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

micromachines

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

Wei Li, Chenzhao Bai, Chengjie Wang, Hongpeng Zhang *, Lebile Ilerioluwa , Xiaotian Wang, Shuang Yu and Guobin Li

School of Marine Engineering, Dalian Maritime University, Dalian 116026, China; [email protected] (W.L.); [email protected] (C.B.); [email protected] (C.W.); [email protected] (L.I.); [email protected] (X.W.); [email protected] (S.Y.); [email protected] (G.L.) * Correspondence: [email protected]

Abstract: 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 Citation: Li, W.; Bai, C.; Wang, C.; Zhang, H.; Ilerioluwa, L.; Wang, X.; of permalloy is added to the sensing unit, the signal-to-noise ratio (SNR) of iron particles is increased Yu, S.; Li, G. Design and Research of by more than 20%, and the signal-to-noise ratio of copper particles is increased by more than 70%. Inductive Oil Pollutant Detection When two pieces of permalloy are added, the signal-to-noise ratio for iron particles is increased by Sensor Based on High Gradient more than 70%, and the SNR for copper particles is increased several times. This method raises the Magnetic Field Structure. lower limit of detection for ferromagnetic metal particles to 20 µm, and the lower limit for detection Micromachines 2021, 12, 638. of non-ferromagnetic metal particles to 80 µm, which is the higher detection accuracy of the planar https://doi.org/10.3390/ coil sensors. This paper provides a new and faster online method for pollutant detection in oil, which mi12060638 is of great significance for diagnosing and monitoring the health of oil in mechanical systems.

Academic Editors: Jie Xu, Ran Zhou Keywords: high-gradient magnetic field; planar coil; inductance detection sensor; oil contami- and Yang Lin nant detection

Received: 28 April 2021 Accepted: 27 May 2021 Published: 30 May 2021 1. Introduction

Publisher’s Note: MDPI stays neutral Condition monitoring and fault diagnosis of machinery are important in modern with regard to jurisdictional claims in industrial contexts. Many crucial industries, including aerospace, offshore platforms, smart published maps and institutional affil- ships, and wind power generation, urgently need faster and more accurate monitoring tech- iations. nology to improve the productivity of their machineries. Online monitoring of machinery health can effectively reduce the need for sudden shutdown of vital machinery which can lead to loss of income, significantly reducing operating costs. Recently, many researchers are looking for methods that can accurately identify the state of machineries, realize re- mote monitoring, and predict inspection and maintenance arrangements in advance [1]. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Although ferrographic analysis, vibration analysis, and thermal imaging technology have This article is an open access article long been applied to wear particle identification and diagnosis, they are affected by factors distributed under the terms and such as equipment and environment, and have great limitations in online wear particle conditions of the Creative Commons monitoring. Lubricating oil analysis technology has become an effective means of early Attribution (CC BY) license (https:// warning about equipment failures, equipment wear, and aging status because oil serves as creativecommons.org/licenses/by/ the “blood” of mechanical equipment [2]. Wear particles and external contaminants do exist 4.0/). in lubricating oil and circulate in the mechanical system together with the oil [3]. Under

Micromachines 2021, 12, 638. https://doi.org/10.3390/mi12060638 https://www.mdpi.com/journal/micromachines Micromachines 2021, 12, 638 2 of 14

normal operating conditions of the system, the size of solid particles is usually 10–20 µm. When the mechanical components are abnormally worn, the abrasive grain size can reach 50–100 µm [4–8] or more, which will affect the normal operation of the equipment. For the identification of metal abrasive contaminants in oil, inductive sensors based on 3-D solenoids and planar coils are commonly used. The inductive wear particle analysis method is less affected by environmental factors, can effectively distinguish ferromagnetic and non-ferromagnetic metals, and it is accepted by the majority of researchers. Based on the 3-D solenoid development technology, Du et al. [9] designed a 3-D solenoid sensor to detect 55 µm iron particles and 100 µm copper particles by using an LCR precision meter. Xiao et al. [10] designed an inductive sensor with a gradient magnetic production structure. This structure uses a large excitation coil to provide a gradient magnetic field. The gradient magnetic field passes through a small crack to form a detection area. This structure can increase the sample flux. Ren et al. [11] designed a three-coil inductive structure. The sensor consists of a detection coil and an excitation coil on both sides of the detection coil. The excitation coil provides the same excitation magnetic field, and the middle coil is responsible for detection. The sensor can detect 130 µm ferromagnetic and 230 µm non-ferromagnetic particles. However, due to the large range of the 3-D solenoid sensing area, when detecting multiple low-sized abrasive particles at the same time, they are likely to be identified as one large abrasive particle, which may cause possible false alarms of machine failures. In order to solve the above-mentioned problems, planar coil sensors have been devel- oped. In the case of the same number of turns, the sensing area of the planar coil is smaller, and the detection accuracy is better than that of a 3-D solenoid. Du et al. [12] designed a resonant high-sensitivity detection unit with two-layer planar coils, which can effectively identify 50 µm iron particles. Zeng et al. [13] designed a double-planar coil structure. Through the connection of two planar coil circuits, it can effectively detect four types of pollutants such as ferromagnetic, non-ferromagnetic particles, water droplets, and bubbles, but the detection accuracy is low. Shi et al. [14] designed a high-gradient magnetic field sensor based on the structure of the double-coil, which improved the detection accuracy of the double-planar coil and was able to identify 30 µm iron particles and 100 µm copper particles. The double-coil structure used in the above detection method mainly uses the mutual inductance generated by the double-coil which is greater than the inductance value of a single coil. However, this method is not stable because the double coils are not completely consistent during the production and installation process, and the mutual inductance value generated is also lower than the theoretical value. In comparison, the single-plane coil has better structural stability, and the production and installation of the sensing unit has less influence on the detection accuracy. Zhang et al. [15] used a single- layer planar coil to design a sensing unit and a detection system, which verified the stability of the single-layer planar coil structure. Ma et al. [16] added an iron core to the inner hole of the single-layer planar coil, and used the high magnetic permeability of the iron core to increase the magnetic field strength of the sensor area, greatly improving the detection accuracy of the single-layer planar coil, allowing it to identify 50 µm ferromagnetic and 130 µm non-ferromagnetic particles. There is still a lot of room for improvement in the detection accuracy of the single-layer planar coil structure. Therefore, this paper proposes a design for a gradient magnetic field structure based on the single-layer planar coil. Embedded high-permeability material- permalloy on both sides of the plane coil. Permalloy is an alloy material with super high magnetic permeability, which is widely used in industry and sensor fields. The design of the new structure can effectively improve the magnetic induction intensity of the detection magnetic field, enhance the detection accuracy of the planar coil structure, and weaken the interference of the external magnetic field, so that the coil magnetic field is concentrated in the detection area. Micromachines 2021, 12, 638 3 of 14

weaken the interference of the external magnetic field, so that the coil magnetic field is Micromachines 2021, 12, 638 3 of 14 concentrated in the detection area.

