A method for monitoring the operating status of numerical control equipment in a footwear production line

Abstract

The present application relates to the field of data processing technology, and in particular to a method for monitoring the operating status of numerical control equipment in a footwear production line. The method includes: obtaining a vibration data segment when an injection molding machine of a footwear production line performs an injection molding operation, and determining an initial abnormal upper limit value in the vibration data segment that is greater than the upper limit of the abnormal value; adjusting the initial abnormal upper limit value in the target vibration data segment according to the initial abnormal upper limit values ​​in other vibration data segments except the target vibration data segment to obtain a target abnormal upper limit value; forming a target data set with the target abnormal upper limit value in the target vibration data segment and other data points except the initial abnormal upper limit value; determining whether there are abnormal data points in the target data set using a box plot algorithm, and outputting a prompt message when there are abnormal data points in the target data set. Through the above technical scheme, the accuracy of monitoring the injection molding machine of the footwear production line can be improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method for monitoring the operating status of numerical control equipment in a footwear production line. Background Art

[0002] The footwear production line includes a variety of CNC equipment such as CNC injection molding machines, CNC drilling machines and CNC assembly machines to realize assembly-line production of footwear; for example, the injection molding machines on the footwear production line can be used to manufacture soles, heels and other parts. The injection molding machines are controlled by pre-configured computer programs to control the injection volume and injection pressure of the injection molding machines during injection molding operations.

[0003] In order to monitor the operating status of equipment such as injection molding machines to ensure that the injection molding machines are in good working condition, in related technologies, for example, in the Chinese patent application document with publication number CN118656272A, a device operation process monitoring system is provided, including: an energy consumption data acquisition module, an energy consumption optimization model module, an energy-saving adjustment suggestion generation module, a predictive maintenance module, and an energy management integration module; the energy consumption data acquisition module integrates current sensors, voltage sensors, power sensors, and temperature sensors to capture the energy consumption and operating status information of the equipment; the energy consumption optimization model module combines machine learning algorithms to construct a multi-model fusion energy consumption optimization model to provide solutions for energy consumption optimization under different working conditions; the energy-saving adjustment suggestion generation module generates energy-saving adjustment suggestions based on the prediction results of the energy consumption optimization model and the actual operation of the equipment; the predictive maintenance module combines equipment operation data and historical fault records to predict equipment failures and issue early warnings.

[0004] In the related art, the data collected by the current sensor, voltage sensor, power sensor and temperature sensor are integrated to monitor the operating status of the equipment, which makes it difficult to achieve targeted monitoring of the vibration of the equipment located on the production line. Therefore, the accuracy of monitoring the vibration of the injection molding machine of the shoe production line is low. Summary of the invention

[0005] In order to overcome the problem of low accuracy in monitoring the vibration of an injection molding machine of a footwear production line in the related art, the present application provides a method for monitoring the operating status of CNC equipment of a footwear production line, comprising: obtaining a vibration data segment when the injection molding machine of the footwear production line performs an injection molding operation, and using a box plot algorithm to determine the upper limit of the abnormal value in the vibration data segment, so as to use the data point in the vibration data segment that is greater than the upper limit as the initial abnormal upper limit value; for a target vibration data segment in multiple vibration data segments, adjusting the initial abnormal upper limit value in the target vibration data segment according to the initial abnormal upper limit values ​​in other vibration data segments except the target vibration data segment, to obtain the target abnormal upper limit value in the target vibration data segment; forming a target data set with the target abnormal upper limit value in the target vibration data segment and other data points except the initial abnormal upper limit value in chronological order; using a box plot algorithm to determine whether there are abnormal data points in the target data set, and outputting a prompt message when there are abnormal data points in the target data set, wherein the prompt message is used to prompt that there is abnormality in the vibration of the injection molding machine of the footwear production line.

[0006] In this way, vibration data segments are obtained when the injection molding machine of the footwear production line performs injection molding operations, and the upper limit of the abnormal value in the vibration data segment is determined using a box plot algorithm to obtain an initial abnormal upper limit value of the vibration data segment, and the initial abnormal upper limit value of the target vibration data segment is adjusted according to the initial abnormal upper limit values ​​of other vibration data segments. The target abnormal upper limit value obtained after the adjustment can avoid the influence of noise data that may exist in the vibration data segment, so that when the abnormal data points are determined according to the target abnormal upper limit value and data points without abnormalities, it is possible to better determine whether there is abnormality in the vibration of the injection molding machine through the determined abnormal data points, so as to achieve more accurate monitoring of the injection molding machine of the footwear production line and improve the accuracy of monitoring the injection molding machine of the footwear production line.

