A monitoring system for spinning production

Abstract

The invention discloses a monitoring system for spinning production, and relates to the technical field of spinning monitoring. The invention monitors the production process of spinning by setting a production monitoring module, a video processing unit intercepts and traces back the video monitoring data of finished products with defects detected in quality inspection, and a manager locates the cause of the defect based on the defect location information based on a manual deviation correction unit, and the manager can adjust the defect location information to make the defect location information of the finished products with defects detected in quality inspection more accurate; the deviation correction analysis module analyzes the defect location information of all past finished products and their intervention image sets, and the auxiliary deviation correction unit re-intercepts and optimizes the video monitoring data that has been intercepted and shortened based on the review and deviation correction information combined with the manager's perspective, so that not only the efficiency and accuracy of the review are improved, but also the storage capacity of the video monitoring data for defective finished products is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of spinning monitoring, and in particular to a monitoring system for spinning production. Background Art

[0002] Spinning is the foundation and initial stage of the textile industry. It involves the process of transforming natural or chemical fibers into yarn. With the continuous growth of global market demand and the increasing demand of consumers for high-quality textiles, traditional spinning production methods are facing the dual pressure of improving efficiency and product quality. In addition, the intensification of market competition forces production companies to constantly seek innovations in production methods to reduce production costs and meet stricter environmental protection requirements. In this context, modern spinning production monitoring systems came into being;

[0003] This process greatly reduces the time cost of manual screening and saves staff from the tedious task of reviewing massive amounts of video surveillance data one by one. However, although the intercepted time period has been greatly shortened compared to all video surveillance data, it is still long for specific defects, and the interception time rules fail to fully consider the perspective of manual review, which reduces efficiency and accuracy to a certain extent.

[0004] In order to solve the above problems, the present invention proposes a solution. Summary of the invention

[0005] The object of the present invention is to provide a monitoring system for spinning production, in order to solve the problems raised in the above background technology;

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A monitoring system for spinning production, comprising:

[0008] A quality inspection processing module is used to perform quality inspection on the finished product after the spinning production is completed. The quality inspection processing module includes a video processing unit;

[0009] After receiving the transmitted defect quality inspection information of the finished product, the video processing unit extracts the shooting time corresponding to the first frame of the image of the spinning production defect type appearing from the video monitoring data of the finished product according to the spinning production defect type and the finished product image data carried therein, and shoots the finished product to obtain its finished product image data;

[0010] Based on the camera moment, the video surveillance data with a time interval of P1 before and after are intercepted from the video surveillance data of the finished product as the defect location data of the finished product, and the defect location information of the finished product is generated according to the defect location data of the finished product and the spinning production defect type, where P1 is the preset backtracking time corresponding to the spinning production defect type;

[0011] An optimization correction module is used for management personnel to quickly locate the cause of the defect type. The optimization correction module includes a manual correction unit. After the management personnel views the defect location data of the finished product, the manual correction unit extracts all frame images whose viewing time exceeds P2 time, and summarizes them into an intervention image set of the finished product;

[0012] After receiving the transmitted defect location information of the finished product, the auxiliary correction unit obtains the corresponding review correction information according to the type of spinning production defect carried therein, and optimizes the defect location data carried in the defect location information of the finished product according to the preset auxiliary optimization rules according to all the review correction intervals carried in the review correction information to obtain new defect location data of the finished product;

[0013] The deviation correction analysis module analyzes the defect location information of all finished products in the past and their intervention image sets to obtain the review and correction information of all spinning production defect types.

[0014] Furthermore, it also includes a production monitoring module, which monitors the spinning production process in real time, and binds the video monitoring data of the finished product after the spinning production is completed and the video monitoring data of the spinning production process to obtain the video monitoring data of the finished product.

[0015] Furthermore, the quality inspection processing module also includes a finished product quality inspection unit, in which a plurality of sample images of qualified spinning products and a plurality of defect sample images corresponding to all spinning production defect types are pre-stored.

