Table of contents

Micro machining plays an important role in the manufacturing of miniature products which are made of various materials with complex 3D shapes and tight machining tolerance. To further improve the accuracy of a micro machining process without increasing the manufacturing cost of a micro machine tool, an effective machining error measurement method and a software-based compensation method are essential. To avoid introducing additional errors caused by the re-installment of the workpiece, the measurement and compensation method should be on-machine conducted. In addition, because the contour of a miniature workpiece machined with a micro machining process is very tiny, the measurement method should be non-contact. By integrating the image re-constructive method, camera pixel correction, coordinate transformation, the error identification algorithm, and trajectory auto-correction method, a vision-based error measurement and compensation method that can on-machine inspect the micro machining errors and automatically generate an error-corrected numerical control (NC) program for error compensation was developed in this study. With the use of the Canny edge detection algorithm and camera pixel calibration, the edges of the contour of a machined workpiece were identified and used to re-construct the actual contour of the work piece. The actual contour was then mapped to the theoretical contour to identify the actual cutting points and compute the machining errors. With the use of a moving matching window and calculation of the similarity between the actual and theoretical contour, the errors between the actual cutting points and theoretical cutting points were calculated and used to correct the NC program. With the use of the error-corrected NC program, the accuracy of a micro machining process can be effectively improved. To prove the feasibility and effectiveness of the proposed methods, micro-milling experiments on a micro machine tool were conducted, and the results have demonstrated the success of the micro-machining accuracy enhancement for micro machine tools.

The identification of flow pattern is a key issue in multiphase flow which is encountered in the petrochemical industry. It is difficult to identify the gas–liquid flow regimes objectively with the gas–liquid two-phase flow. This paper presents the feasibility of a clamp-on instrument for an objective flow regime classification of two-phase flow using an ultrasonic Doppler sensor and an artificial neural network, which records and processes the ultrasonic signals reflected from the two-phase flow. Experimental data is obtained on a horizontal test rig with a total pipe length of 21 m and 5.08 cm internal diameter carrying air-water two-phase flow under slug, elongated bubble, stratified-wavy and, stratified flow regimes. Multilayer perceptron neural networks (MLPNNs) are used to develop the classification model. The classifier requires features as an input which is representative of the signals. Ultrasound signal features are extracted by applying both power spectral density (PSD) and discrete wavelet transform (DWT) methods to the flow signals. A classification scheme of '1-of-C coding method for classification' was adopted to classify features extracted into one of four flow regime categories. To improve the performance of the flow regime classifier network, a second level neural network was incorporated by using the output of a first level networks feature as an input feature. The addition of the two network models provided a combined neural network model which has achieved a higher accuracy than single neural network models. Classification accuracies are evaluated in the form of both the PSD and DWT features. The success rates of the two models are: (1) using PSD features, the classifier missed 3 datasets out of 24 test datasets of the classification and scored 87.5% accuracy; (2) with the DWT features, the network misclassified only one data point and it was able to classify the flow patterns up to 95.8% accuracy. This approach has demonstrated the success of a clamp-on ultrasound sensor for flow regime classification that would be possible in industry practice. It is considerably more promising than other techniques as it uses a non-invasive and non-radioactive sensor.

Plenoptic PIV offers a simple, single camera solution for volumetric velocity measurements of fluid flow. However, due to the novel manner in which the particle images are acquired and processed, few references exist to aid in determining the resolution limits of the measurements. This manuscript provides a framework for determining the spatial resolution of plenoptic PIV based on camera design and experimental parameters. This information can then be used to determine the smallest length scales of flows that are observable by plenoptic PIV, the dynamic range of plenoptic PIV, and the corresponding uncertainty in plenoptic PIV measurements. A simplified plenoptic camera is illustrated to provide the reader with a working knowledge of the method in which the light field is recorded. Then, operational considerations are addressed. This includes a derivation of the depth resolution in terms of the design parameters of the camera. Simulated volume reconstructions are presented to validate the derived limits. It is found that, while determining the lateral resolution is relatively straightforward, many factors affect the resolution along the optical axis. These factors are addressed and suggestions are proposed for improving performance.

