Frequency self-tracing dimension-variation stochastic resonance fault diagnosis system

Abstract

It is frequency self-tracing vary dimension random resonance diagnose system and relates to frequency self-tracing and vary dimension random resonance technique, which is composed of frequency measurement device, sensor, A / D transition card, bistability circuit, D / A transition card, PFT frequency spectrum analyzer, vary-dimension adjustor and signal recovery device. The fifty times of the frequency got by the frequency measurement device serves as sample frequency and it gets signals from the sensor and input it into the vary-dimension random resonance system. The vary-dimension adjustor calculates the data plug delay to make the bistability to generate random resonance. The signal recovers device delays and recoveries the resonance signals and output them to the PFT frequency spectrum analyzer for spectrum characteristic analysis. This invention improves the diagnose accuracy and ensures the safe operation of the device.

Description

technical field [0001] The invention belongs to a detection technology and an automatic device, in particular to a detection technology of frequency self-tracking and variable-scale stochastic resonance. technical background [0002] Stochastic resonance technology originated in the early 1980s. It has unique advantages in signal processing enhancement amplification and detection and identification. It has been widely used in physics, chemistry, biology, celestial bodies, life and other disciplines. In recent years, stochastic resonance technology has also attracted widespread attention in engineering fields such as machinery, electronics, and information, and has begun to be applied to engineering aspects such as fault diagnosis, image processing, and target tracking. Since the stochastic resonance theory studies small parameter signals, that is, the amplitude and frequency of the signal and the intensity of the noise are small parameters, so wh...

AI Technical Summary

Problems solved by technology

Since the stochastic resonance theory studies small parameter signals, that is, the amplitude and frequency of the signal and the intensity of the noise are small parameters, so when facing engineering signals with large parameters, such as large-intensity noise or high-frequency signals, small The stochastic resonance theory of parameters will fail to be usable

Especially in the prediction and diagnosis of mechanical faults, there is no ready-made diagnostic system that can use this technology to realize early fault prediction, and it is still far from the actual engineering application goals.

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