A method and system for controlling the inflation of an injection blow molding machine

Abstract

The present invention relates to the technical field of inflation control of a molding machine, and discloses an inflation control method and system of an injection blow molding machine, comprising the following steps: Step 1: Obtain the expansion data of the mold parison during the inflation process, analyze the obtained inflation data, and calculate the inflation uniformity evaluation value; wherein the inflation data is the inflation size of the mold parison during the inflation process. The present invention first obtains the inflation size change values ​​of multiple measurement points at multiple measurement time points during the inflation process, calculates the inflation size change deviation value based on the inflation size change value, and then calculates the inflation uniformity evaluation value based on the inflation size change deviation value, and judges whether the expansion of the mold parison is uniform at each measurement time point, so that the inflation uniformity of the mold parison can be monitored during the inflation process, the quality of the product during the inflation process can be timely understood, and timely adjustments can be made when unevenness is detected, thereby improving the inflation efficiency.

Description

Technical Field

[0001] The invention relates to the technical field of inflation control of a molding machine, and in particular to an inflation control method and system of an injection blow molding machine. Background Art

[0002] The basic principle of hollow molding technology is to place the preform in a plastic state in the mold cavity, and blow the preform into a swelled shape by introducing compressed air, and then cool it down to shape it, finally obtaining a hollow plastic product. Based on this, the injection blow molding machine combines injection molding with blow molding, and completes the molding of the product in one process, which significantly improves production efficiency and product quality.

[0003] However, in the current traditional injection blow molding machines, the inflation control mainly relies on the operator's experience and adjustment. The inflation size during the injection blow molding process cannot be monitored in real time, and the uniformity of the inflation cannot be evaluated, which will affect the final dimensional accuracy and appearance quality of the product. At the same time, the relationship between the inflation speed and the inflation uniformity cannot be predicted and adjusted, which leads to the inability to make timely adjustments to abnormal situations during the injection blow molding process. Summary of the invention

[0004] The object of the present invention is to provide a method and system for controlling the inflation of an injection blow molding machine, so as to solve the problem in the above background that there is no monitoring system for the expansion uniformity and inflation speed during the inflation process.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A method and system for controlling the expansion of an injection blow molding machine, comprising the following steps: Step 1: obtaining the expansion data of a parison during the expansion process, analyzing the obtained expansion data, and calculating an expansion uniformity evaluation value; wherein the expansion data is the expansion size of the parison during the expansion process; Step 2: comparing the expansion uniformity evaluation value with the expansion uniformity evaluation threshold, and if the expansion uniformity evaluation value is greater than the expansion uniformity evaluation threshold, generating an expansion non-uniformity signal; Step 3: based on the above-obtained expansion non-uniformity signal, obtaining the blowing speed data, analyzing the obtained blowing speed data, calculating the blowing speed characterization value, and making a judgment to generate an abnormal blowing speed signal; Step 4: based on the above-mentioned abnormal blowing speed signal, judging whether the uneven expansion of the parison is related to the abnormal blowing speed, calculating the abnormal synchronous influence value, and making a judgment to generate an influence signal; Step 5: based on the above-mentioned influence signal, obtaining the expansion uniformity value and the blowing speed characterization value during the expansion process, analyzing whether there are other influencing factors affecting the expansion uniformity, generating a signal with no other influence, and establishing a prediction model based on the signal with no other influence.

[0007] As a further solution of the present invention: the process of obtaining the expansion uniformity evaluation value is:

[0008] Obtain the number of values ​​marked as abnormal deviation values ​​and the number of measurement points corresponding to the measurement time, perform ratio processing on the number of values ​​marked as abnormal deviation values ​​and the number of measurement points corresponding to the measurement time, and obtain the unstable ratio BW;

[0009] The maximum value among the abnormal deviation values ​​is extracted, and the ratio is calculated between it and the expansion size change deviation threshold to obtain the abnormal maximum deviation ratio YD;

[0010] Substitute the unstable proportion BW and the abnormal maximum deviation ratio YD into the formula , the expansion uniformity evaluation value JX is calculated, where a and b are weight coefficients, and a+b=1, a>b.

[0011] As a further solution of the present invention: the process of obtaining the abnormal deviation value is:

[0012] The total time of the inflation process is divided into several measuring time points, two adjacent measuring time points are marked as one measuring period, and multiple measuring points are marked on the parison;

[0013] At each measuring time point, the expansion dimensions of the parison at all measuring points are obtained, and the expansion dimension change values ​​of multiple measuring points in each measuring period are calculated;

[0014] In the same measurement time, the expansion size change values ​​of each measurement point are summed and averaged to obtain the expansion size change mean value, and the expansion size change value of each measurement point is calculated to differ from the expansion size change mean value to obtain the absolute value of the difference, which is marked as the expansion size change deviation value;

[0015] comparing the expansion size change deviation value with the expansion size change deviation threshold;

[0016] If the expansion size change deviation value is greater than the expansion size change deviation threshold, it is marked as an abnormal deviation value.