[0007] Optionally, the target abnormal upper limit value in the target vibration data segment is obtained by: ,in, is the target abnormal upper limit value corresponding to the mth initial abnormal upper limit value in the target vibration data segment, is the mth initial abnormal upper limit value in the target vibration data segment, and exp is an exponential function with a natural constant as the base; is a first parameter value of the mth initial abnormal upper limit value in the target vibration data segment, used to characterize the degree of difference between the initial abnormal upper limit values ​​of the target vibration data segment and other vibration data segments; is the second parameter value of the mth initial abnormal upper limit value in the target vibration data segment, which is used to characterize the degree of difference between the pressure data and the vibration data when the injection molding machine performs an injection molding operation; is the first preset positive number, A positive number for the second preset.

[0008] In this way, the second parameter value of the initial abnormal upper limit value in the target vibration data segment is used to characterize the degree of difference between the pressure data and the vibration data when the injection molding machine performs injection molding operation. The second parameter value can reflect the probability that the initial abnormal upper limit value is noise data, so that the target abnormal upper limit value determined according to the second parameter value can better reflect the abnormality of the vibration of the injection molding machine.

[0009] Optionally, the first parameter value is obtained in the following manner: ,in, is the first parameter value of the mth initial abnormal upper limit value in the target vibration data segment; is the third parameter value of the mth initial abnormal upper limit value in the target vibration data segment, which is used to characterize the difference between the mth initial abnormal upper limit value and the lower limit of the abnormal value in the target vibration data segment; norm is the normalization processing function, K is the number of other vibration data segments other than the target vibration data segment, To take the absolute value, is the mth initial abnormal upper limit value in the target vibration data segment, is the upper limit of the abnormal value of the kth vibration data segment other than the target vibration data segment; A positive number for the third preset.

[0010] In this way, compared with the probability of noise data existing in the target vibration data segment, the probability of noise data existing in all vibration data segments is lower. Therefore, by comparing the initial abnormal upper limit value in the target vibration data segment with the upper limit of the abnormal values ​​of other vibration data segments except the target vibration data segment, the other vibration data segments except the target vibration data segment can be used as a reference, thereby avoiding the influence of noise data that may exist in the target vibration data segment, so as to obtain a more accurate target abnormal upper limit value.

[0011] Optionally, the third parameter value of the initial abnormal upper limit value is obtained by: ,in, is the third parameter value of the mth initial abnormal upper limit value in the target vibration data segment, is the mth initial abnormal upper limit value in the target vibration data segment, is the lower limit of the outlier value of the target vibration data segment, is the number of initial abnormal upper limit values ​​in the target vibration data segment.

[0012] In this way, the larger the number of initial abnormal upper limit values ​​in the target vibration data segment, the more likely it is that abnormal fluctuations will occur in the target vibration segment under the influence of noise data. Therefore, determining the third parameter value of the initial abnormal upper limit value in combination with the number of initial abnormal upper limit values ​​in the target vibration data segment helps to determine a more accurate target abnormal upper limit value through the third parameter value.

[0013] Optionally, the second parameter value is obtained in the following way: , is the second parameter value of the mth initial abnormal upper limit value in the target vibration data segment, N is the number of vibration data in the preset time period where the mth initial abnormal upper limit value in the target vibration data segment is located, To take the absolute value, is the percentile of the ith vibration data in the preset time period where the mth initial abnormal upper limit value in the target vibration data segment is located, is the percentile of the ith pressure data within the preset time period where the mth initial abnormal upper limit value in the target vibration data segment is located.

[0014] Optionally, a box plot algorithm is used to determine the upper limit of the outliers in the vibration data segment, including: using a box plot algorithm to determine the upper quartile and the lower quartile in the vibration data segment; taking the difference between the upper quartile and the lower quartile as the interquartile range, and determining the upper limit of the outliers in the vibration data segment based on the interquartile range and the upper quartile.

[0015] Optionally, when there are abnormal data points in the target data set, prompt information is output, including: when there are abnormal data points in the target data set, determining the number of abnormal data points in the target data set that are greater than an upper limit of the abnormal value; when the number of abnormal data points greater than the upper limit of the abnormal value is greater than a preset number threshold, outputting prompt information.

[0016] Optionally, the method further includes: obtaining the target working stage of the injection molding machine of the footwear production line at the current moment; and determining a preset quantity threshold corresponding to the target working stage from multiple quantity thresholds corresponding to multiple preset working stages.

[0017] In this way, the vibration of the injection molding machine can be more accurately monitored during different working stages of the injection molding operation of the injection molding machine.

