A Massively Parallel Approach to Real-Time Bearing Fault Detection Using Sub-Band Analysis on an FPGA-Based Multicore System

The fact that rolling element bearing faults have an amplitude-modulating effect on their characteristic frequencies calls for sub-band analysis to determine an optimal sub-band signal that contains intrinsic information about bearing faults. In this regard, it is significant to accurately assess the presence of a bearing's abnormal symptoms. Hence, a bearing abnormality index (BAI) that properly quantifies how much information a sub-band signal contains about bearing faults is presented. Additionally, to facilitate real-time sub-band analysis based on the BAI, a massively parallel approach is introduced, where the approach involves the use of the multicore system. Likewise, the multicore system supports high-performance computing by exploiting 128 processing elements operating at 200 MHz in a Xilinx Virtex-7 field-programmable gate array (FPGA) device.