The present paper brings together openly available datasets and simulators for testing of
process monitoring and fault diagnosis techniques. Some general characteristics of these …

Deep-neural network-based fault diagnosis methods have been widely used according to
the state of the art. However, a few of them consider the prior knowledge of the system of …

Various faults in the lithium-ion battery system pose a threat to the performance and safety of
the battery. However, early faults are difficult to detect, and false alarms occasionally occur …

The importance of evaluating valve conditions and detecting the onset of possible
malfunctions is recognized as a key issue in control performance monitoring, as they may …

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The series Advances in Industrial Control aims to report and encourage technology transfer
in control engineering. The rapid development of control technology has an impact on all …

In model-based diagnosis, diagnostic system construction is based on a model of the
technical system to be diagnosed. To handle large differential algebraic models and to …

An algorithm is developed for computing which sensors to add to meet a diagnosis
requirement specification concerning fault detectability and fault isolability. The method is …

In the conventional graph convolutional network (GCN)-based fault diagnosis method,
multilayer GCN model is often used for feature extraction. However, the application of …

The battery sensors fault diagnosis is of great importance to guarantee the battery
performance, safety and life as the operations of battery management system (BMS) mainly …