CN111552243B - Intelligent spinning and packaging production line fault detection system - Google Patents
Intelligent spinning and packaging production line fault detection system Download PDFInfo
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Abstract
The invention discloses a fault detection system of an intelligent spinning and packaging production line, which comprises a data acquisition module, a control module, a fault detection module, a storage module, a state display module and an information transmission module, wherein the control module is respectively connected with the data acquisition module, the fault detection module, the storage module and the state display module through the information transmission module; the data acquisition module is used for acquiring the transmission state of each yarn drum and images of the yarn drums before and after single yarn packaging in real time, and the failure detection module is used for analyzing and detecting failure reasons. By the mode, the transmission state of each link on the packaging production line can be monitored in real time, faults can be found in time and analyzed automatically, measures can be taken conveniently in time, and the influence of the faults is reduced; the invention can also carry out image acquisition and analysis on the yarn cylinders before and after single yarn packaging, further detect the faults in the turning and single yarn packaging links, improve the fault detection rate and ensure the product packaging quality.
Description
Technical Field
The invention relates to the technical field of spinning fault detection, in particular to an intelligent spinning packaging production line fault detection system.
Background
In recent years, along with the continuous acceleration of the intellectualization and digitization processes of the textile industry, more and more digital intelligent spinning equipment is applied to spinning production, and the spinning packaging process is used as the last procedure of the spinning production link, and the traditional manual packaging is gradually developed into automatic intelligent packaging, so that the packaging efficiency is greatly improved. However, each automation device on the packaging production line inevitably breaks down in the long-term operation process, and if the automation device is not detected and processed in time, the packaging quality and the production efficiency are affected, and further the reputation and the economic benefit of an enterprise are affected. Therefore, the fault detection of the intelligent spinning packaging production line has important significance for spinning enterprises.
At present, the intelligent spinning and packaging production line mainly comprises single yarn weighing, selective overturning, single yarn packaging, whole bag weighing, code spraying and other links, all the links are mutually matched and orderly carried out, the packaging process can be guaranteed to be smoothly carried out, and if any link breaks down, the whole operation of the packaging production line can be influenced. The method is mainly used for detecting faults caused by abnormal operation of main equipment and screening yarn drums with unqualified weights, but is difficult to detect faults caused by factors such as damage of other parts, change of operating environment or improper operation management, and the whole fault detection rate is low.
Meanwhile, in the selective turning and single yarn packaging links in the intelligent spinning and packaging production line, due to the fact that the operation process is relatively complex, mechanical parts are more involved, the mechanical parts are easy to influence, and the like, the fault detection method generally has high fault rate and low fault detection rate, and therefore further fault detection needs to be carried out manually. However, the problem of high cost and low efficiency exists when fault detection is carried out manually, and the monotonous detection work is easy to fatigue workers, so that misjudgment is generated, and the detection result is not accurate enough. Therefore, at present, it is still necessary to develop a more comprehensive and accurate intelligent fault detection system for the spinning and packaging production line, so as to detect faults in time and reduce the influence of the faults on the packaging production line and the product packaging effect.
Disclosure of Invention
The invention aims to solve the problems and provides an intelligent fault detection system for a spinning and packaging production line, which can find faults in time and automatically analyze the faults by monitoring the transmission state of each link on the packaging production line in real time, is convenient to take measures in time and reduces the influence of the faults on the packaging production line; and through carrying out image acquisition and analysis to yarn section of thick bamboo product before and after single yarn packing, further detect the trouble of upset and single yarn packing link, improve its trouble detectable rate, guarantee product packaging quality.
In order to achieve the purpose, the invention adopts the technical scheme that:
an intelligent fault detection system for a spinning and packaging production line comprises a data acquisition module, a control module, a fault detection module, a storage module, a state display module and an information transmission module, wherein the control module is respectively connected with the data acquisition module, the fault detection module, the storage module and the state display module through the information transmission module; the data acquisition module comprises a transmission state acquisition unit and an image acquisition unit, and is respectively used for acquiring the transmission state of each yarn drum and images of the yarn drums before and after single yarn packaging; the fault detection module is used for analyzing the information acquired by the data acquisition module, detecting whether a fault occurs and analyzing the fault reason; the storage module is used for storing historical data and information collected and transmitted by each module in the system operation process in a classified mode.
