385 results about "Textile production" patented technology

The invention relates to a fabric flaw detection and traceability system based on edge calculation and computing power scheduling, which is suitable for intelligent quality control in a textile production process. The system comprises an acquisition unit, a modeling unit and the like. The acquisition unit acquires fabric images and environmental data through a multispectral imaging device and a process parameter sensor, and constructs time-aligned multi-modal feature tensors. The modeling unit extracts texture features by using unsupervised comparative learning in combination with fabric material characteristics, and generates potential texture fingerprint vectors. And the detection unit adopts a target detection network of a channel attention mechanism to identify fabric flaws and output positions, types and severity. The traceability unit analyzes correlation between defects and process parameters through time sequence causal reasoning, and constructs a causal atlas. And the optimization unit generates a process optimization vector according to the causal atlas and the risk score, and realizes visual display and edge control feedback, thereby constructing a real-time defect control and explainable traceability-oriented closed-loop quality management system.

The invention discloses a textile production defect detection method and system based on image processing, and belongs to the field of textile defect detection. According to the method, the point cloud data is generated by collecting the surface deformation stripes, and the penetrability reflection signal containing the sound wave propagation time is obtained through the multi-frequency ultrasonic probe. Denoising the point cloud data and then positioning a surface deformation candidate area based on a curvature gradient and a normal vector deflection angle; and an internal abnormal region is determined by separating and extracting a reflection wave amplitude value and a time delay parameter through an ultrasonic frequency band. And matching the surface point cloud coordinates with the ultrasonic propagation time by adopting an iterative nearest point algorithm to establish feature association between the normal vector deflection angle and the reflected wave amplitude. And dynamically distributing fusion weights for the surface features and the internal features according to the curvature gradient change rate and the amplitude attenuation rate to generate a multi-modal defect distribution diagram. And geometric shape and reflection intensity parameters are extracted and matched with a preset defect template to realize type and position judgment, and the method can be suitable for production defect detection of the thick textile with a multi-layer composite material structure.

The invention relates to the technical field of textile production scheduling and resource allocation planning, in particular to a textile equipment scheduling management and optimization system of a textile factory, which comprises a data perception and integration module, a scheduling optimization decision module, a plan execution and equipment control module and a closed-loop feedback and self-learning module. The data sensing module collects and fuses order data, equipment operation state data and production environment data in real time, and a unified real-time data view is generated through cleaning and alignment processing; the scheduling module runs a mixed integer programming dynamic model, and minimizes the comprehensive cost and synchronously optimizes the equipment utilization rate and energy consumption in combination with rolling horizon optimization under the condition of meeting the process constraints of order delivery time limit and process dependency matrix representation; the plan execution module analyzes the scheduling instruction into an equipment executable instruction, drives equipment operation and collects execution deviation; and the closed loop module triggers rescheduling when the deviation exceeds the limit or the order is plugged. The scheduling accuracy and adaptability are improved, the cost is reduced, and efficient and stable production is guaranteed.

The invention relates to the technical field of data fusion, in particular to a textile production traceability-oriented data fusion method and system. The method comprises the following steps: obtaining textile production workshop sensing data and textile production workshop camera data, and carrying out textile production chain data stream data fusion to obtain a textile production chain data stream; performing feature cross calculation according to the textile production chain data stream to generate a processing technology enhanced feature space; performing fingerprinting on the textile production chain data stream to obtain a cross-chain time-space stamp fingerprint set; evaluating the batch production quality of the textile production line based on the camera data of the textile production workshop, and obtaining batch data of a to-be-traced production line and batch data of a to-be-stored production line; evaluating the abnormal batch dyeing optimization feasibility of the production line batch data to be traced; and transmitting the batch data of the to-be-stored production line and the batch data of the to-be-traced production line after the dyeing optimization task to a workshop warehouse management platform. The production efficiency is improved, and resource waste is reduced.

