关键词: 智能织造, 云边端协同, 织机, 信息采集, 设备状态监测

Abstract:

Objective In order to improve the reliability of information collection and production control, a loom data acquisition and monitoring system based on cloud edge collaboration was designed. Research was conducted on from three aspects, i.e., information communication collaboration, data storage collaboration, and computing service collaboration, aiming to provide highly reliable and high-quality data support for intelligent production of weaving.

Method In terms of information communication collaboration, this research designed a unified communication module for the underlying terminal information, determines the information communication format of the cloud edge, and developed information communication services for the edge and central cloud. On data storage collaboration, an information model for weaving equipment was defined, and real-time caching data storage solutions for edge end and historical data storage solutions for central cloud end big data were designed. with respect to computing service collaboration, the principle of "demand-based requests at the edge and unified control at the central cloud" was followed to achieve reasonable execution and control of various service applications under cloud edge collaboration.

Results Information communication and processing functions of the central cloud was verified. In order to further reflect the information communication ability of cloud edge collaborative communication, the communication terminals of the underlying devices and the edge end were set up through signal transmission without information analysis and buffering preprocessing, based on the above cloud edge network topology architecture. Communication performance between pure cloud and cloud edge collaborative communication modes was compared, which was concentrated on communication time consumption between pure cloud communication and cloud edge collaborative communication for a total of 102 looms in 17 random groups of devices. Among them, the average communication delay of each group of devices in pure cloud communication mode was 25.54 s, and the average communication delay of each group of devices in cloud edge collaborative communication was 4.74 s. The information upload and download traffic corresponding to 24 h was in two communication modes: pure cloud communication and cloud edge collaborative communication. The average information upload traffic per hour in cloud edge mode was 54.5 Mb/h, and the average download traffic was 365 Mb/h. In the communication processing mode of the central cluster, the average hourly information upload traffic was 111.58 Mb/h, and that for the average download traffic was 754.5 Mb/h. In pure cloud communication, the central cloud server was required to perform identity verification before accessing information to each device, while in cloud edge communication mode, the device terminal and edge end completed the identity verification in advance and cache information. Therefore, the information processing time and transmission consumption flow were much lower in cloud edge communication mode than in pure cloud communication mode, demonstrating superiority of cloud edge collaborative communication mode.

Conclusion At present, the system proposed in this paper has been applied in the actual production environment of the weaving workshop, and the results show that the system is stable and reliable, which can meet the intelligent application requirements in weaving production scenarios and improve the production and operation efficiency of the weaving workshop.

Key words: intelligent weaving, cloud edge collaboration, loom, data acquisition, equipment status monitoring