We introduce a new method for estimating fluid trajectories in time-resolved PIV. It relies on a Lucas–Kanade paradigm and consists in a simple and direct extension of a two-frame estimation with FOLKI-PIV (Champagnat et al 2011 Exp. Fluids50 1169–82). The so-called Lucas–Kanade Fluid Trajectories (LKFT) are assumed to be polynomial in time, and are found as the minimizer of a global functional, in which displacements are sought so as to match the intensities of a series of images pairs in the sequence, in the least-squares sense. All pairs involve the central image, similar to other recent time-resolved approaches (FTC (Lynch and Scarano 2013 Meas. Sci. Technol. 24 035305) and FTEE (Jeon et al 2014 Exp. Fluids55 1–16)). As switching from a two-frame to a time-resolved objective simply amounts to adding terms in a functional, no significant additional algorithmic element is required. Similar to FOLKI-PIV the method is very well suited for GPU acceleration, which is an important feature as computational complexity increases with the image sequence size. Tests on synthetic data exhibiting peak-locking show that increasing the image sequence size strongly reduces both associated bias and random error, and that LKFT has a remaining total error comparable to that of FTEE on this case. Results on case B of the third PIV challenge (Stanislas et al 2008 Exp. Fluids45 27–71) also show its ability to drastically reduce the error in situations with low signal-to-noise ratio. These results are finally confirmed on experimental images acquired in the near-field of a low Reynolds number jet. Strong reductions in peak-locking, spatial and temporal noise compared to two-frame estimation are also observed, on the displacement components themselves, as well as on spatial or temporal derivatives, such as vorticity and material acceleration.

In many situations, 3D velocity measurements in thin (∼1 mm) but wide (∼100  ×  100 mm²) flow channels is an important task. To resolve the in-plane and out-of-plane velocity gradients properly, a precise calibration is required, since 3D measurement approaches rely strongly on the accuracy of the calibration procedure. It is likely that calibration targets do not fit domains with small depths, due to their size. Furthermore, in fields where such measurements are of interest, the accessibility of the measurement volume is often limited or even impossible. To overcome these drawbacks, this paper introduces an in situ calibrated defocusing particle tracking velocimetry approach for wall-bounded measurement domains with depths in the low millimeter range. The calibration function for the particle depth location is directly derived from the particle image geometries and their displacements between two frames. Employing only a single camera, this defocusing approach is capable of measuring the air flow between two parallel glass plates at a distance of 1 mm with an average uncertainty of 2.43% for each track, relative to the maximum velocity. A tomographic particle tracking velocimetry measurement, serving as a benchmark for the single camera technique, reaches an average uncertainty of 1.59%. Altogether, with its straightforward set-up and without requiring a calibration target, this in situ calibrated defocusing approach opens new areas of application for optical flow velocimetry. In particular, for measurement domains with small optical windows and a lack of accessibility.

This paper discusses the propagation of the instantaneous uncertainty of PIV measurements to statistical and instantaneous quantities of interest derived from the velocity field. The expression of the uncertainty of vorticity, velocity divergence, mean value and Reynolds stresses is derived. It is shown that the uncertainty of vorticity and velocity divergence requires the knowledge of the spatial correlation between the error of the x and y particle image displacement, which depends upon the measurement spatial resolution. The uncertainty of statistical quantities is often dominated by the random uncertainty due to the finite sample size and decreases with the square root of the effective number of independent samples. Monte Carlo simulations are conducted to assess the accuracy of the uncertainty propagation formulae. Furthermore, three experimental assessments are carried out. In the first experiment, a turntable is used to simulate a rigid rotation flow field. The estimated uncertainty of the vorticity is compared with the actual vorticity error root-mean-square, with differences between the two quantities within 5–10% for different interrogation window sizes and overlap factors. A turbulent jet flow is investigated in the second experimental assessment. The reference velocity, which is used to compute the reference value of the instantaneous flow properties of interest, is obtained with an auxiliary PIV system, which features a higher dynamic range than the measurement system. Finally, the uncertainty quantification of statistical quantities is assessed via PIV measurements in a cavity flow. The comparison between estimated uncertainty and actual error demonstrates the accuracy of the proposed uncertainty propagation methodology.

