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This article proposes a compensation method for precision sensors considering historical temperature states, which can significantly reduce the thermal drift of the sensors during rapid temperature change process. A typical differential eddy current sensor (ECS) measuring displacement is used as an example to explain the principle. By analyzing the source of thermal drift of the ECS, it is proved that time history of temperature change will also affect the output of the ECS. In this article, the temperature response characteristics of the sensing head of the ECS are obtained by the lumped capacitance method, and the output of the ECS is compensated by convolution operation. Experimental results show that the temperature coefficient of the ECS during a temperature change process is depressed from 34.62 to 1.64 nm/°C with this method, and it is also less than 1/4 of 7.70 nm/°C which is obtained with direct compensation using current temperature value. Furthermore, this method is expected to function efficiently for any precision sensor in complex and harsh temperature environments.

Pulsed eddy current (PEC) is an electromagnetic non-destructive testing (NDT) technique mainly used to inspect corrosion in pipelines. Like many other NDT techniques, to quantify pipe wall thickness, a signal feature has to be extracted from the PEC response. The authors’ previous work has exploited the linear relationship of the time-derivative feature to propose an in-situ calibration routine. However, to extract the time-derivative feature, two configuration parameters need to be determined prior to feature extraction. To the authors’ knowledge, none of the previous works explores the determining factors of this configuration parameters, where the current technique is still limited to using brute force method or trial-and-error. This paper brings novelty by formulating the aforementioned problem as a minimisation problem, and solving it using a particle swarm optimisation (PSO) algorithm. The obtained results, compared against brute force method, demonstrate the feasibility and performance improvement of using PSO in determining the configuration parameters. The approach thus presented is validated and the results obtained are justified by analysing the underlying physical system theory.

This paper describes a two-coil eddy current sensor being used in a transmit-receive arrangement at 1 MHz, where the drive and amplification electronics are miniaturised and built directly behind the coil to reduce noise and the effects from cable length. Small, simulated defects are detected, less than 500 microns in length, on titanium and titanium aluminide, which is an increasingly important alloy for aerospace applications. Data is analysed quantitatively in a parametric approach. This experiment uses a transmitting coil driven by a constant current source and a separate receiving coil, where the magnitude and phase of the induced voltage signals on both coils are measured independently. Experimental measurements are validated using finite element modelling and the phase of the signal on the receiving coil in particular is less susceptible to variations caused by changes in lift-off. A combination of experimental and simulation data of 2D surface scans and lift-off measurements show the variation in the magnitude and phase of the eddy current signal with lift-off on Ti, TiAl (Ti-45Al-2Mn-2Nb-1B) and 316L stainless steel. It is also shown that the high-frequency lower noise approach can reliably detect defects of less than 500 microns in length in both Ti and TiAl.

Eddy current sensors are used to measure shaft clearance in wind turbines and to check that there is a thin film of oil in the clearance. In this case, the oil is usually applied under pressure. Because the eddy current sensors are resistant to oil, pressure and temperature, this allows them to operate reliably in these hostile environments. When the gap becomes too large, a maintenance warning is generated. Eddy current sensors help detect axial and radial deflection of the turbine shaft. Radial movement occurs when the shaft is off-center. Axial movement indicates that the shaft is tilted relative to the central axis. Both cannot be eliminated completely. However, with significant deviations, increased bearing wear occurs. If such situations are detected, the turbine should be shut down as soon as possible for maintenance, even before an accident occurs. Finally, eddy current sensors are used to measure forces or torques applied to the nacelle. These influences can be caused by vibration, wind loads or other factors that, over time, can lead to the destruction of the entire structure. Eddy current sensors can also be used to measure axial, radial or tangential deflection of clutch discs, which ensure the safety of the rotor in the event of strong winds. This article provides a method for calculating an inductive sensor. This calculation will allow you to correctly develop a wind turbine eddy current sensor.

