Building materials machinery equipment play an important role in the production of cement,
brick and tile, glass and other building materials, which are high energy consumption …

The content of free calcium oxide (f-CaO) in cement clinker is an important index affecting
the quality of cement clinker. Because f-CaO content in cement clinker cannot be measured …

Timely detection and diagnosis of process abnormality in industries is crucial for minimizing
downtime and maximizing profit. Among various process monitoring and fault detection …

Random Forest (RF) is one of the mostly used machine learning techniques in fault
detection and diagnosis of industrial systems. However, its implementation suffers from …

Missing data widely exist in industrial processes and lead to difficulties in modeling,
monitoring, fault diagnosis, and control. In this article, we propose a nonlinear method to …

Abstract Principal Component Analysis (PCA) is a widely used technique for fault detection
and diagnosis. PCA works well when the data set has linear characteristics. However, most …

This paper proposes a data‐driven sensor fault detection and isolation approach for the
general class of nonlinear systems. The proposed method uses deep neural network …

This paper proposes a data-driven actuator fault detection and isolation approach for the
general class of nonlinear systems. The proposed method uses a deep neural network …

The chemical industrial processes are both dynamic and complex. The presence of
instability and danger in the production process poses significant challenges to safety …

In this paper, a data-driven identification model of the associated fault propagation path is
proposed. Different from traditional fault diagnosis methods, the alternative approach is …