CN117556185A - Intelligent process identification and counting method, system, terminal and medium of sewing equipment - Google Patents

Intelligent process identification and counting method, system, terminal and medium of sewing equipment Download PDF

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CN117556185A
CN117556185A CN202210921944.7A CN202210921944A CN117556185A CN 117556185 A CN117556185 A CN 117556185A CN 202210921944 A CN202210921944 A CN 202210921944A CN 117556185 A CN117556185 A CN 117556185A
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data
template
counting
dimension
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单一舒
曾树杰
韩安太
栗硕
曲凯朝
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Jack Technology Co Ltd
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06M—COUNTING MECHANISMS; COUNTING OF OBJECTS NOT OTHERWISE PROVIDED FOR
    • G06M1/00—Design features of general application
    • G06M1/08—Design features of general application for actuating the drive
    • G06M1/10—Design features of general application for actuating the drive by electric or magnetic means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract

The application provides an intelligent process identification and counting method, system, terminal and medium of a sewing device, wherein the method, the system, the terminal and the medium are used for acquiring an electric signal converted from mechanical motion of the sewing device and generating corresponding sewing data based on a time sequence according to the electric signal; reducing the sewing data into two dimensions, including the time interval dimension of each action of a motor in sewing equipment and the corresponding sewing needle number dimension; judging the procedure type of the sewing data and determining a procedure template; selecting counting and dividing points for counting the sewing data to be divided according to the motor movement time interval of the procedure template. The invention can identify the procedure corresponding to the data in the known multiple procedure templates, thereby reducing extra manpower work; only the electric signals in the sewing machine are collected, so that the data collection requirement is reduced; accurately judging the starting point and the ending point of each piece; the accuracy of the dividing points is improved by adopting a dynamic time warping method; is applicable to long procedures and short procedures, and has wide market prospect.

Description

Intelligent process identification and counting method, system, terminal and medium of sewing equipment
Technical Field
The application relates to the technical field of sewing, in particular to an intelligent process identification and counting method, system, terminal and medium of sewing equipment.
Background
Pay-per-parts is a widely used pay-per-parts method in factories today, in which how to accurately and efficiently count the parts has been studied. The intelligent metering mode mainly used at present comprises the steps of code scanning metering by workers and metering by a hanging system. Both schemes require that workers frequently carry out additional operations, the efficiency is low, the cost of the hanging system is high, and the two-dimensional code is required to be kept complete and cannot be lost or damaged by the code scanning meter, so that how to enable the sewing machine to automatically count the pieces becomes an important direction of the current research.
The existing automatic counting method of the sewing machine still needs to collect the data such as the sewing needle number, thread cutting times, presser foot lifting signals, seam reinforcing conditions, infrared geminate transistor signals with or without cloth (for example, patent CN102704214A and CN 107345346B), and needs to know which procedure is performed by workers in advance (for example, patent CN107345346B and CN 104018300A), which all need special manual operation, thus increasing the computational load of calculation and greatly reducing the efficiency. In addition, some current metering methods have certain application range requirements for the process, for example, the total needle number in the process is less than 400, and the applicability is not strong (for example, patent CN104018300 a). In addition, the current common counting method only focuses on the number of sewing pieces, and the accuracy of the starting and ending points of each piece is not required, but the actual working state of a worker cannot be accurately recorded, and further detailed analysis of the technical level of the worker cannot be provided for later.
In order to solve such problems and improve efficiency, so that data can play a larger role in subsequent research and analysis, a simpler, more universal and more accurate intelligent metering method is needed.
Disclosure of Invention
In view of the above drawbacks of the prior art, an object of the present application is to provide an intelligent process identification and counting method, system, terminal and medium for a sewing device, which are used for solving the problems of low sewing counting efficiency, low accuracy and the like in the prior art.
