Process monitoring is important for ensuring operational reliability and preventing
occupational accidents. In recent years, data-driven methods such as machine learning and …

This paper introduces a novel sparse dynamic inner principal component analysis (SDiPCA)
based monitoring for multimode dynamic processes. Different from traditional multimode …

In the era of big data, the pervasive use of artificial intelligence (AI) technology has
revolutionized various industries. AI-powered systems, particularly those utilizing data …

This article proposes a novel sparse principal component analysis algorithm with self-
learning ability for multimode process monitoring, where the successive modes are learned …

The proliferation of Internet of Things (IoT) systems has received much attention from the
research community, and it has brought many innovations to smart cities, particularly …

Multiple operating modes have become a key factor affecting the monitoring performance of
practical industrial processes. The monitoring of multiple modes with hybrid variables …

Fault diagnosis plays a vital role in ensuring the operation safety of blast furnaces and
improving the quality of molten iron in the ironmaking and steelmaking industry. The blast …

Efficient monitoring of the blast furnace system is crucial for maintaining high production
efficiency and ensuring product quality. This article introduces a hybrid cluster variational …

Hydrogen, oxygen, carbon, and nitrogen isotopes derived from three different strains of
silkworms at different life stages involved in silkworm rearing, were measured to understand …

Abnormal data detection for industrial processes is essential in industrial process monitoring
and is an important technology to ensure production safety. However, for most industrial …