sequence within the thickness abnormality period:

[0054]

[0055] Where n is the total number of detection time points in the thickness abnormality period, and i represents the sequence number of the thickness abnormality period in chronological order within the cold rolling cycle;

[0056] Based on any thickness difference sequence, obtain the mean μ of the thickness difference sequence, using the standard deviation formula:

[0057]

[0058] Calculate the standard deviation of the thickness difference series within the cold rolling cycle ;

[0059] The total number of detection time points n in the thickness abnormality period is obtained, and the total number of detection time points in the cold rolling cycle is compared with the total number of detection time points to obtain the sequence length ratio of the thickness difference sequence, which is marked as XC;

[0060] The standard deviation of the obtained Data processing is performed with the sequence length ratio XC, using the formula:

[0061]

[0062] The fluctuation characterization value BD of the thickness difference sequence is calculated, where a1 and a2 are both preset proportional coefficients, a1=1.423, a2=3.579;

[0063] Compare the obtained fluctuation characterization value with the fluctuation characterization threshold:

[0064] If the fluctuation characterization value of the thickness difference sequence is less than or equal to the fluctuation characterization threshold, it is judged that the fluctuation degree of the thickness difference sequence is light;

[0065] If the fluctuation characterization value of the thickness difference sequence is greater than the fluctuation characterization threshold, it is judged that the fluctuation degree of the thickness difference sequence is severe, and the thickness abnormal period corresponding to the thickness difference sequence is marked as a severe fluctuation period;

[0066] Step 3: Obtain the duration of the thickness abnormality period and the severe fluctuation period in the cold rolling cycle, perform data processing on them to obtain the cold rolling abnormality value in the cold rolling cycle, judge the abnormality degree in the cold rolling cycle according to the cold rolling abnormality value, and generate a cold rolling abnormality signal or a control analysis signal;

[0067] In some embodiments, the sum of the durations of all thickness abnormality periods in the cold rolling cycle is obtained, and the sum is processed by ratio with the total duration of the cold rolling cycle to obtain the abnormal duration ratio in the cold rolling cycle, which is marked as YS;

[0068] The sum of the durations of all severe fluctuation periods in the cold rolling cycle is obtained, and the sum is ratioed with the total duration of the cold rolling cycle to obtain the severe fluctuation ratio in the cold rolling cycle, which is marked as ZB;

[0069] The obtained abnormal duration ratio YS and severe fluctuation ratio ZB are processed by the formula:

[0070]

[0071] The cold rolling abnormal value BS within the cold rolling cycle is calculated, where b1 and b2 are both preset proportional coefficients, b1=3.214, b2=2.131;

[0072] The obtained cold rolling abnormal value is compared with the cold rolling abnormal threshold value;

[0073] If the cold rolling abnormality value of the cold rolling cycle is greater than or equal to the cold rolling abnormality threshold, it is judged that the abnormality degree in the cold rolling cycle is high, and a cold rolling abnormality signal is generated;

[0074] If the cold rolling abnormality value of the cold rolling cycle is less than the cold rolling abnormality threshold, it is judged that the abnormality level in the cold rolling cycle is low, and a control analysis signal is generated;

[0075] It should be noted that when the abnormality level in the cold rolling cycle is low, the multi-layer cast-rolled slab can still be made to reach the expected thickness uniformly by adjusting the cold rolling mill parameters, thus generating a control analysis signal. When the abnormality level in the cold rolling cycle is too high, it indicates that the cold rolling mill may be damaged or the error is too large. At this time, adjusting the cold rolling mill parameters can no longer make the multi-layer cast-rolled slab reach the expected thickness uniformly.

[0076] Based on the generated abnormal cold rolling signal, the production process of the cold rolling mill is suspended, and maintenance personnel are arranged to inspect the cold rolling mill;

[0077] The technical solution of the embodiment of the present invention is: uniformly taking a number of detection time points with the same distance in the cold rolling cycle, measuring the thickness of the cold-rolled multi-layer cast-rolled slab by a laser thickness gauge, obtaining the thickness value at each detection time point, judging whether there is thickness abnormality in the multi-layer cast-rolled slab in the cold rolling cycle according to the obtained thickness value and marking the thickness abnormality period; analyzing the marked thickness abnormality period, judging the thickness fluctuation degree in the thickness abnormality period, and marking the thickness abnormality period with severe fluctuation as a severe fluctuation period; obtaining the duration of the thickness abnormality period and the severe fluctuation period in the cold rolling cycle, performing data processing on them to obtain the cold rolling abnormality value in the cold rolling cycle, judging the abnormality degree in the cold rolling cycle according to the cold rolling abnormality value and generating a cold rolling abnormality signal or a control analysis signal.