To achieve the above and other related objects, a first aspect of the present application provides an intelligent process identification and counting method of a sewing apparatus, including: acquiring an electric signal converted from mechanical motion of the sewing equipment, and generating corresponding sewing data based on time sequence according to the electric signal; the dimension of the sewing data is reduced to two dimensions, including the dimension of time interval of each action of a motor in the sewing equipment and the dimension of corresponding sewing needle number; judging the procedure type of the sewing data according to the time interval dimension of each action of the motor in the sewing equipment and the corresponding sewing needle number dimension, and determining a corresponding procedure template; after the process template is determined, selecting counting and dividing points according to the motor movement time interval of the process template to-be-divided sewing data so as to count workpieces.
In some embodiments of the first aspect of the present application, the determining, according to a time interval dimension of each action of the motor and a corresponding sewing needle number dimension in the sewing device, a process type to which the sewing data belongs and determining a corresponding process template includes: taking out data segments with the lengths suitable for the sewing data according to the lengths of different process templates, so as to compare the data segments with the process templates; predicting whether the process template can be segmented according to the stop point of each action of the motor in each process template, and dividing the segmented process template into a plurality of sub-processes; if the data segment compared with the segmented process template can be segmented into the same number of segments according to the time interval of each action of the motor, storing the segmented process template into an alternative library, and correspondingly forming each comparison group by each sub-segment segmented from the data segment and each sub-process segmented from the segmented process template to perform similarity calculation, and accumulating the similarity calculation result of each comparison group to obtain a total similarity calculation result between the segmented process template and the corresponding data segment; for the inseparable process templates, storing the inseparable process templates into an alternative library, and calculating the similarity between the inseparable process templates and corresponding data segments for comparison; and selecting a process template with the smallest difference degree with the input sewing data from the alternative library as a process template of the sewing data.
In some embodiments of the first aspect of the present application, the steps of forming each alignment group by corresponding each sub-segment separated from the data segment and each sub-process separated from the partitionable process template for similarity calculation includes calculating the degree of difference between the two in terms of needle count and sewing segment count based on a dynamic time alignment algorithm.
In some embodiments of the first aspect of the present application, the comparison of the first plurality of pieces of stitching data in the incoming stitching data includes comparing the first plurality of pieces of stitching data to a similarity average for each process template; if the deviation is too large, judging that the deviation occurs; if the deviation is not present or is small, it can be determined that the deviation is not present.
In some embodiments of the first aspect of the present application, the selecting a counting and dividing point for counting the sewing data to be divided according to the motor movement time interval of the process template includes: the process templates are divided into long process templates and short process templates according to the difference of the lengths of the process templates.
In some embodiments of the first aspect of the present application, the metering process for the long-procedure template includes: comparing the motor movement time interval of the procedure template with a threshold value, and then primarily screening a plurality of suspected segmentation points; calculating the similarity of the data in the segments and the process templates for each suspected segment point screened initially, and selecting the suspected segment point with the highest similarity as the final piece counting segment point; and readjusting the piece counting dividing point according to the beginning characteristic and the ending characteristic of the process template to judge whether the piece counting dividing point is the ending point of the sewn piece in the template.
In some embodiments of the first aspect of the present application, the metering process for the short-procedure template includes: calculating the difference degree between the data from the starting point to each suspected division point and the template data, and selecting the suspected division point with the smallest difference degree as the final piece counting division point.
To achieve the above and other related objects, a second aspect of the present application provides an intelligent process recognition and counting system of a sewing apparatus, comprising: the acquisition module is used for acquiring an electric signal converted from mechanical motion of the sewing equipment and generating corresponding sewing data based on a time sequence according to the electric signal; the dimension reduction module is used for reducing the dimension of the sewing data to two dimensions, and comprises the time interval dimension of each action of a motor in the sewing equipment and the corresponding sewing needle number dimension; the template module is used for judging the procedure type of the sewing data according to the time interval dimension of each action of the motor in the sewing equipment and the corresponding sewing needle number dimension and determining a corresponding procedure template; and the counting module is used for selecting counting and dividing points of the sewing data to be divided according to the motor movement time interval of the process template after the process template is determined so as to count the workpieces.
To achieve the above and other related objects, a third aspect of the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements an intelligent process recognition and counting method of the sewing apparatus.
