Fault detection method based on ARM-FPGA platform, medium and system

Abstract

The invention requests to protect a fault detection method based on an ARM-FPGA platform, a medium and a system. Firstly, a fault diagnosis model is put forward, modular design is carried out on a data-intensive calculation link in the fault diagnosis process, and under an ARM-FPGA coupling architecture, the parallel operation characteristic of an FPGA is utilized, related links are migrated to an FPGA part based on a high-bandwidth interface to carry out high-speed operation, a diagnosis result is rapidly generated, the response speed is increased, and the diagnosis process efficiency is improved. And secondly, in a data intensive calculation link in a fault diagnosis process, data are efficiently transmitted by adopting different strategies, so that efficient throughput of the FPGA on data streams is realized, and the response speed is improved. And finally, based on the programmable characteristic of the FPGA, a task scheduling algorithm is invented, and real-time dynamic scheduling of logic resources in a programmable logic device is realized, so that waiting time for occupying the FPGA logic resources based on each operation task is reduced, the utilization rate of the logic resources in the FPGA is increased, and the completion time of the total task is prolonged.

Description

technical field [0001] The invention belongs to the technical field of software and hardware collaboration in mechanical fault diagnosis, in particular to a quick response method in the fault diagnosis process based on ARM-FPGA dual-processing coupled heterogeneous platforms. Background technique [0002] Ship propeller shaft system is an important part of ship power plant. The degree of wear and damage of the propeller shaft and its bushings, bearings, and bearing bushes is directly related to whether the ship can sail safely. It is very necessary to understand and master the state of the ship propeller shaft system during operation, determine its overall or partial normal or abnormality, detect faults and their causes early, and be able to predict the development trend of faults. In recent years, the technical level and complexity of the propeller shaft system have been continuously improved. The existing diagnosis and maintenance mode relying on personal experience and sp...

AI Technical Summary

Problems solved by technology

Although some hardware / software scheduling strategies and algorithms already exist, for the intelligent fault diagnosis model of mechanical systems, the effective allocation and scheduling of data computing tasks in the fault diagnosis process has not yet been realized.

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