[0017] As a further solution of the present invention: the process of obtaining the blowing speed characterization value is:

[0018] Obtain the inflation speed during the inflation process, establish a two-dimensional model with time as the X-axis and the inflation speed as the Y-axis, substitute the inflation speed into the two-dimensional model, draw a inflation speed curve, and draw a standard line parallel to the X-axis with the maximum value and the minimum value of the inflation speed range threshold as the standard value, respectively, and mark them as the first standard line and the second standard line respectively;

[0019] The portion of the inflation speed curve that is above the first standard line and below the second standard line is marked as an abnormal inflation speed region, and the portion of the inflation speed curve that is below the first standard line and above the second standard line is marked as a normal inflation speed region;

[0020] In each measurement period, the abnormal area time period is obtained, the obtained abnormal area time period is summed up to obtain the total value of the abnormal area time period, and the total value of the abnormal area time period is ratioed with the time value of the measurement period to obtain the abnormal time proportion of the inflation speed;

[0021] In each measurement period, the extreme value of the blowing speed in the abnormal area is extracted, the difference between the extreme value of the blowing speed and the standard value of the blowing speed is calculated, the absolute value of the difference is calculated by ratio with the standard value of the blowing speed to obtain the abnormal deviation ratio of the blowing speed, and the abnormal deviation ratios of the blowing speed in all abnormal areas are summed to obtain the abnormal degree ratio of the blowing speed;

[0022] The blowing speed characterization value is calculated by multiplying the blowing speed abnormality time ratio and the blowing speed abnormality degree ratio.

[0023] As a further solution of the present invention: the process of generating the abnormal blowing speed signal is:

[0024] Obtaining a blowing speed characterization value of each measuring period, and comparing the blowing speed characterization value of each measuring period with a blowing speed characterization threshold;

[0025] If the blowing speed characterization value is greater than the blowing speed characterization threshold, a blowing speed abnormality signal is generated.

[0026] As a further solution of the present invention: the process of obtaining the abnormal synchronization impact value is:

[0027] Obtaining a time period for generating a blowing speed abnormality signal and a time period for generating a non-uniform expansion signal;

[0028] Calculate the overlapping time period of abnormal blowing speed and uneven expansion and the number of overlapping time periods;

[0029] The total time value of the overlapping time period is multiplied by the number of overlapping time periods to calculate the abnormal synchronization impact value.

[0030] As a further solution of the present invention: the process of generating the influence signal is:

[0031] Get the abnormal synchronization impact value;

[0032] comparing the abnormal synchronization impact value with an abnormal synchronization impact threshold;

[0033] If the abnormal synchronization impact value is greater than the abnormal synchronization impact value, an impact signal is generated.

[0034] As a further solution of the present invention: the process of generating a signal without other influences is:

[0035] Obtain the expansion uniformity value and the blowing speed characterization value corresponding to each measurement time point in the overlapping time period;

[0036] The expansion uniformity value and the blowing speed characterization value corresponding to the same measurement time point are processed by ratio to obtain the influence ratio;

[0037] The influence ratios of all measurement time points in the overlapping time period are summed and averaged to obtain the influence ratio mean, the influence ratio of each measurement time point is calculated to differ from the influence ratio mean, and the absolute value of the difference is marked as the influence ratio deviation value;

[0038] Compare the impact ratio deviation value with the impact ratio deviation threshold. If the impact ratio deviation value is less than or equal to the impact ratio deviation threshold, it is marked as a valid impact ratio. If the impact deviation value is greater than the impact ratio deviation threshold, it is marked as an invalid impact ratio.

[0039] Obtain the number of valid influence ratios and the number of invalid influence ratios, sum them up to obtain the total number of values, perform ratio processing on the valid influence ratio and the total number of values ​​to obtain the valid proportion value, perform ratio processing on the invalid influence ratio and the total number of values ​​to obtain the invalid proportion value;

[0040] Compare the valid proportion value with the invalid proportion value;

[0041] If the valid proportion value is greater than the invalid proportion value, a signal with no other influence is generated.