[0018] The technical solution provided by the embodiments of the present application may include the following beneficial effects: obtaining vibration data segments when an injection molding machine of a footwear production line performs injection molding operations, and using a box plot algorithm to determine the upper limit of abnormal values ​​in the vibration data segments to obtain an initial abnormal upper limit value of the vibration data segments, and adjusting the initial abnormal upper limit value of a target vibration data segment according to the initial abnormal upper limit values ​​of other vibration data segments, so that the target abnormal upper limit value obtained after adjustment can avoid the influence of noise data that may exist in the vibration data segments, so that when abnormal data points are determined based on the target abnormal upper limit value and data points without abnormalities, it is possible to better determine whether there is an abnormality in the vibration of the injection molding machine through the determined abnormal data points, so as to achieve more accurate monitoring of the injection molding machine of the footwear production line and improve the accuracy of monitoring the injection molding machine of the footwear production line.

[0019] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0021] Figure 1 It is a flow chart of a method for monitoring the operating status of numerical control equipment in a footwear production line according to an exemplary embodiment. DETAILED DESCRIPTION

[0022] Here, exemplary embodiments are described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application.

[0023] First, a brief introduction is given to the application scenario of the embodiment of the present application. In the application scenario of the present application, in order to facilitate timely detection of abnormal CNC equipment on a shoe production line and to timely maintain the abnormal CNC equipment on the shoe production line, the operating status of CNC equipment such as injection molding machines on the shoe production line can be monitored.

[0024] Currently, there is a lack of specificity in monitoring the operating status of CNC equipment such as injection molding machines, making it difficult to detect possible abnormalities in the vibration of injection molding machines on footwear production lines. Therefore, the accuracy of monitoring the injection molding machines on footwear production lines is low.

[0025] In view of the above technical problems, the present application provides a method for monitoring the operating status of CNC equipment in a footwear production line. Figure 1is a flow chart of a method for monitoring the operating status of a CNC device on a shoe production line according to an exemplary embodiment, which can be applied to a terminal device for monitoring an injection molding machine on a shoe production line, such as Figure 1 As shown, the method includes the following steps.

[0026] In step S101, a vibration data segment of an injection molding machine of a shoe production line performing an injection molding operation is obtained, and an upper limit of an abnormal value in the vibration data segment is determined using a box plot algorithm, so that data points in the vibration data segment that are greater than the upper limit are used as initial abnormal upper limit values.

[0027] The injection molding machine will generate vibration when performing injection molding operation. The vibration data of the injection molding machine may include vibration amplitude and vibration frequency, etc. The vibration data of the injection molding machine may be acquired through sensors such as acceleration sensors, velocity sensors, displacement sensors, distance sensors and image sensors.

[0028] For example, a speed sensor or an acceleration sensor can be set at a monitoring point on the injection molding machine to determine the speed or acceleration of the monitoring point on the injection molding machine at different times, thereby obtaining the vibration amplitude or vibration frequency of the injection molding machine. Alternatively, a distance sensor can be used to obtain the distance between the position point where the distance sensor is set and the injection molding machine in the vibration direction of the injection molding machine at different times, thereby obtaining the vibration amplitude and vibration frequency of the injection molding machine at different times.

[0029] The vibration data segment of the injection molding machine of the shoe production line when performing the injection molding operation includes multiple vibration data corresponding to multiple moments when the injection molding machine located in the shoe production line performs the injection molding operation. The vibration data at different moments can be respectively used as different vibration data points.

[0030] In the case of determining whether there is an abnormality in the vibration of the injection molding machine at the current moment, a plurality of vibration data at a plurality of moments when the injection molding machine performs injection molding operations before the current moment may be combined into a vibration data segment, for example, a vibration data segment composed of a plurality of vibration data within 60 seconds before the current moment, so as to determine whether there is an abnormality in the vibration of the injection molding machine at the current moment.

[0031] The manager of the injection molding machine of the footwear production line may review the operation of the injection molding machine. Therefore, when determining whether there is any abnormality in the vibration of the injection molding machine at a historical moment, for a target historical moment among multiple historical moments, multiple vibration data at multiple moments when the injection molding machine performs injection molding operations before the target historical moment can be combined into a vibration data segment, such as a vibration data segment composed of multiple vibration data of the injection molding machine within 60 seconds before the target historical moment, so as to determine whether there is any abnormality in the vibration of the injection molding machine at the target historical moment.

[0032] The box plot algorithm can be used to determine abnormal data that may exist in the vibration data segment, such as the vibration amplitude of the injection molding machine during the injection molding operation is higher than the allowed vibration amplitude, or the vibration frequency of the injection molding machine during the injection molding operation is higher than the allowed vibration frequency.

