# TKEO-Enhanced Machine Learning for Classification of Bearing Faults in Predictive Maintenance
## 2 Materials and Methods  
### Description of the Data Used  
For this work, we used open-access data provided by Case Western Reserve University (CWRU), suitable for use in developing diagnostic and fault detection systems [14]. Vibration data were gathered using accelerometers securely mounted on the housing via magnetic bases to ensure stability and accurate signal acquisition.  
As shown in the Figure 1, the test bench was composed of a two-horsepower motor positioned on the left, a torque transducer with an integrated encoder located in the center, and a dynamometer placed on the right. Additionally, a control electronics system was employed to regulate the setup, though this is not shown in the illustration.  
The data were collected for normal bearings, single-point drive-end faults, and fan-end faults. The sampling frequency was 12 kHz, except for the drive-end bearings, where it was 48 kHz. The number of samples ranged from 121,991 to 485,643. Motor bearings were intentionally damaged using electro-discharge machining (EDM), with faults introduced at various locations, including the inner raceway, rolling element (ball), and outer raceway. These faults varied in size, ranging from 0.007 inches to 0.040 inches in diameter. After introducing the faults, the bearings were reinstalled in the test motor, and vibration data were collected for motor loads ranging from 0 to 3 horsepower, corresponding to motor speeds between 1797 RPM and 1720 RPM.  
There were 17 types of defects and one normal signal for the different loads (from 0 to 3 HP) related to each rolling defect. The defects for 1 HP load are listed as follows:  
\(\begin{array}{l}\text{BALL }_{-}007\_{-}1\text{: Ball defect (0.007 inch)}\\ \text{BALL }_{-}014\_{-}1\text{: Ball defect (0.014 inch)}\\ \text{BALL }_{-}021\_{-}1\text{: Ball defect (0.021 inch)}\\ \text{BALL }_{-}028\_{-}1\text{: Ball defect (0.028 inch)}\\ \text{IR }_{-}007\_{-}1\text{: Inner raceway defect (0.007 inch)}\\ \text{IR }_{-}014\_{-}1\text{: Inner raceway defect (0.014 inch)}\\ \text{IR }_{-}021\_{-}1\text{: Inner raceway defect (0.021 inch)}\\ \text{IR }_{-}028\_{-}1\text{: Inner raceway defect (0.028 inch)}\\ \text{OR }_{-}007\_{-}3\_{-}1\text{: outer raceway defect (0.007 inch, data collected from 3 o'clock position)}\\ \text{OR }_{-}014\_{-}3\_{-}1\text{: outer raceway defect (0.014 inch, 3 o'clock position)}\\ \text{OR }_{-}021\_{-}3\_{-}1\text{: outer raceway defect (0.021 inch, 3 o'clock position)}\\ \end{array}\)  
Figure 1: Schematic of CWRU Bearing Fault Test Rig. Source: Adapted from CWRU photos [14].  
OR_007\(6\)1: outer raceway defect (0.007 inch, data collected from 6 o'clock position) OR_014\(6\)1: outer raceway defect (0.014 inch, 6 o'clock position) OR_021\(6\)1: outer raceway defect (0.021 inch, 6 o'clock position) OR_007_12_1: outer raceway defect (0.007 inch, data collected from 12 o'clock position) OR_014_12_1: Outer raceway defect (0.014 inch, 12 o'clock position) OR_021_12_1: Outer raceway defect (0.021 inch, 12 o'clock position) Normal 1: Normal In this study, we used the complete CWRU data packet and all 17 types of defects. The data files were prepared in Matlab format and included vibration data from the fan end and drive end, as well as the motor's rotational speed (RPM).