[0042] As a further solution of the present invention: the process of establishing the prediction model is:

[0043] Obtain the expansion uniformity evaluation value JX and the blowing speed characterization value SD at all measuring time points during the blowing process;

[0044] Create a preset model , where M is the proportional coefficient and N is the error coefficient;

[0045] Marking the expansion uniformity evaluation value and the inflation speed characterization value corresponding to each measurement time point during the inflation process as a set of calculation data;

[0046] Randomly extract two sets of calculation data and substitute them into the preset model to calculate the corresponding proportional coefficient M and error coefficient N;

[0047] Repeat the calculation several times to obtain multiple sets of proportional coefficients M and error coefficients N, sum and average all the proportional coefficients M to obtain MJ, and sum and average all the error coefficients N to obtain NJ;

[0048] Then the prediction model for the expansion uniformity evaluation value and the blowing speed characterization value is: , where SDD is the real-time blowing speed characterization value, and JXX is the predicted expansion uniformity evaluation value.

[0049] As a further solution of the present invention: comprising:

[0050] Expansion data acquisition and calculation module: obtains the expansion data of the parison during the blowing process, analyzes the obtained expansion data, and calculates the expansion uniformity evaluation value;

[0051] Expansion state determination module: compares the expansion uniformity evaluation value with the expansion uniformity evaluation threshold, and generates an expansion non-uniformity signal if the expansion uniformity evaluation value is greater than the expansion uniformity evaluation threshold;

[0052] Blowing speed acquisition and analysis module: based on the above-obtained uneven expansion signal, acquires blowing speed data, analyzes the acquired blowing speed data, calculates the blowing speed characterization value, makes a judgment, and generates a blowing speed abnormality signal;

[0053] Synchronous influence judgment module: based on the above-mentioned abnormal blowing speed signal, judge whether the uneven expansion of the parison is related to the abnormal blowing speed, calculate the abnormal synchronous influence value, make a judgment, and generate an influence signal;

[0054] Impact analysis module: Based on the above impact signals, the expansion uniformity value and the inflation speed characterization value in the inflation process are obtained, and whether there are other influencing factors affecting the expansion uniformity are analyzed, and no other impact signals are generated. Based on the no other impact signals, a prediction model is established.

[0055] Beneficial effects of the present invention:

[0056] (1) The present invention first obtains the expansion dimension change values ​​of multiple measurement points at multiple measurement time points during the inflation process, calculates the expansion dimension change deviation value based on the expansion dimension change value, and then calculates the expansion uniformity evaluation value based on the expansion dimension change deviation value, so as to judge whether the expansion of the parison is uniform at each measurement time point, thereby being able to monitor the expansion uniformity of the parison during the inflation process, timely understand the quality of the product during the inflation process, and make timely adjustments when unevenness is detected, thereby improving the inflation efficiency;

[0057] (2) The present invention obtains the blowing speed during the blowing process, processes the blowing speed, calculates the blowing speed characterization value, and judges whether the blowing speed is abnormal based on the blowing speed characterization value. The synchronous influence value is calculated based on the occurrence of the abnormal blowing speed and the expansion unevenness, and judges whether the abnormal blowing speed causes the expansion unevenness synchronously. If an influence signal is generated, it is analyzed whether there are other influencing factors. If there are no other influencing factors, a prediction model about the expansion evaluation value and the blowing speed characterization value is calculated. Therefore, when the mold blank expands unevenly, the cause of the uneven situation can be judged and a prediction model can be established. Then, by obtaining the prediction model, the blowing process can be accurately controlled and optimized, thereby improving product quality and production efficiency and reducing production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The present invention will be further described below in conjunction with the accompanying drawings.

[0059] Figure 1 It is a schematic flow chart of a method for controlling the inflation of an injection blow molding machine according to the present invention;

[0060] Figure 2 It is a schematic diagram of a process of obtaining an expansion uniformity evaluation value of a method for controlling an injection blow molding machine according to the present invention;

[0061] Figure 3 It is a schematic diagram of the process of obtaining a blowing speed characterization value of a blowing control method of an injection blow molding machine according to the present invention. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] Example 1

[0064] See also Figure 1 - Figure 3 As shown, in the hollow blow molding process, the blowing speed needs to be controlled. A too fast blowing speed may cause decompression in the air inlet area, causing the parison to collapse, or even be cut off by high airflow, resulting in the inability to blow. A too slow blowing speed will extend the molding cycle and reduce production efficiency. The present invention is a blowing control method for an injection blow molding machine, comprising the following steps:

[0065] Step 1: Obtain expansion data of the parison during the blowing process, analyze the obtained expansion data, and calculate the expansion uniformity evaluation value;

[0066] Among them, the expansion data is the expansion size of the parison during the blowing process;

[0067] In some embodiments, the total time of the inflation process is divided into a plurality of measurement time points, two adjacent measurement time points are marked as a measurement period, and a plurality of measurement points are marked on the parison;

[0068] The measuring points include but are not limited to the vicinity of the air inlet, the center area of ​​the mold, the top position of the parison, the bottom position of the parison, and the side position of the parison;

