Non-ferrous Particles Research Articles

A novel formula for calculating repulsive forces in horizontally aligned nonferrous cylindrical particles within an Eddy current separator

Eddy Current Separation (ECS) stands as a highly efficient recycling technology crucial for separating nonferrous particles from waste electrical and electronic equipment (WEEE). This process relies on repulsive forces induced by eddy currents as particles traverse the variable magnetic field of a rotating magnetic drum. Achieving optimal separation in this multifaceted process demands a careful selection of magnetic drum parameters. This study focuses on modeling the repulsive forces acting on diverse nonferrous particle shapes, with a particular emphasis on horizontally oriented cylindrical particles, and exploring their trajectories under various adjustable parameters. The effectiveness of the separator is intimately governed by these repellent magnetic forces. Our numerical model comprehensively accounts for the key magnetic and mechanical forces shaping particle movement. Through a dedicated Matlab program, simulations of trajectories are conducted, dissecting the influence of parameters such as separation angle, number of poles, electromagnetic drum velocity, and particle sizes. The findings, elucidated in detailed diagrams, offer a profound understanding of each parameter's impact, crucial for optimizing ECS processes.

RECOVERY OF NON-FERROUS PARTICLES FROM RECYCLING NEON LAMPS BY MAGNETIC INDUCTION SEPARATOR

The use of lamps worldwide is rapidly increasing, and the number of broken, burned-out, and defective lamps is very significant, polluting the environment. For this reason, we will address the topic of lamp recycling using magnetic induction technology. This paper presents induction separation by an innovative, improved induction separator design with an important advantage. It extracts aluminum particles from a mixture of waste materials, including non-metallic and non-ferrous particles from broken neon lamps. The induction separator features a single vertical disk rotated by an electric motor. The disk has a series of permanent magnets mounted alternately on its surface. The experimental results of the separation process achieved through an induction separator exhibit a high purity level, boasting a 100% separation efficiency, surpassing the performance of previous separators. These findings substantiate the validity of employing the induction separator to recycle conductive materials.

A novel TMR sensor based on digital lock-in amplifier technology for portable oil multipollutant detection system

Metal particles identification in lubrication oil has become a popular technology to perform the fault diagnosis and health monitoring of machinery equipment. Unfortunately, the magnetic signals induced by particles are generally weak or even submerged in heavy noise. The sensitivity of conventional inductive sensors for detecting non-ferrous particles can still be improved to better distinguish between different non-ferrous particles. Based on the above issues, this paper proposed a novel tunnel magnetoresistance (TMR) sensor based on digital lock-in amplifier (DLIA) technology to detect ferrous and multiple nonferrous metallic particles in oil under noisy conditions. Moreover, compared to conventional inductive sensor structures, the proposed method can effectively reduce the sensor volume, which is particularly necessary when considering the design of portable oil multipollutant detection system. Owing to the high resolution of TMR and outstanding versatility of DLIA for extracting weak signal overwhelmed in noise, the detection sensitivity can be improved tremendously. Extensive simulation and experimental results validated that the proposed approach was practical and effective. Based on the experimental results, the minimum values of detectable diameter could be computed as 24.76 µm for iron particles, 81.34 µm and 82.32 µm for copper and aluminium particles respectively.

Two-Stage Leaching of PCBs Using Sulfuric and Nitric Acid with the Addition of Hydrogen Peroxide and Ozone.

