Non-ferromagnetic Particles Research Articles

A Finemet-based microfluidic single-coil microsensor for monitoring oil condition

Wear is an unavoidable phenomenon that generates debris particles. i.e., ferromagnetic and non-ferromagnetic particles. If the system's condition is not monitored effectively, wear can lead to the breakdown of the system. Therefore, an inductive-resistance sensor was designed to monitor and detect debris particles. Moreover, Finemet (Fe73.5Si13.5B9Nb3Cu1) was applied to the sensor to improve its sensitivity. A comparison simulation and experiment examined the sensor's performance and Finemet's impact. The study shows that the induction mode has greater sensitivity in detecting ferromagnetic particles, while the resistance mode is more sensitive in detecting non-ferromagnetic particles. This study also demonstrates that the application of Finemet boosts the sensitivity of the sensors in both findings, indicating the significance of Finemet for the sensor's applications.

The Design and Study of a Four-Coil Oil Multi-Pollutant Detection Sensor

The operating environment of large mechanical equipment on ships is extremely harsh. Under such harsh conditions, it is necessary to effectively monitor and assess the health status of machinery and equipment and to take appropriate maintenance measures to ensure the normal operation of the ship and the safety of the lives and property of the crew. However, currently used methods are less effective in detecting non-ferromagnetic abrasive particles and non-metallic contaminants and may not be able to respond to certain emergencies promptly. Therefore, in this paper, a quad-solenoid coil multi-contaminant oil detection sensor is proposed to detect metallic abrasive particles and non-metallic contaminants using the voltage–capacitance dual mode. We provide an analytical expression for the magnetic field strength of the present sensor and develop a corresponding mathematical model. In order to verify its accuracy, we compared the model results with finite element analysis and verified them experimentally. Analysis of the experimental results shows that by switching the detection mode of the sensor, ferromagnetic metal particles, non-ferromagnetic metal particles, and non-metallic contaminants in the oil can be identified according to the different experimental signal curves. The sensor recognizes ferromagnetic particles over 70 μm in diameter, non-ferromagnetic particles over 220 μm in diameter, water droplets over 100–110 μm in diameter, and air bubbles over 180–190 μm in diameter. By comparing the sensor with existing sensors, the sensor can provide accurate information about various pollutants, help maintenance personnel to develop a reasonable maintenance program, and reduce the maintenance cost of ship machinery.

An online wear metal particles monitoring warning sensor based on electromagnetic induction in lubricating oil

The online monitoring of metal particles in lubricating oil plays an important role in equipment fault diagnosis technology. This paper designs an online wear monitoring warning sensor based on the electromagnetic induction of metal particles in lubricating oil. First, different from the traditional three-coil sensing and detection method, the sensor consists of two excitation coils and one detection coil. In addition, the parallel capacitance and detection capacitance parameters are obtained by COMSOL’s scanning frequency, and the best detection capacitance is 7.53 nF. Second, according to the obtained optimal detection parallel capacitance value, the amplitude data of the particle signal, as well as the ferromagnetic particles above 60 µm and the non-ferromagnetic particles above 80 µm, are obtained. Third, according to the principle of three-coil induction, a mapping relationship model was established between the size range of metal wear particles in lubricating oil. Finally, we set up an oil wear particle platform to verify the sensor performance. The ferromagnetic and non-ferromagnetic particles are divided into multiple size ranges, and the peak-to-peak values of the output signal of different-sized wear particles are measured. We developed a prototype sensor and verified the signal consistency and repeatability of the sensor to wear metal particles. In addition, we used the sensor to test a large number of metal particles of different sizes (14 ferromagnetic particle standard samples with particle sizes ranging from 20.64 to 457.59 µm and ten non-ferromagnetic particle standard samples with particle sizes ranging from 40.52 to 348.07 µm). The experimental results show that the sensor can directly achieve monitoring sensitivity for ferromagnetic particles greater than 64.57 µm and non-ferromagnetic (copper) particles greater than 82.83 µm under the 4.2 mm aperture flow channel. The sensor can effectively realize the sensitivity on monitoring of small ferromagnetic particles and non-ferromagnetic particles, and it is particularly sensitive to small non-ferromagnetic particles.