[0033] The box plot is also known as a box plot or a box-whisker plot. The box plot divides the data set into four equal parts based on the concept of quartiles. Each part contains 25% of the data in the data set before division. The box plot can more easily identify the maximum value, minimum value, median and outliers of the data; or, the box plot can show the overall distribution of the data and the degree of outliers of different data, so as to determine the abnormal data in the data set.

[0034] The upper and lower limits of abnormal values ​​in the vibration data segment can be determined through the box plot algorithm. The injection molding machine has a certain vibration range when performing injection molding operations. Therefore, the vibration data in the vibration data segment that is greater than the upper limit is an abnormal data point, or the vibration data in the vibration data segment that is less than the lower limit is an abnormal data point; the data point in the vibration data segment that is greater than the upper limit can be used as the initial abnormal upper limit value.

[0035] In one embodiment, the upper limit of the outliers in the vibration data segment is determined using a box plot algorithm, including: using a box plot algorithm to determine an upper quartile and a lower quartile in the vibration data segment; taking the difference between the upper quartile and the lower quartile as the interquartile range, and determining the upper limit of the outliers in the vibration data segment based on the interquartile range and the upper quartile.

[0036] In the box plot algorithm, the upper quartile is the third quartile in the data set, indicating that 75% of the data values ​​in the data set are less than or equal to the upper quartile, or the upper quartile is greater than or equal to 75% of the data values ​​in the data set; the lower quartile is the first quartile in the data set, indicating that 25% of the data values ​​in the data set are less than or equal to the lower quartile, or the lower quartile is less than or equal to 25% of the data values ​​in the data set.

[0037] The upper quartile and the lower quartile can better reflect the distribution of data in the vibration data segment, so as to determine the abnormal data that may exist in the vibration data segment. For example, the upper limit of the abnormal value = the upper quartile + 1.5 × the interquartile range, and the upper limit of the abnormal value in the vibration data segment = the lower quartile - 1.5 × the interquartile range, so as to determine the moment when the vibration of the injection molding machine becomes abnormal within the time period corresponding to the vibration data segment.

[0038] In step S102, for a target vibration data segment among multiple vibration data segments, the initial abnormal upper limit value in the target vibration data segment is adjusted according to the initial abnormal upper limit values ​​in other vibration data segments except the target vibration data segment to obtain the target abnormal upper limit value in the target vibration data segment.

[0039] When determining abnormal data points only based on vibration data in the same vibration data segment, since the amount of referenced vibration data is limited, noise data points may exist in the vibration data segment, and the determined initial abnormal upper limit value may be affected by the noise data, thereby affecting the accuracy of monitoring the vibration of the injection molding machine for shoes and boots.

[0040] According to the initial abnormal upper limit values ​​in other vibration data segments except the target vibration data segment, the initial abnormal upper limit value in the target vibration data segment is adjusted. Since the probability of noise data existing in all vibration data segments is low, other vibration data segments can better provide a reference for determining abnormal data points in the target vibration data segment, so as to determine more accurate abnormal data points in the target vibration data segment.

[0041] In one embodiment, the target abnormal upper limit value in the target vibration data segment is obtained by: ,in, is the target abnormal upper limit value corresponding to the mth initial abnormal upper limit value in the target vibration data segment, is the mth initial abnormal upper limit value in the target vibration data segment, and exp is an exponential function with a natural constant as the base; is a first parameter value of the mth initial abnormal upper limit value in the target vibration data segment, used to characterize the degree of difference between the initial abnormal upper limit values ​​of the target vibration data segment and other vibration data segments; is the second parameter value of the mth initial abnormal upper limit value in the target vibration data segment, which is used to characterize the degree of difference between the pressure data and the vibration data when the injection molding machine performs an injection molding operation; is the first preset positive number, A positive number for the second preset.

[0042] The target vibration data segment and other vibration data segments except the target vibration data segment correspond to the same working stage of the injection molding machine performing the injection molding operation, so that the initial abnormal upper limit value in the target vibration data segment can be better adjusted through other vibration data segments.

[0043] The first parameter value of the initial abnormal upper limit value is used to characterize the degree of difference between the target vibration data segment and other vibration data segments between the initial abnormal upper limit value; the greater the degree of difference between the target vibration data segment and other vibration data segments, the higher the probability that the target vibration data segment includes noise data, and the initial abnormal upper limit value can be adjusted to a smaller target abnormal upper limit value to avoid the influence of noise data.