[0016] Beneficial effects of the present invention:

[0017] The present invention monitors the spinning production process by setting a production monitoring module, and the video processing unit intercepts and traces the video monitoring data of the finished product with defects in quality inspection to obtain corresponding defect location information. The management personnel locates the cause of the defect based on the manual correction unit according to the defect location information. In this way, the search for the cause of the defect is faster and more convenient, and the management personnel can adjust the defect location information to make the defect location information of the finished product with defects in quality inspection more accurate.

[0018] The present invention sets a deviation correction analysis module to analyze the defect location information of all past finished products and their intervention image sets to obtain the review and correction information of all types of spinning production defects. The analysis data includes the defect location information actively adjusted by the management personnel. The auxiliary deviation correction unit re-intercepts and optimizes the video surveillance data that has been intercepted and shortened based on the review and correction information combined with the management personnel's perspective, thereby further shortening the duration of the video surveillance data that the management personnel have to view. In this way, not only the efficiency and accuracy of the review are improved, but also the storage capacity of the video surveillance data for defective finished products is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention will be further described below in conjunction with the accompanying drawings.

[0020] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Embodiment 1, as Figure 1 As shown, a monitoring system for spinning production includes a production monitoring module, a quality inspection processing module, an optimization correction module and a correction analysis module;

[0023] Production monitoring module, used to monitor the spinning production process;

[0024] The production monitoring module monitors the spinning production process in real time, and binds the finished product after the spinning production is completed and the video monitoring data of the spinning production process to obtain the video monitoring data of the finished product;

[0025] The production monitoring module transmits the video monitoring data of the finished product to the quality inspection processing module;

[0026] A quality inspection processing module is used to perform quality inspection on the finished product. The quality inspection processing module includes a finished product quality inspection unit and a video processing unit;

[0027] After receiving the transmitted video monitoring data of the finished product, the quality inspection processing module transmits the data to the video processing unit for temporary storage;

[0028] The finished product quality inspection unit performs quality inspection on the finished product obtained after the spinning production is completed. The finished product quality inspection unit pre-stores a number of sample images of qualified spinning products and a number of defect sample images corresponding to all types of spinning production defects, wherein the spinning production defect types refer to various types of problems or defects that may occur in the spinning production process and can directly lead to the quality and performance of the spinning products;

[0029] In this embodiment, the types of spinning production defects include uneven diameter and density of finished products, breakage of finished products, and excessive fibers on the surface of finished products;

[0030] The finished product quality inspection unit takes a picture of the finished product after the spinning production is completed to obtain the corresponding finished product image data, and compares the finished product image data with several sample images of qualified spinning products and several defect sample images corresponding to all spinning production defect types;

[0031] After the comparison is completed, if the finished product image data is consistent with any of the sample images, the finished product is determined to be a qualified finished product, and the video monitoring data of the qualified finished product is transmitted to the cloud monitoring module for storage;

[0032] On the contrary, if the finished product image data is consistent with any defect sample image, the spinning production defect type corresponding to the defect sample image consistent with the finished product image data is obtained, and defect quality inspection information of the finished product is generated according to the spinning production defect type and its video monitoring data transmission;

[0033] The finished product quality inspection unit transmits the defect quality inspection information of the finished product to the video processing unit. After receiving the transmitted defect quality inspection information of the finished product, the video processing unit extracts the shooting time corresponding to the first frame of the image with the spinning production defect type from the video monitoring data of the finished product according to the spinning production defect type and the finished product image data carried therein;

[0034] Based on the shooting moment, the video surveillance data with a time interval of P1 before and after are intercepted from the video surveillance data of the finished product as the defect location data of the finished product, wherein the time interval of P1 before and after is for the shooting moment, that is, the shooting moment corresponding to the first frame and the last frame of the finished product defect location data and the duration between the extracted shooting moment are both P1 time, and P1 is the preset backtracking time corresponding to the spinning production defect type;