[0069] At each measuring time point, the expansion dimensions of the parison at all measuring points are obtained, and the expansion dimension change values ​​of multiple measuring points in each measuring period are calculated;

[0070] In the same measurement time, the expansion size change values ​​of each measurement point are summed and averaged to obtain the expansion size change mean value, and the expansion size change value of each measurement point is calculated to differ from the expansion size change mean value to obtain the absolute value of the difference, which is marked as the expansion size change deviation value;

[0071] Compare the expansion size change deviation value with the expansion size change deviation threshold (the expansion size change deviation threshold is set by a person skilled in the art based on historical experimental data summary);

[0072] If the expansion size change deviation value is less than or equal to the expansion size change deviation threshold, it means that the expansion size change value of the measurement point is slightly different from the expansion size change mean value, and is marked as a normal deviation value;

[0073] If the expansion size change deviation value is greater than the expansion size change deviation threshold, it means that the expansion size change value of the measurement point is significantly different from the expansion size change mean value, and is marked as an abnormal deviation value;

[0074] Obtain the number of values ​​marked as abnormal deviation values ​​and the number of measurement points corresponding to the measurement time, perform ratio processing on the number of values ​​marked as abnormal deviation values ​​and the number of measurement points corresponding to the measurement time, and obtain the unstable ratio BW;

[0075] It should be explained that the meaning reflected by the unstable ratio is: the unstable ratio is calculated by the number of abnormal deviation values ​​and the number of measurement points corresponding to the measurement time, that is, the larger the unstable ratio is, the more the number of abnormal deviation values ​​is, the greater the difference in the expansion size changes of the parison at multiple measurement points at the measurement time point is, and the more uneven the expansion of the parison is;

[0076] The maximum value among the abnormal deviation values ​​is extracted, and the ratio is calculated between it and the expansion size change deviation threshold to obtain the abnormal maximum deviation ratio YD;

[0077] It should be explained that the meaning of the abnormal maximum deviation ratio is: the abnormal maximum deviation ratio is calculated by the maximum value of the abnormal deviation value and the expansion size change deviation threshold, that is, the larger the maximum value of the abnormal deviation value is, the greater the degree of deviation from the expansion size change deviation threshold is, and the more uneven the expansion of the parison at the measurement time point is;

[0078] Substitute the unstable proportion BW and the abnormal maximum deviation ratio YD into the formula , the expansion uniformity assessment value JX is calculated, where a and b are weight coefficients, and a+b=1, a>b, that is, the influence of the unstable proportion on the expansion uniformity is greater than the influence of the abnormal maximum deviation ratio on the expansion uniformity;

[0079] Step 2: Compare the expansion uniformity evaluation value with the expansion uniformity evaluation threshold to generate an expansion uniformity signal or an expansion unevenness signal;

[0080] In some embodiments, an expansion uniformity evaluation value is obtained, and the expansion uniformity evaluation value is compared with an expansion uniformity evaluation threshold value (the expansion uniformity evaluation threshold value is set by a person skilled in the art based on historical experimental data summary);

[0081] If the expansion uniformity evaluation value is less than or equal to the expansion uniformity evaluation threshold, it means that the expansion sizes of multiple measurement points of the parison at the measurement time point are relatively uniform, and an expansion uniformity signal is generated;

[0082] If the expansion uniformity evaluation value is greater than the expansion uniformity evaluation threshold, it means that the expansion sizes of multiple measurement points of the parison at the measurement time point are uneven, and an expansion unevenness signal is generated;

[0083] The core technology of this embodiment is: first, by obtaining the expansion dimension change values ​​of multiple measurement points at multiple measurement time points during the blowing process, the expansion dimension change deviation value is calculated based on the expansion dimension change value, and then based on the expansion dimension change deviation value, the expansion uniformity assessment value is calculated to determine whether the expansion of the parison is uniform at each measurement time point, so that the expansion uniformity of the parison can be monitored during the blowing process, the quality of the product during the blowing process can be understood in time, and timely adjustments can be made when unevenness is monitored to improve the blowing efficiency.

[0084] Example 2

[0085] Based on the above embodiments, when the blowing speed is too fast, decompression may occur in the air inlet area, causing the parison in this area to collapse, which will reduce the cross-sectional area of ​​the air inlet channel and may even break the parison at the die mouth, resulting in the inability to blow or reduced product quality. When the blowing speed is too slow, the various parts of the parison may not reach the expected expansion state at the same time. The present invention is a blowing control method for an injection blow molding machine, which also includes the following steps:

[0086] Step 3: Based on the uneven expansion signal obtained above, the inflation speed data is obtained, and the inflation speed data is analyzed to calculate the inflation speed characterization value, and a judgment is made to generate a normal inflation speed signal or an abnormal inflation speed signal;

