12104 results about "Textile" patented technology

The invention relates to the technical field of textile machinery fault detection, and discloses a spinning machine fault detection method and system based on deep learning, and the method comprises the steps: collecting vibration, temperature and current signals through a plurality of sensors, constructing a data stream after principal component analysis and dimension reduction, employing a variational auto-encoder to reconstruct an error positioning abnormal data segment, and obtaining a spinning machine fault detection result. The method comprises the following steps: extracting local features of a multi-source signal in combination with a convolutional neural network, dynamically distributing feature weights by using an attention mechanism, screening time sequence key features through a forgetting gate, introducing an LSTM network to model a feature sequence dynamic relationship, completing fault category mapping based on a support vector machine, and triggering LSTM secondary classification calibration for samples with insufficient confidence. A closed-loop technical system of data dimension reduction, anomaly detection, feature optimization, time sequence modeling and classification verification is formed, and efficient analysis and accurate recognition of multi-modal fault features under complex working conditions are achieved.

The invention discloses an automatic textile color fastness rating method and system based on a CNN-Transform fusion model, and relates to the technical field of textile digital detection. And then, feature extraction and rating are carried out by using a CNN-Transform fusion model. After the features of the two are fused, weighting is carried out through an attention mechanism, classification is carried out through a full-connection layer, and the color fastness grade probability is determined through a Softmax function. Meanwhile, a cross entropy loss function is combined with a label smoothing technology, an Adam optimizer is utilized, and a learning rate attenuation strategy is matched to train the model. Finally, confidence evaluation and result correction are carried out on the rating result, automatic and high-precision textile color fastness rating is achieved, and the problems that an existing rating method is poor in accuracy, low in consistency, difficult to adapt to fine rating standards and the like are effectively solved.

The invention discloses a textile fabric tearing strength detection method and system, and relates to the technical field of fabric detection.The method comprises the steps that fabric microstructure, macromechanics and component data are synchronously collected through a multi-mode sensing system, and detection modes are dynamically switched based on a real-time recognition result; inputting the space-time correlated defect data into the physical constraint enhanced prediction model to generate a crack propagation trend and a tear strength prediction value; wherein the prediction model is fused with a Griffith crack propagation theory and a hidden Markov model, and double constraints of a material mechanics law and dynamic defect evolution are realized; a non-contact detection module and a flexible contact detection module work cooperatively, and a process optimization scheme is output in combination with an edge and cloud distributed architecture.

The invention discloses an automatic testing device and method for multi-directional tensile strength of textiles based on constant tension, and relates to the technical field of tensile strength detection.The automatic testing device comprises a rigid rack system, and a high-elastic fabric optical response mechanism is integrated on a double-stand-column portal frame of the rigid rack system; the fiber damage process is reflected through the light transmittance of light to the fabric and the light spot change; the high-elastic fabric optical response mechanism comprises a sealing light insulation assembly, a light source assembly and an imaging assembly. The light source assembly comprises pulse LED light source arrays arranged at equal intervals in the fabric stretching direction, a lampshade and a transverse movement driving unit. The problems that in the prior art, when the tensile strength of a fabric is detected, only the limit value when a sample is completely broken can be recorded, and microcracks generated by step-by-step failure of fibers in the stretching process cannot be captured are solved. The device has the advantages that when the tensile strength of the fabric is detected, the fiber fracture process in the fabric is directly reflected through the change of light spots formed by light penetrating through the fabric, and the like.

The present invention is used in the technical field of functional textile materials. Disclosed are a composite fiber-based protective material, and a preparation method therefor and the use thereof. The composite fiber-based protective material comprises a unidirectional moisture-guiding fiber membrane, a bacteriostatic sweat-absorbing layer and a waterproof moisture-permeable membrane, which are sequentially stacked, wherein the unidirectional moisture-guiding fiber membrane comprises a hydrophobic fiber membrane and a hydrophilic fiber membrane sandwiched between the hydrophobic fiber membrane and the bacteriostatic sweat-absorbing layer, and the average pore size of the hydrophobic fiber membrane is larger than the average pore size of the hydrophilic fiber membrane. The average pore size of the hydrophobic fiber membrane is 10-18 μm; and the average pore size of the hydrophilic fiber membrane is 1.0-2.3 μm. The composite fiber-based protective material is prepared from the unidirectional moisture-guiding fiber membrane, the bacteriostatic sweat-absorbing layer and the waterproof moisture-permeable membrane by means of a lamination process. In addition to waterproofness and moisture penetrability, the composite fiber-based protective material also has biodegradability and a bacteriostatic effect.

