Size formulations for cotton yarn weaving at lower relative humidity

Wu, Hailiang; Shen, Yanqin; Yao, Yijun; Zhang, Bin

doi:10.1177/0040517520934880

Cited by 16 publications

(10 citation statements)

References 14 publications

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“…The surface and fracture morphology of PAM-PMMA before and after adhesion to polyester/cotton yarn were observed by scanning electron microscope (SEM; Quanta-450-FEG, USA). 29 The add-on rate of the PAM-PMMA emulsion on cotton yarn and polyester/ cotton yarn is 10%.…”

Section: Yarn Morphologies Analysismentioning

confidence: 99%

“…Thus, the problems of poor size stability, low size film cohesion and uneven sizing are caused easily. In addition, starch graft polyacrylate 28 and polyacrylate-polyacrylamide sizes 29,30 have the problems of a low grafting rate and low yield. 31,32 In particular, due to the different reactivity ratios between acrylamide and acrylate, 33,34 the polymerization rate of acrylamide in thermal initiated copolymerization is significantly faster than that of acrylate.…”

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confidence: 99%

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Preparation of polyacrylamide-poly(methyl methacrylate) emulsion for enhancing the adhesion of polyester/cotton yarn

Bai

Shen

et al. 2023

Textile Research Journal

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Polyacrylamide-poly(methyl methacrylate) copolymer emulsion was synthesized by prepolymerization of methyl methacrylate, and then copolymerization with acrylamide. The final yield of polyacrylamide-poly(methyl methacrylate) emulsion can be up to 93.69%, and its molecular weight was 11.2 × 104 Da, as well as the characteristic peaks of the ester group (–COO) of methyl methacrylate and amide group (–NH2) of acrylamide appeared on its structure. The component content of acrylamide and methyl methacrylate from polyacrylamide-poly(methyl methacrylate) can be effectively controlled by adjusting the prepolymerization conversion of methyl methacrylate. The polyacrylamide-poly(methyl methacrylate) emulsion exhibited spherical morphology, and its particle size was 50–130 nm. Moreover, the correlation between particle size and the film-forming property of the polyacrylamide-poly(methyl methacrylate) emulsion was studied. It was concluded that when the particle size was small, the aggregation ability among molecules was strong, and endowed polyacrylamide-poly(methyl methacrylate) emulsion film with more action during the stretching process, making it able to withstand the larger tensile opposite force. Interestingly, the polyacrylamide-poly(methyl methacrylate) emulsion can reinforce the adhesion of polyester/cotton yarn. These benefit from the strong hydrogen bond between polyacrylamide and cotton yarn and poly(methyl methacrylate) had a similar ester structure to polyester fibers. This work solves the problems of difficult copolymerization between acrylamide and acrylate, it provides a new way to develop acrylamide-based copolymer adhesive.

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Section: Yarn Morphologies Analysismentioning

confidence: 99%

mentioning

confidence: 99%

Preparation of polyacrylamide-poly(methyl methacrylate) emulsion for enhancing the adhesion of polyester/cotton yarn

Bai

Shen

et al. 2023

Textile Research Journal

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“…The size of cotton thread for weaving at minor RH for which studies were conducted at 28°C and different relative humidity levels on the moisture recover tensile force and abrasion resistance of cotton yarns with diverse size formulations. According to the results of the study, the collection of appropriate size formulations allowed equivalent sized yarns to be woven at minimum relative humidity [4]. A new technique based on the appearance of Yarn is evaluated through Machine Vision and Image Processing methods.…”

Section: Observation In Literature Reviewmentioning

confidence: 99%

IOT Based Moisture Measurement and Conveyor Belt Monitoring in Yarn Mill

Devi¹,

Mohan²,

Baluprithviraj³

et al. 2022

J. Phys.: Conf. Ser.

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Yarn manufacturing in spinning mills is done when the twisted length of fiber goes to cheese, doubling, and winding machines. The humidity and temperature must be maintained to ensure the yarn quality. The conveyor belts have to be monitored continuously to avoid the interruption of the belts. This paper provides a solution to maintain the precise range of humidity and temperature and also to surveil the conveyor belts. The system contains a DHT sensor and an IR sensor. If the DHT sensor detects the increase in the moisture level or temperature, the signal is sent to the controller, and using a relay, either the heater or the cooler is activated respectively. The humidity level and the temperature of the yarn are displayed on the LCD. Simultaneously, the values can also be viewed on the user’s mobile application Blynk using an IoT. Another feature of this application is the continuous monitoring of the conveyor belt. If the belt stops, the IR sensor detects it, and the user is alarmed by a buzzer indicating that action is required to restart. This method reduces yarn breakage and improves the quality of the yarn. It provides continuous monitoring; the IoT application provides real-time values.

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“…Among the five basic managements of equipment, operation, process, raw materials and environments in textile mills, workshop environment is very important in the process of cotton textile production. Most of the raw materials in the production of cotton spinning enterprises have a comparatively low ignition point, which may lead fire [1,2]. For example, the ignition point of cotton is 210 • C, and cotton fiber in a loose state is only 150 • C, which burns 15% to 26% faster than wood [3,4].…”

Section: Introductionmentioning

confidence: 99%

A novel smoke detection algorithm based on improved mixed Gaussian and YOLOv5 for textile workshop environments

Chen

Xue

Zhu

et al. 2023

IET Image Processing

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There are a lot of flammable materials in the textile workshop, and once a fire occurs, it will cause property damage and casualties. At present, smoke detection in textile workshops mainly relies on temperature‐sensing smoke sensors with low detection rate and poor real‐time performance, which cannot meet the task of smoke detection in complex environments. Therefore, this paper proposes an improved mixed Gaussian and YOLOv5 smoke detection algorithm for textile workshops. In order to reduce the interference of static background in smoke detection, an improved gaussian mixture algorithm is used to extract suspected smoke areas in video by using the dynamic characteristics of smoke. Then, an adaptive attention module is added to the feature pyramid infrastructure of the YOLOv5 target detection network to improve the multi‐scale target recognition ability. In addition, the focal loss function is used to reduce the impact of background and foreground class imbalances on the detection results. The experimental results show that the detection accuracy of the proposed method is 94.7%, and the average detection speed is 66.7 FPS. By comparing with the existing state‐of‐the‐art algorithms, the detection capability of this method has been significantly improved. At the same time, it has high real‐time performance and detection accuracy in smoke detection in textile workshops.

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Size formulations for cotton yarn weaving at lower relative humidity

Cited by 16 publications

References 14 publications

Preparation of polyacrylamide-poly(methyl methacrylate) emulsion for enhancing the adhesion of polyester/cotton yarn

Preparation of polyacrylamide-poly(methyl methacrylate) emulsion for enhancing the adhesion of polyester/cotton yarn

IOT Based Moisture Measurement and Conveyor Belt Monitoring in Yarn Mill

A novel smoke detection algorithm based on improved mixed Gaussian and YOLOv5 for textile workshop environments

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