The invention discloses a textile equipment collaborative scheduling optimization method based on a graph neural network, and the method comprises the steps: collecting and preprocessing textile production data, and generating a symbol heterogeneous production graph; inputting an improved symbol graph neural network model, and outputting a feasibility matrix and a multi-target cost feature vector; constructing an initial scheduling solution set and initial wave group parameters, and forming an improved water wave optimization algorithm input wave group; executing improved water wave optimization algorithm iteration to generate a global optimal scheduling solution; dynamic disturbance is monitored in real time in the scheduling execution stage, and a dynamic correction scheduling scheme is generated; and fusing to an overall scheduling optimization framework, and outputting a final global optimal scheduling solution and a corresponding scheduling performance index. According to the method, the improved symbol graph neural network model and the improved water wave optimization algorithm are introduced, so that efficient collaborative scheduling and real-time optimization of the textile equipment in complex process constraint and dynamic environments are realized.

The invention relates to the field of textile production, and discloses an intelligent control method for a textile finished product production line, which comprises the following steps: acquiring a textile surface image through a camera array to obtain textile surface image data; performing fiber arrangement density analysis on the textile surface image data to obtain fiber arrangement density difference data; according to the yarn gap distribution characteristic extraction method and device, environmental factors are monitored and compensated in real time through the temperature and humidity correlation deformation correction coefficient, it is ensured that under different environmental conditions, fabric tension is kept stable, the product quality and the production stability are further improved, and the yarn gap distribution characteristic data are obtained. An equipment cooperative control model constructed by using a depth deterministic strategy gradient algorithm realizes real-time speed adjustment and tension compensation of the textile machinery group through edge computing nodes, and the collaboration and automation level of the production process are effectively improved.

The invention relates to the technical field of textile manufacturing safety monitoring, in particular to a textile processing risk perception intelligent identification analysis system which comprises a video analysis module, an equipment prediction module, a product tracing module, a risk fusion module and an early warning response module. Wherein the video analysis module is used for outputting personnel violation signals; the equipment prediction module is used for carrying out fault probability calculation by fusing violation signals and time sequence data and outputting an equipment fault probability; the product tracing module is used for outputting defect source information; the risk fusion module is used for constructing a comprehensive risk index; and the early warning response module is used for triggering a multi-stage early warning instruction according to the threshold interval of the comprehensive risk index. According to the invention, through fusion analysis and graded early warning of multi-source risk factors, intelligent collaborative management and control of personnel, equipment and product defects in the textile production process are realized, and the accuracy of risk identification and the timeliness of safety response are effectively improved.

The invention relates to the technical field of textile production scheduling, in particular to a textile production full-process intelligent scheduling system, which comprises a data acquisition module for setting a target production cycle and collecting basic information of all orders in the target production cycle to form an order set; the basic information of the order comprises an order type, an order quantity and order delivery time; and the working procedure determination module divides the production process of the textiles produced by the orders into a plurality of working procedure links based on the order types and the textile production process conditions, the working procedure links comprise key working procedures and auxiliary working procedures, and the auxiliary working procedures are auxiliary processing procedures of the key working procedures. According to the textile production full-process intelligent scheduling system provided by the invention, personalized prediction can be carried out on the actual production line productivity of each order in the target period, an extensive historical average value is abandoned, and the accuracy of productivity prediction is remarkably improved.

The bobbin yarn taking and placing device comprises a bobbin replacing conveying line, the two ends of the bobbin replacing conveying line communicate with a bobbin conveying line between the automatic winder and a spinning frame, and a bobbin taking mechanism and a bobbin placing mechanism are arranged on the side face of the bobbin replacing conveying line; proximity sensing devices are arranged below the bobbin taking mechanism and the bobbin placing mechanism to sense the positions of bobbins, and the bobbin taking mechanism drives a bobbin clamping jaw to take the bobbins through a translation mechanism and a lifting mechanism; a pipe guiding groove is formed below a stock bin of the pipe discharging mechanism, and bobbins are discharged one by one and overturned to be in a vertical state through the material pushing and overturning mechanism. The device realizes automatic taking-out of bobbins containing residual yarns and automatic putting-in of empty bobbins, improves the production efficiency, reduces the labor cost, and is suitable for modern textile production.