The current state-of-the-art in cross-correlation based time-resolved particle image velocimetry (PIV) techniques are the fluid trajectory correlation, FTC (Lynch and Scarano 2013) and the fluid trajectory evaluation based on an ensemble-averaged cross-correlation, FTEE (Jeon et al 2014a). These techniques compute the velocity vector as a polynomial trajectory $\Gamma$ in space and time, enabling the extraction of beneficial quantities such as material acceleration whilst significantly increasing the accuracy of the particle displacement prediction achieved by standard two-frame PIV. In the context of time-resolved volumetric PIV, the drawback of trajectory computation is the computational expense of the three-dimensional (3D) cross-correlation, exacerbated by the requirement to perform N  −  1 cross-correlations, where N (for typically $5\leqslant N\leqslant 9$) is the number of sequential particle volumes, for each velocity field. Therefore, the acceleration of this calculation is highly desirable. This paper re-examines the application of two-dimensional (2D) cross-correlation methods to three-dimensional (3D) datasets by Bilsky et al (2011) and the binning techniques of Discetti and Astarita (2012). A new and robust version of the 2D methods is proposed and described, called fast 2D projection—re-projection (f2dpr). Performance tests based on computational time and accuracy for both two-frame and multi-frame PIV are carried out on synthetically generated data. The cases presented herein include uniaxial uniform linear displacements and shear, and simulated turbulence data. The proposed algorithm is shown to be in the order of 10 times faster than a standard 3D FFT without loss of precision for a wide range of synthetic test cases, while combining with the binning technique can yield 50 times faster computation. The algorithm is also applied to reconstructed synthetic turbulent particle fields to investigate reconstruction noise on its performance and no significant loss of precision is observed.

High-precision gears are required for advanced motion and power transmission. The reliability of the measured value becomes important as the gear accuracy increases, and the establishment of a traceability system is needed. Therefore, a high-precision gear measuring machine (GMM) with a smaller uncertainty is expected to improve the gear calibration uncertainty. For this purpose, we developed a prototype of a high-precision GMM that adopts a direct drive mechanism and other features. Then, the high measurement capability of the developed GMM was verified using gear artifacts. Recently, some new measurement methods using simple shapes such as spheres and planes have been proposed as standards. We have verified the tooth profile measurement using a sphere artifact and reported the results that the developed GMM had a high capability in tooth profile measurement. Therefore, we attempted to devise a new evaluation method for helix measurement using a wedge artifact (WA) whose plane was treated as the tooth flank, and the high measurement capability of the developed GMM was verified. The results will provide a part of information to fully assess measurement uncertainty as our future work. This paper describes the evaluation results of the developed GMM for helix measurement using both a helix artifact and the WA, and discusses the effectiveness of the WA as a new artifact to evaluate the GMMs.

A new technique based on digital holography and evanescent waves was developed for 3D measurements of the position of gold nanoparticles in water. In this technique, an intensity profile is taken from a holographic image of a gold particle. To detect the position of the gold particle with high accuracy, its holographic image is recorded on a nanosized step made of MEXFLON, which has a refractive index close to that of water, and the position of the particle is reconstructed by means of digital holography. The height of the nanosized step was measured by using a profilometer and the digitally reconstructed height of the glass substrate had good agreement with the measured value. Furthermore, this method can be used to accurately track the 3D position of a gold particle in water.

The color-coded 3D micro particle tracking velocimetry system (CC3DμPTV) is a volumetric velocimetry technique that uses the defocusing digital particle image velocimetry (DDPIV) approach to reconstruct the 3D location of the particle. It is suited for microscopic flow visualization because of the single camera configuration. However, several factors limit the performance of the system. In this study, the limitation of the CC3DμPTV is discussed in detail and a new concept of a multi-camera 3D μ-PTV system is proposed to improve the performance of the original CC3DμPTV system. The system utilizes two dichroic beam splitters to separate the incoming light into 3 spectral ranges, and image with three monochrome image sensors. The use of a color-matched light source, off-center individual pinhole and monochrome image sensors allow the system to achieve better sensitivity and optical resolution. The use of coherent lasers light sources with high-speed cameras improves the velocity measurement dynamic range. The performance of the proposed multi-spectral system is first evaluated with a simulation model based on the finite element method (FEM). The performance is also compared numerically with the CC3DμPTV system. The test results show significant improvements on the signal to noise ratio and optical resolution.