[0087] In some embodiments, the inflation speed during the inflation process is obtained, and a two-dimensional model is established with time as the X-axis and the inflation speed as the Y-axis. The inflation speed is substituted into the two-dimensional model to draw an inflation speed curve graph, and a maximum value and a minimum value of the inflation speed range threshold (the inflation speed range threshold is set by those skilled in the art based on historical experimental summaries) are used as standard values ​​to draw a standard line parallel to the X-axis, which are marked as a first standard line and a second standard line respectively;

[0088] The portion of the inflation speed curve that is above the first standard line and below the second standard line is marked as an abnormal inflation speed region, and the portion of the inflation speed curve that is below the first standard line and above the second standard line is marked as a normal inflation speed region;

[0089] In each measurement period, the abnormal area time period is obtained, the obtained abnormal area time period is summed up to obtain the total value of the abnormal area time period, and the total value of the abnormal area time period is ratioed with the time value of the measurement period to obtain the abnormal time proportion of the inflation speed;

[0090] In each measurement period, the extreme value of the blowing speed in the abnormal area is extracted, and the difference between the extreme value of the blowing speed (the extreme value of the blowing speed is the maximum or minimum value of the blowing speed in the abnormal area) and the standard value of the blowing speed (the standard value of the blowing speed is the maximum or minimum value of the threshold of the blowing speed range) is calculated, and the absolute value of the difference is calculated by ratio with the standard value of the blowing speed to obtain the abnormal deviation ratio of the blowing speed, and the abnormal deviation ratios of the blowing speed in all abnormal areas are summed to obtain the abnormal degree ratio of the blowing speed;

[0091] It should be explained that if the abnormal area is on the upper side of the first standard line, then when calculating the abnormal deviation ratio of the inflation speed, the maximum value of the inflation speed in the abnormal area and the maximum value of the inflation speed range threshold are extracted for calculation; if the abnormal area is on the lower side of the second standard line, then when calculating the abnormal deviation ratio of the inflation speed, the minimum value of the inflation speed in the abnormal area and the minimum value of the inflation speed range threshold are extracted for calculation;

[0092] The blowing speed abnormality time ratio is multiplied by the blowing speed abnormality degree ratio to calculate the blowing speed characterization value;

[0093] It should be explained that the speed characterization value reflects the following meaning: the speed characterization value is calculated by the ratio of the abnormal time of the blowing speed to the abnormal degree of the blowing speed, that is, the longer the abnormal time of the blowing speed, the larger the speed characterization value, and the blowing speed in the measurement period frequently deviates from the normal speed; the longer the abnormal time, the larger the ratio of the abnormal degree of the blowing speed, and the greater the deviation degree of the abnormal blowing speed in the measurement period, and the more abnormal the blowing speed;

[0094] Obtaining a blowing speed characterization value of each measuring period, and comparing the blowing speed characterization value of each measuring period with a blowing speed characterization threshold value (the blowing speed characterization threshold value is set by a person skilled in the art based on historical experimental summaries);

[0095] If the blowing speed characterization value is less than or equal to the blowing speed characterization threshold value, it means that the blowing speed meets the process requirements, and a normal blowing speed signal is generated;

[0096] If the blowing speed characterization value is greater than the blowing speed characterization threshold, it means that the blowing speed does not meet the process requirements, and a blowing speed abnormality signal is generated;

[0097] Step 4: Based on the above-mentioned abnormal blowing speed signal, determine whether the uneven expansion of the parison is related to the abnormal blowing speed, calculate the abnormal synchronization impact value, make a judgment, and generate an impact signal or a non-impact signal;

[0098] In some embodiments, a time period during which a blowing speed abnormality signal is generated and a time period during which an expansion non-uniformity signal is generated are obtained;

[0099] Calculate the overlapping time period of abnormal blowing speed and uneven expansion and the number of overlapping time periods;

[0100] The total time value of the overlapping time period is multiplied by the number of overlapping time periods to calculate the abnormal synchronization impact value;

[0101] It should be explained that the meaning reflected by the abnormal synchronization impact value is: the synchronization impact value is calculated by the total time value of the overlapping time period and the number of overlapping time periods, that is, the larger the total time value of the overlapping time period, the higher the time overlap between the uneven expansion and the abnormal blowing speed, and the larger the number of overlapping time periods, the higher the time overlap between the uneven expansion and the abnormal blowing speed;

[0102] Compare the abnormal synchronization impact value with the abnormal synchronization impact threshold (the abnormal synchronization impact threshold is set by those skilled in the art based on historical experimental summaries);

[0103] If the abnormal synchronization impact value is less than or equal to the abnormal synchronization impact value, it means that the expansion uniformity abnormality and the blowing speed abnormality have a low coincidence degree, and a non-influence signal is generated;