To achieve the above and other related objects, a fourth aspect of the present application provides an electronic terminal, including: a processor and a memory; the memory is used for storing a computer program, and the processor is used for executing the computer program stored in the memory, so that the terminal executes the intelligent process identification and counting method of the sewing equipment.
As described above, the intelligent process identification and counting method, system, terminal and medium of the sewing equipment have the following beneficial effects:
(1) The process corresponding to the data can be identified from the known process templates, so that the templates do not need to be set or modified every time the process is replaced, additional manpower work can be reduced, and the cost is reduced.
(2) Only the electric signal in the sewing machine needs to be collected: and (5) the data of the sewing needle number during the movement of the motor, and recording the data condition under the time sequence and calculating. Thus, the requirements on data acquisition and recording are greatly reduced, the data transmission load is reduced, and the complexity of subsequent calculation is reduced.
(3) The starting point and the ending point of each piece are accurately judged, help is indirectly provided for improving the piece counting accuracy, and meanwhile, a basis is provided for further detailed analysis on the technical level of workers.
(4) Dynamic time warping is adopted, which is widely used in template matching problems, but is not used in calculation methods in the prior patent literature. By the method, the accuracy of the segmentation points is improved.
(5) The method is suitable for long procedures and short procedures, expands the application range of the procedures, and has wide market prospect.
Drawings
FIG. 1 is a schematic diagram of an embodiment of the present application.
Fig. 2 is a schematic diagram of an embodiment of the present application.
Fig. 3 is a schematic diagram of a process for identifying a procedure in an embodiment of the present application.
FIG. 4 is a schematic diagram showing the configuration of an intelligent process recognition and counting system of the stitching device according to an embodiment of the present application.
Fig. 5 is a schematic structural diagram of an electronic terminal according to an embodiment of the present application.
Detailed Description
Other advantages and effects of the present application will become apparent to those skilled in the art from the present disclosure, when the following description of the embodiments is taken in conjunction with the accompanying drawings. The present application may be embodied or carried out in other specific embodiments, and the details of the present application may be modified or changed from various points of view and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
It is noted that in the following description, reference is made to the accompanying drawings, which describe several embodiments of the present application. It is to be understood that other embodiments may be utilized and that mechanical, structural, electrical, and operational changes may be made without departing from the spirit and scope of the present application. The following detailed description is not to be taken in a limiting sense, and the scope of embodiments of the present application is defined only by the claims of the issued patent. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. Spatially relative terms, such as "upper," "lower," "left," "right," "lower," "upper," and the like, may be used herein to facilitate a description of one element or feature as illustrated in the figures as being related to another element or feature.
In this application, unless specifically stated and limited otherwise, the terms "mounted," "connected," "secured," "held," and the like are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the terms in this application will be understood by those of ordinary skill in the art as the case may be.
Furthermore, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes," and/or "including" specify the presence of stated features, operations, elements, components, items, categories, and/or groups, but do not preclude the presence, presence or addition of one or more other features, operations, elements, components, items, categories, and/or groups. The terms "or" and/or "as used herein are to be construed as inclusive, or meaning any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: a, A is as follows; b, a step of preparing a composite material; c, performing operation; a and B; a and C; b and C; A. b and C). An exception to this definition will occur only when a combination of elements, functions or operations are in some way inherently mutually exclusive.
In order to solve the problems in the background art, the invention provides an intelligent process identification and counting method, system, terminal and storage medium of sewing equipment, which are characterized in that a section of operation data of a sewing machine belonging to the same class of processes is input, the process of the sewing machine is firstly identified according to the running state and the number of sewing needles recorded in the operation data, and then counting analysis is carried out according to a template of the process, and meanwhile, the starting point and the end point of each part are recorded, so that efficient and accurate intelligent counting is realized.
In order to make the objects, technical solutions and advantages of the present invention more apparent, further detailed description of the technical solutions in the embodiments of the present invention will be given by the following examples with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Fig. 1 is a schematic flow chart of an intelligent process identification and counting method of a sewing device according to an embodiment of the present invention. It should be appreciated that the intelligent process identification and counting method in this embodiment may be applied to computer devices, such as computers, notebook computers, tablet computers, smart phones, smart bracelets, smart watches, smart helmets, smart televisions, etc.; the method is also applicable to servers which can be arranged on one or more entity servers according to various factors such as functions, loads and the like, and can also be formed by distributed or centralized server clusters.