The invention relates to the technical field of digital twinning, in particular to a method and a system for digitally producing textile fabrics, comprising virtual design and process simulation, physical production and real-time monitoring, predictive intervention and closed-loop control and knowledge precipitation and tracing. Compared with the defects that in the prior art, product development depends on physical proofing and experience trial and error, the research and development period is long, resource waste is serious, and design change response is slow, the digital twinborn driven high-fidelity virtual simulation scheme is adopted; by constructing a multi-scale model covering fiber-yarn-fabric and a multi-physics field coupling engine, defects such as chromatic aberration and skew weft can be accurately predicted and process parameters can be automatically optimized in the design stage, a traditional textile production mode is upgraded to a data-driven pre-verification mode, the development cycle of a new product is greatly shortened, and the production efficiency is improved. The raw material and energy consumption is obviously reduced, and the quick response capability of the complex customized order is improved.

The invention provides a textile flexible production line multi-material scheduling system, which comprises a physical execution layer and a multi-material scheduling layer, wherein the physical execution layer comprises reconfigurable textile production equipment; the intelligent sensing layer is arranged at key nodes of the physical execution layer; the central scheduling and control layer is in communication connection with the physical execution layer and the intelligent sensing layer; and the digital twin layer is a virtual mapping of the physical execution layer in an information space, and forms a closed loop with the central scheduling and control layer and the physical execution layer. According to the method, the perspectiveness and the global optimization capability of a scheduling decision are realized through a digital twinning technology, the system places an initial production scheduling scheme in a high-fidelity virtual production line model for millisecond-level concurrent simulation deduction, and potential process bottlenecks and quality risks during blending production of different materials are accurately predicted; and by taking the production efficiency, the energy consumption and the quality qualification rate as multi-target reward functions, completing iterative optimization of massive strategies in a virtual space, thereby obtaining an approximately globally optimal scheduling instruction before the physical production is put into use.

This invention relates to a fabric defect detection and traceability system based on edge computing and computing power scheduling, applicable to intelligent quality control in textile production processes. The system includes a data acquisition unit and a modeling unit. The data acquisition unit acquires fabric images and environmental data through multispectral imaging equipment and process parameter sensors, and constructs a time-aligned multimodal feature tensor. The modeling unit combines fabric material characteristics and uses unsupervised contrastive learning to extract texture features and generate potential texture fingerprint vectors. The detection unit uses a target detection network with a channel attention mechanism to identify fabric defects and outputs their location, type, and severity. The traceability unit analyzes the correlation between defects and process parameters through temporal causal reasoning, constructing a causal graph. The optimization unit generates process optimization vectors based on the causal graph and risk score, and realizes visualization and edge control feedback, thereby constructing a closed-loop quality management system for real-time defect control and interpretable traceability.

The invention provides a textile production process real-time monitoring system and method based on image recognition, and the method comprises the steps: obtaining visible light image data and near-infrared image data collected by an industrial camera on a textile production line, and carrying out the preprocessing; defect target detection and matching are carried out based on the preprocessed visible light image data and near-infrared image data, and whether textile surface defects exist or not is judged; if the textile surface defects exist, the relative displacement speed of the textile surface defects and a production line and a textile safety quality inspection area are obtained, and a defect response area is delimited based on the relative displacement speed and a defect area threshold value in the textile safety quality inspection area; performing defect channel filtering on the defect response region to obtain defect information in the defect response region; if the textile surface defects exist in the defect response area, a production line emergency shutdown instruction is triggered. According to the invention, high-precision real-time detection and hierarchical control of textile surface defects can be realized, and the false detection rate is reduced.

