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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.

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.

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.

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.

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.

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.

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.

Composite lightweight components of carbon fiber reinforced plastics (CFRP) provide great potential for the automotive industry. Yet, due to their complexity, there is a high amount of quality defects in their production processes. Thus, this article deals with an approach for in-process metrology of CFRP components by means of an eddy-current sensor array. First, the development of the sensor design and its in-process integration is introduced. Second, a method for the quantitative evaluation of the measurement data as well as the measurement uncertainty is elaborated. Finally, a machine learning approach for the classification of crucial defects is shown.

In many advanced industrial applications, the thickness is a critical index, especially for metallic coatings. However, the variance of lift-off spacing between sensors and test pieces affects the measured voltage or impedance, which leads to unreliable results from the sensor. Massive research works have been proposed to address the lift-off issue, but few of them applies to the thickness measurement of planar metallic films with finite-size circular (disk) geometry. Previously, a peak-frequency feature from the swept-frequency inductance was used to compensate the measurement error caused by lift-offs, which was based on the slow-changing rate of impedance phase term in the Dodd-Deeds formulas. However, the phase of measured impedance is nearly invariant merely on a limited range of sample thicknesses and working frequencies. Besides, the frequency sweeping is time-consuming, where a recalibration is needed for different sensor setups applied to the online real-time measurement. In this paper, a single-frequency algorithm has been proposed, which is embedded in the measurement instrument for the online real-time retrieval of thickness. Owing to the single-frequency measurement strategy, the proposed method does not need to recalibrate for different sensor setups. The thickness retrieval is based on a triple-coil sensor (with one transmitter and two receivers). The thickness of metallic disk foils is retrieved from the measured electrical resistance of two transmitter-receiver sensing pairs. Experiments on materials of different electrical conductivities (from direct current), thicknesses and planar sizes (radii) have been carried out to verify the proposed method. The error for the thickness retrieval of conductive disk foils is controlled within 5 % for lift-offs up to 5 mm.

Defect detection in ferromagnetic substrates is often hampered by non-magnetic coating thickness variation when using conventional eddy current testing technique. The lift-off distance between the sample and the sensor is one of the main obstacles for the thickness measurement of non-magnetic coatings on ferromagnetic substrates when using the eddy current testing technique. Based on the eddy current thin-skin effect and the lift-off insensitive inductance (LII), a simplified iterative algorithm is proposed for reducing the lift-off variation effect using a multi-frequency sensor. Compared to the previous techniques on compensating the lift-off error (e.g., the lift-off point of intersection) while retrieving the thickness, the simplified inductance algorithms avoid the computation burden of integration, which are used as embedded algorithms for the online retrieval of lift-offs via each frequency channel. The LII is determined by the dimension and geometry of the sensor, thus eliminating the need for empirical calibration. The method is validated by means of experimental measurements of the inductance of coatings with different materials and thicknesses on ferrous substrates (dual-phase alloy). The error of the calculated coating thickness has been controlled to within 3 % for an extended lift-off range of up to 10 mm.

With the advancement of intelligent manufacturing, the sensor installed on the electromechanical equipment can easily obtain a large amount of field data. In this paper, we establish a pre-warning model of equipment health recognition based on deep learning. The model firstly uses the eddy current sensor to collect the original vibration signal during the operation of the equipment and obtains the time-domain feature sequence as the CNN-LSTM input sample set; The input samples extract robust information from feature learning capabilities of the Convolutional Neural Network (CNN) for device health status recognition; At the same time, multi-layer short and long-time memory neural network (LSTM) coding feature information is introduced to reconstruct the sequence space to predict the operating status. The model is applied to the Bentley rotor test bench of normal, touch grinding, unbalanced three states to identify and predict. The experimental results show that the model has strong feature extraction ability and generalization ability to the original vibration signal, the correct rate of the training samples is 99.16% and the correct rate of the test samples is 98.61%; LSTM coded feature information for target state prediction with fast response and tracking performance. At the same time, three kinds of state recognition and warning of the spindle characteristic test stand, the spindle and the support end, and the crack of the bearing are identified and verified. The feasibility of the CNN-LSTM network is verified and has certain practical value.