In this embodiment, the intelligent process recognition and counting method of the sewing apparatus mainly includes the following steps, and each step will be explained in detail with reference to specific examples.
Step S11: acquiring an electric signal converted by mechanical motion of the sewing device, and generating corresponding sewing data based on time sequence according to the electric signal.
Specifically, the gateway device may receive the electrical signals converted by the mechanical motion of the components of the sewing machine, process the electrical signals into data about the specific motion of the components of the sewing machine (such as a motor, etc.) at specific times, and upload the data to the platform (i.e., the aforementioned computer device or server, etc.) in a time axis sequence. It should be appreciated that gateway devices, also known as gateway connectors or protocol converters, implement internetworking at the network layer, are complex internetworking devices that act as computer systems or devices that convert duplicate.
Step S12: and reducing the dimension of the sewing data to two dimensions, wherein the dimension comprises the time interval dimension of each action of a motor in the sewing equipment and the corresponding dimension of the number of sewing needles. After the data dimension reduction is carried out, the data structure can be more reasonable, the subsequent operation time is reduced, and the process identification and the related calculation of counting are convenient to carry out.
In some examples, the stitching data includes multiple dimensions prior to dimension reduction, and may include parameters of stitching line spacing, stitch length, and stitching, in addition to the remaining time interval dimension of each motion of the motor and corresponding stitching needle count dimensions.
Step S13: judging the procedure type of the sewing data according to the time interval dimension of each action of the motor in the sewing equipment and the corresponding sewing needle number dimension, and determining a corresponding procedure template; the method comprises the following specific steps:
firstly, taking out data segments with the lengths suitable for the sewing data according to the lengths of different process templates, so as to compare the data segments with the process templates; and predicting whether the process template can be divided according to the stop point of each action of the motor in each process template, and dividing the divided process template into a plurality of sub-processes.
And if the data segments compared with the segmented process template can be segmented into the same number of segments according to the time interval of each action of the motor, storing the segmented process template into an alternative library, and correspondingly forming each comparison group by each sub-segment segmented from the data segment and each sub-process segmented from the segmented process template to perform similarity calculation, and accumulating the similarity calculation result of each comparison group to obtain the total similarity calculation result between the segmented process template and the corresponding data segment.
For example, the divisible process template a is divided into 3 sub-processes, namely sub-process A1, sub-process A2 and sub-process A3, and the data segment B for comparison with the divisible template a can be divided into 3 sub-segments, namely sub-segment B1, sub-segment B2 and sub-segment B3. The sub-process A1 and the sub-segment B1 form a first comparison group, the sub-process A2 and the sub-segment B2 form a second comparison group, the sub-process A3 and the sub-segment B3 form a third comparison group, and the similarity calculation results of each comparison group are calculated respectively, for example, the calculated values are C1, C2 and C3 respectively, so that the similarity result of the comparison between the divisible process template a and the data segment B should be (c1+c2+c3).
In the process of identifying the process, the template process may be directly compared without being segmented. The specific steps are that according to the lengths of templates in different procedures, different lengths are correspondingly taken out from input data, the lengths are compared with the dimensions of the template such as the total needle number, the similarity degree of the sewing needle number and the corresponding needle number in the corresponding template when the motor moves each time, and the template with the smallest difference degree is taken as the template of the input data.
In some examples, the steps of dividing the data segment into sub-segments and dividing the sub-segments into sub-processes of the partitionable process template are correspondingly formed into comparison groups to calculate the similarity, which means that the difference degree of the two in the aspects of needle number, sewing segment number and the like is calculated.