Furthermore, the transmission state acquisition unit comprises a plurality of photoelectric sensors, the photoelectric sensors are arranged on one side of each conveyor belt, the height of each photoelectric sensor is consistent with the middle part of each yarn drum, the photoelectric sensors do not move along with the conveyor belts, and the photoelectric sensors are used for acquiring transmission state information of the yarn drums on the conveyor belts in each link of the packaging production line and transmitting the information to the control module; the image acquisition unit comprises a plurality of image acquisition devices consisting of industrial cameras and light sources, the image acquisition devices are arranged on two sides of a conveying belt at the front part and the rear part of a single yarn packaging link on a packaging production line, do not move along with the conveying belt, and are respectively used for acquiring images of yarn cylinders before and after single yarn packaging and transmitting the images to the control module.
Further, the fault detection module comprises a transmission state analysis unit, an image analysis unit, a fault identification unit, a feature extraction unit and a fault analysis unit; one end of the transmission state analysis unit and one end of the image analysis unit are respectively connected with the control module and are used for analyzing the transmission state information and the image information input into the control module; the other ends of the transmission state analysis unit and the image analysis unit are sequentially connected with the fault identification unit, the feature extraction unit and the fault analysis unit and are used for detecting and analyzing faults; the fault identification unit and the fault analysis unit are respectively connected with the control module and used for outputting fault identification and analysis results.
Further, the transmission state analysis unit comprises a signal identification layer, a time detection layer and a parameter calculation layer; the signal identification layer is used for identifying and distinguishing signals sent by photoelectric sensors arranged in different links and transmitting the signals to the time detection layer respectively; the time detection layer is used for detecting the duration of signals sent by each photoelectric sensor and the interval duration between two signals and respectively transmitting the duration to the parameter calculation layer; the parameter calculation layer is used for calculating the transmission speed of the yarn drums in each link and the distance between the adjacent yarn drums, transmitting the transmission speed to the fault identification unit, calculating the transmission frequency of the yarn drums in the single yarn packaging link, and transmitting the transmission frequency to the control module.
Further, the image analysis unit comprises an image recognition layer, an image processing layer, a large and small head detection layer and a packaging detection layer; the image recognition layer is used for recognizing and distinguishing signals sent by the image acquisition units arranged at different positions and respectively transmitting the signals to the image processing layer; the image processing layer is used for converting the analog signals into digital signals and carrying out filtering, denoising and graying processing on the digital signals to obtain gray level images of the front and rear yarn drums of the single yarn package; the large and small end detection layer is used for carrying out edge extraction on the gray level image before single yarn packaging and comparing the number of pixel points in the upper edge and the lower edge; the package detection layer is used for differentiating the gray level images before and after the single yarn package and identifying the change condition of the image gray level.
Further, the fault identification unit comprises a parameter matching layer, a turnover identification layer, a packaging matching layer and a statistic output layer; the parameter matching layer, the turnover identification layer and the package matching layer are respectively used for receiving results output by the parameter calculation layer, the large and small head detection layer and the package detection layer, comparing the results with a set standard state, judging whether a fault exists or not, and outputting the results to the statistic output layer; and the statistic output layer is used for receiving and counting judgment results input by the parameter matching layer, the turnover identification layer and the packaging matching layer, outputting a normal instruction to the control module when the results are all fault-free, and otherwise, outputting the statistic results to the feature extraction unit.
Furthermore, the feature extraction unit is configured to receive the fault result output by the statistical output layer, extract fault elements therein, form a feature vector, and transmit the feature vector to the fault analysis unit; and the fault analysis unit is used for receiving the feature vectors output by the feature extraction unit and carrying out fault analysis on the feature vectors according to the trained model.
Furthermore, the control module comprises a main control unit and an image acquisition frequency control unit, wherein the main control unit is respectively connected with the data acquisition module, the fault detection module, the storage module and the state display module and is used for coordinating and controlling the operation of each module; the image acquisition frequency control unit is respectively connected with the main control unit and the image acquisition unit and is used for receiving an instruction sent by the main control unit and controlling the image acquisition frequency of the image acquisition unit.
Furthermore, the state display module comprises a display unit and a feedback unit, the display unit is used for receiving the information transmitted by the control module and displaying the information on a display screen, a plurality of groups of signal lamps are arranged on the display screen, and each group of signal lamps corresponds to one link in a packaging production line; in the packing production line, each group of signal lamps corresponding to the turning link and the single yarn packing link comprises three colors of red, yellow and green and are respectively used for representing transmission faults, other faults and normal states, and each group of signal lamps corresponding to other links comprises two colors of red and green and are respectively used for representing the transmission faults and the normal states; the feedback unit is used for receiving feedback information of the fault and transmitting the feedback information to the control module.
Furthermore, the information transmission module comprises an industrial Ethernet and an Ethernet switch, and the data acquisition module, the fault detection module and the state display module are respectively connected with the control module through the industrial Ethernet by utilizing the Ethernet switch.
