Eddy Current Detection Research Articles

Optimization design of excitation coil for pulsed eddy current testing of laser welding defect structure of power battery bus-bar

Pulsed eddy current testing is suitable for non-contact detection of conductor structural defect, which is an effective method to realize online detection of welding structural defect of power battery pack. Aiming at the circular laser weld structure between the bus-bar and the terminal of the power battery pack, a three-dimensional finite element simulation model of pulsed eddy current testing is established. According to the structural parameters of the pulsed eddy current excitation coil, which are the inner diameter, outer diameter, height and number of turns, the pulsed eddy current voltage responses of the laser welding defect structure of the battery pack bus-bar are calculated, respectively. By analyzing the influence of the excitation coil parameters on the pulsed eddy current detection results, the pulsed eddy current excitation coil parameters are determined for the testing of laser welding structural defects. It provides a method and basis for the optimal design of the pulsed eddy current detection system for the laser weld structural defect of the battery pack bus-bar.

Design of A Multifunctional Micro-Magnetic Testing Instrument

Micro-magnetic testing technology is capable of non-destructively evaluating the mechanical properties and residual stress in ferromagnetic components. In the applications of micro-magnetic testing technology, several types of magnetic signals, such as magnetic Barkhausen noise, incremental permeability, tangential magnetic field and eddy current, etc., are used to characterize the target properties (mechanical properties and residual stress). In this paper, a unique framework for multifunctional micro-magnetic sensor design is proposed. Accordingly, a multifunctional micro-magnetic instrument is developed. Intermittently superimposed magnetic fields of high (several kHz) and low frequencies (several Hz) are used for material magnetization. Combined magnetic sensors are employed to measure a total of five types of signals, including the magnetic Barkhausen noise, incremental permeability, eddy currents, tangential magnetic field and main flux. Especially, twisted-pair wiring was used for winding two identical sensing coils. One of the sensing coils is used for eddy current or incremental permeability detection and the rest one acts as a compensatory coil to suppress the strong mutual induction voltage in detection coil. The entire instrument is composed of a multi-channel signal generator, a power amplifier, signal processing circuits embedded into the multifunctional sensor and a four-channel signal acquisition device. The multi-channel signal generator is constructed based on FPGA and high speed D/A converters. The direct digital synthesizer and state machine are programed in FPGA to enable the excitation of intermittently superimposed signals of high and low frequencies. Carefully experiments were performed to test the performances of the developed instrument. The results obtained from different types of steels proved that the developed instrument can acquire five types of magnetic signals with high SNR. The features of the five types of magnetic signals can used to distinguish the material and its mechanical properties such as surface hardness.

Imaging and quantitative detection of complex defects with a flexible electromagnetic array sensor

The eddy current non-destructive testing (NDT) method has the advantages of high sensitivity and fast speed and is widely used in the inspection of key metal parts in the military and in industry. The existing scanning imaging method based on eddy current detection will cause the defect and the image to be inconsistent when the angle between the sensor and the defect is different, which will result in the inability to accurately quantify the defect based on the image. Therefore, this paper proposes a method based on a three-axis platform and a flexible eddy current array sensor to realise defect imaging and quantitative detection. First, the sensor is installed on the three-axis motion platform through a flexible substrate. It is intended that the three-axis motion platform will achieve full coverage detection of the surface of the test-piece and the overall image of the surface of the test-piece can be obtained by splicing. Then, the characteristic signal is subjected to bicubic interpolation to obtain clearer two-dimensional and three-dimensional defect images. Finally, morphological image processing is used to binarise the defect greyscale image and then the shape and size of the defect are obtained through contour pixel analysis. Experimental results show that this method can effectively overcome the impact on imaging when the sensor and the defect are at different angles and ensure the consistency of the imaging of the defect at any angle, so as to realise the imaging and quantification of any defect.