Electromagnetic sensors have been used for inspecting small surface defects of metals. Based on the eddy-current thin-skin regime, a revised algorithm is proposed for a triple-coil drive-pickup eddy-current sensor scanning over long surface crack slots (10 mm) with different rotary angles. The method is validated by the voltage measurement of the designed EC sensor scanning over a benchmark (ferromagnetic) steel with surface defects of different depths and rotary angles. With an additional sensing coil for the designed EC sensor, the defect angle (or orientation) can be measured without spatially and coaxially rotating the excitation coil. By referring to the voltage change (due to the defect) diagram (voltage sum versus voltage different) of two sensing pairs, the rotary angle of the surface crack is retrieved with a maximum residual deviation of 3.5 %.

For the electromagnetic eddy current testing, various methods have been proposed for reducing the lift-off error on the measurement of samples. In this paper, 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 non-magnetic conductive plates. The algorithm is based on a sample-independent inductance (SII) feature. That is, under high working frequencies, the inductance is found 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 non-magnetic conductive samples using an iterative method. Considering the eddy current 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 – aluminium, 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.

Mechanical transmission systems require online health monitoring for several reasons. Gearboxes account for many of the maintenance costs due to repairs, replacements and downtime. Transmission systems feature in many applications including rotor aircraft and wind turbines. The wind energy industry since its inception has experienced high levels of failure rates. Principal gearbox design defects and structural problems have been notably significant issues of wind turbines and have had to be addressed by the wind turbine manufacturers. Reliability and safety of conventional wind turbines has improved although rates of failures are still disappointingly high. There still exists a lack of sufficient technology to enable reliable monitoring of the structural and operational conditions of wind turbines and this is currently a significant area of research. Gearbox monitoring in particular lacks sensor technology to successfully detect tooth damage, high speed and low speed shaft faults. Typically, vibration measurement and spectrum analysis are chosen for gearbox monitoring but, these methods are not able to detect the faults until failure is imminent. More recently acoustic emissions sensors are being developed for early detection of stress and surface defects. This paper presents a new concept that employs an eddy current sensor fitted to the teeth of an idler gear to detect early micro and macro pitting of the gear tooth surface. A rotating bench test has been carried out to validate the technique where simple eddy current sensors have been fitted to an idler gear. Seeded faults of three different types on an actual gear have been shown to be detectable using this technique. Eddy current sensors are used for their immunity to dust, dirt and oil contamination. Thus this technique is targeted for in-service operation where sensors have not previously been deployed to access the tooth face, flank and root shank.

In this paper, the phase gradient is taken as the characteristic quantity of defect testing signal by using the phase spectrum analysis method of spatial domain, and the phase gradient of testing signal is extracted by using the digital phase- sensitive demodulation technology to detect and classify different types of defects in the plate metal sample. Dual air core coil eddy current sensor and 1-10kHz multi-frequency excitation signal are used to identify surface defects, lower surface defects and internal defects of the sample. The experimental results show that this experimental system can effectively detect defects, and visual detection results can be obtained through phase spectrum analysis of spatial domain. The phase gradient is used as the characteristic quantity to effectively suppress the influence of lift-off effect, making the detection results more accurate.

This paper presents a novel, non-contact displacement sensor based on the eddy current sensing technique. The moving part of the sensor is a conductive sheet with a simple surface groove. This part is easy to fabricate as the machining process required is simple. The moving part is not electrically connected to the measurement system, like the eddy current proximity sensor. The displacement of the moving part is determined by the change in the inductance of four identical stationary planar coils kept underneath the moving part. A signal conditioning circuit is presented in this paper which measures the difference in inductance between two coils. A suitable algorithm has been developed to calculate the displacement using the corresponding inductance values. A prototype has been fabricated in the laboratory to evaluate the performance. The test result shows that the maximum error is less than 1.65%. The output of the prototype sensor was linear for the full range, as expected. It is well suited for application where the vertical space available for the installation is limited. The overall thickness of the developed sensor is less than 5 mm.