[0044] On the contrary, the smaller the difference between the target vibration data segment and other vibration data segments in the initial abnormal upper limit value, the lower the probability that the target vibration data segment includes noise data, and the higher the probability that the vibration data included in the target vibration data segment is normal data. Adjusting the initial abnormal upper limit value to a larger target abnormal upper limit value can facilitate the screening of noise data points in the target vibration data segment, so as to better realize the monitoring of the injection molding machine.

[0045] The pressure data of an injection molding machine during injection molding operation may refer to the size of the pressure applied by the injection molding machine during injection molding; when an injection molding machine on a footwear production line is performing injection molding operation, the greater the pressure data of the injection molding machine during injection molding operation, the greater the vibration generated by the injection molding machine during injection molding operation; on the contrary, the smaller the pressure data of the injection molding machine during injection molding operation, the smaller the vibration generated by the injection molding machine during injection molding operation.

[0046] When noise data exists in the vibration data segment, the vibration data in the vibration data segment changes relative to the actual vibration data, so that the correlation between the pressure data and the vibration data when the injection molding machine performs the injection molding operation is reduced; the second parameter value of the initial abnormal upper limit value in the target vibration data segment is used to characterize the degree of difference between the pressure data and the vibration data when the injection molding machine performs the injection molding operation. Therefore, the second parameter value can reflect the probability that the initial abnormal upper limit value is noise data, so that the target abnormal upper limit value determined according to the second parameter value can better reflect the abnormality of the vibration of the injection molding machine.

[0047] The existence of the first preset positive number and the second preset positive number can ensure that the adjustment ratio of the initial abnormal upper limit value is within the set range. The first preset positive number can be between 0.8 and 1, and the second preset positive number can be between 0.01 and 0.03.

[0048] In step S103, the target abnormal upper limit value in the target vibration data segment and other data points except the initial abnormal upper limit value are combined into a target data set in chronological order.

[0049] When the vibration data of the injection molding machine is higher than a preset vibration threshold, for example, the vibration amplitude of the injection molding machine is greater than the vibration amplitude threshold, or the vibration frequency of the injection molding machine is higher than the vibration frequency threshold, a larger vibration amplitude or a higher frequency vibration will shorten the service life of the injection molding machine. Therefore, in order to facilitate the monitoring of the working status of the injection molding machine, the target abnormal upper limit value in the target vibration data segment and other data points except the initial abnormal upper limit value can be combined into a target data set in chronological order, so as to determine whether there is any abnormality in the vibration of the injection molding machine based on the target data set.

[0050] In step S104, a box plot algorithm is used to determine whether there are abnormal data points in the target data set, and a prompt message is output if there are abnormal data points in the target data set.

[0051] The target abnormal upper limit value obtained by adjusting the initial abnormal upper limit value can avoid the influence of noise data that may exist in the vibration data segment, so that when the abnormal data points are determined according to the target data set including the target abnormal upper limit value, the obtained abnormal data points can be more consistent with the actual abnormal data points of the injection molding machine.

[0052] With reference to the process of determining the upper limit of the outlier in the vibration data segment, the box plot algorithm can be used to obtain the upper limit of the outlier in the target data set, and the data points in the target data set that are greater than the upper limit of the outlier can be used as abnormal data points; if the vibration data of the injection molding machine at the moment corresponding to the screened out abnormal data point is abnormal, the injection molding machine can be maintained when the vibration is abnormal during the injection molding operation to ensure the reliability of the injection molding machine in the footwear production line.

[0053] When there are abnormal data points in the target data set, prompt information can be output through the terminal device, and the output prompt information can be at least one of the types of prompt information such as audio prompt information, vibration prompt information, text prompt information, and light prompt information.

[0054] Through the method for monitoring the operating status of numerical control equipment of a footwear production line provided in the embodiment of the present application, vibration data segments of an injection molding machine of the footwear production line when performing injection molding operations are obtained, and the upper limit of the abnormal value in the vibration data segment is determined using a box plot algorithm to obtain an initial abnormal upper limit value of the vibration data segment, and the initial abnormal upper limit value of the target vibration data segment is adjusted according to the initial abnormal upper limit values ​​of other vibration data segments. The target abnormal upper limit value obtained after the adjustment can avoid the influence of noise data that may exist in the vibration data segment, so that when the abnormal data point is determined according to the target abnormal upper limit value and the data point without abnormality, it is possible to better determine whether there is an abnormality in the vibration of the injection molding machine through the determined abnormal data point, so as to achieve more accurate monitoring of the injection molding machine of the footwear production line and improve the accuracy of monitoring the injection molding machine of the footwear production line.