[0078] Embodiment 3

[0079] like Figure 1 As shown, the manufacturing process of a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns provided in the embodiment of the present invention optimizes the finishing step described in the first embodiment, and specifically includes the following steps:

[0080] Step 4: Based on the generated control analysis signal, a thickness change curve and a slope value sequence of the thickness change curve in the thickness abnormal period are constructed, a thickness difference sequence of the thickness abnormal period is obtained, the slope value sequence and the thickness difference sequence are analyzed to obtain a similar performance value, and the thickness abnormal periods with high similarity are classified into an abnormal period group according to the similar performance value, and the abnormal period group is analyzed to evaluate whether there is periodicity in the thickness abnormal period in the cold rolling cycle, and the pressure parameters of the cold rolling mill are regulated according to the evaluation results;

[0081] like Figure 3 As shown, the specific steps for obtaining the abnormal time period group are:

[0082] In some embodiments, based on the generated control analysis signal, a thickness variation curve is constructed with time as the abscissa and the thickness value of the multi-layer cast slab produced by cold rolling as the ordinate;

[0083] Based on any abnormal thickness period, obtain the slope value of the thickness change curve in the abnormal thickness period at the detection time point, arrange the slope values ​​in the abnormal thickness period in the time sequence of the detection time points, and construct a slope value sequence in the abnormal thickness period:

[0084]

[0085] Where n is the total number of detection time points in the thickness abnormality period, and i represents the sequence number of the thickness abnormality period in chronological order within the cold rolling cycle;

[0086] Any two equal-length slope value sequences in the cold rolling cycle are analyzed;

[0087] In some embodiments, if the thickness abnormality time periods corresponding to the two slope value sequences are numbered c and m respectively in chronological order within the cold rolling cycle, the two slope value sequences are Kc and Km respectively;

[0088] The two slope value sequences are regarded as points in a multidimensional space, where each dimension represents an element in the sequence, and the Manhattan distance is calculated using the formula:

[0089]

[0090] Calculate the Manhattan distance DK between the two slope value sequences;

[0091] Similarly, the thickness difference sequence within the cold rolling cycle is obtained, and any two thickness difference sequences of equal length within the cold rolling cycle are analyzed;

[0092] In some embodiments, if the thickness anomaly time periods corresponding to the two thickness difference sequences are numbered c and m in chronological order within the cold rolling cycle, the two slope value sequences are Hc and Hm respectively;

[0093] The two thickness difference sequences are regarded as points in a multidimensional space, where each dimension represents an element in the sequence, and the Manhattan distance is calculated using the formula:

[0094]

[0095] The Manhattan distance DH of the two thickness difference sequences is calculated;

[0096] Based on any two thickness anomaly periods of equal duration, the Manhattan distance DK of the slope value sequence and the Manhattan distance DH of the thickness difference sequence of the two thickness anomaly periods are obtained and summed to obtain the similarity performance value DX of the two thickness anomaly periods;

[0097] comparing the similarity performance value to a similarity performance threshold;

[0098] If the similarity performance value of the two thickness abnormality periods is greater than or equal to the similarity performance threshold, it means that the two thickness abnormality periods are not similar;

[0099] If the similarity performance value of two thickness abnormal periods is less than the similarity performance threshold, it means that the two thickness abnormal periods are similar, and the two thickness abnormal periods are classified into one abnormal period group;

[0100] The above operation is performed on all thickness abnormal time periods in the cold rolling cycle. If there is a thickness abnormal time period in the cold rolling cycle that is not classified into any abnormal time period group, the thickness abnormal time period itself is classified into an abnormal time period group and the abnormal time period group is marked as an unordered time period group.