2. Sensor Design and Manufacturing Process 2. SensorThe overall Design design and Manufacturing of the sensor is Process shown in Figure 1a,c. The microchannel has a di- ameterThe of overall 300 μm, design passing of thethrough sensor the is showninner hole in Figureof the1 planea,c. The coil microchannel and two permalloy has a diameternotches. The of 300 diameterµm, passing of the enameled through the wire inner of the hole coil of is the 100 plane μm, and coil the and number two permalloy of turns notches.is 30. Permalloy The diameter is 8 mm of long, the enameled 2 mm high, wire and of the0.3 mm coil iswide. 100 µItm, is fixed and the on numberboth ends of of turns the iscoil, 30. which Permalloy is tightly is 8 mm attached long, 2in mm parallel high, to and the 0.3 coil. mm The wide. core It detection is ﬁxed on area both of ends the sensor of the coil,is shown which in is Figure tightly 1b. attached The position in parallel of th toe microchannel the coil. The core and detection the permalloy area of notch the sensor param- is showneters will in Figurebe analyzed1b. The in position the following of the microchannelcontent. and the permalloy notch parameters will be analyzed in the following content.

FigureFigure 1.1. Sensor design diagram: (a)) The overall design ofof the sensor; ((b)) sensing unit;unit; ((c)) side view; (d)) fabrication process.process.

The manufacturing processprocess ofof thethe permalloypermalloy isis asas followsfollows (Figure(Figure1 1d).d). The The permalloy permalloy material was firstfirst prepared usingusing a precision grinding wheel cutting machine (TWC50-A, Shen Zhen He Dong Dong Technology Technology Co., Co., Ltd., Ltd., Shen Shen Zhen, Zhen, China) China) to to cut cut out out different different sizes sizes of ofpermalloy. permalloy. It was It was then then placed placed in a in hydrogen a hydrogen furnace furnace (QSXF-2-12, (QSXF-2-12, Hang Hang Zhou Zhou Lan LanTu Pre- Tu Precisioncision Instruments Instruments Co., Co.,Ltd., Ltd., Hang Hang Zhou, Zhou, China) China) for annealing for annealing treatment. treatment. The heat-treated The heat- treatedpermalloy permalloy has a strong has a strong magnetic magnetic permeability. permeability. A precision A precision winding winding machine machine (Shi (Shi Li LiSRDZ23-1B, SRDZ23-1B, Zhong Zhong Shan Shan Shi Shi Li Li Wire Wire Winder Winder Equipment, Equipment, Zhong Zhong Shan, China) was usedused toto windwind thethe planeplane coil,coil, andand fixfix thethe woundwound coilcoil onon thethe correctcorrect positionposition on the silicon plate. The permalloy was then fixed on both sides of the coil, a 7 cm long copper rod with a diameter of 300 µm was used as the mold for making the microchannel, and the mold was inserted into the permalloy slot and the inner hole of the plane coil. After mixing PDMS Micromachines 2021, 12, 638 4 of 14

The permalloy was then fixed on both sides of the coil, a 7 cm long copper rod with a diameter of 300 μm was used as the mold for making the microchannel, and the mold was Micromachines 2021, 12, 638 inserted into the permalloy slot and the inner hole of the plane coil. After mixing PDMS4 of 14 (polydimethylsiloxane) and curing agent 10:1, the model was casted with the mixture, and the copper rod for making the microchannel was drawn out, encapsulated, and the sample inlet(polydimethylsiloxane) and outlet were made. and curing agent 10:1, the model was casted with the mixture, and the copper rod for making the microchannel was drawn out, encapsulated, and the sample 3.inlet Detection and outlet Principle were made. and Simulation Analysis When an alternating current is applied to the coil, Biot–Savart’s law shows that this type3. Detection of coil can Principle be simplified and Simulation as the magnetic Analysis field of a circular current-carrying wire, and the magneticWhen an field alternating on its axis current is shown is applied in Figure to the 2. When coil, Biot–Savart’s point 𝑃 is located law shows at the that center this oftype the of circle, coil canthe bemagnetic simplified induction as the magneticintensity at field the ofcenter a circular of the current-carrying coil is the largest, wire, and andthe distancethe magnetic 𝑟 is the field minimum on its axis circumference is shown in Figure radius2. When𝑅, then point the valueP is locatedof point at 𝑃 the is: center of the circle, the magnetic induction intensity at the center of the coil is the largest, and the μ distance r is the minimum circumference radius 0RI, then the value of point P is: B = (1) µ 2IR , B = 0 , (1) 2R

FigureFigure 2. 2. MagneticMagnetic field field on on the the circul circularar current-carrying current-carrying conductor conductor. For a symmetrical magnetic field, when only oil flows through the microchannel, For a symmetrical magnetic field, when only oil flows through the microchannel, as- assuming that the magnetic permeability in the coil is the vacuum permeability u0, the suming that the magnetic permeability in the coil is the vacuum permeability 𝑢, the mag- magnetic induction intensity is B0, and the relationship between the magnetic field intensity netic induction intensity is 𝐵, and the relationship between the magnetic field intensity H and the magnetic induction intensity B0 is: 𝐻 and the magnetic induction intensity 𝐵 is: BHB0 ==µ0μH, (2) 00, (2) When metal particles pass through this position, an eddy current effect will be gen- When metal particles pass through this position, an eddy current effect will be generated at this position, which reduces the magnetic induction intensity of the original erated at this position, which reduces the magnetic induction intensity of the original mag- magnetic field. Let the reduced magnetic flux density be B1. When a spherical metal netic field. Let the reduced magnetic flux density be 𝐵. When a spherical metal particle particle with a radius of r0 passes through the center of the coil, the magnetic induction with a radius of 𝑟 passes through the center of the coil, the magnetic induction intensity intensity B2 at that position is: 𝐵 at that position is: B2 = µ0µr H, (3) BH= μμ ur is the relative permeability of metal20 particles.r The, relationship between the magnetic(3) flux ∅ and the magnetic induction intensity B is ∅ = BS, where S is the cross-sectional area of the metal particle at this position, and the magnetic flux at this position is:

Φ1 = (B2 − B1)S = µ0µr HS − B1S, (4)

The inductance of the coil L is:

L = Φ/I0, (5) Micromachines 2021, 12, 638 5 of 14

I0 for ferromagnetic particles, the relative permeability is much greater than the eddy current effect produced by vacuum permeability and particles, so when ferromagnetic particles pass through, the inductance of the coil will increase. For non-ferromagnetic metal particles, the relative permeability is approximately equal to the vacuum permeability, so when the non-ferromagnetic metal particles pass by, the inductance of the coil will decrease. It can be seen from Equation (4) that the larger the volume of the particle, the larger the cross-sectional area S at that position, and the greater the inductance change value produced, so the inductance change value is proportional to the volume of the particle. This paper is based on the electromagnetic model of the ﬁnite element software COM- SOL (COMSOL Multiphysics 5.3, COMSOL Inc., Stockholm, Sweden), and the solution variable is magnetic loss A. Without considering the displacement current:

∇ × A = B, (6)

Take the curl of both sides:

∇ × (∇ × A) = ∇ × B, (7)