Research on Experimental Bench Testing of Wear Metal Particles in Lubricating Oil Based on Self-Excitation and Self-Induction of Coil

The on-line monitoring of wear metal particles in lubricating oil plays an important role in equipment fault diagnosis technology. According to the principle of electromagnetic induction and the Biot-Savart law, model structure design, coil production, etc., different from traditional multi-coil excitation detection methods and compared to traditional methods that are only sensitive to large particles, this paper designed a self-excitation and self-induction metal particle monitoring sensor in lubricating oil based on LC resonance. At the same time, a sensor experimental bench is built by combining the production of ferromagnetic and non-ferromagnetic metal particle standards. In addition, through experimental verification, the sensor can achieve monitoring sensitivity for ferromagnetic particles greater than 41.28 μm and non-ferromagnetic (copper) particles greater than 61.53 μm under the 4.2 mm aperture flow channel, realizing the sensitivity on monitoring of small wear ferromagnetic particles and wear metal non-ferromagnetic particles, the experiment showed that it is particularly sensitive to small non-ferromagnetic particles. Based on a wide pipeline radius, the accuracy and sensitivity of the designed single-coil sensing system have been demonstrated.

Research on the coupling relationship between metal particles in lubricating oil and inductive coils based on self-excitation single coil

Characterizing the operational wear status of mechanical equipment based on online monitoring of metal particles in lubricating oil plays a significant role in the effect of equipment fault diagnosis technology. According to the theoretical analysis of the electromagnetic induction principle and Biot–Savart’s law, combined with the finite element simulation analysis, systematic study and analysis were conducted on the distribution of magnetic field inside a single inductance coil, the coupling relationship between metal particles in lubricating oil, and the inductance coil. This paper analyzed the effects of four important design parameters that were the excitation frequency, the inside diameter of the coil, the turns number of the coil, and the length of the coil. On magnetic field uniformity and monitoring sensitivity, experiments demonstrated that: the correlation between the uniformity of the magnetic field on the testing surface of the sensor inductance coil and the coil radius and length is the highest, followed by the correlation with the number of coil turns. The correlation with the excitation frequency can be ignored in a negligible manner. In addition, experimental results indicated that if the ratio between the inside diameter of the inductance coil and the length of the coil (R/L) was less than 0.41, the magnetic field uniformity would reach over 91%. Meanwhile, results showed that the sensitivity of the sensor to ferromagnetic and non-ferromagnetic particles increased with the decrease in the coil inner diameter and inductance and increased with the increase in the excitation frequency. There is a specific length that can make the sensor coil monitoring, which is the most sensitive.

Micro-Three-Coil Sensor with Dual Excitation Signals Use Asymmetric Magnetic Fields to Distinguish between Non-Ferrous Metals.

Intelligent operation and maintenance technology for vessels can ensure the safety of the entire system, especially for the development of intelligent and unmanned marine technology. The material properties of metal abrasive particles in oil could demonstrate the wear areas of the marine mechanical system because different components consist of different materials. However, most sensors can only roughly separate metallic contaminants into ferromagnetic and non-ferromagnetic particles but cannot differentiate them in greater detail. A micro-three-coil sensor is designed in this paper; the device applies different excitation signals to two excitation coils to differentiate materials, based on the different effects of different material particles in the asymmetric magnetic field. Therefore, a particle's material can be judged by the shape of the induction electromotive force output signal from the induction coil, while the particle size can be judged by the amplitude of the signal. Experimental results show that the material differentiation of four different types of particles can be achieved, namely, of aluminum, iron, 304 stainless steel, and carbon steel. This newly designed sensor provides a new research prospect for the realization of an inductive detection method to distinguish non-ferrous metals and a reference for the subsequent detection of metal contaminants in oil and other liquids.

Research on the Influence of Coil LC Parallel Resonance on Detection Effect of Inductive Wear Debris Sensor.

The coil structure of the inductive wear debris sensor plays a significant role in the effect of wear debris detection. According to the characteristics of LC parallel resonance, the capacitor and coil are connected in parallel to make sensor coils in the LC parallel resonance state, which is beneficial to improve the ability to detect wear particles. In this paper, the mathematical model of output-induced electromotance of the detection coil is established to analyze the influence of the structure on the detection sensitivity and enhance the sensor’s current rate of change to the disturbance magnetic field, which is essential to resist noise interference. Based on the coherent demodulation principle, the AD630 lock-in amplifier is applied to the test platform to amplify and identify weak signals. In addition, experiments are designed to test the output signals of debris under the condition of different original output voltages of the sensor with a parallel structure. Meanwhile, the near-resonance state of the detection coil with LC parallel circuit is tested by output signal information. Results show that the sensor detection sensitivity will be effectively improved with the LC parallel coil structure. For the sensor structure parameters designed in this paper, the optimal raw output amplification voltage for abrasive particle detection is 4.49 V. The detection performance of ferromagnetic particles and non-ferromagnetic particles is tested under this condition, realizing the detection ability of 103.33 μm ferromagnetic abrasive particles and 320.74 μm non-ferromagnetic abrasive particles.