The invention discloses a textile fabric wetting device for textile production, which is applied to the technical field of textile production and comprises a wetting pool, a support frame is slidably connected to the interior of the wetting pool, a lower compression roller is rotatably connected to the lower part of the inner side of the support frame, and an upper compression roller is arranged at the top of the lower compression roller; the two ends of the upper pressing roller are slidably sleeved with a left sliding sleeve and a right sliding sleeve respectively. Textile cloth is pressed into the infiltrating pool through the upper pressing roller and the lower pressing roller and conveyed, and therefore the textile cloth is infiltrated. Meanwhile, a rotating convex rod slides on one side of an annular inclined groove to push an upper pressing roller, the upper pressing roller can slide left and right on the top of a lower pressing roller in a reciprocating mode through the elastic force of a second spring, an action similar to left-right rubbing is conducted on the textile cloth, fibers with large density can be relatively loose, water absorption wetting can be conveniently and fully conducted, and the wetting effect is improved.

The invention discloses a textile production defect detection system based on image processing, and relates to the technical field of image defect detection.The textile production defect detection system comprises the following steps that a linear array CCD collects a cloth image, and illumination difference is eliminated in a standardized mode; improving an anisotropic diffusion extraction structure layer and a local contrast enhancement detail layer; performing multi-structure element morphological gradient operation, and constructing a composite gradient map according to the expansion corrosion difference value; carrying out weighted product on the detail layer, the structure layer and the frequency domain features, and carrying out normalization to generate a comprehensive feature map; performing 3 sigma threshold binarization and morphological optimization based on a feature map mean value to remove a noise region; defect contour parameters are extracted, and a physical marking device is triggered after classification coding. According to the method, through a multi-scale texture decomposition architecture, spatial separation of a complex textile texture background and defect features is realized, and structural layer extraction based on anisotropic diffusion can retain fabric macroscopic morphological features and can also inhibit interference of periodic textures at the same time.

The invention discloses an efficient automatic yarn throwing robot, relates to the technical field of textile machinery automation, and realizes full-process automation by arranging a feeding assembly, a loading assembly, an identifying and overturning assembly, a yarn detection and operation assembly, a grabbing and throwing assembly and other assemblies and cooperative operation thereof. Yarn bars are conveyed through a conveying belt of the feeding assembly, lifted through a lifting plate, fed to the feeding assembly and then thrown to the recognizing and overturning assembly, and direction correction is completed through infrared distance measurement and air cylinder action. Then, in the yarn detection operation assembly, the yarn bar completes thread residue processing through an electric rotating clamping head, a thread picking needle, a thread suction pipe and the like. And finally, the grabbing and putting manipulator accurately grabs and puts the yarn bars and concentrates the yarns under the cooperation of the air source device according to the image of the camera. The full-process automation of the yarn bars from feeding to yarn concentration is achieved, the labor intensity is greatly reduced, the production efficiency, precision and stability are improved, and automatic and intelligent development of textile production is powerfully promoted.

A needle guide plate bending and milling integrated machine and a needle guide plate bending and milling method. The needle guide plate bending and milling integrated machine comprises a frame (10), a feeding mechanism (20), a bending and milling mechanism (30), and a driving mechanism (40). The feeding mechanism (20) is used for conveying a needle guide plate (1). The bending and milling mechanism (30) is located on one side of the feeding mechanism (20); the bending and milling mechanism (30) is used for bending and milling a part of the structure of the needle guide plate conveyed by the feeding mechanism (20); the bending and milling mechanism (30) comprises bending wheels (31) and a milling wheel (32); the bending wheels (31) and the milling wheel (32) are located in a same plane; the bending wheels (31) and the milling wheel (32) sequentially pass through the part of the structure of the needle guide plate. The driving mechanism (40) is separately connected to the feeding mechanism and the bending and milling mechanism (30); the driving mechanism (40) is used for driving the feeding mechanism (20) to convey the needle guide plate, and is further used for driving the bending wheels and the milling wheel of the bending and milling mechanism to sequentially pass through the part of the structure of the needle guide plate, so as to machine the needle guide plate to be suitable for textile production requirements. The needle guide plate bending and milling integrated machine enables needle guide plates to be bent and milled under the same position reference, avoiding machining errors caused by different references after multiple feedings, and also avoiding the situation where bent guide needle plates are difficult to stack and thus it is inconvenient to further mill the guide needle plates.

