757 results about "Textile production" patented technology

The invention discloses an intelligent textile production line control method and system, and relates to the technical field of industrial automation, and the method comprises the steps: collecting operation data in a textile production process in real time, and carrying out the data preprocessing; dynamically adjusting process parameters of the textile production line based on the preprocessed data; detecting the quality state in the textile production process in real time, and adjusting the operation of the production line based on the detection result; constructing a multi-feature fusion fault prediction model, and predicting the operation state of the production line equipment; potential faults are recognized in advance according to prediction results, and the operation mode of the production line is adjusted. The method combines multi-feature fusion analysis, dynamically optimizes the equipment operation state, identifies and adjusts potential faults in advance, improves the production quality and efficiency, reduces the maintenance cost and the shutdown risk, is significantly superior to a traditional method, and provides powerful technical support for intelligent upgrading of the textile industry.

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 discloses an intelligent management system and method for textile handicrafts, and belongs to the technical field of textile handicraft management, and the method specifically comprises the steps: collecting the production related data of the textile handicrafts in real time, carrying out the preprocessing of the collected production related data of the textile handicrafts, and carrying out the intelligent management of the textile handicrafts according to the preprocessed production related data of the textile handicrafts. According to the method, the quality of the textile is predicted and analyzed, the textile process is optimized, the quality and defects of the textile handicrafts are detected by using an image processing technology, and process parameters in textile production are automatically adjusted according to the quality and defect detection results of the textile handicrafts. A supply chain is dynamically adjusted according to market demands, production progress and inventory conditions, and a distribution path, a time table and production are optimized; related data in the production process are monitored in real time, real-time quality control and process parameter adjustment are carried out according to set standards, and the optimal production schedule is automatically generated through intelligent scheduling, so that the textile handicraft management efficiency is improved.

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 spinning production process optimization method based on an intelligent terminal, and relates to the technical field of spinning production. According to the spinning production process optimization method based on the intelligent terminal, a sensor is integrated through the intelligent terminal, process parameters and yarn surface image data are obtained in real time and input into a spinning production process monitoring model, the matching degree of the process parameters and the yarn surface state is analyzed, and a process adaptation index is obtained. According to the process adaptation index, the yarn tension and the spinning speed are dynamically adjusted through a fuzzy control algorithm, and therefore the production process is optimized. Whether the textile equipment is abnormal or not is judged through the equipment position information and the process adaptation index, the inspection path is optimized through the A star algorithm, and it is ensured that the equipment is inspected and maintained in time. Intelligent monitoring and optimization adjustment in the spinning production process are achieved, the production efficiency, the yarn quality and the equipment operation stability are improved, and manual intervention and fault risks are reduced.

A yarn storage container for storing a yarn, said storage container (101) comprising a, preferably tubular, container (101), having an axial length (L), a, preferably tubular, wall (501) and a first and second axial extremity (113-115), the first axial extremity (113) of said container (101) having an opening (123) for receiving an end of a yarn (200), said second axial extremity (115) of said container (101) being air-permeably closed, said wall (501) is air permeable by means of a plurality of openings (521-523) present along the axial length of said container (101). The invention further relates to a yarn storage system (1000) comprising a plurality of containers (101), to a textile production assembly (2000) and to methods of producing yarn (200) and textiles.

A placeholder positioning assembly (100) configured to mark a position of at least one structural feature (610) in a textile (600), the placeholder positioning assembly (100) being configured to operate in cooperation with a textile (600) producing machine (10) and to engage the at least one structural feature (610) in the textile (600) with a placeholder (500), includes a placeholder positioning unit (110) configured to engage the at least one placeholder (500) with the at least one structural feature (610) to thereby mark the location of the at least one structural feature (610).

The invention discloses a textile production detection method and system based on data feedback, and relates to the technical field of textile production.The method comprises the steps that textile production raw materials are screened based on textile production raw material information, loom parameters are adjusted according to textile quality prediction indexes, and the real-time working environment is optimized; the real-time working environment information, the yarn type information and the yarn environment influence coefficient prediction model of the to-be-processed textile are obtained, the yarn environment real-time influence coefficient is obtained, the real-time yarn state index is obtained through the initial yarn state index and the yarn environment real-time influence coefficient, and finally the real-time yarn quality index is obtained based on the real-time yarn quality index. The textile quality prediction index is obtained, the loom parameters are adjusted according to the textile quality prediction index, the real-time working environment is optimized, the loom can adjust the state of the yarn according to the real-time working environment in the weaving process, the quality of the woven fabric is improved, and therefore the working efficiency is improved.

