537 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 discloses a textile surface defect detection method, which comprises the following steps of: dividing a plurality of defect clusters according to the size of a textile surface defect, and correspondingly training a plurality of target detection models; the method further comprises the following steps: preprocessing the textile surface image to obtain a plurality of image areas containing textile surface defects; according to the image features of the textile surface image, distributing a target detection model for an image area corresponding to the textile surface image; and processing the image area in parallel through a plurality of target detection models, and identifying the textile surface defects. According to the invention, through multi-model parallel processing and the target detection model trained for different defect sizes, the speed and precision of textile surface defect detection are significantly improved. By using accurate intelligent model selection, missing detection and false detection are effectively reduced, the robustness and adaptability of the system are enhanced, and the strict requirements of modern textile production on real-time performance and accuracy are met.

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 provides dye sewage treatment equipment for textile production, and relates to the technical field of sewage treatment equipment.The dye sewage treatment equipment comprises a sewage treatment pond which is provided with a sewage adjusting pond and a sewage coagulative precipitation pond; a separation mechanism for removing physical impurities such as large-particle suspended solids and fibers in textile sewage is arranged at the side end of the sewage treatment tank, a filter cartridge is fixedly mounted at the right side end of the sewage treatment tank, a water inlet for feeding wastewater is formed in the filter cartridge, and the sewage regulating tank is used for balancing the quality and quantity of the textile sewage. By arranging the rotatable filter screen cylinder and the sealing side plate and sealing gasket structure thereof, large-particle suspended solids such as fibers and batting and impurities in textile sewage can be efficiently removed. And the forward rotation design of the filter screen cylinder can guide impurities to the bottom of the filter cylinder to prevent the impurities from being accumulated to block the filter surface, thereby obviously improving the filter efficiency and prolonging the service life of the equipment.

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 fabric acid and alkali resistance detection, in particular to acid and alkali resistance detection equipment for textile production and a detection method thereof. Comprising a detection platform, and a winding type soaking mechanism is arranged above the detection platform; and a soaking barrel is arranged in the center of the top of the detection platform. Two groups of winding columns are controlled to drive a textile sample to be separated from a soaking barrel, meanwhile, the two groups of winding columns are controlled to drive the textile to move upwards and abut against the bottom of a fixing plate, so that the internal space of the sample is closed, and then hot air is introduced into the internal space of the sample; under the action of internal and external air pressure difference, moisture absorbed in a sample can be rapidly discharged and dried, meanwhile, the sample wound by multiple circles can detect the anti-seepage performance of a textile on an acid-base solution by detecting corrosion changes of different areas of the sample, and the detection effect is improved while the working efficiency of the detection equipment is improved.

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 sampling detection device for textile production, and relates to the technical field of textile production detection. Comprising a mounting rack, a traction roller is arranged on the mounting rack, a clamping mechanism is arranged at the bottom end of the mounting rack, and a sampling detection mechanism is arranged at the top end of the mounting rack; the sampling detection mechanism comprises a moving frame, two stretching mechanisms are arranged on the moving frame, a contact mechanism is arranged between the two stretching mechanisms and divides sample cloth, the two stretching mechanisms clamp and stretch one piece of sample cloth respectively, the contact mechanism comprises a detection electric cylinder, and an extrusion part is arranged on a telescopic rod at one end of the detection electric cylinder. A friction part is arranged on the telescopic rod at the other end; the stretching mechanism comprises a rotary table rotationally mounted on the moving frame, and a clamping piece is arranged on the rotary table; after the sample is sampled, the segmentation operation is realized, so that multiple detections are completed, and the sampling and fixing operation is simplified.

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 a textile fabric cutting device for textile production, and belongs to the technical field of textile production, the textile fabric cutting device comprises an anti-toppling protective shell, a discharging hole is formed in the bottom of the side face of the anti-toppling protective shell, and a deformable conveying mechanism corresponding to the discharging hole is arranged at the bottom of the anti-toppling protective shell; a second limiting guide metal plate is arranged on the inner wall of the anti-toppling protection shell, the second limiting guide metal plate is arranged at the top of the anti-toppling protection shell and fixedly connected with the anti-toppling protection shell, and a deformable cutting mechanism corresponding to the second limiting guide metal plate is further arranged on the inner wall of the anti-toppling protection shell. The deformable cutting mechanism is arranged at the top of the anti-toppling protective shell; through mutual cooperation of multiple structures, automatic continuous cutting of the textile fabric is achieved, the textile fabric can be reliably fixed in the cutting process, the textile fabric is prevented from moving in the cutting process, and the cutting precision of the cutting device is higher.

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.

The invention discloses a roving frame spinning quality prediction method and system based on machine learning, and relates to the technical field of spinning quality prediction.The roving frame spinning quality prediction method comprises the following steps that historical yarn quality data are collected, yarn quality is divided into a plurality of quality gears, and an environment index and a machine state index corresponding to each quality gear are obtained; performing correlation analysis on the environment indexes and the machine state indexes to obtain the optimal correlation degree of the environment indexes and the yarn quality and the optimal correlation degree of the machine state indexes and the yarn quality respectively; inputting the optimal relevancy between the environment index and the yarn quality and the optimal relevancy between the machine state index and the yarn quality into a preset machine learning model for training to obtain a spinning quality prediction model of the roving frame; and inputting to-be-predicted yarn data into the roving frame spinning quality prediction model for quality prediction analysis. The problem that the accuracy of roving frame spinning quality prediction is reduced in the modern textile production process is solved.

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 a flying catkins collecting device for textile production and preparation, and relates to the technical field of solid waste pollution treatment, the flying catkins collecting device comprises an air bellow and an air inlet pipe, the air inlet pipe is mounted on the air bellow, one end of the air inlet pipe is connected with a connecting pipe and is perpendicular to the connecting pipe, and two ends of the connecting pipe are communicated with the air bellow through fixing pipes; filtering assemblies are arranged at the two ends of the connecting pipe correspondingly and used for filtering flying catkins in air on a circulation route of the connecting pipe and the fixing pipes, and the communicating state of the fixing pipes at the two ends of the connecting pipe and the air inlet pipe is switched through switching assemblies. The device is improved for solving the problem that when flying catkins in air are separated and collected in the prior art, due to the fact that the content of the flying catkins in the air is not constant, the opportunity cannot be accurately mastered when a filter screen is regularly cleaned or replaced. The device has the advantages that the inner pipe is driven to transversely move through the air pressure difference, rapid and automatic switching of the filtering assemblies at the two ends is achieved, it is ensured that airflow is seamlessly transferred to a standby path when the single end is blocked, and shutdown is avoided.

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.