An Improved High-Throughput Imaging Sensor for Macroscale and Microscale Features of Wear Particles in Online Condition MonitoringYang Fang, Yan-yan Nie, Jian-ping Yang, Li-ming Wang, Zhen-guo Zhang

School of Mechanical Engineering, Shandong University

Journal：《IEEE SENSORS JOURNAL》

Abstract：

Sensors that can real-time monitor the wear particles suspended in lubricating oil are of great value in evaluating the health state of various machines (e.g., engines, transmissions). Here we report an on-line imaging sensor with a new structure, operating with magnetic deposition and flowing dispersion methods. A highly divergent magnetic field is generated by the cage electromagnet to collect ferromagnetic particles which will then disperse via the flow field in the disclike channel. Wear particles in the chain- and separated-form are imaged respectively by the imaging module to acquire four debris features (concentration, size distribution, shape, and colour). We demonstrated that the developed sensor offers a low size detection limit (1–10 μm), a broad concentration-sensing range (2–200 ppm), and a high throughput (~100 ml/min). Beyond that, the type and material of wear debris can also be identified in the test, utilising the shape and colour features getting by the sensor. This sensor shows promise for use in monitoring the machine health condition and studying the wear mechanism of surfaces.

The online oil monitoring sensor is widely used in evaluating the health stage of various equipment through analyzing the macroscale (concentration) and microscale feature (size and shape) of wear debris. However, existing sensors face limitations in acquiring those multiple features effectively with high throughput (100 mL/min). In light of this challenge, an imaging sensor is developed to capture both the macroscale and microscale features, which employs a magnetic field to manipulate particle sampling within a fixed period. In the sampling processes, the wear particles were absorbed and dispersed in turn, which was recorded by two complementary metal-oxide-semiconductor (CMOS) cameras to capture images of the macro and micro features, respectively. The optimal parameters of sensor were calibrated by various oil throughput and magnetic currents (100 mL/min and 0.9 A), which showed wide and accurate capability for measurement of particle shapes and size distribution from 10 to 150 µm. Finally, this sensor was tested for a gearbox wear experiment with 4000 min at a high throughput of 100 mL/min. It effectively identified changes across three different health stages, which showed a promising online condition monitoring application with multifeatures of wear debris at high throughput.

Keywords: High throughput; imaging sensor; lubricating oil; online monitoring; wear debris analysis

Download: https://ieeexplore.ieee.org/document/10801188