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 relates to the technical field of textile industry, and discloses a textile production equipment recommendation scheduling method, which comprises the following steps: S1, extracting production process information: before scheduling, firstly extracting process information of a product to be produced from an order system; s2, obtaining candidate equipment information: after the production process information is obtained, extracting detailed information of all available equipment from an equipment management system; s3, judging a forced constraint condition; s4, multi-dimensional matching of priority conditions is carried out; s5, calculating the matching degree of the raw materials; s6, matching the opening value of the equipment; s7, scheduling optimization is carried out; and S8, generating a scheduling scheme. Through fine matching of process parameters and equipment parameters, the selected equipment can be ensured to be most suitable for the current production task, the equipment adjustment time and the production preparation time are reduced, so that the production efficiency is improved, the use of the equipment can be reasonably arranged, the downtime caused by frequent switching of the equipment or the process is reduced, and the production efficiency is improved. The continuous production capacity is 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 belongs to the technical field of textile production, and relates to an active disperse dye and a dyeing process. The reactive disperse dye comprises a dye matrix and a bis-aziridine chain segment grafted on the dye matrix, and-OCH2-is introduced to an aromatic ring para-position of the bis-aziridine chain segment as an electron-donating group. A dyeing process: after active disperse dye is dissolved, dyeing the textile; the textile consists of more than one of natural fibers and synthetic fibers; the dyeing temperature is 85-100 DEG C, and the dyeing temperature is higher than Tg of the synthetic fibers. According to the invention, a '-OCH2-' electron-donating group is introduced in the para-position of an aromatic ring of a diaziridine chain segment, and the conjugation effect and the induction effect of the group reduce the activation energy of C-N bond breakage, so that carbene can be efficiently generated without depending on a high-temperature or acid-base environment; the problems that in the prior art, the condition for generating carbene through a diaziridine chain segment is harsh, and the color fastness of the dyed textile is low when supercritical CO2 fluid is adopted for dyeing are solved.

A cloth inspecting and connecting machine relates to the field of textile production equipment and comprises a cloth inspecting device, a cloth rolling device, a cutting and sampling device and a packing device, the cloth inspecting device comprises a cloth inspecting table, a working platform and a meter counter, and cloth is arranged on the two sides of the cloth inspecting table around a cloth inspecting roller, flatly laid on a cloth inspecting light curtain and penetrates through the space between the cloth inspecting light curtain and the meter counter; the cloth rolling device is connected with the working platform and is used for receiving the detected cloth roll and rewinding the cloth roll; the cutting and sampling device is connected with the cloth rolling device and comprises a temporary storage roller set used for temporarily storing cloth rolls and a cutting and sampling mechanism which is arranged between the temporary storage roller set and the cloth rolling roller set and can cut and collect cloth at the tail ends of the cloth rolls. The packing device is arranged above the temporary storage roller set in a lifting mode and rolls along with the yardage roll to pack the yardage roll. The cloth inspecting device integrates cloth inspecting, cutting, sampling, rewinding and packaging, cloth can be cut, sampled, rewound and packaged in batches after being inspected through the same device, the working efficiency is improved, various devices do not need to be purchased, and the cost is saved.

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 invention relates to the technical field of textile production, and discloses a loom data intelligent acquisition system, which collects performance, environment and configuration parameters of a loom in real time through a data acquisition module, and ensures effective communication with various loom controllers in a micro-service mode. The data preprocessing module performs cleaning, format unification and standardization processing on the collected data to form a feature data set. Based on this, a performance prediction model building module builds a prediction model to predict the variation trend of future performance parameters of the loom. And the real-time data acquisition module and the prediction data generation module work cooperatively to provide data support for performance monitoring. The system also has the functions of performance monitoring, data comparison and analysis, deviation detection and alarm, and can monitor the performance of the loom in real time, compare prediction and actual data, timely find and mark deviation, trigger an alarm mechanism, and send detailed alarm information to operation and maintenance personnel, thereby realizing intelligent management of the loom.

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 utility model relates to the field of circular blowing cooling devices, in particular to a silk thread circular blowing cooling device for textile production, which comprises a fixing ring, an annular communicating groove is bolted in the center of an inner cavity of the fixing ring, the top of the annular communicating groove is communicated with an air supply pipe, and an air supply groove is formed in the inner cavity of the fixing ring. And fan-shaped grooves are formed in the periphery of the fixing ring, and cooling bins are connected to the inner sides of the fan-shaped grooves in a bolted mode. By means of the fixing ring, the annular communicating groove, the air supply pipe, the air supply groove, the fan-shaped groove and other assemblies, silk threads can be placed in the cooling bin at intervals, the silk threads are prevented from being wound in the cooling device, the silk threads enter different pay-off holes and enter the cooling bin, and the cooling efficiency is improved. Cooling air enters the fixing ring and enters the cooling bin through the second cold air grooves in the two sides of the annular communicating groove, so that the blowing speeds of the two sides of the silk threads are the same, the silk threads are kept perpendicular or inclined at the same angle, and the situation that multiple sets of silk threads adhere together under the condition that the silk threads are not cooled is avoided.

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 relates to the technical field of textile production, and discloses flocked cloth lifting and conveying equipment which comprises a fixing frame, a conveying frame and an auxiliary guide frame, an unfolding frame is installed at the top of the fixing frame, a fixing plate is installed at one end of the fixing frame, a control motor is installed on the fixing plate, and the conveying frame is installed at the end close to the control motor; a plurality of positioning shafts are installed between the conveying frames, the positioning shafts are used for conveying flocked cloth, recycling cavities are installed in the conveying frames, the recycling cavities are open, the flocked cloth faces the open ends of the recycling cavities in the flocked cloth conveying process, a pair of clamping grooves is formed in the inner wall of the fixing frame and used for clamping a winding roller, and the auxiliary guide frame is located over the clamping grooves; compared with the prior art, the flocked cloth conveying device starts to operate through external air pressure equipment, dust, impurities and the like generated in the flocked cloth conveying process can be adsorbed to the grid plate along air flow, and meanwhile in the subsequent flocked cloth stretching process, redundant dust, chippings and the like in gaps of flocked cloth can be rapidly shaken off.

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.