Compared with the prior art, the invention has the beneficial effects that:
1. the intelligent spinning and packaging production line fault detection system provided by the invention can be used for monitoring the transmission state of each link on the packaging production line in real time, finding out faults in time and automatically analyzing the faults, so that measures can be taken in time conveniently, and the influence of the faults on the packaging production line is reduced; meanwhile, the invention can also carry out image acquisition and analysis on the single-yarn packaged yarn drum product, further detect the faults in the turning and single-yarn packaging links, improve the fault detection rate and ensure the product packaging quality.
2. The invention adopts the photoelectric sensor to monitor the transmission speed and the distance of the yarn drum in real time, and can find and position faults in time by comparing the actual monitoring data with the set parameters; and by extracting fault characteristics and establishing a fault model, the fault reason is further analyzed, so that relevant workers can take corresponding measures in time to solve the fault as soon as possible, and smooth operation of the packaging production line is guaranteed.
3. The invention also utilizes the transmission speed and the space of the yarn drums to determine the frequency of image acquisition on the yarn drums, and realizes the accurate acquisition of the image of each yarn drum before and after single yarn package; meanwhile, the large and small end states of the yarn cylinder are judged by analyzing the yarn cylinder image before single yarn packaging; analyzing the image of the single yarn packaged yarn cylinder to judge the packaging condition of the yarn cylinder; therefore, whether the turning and single yarn packaging links break down or not is detected, the failure detection rate is improved, timely processing is facilitated, and the influence of the failure on the product quality is reduced.
Drawings
FIG. 1 is a schematic structural diagram of a fault detection system of an intelligent spinning and packing production line of the invention;
FIG. 2 is a main flow chart of the intelligent spinning packaging production line fault detection system in use.
Detailed Description
The following detailed description of the preferred embodiments of the present invention, taken in conjunction with the accompanying drawings, will make the advantages and features of the invention easier to understand by those skilled in the art, and thus will clearly and clearly define the scope of the invention. It is to be understood that the described embodiments are merely a few embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without any inventive step, are within the scope of the present invention.
Examples
Referring to fig. 1, the present embodiment provides an intelligent spinning and packing production line fault detection system, which includes a data acquisition module, a control module, a fault detection module, a storage module, a status display module and an information transmission module, wherein the control module is respectively connected to the data acquisition module, the fault detection module, the storage module and the status display module through the information transmission module; the data acquisition module comprises a transmission state acquisition unit and an image acquisition unit, and is respectively used for acquiring the transmission state of each yarn drum and images of the yarn drums before and after single yarn packaging; the fault detection module is used for analyzing the information acquired by the data acquisition module, detecting whether a fault occurs and analyzing the fault reason; the storage module is used for storing historical data and information collected and transmitted by each module in the system operation process in a classified mode.
The conveying state acquisition unit comprises six photoelectric sensors, the six photoelectric sensors are respectively arranged on one side of a conveying belt of the single yarn weighing, overturning, single yarn packaging, whole bag weighing and code spraying links, the height of the conveying belt is consistent with the middle of a yarn drum, the conveying belt does not move along with the conveying belt, and the conveying state acquisition unit is used for acquiring conveying state information of the yarn drum in each link and transmitting the information to the control module.
The image acquisition unit comprises four image acquisition devices consisting of an industrial camera and a light source, the image acquisition devices are respectively arranged on two sides of the front part and the rear part of the single yarn packaging link on the packaging production line, do not move along with the conveying belt, are respectively used for acquiring images of yarn barrels before single yarn packaging and after single yarn packaging, and are transmitted to the control module.
The fault detection module comprises a transmission state analysis unit, an image analysis unit, a fault identification unit, a feature extraction unit and a fault analysis unit; one end of the transmission state analysis unit and one end of the image analysis unit are respectively connected with the control module and are used for analyzing the transmission state information and the image information input into the control module; the other ends of the transmission state analysis unit and the image analysis unit are sequentially connected with the fault identification unit, the feature extraction unit and the fault analysis unit and are used for detecting and analyzing faults; the fault identification unit and the fault analysis unit are respectively connected with the control module and used for outputting fault identification and analysis results.
Wherein the transmission state analysis unit comprises a signal identification layer, a time detection layer and a parameter calculation layer; the signal identification layer is used for identifying and distinguishing signals sent by photoelectric sensors arranged in different links and respectively transmitting the signals to the time detection layer; the time detection layer is used for detecting the duration of signals sent by each photoelectric sensor and the interval duration between two signals and respectively transmitting the duration to the parameter calculation layer; the parameter calculation layer is used for calculating the transmission speed of the yarn drums in each link and the distance between the adjacent yarn drums, transmitting the transmission speed to the fault identification unit, calculating the transmission frequency of the yarn drums in the single yarn packaging link, and transmitting the transmission frequency to the control module.