[0035] A video processing unit generates defect location information of the finished product according to the defect location data of the finished product and the type of spinning production defects, and transmits the information to the optimization and correction module for storage;

[0036] An optimization and correction module is used for management personnel to quickly locate the cause of the defect type, the optimization and correction module;

[0037] The optimization correction module includes a manual correction unit and an auxiliary correction unit;

[0038] After receiving the defect location information transmitted to the finished product, the optimization correction module transmits the information to the manual correction unit for storage, and provides it to the management personnel for review and determination of the cause of the spinning production defect type in the finished product;

[0039] After the manager views the defect location data of the finished product, the manual correction unit extracts all frame images whose viewing time exceeds P2, and summarizes them into an intervention image set of the finished product. The manual correction unit transmits the intervention image set of the finished product to the video processing unit for storage, where P2 is the preset viewing record time.

[0040] The correction analysis module is used to periodically analyze the defect location information of all finished products and their intervention image sets stored in the optimization correction module. The analysis steps are as follows:

[0041] S11: First, a spinning production defect type is selected as the type to be corrected, and defect location information of all finished products whose spinning production defect type is the type to be corrected extracted from the optimization correction module is marked as A1, A2, ..., Aa, where a≥1;

[0042] The intervention image sets of the finished product corresponding to the defect location information are marked as B1, B2, ..., Ba in sequence;

[0043] S12: extract all frame images contained in the intervention image set B1, and mark all the extracted frame images as C1, C2, ..., Cc in order from far to near according to the distance between the shooting time corresponding to each frame image and the current time, where c≥1;

[0044] S13: According to the shooting time of frame images C1, C2, ..., Cc, all frame images with an interval time less than or equal to P3 are taken as frame correction sets, and d frame correction sets can be obtained. It should be noted here that the frame images in the frame correction set are arranged in order, from left to right according to the distance from the shooting time to the current time, and P3 is the preset correction review time.

[0045] S14: extract the first frame image in each frame correction set respectively, and mark the frame correction sets corresponding to all the extracted frame images as D1, D2, ..., Dd in order from far to near according to the order of the distance between the shooting time corresponding to each extracted frame image and the current time;

[0046] S15: Calculate and obtain frame node indicators H1, H2, ..., He of the frame images E1, E2, ..., Ee based on the defect location information A1 according to a preset calculation rule. The calculation rule is as follows:

[0047] S151: Mark the first frame image in the frame correction set D1 as E1, and obtain the sequence F1 of the frame image E1 in the defect location data in the defect location information A1. It should be noted here that the sequence of the frame images in the defect location data is arranged linearly according to time, forming the time axis of the defect location data. Each frame is equivalent to an element in this sequence and is numbered and stored according to the order in which they appear in the video.

[0048] S152: Calculate the frame node index H1 of the frame image E1 based on the defect location information A1 using the formula H1=F1 / G1, where G1 is the total number of frame images in the defect location data in the defect location information A1;

[0049] S153: sequentially marking the first frame image in the frame correction set D2, D3, ..., Dd as E2, E3, ..., Ed;

[0050] According to S151 to S152, frame node indicators H2, H3, ..., He of the frame images E2, E3, ..., Ee based on the defect location information A1 are calculated respectively;

[0051] S16: extract the last frame image in the frame correction set D1, mark it as I1, and obtain the frame correction interval J1 of the frame correction set D1 based on the defect location information A1 according to the frame node index H1 and the frame node index of the frame image I1;

[0052] S17: According to S16, frame correction intervals J2, ..., Jd of the frame correction sets D2, D3, ..., Dd based on the defect location information A1 are obtained in sequence. At this time, there is a corresponding relationship as follows: the intervention image set B1 corresponds to the frame correction intervals J1, J2, ..., Jd;

[0053] S18: According to S11 to S17, several frame correction intervals corresponding to the intervention image sets B1, B2, ..., Ba are calculated in sequence;

