Low-Speed Bearing Fault Diagnosis Based on Permutation and Spectral Entropy Measures

Abstract

<jats:p>Despite its influence on wind energy service life, condition-based maintenance is still challenging to perform. For offshore wind farms, which are placed in harsh and remote environments, damage detection is critically important to schedule maintenance tasks and reduce operation and maintenance costs. One critical component to be monitored on a wind turbine is the pitch bearing, which can operate at low speed and high loads. Classical methods and features for general purpose bearings cannot be applied effectively to wind turbine pitch bearings owing to their specific operating conditions (high loads and non-constant very low speed with changing direction). Thus, damage detection of wind turbine pitch bearings is currently a challenge. In this study, entropy indicators are proposed as an alternative to classical bearing analysis. For this purpose, spectral and permutation entropy are combined to analyze a raw vibration signal from a low-speed bearing in several scenarios. The results indicate that entropy values change according to different types of damage on bearings, and the sensitivity of the entropy types differs among them. The study offers some important insights into the use of entropy indicators for feature extraction and it lays the foundation for future bearing prognosis methods.</jats:p>

Entropy Indicators: An Approach for Low-Speed Bearing Diagnosis

“…The validity of this EI is proven by Sandoval et al [ 74 ], who showed that the values of spectral entropy of the SepEn for healthy bearings are higher than the values obtained from vibration signals of bearings with damage.…”

“…Whereas open data sets are available for regular bearings in different repositories [ 71 , 72 , 73 ], low-speed bearing data are scarce and usually proprietary. In this work, to evaluate the proposed strategy, a dataset of vibration signals from low-speed bearings was obtained via an experimental test rig using thrust ball bearings [ 74 ] ( Figure 2 a). Thus, the specific bearing operating conditions were established according to the literature [ 22 , 75 , 76 ]: (i) The bearings rotated at a very low speed (between 5 and 10 rpm), and (ii) the test rig applied a high force (50 kN) to the bearing.…”

“…In contrast with the previous EIs, the values from SpeEn correspond to each rotation made by the shaft washer. To obtain the value of each rotation, the average of each 10,240 is calculated [ 74 ]. This limits the use of all previous indicators to have only one value per rotation, as SpeEn does.…”

“…The last EI used in this study is spectral entropy of the permutation entropy signal (SepEn). This indicator is defined by Sandoval et al [ 74 ], and it is specifically designed (but not limited to) for low-speed bearings. TheSepEn uses EIs for its process: permutation entropy (PerEn) and pectral 215 entropy (SpeEn).…”

“…TheSepEn uses EIs for its process: permutation entropy (PerEn) and pectral 215 entropy (SpeEn). The steps followed for the computation of SepEn is shown in Figure 6 [ 74 ].…”