[0055] In one embodiment, the first parameter value of the initial abnormal upper limit value can be obtained in the following manner: ,in, is the first parameter value of the mth initial abnormal upper limit value in the target vibration data segment; is the third parameter value of the mth initial abnormal upper limit value in the target vibration data segment, which is used to characterize the difference between the mth initial abnormal upper limit value and the lower limit of the abnormal value in the target vibration data segment; norm is the normalization processing function, K is the number of other vibration data segments other than the target vibration data segment, To take the absolute value, is the mth initial abnormal upper limit value in the target vibration data segment, is the upper limit of the abnormal value of the kth vibration data segment other than the target vibration data segment; A positive number for the third preset.

[0056] The third parameter value is used to characterize the degree of difference between the initial abnormal upper limit value and the lower limit of the abnormal value in the target vibration data segment. The higher the degree of difference between the initial abnormal upper limit value and the lower limit of the abnormal value, the higher the degree of fluctuation of the vibration data of the injection molding machine in the time period corresponding to the target vibration data segment, and the higher the probability of noise data existing in the target vibration data segment. The first parameter value determined according to the third parameter value helps to obtain a more accurate target abnormal upper limit value.

[0057] In this way, compared with the probability of noise data existing in the target vibration data segment, the probability of noise data existing in all vibration data segments is lower. Therefore, by comparing the initial abnormal upper limit value in the target vibration data segment with the upper limit of the abnormal values ​​of other vibration data segments except the target vibration data segment, the other vibration data segments except the target vibration data segment can be used as a reference, thereby avoiding the influence of noise data that may exist in the target vibration data segment, so as to obtain a more accurate target abnormal upper limit value.

[0058] The third preset positive number The existence of can avoid the situation where the first parameter value is 0, and ensure that all parameter values ​​involved in the process of determining the target abnormal upper limit value can play a role. The third preset positive number can be between 0.01 and 0.03.

[0059] In one embodiment, the third parameter value of the initial abnormal upper limit value is obtained by: ,in, is the third parameter value of the mth initial abnormal upper limit value in the target vibration data segment, is the mth initial abnormal upper limit value in the target vibration data segment, is the lower limit of the outlier value of the target vibration data segment, is the number of initial abnormal upper limit values ​​in the target vibration data segment.

[0060] The initial abnormal upper limit value in the target vibration data segment is compared with the lower limit of the abnormal value. The larger the difference between the initial abnormal upper limit value and the lower limit of the abnormal value, the greater the degree of difference between the abnormal data in the target vibration data segment, and the higher the probability that the target vibration data segment includes noise data.

[0061] The larger the number of initial abnormal upper limit values ​​in the target vibration data segment, the more likely it is that the target vibration segment will produce abnormal fluctuations under the influence of noise data. Therefore, determining the third parameter value of the initial abnormal upper limit value in combination with the number of initial abnormal upper limit values ​​in the target vibration data segment helps to determine a more accurate target abnormal upper limit value through the third parameter value.

[0062] In one embodiment, the second parameter value is obtained by: , is the second parameter value of the mth initial abnormal upper limit value in the target vibration data segment, N is the number of vibration data in the preset time period where the mth initial abnormal upper limit value in the target vibration data segment is located, To take the absolute value, is the percentile of the ith vibration data in the preset time period where the mth initial abnormal upper limit value in the target vibration data segment is located, is the percentile of the ith pressure data within the preset time period where the mth initial abnormal upper limit value in the target vibration data segment is located.

[0063] Percentiles are used to describe the relative position of a value in a data set in the overall data. Percentiles refer to a certain percentage of data values ​​in a data set that are lower than or equal to a certain value. For example, for a specific value in a data set corresponding to the 80th percentile, it means that 80% of the data in the data set are less than or equal to this specific value, and 20% of the data in the data set are greater than this specific value.

[0064] The percentile can be calculated, for example, by sorting the data in the data set in descending order to obtain a sorted sequence, determining the order of the values ​​of the target data in the data set in the sorted sequence, and thus determining the percentile corresponding to the target data.

[0065] The vibration generated by the injection molding machine of the footwear production line during injection molding is related to the pressure of the injection molding machine during the injection molding operation. Therefore, in the same time period when the injection molding machine is performing the injection molding operation, the percentile corresponding to the pressure data of the injection molding machine at a certain moment is corresponding to the percentile corresponding to the vibration data of the injection molding machine at a certain moment. When there is noise data in the target vibration data segment, part of the vibration data in the same time period changes due to the influence of the noise data. Therefore, under the influence of the noise data, the difference between the percentile corresponding to the pressure data of the injection molding machine at a certain moment and the percentile corresponding to the vibration data of the injection molding machine at a certain moment increases.

