An embedded variable speed bearing fault diagnosis device

Abstract

The invention discloses an embedded variable-rotation-speed bearing fault diagnosis device. The device comprises a signal input module, a rotation speed adjustment module, a core computation module, a core control module and a power supply module. The device is of an FPGA+DSP+ARM structure and is structurally characterized in that an FPGA is adopted in the rotation speed adjustment module, vibration signals collected under a variable-rotation-speed condition are converted into uniform angle sampling results, and therefore the requirement for bearing fault diagnosis under the variable-rotation-speed condition is met; a DSP with a high computation speed and a large number of on-chip peripherals is adopted in the core computation module, and data analysis of the sampling results can be well completed; an ARM serves as the core of the core control module, and data analysis result diagnosis, data analysis result storage, data analysis result man-machine interaction and other functions can be completed with the assistance of peripheral hardware devices like an LCD touch screen; an empirical mode decomposition order spectrum analysis algorithm is adopted in the core computation module, it is the first time that the algorithm has been applied to embedded hardware, and bearing fault diagnosis accuracy and rapidity are improved.

Description

technical field [0001] The invention relates to a bearing fault diagnosis device, in particular to a variable speed bearing fault diagnosis device based on digital signal processing technology and embedded technology. Background technique [0002] As we all know, the failure of rotating machinery caused by bearing failure is not uncommon (for example, in the study of motor reliability co-sponsored by General Electric and IEEE Industrial Application Society, it was found that the problems caused by bearings accounted for more than 40% of the total machine failure). Therefore, the development and research of various bearing fault diagnosis systems corresponding to this has attracted widespread attention from the industry and academia. The traditional bearing fault diagnosis system is based on classical Fourier analysis, which detects and diagnoses faults by performing Fourier transform on the measured signal to obtain characteristic spectra such as amplitude and phase. Due to...

AI Technical Summary

Problems solved by technology

However, the existing bearing fault diagnosis systems generally require constant or near-constant equipment speed, which is not suitable for bearing fault diagnosis under variable speed conditions.

There is currently no public solution to this problem

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