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FPGA Design and Implementation of an Optimized Adaptive Filter for Real Time Extraction of Vibration Signal Related to Bearing Defects

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Self adaptive noise canceller has been successfully used for denoising vibration signal of electrical machine or extracting some of its components. Especially, those related to bearing defects which are crucial for modern maintenance strategy. The high order filter needed for this task requires significant high speed resources. Despite all this, its hardware implementation will reduce both the amount of data to be transmitted and the size of diagnosis applications. This paper investigates the possibility of implementing such filter in Field Programmable Gate Arrays. First, it presents a solution based on an optimized processing unit controlled by a finite state machine. Then, this solution has been improved by paralleling two or three units in order to increase the execution speed, and to meet the needs of the design while providing both chip area and low energy consumption. Finally, the scheduling of this algorithm processes is also presented and timing cost is calculated based on the characteristics and limitations of the hardware. Thus, the different delays are considered in order to ensure real-time processing. The proposed algorithms have been implemented in both fixed and floating point representation.
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Vibration Signatures of Bearing Defect; FPGA Implementation; Parallel Processes; Real Time; Self Adaptive Noise Canceller

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