Eddy current testing (ECT), is a non-destructive method widely applied in detecting defects of metal plates based on the principle of electromagnetic induction. The flexible eddy current testing (FECT) has been developed from ECT. What’s more, it’s also an effective method that is given a higher priority in defect detection of metal with complex surface structure due to its flexibility and small size. An arrayed differential flexible butterfly-shape eddy current sensor is proposed to detect the surface defect of iron screw thread in this paper, which has one butterfly-shape coil, four sets of differential receiver (RX) coils and one top RX coil, and the proposed sensor is designed as butterfly-shape with a certain folding angle to match with the curvature of the internal and external screw thread, which can solve the lift-off problem of screw thread defect detection at the bottom. The theoretical analysis illustrates the design principle for the proposed sensors. The simulation based on COMSOL Multiphysics is applied to illustrate the probability of the proposed sensor, and the experimental testing system is adopted to verify the high performance of the proposed sensors. The results of simulation and experiment are identical, which show the flexible differential butterfly-shape array eddy current sensor can not only improve the sensitivity and reduce the error rate, but also orientate the defect on the surface of the screw thread.

The actual vibration amplitude (AVA) during ultrasonic vibration-assisted face grinding (UVAFG) is an essential parameter that affects grinding force and surface quality. However, an effective method for the real-time measurement of AVA during grinding remains unavailable, hindering research on UVAFG. In this study, an experimental setup for measuring AVA is firstly established using an eddy current sensor. Ultrasonic amplitude curves under the condition of tool rotation without load are measured and analysed. Then, amplitude attenuation with different grinding forces is evaluated during the UVAFG of silicon carbide (SiC) ceramics. The influences of AVA on grinding force and surface quality are investigated through comparative experiments of the UVAFG and conventional grinding (CG) of SiC ceramics. Finally, experimental results indicate that AVA exhibits a negative correlation with grinding force. Compared with CG, UAVFG has lower grinding force when grinding SiC ceramics. AVA is the key factor that affects surface roughness during UVAFG, the AVA of UVAFG is less than 4.3 μm; thus, surface roughness during UAVFG will be less than that during CG. Moreover, vibration can reduce the scratches made by the tools on the grinding surface.

This paper proposes a measurement method for the rotation angle of the spherical joint based on the extreme learning machine (ELM) artificial neural network and four eddy current sensors. Aiming at the problems of small range and low accuracy in the early three-eddy-current angle measurement prototype, the position matching scheme of four eddy current sensors is researched, a new prototype is developed through simulation analysis, and ELM neural network substitutes the previous generalized regression neural network (GRNN) for building a new measurement model. The modelling training and comparison test are completed in the self-developed high-precision angle calibration device. Experimental results show that the new prototype not only covers a ±20° measurement range but also promotes measurement accuracy, and the standard deviation of the single-axis measurement drops to $3^{\prime }$ within the range of 5°–15°. It provides a relatively high-precision measurement method for real-time, multi-axis active detection of spherical joint space rotation angle error.

Displacement sensor is the key component of the magnetic levitation system. Reducing complexity and improving reliability of the sensor circuits are very important to mass production of magnetic levitation devices. In this article, an improved driver circuit of eddy current sensor is proposed. In order to generate a stable oscillating source with high stability and good precision of frequency, a crystal oscillator circuit with power boost is used to replace the traditional Colpitts oscillator circuit. The improved modulation circuit is composed of passive components with a simple structure for improving reliability. The parameters design method of the modulation circuit is analyzed in detail, which greatly affects the sensitivity and linearity of the sensor. The experimental results show that the designed eddy current sensor has good linearity (1.12%) and sensitivity (2.14 V/mm), and it can ensure the stable operation of the magnetic levitated turbomolecular pump at the rated speed.

The mirror in the high-energy laser beam combining system needs to make a fast and high-precision pointing adjustment before working. A two-dimensional electrically controlled adjusting mirror was designed. The main body of the system adopted an integrated flexible support design, the drive adopted a stepping motor and a deceleration mechanism to drive the screw, the precision measurement of the mirror deflection angle adopted an eddy current sensor, and the digital signal processor (DSP) was adopted as the main control module. The working principle and design of the system were analyzed, and the system calibration method as well as the control algorithm were deeply studied. In order to meet the requirements of system adjustment speed, the S-shaped acceleration and deceleration algorithm was adopted as the control algorithm of adjusting mirror, and the system calibration method with piecewise linearity was adopted. Finally, the system was tested experimentally. The experimental results show that within the angle range of ±500″, the in-position time of adjusting mirror is within 3 s, and the control error is less than 2″, which can meet the system requirements.

