Fault diagnosis is of significance for ensuring the safe and reliable operation of machinery
equipment. Due to the heavy noise and interference, it is difficult to detect the fault directly …

As one of the most immensely growing renewable energies, the wind power industry also
experiences a high failure rate and operation & maintenance cost. Therefore, the condition …

Wind energy is contributing to more and more portions in the world energy market. However,
one deterrent to even greater investment in wind energy is the considerable failure rate of …

It is inevitable for gear to become damaged, which has a profound effect on the performance
of gear transmission systems. Solving the problem of gear fault detection using artificial …

Wind turbine technology is experiencing rapid growth with respect to size, market share, and
technological design. Operational and maintenance cost directly determine whether the …

Abstract Minimum Entropy Deconvolution (MED) has been applied successfully to rotating
machine fault detection from vibration data, however this method has limitations. A …

Condition-based maintenance via vibration signal processing plays an important role to
reduce unscheduled machine downtime and avoid catastrophic accidents in industrial …

The extraction of periodic impulses, which are the important indicators of rolling bearing
faults, from vibration signals is considerably significance for fault diagnosis. Maximum …

This paper provides a comprehensive survey on the state-of-the-art condition monitoring
and fault diagnostic technologies for wind turbines. The Part II of this survey focuses on the …

In this paper a new deconvolution method is presented for the detection of gear and bearing
faults from vibration data. The proposed maximum correlated Kurtosis deconvolution method …