The invention discloses a novel textile fabric tensile strength detection device, and relates to the technical field of cloth detection equipment. The device comprises a base, a pressing block is arranged at the top of the base, push plates are arranged on the two sides of the pressing block, and first pressure sensors are installed in the push plates; an adjusting assembly is arranged on the top of the base. A rotating shaft, a gear and a toothed plate of the adjusting assembly are matched with a hydraulic rod and a clamping plate of the clamping assembly, accurate clamping and fan-shaped stretching of the side edge of cloth are achieved, and the defect that a traditional device can only conduct horizontal tension detection is overcome; an adjusting plate, an adjusting groove and a moving shaft of the linkage assembly are driven by a screw rod and a moving sleeve of the driving assembly, so that the cloth generates fan-shaped deformation under the action of lateral tension, the tensile strength of the side edge of the cloth can be evaluated more comprehensively in combination with dual monitoring of a first pressure sensor and a second pressure sensor, the accuracy of detection data is remarkably improved, and the detection efficiency is improved. The device is especially suitable for testing high-strength fabrics with easy-to-tear side edges.

The invention relates to the technical field of three-dimensional image reconstruction, in particular to a VR-based three-dimensional reconstruction method and system for textile culture heritage, and the method comprises the steps: obtaining a multi-view image collection sequence of the textile culture heritage, carrying out the geometric topological feature extraction of the multi-view image collection sequence, generating a three-dimensional point cloud geometric model, and carrying out the reconstruction of the three-dimensional point cloud geometric model. Performing multi-resolution texture feature mapping processing on the three-dimensional point cloud geometric model to generate an initial three-dimensional model fusing geometric topological features and multi-resolution texture features; performing dynamic geometric optimization processing on the initial three-dimensional model based on preset VR display parameters to generate a target three-dimensional model after surface continuity correction; and performing dynamic matching processing on the target three-dimensional model and a preset VR interaction algorithm to generate a VR visual model with a multi-dimensional interaction attribute, and transmitting the VR visual model to a VR display terminal to perform three-dimensional space rendering, so that the three-dimensional reconstruction and interaction intelligence degree of the textile culture heritage can be improved in combination with a VR technology.

The invention discloses a textile fabric wear resistance detection device, and relates to the technical field of textile fabric wear resistance detection, the textile fabric wear resistance detection device comprises a support mechanism I and a detection mechanism, a sampling mechanism is arranged on a support mechanism II, the detection mechanism is arranged on a support seat II, and an adjusting mechanism I and an adjusting mechanism II are arranged on the detection mechanism. The device has the advantages that the third supporting seat is matched with the sampling mechanism, so that an experiment can be performed without manually cutting experimental cloth into a specified size, the preparation time before the experiment is shortened, and the detection efficiency is improved; the detection mechanism is adjusted through the adjusting mechanism I, so that tests of the same test type but different test strengths can be conveniently carried out, and experiment results can be directly compared; the detection mechanism is adjusted through the adjusting mechanism II, so that tests with different test types and the same force as one group can be conveniently carried out, and experiment results can be directly compared; and through horizontal comparison or vertical comparison, a detection result which is more in line with a use scene is provided.