The image analysis unit comprises an image recognition layer, an image processing layer, a large and small head detection layer and a packaging detection layer; the image recognition layer is used for recognizing and distinguishing signals sent by the image acquisition units arranged at different positions and respectively transmitting the signals to the image processing layer; the image processing layer is used for converting the analog signals into digital signals and carrying out filtering, denoising and graying processing on the digital signals to obtain gray level images of the front and rear yarn drums of the single yarn package; the large and small end detection layer is used for carrying out edge extraction on the gray level image before single yarn packaging and comparing the number of pixel points in the upper edge and the lower edge; the package detection layer is used for differentiating the gray level images before and after the single yarn package and identifying the change condition of the image gray level.
The fault identification unit comprises a parameter matching layer, a turnover identification layer, a packaging matching layer and a statistic output layer; the parameter matching layer, the turnover identification layer and the packaging matching layer are respectively used for receiving results output by the parameter calculation layer, the reducer detection layer and the packaging detection layer, comparing the results with a set standard state, judging whether a fault exists or not and outputting the results to the statistic output layer; and the statistic output layer is used for receiving and counting judgment results input by the parameter matching layer, the turnover identification layer and the packaging matching layer, outputting a normal instruction to the control module when the results are all fault-free, and otherwise, outputting the statistic results to the feature extraction unit.
The characteristic extraction unit is used for receiving the fault result output by the statistical output layer, extracting fault elements in the fault result, forming a characteristic vector and transmitting the characteristic vector to the fault analysis unit; and the fault analysis unit is used for receiving the feature vectors output by the feature extraction unit and carrying out fault analysis on the feature vectors according to the trained model.
The control module comprises a main control unit and an image acquisition frequency control unit, wherein the main control unit is respectively connected with the data acquisition module, the fault detection module, the storage module and the state display module and is used for coordinating and controlling the operation of each module; the image acquisition frequency control unit is respectively connected with the main control unit and the image acquisition unit and is used for receiving an instruction sent by the main control unit and controlling the image acquisition frequency of the image acquisition unit.
The state display module comprises a display unit and a feedback unit, the display unit is used for receiving the information transmitted by the control module and displaying the information on a display screen, a plurality of groups of signal lamps are arranged on the display screen, and each group of signal lamps corresponds to one link in a packaging production line; in the packing production line, each group of signal lamps corresponding to the turning link and the single yarn packing link comprises three colors of red, yellow and green and are respectively used for representing transmission faults, other faults and normal states, and each group of signal lamps corresponding to other links comprises two colors of red and green and are respectively used for representing the transmission faults and the normal states; the feedback unit is used for receiving feedback information of the fault and transmitting the feedback information to the control module.
The information transmission module comprises an industrial Ethernet and an Ethernet switch, and the data acquisition module, the fault detection module and the state display module are respectively connected with the control module through the industrial Ethernet by utilizing the Ethernet switch.
With reference to fig. 2, when the intelligent fault detection system for the spinning and packaging production line provided by the embodiment is used, the photoelectric sensors are respectively arranged on the conveyor belts in the links of single yarn weighing, overturning, single yarn packaging, whole bag weighing and code spraying on the packaging production line, and when a yarn drum on the conveyor belt passes through the position of the photoelectric sensor, the corresponding photoelectric sensor continuously sends out a signal; when the yarn drum leaves the position of the photoelectric sensor and the latter yarn drum does not pass, the corresponding photoelectric sensor stops sending signals; the transmission state information of the yarn drums in all links is collected, transmitted to the control module through the industrial Ethernet, read by the main control unit, transmitted to the storage module for classified storage, and controlled by the transmission state analysis unit to analyze the transmission state, the transmission speed of the yarn drums in all links, the distance between adjacent yarn drums and the transmission frequency of the yarn drums in a single yarn packaging link are calculated, and the method mainly comprises the following steps:
s1.1, in a signal identification layer, identifying and distinguishing signals sent by photoelectric sensors arranged in different links, and respectively transmitting the signals to a time detection layer for time detection;
s1.2, in the time detection layer, sending out the duration t of signals to each photoelectric sensoraiAnd the interval duration t between two times of signal sendingbiReal-time detection is carried out, and a transmission parameter calculation layer is calculated;
the value range of i is 1-6, and the value range of i is respectively used for representing signals sent by photoelectric sensors arranged in single yarn weighing, overturning, single yarn packaging, whole bag weighing and code spraying links;
s1.3, in the parameter calculation layer, inputting each duration and the prestored middle outer diameter d of the yarn barrel by the time detection layer0Combined with each other, the conveying speed V of the yarn cylinder in each linkiAnd the space S between adjacent bobbinsiAnd the frequency f of the delivery of the package of individual yarns3The calculation is carried out, and the calculation formulas are respectively as follows:
Si＝Vi·tbi
wherein the delivery speed V of the obtained yarn packageiAnd the spacing S between adjacent bobbinsiTransmitting to a fault identification unit; the transmission frequency f of the bobbin in the single yarn packing link is obtained3The transmission is transmitted to a control module, the main control unit reads the data and sends an instruction to an image acquisition frequency control unit, and the image acquisition frequency control unit controls the image acquisition frequency of an image acquisition device to enable the image acquisition frequency and the transmission frequency f of a yarn drum in a single yarn packaging link3And the images of each bobbin after single yarn is packaged are accurately acquired.
