With the wide adoption of building automation system, and the advancement of data,
sensing, and machine learning techniques, data-driven fault detection and diagnostics …

Over the last decade, transfer learning has attracted a great deal of attention as a new
learning paradigm, based on which fault diagnosis (FD) approaches have been intensively …

摘要提出了一种全新的分类框架, 将故障诊断方法整体分为两大类, 即定性分析的方法和定量
分析的方法. 对现有的方法在此框架下进行了划分, 并详细介绍了每种方法的基本思想 …

Artificial intelligence (AI) may be one of the most disruptive technologies of the 21st century,
with the potential to transform every aspect of society. Preparing for a “good AI society” has …

Abstract Process Systems Engineering (PSE) is the scientific discipline of integrating scales
and components describing the behavior of a physicochemical system, via mathematical …

The article discusses the presence and potential of Artificial Intelligence in Chemical
Engineering and discusses its background. Topics include the Phases of Artificial …

Several techniques for multivariate time series anomaly detection have been proposed
recently, but a systematic comparison on a common set of datasets and metrics is lacking …

Data mining and analytics have played an important role in knowledge discovery and
decision making/supports in the process industry over the past several decades. As a …

Safety is one of the key requirements for automated vehicles and fault diagnosis is an
effective technique to enhance the vehicle safety. The model-based fault diagnosis method …

The main roles of fault detection and diagnosis (FDD) for industrial processes are to make
an effective indicator which can identify faulty status of a process and then to take a proper …