Eddy current sensors can be used to test the characteristics and measure the parameters of the conductive samples. As the main obstacle of the multi-frequency eddy current sensor, the lift-off distance affects the effectiveness and accuracy of the measurement. In this paper, a material-independent algorithm has been proposed for the restoration of the lift-off distance when using the multi-frequency eddy current sensor, which is based on the approximation under the thin-skin effect. Experiment testing on the performance of the proposed method is presented. Results show that from the dual-frequency inductance, the lift-off distance could be restored with a maximum error of 0.24 mm for the distance up to 12 mm. Besides, the derived lift-off distance is used for the inversion of the magnetic permeability. Based on a lift-off insensitive inductance (LII) feature, the magnetic permeability of steels can be inversed in an iterative manner, with an error of less than 0.6 % for the lift-off distance up to 12 mm.

In this work, we propose a real-time noncontact thickness measurement system for conductive materials based on an inductor–capacitor ( LC ) resonant eddy-current sensor. For the aluminum, copper, stainless steel 304, and carbon steel samples of various thicknesses, the in-phase and quadrature components of the sensor output taken during liftoff scans are found to be a series of quadratic-like curves on the phase versus logarithmic amplitude diagram. These curves can be used to generate the standard phase–amplitude relations for thickness conversion. The phase–amplitude relations of the thickness between the values of standard samples are calculated by cubic spline interpolation. With the standard database of phase–amplitude relations, the noncontact thickness measurement was implemented in real time for the copper foil sample with an error of ±3% when the liftoff distance is less than 5 mm. The liftoff tolerance is as large as 100% of the probe diameter, indicating that the proposed method is useful for online quality inspection of conductor films on flexible substrates.

For the electromagnetic eddy current (EC) testing, various methods have been proposed for reducing the lift-off error on the measurement of samples. In this article, instead of eliminating the measurement error caused by the lift-off effect, an algorithm has been proposed to directly measure the lift-off distance between the sensor and nonmagnetic conductive plates. The algorithm is based on a sample-independent inductance (SII) feature. That is, under high working frequencies, the inductance is found to be sensitive to the lift-off distance and independent of the test piece under an optimal single high working frequency (43.87 kHz). Furthermore, the predicted lift-off distance is used for the thickness prediction of the nonmagnetic conductive samples using an iterative method. Considering the EC skin depth, the thickness prediction is operated under a single lower frequency (0.20 kHz). As the inductance has different sensitivities to the lift-off and thickness, the prediction error of the sample thickness is different from that of the lift-off distance. From the experiments on three different nonmagnetic samples—aluminum, copper, and brass, the maximum prediction error of the lift-off distance and sample thickness is 1.1 mm and 5.42%, respectively, at the lift-off of 12.0 mm.

Previously, various techniques have been proposed for reducing the lift-off effect on the thickness measurement of the non-magnetic films, including the peak-frequency feature and phase feature in the Dodd-Deed analytical formulation. To realise a real-time feedback response on the thickness monitoring, the phase term in the Dodd-Deeds formulation must be taken off the integration. Previous methods were based on the slow change rate of the phase term when compared to the rest of the term – the magnitude term. However, the change rate of the phase term is still considerable for a range of working frequencies. In this paper, a high-frequency feature has been found. That is, the ratio between the imaginary and real part of the phase term is proportional to the integral variable under high frequencies. Based on this proportion relationship, the phase term has been taken out; and a thickness algorithm has been proposed. By combing the measured impedance from the custom-built sensor (three coils), the thickness of the metallic film can be reconstructed. Experiments have been carried out for the verification of the proposed scenario. Results show that the thickness of the metal film can be reconstructed with a small error of less than 2 %, and immune to a reasonable range of lift-offs.

