Optimization of Online induction Sensor for Ferrous Metals Particles Identification in Engine Oil

Engine oil is one of most important parameters in internal combustion engine that plays effective role in component wear. One of the ways to optimize the performance of the IC engines is online monitoring of wear particle in engine oil. There are different ways to identifying these particles, most of which are offline. Nowadays online oil monitoring sensors are quickly developed. In this study two online inductive sensors have been designed and tested to optimize and compare these sensors. Sensor No. 1 has two triggers and two sensing coils, and sensor No. 2 has two triggers and one sensing coil. After determining the optimal input variables, the sensors were tested. The outputs of each of the sensors were examined and compared. By detecting the best power of detecting each sensors, an optimal sensor with higher sensitivity was determined. Sensor No. 1 has lower pressure drop and sensitivity than sensor number two. In sensor No. 2, the fluid is faster due to the smaller diameter of the duct, which increases the accuracy and sensitivity of this sensor.