The invention relates to the technical field of biomechanical measurement and analysis, in particular to a home textile recommendation method and system based on child health data monitoring and analysis. The method comprises the following steps: collecting an original point cloud coordinate set of a sleeping posture of a child; extracting a cervical curvature parameter group according to the extracted cervical curvature parameter group of the skeleton key point spatial distribution diagram; performing cervical vertebra and body position analysis according to the cervical vertebra curvature parameter group to obtain cervical vertebra curvature-body position holographic data; collecting a static pressure baseline data set according to the cervical curvature-body position holographic data; performing body position-pressure correlation analysis according to the static pressure baseline data set to obtain a body position-pressure mapping relation table; and generating a pressure distribution index map according to the body position-pressure mapping relation table. According to the method, the physical sign data, the pressure distribution and the physiological curvature change of the children in the natural sleep state are comprehensively collected and analyzed, so that high-precision, whole-process and personalized healthy home textile recommendation is realized.

The invention relates to the technical field of polyester fibers, in particular to a high-strength wear-resistant polyester fiber and a preparation method thereof. The invention aims to solve the problem that the mechanical strength and wear resistance of the existing polyester fiber are difficult to consider at the same time. The preparation method comprises the following steps: carrying out esterification and polycondensation on terephthalic acid, ethylene glycol, hydroxyl-terminated polydimethylsiloxane and isophthalic acid to obtain modified PET; the preparation method comprises the following steps: respectively carrying out oxidation treatment on graphene and a multi-walled carbon nanotube, and then adding polyether amine for grafting; carrying out melt blending with PET slices to obtain nano master batches; carrying out melt blending on the chopped glass fibers and the PET slices to prepare micron master batches; and mixing the modified PET, the nano master batch and the micron master batch, carrying out ultrasonic dispersion, adding an auxiliary agent, and carrying out melt spinning, three-section stretching and three-section heat setting treatment to obtain the high-strength wear-resistant polyester fiber. Through the synergistic effect of the components and the process, the prepared fiber has excellent mechanical properties and wear resistance, and has wide application prospects in the fields of clothing, home textiles, industry and the like.

The invention belongs to the technical field of position tracking control of rigid multi-joint mechanical arms, and discloses a fuzzy self-adaptive visual servo control method and system for a multi-joint mechanical arm system for placing bobbins in a textile workshop, and the method comprises the steps: constructing an image error model according to the positions of feature points on an image plane; the fuzzy logic system is used for processing uncertain items in the system, the instruction filtering and fuzzy self-adaption technology is used for achieving tracking control over the expected trajectory of the system, the problem of calculation complexity is solved, and adverse effects caused by filtering errors are eliminated. In the process of changing the bobbins, the bobbins are placed on a creel through a multi-degree-of-freedom robotic arm, a clamping jaw at the tail end of the robotic arm is required to accurately grab the bobbins for feeding and discharging, and the requirement for accurate and rapid control of the robotic arm is met, so that research on visual servo control of the robotic arm is of great significance. The method has a good control effect, the problem of calculation complexity in the design process of the controller is solved, the trajectory tracking error is smaller, and the system robustness is higher.

The invention relates to the field of textile materials, and particularly discloses a graphene enhanced polyester yarn and a preparation method thereof.The preparation method comprises the following steps that silicon dioxide aerogel serves as a porous carrier to be loaded with graphene, and a graphene-porous carrier composite material is prepared; the graphene-porous carrier composite material is subjected to modification treatment through vinyl trimethoxy silane and 3-amino propyl triethoxy silane, and then a modified graphene composite material is prepared; reacting the modified graphene composite material, a styrene monomer, an acrylate monomer and an initiator to prepare modified graphene; mixing the prepared modified graphene with polyester chips, and then carrying out melt spinning to prepare graphene enhanced polyester yarns; the invention further discloses the graphene enhanced polyester yarn prepared by adopting the preparation method. The preparation method has the characteristics that the dispersion of the graphene in the polyester is improved, and the direct interface compatibility of the graphene and the polyester fiber is improved, so that the mechanical property of the polyester yarn is improved.

