Device for detecting abnormal vibration of industrial equipment

Abstract

The invention discloses a device for detecting abnormal vibration of industrial equipment. The device comprises the industrial equipment, an Internet of Things node module and an intelligent edge computing platform; and the industrial equipment is connected with the Internet of Things node module, the intelligent edge computing platform is in communication connection with the Internet of Things node module, and the Internet of Things node module detects and analyzes vibration data of the industrial equipment so as to judge whether vibration of the industrial equipment is abnormal or not. The Internet of Things node module comprises an embedded soft core, a neural network and a self-learning algorithm are built in the embedded soft core, and unsupervised online training of the neural network is realized by adopting the self-learning algorithm. Therefore, due to the fact that the neural network and the self-learning algorithm are arranged in the embedded soft core, operation data can be collected online to train the neural network online in an unsupervised mode, and the detection result of the trained neural network is more accurate, so the maintenance requirement of industrial equipment can be predicted to avoid emergency maintenance events, the normal operation time of industrial equipment is maximized, and the industrial production efficiency is improved.

Description

technical field [0001] The invention relates to the field of measurement technology, in particular to an abnormal vibration detection device for industrial equipment, which can be used for operation monitoring of industrial equipment. Background technique [0002] At present, intelligent automation of factory production has received more and more attention, because intelligent automation can not only improve production efficiency, but also reduce or eliminate serious losses caused by equipment shutdown. Imbalances, imperfections, loose fasteners and other anomalies in machinery and equipment often translate into vibrations, resulting in loss of accuracy and safety concerns. If left unattended, in addition to performance and safety issues, there will inevitably be lost productivity if equipment is shut down for repairs. Even small changes in equipment performance, which are often difficult to predict in time, can quickly translate into significant productivity losses. [00...

AI Technical Summary

Problems solved by technology

Imbalances, imperfections, loose fasteners and other anomalies in machinery and equipment often translate into vibrations, resulting in loss of accuracy and safety concerns

If left unattended, in addition to performance and safety issues, there will inevitably be lost productivity if equipment is shut down for repairs

Even small changes in equipment performance, which are often difficult to predict in time, can quickly translate into significant productivity losses

[0003] In order to meet the detection requirements of industrial equipment, most factories currently simply rely on manual inspection by technicians, but at this time the human consumption is huge and the reliability of detection is difficult to guarantee

Some use simple piezoelectric sensors or handheld data acquisition tools for device detection, but there are many limitations

On the one hand, human cooperation is still required. On the other hand, these tools simply collect data and cannot detect abnormalities or predict failures.

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