AI-enabled industrial equipment monitoring, diagnosis and health management

Abstract

Artificial intelligence (AI) has achieved significant progress in recent years and its applications cover a wide range of fields such as computer vision, natural language processing, autonomous driving and medical diagnosis. In industry, the rapid development of real-time-sensor measurement techniques promotes equipment surveillance and maintenance into the era of big data. It is still challenging to manually analyze this big data and establish general physical modelling by using the information hidden in these data. To this end, AI technology, such as machine learning and neural networks, has emerged as a promising tool to extract useful knowledge from measured data, and to tackle the real-time monitoring, diagnosis problems as well as enhancing the health management and reliability of modern industrial equipment. With the vision of establishing a strong link between AI and industrial equipment surveillance and maintenance, this special feature is designated to select, organize and exhibit the latest research progress on the cutting-edge research topics relevant to AI-Enabled Industrial Equipment Monitoring, Diagnosis and Health Management. Submissions for this topic in Measurement Science and Technology are open from 23 March 2022 to 30 September 2022 and contains 42 outstanding papers in above research fields.