[0101] Based on any abnormal time period group, the interval durations between the starting points of all adjacent thickness abnormal time periods in the abnormal time period group are obtained, and variance processing is performed on them to obtain the interval duration variance;

[0102] Compare the interval duration variance with the variance threshold;

[0103] If the interval time variance is greater than or equal to the variance threshold, it means that there is no time regularity in the thickness abnormal time period in the abnormal time period group, and the abnormal time period group is marked as a disordered time period group;

[0104] If the interval time variance is less than the variance threshold, it means that the thickness abnormal time period in the abnormal time period group has periodicity, and the abnormal time period group is marked as an ordered time period group;

[0105] Based on the marked ordered time period group, the intervals between the starting points of all adjacent thickness anomaly time periods in the ordered time period group are summed and averaged to obtain the ordered period of the ordered time period group;

[0106] Obtain the ordered cycles of all ordered time period groups in the cold rolling cycle and perform variance processing to obtain the ordered cycle variance, which is marked as ZF;

[0107] Obtain the number of all disordered time period groups in the cold rolling cycle, and perform ratio processing on it and the number of all abnormal time period groups in the cold rolling cycle to obtain the disordered number ratio, which is marked as WS;

[0108] The obtained ordered period variance ZF and disordered number ratio WS are processed by the formula: The disorder performance value FW in the cold rolling cycle is calculated, where s1 and s2 are both preset proportional coefficients, s1=1.427, s2=3.146;

[0109] Compare the obtained disorder performance value with the disorder performance threshold;

[0110] If the disorder performance value is greater than or equal to the disorder performance threshold, it means that there is no time regularity in the thickness abnormal period within the cold rolling cycle, and a disorder signal is generated;

[0111] If the disorder performance value is less than the disorder performance threshold, it indicates that there is periodicity in the thickness anomaly period during the cold rolling cycle, and an ordered signal is generated;

[0112] Based on the generated ordered signal, the ordered periods of all ordered time period groups in the cold rolling cycle are summed and averaged to obtain the change period of thickness change in the cold rolling cycle;

[0113] Based on the generated ordered signal and the change cycle, the pressure parameters of the cold rolling mill are periodically regulated in the next cold rolling. Based on the generated disordered signal, the staff are arranged to manually regulate the pressure parameters of the cold rolling mill in the next cold rolling, so as to prevent the aluminum foil of the expected thickness from not being obtained after cold rolling or the aluminum foil of unqualified quality due to the uneven cold rolling thickness of the multi-layer cast-rolled slab, thereby improving the quality and efficiency of aluminum foil manufacturing;

[0114] The technical solution of the embodiment of the present invention is: based on the generated control and analysis signal, a thickness change curve and a slope value sequence of the thickness change curve in the thickness abnormality period are constructed, a thickness difference sequence in the thickness abnormality period is obtained, the slope value sequence and the thickness difference sequence are analyzed, and it is evaluated whether there is periodicity in the thickness abnormality period in the cold rolling cycle, and the pressure parameters of the cold rolling mill are regulated according to the evaluation results to improve the quality and efficiency of aluminum foil manufacturing.

[0115] Embodiment 4

[0116] The present invention is a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns, which is made by using the manufacturing process of the brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns.

[0117] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0118] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A process for producing a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns, characterized in that: The process includes raw material pretreatment, refining, casting and rolling, finishing rolling, cleaning and leveling, quality inspection and slitting, wherein the finishing rolling step includes the following steps: The thickness of the multi-layer cast-rolled slab produced by cold rolling is measured by a laser thickness gauge, and the thickness value is determined according to the obtained thickness value, whether the multi-layer cast-rolled slab has thickness abnormality during the cold rolling cycle, and the abnormal thickness period is marked; Analyze the marked abnormal thickness period, construct the thickness difference sequence within the abnormal thickness period, perform data processing on the thickness difference sequence to obtain the fluctuation characterization value, judge the thickness fluctuation degree within the abnormal thickness period according to the obtained fluctuation characterization value, and mark the abnormal thickness period with severe fluctuation degree as the severe fluctuation period; Obtain the duration of the thickness abnormality period and the severe fluctuation period in the cold rolling cycle, perform data processing on them to obtain the cold rolling abnormality value in the cold rolling cycle, judge the abnormality degree in the cold rolling cycle according to the cold rolling abnormality value, and generate a cold rolling abnormality signal or a control analysis signal; Based on the generated control and analysis signal, the thickness change curve and the slope value sequence of the thickness change curve during the thickness abnormality period are constructed, the thickness difference sequence during the thickness abnormality period is obtained, the slope value sequence and the thickness difference sequence are analyzed, and it is evaluated whether there is periodicity in the thickness abnormality period within the cold rolling cycle, and the cold rolling mill is controlled according to the evaluation results.