Using mathematical formulas:

∇(∇·A) − ∇2A = µ∇ × H, (8)

∂A ∇ × H = J = σE = σ − − ∇V , (9) ∂t ∂A 1 ∇2A = σµ − ∇V − (∇µ) × (∇A), (10) ∂t µ The governing equation of the detected part (particle, coil and air between coil and particle) can be obtained from Equation (10). Particle interior: ∂A ∇2A = σµ , (11) ∂t Air part: ∇2A = 0, (12) Coil part: ∇2A = −µJ, (13) After high-frequency alternating current is applied to the coil, the magnetic field inside and outside the particle changes due to the action of magnetization and eddy current, which in turn is captured by the current-carrying coil, thus causing the impedance change of the inductor coil. The following was the process to simulate and analyze the coupling magnetic field of the coil and the permalloy. First, a single piece of permalloy is simulated. The simulation tool selects the electromagnetic field module in the COMSOL software. The finite element simulation parameters are the same as the experimental settings. The number of turns of the coil is 30 turns, the diameter of the enameled wire is 100 µm, and it is connected to 2 V alternating current and 2 MHz frequency. The size of Permalloy is the same as the sensor settings, and the simulation is proportional. As shown in Figure3a, triangular grooves with different angles are designed at the center of Permalloy, the groove depth is 1 mm, and the angles are 45◦, 60◦, 90◦, 120◦, and 150◦. The corresponding simulation result picture is shown in Figure3b–f. When the groove depth is constant, the smaller the opening angle, the greater the magnetic flux density. As shown in Figure3b when the permalloy groove angle is at 45 ◦ the maximum magnetic flux density is 8.38 µT, and the maximum position is near the edge of the coil. As the angle increases, the magnetic flux density gradually decreases. When the angle is 150◦ Micromachines 2021, 12, 638 6 of 14

The following was the process to simulate and analyze the coupling magnetic field of the coil and the permalloy. First, a single piece of permalloy is simulated. The simulation tool selects the electromagnetic field module in the COMSOL software. The finite element simulation parameters are the same as the experimental settings. The number of turns of the coil is 30 turns, the diameter of the enameled wire is 100 μm, and it is connected to 2 V alternating current and 2 MHz frequency. The size of Permalloy is the same as the sensor settings, and the simulation is proportional. As shown in Figure 3a, triangular grooves with different angles are designed at the center of Permalloy, the groove depth is 1 mm, and the angles are 45°, 60°, 90°, 120°, and 150°. The corresponding simulation result picture is shown in Figure 3b–f. When the Micromachines 2021, 12, 638 6 of 14 groove depth is constant, the smaller the opening angle, the greater the magnetic flux density. As shown in Figure 3b when the permalloy groove angle is at 45° the maximum magnetic fluxThe following density was is the8.38 process μT, toand simulate the andmaximum analyze the po couplingsition magnetic is near field the edge of the coil. As the ofangle the coil increases, and the permalloy. the magnetic First, a single flux piece de ofnsity permalloy gradually is simulated. decreases. The simula- When the angle is tion tool selects the electromagnetic field module in the COMSOL software. The finite 150° as elementin Figure simulation 3f, the parameters maximum are the samemagnetic as the experimental flux density settings. is The1.34 number μT, nearof the edge of the coil. Theturns simulation of the coil is result30 turns, curves the diameter of di offferent the enameled angles wire are is 100 shown μm, and in it isFigure con- 4a. nected to 2 V alternating current and 2 MHz frequency. The size of Permalloy is the same as the sensor settings, and the simulation is proportional.

o o o o As shown in Figure 3a, triangular grooves with different angles are designed at the 150 120 90 60 center of Permalloy, the groove depth is 1 mm, and the angles are 45°, 60°, 90°, 120°, and o 45 150°. The corresponding simulation result picture is shown in Figure 3b–f. When the Micromachines 2021, 12, 638 groove depth is constant, the smaller the opening angle, the greater the magnetic6 of flux 14 density. As shown in Figure 3b when the permalloy groove angle is at 45° the maximum magnetic flux density is 8.38 μT, and the maximum position is near the edge of the coil. As the angle increases, the magnetic flux density gradually decreases. When the angle is as150° in Figureas in Figure3f, the 3f, maximum the maximum magnetic magnetic ﬂux density flux density is 1.34 isµ 1.34T, near μT, thenear edge the ofedge the of coil. the (a) Thecoil. simulation The simulation result result curves curves of different of different angles angles are shown are shown in Figure in Figure4a. 4a.

o o o o Frequency: 2MHz 150Magnetic 120 90 flux60 density [μT] 45o (b) (c)

(a)

Frequency: 2MHz Magnetic flux density [μT] (b) (c)

(d) (e) (f)

Figure 3. Comparison of simulation results(d) of permalloy triangle notches:(e) (a) Different permalloy(f) structures; (b–f) Simulation results.

FigureFigure 3. Comparison 3. Comparison of simulation of simulation results of results permalloy of permalloy triangle notches: triangle ( notches:a) Different (a )permalloy Different structures; permalloy (b structures;–f) Simulation (b–f )results. Simulation results.

(a) (b)

Figure 4. Results of different triangular and rectangular notches: (a) Corresponding results in Figure3;( b) Corresponding results in Figure5.

Micromachines 2021, 12, 638 7 of 14

Figure 4. Results of different triangular and rectangular notches: (a) Corresponding results in Figure 3; (b) Corresponding results in Figure 5.

Figure 5 shows the simulation results of the permalloy rectangular groove. The depth of the rectangular groove shown in Figure 5a is 1 mm, and the groove width is 300 μm, 600 μm, 900 μm and 1200 μm. The corresponding simulation result picture is shown in Figure 3b–e. Different from the simulation result of the triangular groove, the magnetic flux density of the permalloy of the rectangular groove structure is much greater than that of the permalloy of the triangular structure after being magnetized. When the width of the rectangle is 300 μm, the maximum magnetic flux density is 14.81 μT; When the width Micromachines 2021, 12, 638of the rectangle is 900 μm, the maximum magnetic flux density is 40.80 μT, which is also 7 of 14 the largest magnetic flux density among all the results. The result curve is shown in Figure 4b.