The image acquisition device sets up in the conveyer belt both sides at single yarn packing link front portion and rear portion for gather the both sides image of a yarn section of thick bamboo before the single yarn packing and after the single yarn packing, and transmit it to control module through industrial Ethernet, read the back by main control unit, transmit it to storage module and carry out categorised storage, and control image analysis unit and carry out image analysis to it, be used for detecting the big end state and the packing condition of a yarn section of thick bamboo, mainly include following step:
s2.1, in the image identification layer, identifying and distinguishing signals sent by image acquisition units arranged at different positions, and respectively transmitting the signals to the image processing layer for Gaussian filtering and graying processing;
the position of the image acquisition unit is divided into a front left side, a front right side, a rear left side and a rear right side of a single yarn package, the image acquisition units on the front left side and the front right side are used for acquiring yarn barrel images before packaging, and the image acquisition units on the rear left side and the rear right side are used for acquiring yarn barrel images after packaging.
S2.2, calculating the gradient amplitude | G | of each pixel point (x, y) in the gray level image of the bobbin before single yarn packaging through the large and small head detection layer, wherein the calculation formula is as follows:
in the formula, Gx、GyRespectively representing gradient densities in x and y directions;
then, carrying out non-maximum value inhibition on the gradient amplitude, extracting the image edge, counting the number of pixel points on the upper edge and the lower edge of the image, comparing the number of the pixel points, and if the number of the pixel points on the upper edge is larger than that of the pixel points on the lower edge, outputting an instruction with the large head upwards to a fault identification unit; otherwise, the instruction with the small head upwards is output to the fault identification unit.
S2.3, carrying out differential processing on the gray level images of the yarn drums before and after single yarn packaging to obtain a difference image, and transmitting the difference image to a fault identification unit; the difference processing can be expressed as:
C(x,y)＝|A(x,y)-B(x′,y′)|
in the formula: c (x, y) is a difference image, A (x, y) is a gray image of the bobbin after single yarn packaging, and B (x ', y') is a gray image of the bobbin before single yarn packaging.
Because the surface of the yarn cylinder is coated with a layer of transparent film after single yarn is packaged, the reflectivity of the surface of the yarn cylinder is increased, so that the light energy entering an industrial camera under the same shooting condition is increased, and the gray value of the obtained image is higher; therefore, the gray level images of the yarn bobbin before and after packaging are differentiated according to the method of the step S2.3, and then the difference image is compared with the standard difference image under the normal condition, so that the packaging condition of the yarn bobbin can be judged, and the judgment of the packaging condition of the yarn bobbin is carried out in the fault identification unit.
Specifically, the fault identifying unit is configured to receive results output by the parameter calculating layer, the large and small head detecting layer, and the package detecting layer, and determine whether a fault exists, where the main method is as follows:
s3.1, receiving the yarn drum transmission speed V output by the parameter calculation layer by the parameter matching layeriAnd the spacing S between adjacent bobbinsiAnd matching the parameter with a set parameter range; when both parameters are successfully matched, outputting 'no fault' output; when any parameter is unsuccessfully matched, outputting 'failure' and outputting failure parameter values together;
s3.2, receiving the instruction output by the large and small end detection layer by the overturning identification layer, and comparing the instructions corresponding to the adjacent yarn drums; when the instructions of the adjacent yarn drums are opposite, the direction of the adjacent yarn drums is opposite, the packaging requirement is met, and no fault exists in the output; when the instructions of the adjacent yarn drums are the same, the fact that the overturning link is abnormal is indicated, and then a fault is output;
s3.3, receiving the difference image output by the packaging detection layer by the packaging matching layer, matching the difference image with a pre-stored standard difference image, and judging the similarity degree of the difference image; when the similarity degree is not lower than a set threshold, the matching is successful, and 'no fault' is output; when the similarity degree is lower than a set threshold value, the single yarn packaging environment is abnormal, and then a fault is output;
s3.4, receiving and counting the output results of the parameter matching layer, the turnover identification layer and the packaging matching layer by the counting output layer; when all the output results are 'no fault', outputting the normal instruction to the control module; otherwise, outputting the statistical 'fault' result to the feature extraction unit.