The invention relates to the field of textile materials, and provides an antibacterial breathable yarn obtained by blended spinning of polyester fibers, polyamide fibers, cotton fibers and elastic fibers. The polyester fiber is prepared through melt blending and spinning processes and comprises polyethylene glycol terephthalate slices, modified chitosan zinc oxide, an antioxidant 1010, a POE elastomer, polyether modified silicone oil and polyethylene glycol 200, and the modified chitosan zinc oxide is prepared by compounding chitosan cinnamyl aldehyde Schiff base and silane modified zinc oxide. The chitosan cinnamyl aldehyde Schiff base is prepared through a Schiff base condensation reaction of chitosan and cinnamyl aldehyde, and the silane modified zinc oxide is prepared from nano rod-shaped zinc oxide particles modified by isocyanate propyl triethoxy silane. The yarn has excellent antibacterial property, air permeability and flexibility and is further used for knitting antibacterial breathable socks, the knitting density of the sock bottom part is reduced to enhance the air permeability, the knitting density of the sock opening part is improved to improve the elasticity and the fitting degree, and the yarn has wide application value.

The invention provides a textile state detection and analysis system, and relates to the field of state detection.The textile state detection and analysis system comprises the steps that firstly, a to-be-detected textile surface image is obtained and preprocessed, then a double-branch feature extraction network is constructed synchronously, and local edge features of microscopic flaws and a global distribution rule of a macrostructure are captured respectively; local details and global semantics are further associated through cross-scale feature fusion, multi-scale image coding features of the surface of the to-be-detected textile are generated, finally, defect positioning, classification and confidence evaluation are performed on the fused features in combination with a pre-trained deep learning model, and whether an alarm signal is sent out or not is automatically judged according to a detection result. Therefore, defect detection can still keep high sensitivity in a complex light environment, false detection and missing detection of a shadow or overexposure area are effectively inhibited, and the accuracy and reliability of defect detection are remarkably improved.

The invention discloses an intelligent identification and sorting method for waste textiles, and belongs to the technical field of textile recovery. An intelligent identification and sorting method for waste textiles comprises the steps of scanning recycled waste textiles by using a hyperspectral camera, obtaining hyperspectral image data of the waste textiles, preprocessing the obtained hyperspectral image data to improve data quality, constructing a material identification model, inputting dimension-reduced hyperspectral features into the model, and identifying the waste textiles according to the dimension-reduced hyperspectral features. Through training and learning spectral feature differences of different materials, the materials of the waste textiles are accurately identified; recording the surface condition of the waste spinning through a monitoring device, and analyzing the influence of the surface condition on spectrum identification; according to the material recognition result and the surface recognition result, sorting equipment is controlled to carry out sorting operation on polyester textiles in the waste textiles; a sorting result is fed back to a control system, the sorting accuracy rate is recorded, and the performance of the recognition model and the sorting equipment is evaluated and optimized.

The invention discloses a phase change energy storage waterborne polyurethane nanofiber membrane and a preparation method thereof. Lignin-based phase change microcapsules are prepared by combining ultraviolet crosslinking with lignin shell packaging, and then the nanofiber membrane containing the phase change microcapsules is prepared through an electrostatic spinning technology. And finally, constructing the waterborne polyurethane phase change fiber membrane with asymmetric wettability through a low-temperature plasma technology. According to the invention, lignin is self-assembled to form nanoparticles, and ultraviolet light induces free radical polymerization to form a polymer film, so that the packaging capability of the phase change material is improved. The phase change microcapsule prepared by the method is high in packaging efficiency and excellent in phase change performance, the preparation process is green and environment-friendly, the technological operation is simple, the temperature of the prepared phase change energy storage waterborne polyurethane nanofiber membrane conforms to the comfortable temperature range of a human body, and the phase change energy storage waterborne polyurethane nanofiber membrane has excellent temperature regulation, waterproof and moisture permeable performance and is suitable for being used in the field of water treatment. Good application prospects are realized in the field of functional textiles with functions of intelligent temperature regulation, water resistance and air permeability and the like.