Eddy-current sensors are the most commonly used position sensors in a magnetic bearing application. Most commercial eddy current sensor outputs analog voltage of 0–2 V or 0–5 V in their measurement range. Such eddy current sensors are quite expensive and are in the price range of $2500 (USD). This paper presents a design of a $20 (USD) low-cost eddy current sensor capable of resolving displacements of 7 micron which is suitable for high-speed position control in active magnetic bearings. A novel method of directly converting the time period of the square wave signal from the eddy current sensor output for digital servo position feedback is employed in this design. This paper presents a scheme to implement digital position servo control algorithm on Texas Instruments C2000 real-time microcontroller to control the position of magnetically levitated object by controlling the magnetic actuator’s coil current. The magnetic actuators are electromagnetic coils that generate the magnetic force in the bearing.

Purpose The purpose of this paper is to investigate the process of rapid prototyping eddy current sensors using 3D printing technology. Making full use of the advantages of 3D printing, the authors study on a new method for fabrication of an eddy current sensor. Design/methodology/approach In this paper, the authors establish a 3D model using SolidWorks. And the eddy current sensor is printed by the fused deposition modeling method. Findings Measurement results show that the 3D printing eddy current sensor has a wider linear measurement range and better linearity than the traditional manufacturing sensor. Compared to traditional eddy current sensor fabrication method, this 3D printed sensor can be fabricated at a lower cost, and the fabrication process is more convenient and faster. Practical implications This demonstrated 3D printing process can be applied to the 3D printing of sensors of more sophisticated structures that are difficult to fabricate using conventional techniques. Originality/value In this work, the process of rapid prototyping eddy current sensors using 3D printing is presented. Sensors fabricated with the 3D printing possess lots of merits than traditional manufactures. 3D printed sensors can be customized according to the configuration of the overall system, thus reducing the demand of sensor's rigid mounting interfaces. The 3D printing also reduce design costs as well as shortens the development cycle. This allows for quick translation of a design from concept to a useful device.

The Cutter runout in traditional studies about milling mechanics and dynamics are always assumed as a constant value. Actually, the dynamic characteristics and vibration response of spindle system will change under different spindle speeds, which would result in a spindle speed dependent effect for cutter runout. A non-contact calibration method for cutter runout with consideration of spindle speed dependent effect is proposed in the paper, and the influence of cutter runout on milling mechanics and dynamics is further analyzed. Based on the measured relative variation of tooth by the eddy current sensor measurement system, a numerical optimization method for identifying cutter runout parameters is presented. The main advantage of the method is simple and convenient, especially for studying the cutter runout under different spindle speeds. Then, the paper gives out an instantaneous uncut chip thickness model during cutter/workpiece engagement with runout effect, and puts forward an enhanced SDM for milling stability prediction. Theoretical and experimental results show that milling force, stability and SLE prediction considering the cutter runout with spindle speed dependent effect have a higher prediction accuracy compared with other previous methods. Lastly, the studies analyze the influence of cutter runout on milling force, milling stability and SLE, and the results indicate that cutter runout can improve the milling stability, but deteriorate the milling force excitation characteristics and SLE.

This paper proposes a circular arrayed eddy current non-destructive testing sensor for detecting fibers orientation and in-plane fiber waviness defects in unidirectional carbon fibers reinforced polymer (CFRP). The design procedure involves two steps, the application of the rotating rectangular sensor principle on a pair of coils. In this case, to test the used simulation method, the results are experimentally verified. In the second step, the resulted form is exploited to simulate a circular arrayed sensor. This sensor allows the cancellation of the mechanical rotation of the conventional sensors and it permits to reduce the inspection procedure duration. The electromagnetic phenomena are calculated by using 3D finite element method (FEM) based on the electromagnetic AV-A formulation. Then, the sensor responses are analyzed through polar diagrams of the impedance variation. The circular arrayed sensor is used to characterize a unidirectional CFRP and to detect the in-plane fiber waviness in a layer of CFRP.