Simulation and experimental research on 316L liner of bimetal composite pipe with eddy current testing

Conventional magnetic flux leakage technology is unable to identify the stainless steel-lined defects of bimetallic composite pipe. In this paper, the in-line inspection technology of a 316L liner based on the eddy current flaw detection principle is studied with the aim of solving this problem. A printed circuit board (PCB) coil is designed and parameters such as the external diameter, the number of turns, the number of layers and the shape of the eddy current testing coil are determined. The impedance changes that occur under the influence of different factors of the coil are analysed according to finite element simulation. The contribution of each influencing factor during eddy current testing is investigated to optimise the coil parameters and excitation parameters. An eddy current flaw detection model for the stainless steel liner is finally established and numerical calculation is carried out on the impedance response of the defect, which is detected by parameterised scanning with the coil swept. The coil impedance is obtained under the ideal state and then verified by the experimental tests. The results show that the eddy current array testing coil has good applicability in the detection of surface defects on the stainless steel liner, which can provide references for the development of a bimetallic tube composite probe.

Effect of Pore Defect Size and Location on Damage Tolerance of Aluminum Alloy Piston and Fiber Ring Groove

The defects of high-power density piston aluminum alloy components involved in this paper include surface crack, internal crack, shrinkage cavity and cold shut. The service condition of piston components is 350°C-420°C, and the explosion pressure of piston crown is 28Mpa. The requirements for eddy current flaw detection of this component are in accordance with a and requirements in GB / T5126-2013 eddy current flaw detection standard, that is, it is not allowed to be greater than 0.12mm × 0.2mm × 3mm volumetric defects, and Ф1.0mm flat bottom hole equivalent point defect. For the piston components of 88kw / L high-power diesel engine, under the service conditions of temperature 350°C-420°C and piston top explosion pressure 28Mpa. Under the condition of thermal mechanical coupling, the typical NDT defects such as surface crack, internal crack, shrinkage cavity and cold shut of the first ring groove and internal position of the piston are studied. On scale, morphology and position sensitivity and their quantitative relationship. At the same time, numerical simulation analysis combined with relevant experimental verification is used to comprehensively analyze and evaluate the damage tolerance of defects, and scientifically evaluate the defects of different properties and sizes.

Development of a Cone-Shaped Pulsed Eddy Current Sensor

Compared with the conventional eddy current, pulsed eddy current (PEC) technology has the characteristic of abundant components in the frequency domain, which is a significant technological advancement. Improvements in the production and performance of PEC sensors are necessary for nondestructive testing. Sensor configuration parameters have significant influence on the development of PEC system. In this study, through finite element simulation and experimental investigation, different optimization methods for PEC sensors are compared and studied. According to the eddy current detection principle, a two-dimensional finite element simulation model was established to study the influence of the shape and size parameters of cone-shaped PEC sensors. Then a cone-shaped PEC sensor was optimized by the orthogonal methodology and the response surface methodology, respectively. To compare the effectiveness of the optimization methods, two optimized sensors were fabricated. It was demonstrated that the combination of finite element method and response surface methodology was superior for improving the detection performance of the PEC sensor compared with the orthogonal methodology. The result also indicated that the developed cone-shaped PEC sensor had a stronger defect detection capability than cylindrical-shaped PEC sensors. The proposed optimization design method provides a feasible reference method for the design of PEC sensors and corresponding parameters.

Analysis of Eddy Current Testing Detection Ability to the Varied Longitudinal Cracks on Coated Weld Metal Tee Joint of 5083 Aluminum Ship Structure

Due to its service, crack sometimes occur on the coated 5083 aluminum weld metal. One method for finding crack under protective coating is by using eddy current testing (ECT). This method of nondestructive testing relies on a circular electrical path generated by the coils positioned just above the surface being examined. The purpose of this research is to analyze the sensitivity of ECT by using variety of crack dimensions on 5083 aluminum welded plate tee joint. Five test pieces, each 200 mm × 50 mm × 10 mm were used and each sample contain four cracks. Artificial cracks are fabricated using electrical discharge machining (EDM) with length and depth variations. Variations in crack length are 5.0 mm, 7.0 mm, 9.0 mm, and 15.0 mm, and variation in depth are 0.5 mm, 1.0 mm, 1.5 mm, 2.0 mm and 2.5 mm. Results obtained by the analysing height and average length of the crack signal indication are as follows: for 0.5 mm crack depth, the height of the crack signal is 5 mm; 1.0 mm depth is 11.75 mm; 1.5 mm depth is 19.75 mm; 2.0 mm depth is 26.5 mm and 2.5 mm depth is 31.25 mm. The degree of accuracy obtained for the detection of crack depth is 93.57%. For the detection of crack length, it is found that the measured average length of artificial cracks is 5 mm actual crack length has measured crack length of 6.32 mm; 7 mm actual crack length has measured crack length value of 7.18 mm; 9 mm actual crack length has a measured crack length value of 8.8 mm and 15 mm actual crack length has measured crack length of 14.48 mm. The degree of accuracy obtained for crack length detection is 91.31%.