300μm

1200μm 600μm 900μm

(a)

Frequency: 2MHz Magnetic flux Density: (μT) (b)

Figure 5. ComparisonFigure 5.of simulationComparison results of simulation of permalloy results triangle of permalloynotches: (a) triangle Different notches: permalloy (a) structures; Different permalloy(b–e) Simulation structures; results. (b –e) Simulation results. According to the analysis of the above simulation results, when the rectangular slot width is 900 μFigurem, the5 simulationshows the simulationeffect is the results best, and of the the permalloy maximum rectangular value is at groove.the rectan- The depth gular slotof near the rectangularthe edge of the groove coil, as shown shown in in Figure Figure5a 6a. is When 1 mm, the and edge the of groove the rectangular width is 300 µm, slot is closer600 µ tom, the 900 edgeµm of and the 1200 innerµm. hole The of correspondingthe coil, the magnetized simulation permalloy result picture magnetic is shown in flux is larger,Figure and3b–e. the Different magnetic from field the of simulationthe detection result area ofis thestronger. triangular Therefore, groove, we the con- magnetic tinue to fluxoptimize density the of rectangular the permalloy slot. of As the shown rectangular in Figure groove 6b, structurethe rectangular is much slot greater has a than that width ofof 300 the μ permalloym and a depth of the of triangular 500 μm, and structure it is close after to being the ed magnetized.ge of the inner When hole the of width the of the plane coil.rectangle The related is 300 simulationsµm, the maximum on these magnetic structures flux were density carried is 14.81 out, andµT; Whenthe results the width of are shownthe in rectangle Figure 6c,d. is 900 Inµ them, position the maximum shown magnetic in Figure flux 6b, densitythe maximum is 40.80 magneticµT, which flux is also the density largestis 76.72 magneticμT, and the flux degree density of among increase all in the magnetic results. Theflux result is much curve greater is shown than in the Figure 4b. magnetic fluxAccording density at to the the position analysis in of Figure the above 6a. Therefore, simulation the results, rectangular when thegroove rectangular shown inslot Figure width 6b isis 900selectedµm, as the the simulation best position effect of ispermalloy. the best, Figure and the 6c maximum is the simulation value is at the result correspondingrectangular slot to Figure near the 6b, edge and of Figure the coil, 6d asis the shown result in of Figure two6 permalloysa. When the of edge the of the same specification.rectangular Figure slot is closer6d shows to the that edge a pi ofece the of inner the same hole ofgauge the coil, is added the magnetized on the basis permalloy of a singlemagnetic piece of flux permalloy. is larger, At and this the time, magnetic the magnetic field of flux the detectiondensity inside area the is stronger. coil is also Therefore, doubled.we After continue simulation to optimize analysis, the the rectangular structure slot. in Figure As shown 6d was in Figure chosen6b, since the rectangular it gives slot has a width of 300 µm and a depth of 500 µm, and it is close to the edge of the inner hole of the plane coil. The related simulations on these structures were carried out, and the results are shown in Figure6c,d. In the position shown in Figure6b, the maximum magnetic flux density is 76.72 µT, and the degree of increase in magnetic flux is much greater than the magnetic flux density at the position in Figure6a. Therefore, the rectangular groove shown in Figure6b is selected as the best position of permalloy. Figure6c is the simulation result corresponding to Figure6b, and Figure6d is the result of two permalloys of the same specification. Figure6d shows that a piece of the same gauge is added on the basis of a single piece of permalloy. At this time, the magnetic flux density inside the coil is also doubled. After simulation analysis, the structure in Figure6d was chosen since it gives the optimal result, and the subsequent experimental verification is also based on this conclusion. Micromachines 2021, 12, 638 8 of 14

Micromachines 2021, 12, 638 8 of 14 the optimal result, and the subsequent experimental verification is also based on this conclusion. Micromachines 2021, 12, 638 8 of 14

Microchannel location Maximum magnetic Maximum magnetic flux density the optimalflux result, density and the subsequent experimental verification is also based on this conclusion.

Microchannel location Maximum magnetic Maximum magnetic flux density flux density

(a) (b)

(b) (a) (e)

Frequency: 2MHz(e) Magnetic flux Density: (μT) Frequency: 2MHz Magnetic flux Density: (μT) (c) (d)

(c) (d) Figure 6. PermalloyFigure structure 6. Permalloy with the structure highest with magnetic the highest flux magnetic density: flux (a density:) 1200μ (ma) 1200wideµm rectangular wide rectangular slot, slot,the maximum the maximum magnetic flux magnetic flux density is at the edge of the slot and inner hole of the coil; (b) A rectangular slot with a width of 300µm and density is at theFigure edge 6. Permalloyof the slot structure and inner with holethe high of estthe magnetic coil; (b flux) A density:rectangular (a) 1200 slotμm withwide rectangulara width of slot, 300 thμem maximum and a depth magnetic of 500flux μm, the µ c maximum magneticdensitya depth fluxis at thedensity of 500edgem, of is the theat maximumtheslot edgeand inner magneticof the hole slot of flux the and density coil; inner (b) is A athole rectangular the of edge the of coil;slot the with slot(c) andSimulation a width inner of hole 300 results ofμm the and coil; corresponding a depth ( ) Simulation of 500μm, to the the figure (b); (d) The resultmaximum ofresults two magnetic corresponding pieces flux of Permalloy density to the is figure at inthe (bfigure edge); (d) of The ( theb); result slot(e) andThe of two inner Microchannel pieces hole of of Permalloy the coil; location (c in) Simulation figure in figure (b); (resultse) The(b). Microchannelcorresponding location to the figure (b); (din) The figure result (b). of two pieces of Permalloy in figure (b); (e) The Microchannel location in figure (b). Figure 7 shows the magnetic field distribution in different directions in the sensing Figure 77 showsshows thethe magneticmagnetic fieldfield distributiondistribution inin differentdifferent directionsdirections inin thethe sensingsensing region. Figureregion. Figure 7a is 7the7aa isis horizontal thethe horizontalhorizontal magnet magneticmagneticic fieldfieldfield distribution. distribution.distribution. ComparedCompared Compared withwith V-shapedV-shapedwith V-shaped groove permalloy,groove permalloy,permalloy, the therectangular the rectangular rectangular groove groove groove permalloy pe permalloyrmalloy can can significantlycan significantly significantly enhance enhance enhance the magneticthe mag- the mag- field in the sensing region, and the magnetic field intensity at both ends of the induction netic fieldnetic in field the insensing the sensing region, region, and and the the magnet magneticic field field intensity intensity at both at both ends ofends the in-of the in- region near the coil is the highest. Figure7b is the horizontal magnetic field distribution. duction region near the coil is the highest. Figure 7b is the horizontal magnetic field dis- duction Withregion the increasenear the of coil height, is the magnetic highest. field Figure intensity 7b is gradually the horizontal decreases, magnetic and the effect field distribution. With the increase of height, the magnetic field intensity gradually decreases, tribution.of theWith same the rectangular increase grooveof height, permalloy the magnetic is better than field that intensity of V-groove gradually permalloy decreases, in and the effect of the same rectangular groove permalloy is better than that of V-groove enhancing the magnetic field in the sensing area. and the permalloyeffect of inthe enhancing same rectangular the magnetic fieldgroove in the permalloy sensing area. is better than that of V-groove permalloy in enhancing the magnetic field in the sensing area.

