Research And Design Of Intelligent Detection System For Spinning Frame Production Process

Textile industry is a highly competitive and internationally dependent industry in China,and it is also one of the traditional pillar industries with labor-intensive and advantages.However,compared with some developed countries,China’s textile enterprises lag behind in production automation,production efficiency and production management.In order to improve the technological level of China’s textile industry,China has also carried out research on the intellectualization of the textile industry.This paper mainly focuses on the research and design of intelligent detection system in spinning frame production process.The topic selection has great theoretical significance and practical value.In this paper,one of the processes in the textile workshop is taken as the research object,mainly the intelligent detection of spinning machine production process parameters.The network system of spinning machine production process parameters detection is designed and implemented by using wireless sensor network technology.Firstly,the production parameters of the spinning frame are tested.In view of the running situation of spinning frame in spinning mill,Hall sensor is used to detect the rotational speed of spinning frame axes,and the required parameters are calculated.In order to centralize the monitoring of spinning frame operation,analyze the production site environment,communication distance and node layout,ZigBee is used to establish a network monitoring system to improve the stability of rate acquisition and data transmission reliability.According to the actual situation of the production site,the traditional ZigBee routing algorithm is improved to make it more convenient and efficient in the environment of textile mills and reduce the packet loss rate.The rate acquisition node sends the collected data to the coordinator,which is relayed by the WIFI gateway through the WIFI module and uploaded to the PC’s upper computer.The second is the detection of broken ends of spinning yarns.Firstly,the collected image signal is filtered by median filter,which effectively avoids the interference of the judgment of broken yarn due to the intensity of light and the fast rotation of yarn.Then,the gray level histogram is used to calculate the number of corresponding pixels from large to small and set the threshold value.Then,the gray level image is converted into binary image,and then the binary image is projected vertically and horizontally through vertical and horizontal projection.Horizontal projection determines the rows and columns of noise and filters them out.Because the standard Hough transform algorithm can not be applied to pre-processed images,and in order to further eliminate the influence of background noise on yarn breakage judgment,this paper proposes an improved Hough transform algorithm to detect the line in binary images,in order to quickly extract yarn information.At the same time,the scanning angle and step length of the Hough transform algorithm are optimized,the calculation speed is increased,the calculation time is shortened,and the detection efficiency of yarn broken ends is improved.Finally,the spinning frame production management cloud platform system is built.The cloud platform system described in this paper is a Web application based on Spring,Spring MVC,MyBatis framework and MySQL database.It shows in detail the daily operation of spinning frame,production process parameters,daily production output,employee information and so on.At present,the application can run normally on Aliyun server,realize remote login and management,solve the shortcoming that the original host computer software can only be monitored locally,and now it can be used by enterprise managers anytime and anywhere to monitor the operation of spinning frame.