Aluminum alloys are commonly used in commercial aircraft due to their low density and excellent mechanical properties. However, they need to become increasingly competitive in order that aluminum plate manufacturers maintaining market share. One way to ensure this is to improve or control parameters used in heat treatments. It is well known that electrical conductivity of metal alloys varies with microstructural change. Therefore, it is believed that In-Situ control of microstructural evolution can lead to optimization of treatment time, reduced energy consumption, increased production and final product quality, as well as reduction of costs, nonconformities and rework, having low implementation cost. In this way, eddy current sensors can be coupled to the furnace controller to optimize time and quality of heat treatment through the analysis of electrical conductivity with low implementation cost. Therefore, the objective of this work is to design, model and validate an eddy current sensor to monitor heat treatment of precipitation hardenable aluminum alloys in real time. Samples of 2024 alloy were prepared by solution treatment at 495 °C for 3 h and monitorization of aging treatment was performed at 190 °C for 9 h. Hardness, metallography, electrical conductivity (outside furnace) and relative electrical conductivity (inside furnace) were analyzed. The results were compared with the literature. There is a lot of discrepancy in the results of other authors. The eddy current sensor showed that behavior is similar to electrical conductivity through four-terminal method outside furnace.

A simple-to-implement technique for measuring radial clearances with controlled precision due to decreasing random components of errors is considered. The quantitative estimates of precision, performance, and efficiency of the proposed technique are provided. This technique is stochastic, is based on characteristics of random errors and on periodicity of blade wheel rotation, and allows obtaining the measurement results with uniform precision in the entire range of rotation speeds of the turbomachine rotor. The considered technique makes it possible to avoid procedures for approximating numerical readouts.

This article proposes a self-temperature compensation method based on an analog multiplier, which reduces the circuit thermal drift by more than an order of magnitude. An ac bridge eddy current sensor (ECS) is used as an example to analyze the thermal drift of the circuit in detail, and the basic principle of the compensation method is expounded. A high-precision ECS prototype is manufactured and tested. Results show that the temperature coefficient of the circuit in the prototype is decreased from 243 to 5 ppm/°C with this technique. This self-compensation method is simple, effective, and universal. Furthermore, this technique has a unique advantage for high-bandwidth and high-precision sensors and can work efficiently in complex and harsh temperature environments.

In the field of massive forged components the mechanical engineering industry searches for processes with increasing energy and resource efficiency. The new generation bainitic steels are promising for such application because of the high strength, toughness and fatigue properties. In order to achieve the desired mechanical properties, the development of the bainitic microstructure depending on the parameters of the thermomechanical process and on the cooling procedure must be well-known. In the present work diverse experimental techniques were applied for the investigation of the microstructural development during thermomechanical treatment and subsequent continuous cooling through the bainitic transformation range. The thermomechanical processes were simulated using dilatometers and at the same time, the specimens were analyzed using an eddy current sensor or using in-situ X-ray diffraction measurements at synchrotron (DESY). The results show that the eddy current sensor is suitable for the monitoring of the microstructural development during cooling and during deformation. From the investigations suitable process parameters were deduced for achieving a possibly fine bainitic microstructure. The main factors are a relatively low deformation temperature in austenitic range, a fast cooling (> 2 K/s) into the bainitic range, bainitic transformation and/or a short deformation in the lower bainite range, and finally a slower cooling until room temperature.

The development of innovative measuring technology for process optimization in hot rolling mills becomes more and more relevant because of increasing demands on product quality. Measurement technology for high-resolution non-contact cross-sectional area measurement has shown that the variation in cross-sectional area contains information about the rolling process. This information can be used for the development of new measurement devices and analytical methods for process optimization. The harsh environmental conditions and strict safety regulations result in great effort when implementing a new sensor prototype in hot rolling mills. For this reason, this work presents a mechatronic test stand that can simulate the cross-sectional area variation under laboratory conditions realistically.

The classification of conductivity is significant for recycling metallic scraps. The eddy current sensor is distinct from other classification methods by its merits of non-contact, economical set-up, fast measuring, and so forth. By introducing a set-up that could ensure the single-valued mutual inductance trajectory on the complex plane, we propose the circle fitting method to extract the global features of different trajectories. It is subsequently observed that the fitting circle centers-one of the global features-for the same conductivity with various tilting angles are distributed longitudinally close to each other. The feature line, which is parallel to the abscissa axis, is introduced to represent this gathering distribution behavior. The feature lines for different conductivity are distinguishable. Thus, we construct a simple classification method with only two steps. The test results show great fidelity of the proposed classification technique which can successfully classify the tilting metallic samples within 11.3°.

