Analysis of lubricating oil is an effective approach in judging machine's health condition and providing early warning of machine's failure progression. Many studies from both academia and industry have been conducted. This paper presents a comprehensive review of the state-of-the-art online sensors for measuring lubricant properties (e.g. wear debris, water, viscosity, aeration, soot, corrosion, and sulfur content). These online sensors include single oil property sensors based on capacitive, inductive, acoustic, and optical sensing and integrated sensors for measuring multiple oil properties. Advantages and disadvantages of each sensing method, as well as the challenges for future developments, are discussed. Research priorities are defined to address the industry needs of machine health monitoring.

Detection of small metallic wear debris is critical to identify abnormal wear conditions for prognosis of pending machinery failure. In this paper we applied an inductance–capacitance (LC) resonance method to an inductive pulse debris sensor to increase the sensitivity. By adding an external capacitor to the sensing coil of the sensor, a parallel LC resonance circuit is formed that has a unique resonant frequency. At an excitation frequency close to the resonant frequency, impedance change (and thus change in voltage output) of the LC circuit caused by the passage of a debris particle is amplified due to sharp change in impedance at the resonant peak; thus signal-to-noise ratio and sensitivity are significantly improved. Using an optimized measurement circuit, iron particles ranging from 32 to 96 µm and copper particles ranging from 75 to 172 µm were tested. Results showed that the parallel LC resonance method is capable of detecting a 20 µm iron particle and a 55 µm copper particle while detection limits for the non-resonance method are 45 and 125 µm, respectively. In contrast to the non-resonant method, the sensitivity of the resonance method has been significantly improved.

No abstract

A high throughput wear debris sensor consisting of 3×3 sensing channels is presented for real time online lubricant oil conditioning monitoring. Time division multiplexing was applied to the sensing channels formeasuring responses of multiple channelsusing one set of measurement electronics. Crosstalk among the 3×3 sensing channels was eliminated by diodes that are connected in series with each channel.Parallel L-C-Rresonancewas also applied to each sensing coil to increase the sensitivity. Furthermore, a unique synchronized sampling method was used to reduce the date size 50 times.Finally, we demonstrated that the sensor is capable of real time detection of wear debris as small as 50µm in SAE0W-5at a flowrate of 460ml/min; the measured debris concentration is in good agreement with the estimated actual concentration. The design can be extended to a N×N sensor array for an extremely high throughput without sacrificing the sensitivity, and can potentially be used for real time wear debris monitoring for health condition of rotating or reciprocating machineries.

A multiplexed inductive sensor consisting of multiple mini-sized planar spiral coils for detecting multiple tip clearances of rotor blades is presented. The sensor measures the tip clearances by monitoring the inductance changes of planar spiral coils caused by the passage of the rotor blades. A resonance frequency division multiplexing technique and parallel LC resonance measurement were applied to the multiple sensor coils, making it feasible to measure multiple tip clearances using only one set of measurement electronics with high sensitivity and resolution. The results from tests conducted on a bench-top test rig have demonstrated that the sensor is capable of simultaneously measuring multiple tip clearances from 0 to 5 mm with a 10 μm resolution at a high rotary speed up to 80 000 RPM. With its high resolution, high sensitivity and capability of monitoring a large number of tip clearances simultaneously, this sensor can potentially be used for advanced active tip clearance control in turbine machinery.

Several studies have shown that miR‐215‐5p acts as a tumor suppressor in certain cancers, but its role in the progression and metastasis of breast carcinoma remains incompletely understood. Herein, we prove that miR‐215‐5p is substantially down‐expressed in breast carcinoma as compared with nontumor tissue. Up‐regulation of miR‐215‐5p inhibits the aggressive abilities of breast carcinoma cells in vitro. We performed luciferase reporter tests to show that SRY‐Box 9 (Sox9) is the target of miR‐215‐5p; as predicted, Sox9 depletion replicates the suppressive effects of miR‐215‐5p on breast carcinoma cells, and overexpression of Sox9 rescues the effects of miR‐215‐5p on breast cancer cell progression. In addition, a xenograft model assay was used to reveal that miR‐215‐5p inhibits breast cancer cell growth and metastatic potential in vivo. Overall, these results imply that miRNA‐215‐5p suppresses the aggressiveness of breast cancer cells through targeting Sox9.

Detecting wear debris and measuring the increasing number of wear debris in lubrication oil can indicate abnormal machine wear well ahead of machine failure, and thus are indispensable for online machine health monitoring. A portable wear debris sensor with ferrite cores for online monitoring is presented. The sensor detects wear debris by measuring the inductance change of two planar coils wound around a pair of ferrite cores that make the magnetic flux denser and more uniform in the sensing channel, thereby improving the sensitivity of the sensor. Static testing results showed this wear debris sensor is capable of detecting 11 µm and 50 µm ferrous debris in 1 mm and 7 mm diameter fluidic pipes, respectively; such a high sensitivity has not been achieved before. Furthermore, a synchronized sampling method was also applied to reduce the data size and realize real-time data processing. Dynamic testing results demonstrated that the sensor is capable of detecting wear debris in real time with a high throughput of 750 ml min−1; the measured debris concentration is in good agreement with the actual concentration.

One effective approach to detect signs of potential failure of a rotating or reciprocating machine is to examine the conditions of its lubrication oil. Here we present an integrated oil condition sensor for detecting both wear debris and lubricant properties. The integrated sensor consists of miniature multiplexed sensing elements for detection of wear debris and measurements of viscosity and moisture. The oil debris sensing element consists of eight sensing channels to detect wear debris in parallel; the elements for measuring oil viscosity and moisture, based on interdigital electrode sensing, were fabricated using micromachining. The integrated sensor was installed and tested in a laboratory lubricating system. Signal multiplexing was applied to the outputs of the three sensing elements such that responses from all sensing elements were obtained within two measurements, and the signal-to-noise ratio was improved. Testing results show that the integrated sensor is capable of measuring wear debris (>50 µm), moisture (>50 ppm) and viscosity (>12.4 cSt) at a high throughput (200 ml min−1). The device can be potentially used for online health monitoring of rotating machines.