Signal Processing and Defect Characterization of Pulsed Eddy Current Testing Based on Cross-Correlation

In order to solve the problems of the low signal-to-noise ratio and inaccurate feature extraction of time domain signal in pulsed eddy current detection, a method of signal processing and feature extraction for pulsed eddy current detection based on cross correlation is proposed. the pulsed eddy current testing of cracks in different sizes and positions of multi-layer aluminum alloy specimens is carried out by using magnetic differential probe based on Tunnel Magnetoresistance sensor (TMR). Experimental results show that compared with the traditional method, the proposed method can characterize the defects at different position depths more clearly and accurately, which improves the detection depth and accuracy of pulsed eddy current detection. According to the variation rule between the size and depth of the defect and the cross-correlation eigenvalue, the exponential change curve of peak-to-peak time of cross-correlation can be determined, which can effectively identify the defects exceeding the geometric size of threshold at different depths.

Defect type identification of thin-walled stainless steel seamless pipe based on eddy current testing

Aimed at eddy current detection of defects in thin-walled stainless steel seamless pipes, an effective detection method for identifying defect types is proposed. First, the empirical mode decomposition (EMD) method is used to process the collected eddy current signals and obtain the principal intrinsic mode function (IMF) components of different defects. The Hilbert-Huang transform (HHT) is used to extract the frequency-domain features of the principal IMF components, which are combined with the time-domain features to form an effective defect feature vector. Then, principal component analysis (PCA) is used to reduce the dimensions of the defect feature vector and the redundant information is removed to obtain the principal component vector of the defect. Finally, two radial basis function (RBF) neural networks are used to identify and classify the defect types and three error evaluation indicators are selected to evaluate the performance of the classification network models.

Design and Experimental Study of Array Eddy Current Sensor for Internal Inspection of Natural Gas Pipeline

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.

Research on Application of Pulsed Eddy Current Testing in Nuclear Power Plant Pipelines

The condensate pipelines, main water supply pipelines, drain pipelines, and partial extraction pipelines of nuclear power plants are all coated with coatings on the outside of the pipelines to improve heat exchange efficiency. At present, the detection methods of ferromagnetic pipelines are mainly conventional ultrasound and ultrasonic guided waves. It is necessary to remove the insulation layer of the outer wall of the pipeline before the inspection, which leads to a prolonged inspection period and increased labor costs. This paper uses the measured and calculated values of the induced voltage to establish the optimal parameter inversion problem and combines the coupling relationship between the parameters to propose a reliable pulsed eddy current detection method for the relative wall thickness of ferromagnetic pipes. Using the pulsed eddy current detection method for the relative wall thickness of ferromagnetic pipelines proposed in this paper, the scanning detection of nuclear power plant steel pipes is compared with conventional ultrasonic testing. The detection results are reliable and suitable for non-destructive testing and evaluation of nuclear power plant ferromagnetic pipeline wall thickness corrosion thinning.

Eddy current tomography for visualization of cracks in aircraft riveted joints

The control of the subsurface areas of metal products is necessary in many technological processes. So, for example, in aerospace technology it is essential to determine the presence of defects in aircraft engines. The same problems arise in chemical, power and other industries, which are letting out the highly technological equipment one of the widely known methods for inspecting metal products in the aviation industry is the eddy current method. This method is widely used to control small microscopic defects inside conductive materials. This method allows to ensure the safety of the operation of various products and devices in many areas of modern industry. An eddy current detector (probe) is a device, which induces eddy currents into metal objects and then detects the magnetic fields produced by these eddy currents. A magnetic field is created by a coil, or set of coils, through which a time-varying electrical current is driven. The frequency regime is sufficiently low, a few hertz to a few hundred kilohertz, so the targets of interest are within the near field of the transmitter. Considering the high conductivity of study samples, we can define that used waves in metals are located in the millimeter wave band. An eddy current imaging can be considered near-field imaging and a device allowing obtaining the eddy current images as a scanning near-field microscope. The obtained experimental results showed that the proposed tomographic method is effective for studying various complex inhomogeneities under the metal surface