(a) (b)

Figure 7. DistributionDistribution of of magnetic magnetic fields fields in indifferent different directions directions in the in induction the induction area: area:(a) Horizontal (a) Horizontal magnetic magnetic field distri- field bution; (b) Magnetic field distribution in the vertical direction. distribution; (b) Magnetic(a) field distribution in the vertical direction. (b)

4. Experiment and Data Analysis Figure 7. Distribution of magnetic fields in different directions in the induction area: (a) Horizontal magnetic field distri- The experimental system consisted of an impedance analyzer (Keysight E4980A, Ag- bution; (b) Magnetic field distribution in the vertical direction. ilent Technologies Inc., Bayan Lepas, Malaysia), a microscope (Nikon AZ100, Nikon, To- kyo, Japan), a micro-injection pump (Harvard Apparatus B-85259, Harvard Apparatus, 4. Experiment and Data Analysis The experimental system consisted of an impedance analyzer (Keysight E4980A, Ag- ilent Technologies Inc., Bayan Lepas, Malaysia), a microscope (Nikon AZ100, Nikon, To- kyo, Japan), a micro-injection pump (Harvard Apparatus B-85259, Harvard Apparatus,

Micromachines 2021, 12, 638 9 of 14

4. Experiment and Data Analysis Micromachines 2021, 12, 638 9 of 14 The experimental system consisted of an impedance analyzer (Keysight E4980A, Agilent Technologies Inc., Bayan Lepas, Malaysia), a microscope (Nikon AZ100, Nikon, Tokyo, Japan), a micro-injection pump (Harvard Apparatus B-85259, Harvard Appara- tus,Holliston, Holliston, MA, MA,USA), USA), a computer a computer with witha LabVIEW a LabVIEW data acquisition data acquisition unit and unit our and high- our high-gradientgradient magnetic magnetic field sensor. ﬁeld sensor. The iron The particles iron particles and copper and copper particles particles used in used the experi- in the experimentment were werecustomized customized by professional by professional laboratory laboratory equipment equipment manufacturers manufacturers (Beijing(Beijing HuafengHuafeng ExperimentalExperimental MaterialsMaterials Co.,Co., Ltd.,Ltd., Beijing,Beijing, China).China). TheThe testtest benchbench systemsystem isis shownshown inin FigureFigure8 8..

FigureFigure 8.8. Experimental system.system.

BeforeBefore thethe experiment,experiment, thethe mixturemixture ofof oiloil andand metalmetal particlesparticles waswas firstfirst prepared.prepared. IronIron particlesparticles withwith sizes of 20 µμm,m, 3030 µμm,m, 4040 µμm,m, 5050 µμm,m, 6060 µμmm andand 7070 µμmm werewere used.used. AA totaltotal ofof 55 mgmg waswas weighedweighed withwith aa precisionprecision balance,balance, then mixed with 120 mL of hydraulic oil. TheThe mixturemixture waswas placedplaced onon anan ultrasonicultrasonic oscillatoroscillator (IKA(IKA S25,S25, IKAIKA Inc.,Inc., Staufen,Staufen, Germany) andand shakenshaken wellwell forfor 22 min.min. TheThe non-ferromagneticnon-ferromagnetic particlesparticles werewere representedrepresented byby coppercopper particles.particles. Copper particles of 80 μµm, 90 µμm, 100 µμm, 110 µμm,m, 120120 µμmm andand 130130 µμmm werewere prepared,prepared, 6 mg mg was was weighed weighed with with a aprecision precision balance, balance, and and then then mixed mixed with with 120 120mL mLhy- hydraulicdraulic oil. oil. Similar Similar to tothe the iron iron particles, particles, the the mixture mixture of of copper copper particle particle and oil was placedplaced onon anan ultrasonicultrasonic oscillator oscillator and and shaken shaken for for 2 min.2 min. Finally, Finally, samples samples of different of different specifications specifica- oftions particles of particles and oil and mixtures oil mixtures were were taken taken out and out placed and placed in the in micro-syringe the micro-syringe pump. pump. The µ flowThe flow rate ofrate the of micro-syringe the micro-syringe pump pump was adjustedwas adjusted to 50 toL/min, 50 μL/min, the impedance the impedance analyzer ana- outputlyzer output voltage voltage was set was to 2 set V, andto 2V, the and output the frequency output frequency was 2 MHz was (the 2 MHz highest (the frequency highest providedfrequency by provided Keysight by E4980A Keysight is 2E4980A MHz). is 2 MHz). All experiments are the results of multiple measurements in dynamic mode. The All experiments are the results of multiple measurements in dynamic mode. The ex- experiment adopts the rectangular structure in Figure6e. The comparison experiment periment adopts the rectangular structure in Figure 6e. The comparison experiment was was carried out using sensor with no permalloy, one piece of permalloy, and two pieces of carried out using sensor with no permalloy, one piece of permalloy, and two pieces of permalloy. The iron particles of 70 µm and 100 µm, and the copper particles of 140 µm and permalloy. The iron particles of 70 μm and 100 μm, and the copper particles of 140 μm 150 µm were randomly selected to compare the detection signals. The signal results are and 150 μm were randomly selected to compare the detection signals. The signal results shown in Figure9. The magnetization of iron particles is greater than that of eddy currents, are shown in Figure 9. The magnetization of iron particles is greater than that of eddy so upward signals were generated, as shown in Figure9a,b; the magnetization of copper currents, so upward signals were generated, as shown in Figure 9a,b; the magnetization particles is smaller than that of eddy currents, so downward signals were generated, such of copper particles is smaller than that of eddy currents, so downward signals were gen- as Figure9c,d. erated, such as Figure 9c,d. In Figure 9, the red curve is the signal diagram of particles without permalloy; the blue is the detection signal diagram of particles with only one piece of permalloy; the black curve is the detection signal diagram of particles with two pieces of permalloy. The result of the detection signal in the Figure 8 reflects that after adding permalloy at both ends of the coil, the value of the detection signal is significantly improved. For 140 μm copper particles, when there is no permalloy, the sensor cannot capture the detection signal of copper particles; when a piece of permalloy is added, it can detect the signal of 140 μm

Micromachines 2021, 12, 638 10 of 14

Micromachines 2021, 12, 638 10 of 14 copper particles, and the average signal value at this time is −7.2045 × 10−10 H; when two pieces of permalloy are added, the average detection signal value is −2.1850 × 10−9 H.

70μm iron Without permalloy With one With two

(a)

100μmiron Without With two With one permalloy (b)

140μm copper

(c)

Without permalloy With two With one

150μm copper

(d) Without permalloy With two With one

FigureFigure 9. 9. SignalSignal value value comparison: comparison: ( (aa)) 70 70 μµmm iron particles; ((bb)) 100100µ μmm ironiron particles; particles; (c ()c 140) 140µ mμm copper copper particles; particles;(d )(d 150) 150µm μm copper particles. copper particles.

