FPGA-Flux Proprietary System for Online Detection of Outer Race Faults in Bearings

Abstract

[EN] The online faults detection in industrial machinery such as induction motors, or their components (as bearings), continues to be a priority. Most commercial equipment provides general measurements and not a diagnosis. On the other hand, commonly research works focused on faults detection are tested offline or over processors that do not comply with online diagnosis. In this sense, the present work proposes a system based on a proprietary field programmable gate array (FPGA) platform, with several intellectual property cores (IPcores) and tools developed. The FPGA platform together with a stray magnetic flux sensor are used for online detecting faults in the outer race of bearings in induction motors. The parts integrating the monitoring system are the stray magnetic flux triaxial sensor, several developed IPcores, an embedded processor for data processing, and the user in-terface where the diagnosis is visualized. The system performs the fault diagnosis through statistical analysis as follows. At first place, a triaxial sensor measures the stray magnetic flux in the motor surrounding (this flux will vary as symptom of the fault). In second place, an embedded processor into a FPGA-based proprietary board drives developed IPcores for calculating statistical features. In third place, a set of ranges is defined for the statistical features values, and it is used to indicate the condition of the bearing into the motor. Therefore, if the value of a statistical feature belongs to a specific range the system will return a diagnosis: whether the fault is present or not and the damage severity in the outer race. The results demonstrate that the values of the root mean square (RMS) and the kurtosis, extracted from the stray magnetic field from the motor, provide a reliable diagnostic of the analyzed bearing. The results are provided online and displayed to the user through interfaces that have been developed on the FPGA platform such as in a liquid crystal display or through serial communication by a Bluetooth module. The platform is based on a FPGA XC6SLX45 Spartan 6 of Xilinx and the architecture of the modules used are described through hardware description lan-guage. This system aims to be an online tool that can help users of induction motors in the maintenance tasks and for early fault detection related with bearings.