The invention discloses an ancient textile image restoration system based on artificial intelligence. The system comprises a multi-source image acquisition module, a damaged area detection module, a pattern generation module, a color restoration module, a texture synthesis module and a multi-scale fusion module. The system introduces a wavelet guidance-frequency domain attention mechanism and a rotation invariant Haar wavelet basis function to realize accurate identification and classification of a damaged area; a saliency-guided wavelet decomposition control and self-adaptive threshold denoising method is combined, so that the perception capability of slant textures and edge details is improved; the texture synthesis module constructs a hierarchical modeling strategy fusing Gram style loss, Wasserstein style loss and a total variation regular term, and realizes generation of high-quality textures with unified styles and smooth edges; the system can be widely applied to cultural relic digital repair and display scenes.

The invention relates to the technical field of printing and dyeing textile equipment, and discloses an automatic cloth roll dismounting device which comprises a stacking support, a plurality of cloth rolls can be stacked on the stacking support in sequence, and binding ropes are bound to the two ends of each cloth roll; a robot body is arranged on one side of the stacking support, and a first clamp or a second clamp can be installed at the top end of the robot body. Wherein the first clamp and the second clamp are installed in a mutually exclusive mode, that is, only one set of the first clamp and the second clamp can be installed at the same position of the top end of the robot body, the equipment for automatically disassembling the yardage rolls can achieve unstacking of the yardage rolls, cutting off binding ropes and adjusting the orientation of cloth ends of the yardage rolls, meanwhile, automation of the whole carrying and feeding process of the yardage rolls is achieved, and the automation degree is high. The effect of saving labor and corresponding labor cost input in the unwinding link is achieved to the maximum extent, meanwhile, the effective working efficiency of unwinding can be greatly improved, and the labor intensity of workers is relieved.

The invention provides a method for recovering a BHET monomer from a waste polyester textile alcoholysis solution, and is characterized in that the recovery method comprises the following steps: (1) filtering: mixing the waste polyester textile alcoholysis solution with water under a stirring condition, and filtering at 55-70 DEG C; and (2) cooling crystallization: under a stirring condition, carrying out primary cooling on the filtrate obtained by filtering in the step (1) from 55-70 DEG C to 45-55 DEG C, then adding a BHET seed crystal, then carrying out secondary cooling to 5-15 DEG C, and maintaining the temperature for 20-60 min to obtain the BHET monomer. The mixed solution cooling crystallization method is developed on the basis of complexity of components of the waste polyester textile fabric, the problems that in the conventional production process, a BHET crystal product is low in quality, prone to scaling, difficult to filter and dry and the like are solved, and the obtained BHET product is large in particle size, narrow in particle size distribution, high in purity, good in fluidity and high in stability.

The invention provides a preparation method of a waterproof flame-retardant multifunctional fabric, and belongs to the technical field of functional textiles. The preparation method comprises the following steps: heating dihydric alcohol until the dihydric alcohol is completely melted, adding diisocyanate, a flame retardant and a catalyst, reacting to obtain a polyurethane prepolymer, adding a chain extender for chain extension, then adding an end-capping reagent for end capping, cooling, adding an emulsifier to obtain a waterproof flame retardant emulsion, adding water to form a finishing agent, soaking a polyacrylonitrile pre-oxidized fiber fabric in the finishing agent for treatment, and drying to obtain the waterproof flame retardant fabric. And pre-drying and baking to obtain the multifunctional fabric. Polyhydric alcohol with a long alkane chain is adopted to carry out chain extension on a polyurethane prepolymer, the obtained waterproof agent has good film-forming property, can be firmly fixed on the surface of a fiber without the help of a cross-linking agent or an adhesive during application, and endows a modified textile with excellent washing fastness.

The invention belongs to the technical field of recycled polyester, and particularly relates to a waste polyester textile recycling method which comprises the following steps: decolorizing colored waste polyester textiles by adopting a decolorizing agent which is more than one of dimethyl carbonate, diethyl carbonate and methyl ethyl carbonate; the depolymerization agent is adopted to depolymerize the decolored polyester textile to obtain the terephthalate, and the depolymerization rate of the decolored polyester textile is 98.0-100%; firstly, terephthalate is converted into DMT, and then DMT, ethylene glycol, a catalyst and a functional additive are subjected to a repolymerization reaction to obtain regenerated PET. According to the method, a process of decoloring and depolymerizing sequentially is adopted, and decoloring and depolymerizing are coordinated, so that the process is simplified, the energy consumption and pollution are reduced, and the economical efficiency and sustainability of waste polyester textile recycling are improved.

