基于人工智能的木材缺陷检测研究进展

Research Advances in Wood Defect Detection Based on Artificial Intelligence

木材缺陷检测是木制品加工前的重要步骤,为了提高检测效率和经济效益,木材缺陷检测也从传统的人工方法向智能化方向转变。随着计算机技术的不断提高,人工智能得到快速发展,人工智能在木材缺陷检测中的应用也进一步增加。目前,人工智能主要通过机器学习、人工神经网络、深度学习等算法实现对木材缺陷的预处理和检测。文中阐述部分常用人工智能算法在木材缺陷检测中的应用,包括相关算法的原理、特点;综合分析算法优缺点,并对人工智能技术在木材缺陷检测中的研究进行了展望。

Wood defect detection is an important step before wood products processing. In order to improve the detection efficiency and economic benefits, wood defect detection has also changed from traditional manual to intelligent detection. With the continuous improvement of computer technology, artificial intelligence has been developed rapidly, and its application to wood defect detection has also been further enhanced. At present, artificial intelligence can pre-process and detect wood defects through machine learning, artificial neural network, in-depth learning and other algorithms. This paper describes the application of commonly used artificial intelligence algorithms to wood defect detection, summarizes the principles and characteristics of related algorithms, comprehensively analyzes the advantages and disadvantages of these algorithms, and discusses a prospect of future research on artificial intelligence technology for wood defect detection.