Parallel sensing of metallic wear debris in lubricants using undersampling data processing

Abstract

Online lubricant monitoring requires a debris sensor that can rapidly detect wear debris in a large volume of lubricants. To meet this need, we present a fluidic oil debris sensor using parallel multiple sensing channels for detecting metallic wear debris. Each sensing element is comprised of a two-layer planar coil and a meso-scale fluidic pipe crossing its center. The detection of metallic debris is based on inductive Coulter counting principle. The use of multiple parallel channels allows the sensor to process a large amount of lubricants without sacrificing the detection sensitivity. An undersampling process was performed on the voltage signal across each sensing planar coil to enable rapid measurement of inductance changes caused by the presence of metallic debris in all sensing channels. The testing results using iron and copper particles ranging in size from 75 to 150μm have demonstrated that the device is capable of processing 21ml lubricants per minute while detecting ferrous and nonferrous metallic debris at a high throughput. The crosstalk among the seven channels was analyzed and found to be negligible. A much higher throughput can be reached by using a large number of sensing channels to fulfill the needs for online monitoring of lubrication oils.