Feature Engineering of Time-Domain Signals Based on Principal Component Analysis for Rebar Corrosion Assessment Using Pulse Eddy Current

Corrosion of steel rebars in reinforced concrete impacts structural integrity of the infrastructure. While several Non-Destructive Testing and Evaluation (NDT&E) techniques exist for corrosion monitoring in structures, there is a need for cost-effective solution for early detection of sub-surface corrosion of rebars in civil infrastructure. Here we present a low-cost corrosion sensing system based on pulsed eddy current detection using anisotropic magnetoresistive (AMR) sensor to detect the corrosion in steel reinforcing bars. A novel probe with large figure of merit ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$21.62\times6$ </tex-math></inline-formula> m <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{T}^{-1}$ </tex-math></inline-formula> ) is presented, that can detect corrosion in 20 mm diameter rebars at lift-off distances as high as 55 mm with low excitation current of 0.2 A. The sensitivity is enhanced by using area under the curve of various segments of the time-domain sensor output as features. Optimal feature selection and dimensionality reduction, as well as quantitative estimation of extent of corrosion are demonstrated using principal component analysis.

Eddy current detection of laser-dispersed markers as a new approach to determining the position of load supporting means

The logistic industry has a steady need for improved positioning of goods to keep commercial success. Next to high accuracy, a low maintenance system is needed to ensure the benefits of automation. While state of the art position determination is done by mechanical, optical, or hydraulic techniques, this research addresses a new approach using laser-dispersed position markers and contactless eddy current technology for detection. A fiber laser is used to create thin melt tracks on lifting profiles, and zirconium oxide powder is added to the melt to create a dispersed track as a position marker. The influence of the laser process parameters on the track width and surface topology is determined, as well as the influence on eddy current measurements. It has been found that increasing the laser power and the powder feed rate of zirconium oxide in the investigated range from 190 to 490 W and 1.16 to 3.6 g/min, respectively, increased the signal from the eddy current sensor unit. Positioning concepts are examined by moving the eddy current sensor above the lifting profile with speeds up to 4000 mm/min. The laser-dispersed markers are clearly recognizable in the sensor signal with a minimum distance of 2 mm from each other and an interspace of 0.8 mm from the lifting profile to the sensor head. The recognition error rate is quite low at around 0.0037%. However, the resolution, which can be derived from the eddy current sensor signal, is about 0.5 mm ± 0.11 mm. In order to gain insight into the suitability of the examined technology for forklifts, the eddy current sensor is mounted on the fork bracket and typical actions are simulated. Last, other applications for eddy current detection of laser-dispersed markers, such as storing and reading information for component identification, are demonstrated.

Composition of some metallic fragments found in food that are undetectable by magnetic or eddy currents equipment: A case study

Contamination of food with metallic fragments implies a serious risk to the end consumer. Therefore, that metallic waste must be detected and removed before that contaminated food arrives to the market. One of the cheapest and most common ways of dealing with this problem is the use of magnetic separators for ferromagnetic waste. If the waste has a non-ferromagnetic character eddy current metal detectors are a good alternative. However, depending on the composition and shape of the metallic fragments, its detection can be very difficult.This paper presents a study on the composition of some metal fragments, a hypodermic needle used during veterinary treatments and metallic wire, that were not detected by the magnetic separator nor by the eddy current sensors of a meat processing line. The composition of the fragments was analyzed by EDX Spectroscopy and compared with the results of a plain magnetic attraction test. The results show the non-detected fragments were made of stainless austenitic steels, which have a non-ferromagnetic character and a relatively low electric conductivity, making this material difficult to detect using magnetic means. To avoid this problem and guarantee the detectability, austenitic steels should, when possible, be substituted by ferritic or duplex stainless steels.