The invention discloses a preparation method of a composite phase-change temperature-adjusting organic fiber membrane with a flexible core-shell structure, and belongs to the field of intelligent textile materials.The preparation method comprises the following steps that polyacrylonitrile (PAN) serves as a sheath layer material, n-octadecane serves as a core layer phase-change material, and the composite phase-change fiber membrane is prepared through a melt spinning method and a coaxial electrostatic spinning technology. According to the invention, the fiber membrane with high melting enthalpy value (171.6 J / g), excellent thermal stability (the latent heat is still 117.7 J / g after 100 times of heating-cooling circulation) and excellent mechanical properties (the tensile strength is 2.418 MPa, the tensile yield stress is 2.331 MPa, the tensile strain at break is 36.5%, and the elastic modulus is 58.226 MPa) can be prepared; a new thought is provided for preparing intelligent textiles with good flexibility and efficient heat management capability.

The invention discloses functional caprolactam, an intrinsic flame-retardant nylon material as well as a preparation method and application thereof, and relates to the technical field of flame-retardant nylon materials. The preparation method comprises the following steps: preparing an alpha-amino-epsilon-caprolactam intermediate by taking lysine as an initial raw material through one-step efficient cyclization, then reacting with a reagent containing a flame-retardant group to obtain functional caprolactam, and finally introducing the flame-retardant group into a side chain of nylon 6 by utilizing ring-opening copolymerization of the functional caprolactam and caprolactam to prepare the intrinsic flame-retardant nylon material. The flame-retardant nylon material can effectively avoid the migration and loss of the flame retardant, improve the dispersity of the flame retardant and enhance the flame-retardant effect, can keep the main chain structure of the nylon 6 unchanged, reduces the influence on the inherent performance of the nylon 6, is expected to directly replace the existing nylon 6 material, and is applied to the fields of automobiles, textiles, electronics and electrics, buildings, packaging and the like. In addition, a renewable lysine resource is used for partially replacing a petroleum resource, so that the method has the advantages of resource conservation, environmental friendliness, simple process, low cost and the like.

The invention discloses a flame-retardant nylon material as well as a preparation method and application thereof, relates to the technical field of flame-retardant high polymer materials, and solves the problems that a flame-retardant nylon material prepared by a blending method is unstable in flame-retardant effect and a flame-retardant nylon material prepared by a copolymerization method is complex in process. The preparation method comprises the following steps: carrying out ring-opening copolymerization on a seven-membered ring lysine derivative monomer formed by ring formation of lysine and other lactam monomers to obtain copolyamide with a functional group on a side chain, and reacting a reagent containing a flame-retardant group with the functional group to prepare the flame-retardant nylon material. The flame-retardant nylon material prepared by the invention can effectively avoid migration and loss of the flame retardant, improve the dispersity of the flame retardant and enhance the flame-retardant effect. Meanwhile, a renewable lysine resource is used for partially replacing a petroleum resource, so that the method has the advantages of resource conservation, environmental friendliness, simple process, low production cost and the like. The flame-retardant nylon material disclosed by the invention has lasting and stable flame-retardant performance and can be widely applied to the fields of automobiles, textiles, electronics and electricity, buildings, packaging and the like.