This paper proposes a linear eddy-current feature to determine the radius of a metallic ball in a non-contact manner. An electromagnetic eddy-current sensor with two coils is placed co-axially to the metal ball during measurement. It is well known that the distance between the sensor and test piece (i.e. lift-off) affects eddy-current signals. In this paper, it is found that the peak frequency feature of inductance spectrum is linear to the lift-off spacing between the centre of coil and ball. Besides, the slope of peak frequencies versus lift-offs is linked to the radius of ball. The radius of metallic balls is retrieved from the experimental and embedded analytical result of the slope. Measurements have been carried out on 6 metallic balls with different radii. The radius of the metallic ball can be retrieved with an error of less than 2 %.

Array eddy current detection (ECAT) technology has the advantages of fast scanning speed and high detection efficiency, and has a wide range of application prospects. However, the traditional array eddy current sensor has a poor coupling effect with the inner wall of the pipeline and is not suitable for in-pipe inspection. Based on the basic principles of ECAT, a flexible array eddy current sensor made by flexible printed circuit board (FPCB) technology is designed and developed, which can realize 360° detection of defects on the inner wall of natural gas pipelines. The paper uses ANSYS finite element software to establish a simulation model of multi-parameter effects, study the influence of sensor size parameters and detection parameters on eddy current signals, carry out detection experiments on blind hole defects in the inner wall of steel pipes, analyze the response characteristics of defect signals, and verify the feasibility of using the FPCB array eddy current sensor for internal inspection of natural gas pipeline.

According to the inverse magnetostrictive effect, magnetic permeability variations in ferromagnetic materials under elastic stress offer the potential to measure tension. In this study, a prototype sensor was designed, fabricated, and tested. An eddy current sensor (ECS) with a single coil structure was used to detect tension due to its lower cost, simpler structure and less mutual interference than that of conventional elastomagnetic (EM) sensors. In addition, the influence of a sleeve structure on the ECS was investigated through experimental studies. The experimental results indicated that the use of sleeve structure could enhance the relative sensitivity and reduce the repeatability error of the sensor. Furthermore, a bypass structure was designed to adjust the bias magnetic field by changing air gap in the lower magnetic circuit or by rotating yoke in the upper magnetic circuit. The results demonstrated a linear relationship between voltage across the sensor and tension. Finally, the bias magnetic field and working frequency were optimized by monitoring the sensor sensitivity.

Manufacturing a high-pressure sensitive diaphragm type sensor is a complex task. Due to it’s complex shape, several parts are designed individually. It involves welding of several parts. As welding involves several parameters it’s difficult to control the welding geometry where it is being fused. So it is likely that the physical boundary condition of the welded region will be different from the theoretical boundary conditions. So the change in boundary condition will make the deflection of the diaphragm different. For a precision device, any effect of a change in boundary condition can affect the deflection of the diaphragm largely. Thus, any effect of imperfect welding in a high precision measuring device can hamper the sensitivity of the particular device. A welded diaphragm of steel for a pressure sensor using eddy current sensor to detect it’s deflection due to pressure can lose it’s effectivity, due to the unpredictable boundary conditions created after the welding. In this paper, we will be trying to find the cause of deviation between the theoretical and experimental results due to the effect of a change in boundary conditions at the welded region.

Purpose Magnetic permeability variations of ferromagnetic materials under elastic stress offer the potential to monitor tension based on the inverse magnetostrictive effect. The purpose of this paper is to propose an innovative self-inductance tension eddy current sensor to detect tension. Design/methodology/approach The effectiveness of conventional elasto-magnetic (EM) sensor is limited during signal detection, due to its complex sensor structure, which includes excitation and induction coils. In this paper, a novel self-inductance tension eddy current sensor using a single coil is presented. Findings The output signal was analyzed through oscilloscope in the frequency domain and via self-developed data logger in the time domain. Experimental results show the existence of a linear relationship between voltage across the sensor and tension. The sensor sensitivity is dependent on operating conditions, such as current and frequency of the input signal. Practical implications The self-inductance sensor has great potential for replacing conventional EM sensor due to its low cost, simple structure, high precision and good repeatability in tension detection. Originality/value A spilt sleeve structure provides a higher permeability path to magnetic field lines than a non-sleeve structure, thus reducing the loss of magnetic field. The self-developed data logger improves sensitivity and signal-to-noise ratio of sensor. The novel sensor, as a replacement of the EM sensor, can easily and accurately monitor the tension force.