The invention provides an automatic control method and system for a textile production line, and relates to the technical field of textile production, and the method comprises the steps: applying a controlled dynamic excitation signal to a yarn, so as to obtain the instant response data of the yarn; according to the instant response data, physical characteristic information of the yarn is calculated; determining a running parameter range of the yarn according to the physical characteristic information; continuously acquiring running state information of the loom and the yarn, and comparing the running state information with the running parameter range to judge whether the production state is close to or beyond the boundary of the running parameter range; when it is judged that the production state approaches or exceeds the boundary of the operation parameter range, control parameters in the production process are adjusted according to the operation state information, so that the production state is maintained within the operation parameter range. The system can effectively avoid production efficiency reduction and product quality problems caused by material characteristic changes, and overcomes the limitation that a traditional system cannot adapt to new materials.

The invention discloses a fabric defect visual detection method based on fabric visual cognition, and relates to the technical field of textile production and quality control, and the method comprises the following steps: generating standardized fabric surface image data; constructing texture structure features used for representing normal fabric texture distribution; generating a fabric defect candidate area; obtaining a fabric defect detection result; and constructing a time sequence feature analysis model, generating corresponding quality risk early warning information and prevention and control suggestions, and generating batch-level quality inspection associated data. According to the method, the problems that in the prior art, fabric defect feature representation is not comprehensive, the complex defect recognition accuracy is low, and quality inspection data are difficult to continuously store and trace are solved, the fabric visual cognition model based on fabric visual cognition is constructed, and multi-dimensional texture structure features and a time sequence analysis mechanism are fused; according to the invention, accurate identification and quality risk prediction of fabric defects are realized, and the technical effects of stability, continuity and traceability of fabric quality detection are improved.

The invention discloses an embroidery textile production quality detection method based on data analysis, and relates to the technical field of intelligent textile, and the method comprises the steps: collecting embroidery production line multi-source sensor data in real time, carrying out timestamp synchronization and normalization processing through an Internet of Things edge node, and outputting structured process flow data; dynamically constructing a process causal graph model based on structured process flow data, taking embroidery thread batch quality, needle speed parameters and environment temperature and humidity parameters as nodes, taking Bayesian conditional probability as edge weight, and calculating a causal effect value of the needle speed parameters on broken needle defects through do-calculus; adjusting and controlling a needle speed parameter and an embroidery thread tension value in real time according to the dynamic parameter adjusting instruction, and synchronizing coordinates of the faulted embroidery machine to an operation and maintenance terminal through a fusing signal. According to the method, the causal influence strength of the interaction between the needle speed parameter and the environment temperature and humidity is accurately quantified through the Bayesian conditional probability and the do-calculus framework.

The invention discloses an intelligent waste gas treatment device for textile production, which comprises a fixed cylinder, a rotating ring, a mounting plate and a mounting ring, one end of the rotating ring is provided with an annular groove, the annular groove is rotatably connected with the fixed cylinder, the mounting plate is fixedly connected to one end of the inner wall of the rotating ring, and the surface of the mounting plate is provided with four filter screens. The mounting ring sleeves one end of the rotating ring, a sealing cover is fixedly connected to the top of the inner wall of the mounting ring, one end of the sealing cover communicates with an air guide pipe, a first mounting cover is fixedly connected to the bottom of the inner wall of the mounting ring, a first motor is fixedly connected to one end of the outer wall of the first mounting cover, and an output shaft of the first motor extends into the first mounting cover; a brush plate is fixedly connected, and one end of the bottom of the first mounting cover communicates with a first drainage pipe; the four filter screens are mounted on the mounting plate, so that the four filter screens can be alternately used.