The invention relates to the field of yarn spinning, in particular to a real-time quality rating method and system for yarn spinning. The method comprises the following steps: acquiring a space-time charge data set, and generating a yarn electrostatic state data set through a multi-mode sensing fusion strategy; on the basis of the yarn static state data set, yarn spinning quality defects are recognized by combining yarn form data collected in real time, two-dimensional dynamic rating is executed according to defect types and severity, and yarn real-time quality rating is generated; according to the yarn real-time quality rating, carrying out change trend analysis on the yarn real-time quality rating to generate a yarn subsequent quality change trend; and executing a corresponding process regulation and control instruction according to the subsequent quality change trend of the yarn, and outputting a quality rating log. In the yarn spinning process, process look-ahead optimization is achieved, quality tracing is perfected, and the accuracy and real-time performance of quality rating are improved.

The invention relates to the technical field of antibacterial non-woven fabrics, and discloses an intrinsic antibacterial non-woven fabric and a preparation method thereof.The intrinsic antibacterial non-woven fabric is prepared by adopting a dip-coating method and by soaking a non-woven fabric in antibacterial slurry, taking out the non-woven fabric for drip drying and then drying the non-woven fabric to constant weight; wherein the antibacterial slurry is prepared by compounding antibacterial polyol with a synergistic antibacterial effect, nano titanium dioxide modified by a coupling functional phenolic hydroxyl Schiff base type antibacterial monomer and a branched antibacterial monomer. According to the intrinsic antibacterial non-woven fabric, the technical problems that in the prior art, an antibacterial agent is large in toxicity, prone to loss and insufficient in antibacterial spectrum coverage range are solved, and the intrinsic antibacterial non-woven fabric can also be applied to the field of filtering materials, the field of medical treatment and public health and the field of textile materials and has the beneficial technical effects of inhibiting bacterial growth and guaranteeing sanitation and safety.

This utility model discloses a yarn tension adjusting device for textile machinery, including a support plate. A first motor is fixedly connected to the upper surface of the support plate, and a lead screw is fixedly connected to the output end of the first motor. A slider is threadedly connected to the outer surface of the lead screw, and a connecting plate is fixedly connected to the front surface of the slider. A lifting block is fixedly connected to the lower surface of the connecting plate. The first and second limiting plates can block the yarn, preventing it from tangling during transport to the textile machinery and thus avoiding interference with yarn processing. The second motor, first guide post, and second guide post structure ensure that when the yarn comes into contact with the first and second guide posts, activating the second motor causes the first and second guide posts to rotate at a uniform speed, making the yarn more stable during transport to the textile machinery.

The present invention relates to an electrospun fiber, a process for preparing the same, a nonwoven fabric comprising the electrospun fiber, as well as corresponding uses and articles. The inventive electrospun fiber comprises a polymer, a surface-reacted calcium carbonate and a pharmaceutically or nutraceutically active ingredient, wherein at least a part of the pharmaceutically or nutraceutically active ingredient is present within the pores of the surface-reacted calcium carbonate. The inventive fibers may be used e.g. in yarns, transdermal patches, intrabuccal patches, implantable textiles, wound dressings and / or medical tapes.

Devices and methods of harvesting textile hemp are presented. The methods comprise mowing the hemp and wherein the cut stems are held between crossed conveyor belts and then rotated 90° from vertical to horizontal, taken over one or more times by other belts, to be deposited in parallel swaths on the field.

The invention relates to a textile product defect identification method based on improved YOLOv11. The method comprises the following steps: acquiring a textile product defect image data set; performing pretreatment; dividing into a training set and a verification set; the method comprises the following steps: introducing MConv into a YOLOv11 backbone network, adding a CCIAP module behind a C2PSA module, and applying BiFPN in a path aggregation network; performing prediction through YOLO Head to obtain N prediction feature maps; the overall loss of the network is calculated, and network parameters are optimized through back propagation; predicting the verification set image through a network to output AP values of various categories; repeating the above steps to obtain a trained YOLOv11 network; and detecting the test image or video by using the trained detector to obtain a detection result. According to the method, the MConv is introduced into the YOLOv11 network to enlarge the receptive field, the CCIAP module is added behind the C2PSA to improve the feature extraction capability, and the BiFPN is applied to the Neck layer to enhance the feature fusion capability, so that the target detection precision is improved and the real-time detection of textile product flaws is realized under the condition that the reasoning speed is not influenced.