Xianfeng Cao¹, Meihua Yao², Yahui Zhang^3,*, Xiaofeng Hu⁴, Chuanxun Wu³

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3233-3253, 2024, DOI:10.32604/cmes.2023.030773 - 11 March 2024

Abstract As the take-off of China’s macro economy, as well as the rapid development of infrastructure construction, real estate industry, and highway logistics transportation industry, the demand for heavy vehicles is increasing rapidly, the competition is becoming increasingly fierce, and the digital transformation of the production line is imminent. As one of the most important components of heavy vehicles, the transmission front and middle case assembly lines have a high degree of automation, which can be used as a pilot for the digital transformation of production. To ensure the visualization of digital twins (DT), consistent control More > Graphic Abstract

Bowen Yu, Chunli Xie^*

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1329-1343, 2024, DOI:10.32604/cmc.2023.046248 - 30 January 2024

Abstract With the advent of Industry 4.0, marked by a surge in intelligent manufacturing, advanced sensors embedded in smart factories now enable extensive data collection on equipment operation. The analysis of such data is pivotal for ensuring production safety, a critical factor in monitoring the health status of manufacturing apparatus. Conventional defect detection techniques, typically limited to specific scenarios, often require manual feature extraction, leading to inefficiencies and limited versatility in the overall process. Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes. Our… More >

Xi Wang^*, Guangping Zeng

FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.3, pp. 563-576, 2022, DOI:10.32604/fdmp.2022.017884 - 22 February 2022

Abstract An efficient and versatile intelligent algorithm is developed for the control of the cabin environment of wind power generators. The method can be used to monitor and solve wind power generation problems at the same time. It also provides several advantages with respect to other traditional methods which imply significant workload and maintenance personnel. The functional requirements of the intelligent control system are analyzed, and a control algorithm for the stepping motor is selected and evaluated. Through the comparative analysis of the active power and internal temperature curve for three kinds of output power of More >

Yefeng Liu^1,2,*, Yuan Zhao^1,2, Kangju Li^1,2, Shengping Yu³, Shaowu Li⁴

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 1081-1096, 2020, DOI:10.32604/iasc.2020.010139

Abstract The intelligent flexible system is a powerful means for manufacturing enterprises to achieve high efficiency and high output. The physical structure of the flexible system is constructed in this paper. The three systems; workshop intelligent logistics system, management and control system and three flexible processing that produce four products are given by the deeper design. The local workshop net which contains; position sensors, radio frequency identification (RFID), AGVs, intelligent machine, robots, raw materials and operation devices is constructed in this paper. The software, which includes gages, real-time workshops, logistics trolley, and information of all kinds More >