[0104] If the abnormal synchronization impact value is greater than the abnormal synchronization impact value, it means that the expansion uniformity abnormality and the blowing speed abnormality have a high overlap, and an impact signal is generated;

[0105] Step 5: Based on the above-mentioned influencing signals, obtain the expansion uniformity value and the inflation speed characterization value during the inflation process, analyze whether there are other influencing factors affecting the inflation uniformity, generate no other influencing signals or other influencing signals, and establish a prediction model based on no other influencing signals;

[0106] In some embodiments, obtaining the expansion uniformity value and the inflation speed characterization value corresponding to each measurement time point in the overlapping time period;

[0107] The expansion uniformity value and the blowing speed characterization value corresponding to the same measurement time point are processed by ratio to obtain the influence ratio;

[0108] The influence ratios of all measurement time points in the overlapping time period are summed and averaged to obtain the influence ratio mean, the influence ratio of each measurement time point is calculated to differ from the influence ratio mean, and the absolute value of the difference is marked as the influence ratio deviation value;

[0109] Compare the impact ratio deviation value with the impact ratio deviation threshold (the impact ratio deviation threshold is set by a person skilled in the art based on historical experimental data). If the impact ratio deviation value is less than or equal to the impact ratio deviation threshold, it is marked as a valid impact ratio. If the impact deviation value is greater than the impact ratio deviation threshold, it is marked as an invalid impact ratio.

[0110] Obtain the number of valid influence ratios and the number of invalid influence ratios, sum them up to obtain the total number of values, perform ratio processing on the valid influence ratio and the total number of values ​​to obtain the valid proportion value, perform ratio processing on the invalid influence ratio and the total number of values ​​to obtain the invalid proportion value;

[0111] Compare the valid proportion value with the invalid proportion value;

[0112] If the effective proportion value is greater than the invalid proportion value, it means that there is a certain proportional relationship between the expansion uniformity evaluation value and the blowing speed characterization value in the overlapping time period, and no other influencing signal is generated;

[0113] If the effective proportion value is less than or equal to the invalid proportion value, it means that there is no proportional relationship between the expansion uniformity evaluation value and the blowing speed characterization value in the overlapping time period, and other influencing signals are generated;

[0114] Based on the above generated signal without other influences, the expansion uniformity evaluation value JX and the blowing speed characterization value SD at all measuring time points during the blowing process are obtained;

[0115] Create a preset model , where M is the proportional coefficient and N is the error coefficient;

[0116] Marking the expansion uniformity evaluation value and the inflation speed characterization value corresponding to each measurement time point during the inflation process as a set of calculation data;

[0117] Randomly extract two sets of calculation data and substitute them into the preset model to calculate the corresponding proportional coefficient M and error coefficient N;

[0118] Repeat the calculation several times to obtain multiple sets of proportional coefficients M and error coefficients N, sum and average all the proportional coefficients M to obtain MJ, and sum and average all the error coefficients N to obtain NJ;

[0119] Then the prediction model for the expansion uniformity evaluation value and the blowing speed characterization value is: , where SDD is the real-time inflation speed characterization value, and JXX is the predicted inflation uniformity evaluation value, that is, the inflation uniformity evaluation value can be predicted according to the real-time inflation speed characterization value, so that the abnormality can be adjusted based on the prediction result;

[0120] The core technology of this embodiment is: by acquiring the blowing speed during the blowing process and processing the blowing speed, a blowing speed characterization value is calculated, and based on the blowing speed characterization value, whether the blowing speed is abnormal is judged, and a synchronous influence value is calculated based on the occurrence of abnormal blowing speed and uneven expansion, to judge whether the abnormal blowing speed causes the occurrence of uneven expansion synchronously, and if an influence signal is generated, it is analyzed whether there are other influencing factors, and if there are no other influencing factors, a prediction model for the expansion evaluation value and the blowing speed characterization value is calculated, so that when the mold blank expands unevenly, the cause of the uneven situation can be judged and a prediction model can be established, and then by obtaining the prediction model, the blowing process can be accurately controlled and optimized, product quality and production efficiency can be improved, and production costs can be reduced.