The integration of quality control processes in immature production systems such as the resin transfer moulding (RTM) process in the production of carbon fibre reinforced plastics (CFRP) faces numerous challenges. Requirements towards the reliability and product design as well as the consideration of economic restrictions lead to challenging requirements for measurement systems. This paper presents the development of a process integrated quality control using eddy current inspection. The concept focuses on an eddy current sensor array that is integrated in a preforming tool and thus enables a 100% quality control of CRFP parts with minor effects on the production environment.

The study of 3D eddy current non destructive testing system for cracks characterization using finite element method requires a great amount of computing time and memory space. In this article, we have validated the developed model and then determined directly the crack length by analyzing the complete signal. Afterwards, we have extracted from the complete sensor sweep signal the maximal amplitude that we have exploited to estimate the crack depth

Sensor detection probe is an important part of pipeline internal detector. This paper designs a new type of magnetic leakage and eddy current composite sensor which is suitable for nondestructive testing of oil and gas pipelines. The working principle, structure and characteristics of the composite sensor are introduced. The internal and external wall defects can be distinguished and evaluated in combination with the advantages of the leakage flux sensor to the wall volume defect sensitivity and the high frequency eddy current sensor to the surface defect of the pipe wall. Experimental results show that the new type of magnetic leakage and eddy current composite sensor can not only detect defects in the process of pipeline defect detection and can distinguish internal and external wall defect, especially to the surface crack defects may have potential detection.

Eddy current (EC) sensors placed in the vicinity of a rail track and sensitive to passing train components are safety-critical components commonly used in the railway sector. From the engineering point of view they form a system with numerous variables including their geometry, the lift-off, magnetic properties of the applied materials, the operating frequency and electrical characteristics of the built-in circuits. Although some simple configurations of the EC devices have been studied experimentally, numerically and analytically, there have so far been no universal algorithm allowing for predicting, understanding and optimizing output signals for arbitrarily device/track/wheel characteristics. A significant step towards such an universal algorithm is presented in this work, combining a linear 3D finite element modelling and a set of analytical formulas derived directly from the constants of the resonance circuit. Functions correlating the magnetic induction space/time characteristics with the circuit outputs are proposed and validated against experiment in three stages: (a) by determination of the signal from a flat thin FeSi plate (i.e. in fully controlled laboratory conditions), (b) by laboratory measurements of a highly degraded rail with uncertain material properties, (c) by tests of a commercial EC wheel detector, with reference to averaged service data. The proposed methodology can be extended to any NDT field where EC devices are applied.

In the dissertation, an automatic and integrated calibration device for the static characteristics of eddy current sensors was researched aimed at the great demand of improving the efficiency of calibrating eddy current sensors. The design proposal for the control system in the slave computer of automatic and integrated calibration device for the dynamic characteristics of eddy current sensors was studied. The control method of vibration level automatic adjustment was proposed. A signal generator, a data acquisition unit and a data storage unit were designed. Besides, the serial communication module was also designed to communicate with the master computer.

© 2018 Elsevier Ltd A ferromagnetic material thickness quantification method based on the decay rate of the Pulsed Eddy Current sensor detector coil voltage is proposed. An expression for the decay rate is derived and the relationship between the decay rate and material thickness is established. Pipe wall thickness estimation is done with a developed circular sensor incorporating the proposed method, and results are evaluated through destructive testing. The decay rate feature has a unique attribute of being lowly dependent on properties such as sensor shape and size, and lift-off, enabling the method to be usable with any detector coil-based sensor. A case study on using the proposed method with a commercial sensor is also presented to demonstrate its versatility.