TheIn Figuresignal-to-noise9, the red ratio curve (SNR) is the expresses signal diagram the detection of particles capability without of the permalloy; sensor. The the largerblue isthe the value detection of the signal SNR, diagramthe stronger of particles the detection with only effect, one and piece the of smaller permalloy; the value the black of SNR,curve the is worse the detection the detection signal effect. diagram Th ofe formula particles for with calculating two pieces the of SNR permalloy. is: The result of the detection signal in the Figure8 reﬂects that after adding permalloy at both ends of Signal value the coil, the value of the detection SNR signal = is signiﬁcantly improved. For 140 µm copper(14) Noise value particles, when there is no permalloy, the sensor cannot capture the detection signal of µ copperSignal particles; value is whenthe maximum a piece of value permalloy of the signal is added, minus it canthe average detect the noise signal value. of 140Noisem − × −10 valuecopper equals particles, average and maximum the average minus signal average value minimum. at this time As isshown7.2045 in Figure10 10.H; when two pieces of permalloy are added, the average detection signal value is −2.1850 × 10−9 H. The signal-to-noise ratio (SNR) expresses the detection capability of the sensor. The larger the value of the SNR, the stronger the detection effect, and the smaller the value of SNR, the worse the detection effect. The formula for calculating the SNR is:

Signal value SNR = (14) Noise value

Micromachines 2021, 12, 638 11 of 14

Micromachines 2021, 12, 638 11 of 14 Micromachines 2021, 12, 638 11 of 14

Noise value Micromachines 2021, 12, 638 Signal value 11 of 14

Signal value is the maximum value of the signal minus the average noise value. Noise Noise value value equals average maximum minus average minimum.Signal Asvalue shown in Figure 10.

Noise value Signal value

Figure 10. Signal value and noise value schematic diagram.

FigureIn order 10. Signal to further value and verify noise the value ability schematic of permalloy diagram. to improve the detection accuracy

of the sensor, the experimental group tested different sizes of iron particles and copper Figure 10. Signal value and noise value schematic diagram. particles.In FigureorderThe signal 10.to Signalfurther values value verify and and noisethesignal-to-no ability value schematic ofise permalloy ratio diagram. (SNR) to improve values obtained the detection from accuracythe ex- perimentsof the sensor, Inare order shown the to further experimental in Figures verify the 11 ability group and of 12. permalloytested different to improve sizes the detection of iron accuracy particles and copper particles.of the The sensor,In signalorder the experimental to values further and verify group signal-to-no testedthe ability differentise of sizespermalloyratio of (SNR) iron particlesto valuesimprove and obtained copper the detection from accuracy the experimentsparticles.of the are Thesensor, shown signal the in values experimentalFigures and signal-to-noise 11 and group 12. tested ratio (SNR) different values sizes obtained of iron from particles the and copper experimentsparticles. are The shown signal in Figures values 11 andand 12signal-to-no. ise ratio (SNR) values obtained from the experiments are shown in Figures 11 and 12.

(a) (b)

(a) Figure 11. Iron particle detection results: (a) Average signal value of iron particles; (b) Average(b) SNR value of iron particles. (a) (b) Figure 11. Iron particle detection results: (a) Average signal value of iron particles; (b) Average SNR value of iron particles. Figure 11. Iron particle detection results: (a) Average signal value of iron particles; (b) Average SNR value of iron particles. Figure 11. Iron particle detection results: (a) Average signal value of iron particles; (b) Average SNR value of iron particles.

(a) (b)

Figure 12. Copper particle detection results.(a (a)) Average signal value of copper particles; (b) Average( SNRb) value of copper Figure 12. Copper particle detection results. (a(a)) Average signal value of copper particles; (b) (Averageb) SNR value of copper particles. particles. Figure 12. Copper particle detection results. (a) Average signal value of copper particles; (b) Average SNR value of copper particles. Figure 12. Copper particle detectionFigure results. 11a(a) Average shows the signal average value ofsignal copper value particles; of different (b) Average iron SNRparticles, value whichof copper confirms particles. the previous conclusion.Figure 11a shows When the permalloy average signal is added value ofto differentthe sensor, iron theparticles, amplitude which ofconfirms the detectionFigurethe signal previous 11a significantly shows conclusion. the average increases, When signal permalloyand value the larger ofis addeddifferent the particleto theiron sensor, particles, size, thethe morewhichamplitude obvious confirms of the thethe signal previousdetection increase. conclusion. signal Figure significantly 11bWhen shows permalloy increases, the SNR isand vaadded thelues larger ofto ironthe the sensor,particles particle the size, of amplitudedifferent the more sizes.obvious of the the signal increase. Figure 11b shows the SNR values of iron particles of different sizes. Thedetection SNR ratio signal reflects significantly the accuracy increases, of the sensor and the for larger particle the detection. particle size, In Figure the more 11b, obviouswhen The SNR ratio reflects the accuracy of the sensor for particle detection. In Figure 11b, when thethe iron signal particle increase. size isFigure 30 μm 11b and shows 40 μm, the the SNR SNR va oflues the of sensor iron particles without ofpermalloy different issizes. 1, the iron particle size is 30 μm and 40 μm, the SNR of the sensor without permalloy is 1, whichThe SNR indicates ratio thatreflects the thesensor accuracy cannot of detect the sensor particles for particle of this size.detection. The sensor In Figure with 11b, a piece when the ironwhich particle indicates size is that 30 theμm sensor and 40 cannot μm, thedetect SNR pa rticlesof the of sensor this size. without The sensor permalloy with a pieceis 1, of permalloyof permalloy has a SNR has of a SNR1 for of detecting 1 for detecting iron particles iron particles of 30 of μ m,30 μandm, andthe thesensor sensor cannot cannot which indicates that the sensor cannot detect particles of this size. The sensor with a piece detect particlesdetect particlesof 30 μm. of In30 contrast,μm. In contrast, the sensor the sensor with twowith piecestwo pieces of permalloy of permalloy has has a SNR a SNR of permalloy has a SNR of 1 for detecting iron particles of 30 μm, and the sensor cannot of 1.47 whenof 1.47 detecting when detecting iron particles iron particles of 30 μ ofm, 30 which μm, which indicates indicates that thatthe sensorthe sensor can can detect detect irondetect particles particlesiron particlesbelow of 3030 below μ μm.m. In 30As contrast, μ them. Asparticle the the particle sensor size increases, sizewith increases, two the pieces SNR the ofSNR value permalloy value increases, increases, has aand SNR and of 1.47 when detecting iron particles of 30 μm, which indicates that the sensor can detect iron particles below 30 μm. As the particle size increases, the SNR value increases, and