[0121] Example 3

[0122] Based on the above embodiments, the present invention is a blow molding control system for an injection blow molding machine, comprising:

[0123] Expansion data acquisition and calculation module: obtains the expansion data of the parison during the blowing process, analyzes the obtained expansion data, and calculates the expansion uniformity evaluation value;

[0124] Expansion state determination module: compares the expansion uniformity evaluation value with the expansion uniformity evaluation threshold (the expansion uniformity evaluation threshold is set by a person skilled in the art based on historical experimental data), and generates an expansion uniformity signal or an expansion non-uniformity signal;

[0125] Blowing speed acquisition and analysis module: based on the above-obtained uneven expansion signal, acquires blowing speed data, analyzes the acquired blowing speed data, calculates the blowing speed characterization value, makes a judgment, and generates a blowing speed normal signal or a blowing speed abnormal signal;

[0126] Synchronous influence judgment module: based on the above-mentioned abnormal blowing speed signal, judge whether the uneven expansion of the parison is related to the abnormal blowing speed, calculate the abnormal synchronous influence value, make a judgment, and generate an influence signal or a non-influence signal;

[0127] Impact analysis module: Based on the above impact signals, the expansion uniformity value and the inflation speed characterization value in the inflation process are obtained, and whether there are other influencing factors affecting the expansion uniformity are analyzed, and there are no other impact signals or other impact signals are generated, and based on the absence of other impact signals, a prediction model is established.

[0128] 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 method for controlling the inflation of an injection blow molding machine, characterized in that: The following steps are involved: Step 1: Obtain expansion data of the parison during the blowing process, analyze the obtained expansion data, and calculate the expansion uniformity evaluation value; Among them, the expansion data is the expansion size of the parison during the blowing process; The process of obtaining the expansion uniformity evaluation value is as follows: The total time of the inflation process is divided into several measuring time points, two adjacent measuring time points are marked as one measuring period, and multiple measuring points are marked on the parison; At each measuring time point, the expansion dimensions of the parison at all measuring points are obtained, and the expansion dimension change values ​​of multiple measuring points in each measuring period are calculated; In the same measurement time, the expansion size change values ​​of each measurement point are summed and averaged to obtain the expansion size change mean value, and the expansion size change value of each measurement point is calculated to differ from the expansion size change mean value to obtain the absolute value of the difference, which is marked as the expansion size change deviation value; comparing the expansion size change deviation value with the expansion size change deviation threshold; If the expansion size change deviation value is greater than the expansion size change deviation threshold, it is marked as an abnormal deviation value; Obtain the number of values ​​marked as abnormal deviation values ​​and the number of measurement points corresponding to the measurement time, perform ratio processing on the number of values ​​marked as abnormal deviation values ​​and the number of measurement points corresponding to the measurement time, and obtain the unstable ratio BW; The maximum value among the abnormal deviation values ​​is extracted, and the ratio is calculated between it and the expansion size change deviation threshold to obtain the abnormal maximum deviation ratio YD; Substitute the unstable proportion BW and the abnormal maximum deviation ratio YD into the formula , calculate the expansion uniformity evaluation value JX, where a and b are weight coefficients, and a+b=1, a>b; Step 2: Compare the expansion uniformity evaluation value with the expansion uniformity evaluation threshold, and if the expansion uniformity evaluation value is greater than the expansion uniformity evaluation threshold, generate an expansion non-uniformity signal; Step 3: Based on the uneven expansion signal obtained above, the inflation speed data is obtained, and the inflation speed data is analyzed to calculate the inflation speed characterization value, and a judgment is made to generate an inflation speed abnormality signal; The process of obtaining the inflation velocity characterization value is as follows: Obtain the inflation speed during the inflation process, establish a two-dimensional model with time as the X-axis and the inflation speed as the Y-axis, substitute the inflation speed into the two-dimensional model, draw a inflation speed curve, and draw a standard line parallel to the X-axis with the maximum value and the minimum value of the inflation speed range threshold as the standard value, respectively, and mark them as the first standard line and the second standard line respectively; The portion of the inflation speed curve that is above the first standard line and below the second standard line is marked as an abnormal inflation speed region, and the portion of the inflation speed curve that is below the first standard line and above the second standard line is marked as a normal inflation speed region; In each measurement period, the abnormal area time period is obtained, the obtained abnormal area time period is summed up to obtain the total value of the abnormal area time period, and the total value of the abnormal area time period is ratioed with the time value of the measurement period to obtain the abnormal time proportion of the inflation speed; In each measurement period, the extreme value of the blowing speed in the abnormal area is extracted, the difference between the extreme value of the blowing speed and the standard value of the blowing speed is calculated, the absolute value of the difference is calculated by ratio with the standard value of the blowing speed to obtain the abnormal deviation ratio of the blowing speed, and the abnormal deviation ratios of the blowing speed in all abnormal areas are summed to obtain the abnormal degree ratio of the blowing speed; The blowing speed abnormality time ratio is multiplied by the blowing speed abnormality degree ratio to calculate the blowing speed characterization value; Step 4: Based on the above-mentioned abnormal blowing speed signal, determine whether the uneven expansion of the parison is related to the abnormal blowing speed, calculate the abnormal synchronization impact value, make a judgment, and generate an impact signal; The process of obtaining the abnormal synchronization impact value is as follows: Obtaining a time period for generating a blowing speed abnormality signal and a time period for generating a non-uniform expansion signal; Calculate the overlapping time period of abnormal blowing speed and uneven expansion and the number of overlapping time periods; The total time value of the overlapping time period is multiplied by the number of overlapping time periods to calculate the abnormal synchronization impact value; Step 5: Based on the above-mentioned influencing signals, obtain the expansion uniformity value and the inflation speed characterization value during the inflation process, analyze whether there are other influencing factors affecting the expansion uniformity, generate a signal with no other influencing factors, and establish a prediction model based on the signal with no other influencing factors; The process of generating a signal with no other effects is: Obtain the expansion uniformity value and the blowing speed characterization value corresponding to each measurement time point in the overlapping time period; The expansion uniformity value and the blowing speed characterization value corresponding to the same measurement time point are processed by ratio to obtain the influence ratio; The influence ratios of all measurement time points in the overlapping time period are summed and averaged to obtain the influence ratio mean, the influence ratio of each measurement time point is calculated to differ from the influence ratio mean, and the absolute value of the difference is marked as the influence ratio deviation value; Compare the impact ratio deviation value with the impact ratio deviation threshold. If the impact ratio deviation value is less than or equal to the impact ratio deviation threshold, it is marked as a valid impact ratio. If the impact deviation value is greater than the impact ratio deviation threshold, it is marked as an invalid impact ratio. Obtain the number of valid influence ratios and the number of invalid influence ratios, sum them up to obtain the total number of values, perform ratio processing on the valid influence ratio and the total number of values ​​to obtain the valid proportion value, perform ratio processing on the invalid influence ratio and the total number of values ​​to obtain the invalid proportion value; Compare the valid proportion value with the invalid proportion value; If the effective proportion value is greater than the invalid proportion value, a signal with no other influence is generated; The prediction model acquisition process is as follows: Obtain the expansion uniformity evaluation value JX and the blowing speed characterization value SD at all measuring time points during the blowing process; Create a preset model , where M is the proportional coefficient and N is the error coefficient; Marking the expansion uniformity evaluation value and the inflation speed characterization value corresponding to each measurement time point during the inflation process as a set of calculation data; Randomly extract two sets of calculation data and substitute them into the preset model to calculate the corresponding proportional coefficient M and error coefficient N; Repeat the calculation several times to obtain multiple sets of proportional coefficients M and error coefficients N, sum and average all the proportional coefficients M to obtain MJ, and sum and average all the error coefficients N to obtain NJ; Then the prediction model for the expansion uniformity evaluation value and the blowing speed characterization value is: , where SDD is the real-time blowing speed characterization value, and JXX is the predicted expansion uniformity evaluation value.