[0054] S19: Determine whether the inspection interval meets the correction standard according to the preset inspection and judgment rules. The inspection and judgment rules are as follows:

[0055] S191: Select the frame correction interval J1 as the interval to be examined, create an overlapping frequency variable K1 of the interval to be examined, and the initial value of K1 is 0;

[0056] S192: Obtain the number L1 of frame correction intervals intersecting with the interval to be examined from the plurality of frame correction intervals corresponding to the intervention image set B2, and determine L1. If L1≠1, then use the formula M1=1+L1×ɑ1 to calculate and obtain the overlap index M1 of the intervention image set B2 based on the intervention image set B1. Otherwise, the overlap index M1 of the intervention image set B2 based on the intervention image set B1=1, and ɑ1 is a preset adjustment factor.

[0057] S193: According to S191 to S192, overlapping indexes M2, M3, ..., Ma-1 of the intervention image sets B3, B4, ..., Ba based on the intervention image set B1 are calculated in sequence;

[0058] S194: Calculate the global review index N1 of the interval to be reviewed using the formula N1=M1+ M2+…+Ma-1, and compare N1 with PN1, where PN1 is the preset global review standard index;

[0059] S195: If N1≥PN1, it is determined that the interval to be reviewed meets the correction standard, and all frame correction intervals that have intersections with the interval to be reviewed among the several frame correction intervals corresponding to the intervention image sets B2, B3, ..., Ba are traversed, and the minimum and maximum values ​​of the frame node indicators are extracted therefrom. The review correction interval of the interval to be reviewed is generated based on the extracted minimum and maximum values ​​of the frame node indicators. Otherwise, it is determined that the interval to be reviewed does not meet the correction standard;

[0060] S110: According to S19, a plurality of frame correction intervals corresponding to the intervention image sets B1, B2, ..., Ba are selected in sequence as the intervals to be reviewed, and the review correction intervals of all frame correction intervals that are determined to meet the correction standard are obtained;

[0061] Generating review and correction information of the type to be corrected according to the review and correction intervals of all frame correction intervals that are determined to meet the correction standard, and transmitting the information to the auxiliary correction unit for updating and storage;

[0062] S111: According to S11, all types of spinning production defects are selected in turn as types to be corrected, and according to S12 to S110, review and correction information of all types of spinning production defects is generated, and the information is transmitted to the auxiliary correction unit for updating and storage;

[0063] Embodiment 2 is implemented on the basis of embodiment 1;

[0064] After the review and correction information of all spinning production defect types is stored in the auxiliary correction unit, the optimization correction module receives the defect location information of the transmitted finished product and transmits it to the auxiliary correction unit;

[0065] After receiving the transmitted defect location information of the finished product, the auxiliary correction unit obtains the corresponding review correction information according to the type of spinning production defect carried therein, and optimizes the defect location data carried in the defect location information of the finished product according to the preset auxiliary optimization rules according to all the review correction intervals carried in the review correction information. The auxiliary optimization rules are as follows:

[0066] S21: Mark all the review and correction intervals in the review and correction information as Q1, Q2, ..., Qq, q≥1;

[0067] S22: Mark the left and right endpoint values ​​of the review and correction interval Q1 as R1 and R2 respectively;

[0068] S23: Calculate the camera moments corresponding to R1 and R2 from the defect location data of the finished product according to R1 and R2, and extract the defect location data at these two camera moments from the defect location data, and use them as auxiliary correction data for the review correction interval Q1;

[0069] S24: According to S23, auxiliary correction data of the inspection correction intervals Q1, Q2, ..., Qq are respectively calculated and obtained;

[0070] The auxiliary correction unit generates defect location data of the finished product based on the auxiliary correction data of the review correction intervals Q1, Q2, ..., Qq, and transmits it to the manual correction unit in the optimization correction module for storage;

[0071] In the description of the specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0072] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

