In order to denoise the raw signal and fuse multiple sources of information for the fault
diagnosis of reciprocating compressor, this paper proposes a novel convolutional deep …

One of the most critical devices in an electrical system is the transformer. It is continuously
under different electrical and mechanical stresses that can produce failures in its …

Empirical wavelet transform (EWT) is a novel adaptive signal decomposition method, whose
main shortcoming is the fact that Fourier segmentation is strongly dependent on the local …

In motor drive system, Bearing fault detection through motor current signal (MCS) analysis
has gained recognition for its cost-effectiveness and non-invasive nature. However, two …

Featured Application The proposed method can be used for monitoring the healthy condition
of civil structures. Abstract Truss-type designs are widely used in civil structures. Despite the …

To solve the problem of fault signals of wind turbine bearings being weak, not easy to
extract, and difficult to identify, this paper proposes a fault diagnosis method for fan bearings …

Abstract Impulse Frequency Response Analysis (IFRA) provides an alternative technique for
detection of mechanical type faults in power transformers among researchers. However, the …

Research on data-driven fault diagnosis methods has received much attention in recent
years. The deep belief network (DBN) is a commonly used deep learning method for fault …

Aiming at the problems of high similarity of T-type inverter open-circuit fault features,
cumbersome manual extraction of fault features, and the inability of one-dimensional …

The authors describe experimental and theoretical analyses of faults of power transformer
winding. Faults were caused by mechanical effect of short-circuit currents. Measurements of …