Micromachines 2021, 12, 638 12 of 14

Figure 11a shows the average signal value of different iron particles, which confirms the previous conclusion. When permalloy is added to the sensor, the amplitude of the detection signal significantly increases, and the larger the particle size, the more obvious the signal increase. Figure 11b shows the SNR values of iron particles of different sizes. The SNR ratio reflects the accuracy of the sensor for particle detection. In Figure 11b, when the iron particle size is 30 µm and 40 µm, the SNR of the sensor without permalloy is 1, which indicates that the sensor cannot detect particles of this size. The sensor with a piece of permalloy has a SNR of 1 for detecting iron particles of 30 µm, and the sensor cannot detect particles of 30 µm. In contrast, the sensor with two pieces of permalloy has a SNR of 1.47 when detecting iron particles of 30 µm, which indicates that the sensor can detect Micromachines 2021, 12, 638 12 of 14 iron particles below 30 µm. As the particle size increases, the SNR value increases, and the SNR of the sensor with two pieces of permalloy drastically increases as compared to others. Figure 12 shows the detection signal value and SNR of copper particles. The result ofthe Figure SNR of12 athe shows sensor that with the two signal pieces value of ofpe thermalloy sensor drastically without increases permalloy as is compared lower than to thatothers. of the Figure sensor 12 shows with permalloy the detection when signal detecting value copperand SNR particles of copper of differentparticles. sizes. The result The lowerof Figure detection 12a shows limit ofthat the the sensor signal without value permalloyof the sensor is 150 withoutµm, the permalloy sensor with is lower one piece than ofthat permalloy of the sensor can detect with permalloy 130 µm, and when the detect sensoring with copper two piecesparticles of permalloyof different can sizes. detect The copperlower detection particles oflimit 100 ofµm, the with sensor an without SNR of1.65. permalloy This shows is 150 thatμm, thethe structuresensor with designed one piece in thisof permalloy paper can can detect detect copper 130 particles μm, and below the sensor 100 µ m,with as showntwo pieces in Figure of permalloy 12b. The can results detect of thecopper increasing particles SNR of 100 of ironμm, particleswith an SNR and of copper 1.65. This particles shows of that different the structure sizes are designed shown in in Tablethis paper1 below. can detect copper particles below 100 μm, as shown in Figure 12b. The results of the increasing SNR of iron particles and copper particles of different sizes are shown in Table 1. SNR and added value in different sensors. Table 1 below. Without WithTable One 1 shows With the Two calculated SNR of particWithoutles with different WithOne sizes which With were Two de- Iron (µm) Coper (µm) SNR andtected Percentage with Increase different (%) sensors. For 30 μm iron particles, SNR and the Percentage SNR of the Increase sensor (%) with two permalloy structures has increased by 47%. For 100 μm copper particles, the SNR has in- 30 1 1/0% 1.47/47% 100 1 1/0% 1.65/65% creased by 65%. The larger the particle size, the more obvious the increase in SNR value, 40 1and 1.45/45% the detection 2.37/137% capability of the 110sensor of this structure 1 is significantly 1/0% stronger 2.01/101% than 50 2.27the 3.03/33.6% sensor without 3.86/70% permalloy and the 120 sensor with a 1 slice of permalloy. 1/0% The detection 2.53/153% limit 60 3.13of 4.15/32.6% the dual permalloy 5.45/74% structure sensor 130 is 20 μm iron 1 and 80 μm 1.7/70% copper particles. 3.32/232% Among the same type of sensors, this structure has the highest detection accuracy. The signal 70 3.86 4.86/25.9% 6.75/74.9% 140 1 2.6/160% 4.93/393% value is shown in the Figures 13 and 14. 80 4.78 5.81/21.5% 8.56/79.1% 150 1.75 3.84/119% 8.18/367% Table 1. SNR and added value in different sensors. Table1 shows the calculated SNR of particles with different sizes which were detected Without With One With Two Without With One With Two Iron (μm) with different sensors. For 30 µmCoper iron particles, (μm) the SNR of the sensor with two permalloy SNR andstructures Percentage has Increase increased (%) by 47%. For 100 µm copperSNR particles, and Percentage the SNR Increase has increased (%) by 30 1 65%. The1/0% larger the1.47/47% particle size, the100 more obvious1 the increase1/0% in SNR value,1.65/65% and the 40 1 detection1.45/45% capability 2.37/137% of the sensor of this110 structure is significantly1 stronger1/0% than2.01/101% the sensor 50 2.27 without3.03/33.6% permalloy and3.86/70% the sensor with120 a slice of permalloy.1 The detection1/0% limit2.53/153% of the dual 60 3.13 permalloy4.15/32.6% structure 5.45/74% sensor is 20 µm130 iron and 80 µm1 copper particles.1.7/70% Among3.32/232% the same 70 3.86 type4.86/25.9% of sensors, this6.75/74. structure9% has the140 highest detection 1 accuracy. 2.6/160%The signal value4.93/393% is shown 80 4.78 in the5.81/21.5% Figures 13 and8.56/79.1% 14. 150 1.75 3.84/119% 8.18/367%

Noise value

1 2

1,2 is Signal value

Figure 13. Signal of 20 µm iron particles. Figure 13. Signal of 20μm iron particles.

1,2 ,3 is Signal value Noise value

2 3 1

Micromachines 2021, 12, 638 12 of 14

the SNR of the sensor with two pieces of permalloy drastically increases as compared to others. Figure 12 shows the detection signal value and SNR of copper particles. The result of Figure 12a shows that the signal value of the sensor without permalloy is lower than that of the sensor with permalloy when detecting copper particles of different sizes. The lower detection limit of the sensor without permalloy is 150 μm, the sensor with one piece of permalloy can detect 130 μm, and the sensor with two pieces of permalloy can detect copper particles of 100μm, with an SNR of 1.65. This shows that the structure designed in this paper can detect copper particles below 100 μm, as shown in Figure 12b. The results of the increasing SNR of iron particles and copper particles of different sizes are shown in Table 1 below. Table 1 shows the calculated SNR of particles with different sizes which were detected with different sensors. For 30 μm iron particles, the SNR of the sensor with two permalloy structures has increased by 47%. For 100 μm copper particles, the SNR has increased by 65%. The larger the particle size, the more obvious the increase in SNR value, and the detection capability of the sensor of this structure is significantly stronger than the sensor without permalloy and the sensor with a slice of permalloy. The detection limit of the dual permalloy structure sensor is 20 μm iron and 80 μm copper particles. Among the same type of sensors, this structure has the highest detection accuracy. The signal value is shown in the Figures 13 and 14.

Table 1. SNR and added value in different sensors.

Without With One With Two Without With One With Two Iron (μm) Coper (μm) SNR and Percentage Increase (%) SNR and Percentage Increase (%) 30 1 1/0% 1.47/47% 100 1 1/0% 1.65/65% 40 1 1.45/45% 2.37/137% 110 1 1/0% 2.01/101% 50 2.27 3.03/33.6% 3.86/70% 120 1 1/0% 2.53/153% 60 3.13 4.15/32.6% 5.45/74% 130 1 1.7/70% 3.32/232% 70 3.86 4.86/25.9% 6.75/74.9% 140 1 2.6/160% 4.93/393% 80 4.78 5.81/21.5% 8.56/79.1% 150 1.75 3.84/119% 8.18/367%

Noise value

1 2

1,2 is Signal value

Micromachines 2021, 12, 638 13 of 14 Figure 13. Signal of 20μm iron particles.

1,2 ,3 is Signal value Noise value

2 3 1

Figure 14. Signal of 80 µm copper particles.

5. Conclusions Table2 shows the advantages and disadvantages of corresponding works. The comparison indicates that the detection accuracy from Hong [10] is relatively high, but it can only detect single pollutant types and has a moderate manufacturability. The detection accuracy of Du’s work [12] is relatively high and the production is simple, but it can only detect single pollutants types. The detection accuracy of Wei’s work [17] is relatively low, and it can detect single pollutant types. Ren’s work [11] can detect ferromagnetic and non-ferromagnetic pollutants, but the detection accuracy is relatively low. The works of [14,16] can detect relatively high accuracy, but there is still an improved level.

Table 2. Comparison of other work.