Electromagnetic eddy current sensors are commonly used to identify and quantify the surface notches of metals. However, the unintentional tilt of eddy current sensors affects results of size profiling, particularly for the depth profiling. In this paper, based on the eddy current thin-skin regime, a revised algorithm has been proposed for the analytical voltage or impedance of a tilted driver–pickup eddy current sensor scanning across a long ideal notch. Considering the resolution of the measurement, the bespoke driver–pickup, also termed as transmitter–receiver (T-R) sensor is designed with a small mean radius of 1 mm. In addition, the T-R sensor is connected to the electromagnetic instrument and controlled by a scanning stage with high spatial travel resolution, with a limit of 0.2 μm and selected as 0.25 mm. Experiments were conducted for imaging of an aluminium sheet with seven machined long notches of different depths using T-R sensor under different tilt angles. By fitting the measured voltage (both real and imaginary part) with proposed analytical algorithms, the depth profiling of notches is less affected by the tilt angle of sensors. From the results, the depth of notches can be retrieved within a deviation of 10% for tilt angles up to 60 degrees.

Electromagnetic sensing has been used for diverse applications of non-destructive testing, including the surface inspection, measurement of properties, object characterization. However, the measurement accuracy could be significantly influenced by the lift-off between sensors and samples. To address the issue caused by lift-offs, various strategies have been proposed for the permeability measurement of ferromagnetic steels, which mainly involves different sensor designs and signal features (e.g., the zero-crossing feature). In this paper, a single high-frequency scenario for the permeability retrieval is introduced. By combining the signal of two sensing pairs, the retrieval of magnetic permeability is less affected by the lift-off of sensors. Unlike the previous strategy on reducing the lift-off effect (directly taking the phase term out of the integration) using the Dodd-Deeds analytical method, the proposed method is based on a high-frequency linear feature of the phase term. Therefore, this method has the merit of high accuracy and fast processing for the permeability retrieval (a simplified version of Dodd-Deeds analytical formulas after the integration). Experimental measurement has been carried out on the impedance measurement of designed sensors interrogating ferromagnetic dual-phase steels. For sensor lift-offs of up to 10 mm, the error of the permeability retrieval is controlled within 4 % under the optimal frequency.

Funding Information: This research was funded by the 19ENG07 Met4Wind project, which has received funding from the EMPIR programme co-financed by the Participating States and from the European Union’s Horizon 2020 research and innovation programme . Additionally, the research was funded by the Business Finland as part of the Reboot IOT project (grant number 4356/31/2019 ) and by ABB Motors and Generators, Finland . Publisher Copyright: © 2021 The Authors Copyright: Copyright 2021 Elsevier B.V., All rights reserved. Several standards for vibration testing of rotating machinery define limits for relative shaft displacement during rotation. With requirements for relative shaft displacement, limits are given for combined electrical and mechanical runout, which is the eddy probe reading error and the error caused by geometry of the measured shaft. Some standards allow for compensation of the mechanical and electrical runout by vectorially subtracting them from the eddy current probe values. This paper presents a measurement procedure applying multi-probe error separation to accurately determine the roundness profile and center point motion of electric motor shafts. The roundness error and center point movement obtained from multi-probe measurement with tactile displacement probes are compared with eddy current sensor displacement measurements to separate the total displacement measured with an eddy current probe into three components: center point motion, roundness error and electrical runout. Additionally, a transform for the measured eccentric component is presented to obtain an estimate for permanent rotor bow regardless of the rotor support arrangement during measurement. The relevant industrial vibration testing standards were reviewed. Several issues were found in the measurement methods required by the standards. The requirements of the standards and the used terminology are assessed critically and improvement proposals are presented.

With the development of a new generation of high-integrated semiconductors, a need for improvement of technology to monitor processes on a nanometer scale is increased. A detection technology that accurately measures the thickness of thin films and informs the end-point of the chemical mechanical polishing process is also required. In this study, the thickness of thin copper films with sub-micron scales was measured by fabricated eddy current sensors with increased sensitivity. The sensitivity of the sensor was improved by aligning the resonant frequency of the circuit with the frequency of the supplied AC voltage and increasing the Q factor of the circuit. The thickness of the wafer was changed through the polishing process and output voltages depending on the thickness of the copper layer were observed by the eddy current sensor. The thickness with a sub-micron scale of the copper film was precisely measured within ±1.5 nm of an average error.

