1. A Novel Multichannel Inductive Wear Debris Sensor Based on Time Division Multiplexing
- Author
-
Wu Sen, Zhuohang Sui, Zixiao Fan, Yu Kezhen, Xinxiang Pan, Zhijian Liu, Ziyi Yuan, and Yin Yi
- Subjects
Computer science ,Acoustics ,010401 analytical chemistry ,Condition monitoring ,01 natural sciences ,Signal ,Synchronization ,0104 chemical sciences ,Time-division multiplexing ,Electromagnetic coil ,Waveform ,Sensitivity (control systems) ,Electrical and Electronic Engineering ,Instrumentation ,Throughput (business) - Abstract
Inductive wear debris sensor has been proved to be an effective device for lubricant oil condition monitoring and fault diagnosis. However, the narrow internal diameter of current sensing coil, designed for high sensitivity, limits the oil throughput. To improve the throughput without sacrificing the sensitivity, a novel multichannel wear debris detection method based on time division multiplexing is presented in this work. Only one excitation signal is used to excite multiple sensing coils. Then, the signals from multiple sensing coils are combined with a serials of square waves separately, which are self-designed specially. As a result, the peak waveforms are lifted in different timeslots by the high-level voltages in squares waves. After that, the peaks of the signals are cut out and combined into one output signal. Then, we used synchronized sampling method to record the peak values of the output signal. The signals for all sensing channels are finally extracted from the recorded peak values. To validate the feasibility of the proposed method, we designed a ten-channel sensor system using time division multiplexing. Through the pseudo-dynamic and dynamic test, it is proved that the sensor could detect wear debris in different channels simultaneously and independently without sacrificing the sensitivity. In addition, the proposed method has the potential to integrate more channels into one system, which would contribute to high throughput real time lubricant oil detection.
- Published
- 2021