Inductive Magnetic Nanoparticle Sensor Based on Microfluidic Chip Oil Detection Technology

The wear debris in hydraulic oil or lubricating oil has a wealth of equipment operating information, which is an important basis for large mechanical equipment detection and fault diagnosis. Based on traditional inductive oil detection technology, magnetic nanoparticles are exploited in this paper. A new inductive oil detection sensor is designed based on the characteristics of magnetic nanoparticles. The sensor improves detection sensitivity based on distinguishing between ferromagnetic and non-ferromagnetic wear debris. Magnetic nanoparticles increase the internal magnetic field strength of the solenoid coil and the stability of the internal magnetic field of the solenoid coil. During the experiment, the optimal position of the sensor microchannel was first determined, then the effect of the magnetic nanoparticles on the sensor’s detection was confirmed, and finally the concentration ratio of the mixture was determined. The experimental results show that the inductive oil detection sensor made of magnetic nanoparticle material had a higher detection effect, and the signal-to-noise ratio (SNR) of 20–70 μm ferromagnetic particles was increased by 20%–25%. The detection signal-to-noise ratio (SNR) of 80–130 μm non-ferromagnetic particles was increased by 16%–20%. The application of magnetic nanoparticles is a new method in the field of oil detection, which is of great significance for fault diagnosis and the life prediction of hydraulic systems

Design and Parameter Research of Time-Harmonic Magnetic Field Sensor Based on PDMS in Microfluidic Technology

In order to improve the throughput and sensitivity of the inductive metal micro-abrasive particle detection sensor, this paper uses microfluidic detection technology to design a high-throughput abrasive particle detection sensor based on PDMS (Polydimethylsiloxane). Theoretical modeling analyzes the magnetization of metal abrasive particles in the coil’s time-harmonic magnetic field, and uses COMSOL simulation to calculate the best performance parameters of the sensor. Through the experiment of the control variable method, the corresponding signal value is obtained and the signal-to-noise ratio (SNR) is calculated. The SNR value and error value are calculated, and the SNR is corrected. The detection limit of the sensor is determined to be 10 μm iron particles and 60 μm copper particles. The optimal design parameters of the 3-D solenoid coil and the frequency characteristics of the sensor are obtained. Finally, through high-throughput experiments and analysis, it was found that there was a reasonable error between the actual throughput and the theoretical throughput. The design ideas suggested in this article can not only improve the sample throughput, but also ensure the detection accuracy. This provides a new idea for the development of an inductive on-line detection method of abrasive particle technology

Design and Research of Inductive Oil Pollutant Detection Sensor Based on High Gradient Magnetic Field Structure

An inductive oil pollutant detection sensor based on a high-gradient magnetic field structure is designed in this paper, which is mainly used for online detection and fault analysis of pollutants in hydraulic and lubricating oil systems. The innovation of the sensor is based on the inductance detection method. Permalloy is embedded in the sensing region of the sensor, so that the detection area generates a high gradient magnetic field to enhance the detection accuracy of the sensor. Compared with traditional inductive sensors, the sensor has a significant improvement in detection accuracy, and the addition of permalloy greatly improves the stability of the sensor’s detection unit structure. The article theoretically analyzes the working principle of the sensor, optimizes the design parameters and structure of the sensor through simulation, determines the best permalloy parameters, and establishes an experimental system for verification. Experimental results show that when a piece of permalloy is added to the sensing unit, the signal-to-noise ratio (SNR) of iron particles is increased by more than 20%, and the signal-to-noise ratio of copper particles is increased by more than 70%. When two pieces of permalloy are added, the signal-to-noise ratio for iron particles is increased by more than 70%, and the SNR for copper particles is increased several times. This method raises the lower limit of detection for ferromagnetic metal particles to 20 μm, and the lower limit for detection of non-ferromagnetic metal particles to 80 μm, which is the higher detection accuracy of the planar coil sensors. This paper provides a new and faster online method for pollutant detection in oil, which is of great significance for diagnosing and monitoring the health of oil in mechanical systems