When the counting output layer outputs the normal instruction to the control module, the main control unit reads the normal instruction and controls green signal lamps corresponding to all links on the display unit to light up, which indicates that all links on the current packaging production line are in a normal state; when the statistical output layer outputs the fault result to the feature extraction unit, the feature extraction unit extracts the fault feature and the fault reason analysis is carried out through the fault analysis unit, and the method comprises the following specific steps:
s4.1, receiving and identifying the fault result output by the statistic output layer by the characteristic extraction unit, extracting fault elements in the fault result, and forming a characteristic vector T ═ V1,V2,…,V6,S1,S2,…,S6M, N), wherein V1～V6And S1～S6The yarn package device is used for respectively representing the conveying speed and the distance of yarn drums in six links, M, N is used for respectively representing the fault conditions of a turnover link and a single yarn package link, when no fault exists in a corresponding link, the value of the fault is 0, otherwise, the value of the fault is 1;
s4.2, receiving the feature vectors output by the feature extraction unit by a fault analysis unit, and carrying out fault analysis on the feature vectors through a trained neural network model; wherein the neural network model is trained based on historical data in the storage module to obtain a fault cause set R (R)xy) Corresponding relation and confidence with the characteristic vector T;
s4.3, outputting a fault reason set R (R) according to the neural network modelxy) Identifying corresponding faults and outputting fault analysis results to a control module; the value range of x is 1-8, and the value range corresponds to the conveying faults of single yarn weighing, overturning, single yarn packaging, whole bag weighing and code spraying links and other faults of overturning and single yarn packaging links.
When the control module receives a fault analysis result output by the fault analysis unit, the main control unit reads the fault analysis result, and if a transmission fault exists, the red indicator lamp of the corresponding fault link is controlled to be turned on, and the fault reason is displayed; if other faults exist, the yellow indicator lamp corresponding to the fault link is controlled to be turned on, the fault reason is displayed, and related personnel can conveniently and timely handle the faults.
In addition, after the relevant personnel process the condition displayed by the state display module, the feedback can be carried out through the feedback unit of the state display module, the feedback content comprises that the fault is processed, the fault is reported by mistake and the fault is missed, the feedback information is read by the main control unit and then is transmitted to the storage module, and the feedback information can be used for statistical analysis and generating a corresponding report.
Through the mode, the intelligent spinning packaging production line fault detection system provided by the invention can be used for monitoring the transmission state of each link on the packaging production line in real time, finding out faults in time and automatically analyzing the faults, so that measures can be taken conveniently in time, and the influence of the faults is reduced; the invention can also carry out image acquisition and analysis on the single-yarn packaged yarn drum product, further detect the faults of the turning and single-yarn packaging links, improve the fault detection rate and ensure the product packaging quality.
The above description is only for the purpose of illustrating the technical solutions of the present invention and is not intended to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; all the equivalent structures or equivalent processes performed by using the contents of the specification and the drawings of the invention, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (9)
1. The utility model provides an intelligence spinning packing production line fault detection system which characterized in that: the intelligent control system comprises a data acquisition module, a control module, a fault detection module, a storage module, a state display module and an information transmission module, wherein the control module is respectively connected with the data acquisition module, the fault detection module, the storage module and the state display module through the information transmission module; the data acquisition module comprises a transmission state acquisition unit and an image acquisition unit, and is respectively used for acquiring the transmission state of each yarn drum and images of the yarn drums before and after single yarn packaging; the fault detection module is used for analyzing the information acquired by the data acquisition module, detecting whether a fault occurs and analyzing the fault reason; the storage module is used for storing historical data and information acquired and transmitted by each module in the system operation process in a classified manner;
the conveying state acquisition unit comprises six photoelectric sensors, is respectively arranged on one side of a conveying belt in the single yarn weighing, overturning, single yarn packaging, whole bag weighing and code spraying links, has the same height as the middle part of the yarn cylinder, does not move along with the conveying belt, is used for acquiring conveying state information of the yarn cylinder in each link and transmitting the information to the control module; the image acquisition unit comprises a plurality of image acquisition devices consisting of industrial cameras and light sources, the image acquisition devices are arranged on two sides of the conveying belts at the front part and the rear part of the single yarn packaging link on the packaging production line, do not move along with the conveying belts, are respectively used for acquiring images of the yarn cylinders before and after single yarn packaging, and are transmitted to the control module; the fault detection module comprises a transmission state analysis unit, an image analysis unit, a fault identification unit, a feature extraction unit and a fault analysis unit;
the transmission state analysis unit is used for calculating the transmission speed of the yarn cylinders in each link, the distance between the adjacent yarn cylinders and the transmission frequency of the yarn cylinders in the single yarn packaging link.