Intelligent embedded system for decision support in pulsed eddy current corrosion detection using Extreme Learning Machine

In this work an intelligent electronic system was proposed to generate, acquire and process Pulsed Eddy Currents (PEC) signals for corrosion detection in carbon steel pipes thermally insulated with composite coating. The system includes analog (excitation circuit and data acquisition) and digital (signal processing, feature extraction and decision support) sub-systems. The proposed signal processing chain comprises feature extraction using both discrete Fourier and Wavelet transforms, combined with information compaction by Principal Component Analysis (PCA) and decision support through intelligent classification techniques. Two neural network architectures were considered for classification, the traditional Multi-Layer Perceptron (MLP) and also the Extreme Learning Machine (ELM). The results obtained from thermally insulated carbon steel pipes subject to corrosion under isolation indicate the efficiency of the proposed method. Combining the ELM technique and data compaction it was possible to achieve a fast-training portable intelligent system for PEC evaluation and decision support.

Model Construction for Far Field Eddy Current Examination Simulation on Ferromagnetic Tubes

Ferromagnetic tubes are widely applied in fossil power plants such as waterfall tubes, overheat tubes or reheating tubes. Outer surface corrosion, wearing, depth reduction, cracks are common defects during manufacturing and long term operation. Eddy current detection is a traditional method for the examination of surface and near surface defects. However the efficiency is restricted by lift-off effect and skim effect. Far field eddy current overcomes the above disadvantages with high efficiency and fast examination speed and high sensitivity. In this paper, numerical simulation has been carried out to study the far field eddy current Detection for defects in small diameter ferromagnetic tubes in fossil power plants.

A review of two types of non-destructive testing technique for pressure pipelines

Pulsed eddy current testing (PECT) and electromagnetic ultrasonic non-destructive testing (NDT) techniques are important methods for detecting defects in pressure pipelines. Although these methods have the advantages of no contact requirement, fast detection and simple signal processing, there is a near-surface blind area in electromagnetic ultrasonic detection and pulsed eddy current detection cannot accurately detect deep locations due to the skin depth. However, these two techniques can be combined to potentially overcome their individual limitations. This paper presents an in-depth study of the use of pulsed eddy current testing and electromagnetic ultrasonic non-destructive testing techniques to detect defects in pipelines. Moreover, the basic principles, numerical simulation methods, testing systems and application characteristics of the individual methods and their combined use are discussed.

Characterization of image sequences of a defect using pulsed eddy current signals

Pulsed eddy current testing (PECT) has the advantages of rich information, efficiency and noncontact among defect nondestructive testing. Pulsed eddy current imaging technology also has a wide range of applications. However, the imaging method based on single feature is mostly adopted at this stage. In order to make better use of pulsed eddy current signals, signal slice based method was proposed for pulsed eddy current sequence imaging. Through the difference analysis of air-subtracted signal (ASS) and non-defect-subtracted signal (NDSS), sequence imaging in different ways is carried out. The influence of defects was explained by visualizing the diffusion of eddy currents in different specimens using a finite element model. ASS and NDSS image sequences were evaluated through image quality evaluation and quantitative identification. The result shows that there are some image frames in the image sequence that are better than the images generated by a single feature value in the image quality evaluation and quantitative analysis. It proves that the image sequence contains more defect information, which also illustrates the information richness of pulse eddy current detection.

Real-time defect identification of narrow overlap welds and application based on convolutional neural networks

To improve the quality of narrow overlap welds and reduce cost during the high-strength production, it is essential to detect weld defects promptly by identification of the type of defects to provide solution accordingly. This paper proposes an integrated weld defect identification approach combing eddy current detection with 3D laser scanning based on Convolutional Neural Networks (CNN). The detection principle and equipment of the two detection methods are introduced. To fit the training process of CNN, two set of detection signals are preprocessed: a two-dimensional time-frequency diagram for eddy current signals using continuous wavelet transform and for laser images, weld edges are extracted and divided by region using image convolution and combining with integral graph. CNN model VGG16 is trained afterwards with data collected from one local manufacturer in Shanghai. It is discovered that performance of eddy current and laser image identification on different types of weld defects is different, and the accuracy can be increased with the two methods combined. Last, to achieve real-time detection of narrow overlap welding, a two-stage defect recognition model is built which greatly improves the efficiency of weld defect identification without affecting the accuracy of weld defect identification.