Pulsed eddy current (PEC) with transient analysis is a significant advance over conventional eddy current testing using impedance analysis at a particular frequency. The fabrication and optimization of PEC sensor are important issues in PEC applications in nondestructive testing (NDT) field especially for ferromagnetic materials. In this work, the influence of metallic shields on circular PEC sensor for defect detectability in ferromagnetic metals has been investigated through finite element models (FEM) and experimental studies by comparing iron and aluminum shields with no-shield. Both simulations and experiments indicate that PEC probe with an aluminium shield can effectively enhance the amplitude of PEC response in both surface and subsurface defect detection. However, the sensitivity is decreased. In contrast, iron shield has better shielded performance and can effectively improve the sensitivity of both surface and subsurface defects detection in ferromagnetic materials.

Disc cutter is the main rock breaking tool of TBM. It is angled worn frequently because of locked-rotor; as a result, monitoring relevant operating parameters of TBM disc cutter has become an urgent technical problem. This paper studies nondestructive and non-contact online detection disc cutter rotational speed method of based on eddy current sensor: applies eddy current sensor to detecting six 2 mm-high metal bumps setting on the disc cutter, so as to detect the rotational speed of disc cutter. K60 MCU is applied as the main control core. The experimental results show that the on-line rotational speed monitor system of disc cutter features high anti-jamming ability and is reliable.

Corner radius as a non-main cutting parameters, study of corner radius about cutting vibration is relatively small.Turning experiments use PCBN tool in CAK4085 CNC lathe,cutting hardened steel HRC50-52 Cr12MoV and hardened steel HRC62-64 GCr15, eddy current sensor measure the tool vibration amplitude of each group parameters, analysis influence of the corner radius for tool vibration amplitude. With corner radius increases, tool vibration amplitude increases. Research will contribute to the development of high-speed machining of hardened steel.

基于BP神经网络算法，对H型传感器测厚系统采集到的感应差压信号进行分析处理。由不同厚度铝箔采集到的感应差压信号建立网络预测被测铝箔的厚度。 The BP neural network algorithm was used to create a connection between the collected differential induced voltage signal and the thickness of tested aluminum foil with neural network toolbox in MATLAB environment.

The paper reviews features and applications of the upgraded inductive sensor for BTT, which is able to operate in contact with exhaust gases of temperature even as high as 1200 K. The new design includes metal-ceramic housing ensuring proper heat transfer, magnetic circuit containing set of permanent magnets with various magnetic field values and Curie temperatures, completely redesigned windings and current/voltage converter used instead of an electromotive force amplifier. Its principle of operation is based on electro-dynamical interaction and therefore it may be referred as a passive eddy-current sensor. The sensor technique has been demonstrated on four stages of a surplus military turbofan including the high pressure turbine as part of the engine health monitoring system. We present signal samples and review methods used for online processing of time-of-arrival signals when only a limited number of sensors is available.

The Koch curve exciting coil eddy current sensor is a kind of novel flexible planar eddy current probe. In this study, an intersection angle spectrum entropy index and a radial direction energy spectrum entropy were proposed to evaluate the eddy current distribution. Eddy current distributions induced by one turn of a circular coil and one turn of a second order Koch curve coil feed with different exciting frequency alternative currents and at different lift-off distances, were simulated and the eddy current distributions varying with lift-off distance in different exciting frequencies were compared by the two proposed indices. With the increase of the lift-off distance or the decrease of exciting frequency, the similarity between the shape of the Koch curve and the eddy current distribution became weakened and the degree of the concentration of the eddy current distribution in the specimen under the exciting coil was loosened.