2. The intelligent spinning packaging production line fault detection system of claim 1, wherein: one end of the transmission state analysis unit and one end of the image analysis unit are respectively connected with the control module and are used for analyzing the transmission state information and the image information input into the control module; the other ends of the transmission state analysis unit and the image analysis unit are sequentially connected with the fault identification unit, the feature extraction unit and the fault analysis unit and are used for detecting and analyzing faults; the fault identification unit and the fault analysis unit are respectively connected with the control module and used for outputting fault identification and analysis results.
3. The intelligent spinning packaging production line fault detection system of claim 2, wherein: the transmission state analysis unit comprises a signal identification layer, a time detection layer and a parameter calculation layer; the signal identification layer is used for identifying and distinguishing signals sent by photoelectric sensors arranged in different links and transmitting the signals to the time detection layer respectively; the time detection layer is used for detecting the duration of signals sent by each photoelectric sensor and the interval duration between two signals and respectively transmitting the duration to the parameter calculation layer; the parameter calculation layer is used for calculating the transmission speed of the yarn drums in each link and the distance between the adjacent yarn drums, transmitting the transmission speed to the fault recognition unit, calculating the transmission frequency of the yarn drums in the single yarn packaging link, and transmitting the transmission frequency to the control module.
4. The intelligent spinning packaging production line fault detection system of claim 3, wherein: the image analysis unit comprises an image recognition layer, an image processing layer, a large and small head detection layer and a packaging detection layer; the image recognition layer is used for recognizing and distinguishing signals sent by the image acquisition units arranged at different positions and respectively transmitting the signals to the image processing layer; the image processing layer is used for converting the analog signals into digital signals and carrying out filtering, denoising and graying processing on the digital signals to obtain gray level images of the front and rear yarn drums of the single yarn package; the large and small end detection layer is used for carrying out edge extraction on the gray level image before single yarn packaging and comparing the number of pixel points in the upper edge and the lower edge; the package detection layer is used for differentiating the gray level images before and after the single yarn package and identifying the change condition of the image gray level.
5. The intelligent spinning packaging production line fault detection system as claimed in claim 4, characterized in that: the fault identification unit comprises a parameter matching layer, a turnover identification layer, a packaging matching layer and a statistic output layer; the parameter matching layer, the turnover identification layer and the packaging matching layer are respectively used for receiving results output by the parameter calculation layer, the reducer detection layer and the packaging detection layer, comparing the results with a set standard state, judging whether a fault exists or not and outputting the results to the statistic output layer; and the statistic output layer is used for receiving and counting judgment results input by the parameter matching layer, the turnover identification layer and the packaging matching layer, outputting a normal instruction to the control module when the results are all fault-free, and otherwise, outputting the statistic results to the feature extraction unit.
6. The intelligent spinning packaging production line fault detection system of claim 5, wherein: the characteristic extraction unit is used for receiving the fault result output by the statistical output layer, extracting fault elements in the fault result, forming a characteristic vector and transmitting the characteristic vector to the fault analysis unit; and the fault analysis unit is used for receiving the feature vectors output by the feature extraction unit and carrying out fault analysis on the feature vectors according to the trained model.
7. The intelligent spinning packaging production line fault detection system of claim 3, wherein: the control module comprises a main control unit and an image acquisition frequency control unit, wherein the main control unit is respectively connected with the data acquisition module, the fault detection module, the storage module and the state display module and is used for coordinating and controlling the operation of each module; the image acquisition frequency control unit is respectively connected with the main control unit and the image acquisition unit and is used for receiving an instruction sent by the main control unit and controlling the image acquisition frequency of the image acquisition unit.
8. The intelligent spinning packaging production line fault detection system of claim 1, wherein: the state display module comprises a display unit and a feedback unit, the display unit is used for receiving the information transmitted by the control module and displaying the information on a display screen, a plurality of groups of signal lamps are arranged on the display screen, and each group of signal lamps corresponds to one link in a packaging production line; in the packing production line, each group of signal lamps corresponding to the turning link and the single yarn packing link comprises three colors of red, yellow and green and are respectively used for representing transmission faults, other faults and normal states, and each group of signal lamps corresponding to other links comprises two colors of red and green and are respectively used for representing the transmission faults and the normal states; the feedback unit is used for receiving feedback information of the fault and transmitting the feedback information to the control module.
