Support vector machines (SVM) have received widespread attention for their excellent ability to learn, and have been applied in many fields. The application of SVM in weld defect defection of X-ray images is receiving more and more attention, which has led to the rapid development of weld defect detection automation. In this paper, a method of weld defect detection based on SVM is proposed. First, all potential defects are detected by a novel method based on grey-level profile analysis. Then three feature vectors are extracted from potential weld defects and used to train the SVM. Lastly, the trained SVM is used to distinguish real defects from potential defects. Results show that the proposed method can achieve a high correct defection rate.

This paper proposes a non-contact, online, rapid, and non-destructive measurement method of Pinus densiflora S.et Z. (Pinus densiflora) dimension lumber based on an algorithm of maximizing lumber recovery by minimizing the enclosure rectangle fitting area. The method takes the full influence of multiple factors, such as the difficulty in measuring large-size dimension lumber, conveying deflection, etc. into account. Image splicing, object and background segmentation, and lumber size measurements are carried out. Compared to other current algorithms, it can decrease the measurement errors and improve measurement efficiency. The problems of slow image segmentation, large-size lumber measurement, and conveying deflection are solved. Through measurement tests and error analysis, the measurement accuracy of the lumber size can reach 0.8 mm/m. This method meets the requirements of high-speed lumber production and lays the foundation for the development of a lumber detection and evaluation system.

The high-quality development of the high-end equipment manufacturing industry is inseparable from the support of emerging technologies. As a typical emerging cross-cutting technology, artificial intelligence has been widely used in many fields of the high-end equipment manufacturing industry in Linyi City, Shandong Province. Combined with the application of artificial intelligence technology in the local high-end equipment manufacturing industry in Linyi, the paper analyzes and explores the impact of artificial intelligence technology on the development of high-end equipment manufacturing industry, and focuses on artificial intelligence technology in construction machinery, agricultural machinery, intelligent manufacturing equipment, new Specific application cases of key equipment manufacturing industries in Linyi City, such as energy vehicles and parts, illustrate specific measures and methods on how to apply artificial intelligence technology to promote the development of high-end equipment manufacturing industries.

To simulate each kind of natural phenomenon is an important exploration computer graphics domain, especially for those irregular objects is a difficult problem. This paper presented a survey on several methods for modeling and simulating irregular objects such as flame, smoke, and clouds. Some main research methods are introduced briefly, and the future development trend of irregular objects simulation will be given in this paper.