Monitoring Metal Wear Particles of Friction Pairs in the Oil Systems of Gas Turbine Power Plants

In the example of the aviation gas turbine engine the problem of monitoring metal wear particles of friction pairs in the oil systems of gas turbine power plants is considered. The solution based on using the multi-channel cluster single-coil eddy current sensor (CSCECS) with sensitive elements in the form of single circuits is proposed. The CSCECS provides the detection of ferromagnetic and non-ferromagnetic particles and their ranking by several size groups. The sensor is invariant to the size (inner diameter) of the monitored oil pipeline and has high throughput and identical sensitivity across all channels. Two variants of the hardware structure of the debris continuous monitoring system (DCMS) prototype implementing the proposed approach are suggested. The first variant is intended for engine bench tests and contains the CSCECS with integrated preamplifiers and forced air cooling of the electronic modules. The second variant of the DCMS prototype involves the use of the uncooled sensors without built-in electronics and it focuses on operation in autonomous mode not only in bench tests but also during the engine normal operation. A brief description of the DCMS operational algorithm is given. The algorithm is the same for both hardware versions but differs at the software implementation level. The correctness of the algorithm for the detection and size identification of the wear metal particles was verified during the laboratory experiments with a total duration of 5 h and 30 min. The DCMS prototype was also examined during the full-scale engine bench tests. The experiments indicated that the number, size, and magnetic properties of the particles detected by DCMS generally corresponded to the number, size, and magnetic properties of the particles fixed by the MetalSCAN oil debris monitoring system which was used for verification of the DCMS functional capability. The results were also confirmed through laboratory analysis of the wipe samples on the debris filters. However, unlike the existing approaches, the design of the CSCECS additionally made it possible to evaluate the oil flow features in the pipeline of the engine lubrication system.

Analysis of the Effect of Velocity on the Eddy Current Effect of Metal Particles of Different Materials in Inductive Bridges.

A method for analyzing the influence of velocity changes on metal signals of different materials in oil detection technology is proposed. The flow rate of metal contaminants in the oil will have a certain impact on the sensitivity of the output particle signal in terms of electromagnetic fields and circuits. The detection velocity is not only related to the sensitivity of the output particle signal, but also to the adaptability of high-speed and high-throughput in oil online monitoring. In this paper, based on a high-sensitivity inductive bridge, the eddy current effect of velocity in a time-harmonic magnetic field is theoretically analyzed and experimentally verified, the phenomenon of particle signal variation with velocity for different materials is analyzed and discussed, and finally the effect of velocity on the output signal of the processing circuit is also elaborated and experimentally verified. Experiments show that under the influence of the time-harmonic magnetic field, the increase of the velocity enhances the detection sensitivity of non-ferromagnetic metal particles and weakens the detection sensitivity of non-ferromagnetic particles. Under the influence of the processing circuit, different velocities will produce different signal gains, which will affect the stability of the signal at different velocities.

Research on High Sensitivity Oil Debris Detection Sensor Using High Magnetic Permeability Material and Coil Mutual Inductance.

Metallic contaminants (solid) are generated by friction pair, causing wear of equipment by enters the lubricating system. This poses a great potential threat to the normal operation of such machines. The timely analysis and detection of debris can lead to the avoidance of mechanical failures. Abnormal wear in machinery may produce debris exceeding 10 μm. The traditional inductance detection method has low sensitivity and cannot meet the actual detection requirements. To boost the sensitivity of the inductance sensor, the mutual inductance of coils and the strong magnetic conductivity of permalloy was utilized to design a high sensitivity inductance sensor for the detection of debris in lubricating oil. This design was able to detect 10–15 μm iron particles and 65–70 μm copper particles in the oil. The experimental results illustrate that low-frequency excitation is the best for detecting ferromagnetic particles, while high-frequency excitation has the best effect for detecting non-ferromagnetic particles. This paper demonstrates the significant advantages of coil mutual inductance, and strong magnetic conductivity of permalloy in improving the detection sensitivity of oil debris sensors. This will provide technical support for wear detection in mechanical equipment and fault diagnosis.