2. The process for producing a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns according to claim 1, characterized in that: The specific method for obtaining the abnormal thickness period is: Take a Flag value and assign its initial value to 0. Based on any detection time point, if a thickness abnormality signal is generated and the Flag value is 0, the Flag value is set to 1. If a thickness normal signal is generated, the Flag value is set to 0. The period when the Flag is 1 is marked as the thickness abnormality period. Analyze all thickness abnormality periods in the cold rolling cycle to obtain the duration of the interval period between adjacent thickness abnormality periods, where the interval period represents the interval period between the end point of the previous thickness abnormality period and the starting point of the next thickness abnormality period; Comparing the duration of the interval period with the interval duration threshold; If the duration of the interval between adjacent thickness abnormal time periods is less than the interval duration threshold, it is determined that the thickness value changes dramatically between the two thickness abnormal time periods, and the two thickness abnormal time periods and the interval period are combined into one thickness abnormal time period; All adjacent thickness abnormal time periods in the cold rolling cycle are analyzed until the duration of the interval between no adjacent abnormal time periods is less than the interval duration threshold.

3. The process for producing a brick-shaped aluminum foil with a thickness of 6 microns for aseptic packaging according to claim 2, characterized in that: The specific method of obtaining the abnormal thickness signal and the normal thickness signal is as follows: The time required for one cold rolling pass of the multi-layer cast-rolled slab is marked as a cold rolling cycle, and a number of detection time points are evenly taken in the cold rolling cycle, and the intervals between adjacent detection time points are the same. At each detection time point, the thickness of the cold-rolled multi-layer cast-rolled slab is measured in real time through the thickness detection point of the laser thickness gauge; Based on any detection time point, the thickness values ​​measured at all thickness detection points within the detection time point are summed and averaged to obtain the thickness value of the cold-rolled multi-layer cast-rolled slab at the detection time point, the thickness value is subtracted from the thickness standard value and the absolute value is taken to obtain the absolute thickness difference, and the obtained absolute thickness difference is compared with the absolute thickness difference threshold; If the absolute thickness difference is less than or equal to the absolute thickness difference threshold, it means that the thickness of the multi-layer cast slab produced by cold rolling is normal, and a normal thickness signal is generated; If the absolute thickness difference is greater than the absolute thickness difference threshold, it means that the thickness value of the multi-layer cast slab produced by cold rolling is abnormal, and a thickness abnormality signal is generated.

4. The process for producing a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns according to claim 1, characterized in that: The specific method of obtaining the severe fluctuation period is as follows: Compare the obtained fluctuation characterization value with the fluctuation characterization threshold: If the fluctuation characterization value of the thickness difference sequence is greater than the fluctuation characterization threshold, it is judged that the fluctuation degree of the thickness difference sequence is severe, and the thickness abnormal period corresponding to the thickness difference sequence is marked as a severe fluctuation period.

5. The process for producing a brick-shaped aluminum foil with a thickness of 6 microns for aseptic packaging according to claim 4 is characterized in that: The specific method of obtaining the fluctuation characterization value is: Based on any abnormal thickness period, the absolute thickness difference within the abnormal thickness period is arranged in the time order of the detection time points to construct a thickness difference sequence within the abnormal thickness period. Based on any thickness difference sequence, the standard deviation of the thickness difference sequence is calculated. ; The total number of detection time points n in the thickness abnormality period is obtained, and the total number of detection time points in the cold rolling cycle is compared with the total number of detection time points to obtain the sequence length ratio of the thickness difference sequence, which is marked as XC; The standard deviation of the obtained The data is processed with the sequence length ratio XC, and the fluctuation characterization value BD of the thickness difference sequence is calculated by the formula.

6. The process for making a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns according to claim 1 is characterized in that: The specific method for judging the abnormality degree in the cold rolling cycle is: The sum of the durations of all thickness abnormality periods in the cold rolling cycle is obtained, and the sum is ratioed to the total duration of the cold rolling cycle to obtain the abnormal duration ratio in the cold rolling cycle, which is marked as YS; The sum of the durations of all severe fluctuation periods in the cold rolling cycle is obtained, and the sum is ratioed with the total duration of the cold rolling cycle to obtain the severe fluctuation ratio in the cold rolling cycle, which is marked as ZB; The obtained abnormal duration ratio YS and severe fluctuation ratio ZB are processed, and the cold rolling abnormal value BS within the cold rolling cycle is calculated by the formula; The obtained cold rolling abnormal value is compared with the cold rolling abnormal threshold value; If the cold rolling abnormality value of the cold rolling cycle is greater than or equal to the cold rolling abnormality threshold, it is judged that the abnormality degree in the cold rolling cycle is high, and a cold rolling abnormality signal is generated; If the cold rolling abnormality value of the cold rolling cycle is less than the cold rolling abnormality threshold, it is judged that the abnormality degree in the cold rolling cycle is low, and a control analysis signal is generated.