The similarity calculation can adopt a similarity or distance function suitable for time series data to calculate the similarity, and the similarity degree judgment of the sewing needle number and the needle number in the template in the motor motion in the sewing machine data mentioned in the method adopts a dynamic time warping method; DTW (Dynamic Time Warping) refers to a dynamic time warping algorithm that can be used to measure the similarity between two independent time sequences; the DTW is widely applied to the template matching problem, and can better solve the problem that two groups of data are difficult to compare due to different lengths. In DTW, the euclidean distance method is used for distance measurement. In the DTW method, the distance is measured using the euclidean distance method, and the calculation may be performed by using the manhattan distance.
And storing the inseparable process templates into an alternative library for the inseparable process templates, and calculating the similarity between the inseparable process templates and the corresponding data segments for comparison. Specifically, the data segment and the process template may be compared differently from the total number of stitches, the similarity of the number of stitches per motor run and the number of stitches corresponding to the process template, and the like.
At this time, one or more process templates are stored in the candidate library, and the process templates may be non-partitionable process templates or partitionable process templates, but both the partitionable process templates and the non-partitionable process templates have a corresponding similarity calculation result. In the alternative library, a process template having the smallest difference (i.e., highest similarity) from the input sewing data is selected as the process template of the sewing data.
Further, in order to avoid deviation in process data due to a manual operation error or other unnecessary reasons, i.e., in order to reduce the error probability, for example, for some novice workers, since the business is not yet skilled, mistaking the wrong template (actually, the correct template) after comparing the sewing data of the first piece with the process template, an increase in error rate may be caused. Therefore, in this embodiment, the first several pieces of sewing data in the incoming sewing data are preferably compared and detected, specifically, the first several pieces of sewing data are compared with the average value of the similarity of the process templates; if the deviation is too large, judging that the deviation occurs; if the deviation is not present or is small, it can be determined that the deviation is not present.
In order to facilitate understanding of the process of identifying the procedure in this embodiment, in addition to the above text explanation, fig. 2 is used to assist in understanding, and the flow in this figure is actually described in step S13 and the explanation thereof.
Step S14: after the process template is determined, selecting counting and dividing points according to the motor movement time interval of the process template to-be-divided sewing data so as to count workpieces.
Preferably, the process templates are divided into a long process template and a short process template according to the different lengths of the process templates, and the long process template and the short process template are counted in different modes respectively, because for the long process template, errors can be accumulated, if the previous counting is wrong, the errors are accumulated continuously, and the final counting result is inevitably huge in deviation.
The counting process for the long-procedure template is as follows:
firstly, comparing a motor movement time interval of a process template with a threshold value, and then primarily screening a plurality of suspected dividing points as possible dividing points between pieces; it should be understood that here the so-called piece-to-piece dividing points are used to distinguish between two different sewn pieces, so that the number of dividing points determines the counting result.
And then, calculating the similarity between the segments and the data in the process template for each suspected segment point screened initially, and selecting the suspected segment point with the highest similarity as the final piece counting segment point. Specifically, the total needle count from each starting point to the suspected division points is calculated, if the total needle count meets the range of the target needle count (the target needle count is set according to the process template data), the similar degree of the sewing needle count and the corresponding needle count in the process template is taken as the main part when the motor moves each time, the dimensions of the total needle count, the sewing section count and the like are taken as the auxiliary calculation starting point to the difference degree of the data of each suspected division point and the template data, and the division point with the smallest calculation result is selected as the end point of one piece (namely the piece counting division point) for counting pieces.
Further, in order to avoid misjudgment of the dividing points of the piece due to some special conditions, the following technical means are added in the embodiment: and readjusting the piece counting dividing point according to the beginning characteristic and the ending characteristic of the process template to judge whether the piece counting dividing point is the ending point of the stitching piece in the template, wherein the comparison can be carried out between the dimensions such as time interval or needle number and the beginning/ending characteristic of the template. For example, some processes require sewing a pair of legs, so that two legs are sewn to complete a piece, but because the sewing data mapped by each leg is completely symmetrical, it is highly likely that the first leg is mistaken for a part count cut point (i.e., both legs are already sewn when one leg is sewn), and it is therefore necessary to compare the beginning and ending features of the process template with the part count cut point.