Enhancement effect of nonferromagnetic particles on the viscosity of magnetorheological fluid under a dynamic magnetic field

This study aims to investigate the effect of nonferromagnetic particle content on the properties of the magnetorheological fluid (MRF) under a dynamic magnetic field. A magnetic-induced viscosity calculation model under the temperature field was built. The influence on the viscosity of the MRF made in-house was analyzed by adding different proportions of nonferromagnetic particles, such as glass powder. Experiments show that a certain proportion of glass powder can increase the viscosity of the MRF. When the powder content is less than 10%, viscosity increases as the glass powder content increases. Conversely, viscosity decreases as the glass powder content increases when the content is more than 10% but less than 20%. These results indicate that adding micron glass powder to the MRF can increase the magnetic saturation limit of the MRF under the dynamic magnetic field and improve its settlement resistance by 25.6%.When 10% glass powder is added to the MRF containing 60% iron powder, sedimentation resistance increases by 25.6%. When the magnetic field intensity is 640 mT, the viscosity of the MRF increases by 6.6 times.

Inductive-Capacitive Coulter Counting: Detection and Differentiation of Multi-Contaminants in Hydraulic Oil Using a Microfluidic Sensor

A microfluidic sensor based on the inductivecapacitive Coulter counting principle to detect multicontaminants in hydraulic oil is presented. The sensor consists of a silicon steel plate and a planar coil. The silicon steel plate makes the distribution of the magnetic flux more dense and uniform, thereby effectively improving the dection sensitivity. The experimental results show that the low-frequency alternating current should be used to detect ferromagnetic particles, and the high-frequency alternating current should be used to detect non-ferromagnetic particles. In inductance mode, the high-frequency excitation should be selected to identify smaller copper particles for comprehensive accuracy, and 30μm iron particles and 110μm copper particles were detected at 2.0MHz. In capacitance mode, the signal amplitude decreases with frequency, but the signal-tonoise ratio increases first with frequency and then decreases. There is the best capacitancedetection sensitivity at 0.7MHz, and 100μm water droplets and 160μm air bubbles were detected. As the core component of the portable oil detection device, this sensor can be used for health monitoring of mechanical equipment to prevent hydraulic system failure.

High-sensitivity distinguishing and detection method for wear debris in oil of marine machinery

Oil debris distinguishing and detection is to characterize the wear position, rate and degree of mechanical system by detecting the properties, count and size of debris in the oil, which contributes to the health status monitoring and fault diagnosis of marine machinery. To improve the sensitivity of inductive detection method, especially for the detection of non-ferromagnetic particles, a double-wire solenoid coil and an inductance-resistance detection method are presented in the paper. The frequency characteristics of inductance and resistance detection are discussed, which shows that the first method is sensitive to ferromagnetic metal particles, and the second method is sensitive to non-ferromagnetic metal particles. We demonstrated that the double-wire solenoid coil sensor can detect iron particles with diameter of 20 μm onwards and copper particles with diameter of 60 μm onwards with inductance-resistance detection method.

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.

High-Throughput Sensor to Detect Hydraulic Oil Contamination Based on Microfluidics

Based on the microfluidic technology, we designed a high-throughput sensor to detect the hydraulic oil contamination. The sensor has two working modes: inductance detection and capacitance detection. The inductance detection mode can detect ferromagnetic and non-ferromagnetic metal particles in the hydraulic oil. By changing the coil connection to switch to the capacitance detection mode, it can detect water droplets and air bubbles in the hydraulic oil. An annular microchannel is designed to increase the detection flow and to shorten the detection time. A pair of silicon steel sheets are built into the annular microchannel to collect the dispersed magnetic field in the detection area, which improves the accuracy in detecting ferromagnetic and non-ferromagnetic particles. Our experiments showed that the detection sensor is more stable when the plane coils have 20 turns. The magnetic field effect of the silicon steel sheet can improve the detection accuracy in inductance detection. Without the silicon steel sheet, the sensor can detect iron particles as small as 60–70 $\mu \text{m}$ with a signal-to-noise ratio (SNR) of 1.55 and copper particles as small as 150– $160~\mu \text{m}$ with an SNR of 1.35. With the silicon steel sheet, the sensor can detect iron particles as small as 60– $70~\mu \text{m}$ with an SNR of 3.42 and copper particles as small as 150– $160~\mu \text{m}$ with an SNR of 3.10. Capacitance detection can detect the water droplets of size 190– $200~\mu \text{m}$ and air bubbles of size 260– $270~\mu \text{m}$ .

A Novel On-Chip Impedance Sensor for the Detection of Particle Contamination in Hydraulic Oil.