The traditional pressure sensors are mostly based on piezoresistive, piezoelectric effect, and strain gauge, which are easily affected by ambient temperature. The structure of some sensors is rather complex to effectively acquire the signal or measure distribution force. Therefore, a pressure sensor based on the planar coil and elastic element was designed to solve this problem. The newly designed sensor has a spiral planar coil made by a printed circuit board and a polydimethylsiloxane (PDMS) thin film as the elastic element. The conductive layer is attached on the upper surface of PDMS to realise the eddy current effect. Meanwhile, a simulation model was established to find the relationship between deformation displacement and the pressure of the elastic element. By generating the experimental curves of the deformation displacement of the elastic element and the output frequency of the eddy current sensor, the pressure measurement on the surface of the elastic element can be identified. The preliminary experimental results showed that the eddy current pressure sensor based on the plane coil has good linearity and repeatability, and it can realise large area distributed pressure measurement, which is also suitable for accurate measurement of distribution force.

In order to perform the rapid and efficient automatic on-line inspection of the surface quality of steel ball, a new spherical deployment method based on flexible array eddy current sensor (FAECS) is proposed. Full unfolding of the steel ball surface can be performed by combining the flexible array eddy current sensor with the one-dimensional orbital deployment. The inspection coil of array eddy current sensor is fabricated on flexible printed circuit board (FPCB), which is bent into a semicircle to fix on the top of one-dimensional track. When the steel ball rolls on the one-dimensional track, complete inspection of steel ball surface can be performed by the flexible array eddy current sensor. In this method, one-dimensional mechanical motion is used instead of the traditional two-dimensional deployment motion, which reduces the complexity and cost of deployment structure. Three typical defects include linear cracks (0.12 mm width × 0.5 mm depth), cross cracks (0.06 mm width × 0.9 mm depth) and arc cracks (0.05 mm width × 0.1 mm depth) are measured in the experiment to verify the effectiveness of the inspection system. Subsequently, same batch of steel balls are tested at speed of 4 pcs/s, results show that the inspection accuracy of surface defect of steel balls is 95.52%, and the false inspection rate is less than 0.7%, which proves this method efficiency.

Array eddy current testing (AECT) sensor is capable of inspecting a large area in a single probe pass resulting in a C-scan image, which is beneficial for customizing the profile of the part being inspected. This paper presents a novel AECT sensor with three-phase excitation. The sensor has two rows of excitation coils and a row of pickup coils. The excitation coils are driven by three-phase currents that are 120° apart in phase. The induced eddy current in the conductive sample shifts electrically along the phase variation direction of the excitation currents. As a result, the sensor does not need multiplexer resulting in advantages of lower cost, less noise and faster inspection speed. The background signal measured by the sensor is small if there is no defect in the sample. Therefore, the sensor has high relative sensitivity to the presence of defect. A 3D finite element method (FEM) model is utilized to study the operating principle of the sensor. A prototype sensor has been developed and tested, with which aluminum sample and carbon fiber reinforced polymer (CFRP) sample with machined defects are inspected. The experiment results demonstrate the feasibility of the sensor for fast imaging of conductive materials.

Lift-off of sensor affects the prediction of electromagnetic properties for both ferrous and non-ferrous steel plates. In this paper, we developed a strategy to address this issue for ferrous plates. With increased lift-off, the phase of the measured impedance for steel plates reduces. Meanwhile, the magnitude of the impedance signal decreases. Based on these facts, a phase compensation algorithm is developed which corrects the phase change due to lift-off considering the magnitude of the impedance signal. Further, a new magnetic permeability prediction technique is presented, which has been validated by analytical and measured results. With this new technique, the error in permeability prediction is less than 2% within the range of lift-offs tested.

