Rotating machine equipment vibration detection system based on unsupervised learning

The invention relates to a rotating machine equipment vibration detection system based on unsupervised learning, the system comprises a vibration sensor, a measuring range switching circuit, a signal switching circuit, an analog-to-digital conversion circuit, a microprocessor and a monitoring terminal which are connected in sequence, the microprocessor is wirelessly connected with the monitoring terminal, the vibration sensor collects vibration signals of rotating machine equipment, the measuring range switching circuit selects the measuring range of the vibration sensor, the signal switching circuit selects the types of vibration signals, the types comprise acceleration, speed and displacement, the analog-to-digital conversion circuit converts the vibration signals into voltage signals and inputs the voltage signals into the microprocessor, the microprocessor wirelessly transmits the voltage signal to a monitoring terminal, a trained fault diagnosis model is stored in the monitoring terminal, and the fault d