Dynamic abrasive particle image acquisition device based on Raspberry Pi and operation method thereof

Abstract

The invention discloses a dynamic abrasive particle image acquisition device based on Raspberry Pi and an operation method thereof. The device comprises a focusing system, a lubricating oil pipeline system, a light source system and an image acquisition system, wherein the focusing system is used for realizing calibration and focusing of the image acquisition system; the lubricating oil pipeline system is used for providing a flowing pipeline for lubricating oil with abrasive particles; the light source system is used for irradiating the lubricating oil pipeline system so as to realize focusing of the focusing system and camera calibration of the image acquisition system; and the image acquisition system is used for acquiring an abrasive particle image and realizing accurate focusing of the camera on the abrasive particles. The device is based on Raspberry Pi, combines the image acquisition system, can accurately acquire images of abrasive particles with different sizes in a lubricating oil pipeline, remotely transmits the abrasive particle images through a wireless network system supported by the Raspberry Pi, timely judges the abrasion condition of mechanical equipment in time, predicts faults of large rotary mechanical equipment in advance, and greatly reduces the maintenance cost.

Description

Technical field [0001] The invention belongs to the field of aero engine oil monitoring, and relates to a wear particle image monitoring technology, in particular to a Raspberry Pi-based dynamic wear particle image acquisition device and an operation method thereof. Background technique [0002] Oil monitoring is to evaluate the working condition of the machine and predict its failure by analyzing the changes in the performance of the lubricants of the mechanical equipment and the wear particles carried by the oil. Due to various difficulties in the real-time monitoring of oil, most of the current monitoring methods for the wear particles carried by the oil use offline indirect detection methods, such as spectral analysis, magnetic plug inspection, particle counters, etc. These methods cannot be directly observed in real time. The morphology of the abrasive particles, the amount of information detected is small, and the detection results are not accurate enough. Although the ana...

AI Technical Summary

Problems solved by technology

Due to various difficulties in real-time monitoring of oil, most of the current monitoring methods for wear particles carried by oil use off-line indirect detection methods, such as spectral analysis, magnetic plug inspection, particle counter, etc. These methods cannot be directly observed in real time The shape of the abrasive grains, the amount of information detected is small, and the detection results are not accurate enough

Although the ferrography-based analysis technology can see the wear morphology, due to the limitation of the performance of the ferrography instrument itself, the abrasive particles often accumulate or even overlap, and some fine abrasive particles are deposited as deposition chains, so it is impossible to clearly observe each abrasive particle in real time the shape of

In addition, from the perspective of abrasive grain images, since the diameter of abrasive grains is on the micron scale, the commonly used off-line detection tools are microscopes combined with industrial cameras for real-time collection. In addition, PC-based equipment has complex structures, high power consumption, large volume, and high cost. shortcoming

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