[0066] In this way, by comparing the percentile of the vibration data within the preset time period where the initial abnormal upper limit value in the target vibration data segment is located with the percentile of the pressure data within the preset time period where the initial abnormal upper limit value in the target vibration data segment is located, the second parameter value can take into account the influence of possible noise data, which helps to avoid the adverse effects of possible noise data on the obtained target abnormal upper limit value, thereby better realizing the monitoring of the vibration of the injection molding machine of the footwear production line.

[0067] In one embodiment, when there are abnormal data points in the target data set, prompt information is output, including: when there are abnormal data points in the target data set, determining the number of abnormal data points in the target data set that are greater than the upper limit of the abnormal value; when the number of abnormal data points greater than the upper limit of the abnormal value is greater than a preset number threshold, outputting prompt information.

[0068] When the vibration data of the injection molding machine of the shoe production line exceeds the upper limit of the abnormal value, it will affect the service life of the injection molding machine of the shoe production line. Therefore, we can focus on the vibration data of the injection molding machine on the shoe production line that exceeds the upper limit of the abnormal value to better monitor the vibration of the injection molding machine.

[0069] When the number of abnormal data points greater than the upper limit of the abnormal value is greater than the preset number threshold, it means that the injection molding machine has a large number of vibration anomalies in the time period of the target data set. A large number of vibration anomalies will affect the service life of the injection molding machine and may also affect the quality of the soles or insoles obtained by the injection molding machine. Therefore, a prompt message can be output so that the supervisor can maintain the injection molding machine to reduce the abnormalities of the injection molding machine.

[0070] In one embodiment, the target working stage of the injection molding machine of the footwear production line at the current moment can also be obtained; and the preset quantity threshold corresponding to the target working stage is determined from multiple quantity thresholds corresponding to multiple preset working stages.

[0071] Here, the injection molding machines on the footwear production line have different allowable vibrations corresponding to different preset working stages of the injection molding operation, or the same vibration has different degrees of influence on the quality of the injection molded products.

[0072] For example, multiple preset working stages may include feeding, melting, injection, filling, holding pressure and cooling; for example, the feeding stage is used to add plastic particles or powder into the hopper of the injection molding machine; the melting stage is used to feed the material in the hopper into the heating zone, and generate heat and shear force through the rotation of the screw, so that the material melts into a flowing state; the injection stage is used to inject the molten plastic into the closed mold through the injection nozzle under high pressure; the filling stage is used to make the plastic flow in the mold cavity and fill the entire mold space; the holding pressure stage is used to continue to maintain a certain pressure after the plastic filling is completed to ensure that the plastic can completely fill the mold and compensate for the shrinkage caused by cooling; the cooling stage is used to turn off the injection pressure of the injection molding machine and allow the plastic in the mold to solidify within the set cooling time.

[0073] Different preset working stages correspond to different quantity thresholds. For example, compared with the number of vibration anomalies that may occur in the filling stage, the number of vibration anomalies that may occur in the pressure holding stage is less, and the quantity threshold corresponding to the pressure holding stage can be less. In this way, more accurate monitoring of the vibration of the injection molding machine can be achieved at different working stages of the injection molding operation of the injection molding machine.

[0074] It should be understood that the features of some embodiments of the various applications described herein may be combined with each other, unless specifically stated otherwise.

[0075] Although terms such as "first", "second", and "third" may be used herein to describe various components, parts, regions, layers, or sections, these components, parts, regions, layers, or sections are not limited to these terms. Instead, these terms are only used to distinguish one component, part, region, layer, or section from another component, part, region, layer, or section. Therefore, without departing from the teachings of the examples described herein, the first component, part, region, layer, or section mentioned in the examples may also be referred to as the second component, part, region, layer, or section.

[0076] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description herein, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0077] In addition, the word "exemplary" is used herein to mean serving as an example, instance, or diagram. Any aspect or design described herein as "exemplary" is not necessarily to be understood as being advantageous over other aspects or designs. Instead, the use of the word exemplary is intended to present concepts in a concrete manner. As used herein, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or".

[0078] Likewise, although the present application has been shown and described with respect to one or more implementations, equivalent variations and modifications will occur to those skilled in the art upon reading and understanding this specification and the accompanying drawings. With particular regard to the various functions performed by the components (e.g., elements, resources, etc.) described above, unless otherwise noted, the terms used to describe such components are intended to correspond to any component (functionally equivalent) that performs the specific functions of the described components, even if not structurally equivalent to the disclosed structures.

[0079] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary technical means in the art that are not disclosed in the present application, and the specification and embodiments are only considered as exemplary.