The invention relates to an automatic tension adjusting mechanism and a cloth flatness detection device based on laser measurement, and belongs to the technical field of laser measurement instruments. The invention aims to solve the problem that the detection precision is interfered by detection distortion and edge curling caused by unstable cloth tension in the existing laser detection device. The automatic tension adjusting mechanism comprises a rack, a movable workbench arranged on the rack in a sliding mode, a driving assembly and a limiting assembly. The driving assembly is matched with a motor I through a lead screw and a ball nut to drive the movable workbench to slide along a guide rail I so as to change the cloth conveying distance, and tension adjustment is achieved. The arrangement mechanism drives two groups of rotating discs to rotate reversely through a driving shaft, a worm and a worm gear, so that a sliding rod slides along a guide frame and is matched with a spring to drive a smoothing rod to stretch out and draw back, and hemming arrangement is realized. The device is suitable for flatness detection of cloth of different materials in textile production, and the detection precision and efficiency can be improved.

The application discloses a kind of intelligent waste gas treatment devices for textile production, including fixed cylinder, rotating ring, mounting plate and mounting ring, the rotating ring one end of rotating ring is equipped with annular groove, the annular groove is rotatably connected with fixed cylinder, mounting plate is fixedly connected in rotating ring inner wall one end, the mounting plate surface is provided with four filter screens, mounting ring is sleeved in one end of rotating ring, the mounting ring inner wall top is fixedly connected with sealing cover, the sealing cover one end is communicated with gas guide pipe, the mounting ring inner wall bottom is fixedly connected with first installation cover, the first installation cover outer wall one end is fixedly connected with first motor, the first motor output shaft extends to first installation cover inside, and is fixedly connected with brush plate, the first installation cover bottom one end is communicated with first drain pipe;The application is installed four filter screens on mounting plate, so that four filter screens can be alternately used.

The utility model discloses a kind of ironing device for textile production, including four stand, four the top of stand is fixed with table top, the inside rotation of table top is equipped with conveying component, two are fixed with fixed component in the top front and rear symmetry of table top, the top of table top is fixedly connected with ironing component.The utility model discloses a kind of ironing device for textile production, by setting infrared heating plate, compared with traditional resistance wire heating plate or steam heating plate, infrared heating plate can produce heat instantaneously, substantially shorten preheating and temperature rising waiting time, while infrared heating plate is strong, can be heated to the inside and outside of relatively thick textile quickly, improve the uniformity of ironing, by setting synchronous belt, textile and transmission roller between by traditional point line contact change into surface contact, can effectively reduce the stretch and friction to light and thin elastic textile, to solve the problem that textile is deformed and wrinkled in conveying process.

The invention discloses a textile production quality control method, relates to the technical field of textile production, and solves the problem that it is difficult to design double algorithms to calculate initial warp and weft density, correct the initial warp and weft density in combination with yarn physical characteristics and environmental parameters, and improve the production efficiency. The technical problem of lack of construction of an exclusive regression model for effectively counteracting interference of yarn physical characteristics and environmental parameters is solved. Comprising the following steps: acquiring comprehensive production data, and generating a multi-dimensional feature map by using a multi-channel convolutional neural network; a Transform model is adopted to extract a yarn path, the initial warp and weft density is calculated by combining fast Fourier transform and local extremum detection double algorithms, the density is corrected by combining yarn physical characteristics and environmental parameters through an exclusive gradient promotion decision tree regression model, and a verification mechanism is introduced to guarantee the precision; and a density correlation type digital model is constructed to realize production data real-time mapping and parameter visual linkage debugging, and a full-link quality tracing system containing a unique tracing code is established.

The invention discloses a special shock absorber for textile equipment and a shock absorption method of the special shock absorber, the special shock absorber structurally comprises a universal ball, a shifting frame, a shock absorber and a connecting disc, the universal ball is connected with the shock absorber through the connecting disc, and the shifting frame is mounted on the surface of an outer ring of the shock absorber; the shifting frame comprises an extending table, a connecting strip, universal wheels, a supporting column, a spring, a pressing face and a connecting ring, the extending table and the connecting ring are of an integrated structure, the connecting strip penetrates through the connecting ring and is connected with the pressing face, the spring is installed between the pressing face and the extending table, the supporting column is fixed to the bottom of the pressing face, and the universal wheels are connected with the supporting column and can rotate. The universal wheels can rotate along the supporting columns, the textile equipment has high requirements for operation precision, when the equipment has position deviation due to vibration, fixing of the suction cups can be relieved only through pressing operation, the universal wheels are started for position correction, equipment parts do not need to be disassembled in the whole process, production stagnation caused by disassembly and debugging is effectively avoided, and the production efficiency is improved. And the continuity of textile production and the stability of product quality are ensured.