9. The intelligent spinning packaging production line fault detection system as claimed in claim 1, characterized in that: the information transmission module comprises an industrial Ethernet and an Ethernet switch, and the data acquisition module, the fault detection module and the state display module are respectively connected with the control module through the industrial Ethernet by utilizing the Ethernet switch.
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| CN112977985B (en) * | 2021-02-19 | 2022-05-06 | 北京中都星徽物流有限公司 | Intelligent transportation packaging line |
| CN113610788B (en) * | 2021-07-27 | 2023-03-07 | 上海众壹云计算科技有限公司 | Fault monitoring method and device for image acquisition device, electronic equipment and storage medium |
| CN113620119B (en) * | 2021-08-31 | 2023-03-24 | 上海兰宝传感科技股份有限公司 | Bobbin quantity detection system and method |
| CN113568391B (en) * | 2021-09-26 | 2021-12-17 | 深圳市迪壹六电子有限公司 | Selective synchronous remote control method, system and computer readable storage medium |
| CN115947181B (en) * | 2022-12-09 | 2024-01-23 | 苏州世祥生物纤维有限公司 | Yarn mixing processing method, processing device and processing system of packer |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1961687A2 (en) * | 2007-02-20 | 2008-08-27 | SAVIO MACCHINE TESSILI S.p.A. | Device for distinguishing spools on the basis of their yarn content |
| CN102519980A (en) * | 2011-12-15 | 2012-06-27 | 广东工业大学 | System and method for detecting appearance quality of industrial explosive cartridge package |
| CN104475344A (en) * | 2014-11-04 | 2015-04-01 | 上海维宏电子科技股份有限公司 | Method for realizing sorting of textile bobbins based on machine vision |
| CN104709770A (en) * | 2013-12-16 | 2015-06-17 | 索若德国两合股份有限公司 | Method for operating a winding machine and a winding machine |
| CN105256420A (en) * | 2015-11-30 | 2016-01-20 | 天津仁众人机械自动化技术有限公司 | Online monitoring device of flyer frame |
| CN105562362A (en) * | 2015-12-30 | 2016-05-11 | 上海日耀机械有限公司 | Bobbin sorting equipment and control method thereof |
| CN207507851U (en) * | 2017-09-18 | 2018-06-19 | 魏桥纺织股份有限公司 | A kind of quality visual detecting system |
| CN110371788A (en) * | 2019-06-27 | 2019-10-25 | 武汉裕大华纺织服装集团有限公司 | A kind of intelligence Spinning process lines conveying equipment |
| CN110407031A (en) * | 2019-07-30 | 2019-11-05 | 清华大学 | Automatic winder based on image recognition goes up yarn System and method for automatically |
| CN110597212A (en) * | 2019-09-27 | 2019-12-20 | 红云红河烟草(集团)有限责任公司 | Method for fault early warning of wrapping equipment based on equipment vibration imaging diagnosis |
-
2020
- 2020-04-22 CN CN202010320366.2A patent/CN111552243B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1961687A2 (en) * | 2007-02-20 | 2008-08-27 | SAVIO MACCHINE TESSILI S.p.A. | Device for distinguishing spools on the basis of their yarn content |
| CN102519980A (en) * | 2011-12-15 | 2012-06-27 | 广东工业大学 | System and method for detecting appearance quality of industrial explosive cartridge package |
| CN104709770A (en) * | 2013-12-16 | 2015-06-17 | 索若德国两合股份有限公司 | Method for operating a winding machine and a winding machine |
| CN104475344A (en) * | 2014-11-04 | 2015-04-01 | 上海维宏电子科技股份有限公司 | Method for realizing sorting of textile bobbins based on machine vision |
| CN105256420A (en) * | 2015-11-30 | 2016-01-20 | 天津仁众人机械自动化技术有限公司 | Online monitoring device of flyer frame |
| CN105562362A (en) * | 2015-12-30 | 2016-05-11 | 上海日耀机械有限公司 | Bobbin sorting equipment and control method thereof |
| CN207507851U (en) * | 2017-09-18 | 2018-06-19 | 魏桥纺织股份有限公司 | A kind of quality visual detecting system |
| CN110371788A (en) * | 2019-06-27 | 2019-10-25 | 武汉裕大华纺织服装集团有限公司 | A kind of intelligence Spinning process lines conveying equipment |
| CN110407031A (en) * | 2019-07-30 | 2019-11-05 | 清华大学 | Automatic winder based on image recognition goes up yarn System and method for automatically |
| CN110597212A (en) * | 2019-09-27 | 2019-12-20 | 红云红河烟草(集团)有限责任公司 | Method for fault early warning of wrapping equipment based on equipment vibration imaging diagnosis |
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