This paper presents a newly developed highly accurate interferometric 6° of freedom (DoF) measurement system with Ångström resolution for displacement and μrad resolution for angle measurement, respectively. The new interferometer is based on a modified homodyne Twyman–Green interferometer concept. It uses a novel signal acquisition and processing approach whereby a spatial interferogram is captured by a CMOS camera and the registered fringe pattern is transformed into its frequency spectrum [1]. The spectral representation of a movement of e.g. a positioning stage is analyzed for its major components: the phase information directly correlates with the displacement of the stage, while a possible rotational motion causes a shift in the frequency spectrum. The developed compact 6 DoF head uses multiple rays in parallel to detect x–y–z displacements and roll-pitch-yaw movements.

Obtaining pressure field data from particle image velocimetry (PIV) is an attractive technique in fluid dynamics due to its noninvasive nature. The application of this technique generally involves integrating the pressure gradient or solving the pressure Poisson equation using a velocity field measured with PIV. However, very little research has been done to investigate the dynamics of error propagation from PIV-based velocity measurements to the pressure field calculation. Rather than measure the error through experiment, we investigate the dynamics of the error propagation by examining the Poisson equation directly. We analytically quantify the error bound in the pressure field, and are able to illustrate the mathematical roots of why and how the Poisson equation based pressure calculation propagates error from the PIV data. The results show that the error depends on the shape and type of boundary conditions, the dimensions of the flow domain, and the flow type.

The laser beam drift is a main factor that influences laser collimation measurement accuracies. In such measurements, the common-path compensation method is an efficient way to eliminate errors which are normally produced by the laser beam drift. Based on our current common-path compensation system, compensations for the laser beam drift were studied by different laser beam radii and detectors. The measurements have shown that the compensation effect for 3 mm beam radius is better than the ones of 1.5 mm and 4.0 mm beam radii. Based on this, the ratio between the 3 mm beam radius and the total area of the quadrant detector, which is 36%, has indicated the best compensation effect.

We present a digital algorithm for measuring the phase of a sinusoidal signal that combines the modified digital fringe-counting method with two-sample zero crossing to enable sequential signal processing. This technique can be applied to a phase meter for measuring dynamic phase differences between two sinusoidal signals with high resolution, particularly for heterodyne interferometry. The floor noise obtained from a demonstration with an electrical apparatus is $5\times {{10}^{-8}}\,\text{rad}\text{/}{{\sqrt{\text{Hz}}}^{{}}}$ at frequencies above approximately 0.1 Hz for 80 kHz signal frequency. In addition, by applying this method to a commercial heterodyne interferometer with a modulation frequency of 80 MHz, the floor-noise level is confirmed to be $7\times {{10}^{-14}}\text{m}\text{/}{{\sqrt{\text{Hz}}}^{{}}}$ from 4 kHz to 1 MHz. We also confirm the validity of the algorithm by comparing its results with those from a standard homodyne interferometer for measuring shock-motion peak acceleration greater than $5000\,\text{m}\,{{\text{s}}^{-2}}$ and a 10 mm stroke.

The potential exploitation of thermoelectric modules into mass market applications such as exhaust gas heat recovery in combustion engines requires an accurate knowledge of their performance. Further expansion of the market will also require confidence on the results provided by suppliers to end-users. However, large variation in performance and maximum operating point is observed for identical modules when tested by different laboratories. Here, we present the first metrological study of the impact of mounting and testing procedures on the precision of thermoelectric modules measurement. Variability in the electrical output due to mechanical pressure or type of thermal interface materials is quantified for the first time. The respective contribution of the temperature difference and the mean temperature to the variation in the output performance is quantified. The contribution of these factors to the total uncertainties in module characterisation is detailed.

Aimed at solving the key problem in weak transient detection, the present study proposes a new transient feature extraction approach using the optimized Morlet wavelet transform, kurtosis index and soft-thresholding. Firstly, a fast optimization algorithm based on the Shannon entropy is developed to obtain the optimized Morlet wavelet parameter. Compared to the existing Morlet wavelet parameter optimization algorithm, this algorithm has lower computation complexity. After performing the optimized Morlet wavelet transform on the analyzed signal, the kurtosis index is used to select the characteristic scales and obtain the corresponding wavelet coefficients. From the time-frequency distribution of the periodic impulsive signal, it is found that the transient signal can be reconstructed by the wavelet coefficients at several characteristic scales, rather than the wavelet coefficients at just one characteristic scale, so as to improve the accuracy of transient detection. Due to the noise influence on the characteristic wavelet coefficients, the adaptive soft-thresholding method is applied to denoise these coefficients. With the denoised wavelet coefficients, the transient signal can be reconstructed. The proposed method was applied to the analysis of two simulated signals, and the diagnosis of a rolling bearing fault and a gearbox fault. The superiority of the method over the fast kurtogram method was verified by the results of simulation analysis and real experiments. It is concluded that the proposed method is extremely suitable for extracting the periodic impulsive feature from strong background noise.