The invention belongs to the technical field of textile production, and particularly relates to a production method of a high-grade combed cotton and linen woven fabric. The production method comprises the steps that cotton assorting, cotton carding, pre-drawing, sliver lap forming, combing, drawing (two passes), roving, spinning and spooling are conducted on spinning, the high-grade combed cotton and linen woven fabric is obtained through slashing, weaving and finishing, the obtained fabric has softness of cotton, stiffness and smoothness of linen and high-grade gloss, and the defect problem of a cloth cover is solved.

The utility model belongs to the technical field of textile production devices, and particularly relates to a laminating device for laminated cloth, which comprises a workbench, a first support and an adjusting mechanism, the first support and the adjusting mechanism are arranged on the workbench, the first support is slidably connected with a lifting seat in the vertical direction, and a rollable upper press roll is arranged at the bottom of the lifting seat. A rolling lower pressing roller is arranged at the bottom of the first bracket; the adjusting mechanism comprises a linear module arranged at the top end of the first support, the bottom of the sliding table is connected with a movable block facing the lifting base, the bottom of the movable block is provided with a first inclined face, the first inclined face is inwards concavely provided with a dovetail groove with the two through ends, and the top of the lifting base is provided with a second inclined face. A guide column is arranged on the second inclined face in the length direction in an outward protruding mode. The gap between the upper pressing roller and the lower pressing roller is adjusted through the adjusting mechanism, so that the production requirement for more thicknesses can be met, and the application range of the device is widened.

The utility model provides an auxiliary oiling device of a drawing machine, which belongs to the field of textile production and comprises a support, a limiting mechanism used for adjusting the oiling angle and position is arranged on the side wall of the support, and an oiling assembly used for oiling drawn fibers is arranged on the limiting mechanism. The oiling assembly is provided with an oil conveying assembly used for conveying lubricating oil to the oiling assembly. According to the oil feeding assembly, when the oil feeding assembly is used, a V-shaped plate is fixedly connected with the telescopic inner pipe through welding, the bottom of the V-shaped plate is in bolted connection with a fixing plate through three fixing bolts, a stable structure is formed, the installation angle of oil absorption felt is guaranteed, disassembly and maintenance are convenient, and the oil absorption felt is of a porous fiber structure and can absorb a large amount of lubricating oil and slowly release the lubricating oil; meanwhile, the oil absorption felt is soft in texture, and mechanical damage cannot be generated when the oil absorption felt makes contact with silk threads.

The utility model discloses a godet wheel support structure which comprises a godet wheel body, a U-shaped plate is installed below the outer side of the godet wheel body in a rotating mode, a support is arranged below the U-shaped plate, a transverse frame is arranged below the support and comprises a transverse box, a sliding seat and a bottom plate, the bottom plate is arranged below the transverse box, and the sliding seat is arranged on the bottom plate. The sliding seat is fixedly installed above the bottom plate, a ball screw is rotatably installed in the transverse box, a sliding block is slidably installed on the outer side of the ball screw through a ball nut, a transmission plate is fixedly installed below the sliding block, and the lower end of the transmission plate penetrates out of the interior of the transverse box and is fixedly connected with the bottom plate; a displacement sensor is fixedly installed on the upper portion of the interior of the transverse box. According to the godet wheel adjusting device, the capability of automatically adjusting the position of the godet wheel is achieved, practicability is improved, and therefore the problems that when the godet wheel is adjusted in the left-right direction, manual operation of workers is needed, practicability is poor, and intelligence of the spinning production process is not facilitated are solved.