[0080] It should be understood that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A method for monitoring the operating status of numerical control equipment in a footwear production line, characterized in that: include: Obtaining vibration data segments when an injection molding machine of a shoe production line performs an injection molding operation, and determining an upper limit of abnormal values ​​in the vibration data segments using a box plot algorithm, so as to use data points in the vibration data segments that are greater than the upper limit as initial abnormal upper limit values; For a target vibration data segment among the multiple vibration data segments, adjusting the initial abnormal upper limit value in the target vibration data segment according to initial abnormal upper limit values ​​in other vibration data segments except the target vibration data segment, to obtain a target abnormal upper limit value in the target vibration data segment; The target abnormal upper limit value in the target vibration data segment is obtained by: ,in, is the target abnormal upper limit value corresponding to the mth initial abnormal upper limit value in the target vibration data segment, is the mth initial abnormal upper limit value in the target vibration data segment, and exp is an exponential function with a natural constant as the base; is a first parameter value of the mth initial abnormal upper limit value in the target vibration data segment, used to characterize the degree of difference between the initial abnormal upper limit values ​​of the target vibration data segment and other vibration data segments; is the second parameter value of the mth initial abnormal upper limit value in the target vibration data segment, which is used to characterize the degree of difference between the pressure data and the vibration data when the injection molding machine performs an injection molding operation; is the first preset positive number, A positive number is preset for the second; The target abnormal upper limit value in the target vibration data segment and other data points except the initial abnormal upper limit value are formed into a target data set in chronological order; A box plot algorithm is used to determine whether there are abnormal data points in the target data set, and a prompt message is output when there are abnormal data points in the target data set. The prompt message is used to indicate that there is abnormal vibration in the injection molding machine of the shoe production line.

2. The method for monitoring the operation status of numerical control equipment of a footwear production line according to claim 1 is characterized in that: The first parameter value is obtained in the following way: ,in, is the first parameter value of the mth initial abnormal upper limit value in the target vibration data segment; is the third parameter value of the mth initial abnormal upper limit value in the target vibration data segment, which is used to characterize the difference between the mth initial abnormal upper limit value and the lower limit of the abnormal value in the target vibration data segment; norm is the normalization processing function, K is the number of other vibration data segments other than the target vibration data segment, To take the absolute value, is the mth initial abnormal upper limit value in the target vibration data segment, is the upper limit of the abnormal value of the kth vibration data segment other than the target vibration data segment; A positive number for the third preset.

3. The method for monitoring the operation status of numerical control equipment of a footwear production line according to claim 2 is characterized in that: The third parameter value of the initial abnormal upper limit is obtained by: ,in, is the third parameter value of the mth initial abnormal upper limit value in the target vibration data segment, is the mth initial abnormal upper limit value in the target vibration data segment, is the lower limit of the outlier value of the target vibration data segment, is the number of initial abnormal upper limit values ​​in the target vibration data segment.

4. The method for monitoring the operation status of numerical control equipment of a footwear production line according to claim 1, characterized in that: The second parameter value is obtained in the following way: , is the second parameter value of the mth initial abnormal upper limit value in the target vibration data segment, N is the number of vibration data in the preset time period where the mth initial abnormal upper limit value in the target vibration data segment is located, To take the absolute value, is the percentile of the ith vibration data in the preset time period where the mth initial abnormal upper limit value in the target vibration data segment is located, is the percentile of the ith pressure data within the preset time period where the mth initial abnormal upper limit value in the target vibration data segment is located.

5. The method for monitoring the operation status of numerical control equipment of a footwear production line according to claim 1 is characterized in that: Determining an upper limit of outliers in the vibration data segment using a box plot algorithm includes: Determining an upper quartile and a lower quartile in the vibration data segment using a box plot algorithm; The difference between the upper quartile and the lower quartile is taken as the interquartile range, and the upper limit of the outliers in the vibration data segment is determined based on the interquartile range and the upper quartile.

6. The method for monitoring the operation status of numerical control equipment of a footwear production line according to claim 1, characterized in that: Output prompt information when there are abnormal data points in the target data set, including: In the case where there are abnormal data points in the target data set, determining the number of abnormal data points in the target data set that are greater than an upper limit of the abnormal value; When the number of abnormal data points greater than the upper limit of the abnormal value is greater than a preset number threshold, a prompt message is output.

7. The method for monitoring the operation status of numerical control equipment of a footwear production line according to claim 6 is characterized in that: The method further comprises: Get the target working stage of the injection molding machine of the footwear production line at the current moment; A preset quantity threshold corresponding to the target working stage is determined from a plurality of quantity thresholds corresponding to a plurality of preset working stages.

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