ArticleSensors (Basel, Switzerland)2017
Photonic Low Cost Micro-Sensor for in-Line Wear Particle Detection in Flowing Lube Oils.
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Correlative Method for Diagnosing Gas-Turbine Tribological Systems.Sensors (Basel, Switzerland) · 2023Article
- Solid Particle Swarm Measurement in Jet Fuel Based on Mie Scattering Theory and Extinction Method.Sensors (Basel, Switzerland) · 2023Article
- A Novel Method for Detecting Ferromagnetic Wear Debris with High Flow Velocity.Sensors (Basel, Switzerland) · 2022Article
- Comprehensive Improvement of the Sensitivity and Detectability of a Large-Aperture Electromagnetic Wear Particle Detector.Sensors (Basel, Switzerland) · 2019Article
- Segmentation of Online Ferrograph Images with Strong Interference Based on Uniform Discrete Curvelet Transformation.Sensors (Basel, Switzerland) · 2019Article
- A Wear Debris Segmentation Method for Direct Reflection Online Visual Ferrography.Sensors (Basel, Switzerland) · 2019Article
- Magnetic Properties of Ferromagnetic Particles under Alternating Magnetic Fields: Focus on Particle Detection Sensor Applications.Sensors (Basel, Switzerland) · 2018Article
- Low Cost Photonic Sensor for in-Line Oil Quality Monitoring: Methodological Development Process towards Uncertainty Mitigation.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The presence of microscopic particles in suspension in industrial fluids is often an early warning of latent or imminent failures in the equipment or processes where they are being used. This manuscript describes work undertaken to integrate different photonic principles with a micro- mechanical fluidic structure and an embedded processor to develop a fully autonomous wear debris sensor for in-line monitoring of industrial fluids. Lens-less microscopy, stroboscopic illumination, a CMOS imager and embedded machine vision technologies have been merged to develop a sensor solution that is able to detect and quantify the number and size of micrometric particles suspended in a continuous flow of a fluid. A laboratory test-bench has been arranged for setting up the configuration of the optical components targeting a static oil sample and then a sensor prototype has been developed for migrating the measurement principles to real conditions in terms of operating pressure and flow rate of the oil. Imaging performance is quantified using micro calibrated samples, as well as by measuring real used lubricated oils. Sampling a large fluid volume with a decent 2D spatial resolution, this photonic micro sensor offers a powerful tool at very low cost and compacted size for in-line wear debris monitoring.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.