[0073] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A monitoring system for spinning production, characterized in that: include: A quality inspection processing module is used to perform quality inspection on the finished product after the spinning production is completed. The quality inspection processing module includes a video processing unit; After receiving the transmitted defect quality inspection information of the finished product, the video processing unit extracts the shooting time corresponding to the first frame of the image of the spinning production defect type appearing from the video monitoring data of the finished product according to the spinning production defect type and the finished product image data carried therein, and shoots the finished product to obtain its finished product image data; Based on the camera moment, the video surveillance data with a time interval of P1 before and after are intercepted from the video surveillance data of the finished product as the defect location data of the finished product, and the defect location information of the finished product is generated according to the defect location data of the finished product and the spinning production defect type, where P1 is the preset backtracking time corresponding to the spinning production defect type; An optimization correction module is used for management personnel to quickly locate the cause of the defect type. The optimization correction module includes a manual correction unit. After the management personnel views the defect location data of the finished product, the manual correction unit extracts all frame images whose viewing time exceeds P2 time, and summarizes them into an intervention image set of the finished product; After receiving the transmitted defect location information of the finished product, the auxiliary correction unit obtains the corresponding review correction information according to the type of spinning production defect carried therein, and optimizes the defect location data carried in the defect location information of the finished product according to the preset auxiliary optimization rules according to all the review correction intervals carried in the review correction information to obtain new defect location data of the finished product; The deviation correction analysis module analyzes the defect location information of all finished products in the past and their intervention image sets to obtain the review and correction information of all spinning production defect types. The steps for analyzing and obtaining the review and correction information of all spinning production defect types are as follows: S11: firstly, a spinning production defect type is selected as the type to be corrected, and defect location information of all finished products whose spinning production defect type is the type to be corrected extracted from the optimization correction module is marked as A1, A2, ..., Aa, where a≥1; The intervention image sets of the finished product corresponding to the defect location information are marked as B1, B2, ..., Ba in sequence; S12: extract all frame images contained in the intervention image set B1, and mark all the extracted frame images as C1, C2, ..., Cc in order from far to near according to the distance between the shooting time corresponding to each frame image and the current time, where c≥1; S13: according to the shooting time of the frame images C1, C2, ..., Cc, all the frame images with an interval length less than or equal to P3 are taken as frame correction sets, and d frame correction sets can be obtained; S14: extract the first frame image in each frame correction set respectively, and mark the frame correction sets corresponding to all the extracted frame images as D1, D2, ..., Dd in order from far to near according to the order of the distance between the shooting time corresponding to each extracted frame image and the current time; S15: Calculate and obtain frame node indicators H1, H2, ..., He of the frame images E1, E2, ..., Ee based on the defect location information A1 according to a preset calculation rule; S16: extract the last frame image in the frame correction set D1, mark it as I1, and obtain the frame correction interval J1 of the frame correction set D1 based on the defect location information A1 according to the frame node index H1 and the frame node index of the frame image I1; S17: According to S16, frame correction intervals J2, ..., Jd of the frame correction sets D2, D3, ..., Dd based on the defect location information A1 are obtained in sequence. At this time, there is a corresponding relationship as follows: the intervention image set B1 corresponds to the frame correction intervals J1, J2, ..., Jd; S18: According to S11 to S17, several frame correction intervals corresponding to the intervention image sets B1, B2, ..., Ba are calculated in sequence; S19: determining whether the interval to be examined meets the correction standard according to the preset examination and determination rules; if it is determined to meet the correction standard, calculating and obtaining the examination and correction interval of the interval to be examined; S110: According to S19, a plurality of frame correction intervals corresponding to the intervention image sets B1, B2, ..., Ba are selected in sequence as the intervals to be reviewed, and the review correction intervals of all frame correction intervals that are determined to meet the correction standard are obtained; Generating review and correction information of the type to be corrected according to the review and correction intervals of all frame correction intervals that are determined to meet the correction standard; S111: According to S11, all types of spinning production defect types are selected in turn as types to be corrected, and according to S12 to S110, review and correction information of all types of spinning production defect types is generated.

