Condition monitoring of a wind turbine is important to extend the wind turbine system's reliability and useful life. However, in many cases, to extract feature components becomes challenging and the applicability of information drops down due to the large amount of noise. Stochastic resonance...

Fault diagnosis for wind turbine transmission systems is an important task for reducing their maintenance cost. However, the non-stationary dynamic operating conditions of wind turbines pose a challenge to fault diagnosis for wind turbine transmission systems. In this paper, a novel fault...

With modern data-acquisition equipment and on-line computers used during production, it is now common to monitor several correlated quality characteristics simultaneously in multivariate processes. Multivariate control charts (MCC) are important tools for monitoring multivariate processes. One...

The low delta-T syndrome exists in many large primary–secondary chilled water systems, which results in the degradation of the system overall energy performance. This paper presents a method and a case study on diagnosing the low delta-T problem resulted from the deficit flow that frequently...

In rotating machines, shaft and bearing are the critical components of interest for fault diagnosis. In recent years, the application of machine learning for fault diagnosis is gaining momentum. This paper presents the fault diagnosis of shaft and bearing using support vector machine (SVM). The...

Monoblock centrifugal pumps are widely used in a variety of applications. Defects and malfunctions (faults) of these pumps result in significant economic loss. Therefore, the pumps must be under constant monitoring. When a possible fault is detected, diagnosis is carried out to pinpoint it. In...

Feature selection is critical to maintain high performance of classification-based fault diagnosis with a large feature size. In this paper, we propose a criterion to evaluate features effectiveness by class separability that is defined on cosine similarity in the kernel space of the Gaussian...

As the use of wind power has steadily increased, the importance of a condition monitoring and fault diagnosis system is being emphasized to maximize the availability and reliability of wind turbines. To develop novel algorithms for fault detection and lifespan estimation, a wind turbine...

The commercial viability of PEMFC (proton exchange membrane fuel cell) systems depends on using effective fault diagnosis technologies in PEMFC systems. However, many researchers have experimentally studied PEMFC (proton exchange membrane fuel cell) systems without considering certain fault...

In order to increase the diagnostic accuracy of ground-source heat pump (GSHP) system, especially for multiple-simultaneous faults, the paper proposes a multi-source information fusion based fault diagnosis methodology by using Bayesian network, due to the fact that it is considered to be one of...