Technology and Application of Digital Nondestructive Prescreening Based on Automated Storage

• Published in: Wireless communications and mobile computing Vol. 2022; pp. 1 - 9
• Main Authors: Wu, Bingzhao, Miao, Ningjie, Wang, Liujun, Mao, Linming, Jin, Congyou
• Format: Journal Article
• Language: English
• Published: Oxford Hindawi 09.08.2022; Hindawi Limited
• Subjects: Algorithms; Automatic pilots; Automation; Cathode rays; Coils; Cold cathodes; Commodities; Data acquisition; Diameters; Digital imaging; Efficiency; Inspection; Insulation; Inventory; Logistics; Machinery; Market economies; Object recognition; Product design; Screening; Software; Warehouses; Wire
• ISSN: 1530-8669; 1530-8677
• DOI: 10.1155/2022/9443943

This project around “DR digital imaging non-destructive prediction based on automatic warehousing screening technology and application” project can be divided into cable full inspection in coil based on DR digital imaging mode of the whole case study, with a small piece of material screening technology research, based on the data acquisition and recognition algorithm used for the detection of automated storage research and pilot test three corpus. The hardware framework structure and software system security access model are designed based on existing warehouse conditions. A non-destructive batch automatic pre-screening equipment is developed for small materials, which has both DR and CT functions. Cold cathode pulse ray source for needle tip pulse discharge is improved. A set of non-destructive pre-screening equipment for the whole length of the cable is developed and arranged on the warehouse automatic tray wire rack. Through the multiangle scan imaging of two ray sources, the application of image recognition is expanded, and the automatic size labeling problem warning is realized. The non-destructive pre-screening of the whole length of the cable is implemented synchronously during the process of unloading the cable from the warehouse. The insulation layer scars of the wire diameter and thickness are compared and checked, and the quality problems are visually reflected, and the detection report is automatically generated.