2. A monitoring system for spinning production according to claim 1, characterized in that: It also includes a production monitoring module, which monitors the spinning production process in real time, and binds the video monitoring data of the finished product after the spinning production is completed and the video monitoring data of the spinning production process to obtain the video monitoring data of the finished product.

3. A monitoring system for spinning production according to claim 1, characterized in that: The quality inspection processing module also includes a finished product quality inspection unit, in which a number of sample images of qualified spinning products and a number of defect sample images corresponding to all spinning production defect types are pre-stored.

4. A monitoring system for spinning production according to claim 1, characterized in that: The calculation rules for calculating the frame node indicators H1, H2, ..., He of the frame images E1, E2, ..., Ee based on the defect location information A1 are as follows: S151: Mark the first frame image in the frame correction set D1 as E1, and obtain the order F1 of the frame image E1 in the defect location data in the defect location information A1; S152: Calculate the frame node index H1 of the frame image E1 based on the defect location information A1 using the formula H1=F1 / G1, where G1 is the total number of frame images in the defect location data in the defect location information A1; S153: sequentially marking the first frame image in the frame correction set D2, D3, ..., Dd as E2, E3, ..., Ed; According to S151 to S152, frame node indicators H2, H3, ..., He of frame images E2, E3, ..., Ee based on defect location information A1 are calculated and acquired respectively.

5. A monitoring system for spinning production according to claim 1, characterized in that: The review and determination rules for determining whether the review interval meets the correction standards are as follows: S191: Select the frame correction interval J1 as the interval to be examined, create an overlapping frequency variable K1 of the interval to be examined, and the initial value of K1 is 0; S192: Obtain the number L1 of frame correction intervals intersecting with the interval to be examined from the plurality of frame correction intervals corresponding to the intervention image set B2, and determine L1. If L1≠1, then use the formula M1=1+L1×ɑ1 to calculate and obtain the overlap index M1 of the intervention image set B2 based on the intervention image set B1. Otherwise, the overlap index M1 of the intervention image set B2 based on the intervention image set B1=1, and ɑ1 is a preset adjustment factor. S193: According to S191 to S192, overlapping indexes M2, M3, ..., Ma-1 of the intervention image sets B3, B4, ..., Ba based on the intervention image set B1 are calculated in sequence; S194: Calculate the global review index N1 of the interval to be reviewed using the formula N1=M1+ M2+...+Ma-1, and compare N1 with PN1, where PN1 is the preset global review standard index; S195: If N1≥PN1, then it is determined that the interval to be reviewed meets the correction standards, and all frame correction intervals that have intersections with the interval to be reviewed among the several frame correction intervals corresponding to the intervention image sets B2, B3, ..., Ba are traversed, and the minimum and maximum values ​​of the frame node indicators are extracted therefrom. The review and correction interval of the interval to be reviewed is generated based on the extracted minimum and maximum values ​​of the frame node indicators. Otherwise, it is determined that the interval to be reviewed does not meet the correction standards.

6. A monitoring system for spinning production according to claim 1, characterized in that: The auxiliary optimization rules for obtaining new defect location data of the finished product are as follows: S21: Mark all the review and correction intervals in the review and correction information as Q1, Q2, ..., Qq, q≥1; S22: Mark the left and right endpoint values ​​of the review and correction interval Q1 as R1 and R2 respectively; S23: Calculate the camera moments corresponding to R1 and R2 from the defect location data of the finished product according to R1 and R2, and extract the defect location data at these two camera moments from the defect location data, and use them as auxiliary correction data for the review correction interval Q1; S24: Calculate and obtain auxiliary correction data of the inspection correction intervals Q1, Q2, ..., Qq respectively according to S23; The auxiliary correction unit generates new defect location data of the finished product based on the auxiliary correction data of the review correction intervals Q1, Q2, ..., Qq.

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