The paper presents the possibility of recovering metals from printed circuit boards (PCBs) of spent mobile phones using the hydrometallurgical method. Two-stage leaching of Cu(II), Fe(III), Sn(IV), Zn(II), Ni(II) and Pb(II) with H2SO4 (2 and 5 M) and HNO3 (2 M) with the addition of H2O2 (10 and 30%) and O3 (9 or 15 g/h) was conducted at various process conditions (temperature-313, 333 and 353 K, time-60, 120, 240, 300 min, type and concentration of leaching agent, type and concentration of oxidant, solid-liquid ratio (S/L)), allowing for a high or total metals leaching rate. The use of two leaching stages allows for the preservation of selectivity, separation and recovery of metals: in the first stage of Fe(III), Sn(IV) and in the second stage of the remaining tested metal ions, i.e., Cu(II), Zn(II), Ni(II) and Pb(II). Removing Fe from the tested PCBs' material at the beginning of the process eliminates the need to use magnetic methods, the purpose of which is to separate magnetic metal particles (ferrous) from non-magnetic (non-ferrous) particles; these procedures involve high operating costs. Since the leaching of Cu(II) ions with sulfuric(VI) acid practically does not occur (less than 1%), this allows for almost complete transfer of these ions into the solution in the second stage of leaching. Moreover, to speed up the process and not generate too many waste solutions, oxidants in the form of hydrogen peroxide and ozone were used. The best degree of leaching of all tested metal ions was obtained when 2 M sulfuric(VI) acid at 353 K was used in the 1st research stage, and 2 M nitric(V) acid and 9 g/h O3 at 298 K in the 2nd stage of leaching, which allowed it to be totally leached 100% of Fe(III), Cu(II), Sn(IV), Zn(II), Ni(II) and 90% Pb(II).

BesNet: binocular ferrographic image recognition model based on deep learning technology

PurposeUsing computer technology to realize ferrographic intelligent fault diagnosis technology is fundamental research to inspect the operation of mechanical equipment. This study aims to effectively improve the technology of deep learning technology in the field of ferrographic image recognition.Design/methodology/approachThis paper proposes a binocular image classification model to solve ferrographic image classification problems.FindingsThis paper creatively proposes a binocular model (BesNet model). The model presents a more extreme situation. On the one hand, the model is almost unable to identify cutting wear particles. On the other hand, the model can achieve 100% accuracy in identifying Chunky and Nonferrous wear particles. The BesNet model is a bionic model of the human eye, and the used training image is a specially processed parallax image. After combining the MCECNN model, it is changed to BMECNN model, and its classification accuracy has reached the highest level in the industry.Originality/valueThe work presented in this thesis is original, except as acknowledged in the text. The material has not been submitted, either in whole or in part, for a degree at this or any other university. The BesNet model developed in this article is a brand new system for ferrographic image recognition. The BesNet model adopts a method of imitating the eyes to view ferrography images, and its image processing method is also unique. After combining the MCECNN model, it is changed to BMECNN model, and its classification accuracy has reached the highest level in the industry.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0150/

The Optimization of Parallel Resonance Circuit for Wear Debris Detection by Adjusting Capacitance

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.

Effects of material temperature on the separation efficiency in a rotary-drum type eddy current separator

Improving the separation efficiency of eddy current separator is of great significance in solid waste recycling. In this study, a three-dimensional transient simulation model of eddy current separator was established based on the finite element analysis. The effects of material temperature on the separation were investigated by combining simulations and separation experiments. New concepts, such as separation index and direction angle, were proposed to clarify the related mechanism. It was found that reducing the material temperature can increase the Lorentz force on conductive non-ferrous particles, so the residual temperature after cryogenic crushing can be used to improve the separation between conductive non-ferrous and non-conductive materials. Reducing the material temperature will also increase the fluctuation of the Lorentz force, which negatively affects the separation between different non-ferrous metals. The results revealed that different optimization indexes should be set for different mixtures in the design and optimization of the eddy current separator.

Eddy current separation can be used in separation of non-ferrous particles from crushed waste printed circuit boards

Waste printed circuit boards are produced greatly due to the wide application of electronic devices, in which non-ferrous metals are valuable resources. Without effective recovery processes, it can cause serious heavy metal pollution. Traditional recover technologies will cost too much energy, materials, manpower together with producing secondary ecological and environmental pollution. Eddy current separation is a green and low-cost technology to separate non-ferrous metals from others. However, it was well reported that there was a certain particle size limitation for the separated non-ferrous metals. Was it a truth or unbreakable principle for eddy current separation? In this paper, we researched the causes of the size limitation for eddy current separation. Meanwhile, the eddy current separation mechanism was detailed explained in a new comprehension related to the change of magnetic flux density, generation of eddy current force and particles’ motor behaviors. We consider that there is no size limitation for the separated non-ferrous metals in eddy current separation as long as the size of magnetic pole is enough big or small. This paper brings a new recognition about the traditional eddy current separation and will expand new application area for this environment-friendly and low-cost technology.