7. The process for producing a brick-shaped aluminum foil with a thickness of 6 microns for aseptic packaging according to claim 1, characterized in that: The specific method for evaluating whether there is periodicity in the abnormal thickness period during the cold rolling cycle is: Based on the marked ordered time period group, the intervals between the starting points of all adjacent thickness anomaly time periods in the ordered time period group are summed and averaged to obtain the ordered period of the ordered time period group; Obtain the ordered cycles of all ordered time period groups in the cold rolling cycle and perform variance processing to obtain the ordered cycle variance, which is marked as ZF; Obtain the number of all disordered time period groups in the cold rolling cycle, and perform ratio processing on it and the number of all abnormal time period groups in the cold rolling cycle to obtain the disordered number ratio, which is marked as WS; The obtained ordered cycle variance ZF and disordered number ratio WS are processed, and the disordered performance value FW in the cold rolling cycle is calculated by the formula; Compare the obtained disorder performance value with the disorder performance threshold; If the disorder performance value is greater than or equal to the disorder performance threshold, it means that there is no time regularity in the thickness abnormal period within the cold rolling cycle, and a disorder signal is generated; If the disorder performance value is less than the disorder performance threshold, it means that there is periodicity in the thickness anomaly period within the cold rolling cycle, and an ordered signal is generated.

8. The process for making a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns according to claim 7, characterized in that: The specific method of obtaining the ordered time period group and the disordered time period group is as follows: Based on any abnormal time period group, the interval durations between the starting points of all adjacent thickness abnormal time periods in the abnormal time period group are obtained, and variance processing is performed on them to obtain the interval duration variance; Compare the interval duration variance with the variance threshold; If the interval time variance is greater than or equal to the variance threshold, or there is only one thickness abnormal period in the abnormal period group, it means that there is no time regularity in the thickness abnormal period in the abnormal period group, and the abnormal period group is marked as a disordered period group; If the interval time variance is less than the variance threshold, it means that the thickness abnormal time period in the abnormal time period group has periodicity, and the abnormal time period group is marked as an ordered time period group.

9. The process for producing a brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns according to claim 8, characterized in that: The specific method of obtaining the abnormal time period group is as follows: Based on the generated control analysis signal, a thickness variation curve is constructed with time as the horizontal coordinate and the thickness value of the multi-layer cast slab produced by cold rolling as the vertical coordinate; Based on any thickness abnormality period, the slope value of the thickness change curve in the thickness abnormality period at the detection time point is obtained, the slope values ​​in the thickness abnormality period are arranged in the time sequence of the detection time points, and a slope value sequence in the thickness abnormality period is constructed; Any two slope value sequences of equal length in the cold rolling cycle are analyzed, and the two slope value sequences are regarded as points in a multidimensional space, where each dimension represents an element in the sequence. The Manhattan distance DK of the two slope value sequences is calculated using the Manhattan distance calculation formula; Similarly, the thickness difference sequence in the cold rolling cycle is obtained, and any two thickness difference sequences of equal length in the cold rolling cycle are analyzed, and the Manhattan distance DH of the two thickness difference sequences is calculated by the Manhattan distance calculation formula; Based on any two thickness anomaly periods of equal duration, the Manhattan distance DK of the slope value sequence and the Manhattan distance DH of the thickness difference sequence of the two thickness anomaly periods are obtained and summed to obtain the similarity performance value DX of the two thickness anomaly periods; comparing the similarity performance value to a similarity performance threshold; If the similarity performance value of two thickness abnormal periods is less than the similarity performance threshold, it means that the two thickness abnormal periods are similar, and the two thickness abnormal periods are classified into one abnormal period group; All thickness abnormality periods in the cold rolling cycle are analyzed. If there is a thickness abnormality period in the cold rolling cycle that is not classified into any abnormal period group, the thickness abnormality period itself is classified into an abnormal period group.

10. A brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns, characterized in that: The brick-shaped aluminum foil for aseptic packaging with a thickness of 6 microns is produced by the production process described in any one of claims 1 to 9.

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