2. The method for controlling the inflation of an injection blow molding machine according to claim 1, characterized in that: The process of generating the abnormal blowing speed signal is: Obtaining a blowing speed characterization value of each measuring period, and comparing the blowing speed characterization value of each measuring period with a blowing speed characterization threshold; If the blowing speed characterization value is greater than the blowing speed characterization threshold, a blowing speed abnormality signal is generated.

3. The method for controlling the inflation of an injection blow molding machine according to claim 1, characterized in that: The process of generating the impact signal is: Get the abnormal synchronization impact value; comparing the abnormal synchronization impact value with an abnormal synchronization impact threshold; If the abnormal synchronization impact value is greater than the abnormal synchronization impact value, an impact signal is generated.

4. A blowing control system for an injection blow molding machine, the system implementing the method according to any one of claims 1 to 3, characterized in that: include: Expansion data acquisition and calculation module: obtains the expansion data of the parison during the blowing process, analyzes the obtained expansion data, and calculates the expansion uniformity evaluation value; Expansion state determination module: compares the expansion uniformity evaluation value with the expansion uniformity evaluation threshold, and generates an expansion non-uniformity signal if the expansion uniformity evaluation value is greater than the expansion uniformity evaluation threshold; Blowing speed acquisition and analysis module: based on the above-obtained uneven expansion signal, acquires blowing speed data, analyzes the acquired blowing speed data, calculates the blowing speed characterization value, makes a judgment, and generates a blowing speed abnormality signal; Synchronous influence judgment module: based on the above-mentioned abnormal blowing speed signal, judge whether the uneven expansion of the parison is related to the abnormal blowing speed, calculate the abnormal synchronous influence value, make a judgment, and generate an influence signal; Impact analysis module: Based on the above impact signals, the expansion uniformity value and the inflation speed characterization value in the inflation process are obtained, and whether there are other influencing factors affecting the expansion uniformity are analyzed, and a signal with no other impact is generated, and a prediction model is established based on the signal with no other impact.

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