A Method for Measurement of Nonferrous Particles Sizes in Lubricant Oil Independent of Materials Using Inductive Sensor

Machine operating conditions can be obtained through lubrication oil detection; solid metal particles are the primary factor causing mechanical wear. The surface of the friction pair is usually specially treated with the nonferrous metal protective coating. Therefore, there are many kinds of nonferrous particles in the lubricating oil. In this paper, a method for measurement of nonferrous particles sizes independent of materials using the impedance signal of the inductive sensor is presented. Both the imaginary part and real part of the coil impedance signal are studied in this paper, which is different from traditional inductive sensor research only the imaginary part of impedance signal output is considered. Through theoretical analysis, it is found that the real and imaginary parts of coil impedance changes with different materials at the same size are corresponding to an elliptic function. Combining with the coil impedance measured in the experiment, the particle size can be obtained, which is independent of particle material.

Ultrasensitive Inductive Debris Sensor With a Two-Stage Autoasymmetrical Compensation Circuit

Inductive oil debris sensors have been widely used in the health monitoring of mechanical equipment. Such sensors are important for fault diagnosis, life prediction, and prevention of catastrophic failures. In this article, the concept that the residual voltage caused by the asymmetry of two incentive coils hinders the improvement of the sensor resolution is theoretically demonstrated for the first time. In order to achieve ultrasensitive detection, a novel two-stage autoasymmetrical compensation circuit (AACC) is introduced into the triple-coil debris sensor to automatically suppress the residual voltage in real time. The experimental results show the successful detection of 70 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> m (diameter or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</i> ) ferrous particles and 165 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> m ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</i> ) nonferrous particles in a sensing channel with a diameter of 43 mm. The AACC is verified effectively to maintain the residual voltage at an ultrasmall value even in the presence of environmental fluctuations, and the sensitivity of the sensor using AACC is more than 31 times that of the sensor without AACC.

Comparison of the experimental and numerical analyses of silver nanofluid under influence of strong magnetic field

Purpose Nanofluids’ properties made them interesting for various areas like engineering, medicine or cosmetology. Discussed here, research pertains to specific problem of heat transfer enhancement with application of the magnetic field. The main idea was to transfer high heat rates with utilization of nanofluids including metallic non-ferrous particles. The expectation was based on changed nanofluid properties. However, the results of experimental analysis did not meet it. The heat transfer effect was smaller than in the case of base fluid. The only way to understand the process was to involve the computational fluid dynamics, which could help to clarify this issue. The purpose of this research is deep understanding of the external magnetic field effect on the nanofluids heat transfer. Design/methodology/approach In presented experimental and numerical studies, the water and silver nanofluids were considered. From the numerical point of view, three approaches to model the nanofluid in the strong magnetic field were used: single-phase Euler, Euler–Euler and Euler–Lagrange. In two-phase approach, the momentum transfer equations for individual phases were coupled through the interphase momentum transfer term expressing the volume force exerted by one phase on the second one. Findings Therefore, the results of numerical simulation predicted decrease of convection heat transfer for nanofluid with respect to pure water, which agreed with the experimental results. The experimental and numerical results are in good agreement with each other, which confirms the right choice of two-phase approach in analysis of nanofluid thermo-magnetic convection. Originality/value The Euler–Lagrange exhibit the best matching with the experimental results.

