Diesel engines have a wide range of functions in the industrial and military fields. An urgent
problem to be solved is how to diagnose and identify their faults effectively and timely. In this …

Background The significant nonlinearity between the monitoring variables introduces
challenges in the task of features extraction when implementing fault detection for an …

As scalar neurons of traditional neural networks promote dimension reduction caused by
pooling, it is a difficult task to extract the high-dimensional spatial features and long-term …

To guarantee the safety and reliability of equipment operation, such as liquid rocket engine
(LRE), carrying out system-level anomaly detection (AD) is crucial. However, current …

In the industrial processes, the drift in operation conditions would cause the discrepancy of
data distribution. In this study, an unsupervised transfer autoencoder model based on …

In order to bridge the gap between the ideal experimental environment and practical
engineering applications, many fault diagnosis studies have focused on transfer learning …

In this paper, we propose a localization methodology aimed at improving accuracy through
two primary aspects: environment information assisting fusion algorithm and the elaborate …

Electricity consumption forecasting provides a reference basis for electricity scheduling, it
has become a research hotspot in the field of electric power. The fluctuation of electricity …

Abstract Hybrid Electric Power Systems (HEPS) have gained popularity as a more efficient
and eco-friendly alternative. However, with increasing system complexity, fault potential …

On-board gas-path diagnosis is integral to condition-based maintenance, with the false
alarm rate as a primary metric. Engine variations from manufacturing and performance …