For the short-procedure template, the difference degree between the data from the starting point to each suspected dividing point and the template data can be directly calculated from the dimensions of the total needle number, the sewing segment number and the like, and the suspected dividing point with the smallest difference degree (namely the highest similarity) is selected as the final piece counting dividing point.
It should be noted that, in the counting process, different methods may be adopted to perform counting segmentation. In the case of determining the start point of data, all points where the total needle count of the sewing machine data satisfies the target needle count range when the end point is selected. For each end point, the data to be compared is taken out, and the degree of difference between the data and the template is calculated (the same method as the original method). For the point with the smallest numerical value of the calculation result, the point with the closest time and meeting the time interval requirement is selected as the ending point of the piece. In addition, in the counting process, the method of searching the dividing points of the dividing pieces and the pieces can also adopt a mode of segmenting the templates, then finding the sub-process of the corresponding templates in the data, and finally combining the small processes into the complete process data of the corresponding templates, thereby completing the dividing and counting of one piece.
To facilitate understanding of the process of identifying the procedure in this embodiment, in addition to the above text explanation, fig. 3 is used to assist in understanding, and the flow in this figure is actually described in step S14 and the explanation thereof.
As shown in fig. 4, a schematic structural diagram of an intelligent process recognition and counting system of a sewing device according to the present embodiment is shown. The intelligent process identification and counting system 400 of this embodiment includes: an acquisition module 401, a dimension reduction module 402, a template module 403 and a piece counting module 404.
The acquisition module 401 is used for acquiring an electric signal converted by mechanical motion of the sewing equipment and generating corresponding sewing data based on time sequence according to the electric signal; the dimension reduction module 402 is configured to reduce the dimension of the sewing data to two dimensions, including a time interval dimension of each action of the motor in the sewing device and a corresponding sewing needle number dimension; the template module 403 is configured to determine a process type to which the sewing data belongs and determine a corresponding process template according to a time interval dimension of each action of the motor in the sewing device and a corresponding sewing needle number dimension; the counting module 404 is used for selecting counting and dividing points for counting the sewing data to be divided according to the motor movement time interval of the process template after the process template is determined.
It should be noted that, the intelligent process identification and counting system in this embodiment is similar to the intelligent process identification and counting method in the above description, so that the description is omitted.
It should be understood that the division of the modules of the above apparatus is merely a division of a logic function, and may be fully or partially integrated into a physical entity or may be physically separated when actually implemented. And these modules may all be implemented in software in the form of calls by the processing element; or can be realized in hardware; the method can also be realized in a form of calling software by a processing element, and the method can be realized in a form of hardware by a part of modules. For example, the component counting module may be a processing element which is set up separately, may be implemented in a chip of the above-mentioned apparatus, or may be stored in a memory of the above-mentioned apparatus in the form of a program code, and the function of the component counting module may be invoked and executed by a processing element of the above-mentioned apparatus. The implementation of the other modules is similar. In addition, all or part of the modules can be integrated together or can be independently implemented. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in a software form.
For example, the modules above may be one or more integrated circuits configured to implement the methods above, such as: one or more application specific integrated circuits (Application Specific Integrated Circuit, abbreviated as ASIC), or one or more microprocessors (digital signal processor, abbreviated as DSP), or one or more field programmable gate arrays (Field Programmable Gate Array, abbreviated as FPGA), or the like. For another example, when a module above is implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a central processing unit (Central Processing Unit, CPU) or other processor that may invoke the program code. For another example, the modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).
Fig. 5 is a schematic structural diagram of an electronic terminal according to an embodiment of the present invention. The electronic terminal provided in this example includes: a processor 51, a memory 52, a communicator 53; the memory 52 is connected to the processor 51 and the communicator 53 through the system bus and performs communication with each other, the memory 52 is used for storing a computer program, the communicator 53 is used for communicating with other devices, and the processor 51 is used for running the computer program to enable the electronic terminal to execute the steps of the intelligent process identification and counting method of the sewing device.