The use of x-ray computed tomography for dimensional measurements associated with engineering applications has flourished in recent years. However, error sources associated with the technology are not well understood. In this paper, a novel two-sphere reference sample has been developed and used to investigate the stability of the imaging system that consists of an x-ray tube and a detector. In contrast with other research work reported, this work considered relative positional variation along the x-, y- and z-axes. This sample is a significant improvement over the one sphere sample proposed previously, which can only be used to observe the stability of the imaging system along x- and y-axes. Temperature variations of different parts of the system have been monitored and the relationship between temperature variations and x-ray image stability has been studied. Other effects that may also influence the stability of the imaging system have been discussed. The proposed reference sample and testing method are transferable to other types of x-ray computed tomography systems, for example, systems with transmission targets and systems with sub-micrometre focal spots.

Roughness parameters that characterize contacting surfaces with regard to friction and wear are commonly stated without uncertainties, or with an uncertainty only taking into account a very limited amount of aspects such as repeatability of reproducibility (homogeneity) of the specimen. This makes it difficult to discriminate between different values of single roughness parameters.

Therefore uncertainty assessment methods are required that take all relevant aspects into account. In the literature this is rarely performed and examples specific for parameters used in friction and wear are not yet given.

We propose a procedure to derive the uncertainty from a single profile employing a statistical method that is based on the statistical moments of the amplitude distribution and the autocorrelation length of the profile. To show the possibilities and the limitations of this method we compare the uncertainty derived from a single profile with that derived from a high statistics experiment.

In this paper, we present a cantilever-probe system excited by a piezoelectric actuator, and use it to measure the dynamic mechanical properties of a micro- and nanoscale fiber. Coupling the fiber to the free end of the cantilever probe, we found the dynamic stiffness and damping coefficient of the fiber from the resonance frequency and the quality factor of the fiber-cantilever-probe system. The properties of Bacillus subtilis fibers measured using our proposed system agreed with tensile measurements, validating our method. Our measurements show that the piezoelectric actuator coupled to cantilever probe can be made equivalent to a clamped cantilever with an effective length, and calculated results show that the errors of measured natural frequency of the system can be ignored if the coupled fiber has an inclination angle of alignment of less than 10°. A sensitivity analysis indicates that the first or second resonant mode is the sensitive mode to test the sample's dynamic stiffness, while the damping property has different sensitivities for the first four modes. Our theoretical analysis demonstrates that the double-cantilever probe is also an effective sensitive structure that can be used to perform dynamic loading and characterize dynamic response. Our method has the advantage of using amplitude-frequency curves to obtain the dynamic mechanical properties without directly measuring displacements and forces as in tensile tests, and it also avoids the effects of the complex surface structure and deformation presenting in contact resonance method. Our method is effective for measuring the dynamic mechanical properties of fiber-like one-dimensional (1D) materials.

High-accuracy 3D measurement based on binocular vision system is heavily dependent on the accurate calibration of two rigidly-fixed cameras. In most traditional calibration methods, stereo parameters are iteratively optimized through the forward imaging process (FIP). However, the results can only guarantee the minimal 2D pixel errors, but not the minimal 3D reconstruction errors. To address this problem, a simple method to calibrate a stereo rig based on the backward projection process (BPP) is proposed. The position of a spatial point can be determined separately from each camera by planar constraints provided by the planar pattern target. Then combined with pre-defined spatial points, intrinsic and extrinsic parameters of the stereo-rig can be optimized by minimizing the total 3D errors of both left and right cameras. An extensive performance study for the method in the presence of image noise and lens distortions is implemented. Experiments conducted on synthetic and real data demonstrate the accuracy and robustness of the proposed method.

