Jiang Xiuming

Detection clustering analysis algorithm and system parameters study of the near-point multi-class foreign fiber

Abstract In this paper, we investigate a detection algorithm for foreign fiber during the processing of cotton textile. By collecting a large number of samples, we determine the color model and establish its characteristic parameters of a foreign fiber. We found foreign fibers of multiple types (classes) and proposed a classification–recognition algorithm based on clustering analysis. The maximum error of the studied recognition algorithm is 0.012, which meets the requirement to recognize foreign fibers. Through many experiments, the optimal parameters for the foreign fiber detection system were determined, and the fiber recognition rates for different types were obtained. The lowest recognition rate is 85%. This is sufficiently high to reject foreign fibers and reach the standards of the textile industry. Experimental results show that foreign fiber clustering analysis algorithm is feasible, and it not only improves the quality of foreign fiber detection significantly, but also has high theoretical value and practical value.

Research of foreign fibers in cotton yarn defect model based on regression analysis

The detecting of foreign fiber may not be very effective, particularly around the detection zone where many types of foreign fibers may coexist. In order to eliminate the fibers more effectively, a model has been established to detect foreign fiber faults in yarn. Relevant data were collected through investigation of a number of standard samples, with the length and area of foreign fibers as the independent variables, and the number of defects as the dependent variable, which were combined using linear regression theory to establish a regression equation for different fiber defects. The equations to find the regression coefficients, which include the model fitting degree, the Durbin–Watson value, the standard error, and the Cook distance, were rigorously tested, and the regression equation was eventually compiled to produce the yarn faults model. When the fiber detection equipment recognizes fibers with a foreign profile, the calculated profile fiber size is used in a corresponding regression equation which obtains the defect points and compares them with each other, so that foreign fibers which are potentially more dangerous can be identified and preferentially eliminated. In order to verify the model, spinning experiments are performed. The actual defects from the experiment are compared with the predicted theoretical defects from the equation, and the prediction accuracy was found to reach more than 95%, showing that the foreign fiber yarn faults model, which lays a theoretical foundation for foreign fiber detection, is accurate and effective.

One-step scouring and bleaching of cotton fabrics in the lye of PID control system

This article describes the one-step scouring and bleaching of cotton fabrics in the PID control lye, the issue is the first Ministry of Science and Industrial Technology Innovation Alliance program sub-topics; it is also Tianjin Science and Technology sub-project issues. These implements ① One-step scouring and bleaching, significant time savings.② Multi-sensor data fusion technology is adopted, the test data results of the three detecting device will be fusion, improve the accuracy of the detection data, the system dynamic performance and control accuracy.③ Smart sub-processes and non-linear processing are adapted, the inference detection signal agencies to achieve a smooth transition, checking and correction.④ Smart follow, even with the decoupling control technology are adapted, the reasoning sector in achieving the following level of each tank, even, once again realized the liquid level and flow decoupling. The system has been running at the production site.

Notice of Retraction Detection Press Palm Strength of Flyer of Fly Frame Based on ZigBee Wireless Transmission Technology

Roving frame is one of the important textile machines. The quality of the wound package of its produces is affected by the flyer of roving frame. In order to test accurately interrelated parameters of flyer, the new press palm strength of flyer of fly frame detected wireless signal transmission testing system is developed. In order to more accurate transmission for detection signal of the press palm strength of flyer of fly frame in the testing process, this paper introduced a way of wireless transmission based on ZigBee wireless network technology and MC13192 chip as transceiver circuit, with SCM MCS08GT60, which will sensor detects the electrical signals transmitted to the PLC by the wireless transmission, it can solve the inconvenience and drawbacks when the flyer test connected lineate, also makes detection accuracy and stability of the greatly increased. So this method is feasibility, it is applicable to a wide range of the flyer of fly frame detection areas.