Information on the vibration characteristics of machinery or civil structures is crucial in identifying or diagnosing potential malfunctions or faults. The use of cameras in vibration frequency measurement enables the acquisition of spatially high-density information of a distant measurement target. Cameras can be used for remote monitoring or as contact-less inspection sensors for machinery or civil structures owing to their low cost, high availability, and ease of installation. However, this requires complex image processing and signal processing algorithms to interpret the vibration frequency from image data. This paper proposes an image- and machine-learning-based method to measure the vibration frequency, in which long short-term memory-recurrent neural networks (LSTM-RNNs) and multi-target learning are used to predict the vibration frequency components directly. The results of the proposed method are compared against the results obtained using an accelerometer and eddy current sensor in the frequency domain. The methodology was applied in forced vibration and free vibration laboratory experiments and real-world structure experiments including a membrane structure and a cable bridge. The experimental results show that the proposed method is robust and accurate. Proposals for future applications and research directions of this methodology and limitations and challenges in real-world implementations are presented.

This article presents a study of a Multi-coils circular eddy current non-destructive testing sensor for determining the fibers orientation as well as the detection of defect in multidirectional car...

Deep defect detection for ferromagnetic materials is a challenging task for Eddy Current testing (ECT) due to the skin effect of the low penetration depth. Pulsed Eddy Current testing (PECT) is a potential and effective method for detecting deep subsurface defects as it can obtain multiple depth information owing to its wide spectrum range. A novel weak coupling sensing structure of pulsed eddy current is proposed. In particular, the structure improves the ratio of the indirect coupling energy by reducing the direct coupling energy between the excitation and the detection coils. It obviously improves the ability to detect deep subsurface defects of ferromagnetic materials. The principle of penetration and the analysis of its equivalent circuit are presented. In addition, both experiments and simulations on different defects detection have been studied. The results have confirmed that all types of defects can be detected and it has shown the relatively monotonic linear relationships and reliability.

The disc cutter is the main rock cutting tool of a tunnel boring machine (TBM), and its wear directly affects the cutter change decision. Therefore, real-time monitoring of disc cutter wear has become an urgent technical problem for boring machines. In this study, an online monitoring system based on an eddy current sensor is designed to monitor disc cutter wear in real time. The effects of three types of rock and muddy water mixture on the measurement data are compared. Results show that measuring the eddy current distance can solve the problem of inaccurate measurement after the disc cutter is covered by rocks. Besides, the error data of this method in measuring disc cutter wear are analyzed. A function test is performed for similar disc cutters on a multi-function disc cutter performance test bench, and a real-time continuous test is conducted for the wear of two disc cutters in a certain TBM project. With a comparison of monitored and measured results, it shows that the error is less than 1 mm, which indicates that the system exhibits stable transmission and high accuracy in measurement and meets engineering requirements.

Aiming at the problem of low resolution of traditional eddy current sensor for buried defects detection in metal materials, a null-offset planar eddy current sensor array is designed, realized, and tested. The arrayed sensor is composed of a spatially periodic excitation coil and multiple differential detection coils, which are skillfully designed and can effectively suppress the common mode component in the induced voltage and improve the signal-noise-ratio of the sensor. The null-offset eddy current sensor is fabricated and utilized to detect the buried defects 0.5-mm depth beneath the surface of aluminum alloy test pieces. The simulation and experimental results show that the null-offset eddy current detection unit improves the detection resolution of buried defects by more than 1000 times.

An electric machine supported by an active magnetic bearing (AMB) can realize ultrahigh speed and high power density, and it is developing toward the trends of higher rotation speed and higher power density. The displacement sensor used for an AMB is one of the most important components in a magnetic suspension electric machine, so improving the dynamic response and the resolution of the displacement sensor become a critical technology. In this paper, a novel self-differential eddy-current displacement sensor (ECDS) based on the Hartley principle for a high-speed magnetic suspension electric machine is proposed and verified. First, the integral structure of the ECDS probe and the novel design scheme are presented. Second, the phase advance network method is described in detail to improve the dynamic characteristic of the sensor. Third, the detailed suppression procedure of the sensor-to-sensor crosstalk noise is given to improve the sensor's resolution. Finally, a series of experiments is carried out on two typical prototypes of a high-speed magnetic suspension electric machine. The experimental results indicate that the proposed ECDS with high dynamic response and resolution is valid in the application of the high-speed magnetic suspension rotating machinery in industrial applications.