Quality prediction is beneficial to intelligent inspection, advanced process control, operation
optimization, and product quality improvements of complex industrial processes. Most of the …

In the era of industrial big data, traditional shallow machine learning-based data analytical
technologies cannot handle complex industrial system fault detection issue effectively. In …

Although recent transfer learning soft sensors show promising applications in multigrade
chemical processes, good prediction performance mainly relies on available target domain …

Multiple modes are ubiquitous in current industrial processes, and the amount of historical
data contained in different modes may vary considerably. Insufficient data can easily lead to …

Abstract The Electro-hydraulic Steer-by-Wire (EH-SBW) is the future trend of commercial
vehicle steering systems due to their dual actuator redundancy. The accurate fault diagnosis …

Process shift of multimode process involving data distribution and dynamic relation makes
traditional transfer learning methods be intractable and even result in negative transfer. To …

Industrial processes are evolving to become larger and more integrated, resulting in
frequent transitions between different operating conditions. When performing fault detection …

In order to meet the increasing demand for food safety and quality, new methods for
simultaneous and rapid determination of multiple food quality parameters (FQPs) are …

Few-sample modes are easy to appear when a new working condition is triggered in
industrial processes especially during the early stages of the new working mode. However …

Aiming to address soft sensing model degradation under changing working conditions, and
to accommodate dynamic, nonlinear, and multimodal data characteristics, this paper …