The system bus mentioned above may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, or the like. The system bus may be classified into an address bus, a data bus, a control bus, and the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus. The communication interface is used to enable communication between the database access apparatus and other devices (e.g., clients, read-write libraries, and read-only libraries). The memory may comprise random access memory (Random Access Memory, RAM) and may also comprise non-volatile memory (non-volatile memory), such as at least one disk memory.
The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but also digital signal processors (Digital Signal Processing, DSP for short), application specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), field-programmable gate arrays (Field-Programmable Gate Array, FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
The invention also provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, realizes the intelligent process identification and counting method of the sewing equipment.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by computer program related hardware. The aforementioned computer program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
In the embodiments provided herein, the computer-readable storage medium may include read-only memory, random-access memory, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, flash memory, U-disk, removable hard disk, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. In addition, any connection is properly termed a computer-readable medium. For example, if the instructions are transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. It should be understood, however, that computer-readable and data storage media do not include connections, carrier waves, signals, or other transitory media, but are intended to be directed to non-transitory, tangible storage media. Disk and disc, as used herein, includes Compact Disc (CD), laser disc, optical disc, digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers.
In summary, the present application provides an intelligent process identifying and counting method, system, terminal and medium for a sewing device, which can identify a process corresponding to data in a plurality of known process templates, so that the templates do not need to be set or modified every time of process replacement, thereby reducing extra manpower and cost; only the electric signal in the sewing machine needs to be collected: and (5) the data of the sewing needle number during the movement of the motor, and recording the data condition under the time sequence and calculating. The requirements on data acquisition and recording are greatly reduced, meanwhile, the data transmission load is reduced, and the complexity of subsequent calculation is also reduced; the starting point and the ending point of each piece are accurately judged, help is indirectly provided for improving the piece counting accuracy, and meanwhile, a basis is provided for further detailed analysis on the technical level of workers in the follow-up process; dynamic time warping is adopted, which is widely used in template matching problems, but is not used in calculation methods in the prior patent literature. By the method, the accuracy of the segmentation points is improved; the method is suitable for long procedures and short procedures, expands the application range of the procedures, and has wide market prospect. Therefore, the method effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles of the present application and their effectiveness, and are not intended to limit the application. Modifications and variations may be made to the above-described embodiments by those of ordinary skill in the art without departing from the spirit and scope of the present application. Accordingly, it is intended that all equivalent modifications and variations which may be accomplished by persons skilled in the art without departing from the spirit and technical spirit of the disclosure be covered by the claims of this application.

Claims (10)

1. An intelligent process identification and counting method of sewing equipment is characterized by comprising the following steps:
acquiring an electric signal converted from mechanical motion of the sewing equipment, and generating corresponding sewing data based on time sequence according to the electric signal;
the dimension of the sewing data is reduced to two dimensions, including the dimension of time interval of each action of a motor in the sewing equipment and the dimension of corresponding sewing needle number;
judging the procedure type of the sewing data according to the time interval dimension of each action of the motor in the sewing equipment and the corresponding sewing needle number dimension, and determining a corresponding procedure template;
after the process template is determined, selecting counting and dividing points according to the motor movement time interval of the process template to-be-divided sewing data so as to count workpieces.
2. The intelligent process identification and counting method of sewing equipment according to claim 1, wherein the steps of determining the process type to which the sewing data belong and determining the corresponding process template according to the time interval dimension of each action of the motor in the sewing equipment and the corresponding sewing needle number dimension comprise:
taking out data segments with the lengths suitable for the sewing data according to the lengths of different process templates, so as to compare the data segments with the process templates;
predicting whether the process template can be segmented according to the stop point of each action of the motor in each process template, and dividing the segmented process template into a plurality of sub-processes;
if the data segment compared with the segmented process template can be segmented into the same number of segments according to the time interval of each action of the motor, storing the segmented process template into an alternative library, and correspondingly forming each comparison group by each sub-segment segmented from the data segment and each sub-process segmented from the segmented process template to perform similarity calculation, and accumulating the similarity calculation result of each comparison group to obtain a total similarity calculation result between the segmented process template and the corresponding data segment;
for the inseparable process templates, storing the inseparable process templates into an alternative library, and calculating the similarity between the inseparable process templates and corresponding data segments for comparison;
and selecting a process template with the smallest difference degree with the input sewing data from the alternative library as a process template of the sewing data.