Simulation of Eddy Current and Repulsive Force of Non-Ferrous Particles in Eddy Current Separator

Simulation of Eddy Current and Repulsive Force of Non-Ferrous Particles in Eddy Current Separator

Triple-Coil Inductive Debris Sensor with Special Shielded Coils for Depressing Interference of Dielectric Components

Dielectric contents, such as air bubbles and water droplets in the lubricating oil, can severely interfere with the performance of inductive debris sensor due to the effect of coil parasitic capacitance. This study proposes a special mesh screen that can effectively eliminate the interference to a triple-coil inductive sensor to avoid false alarms and increase productivity. Experimental results show that the sensor can detect 353 μm (D) ferrous particles and 706 μm (D) nonferrous particles in a pipe with a diameter of 50 mm. Comparison experiments indicate that a water droplet with a volume of 697 mm3 can generate an interference signal equivalent to that of a ferrous particle with a diameter of 560 μm for the sensor without screen, while no interference is generated for the sensor with the screen.

A highly sensitive triple-coil inductive debris sensor based on an effective unbalance compensation circuit

Wear particles in the lubrication oil of machinery contain a considerable amount of information about the level of wear in the machinery components, which can provide very early warnings of faults. Inductive debris sensors play an important role in online oil debris detecting techniques. A large unbalance voltage in the sensing coil induced by the asymmetry of two excitation coils harms the performance of a triple-coil inductive debris sensor. This work proposes an effective signal processing system which contributes to the establishment of a high-performance triple-coil inductive debris sensor. Several experiments are conducted to test the sensor’s detection performance. The results show that the sensor is sensitive, and can effectively detect 134 µm (D) ferrous particles and 230 µm (D) nonferrous particles in a sensing channel with an inner diameter of 43 mm.

Detection of foreign particles in lubrication oil with a microfluidic chip

PurposeThe purpose of this paper is to help understand the mathematical model of inductive sensor and to improve the sensitivity of nonferrous metal particle detection.Design/methodology/approachThe expression of impedance change is established, while the distribution regularities of the magnetic field inside and outside the metal particle are obtained based on the Maxwell equations in complex forms, the analytic solution of the electromagnetic field is obtained and the experiment validation is implemented.FindingsThe expression of impedance and the analytic solution of the electromagnetic field are obtained. It is shown that the inductance change is more obvious than resistance change for the iron particles, but for copper particles, resistance change is more obvious and the resistance change increases with the frequency. In this work, copper particles (size: 20 µm) are detected at 2 MHz excitation frequency, and the imaginary part of impedance changes without adding any device, which is provided with a prominent guideline for detection of nonferrous particles of size less than 100 µm.Originality/valueThe expression of impedance change is established, the analytic solution of the electromagnetic field is obtained and copper particles (size: 20 µm) are detected at 2 MHz excitation frequency, and the imaginary part of impedance change without adding any device, which is provided with a prominent guideline for detection of nonferrous particles of size less than 100 µm.

Inductive debris sensor using one energizing coil with multiple sensing coils for sensitivity improvement and high throughput

Abstract Inductive oil debris monitoring has been widely used in the prognosis of machinery faults. This work proposes a new structure of inductive debris sensor that provides sensitive debris-sensing capability. This structure, which includes multiple sensing coils inside an energizing coil, considerably differs from traditional structures. Theoretical analysis shows that the proposed structure can significantly improve sensitivity. The sensor with two semicircular sensing coils is preliminarily designed and tested. The performance of the sensor is evaluated using a simple and efficient test platform. Experimental results show that the designed sensor can identify 120 μm (D) ferrous particles and 210 μm (D) non-ferrous particles in a pipe with an inner diameter of 34 mm.