The Works Inductive Method Detection of Pollutant Types Detection Accuracy Easy to Manufacture [10] Yes Ferromagnetic 13 µm iron Moderate [12] Yes Ferromagnetic 55 µm iron High [17] Yes Ferromagnetic 81 µm iron Moderate Ferromagnetic 130 µm iron [11] Yes Moderate Non-ferromagnetic 230 µm copper Ferromagnetic 50 µm iron [16] Yes High Non-ferromagnetic 130 µm copper Ferromagnetic 30 µm iron [14] Yes High Non-ferromagnetic 100 µm copper Ferromagnetic 20 µm iron This paper Yes High Non-ferromagnetic 80 µm copper

This paper designs a sensor for monitoring metal pollutants in oil. The sensor has a high-gradient magnetic field structure by adding two high-permeability materials. Through simulation and experimental verification, it is confirmed that this structure can improve the detection accuracy of the inductive sensor. The simulation respectively simulated the magnetic field distribution of the sensor unit when there is no permalloy, one piece of permalloy, and two pieces of permalloy, and the optimal structure of the sensor unit is determined. Then, comparative experiments were performed on iron particles and copper particles of different sizes to obtain the SNR and the increase in percentage. For ferromagnetic metals, it can successfully detect 20 µm iron particles, and for non-ferromagnetic metals, it can detect the inductance signal of 80 µm copper particles. This result is the highest detection accuracy in the single-plane coil sensor, which has a guiding role in the design of this type of sensor. Micromachines 2021, 12, 638 14 of 14

Author Contributions: Conceptualization, W.L. and C.B.; methodology, W.L., C.B., C.W. and H.Z.; software, C.W. and X.W.; validation, W.L., C.B. and C.W.; formal analysis, W.L. and C.B.; investigation, W.L., C.B., X.W. and S.Y.; resources, H.Z. and G.L.; data curation, W.L. and C.W.; writing—original draft preparation, W.L.; writing—review and editing, H.Z., L.I., S.Y. and G.L.; visualization, C.B., C.W., L.I., X.W. and S.Y.; supervision, C.B.; project administration, W.L. and C.B.; funding acquisition, H.Z. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by National Natural Science Foundation of China, grant number 51679022. It was funded by Supported by LiaoNing Revitalization Talents Program, grant number XLYC2002074. And it was also funded by the Technology Innovation Foundation of Dalian, grant number 2019J12GX023. Acknowledgments: The authors wish to thank the financial support of the National Natural Science Foundation of China (51679022), the Fundamental Research Funds for the Central Universities (3132019034) and the Technology Innovation Foundation of Dalian (2019J12GX023). The authors would also like to thank Dalian Maritime University for their support of this research. Conflicts of Interest: The authors declare no conflict of interest.

References 1. Zhu, X.; Zhong, C.; Zhe, J. Lubricating oil conditioning sensors for online machine health monitoring—A review. Tribol. Int. 2017, 109, 473–484. [CrossRef] 2. Kumar, M.; Mukherjee, P.S.; Misra, N.M. Advancement and current status of wear debris analysis for machine condition monitoring: A review. Ind. Lubr. Tribol. 2013, 65, 3–11. [CrossRef] 3. Tucker, J.E.; Reintjes, J.; Galie, T.R.; Schultz, A.; Lu, C.; Tankersley, L.L.; Sebok, T.; Holloway, C.; Howard, P.L. Lasernet fines optical wear debris monitor: A Navy shipboard evaluation of CBM enabling technology. Improv. Prod. Appl. Cond. Monit. 2000, 2000, 191–199. 4. Bai, C.; Zhang, H.; Wang, W.; Zhao, X.; Chen, H.; Zeng, N. Inductive-capacitive dual-mode oil detection sensor based on magnetic nanoparticle material. IEEE Sens. J. 2020, 20, 12274–12281. [CrossRef] 5. Zhang, X.; Zeng, L.; Zhang, H.; Huang, S. Magnetization model and detection mechanism of a microparticle in a harmonic magnetic field. IEEE/Asme Trans. Mechatron. 2019, 24, 1882–1892. [CrossRef] 6. Bai, C.; Zhang, H.; Zeng, L.; Zhao, X.; Yu, Z. High-throughput sensor to detect hydraulic oil contamination based on microfluidics. IEEE Sens. J. 2019, 19, 8590–8596. [CrossRef] 7. Toms, A.; Alturki, F.A.; Ahmed, S.M. Fractal analysis of cavitation eroded surface in dilute emulsions. J. Tribol. 2011, 133, 041403. 8. Bai, C.; Zhang, H.; Zeng, L.; Zhao, X.; Ma, L. Inductive magnetic nanoparticle sensor based on microfluidic chip oil detection technology. Micromachines 2020, 11, 183. [CrossRef][PubMed] 9. Du, L.; Zhe, J.; Carletta, J. Real-time monitoring of wear debris in lubrication oil using a microfluidic inductive Coulter counting device. Microfluid. Nanofluidics 2010, 9, 1241–1245. [CrossRef] 10. Xiao, H.; Wang, X.Y.; Li, H.C.; Luo, J.F.; Feng, S. An inductive debris sensor for a large-diameter lubricating oil circuit based on a high-gradient magnetic field. Appl. Sci. 2019, 9, 1546. [CrossRef] 11. Ren, Y.; Zhao, G.; Qian, M.; Feng, Z. A highly sensitive triple-coil inductive debris sensor based on an effective unbalance compensation circuit. Meas. Sci. Technol. 2019, 30, 015108. [CrossRef] 12. Du, L.; Zhu, X.; Han, Y.; Zhe, J. High throughput wear debris detection in lubricants using a resonance frequency division multiplexed sensor. Tribol. Lett. 2013, 51, 453–460. [CrossRef] 13. Zhang, H.; Zeng, L.; Teng, H.; Zhang, X. A Novel on-Chip Impedance Sensor for the Detection of Particle Contamination in Hydraulic Oil. Micromachines 2017, 8, 249. [CrossRef][PubMed] 14. Shi, H.; Zhang, H.; Ma, L.; Rogers, F.; Zhao, X.; Zeng, L. An Impedance Debris Sensor Based on a High-Gradient Magnetic Field for High Sensitivity and High Throughput. IEEE Trans. Ind. Electron. 2021, 6, 5376–5384. [CrossRef] 15. Zhang, X.; Zhang, H.; Sun, Y.; Chen, H.; Zhan, Y.; Zeng, L. Research on the Output Characteristics of Microfluidic Inductive Sensor. J. Nanomater. 2014, 2014, 5376–5384. [CrossRef] 16. Ma, L.; Zhang, H.; Qiao, W.; Han, X.; Zeng, L.; Shi, H. Oil metal debris detection sensor using ferrite core and flat channel for sensitivity improvement and high throughput. IEEE Sens. J. 2020, 20, 7303–7309. [CrossRef] 17. Wei, H.; Wang, S.; Tomovic, M.; Liu, H.; Wang, X. A new debris sensor based on dual excitation sources for online debris monitoring. Meas. Sci. Technol. 2015, 16, 12.