A novel impedance sensor based on a microfluidic chip is presented. The sensor consists of two single-layer coils and a straight micro-channel, and can detect, not only ferromagnetic and non-ferromagnetic particles in oil as an inductive sensor, but also, water droplets and air bubbles in oil as a capacitive sensor. The experiments are carried out at different excitation frequencies, number of coil turns and particle sizes. For the inductance detection, the inductance signals are found to increase with the excitation frequency and the noise is constant; both the inductance signals and the noise increase with the number of coil turns, but because the noise increases at a faster rate than the signal, the signal-to-noise ratio decreases with the number of coil turns. We demonstrate the successful detection of 40 μm iron particles and 110 μm copper particles using the coil with 20 turns at the excitation frequency of 2 MHz. For the capacitance detection, capacitance signals decrease with the excitation frequency and the noise is constant; the capacitance signals decrease with the number of coil turns, while the noise increases, thus, the signal-to-noise ratio decreases with the number of coil turns. We can detect 100 μm water droplets and 180 μm bubbles successfully using the coil with 20 turns at the excitation frequency of 0.3 MHz.

Switchable Opening and Closing of a Liquid Marble via Ultrasonic Levitation

Liquid marbles have promising applications in the field of microreactors, where the opening and closing of their surfaces plays a central role. We have levitated liquid water marbles using an acoustic levitator and, thereby, achieved the manipulation of the particle shell in a controlled manner. Upon increasing the sound intensity, the stable levitated liquid marble changes from a quasi-sphere to a flattened ellipsoid. Interestingly, a cavity on the particle shell can be produced on the polar areas, which can be completely healed when decreasing the sound intensity, allowing it to serve as a microreactor. The integral of the acoustic radiation pressure on the part of the particle surface protruding into air is responsible for particle migration from the center of the liquid marble to the edge. Our results demonstrate that the opening and closing of the liquid marble particle shell can be conveniently achieved via acoustic levitation, opening up a new possibility to manipulate liquid marbles coated with non-ferromagnetic particles.

Determining inductive sensor wear debris limits for rolling contact fatigue of bearings

A relatively recent development for the condition monitoring of oil-wetted machinery has been the in-line full-flow inductive wear debris sensor (hereafter referred to as inductive wear debris sensors). These sensors detect a disturbance to a magnetic field caused by metallic wear debris shed from deteriorating dynamic components that is entrained in the lubricant. Applications for these sensors currently include (but are not limited to) aviation machinery, wind-turbine generators, marine propulsion systems, and locomotives. Inductive wear debris sensors can distinguish between ferromagnetic and nonferromagnetic particles as well as providing size and other related information. One of the primary advantages of this sensor type is that the detectable size range is broad and may be used to track the progress of an incipient failure such as the rolling contact fatigue of a bearing or gear as it occurs. One aspect that has received little attention in the literature is the methodology for determining a suitable limit for a particular application. Limits are a critically important aspect of machinery condition monitoring and need to be established by a robust and reliable method otherwise unnecessary maintenance can occur or an incipient fault may be missed. This paper describes a generic method for determining a physically meaningful debris limit for a deteriorating rolling element bearing when utilizing an inductive wear debris sensor.

Investigation of radiation damage in VVER-440 reactor vessel steels by SANS

The effect of neutron irradiation on the microstructure of VVER-440 type reactor pressure vessel steels was studied by small-angle neutron scattering (SANS). The SANS spectra were fitted by a model of non-ferromagnetic particles in saturated ferromagnetic matrix, which permitted us to evaluate apparent volume fractions (weighted by scattering contrast), size distributions and mean ratio of magnetic to total scattering cross-sections for small ( R<3 nm) irradiation-induced precipitates. Close correlation between the apparent volume fraction of the damaged domains and ductility transition temperature was observed. Differences in the volume fractions obtained from magnetic and nuclear scattering indicated that chemical composition varied with increasing fluence and could be explained by increasing concentrations of solute atoms in the damaged domains. This coarsening effect is also manifested on the size distributions by slight growth of mean domain radius.

Magnetic Alignment at Reduced Field Intensity Due to Decrease of Temperature Observed for Nonferromagnetic Particles Possessing Paramagnetic and Diamagnetic Anisotropy

The reduction of field intensity to achieve magnetic alignment of micron-sized nonferromagnetic particles caused by the variations of various parameters was studied systematically, based on the experimental data obtained for various non ferromagnetic materials. The field intensity where the order parameter reached <m>=0.8, denoted by Bs, was proportional to the square root of temeprature for graphite crystals free of paramagnetic ions. The relationship was consistent with the Langevin theory on magnetic alignment. The majority of inorganic oxides is expected to possess diamagnetic anisotropy, since their origin can be explained quantitatively by assuming a constant anisotropy on the individual bonding orbital composing the material. Bs is expected to decrease with the temperature for these oxides, in the same manner observed for the graphite grains. Experiments on talc and kaolinite particles including paramagnetic ions revealed that Bs was proportional to temperature when the paramagnetic concentration was high, since the paramagnetic anisotropy followed the Curie law.