Online condition monitoring of misaligned meshing gears using wear debris and oil quality sensors

PurposeThis paper aims to investigate the effect of misalignment on wear of spur gears and on oil degradation using online sensors.Design/methodology/approachThe misalignment effect on gears is created through a self-alignment bearing, and is measured using laser alignment system. Several online sensors such as Fe-concentration sensor, moisture sensor, oil condition sensor, oil temperature sensor and metallic particle sensor are installed in the gear test rig to monitor lubricant quality and wear debris in real time to assess gearbox failure.FindingsOffset and angular misalignments are detected in both vertical and horizontal planes. The failure of misaligned gear is observed at both the ends and on both the surfaces of the gear teeth. Larger-size ferrous and non-ferrous particles are traced by metallic particle sensor due to gear and seal wear caused by misalignment. Scanning electron microscope (SEM) images examine chuck, spherical and flat platelet particles, and confirm the presence of fatigue (pitting) and adhesion (scuffing) wear mechanism. Energy-dispersive X-ray spectroscopy analysis of SEM particles traces carbon (C) and iron (Fe) elements due to gear failure.Originality/valueGear misalignment is one of the major causes of gearbox failure and the lubricant analysis is as important as wear debris analysis. A reliable online gearbox condition monitoring system is developed by integrating wear and oil analyses for misaligned spur gear pair in contact.

Determination of Oil Change Interval for Gasoline Engines According to the Amount of Non-Ferrous Metals

Friction is closely related to every moving machine and fundamentally affects efficiency and service life. Wear tracking of moving and non-moving parts of the engine mechanism is important for expressing the wear trend. The wear and tear trend is specific for gasoline engines in urban traffic. The increase in the number of abrasive non-ferrous particles (Al, Cu, Ni, Cr, Sn, Si) is monitored in Ĺ koda Octavia vehicles. The statistical evaluation of nomogram the wear and the determination of the optimum oil change interval of a vehicle group with sparkignition engines are performed for individual non-ferrous particles. The main aim of the article is to propose and verify the method of determination of the optimal oil change interval using Atomic Absorption Spectroscopy, Thin Layer Chromatography and using limit values of discriminatory analysis. On the basis of the results of the analyses, it is clear that the oil change interval by the manufacturer is inadequate and the oil level must be monitored.

Performance Determination of Novel Design Eddy Current Separator for Recycling of Non-Ferrous Metal Particles

Improvements were made in the study for the design of the conventional Eddy Current Separator (ECS) used for separating small sized non-ferrous particles in the waste. These improvements include decreasing the air gap between the material and magnetic drum, making the drum position adjustable and placing the splitter closer to the drum. Thus, small particles were separated with high efficiency. The magnetic drum was removed from inside the ECS conveyor belt system as design change and was placed as a separate unit. Hence, the force generated on the test material increased by about 5.5 times while the air gap between the non-ferrous materials and drum decreased from 3 mm to 1 mm. The non-metal material in the waste is separated before the drum in the novel design. Whereas non-ferrous metal particles are separated by falling into the splitter as a result of the force generated as soon as the particles fall on the drum. Every material that passes through the drum can be recycled as a result of moving the splitter closer to the contact point of the drum. In addition, the drum can also be used for the efficient separation of large particles since its position can be adjusted according to the size of the waste material. The performance of the novel design ECS was verified via analytical approaches, finite element analysis (FEA) and experimental studies.

An online debris sensor system with vibration resistance for lubrication analysis.

The health condition of the lubricated systems can be directly indicated by the concentration and material type of the abrasive particles, which may provide very early warnings of faults/failures and benefit the condition based maintenance. Oil debris particle detecting techniques are thus important for machinery condition monitoring and fault diagnosis. This work proposes a new structure of online debris sensor (ODS), which applies the radial magnetic field, different from the traditional axial magnetic field. The designed ODS can effectively reduce the interferences of the background noise and the vibration of the machine in operation. Moreover, in order to optimally determine the number of turns of an inductive coil and the current of the drive coils, two methods are developed respectively in this work which can ensure sensitivity and anti-vibration features of the ODS. The instrumentation circuit system for detecting debris particles and sensing signals has been also designed to extract and to record the signatures of particles. The designed ODS device is then applied to analyze micro debris particles in the lubricating system on a test rig. Experimental results have demonstrated that ODS can successfully detect the 120 μm(H) ferrous particles and 500 μm(H) non-ferrous particles under vibration conditions.