An Improved Online De-Noising Method for Ultrasonic Echo Signal of Wear Debris in Oil

Abstract

The ultrasonic echo signal of wear debris is influenced by many matters. It causes so much more noise. Therefore, it puts forward an improved online de-noising method for ultrasonic echo signal of wear debris in oil. In the dual-tree complex wavelet transform (DTCWT) field, a method, which combines the new non-linear threshold function with adaptive threshold, utilizes particle swarm optimization (PSO) for optimizing the parameter of non-linear threshold function to get the optimal solution. The result of de-noising method can be evaluated. Experimental results show that the proposed method has obvious effect on signal de-noising.

Improving the Detection Ability of Inductive Micro-Sensor for Non-Ferromagnetic Wear Debris

“…Based on the real-time oil monitoring results, the operators can repair and replace the oil to ensure the safe operation of the equipment and prolong remaining useful life. Over the past decades, oil condition monitoring technology with different detection principles is studied, mainly including ferrographic analysis [ 4 , 5 ], spectroscopy analysis [ 6 , 7 ], acoustic detection [ 8 , 9 ], imaging method [ 10 , 11 ], capacitance detection [ 12 , 13 ], and inductance detection [ 14 , 15 ]. Among the above methods, inductance detection is a non-destructive method based on the principle of electromagnetic induction.…”