The segmented mirror active optics technology is one of the key technologies for the extremely large telescope, while edge sensor is one of the essential core components of active optics for the co-phasing maintenance of all segmented mirrors. The main properties of these edge sensors are of high precision of nanometers, high linearity, and low sensitivity to temperature and humidity fluctuations as well as high reliability. This paper presents an eddy current edge sensor design developed cooperatively by Nanjing Institute of Astronomical Optics and Technology and University of Science and Technology of China. The stage work performance results of eddy current sensor prototype under representative operational conditions are also presented.

This publication presents the realisation of a sensor concept, which is based on eddy current testing, to detect textile defects during preforming of semi-finished carbon fibre parts. The presented system has the potential for 100% control of manufactured carbon fibre based components, allowing the immediate exclusion of defective parts from further process steps. The core innovation of this system is given by the high degree of process integration, which has not been implemented in the state of the art. The publication presents the functional principle of the sensor that is based on half-transmission probes as well as the signals that can be gained by its application. Furthermore, a method to determine the optimum sensor resolution is presented as well as the sensor housing and its integration in the preforming process.

In industrial production and life, it is often necessary to accurately measure the relative position among the instruments. Sliding bearings are key parts of many heavy machinery. And sliding bearing working conditions directly affect the safety of rotating machinery, thus stable and reliable operation is necessary. At the same time, mechanical vibration is common in the work of equipment, so the study of mechanical vibration has been one of the important issues in this field. In engineering practice, the mechanical vibration must be measured to observe the mechanical vibration and quantitative qualitative measurement. Therefore, it is necessary to study a set of sliding bearing vibration detection system, which is useful for equipment observation and theoretical practice research. This paper describes the bearing vibration sensor sliding bearing vibration detection system background, hardware design and software design part. The system uses ARM-based embedded microcontroller STM32F103 as the master chip, selects 50mm diameter probe JX20 bearing vibration sensor, uses dot matrix LCD screen LCD5110 real-time display of the measured results. According to the output of the bearing vibration sensor, the corresponding signal conditioning circuit is designed. Meanwhile, according to the system hardware design, the design of the corresponding software programs, including ADC sampling procedures and liquid crystal display program.

Degradation diagnosis of cable is one of major issues for operation and maintenance in overhead distribution power lines. The diagnostic system for overhead power lines is composed of three parts in functional aspect - a travelling unit, a sensing unit and a communication unit. Among them, sensor detects the defects such as corrosion and disconnecting of power lines. Performance of sensor is very important, and besides, the size and structure of sensor is restricted for installation to small and lightweight diagnostic system. This paper suggests an optimal eddy current sensor best suit for small and lightweight diagnostic system in consideration of detecting performance, size and ease of installation and so on. Proposed sensor has been designed by Drum core structure and can be applied to the all domestic overhead power lines regardless of the cross-sectional areas. Also, it is showed that results of mock environmental test are satisfied.

The precise localisation of rail vehicles is fundamental to the development and employment of more efficient train control systems in security, logistics and disposition applications. A key element of this is the exact and reliable velocity and distance estimation. The popular satellite navigation (global navigation satellite systems) and visual odometry, based on optical systems, tend to fail in the rough environment of rail application scenarios. This study describes an approach to making a precise distance estimate using an innovative eddy current sensor system. This is achieved through the combination of an augmented cross-correlation approach to highly accurate velocity estimation. That is subsequently employed to determine the travelled distance based on counting rail clamps in a spatial transformed space. This approach relies on recursive state estimation of the dynamic states and a statistical assessment of the counted rail clamps for the purpose of outlier rejection. The proposed methods are compared and evaluated in a quantitative way on the basis of experimental data. The results prove that the proposed approach can improve the accuracy and reliability of velocity measurement and relative position detection.

At present, the development of a detection device in order to prevent accidents due to wire deterioration in the distribution lines is required. Distribution line is not possible to check the internal state in a normal way because it is covered with the coating. Accordingly, various eddy current techniques that is the non-destructive test (NDT) techniques have been applied to solve this problem. In this paper, we have seen examining the characteristic change of the eddy current sensor according to the simplified shape of the sensor in order to solve the problems for the simplified shape that is generated when the simulation for the shape of the eddy current sensor.