3. The intelligent process recognition and counting method of a sewing machine according to claim 1, wherein the steps of forming each comparison group corresponding to each sub-process divided from the data segment and each sub-process divided from the partitionable process template for similarity calculation include calculating the degree of difference between the two in terms of needle count and sewing segment count based on a dynamic time alignment algorithm.
4. The intelligent process recognition and counting method of sewing equipment according to claim 1, wherein the comparison and detection of the first several items of sewing data in the incoming sewing data comprises comparing the first several items of sewing data with a similarity average value of each process template; if the deviation is too large, judging that the deviation occurs; if the deviation is not present or is small, it can be determined that the deviation is not present.
5. The intelligent process recognition and counting method of the sewing equipment according to claim 1, wherein the selecting the counting dividing points for counting the sewing data to be divided according to the motor movement time interval of the process template comprises: the process templates are divided into long process templates and short process templates according to the difference of the lengths of the process templates.
6. The intelligent process recognition and counting method for sewing equipment according to claim 5, wherein the counting process for the long process template comprises:
comparing the motor movement time interval of the procedure template with a threshold value, and then primarily screening a plurality of suspected segmentation points;
calculating the similarity of the data in the segments and the process templates for each suspected segment point screened initially, and selecting the suspected segment point with the highest similarity as the final piece counting segment point;
and readjusting the piece counting dividing point according to the beginning characteristic and the ending characteristic of the process template to judge whether the piece counting dividing point is the ending point of the sewn piece in the template.
7. The intelligent process recognition and counting method for sewing equipment according to claim 5, wherein the counting process for the short process template comprises: calculating the difference degree between the data from the starting point to each suspected division point and the template data, and selecting the suspected division point with the smallest difference degree as the final piece counting division point.
8. An intelligent process identification and counting system of a sewing device, comprising:
the acquisition module is used for acquiring an electric signal converted from mechanical motion of the sewing equipment and generating corresponding sewing data based on a time sequence according to the electric signal;
the dimension reduction module is used for reducing the dimension of the sewing data to two dimensions, and comprises the time interval dimension of each action of a motor in the sewing equipment and the corresponding sewing needle number dimension;
the template module is used for judging the procedure type of the sewing data according to the time interval dimension of each action of the motor in the sewing equipment and the corresponding sewing needle number dimension and determining a corresponding procedure template;
and the counting module is used for selecting counting and dividing points of the sewing data to be divided according to the motor movement time interval of the process template after the process template is determined so as to count the workpieces.
9. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the intelligent process identification and counting method of a sewing apparatus according to any one of claims 1 to 7.
10. An electronic terminal, comprising: a processor and a memory;
the memory is used for storing a computer program;
the processor is configured to execute the computer program stored in the memory, so that the terminal performs the intelligent process identification and counting method of the sewing apparatus according to any one of claims 1 to 7.
CN202210921944.7A 2022-08-02 2022-08-02 Intelligent process identification and counting method, system, terminal and medium of sewing equipment Pending CN117556185A (en)

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CN202210921944.7A CN117556185A (en) 2022-08-02 2022-08-02 Intelligent process identification and counting method, system, terminal and medium of sewing equipment
PCT/CN2023/090560 WO2024027227A1 (en) 2022-08-02 2023-04-25 Sewing device intelligent process identification and piece counting method and system, and terminal, and medium

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JP2009160084A (en) * 2007-12-28 2009-07-23 Juki Corp Work analyzer of sewing machine
JP5130159B2 (en) * 2008-09-05 2013-01-30 Ｊｕｋｉ株式会社 Work analysis device
KR102043885B1 (en) * 2017-12-01 2019-12-02 김태강 Smart counter for manufacturing product of sewing and method, and sewing manufacture management system including it and method for processing thereof
WO2021125727A1 (en) * 2019-12-18 2021-06-24 한국생산기술연구원 Integrated system for manufacturing apparel

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