Inductive wear debris sensor has been widely used in real time machine lubricant oil condition monitoring and fault forecasting. However, the small sensing zone, which is designed for high sensitivity, of the existing sensors leads to low throughput. In order to improve the throughput, a novel multichannel wear debris sensor that is based on phase division multiplexing is presented. By introducing the phase shift circuit into the system, multiple sensing coils could work at different initial phases. Multiple signals of sensing coils could be combined into one output without information loss. Synchronized sampling is used for data recording, and output signals of multiple sensing coils are extracted from the recorded data. A four-channel wear debris sensor system was designed to demonstrate our method. Subsequently, crosstalk analysis, pseudo-dynamic testing and dynamic testing were conducted to check the sensing system. Results show that signals of four sensing coils could be simultaneously detected and the detection limit for ferrous wear debris is 33 μm. Using the presented method, real time wear debris detection in multiple channels could be achieved without increasing the number of excitation source and data acquisition equipment.

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.

Wear debris in lubrication oil provides important information for marine engine condition monitoring and faults diagnosis. Inductive sensors have been widely used to detect wear debris in lubrication oil. To improve the sensitivity, the inductive coil is always connected with a capacitor in parallel to form parallel LC resonance-sensing circuit. A previous study optimized the parallel resonance circuit by adjusting the excitation frequency. However, multiple parameters (namely, excitation signal, signal detection circuits, and signal-processing program, etc.) need to be adjusted accordingly for a series of the testing frequencies. To simplify the optimization, we propose a method based on adjusting the parallel capacitance in this work. The impedance (inductance and internal resistance) of the sensing coil and its variation induced by particles are first measured, which are the necessary parameters for establishing the function relationship between the parallel capacitance and the relative impedance variation. With the function relationship, the relative impedance variation is calculated directly, and the optimal capacitance is located at the highest absolute value of it. The experimental results for the ferrous and nonferrous particles match the calculation results well. Interestingly, the optimal capacitance for the nonferrous particle was larger than that of the ferrous particle. We speculate that the difference is generated due to the increased resistance induced by the eddy current effect.

The inductive detection of wear debris in lubrication oil is an effective method to monitor the machine status. As the wear debris is usually micro scale, a micro inductive sensor is always used to detect them in research papers or high-tech products. However, the improvement of detection sensitivity for micro inductive sensors is still a great challenge, especially for early wear debris of 20 μm or smaller diameter. This paper proposes a novel method to improve the detection sensitivity of a micro inductive sensor. Regarding the magnetic powder surrounding the sensor, the magnetic field in the core of the sensor where the wear debris pass through would be enhanced due to the increased relative permeability. Thus, the inductive signal would be improved and the detection sensitivity would be increased. It is found that the inductive signal would linearly increase with increasing the concentration of the magnetic powder and this enhancement would also be effective for wear debris of different sizes. In addition, the detection limit of the micro inductive sensor used in our experiment could be extended to 11 μm wear debris by the proposed method.

Particle counting serves as a pivotal constituent in diverse analytical domains, encompassing a broad spectrum of entities, ranging from blood cells and bacteria to viruses, droplets, bubbles, wear debris, and magnetic beads. Recent epochs have witnessed remarkable progressions in microfluidic chip technology, culminating in the proliferation and maturation of microfluidic chip-based particle counting methodologies. This paper undertakes a taxonomical elucidation of microfluidic chip-based particle counters based on the physical parameters they detect. These particle counters are classified into three categories: optical-based counters, electrical-based particle counters, and other counters. Within each category, subcategories are established to consider structural differences. Each type of counter is described not only in terms of its working principle but also the methods employed to enhance sensitivity and throughput. Additionally, an analysis of future trends related to each counter type is provided.