A morphological filter is proposed to obtain a high-accuracy roundness measurement based on the four-parameter roundness measurement model, which takes into account eccentricity, probe offset, probe tip head radius and tilt error. This paper analyses the sample angle deviations caused by the four systematic errors to design a morphological filter based on the distribution of the sample angle. The effectiveness of the proposed method is verified through simulations and experiments performed with a roundness measuring machine. Compared to the morphological filter with the uniform sample angle, the accuracy of the roundness measurement can be increased by approximately 0.09 μm using the morphological filter with a non-uniform sample angle based on the four-parameter roundness measurement model, when eccentricity is above 16 μm, probe offset is approximately 1000 μm, tilt error is approximately 1'', the probe tip head radius is 1 mm and the cylindrical component radius is approximately 37 mm. The accuracy and reliability of roundness measurements are improved by using the proposed method for cylindrical components with a small radius, especially if the eccentricity and probe offset are large, and the tilt error and probe tip head radius are small. The proposed morphological filter method can be used for precision and ultra-precision roundness measurements, especially for functional assessments of roundness profiles.

This paper presents a computational model written in Modelica for the high pressure piston prover (HPPP) used as the national primary standard for high pressure natural gas flow metering in Germany. With a piston prover the gas flow rate is determined by measuring the time a piston needs to displace a certain volume of gas in a cylinder. Fluctuating piston velocity during measurement can be a significant source of uncertainty if not considered in an appropriate way. The model was built to investigate measures for the reduction of this uncertainty. Validation shows a good compliance of the piston velocity in the model with measured data for certain volume flow rates. Reduction of the piston weight, variation of the start valve switching time and integration of a flow straightener were found to reduce the piston velocity fluctuations in the model significantly. The fast and cost effective generation of those results shows the strength of the used modelling approach.

This paper presents a novel orientation method for two laser trackers using on-board targets attached to the tracker head and rotating with it. The technique extends an existing method developed for theodolite intersection systems which are now rarely used. This method requires only a very narrow space along the baseline between the instrument heads, in order to establish the orientation relationship. This has potential application in environments where space is restricted. The orientation parameters can be calculated by means of two-face reciprocal measurements to the on-board targets, and measurements to a common point close to the baseline. An accurate model is then applied which can be solved through nonlinear optimization. Experimental comparison has been made with the conventional orientation method, which is based on measurements to common intersection points located off the baseline. This requires more space and the comparison has demonstrated the feasibility of the more compact technique presented here. Physical setup and testing suggest that the method is practical. Uncertainties estimated by simulation indicate good performance in terms of measurement quality.

The real-time and high-precision trajectory prediction of a moving object is a core technology in the field of aerospace engineering. The real-time monitoring and tracking technology are also significant guarantees of aerospace equipment. A dynamic trajectory prediction method called grey dynamic filter (GDF) which combines the dynamic measurement theory and grey system theory is proposed. GDF can use coordinates of the current period to extrapolate coordinates of the following period. At meantime, GDF can also keep the instantaneity of measured coordinates by the metabolism model. In this paper the optimal model length of GDF is firstly selected to improve the prediction accuracy. Then the simulation for uniformly accelerated motion and variably accelerated motion is conducted. The simulation results indicate that the mean composite position error of GDF prediction is one-fifth to that of Kalman filter (KF). By using a spacecraft landing experiment, the prediction accuracy of GDF is compared with the KF method and the primitive grey method (GM). The results show that the motion trajectory of spacecraft predicted by GDF is much closer to actual trajectory than the other two methods. The mean composite position error calculated by GDF is one-eighth to KF and one-fifth to GM respectively.

In-cylinder flow measurements are necessary to gain a fundamental understanding of swirl-supported, light-duty Diesel engine processes for high thermal efficiency and low emissions. Planar particle image velocimetry (PIV) can be used for non-intrusive, in situ measurement of swirl-plane velocity fields through a transparent piston. In order to keep the flow unchanged from all-metal engine operation, the geometry of the transparent piston must adapt the production-intent metal piston geometry. As a result, a temporally- and spatially-variant optical distortion is introduced to the particle images. To ensure reliable measurement of particle displacements, this work documents a systematic exploration of optical distortion quantification and a hybrid back-projection procedure that combines ray-tracing-based geometric and in situ manual back-projection approaches.

The proposed hybrid back-projection method for the first time provides a time-efficient and robust way to process planar PIV measurements conducted in an optical research engine with temporally- and spatially-varying optical distortion. This method is based upon geometric ray tracing and serves as a universal tool for the correction of optical distortion with an arbitrary but axisymmetric piston crown window geometry. Analytical analysis demonstrates that the ignorance of optical distortion change during the PIV laser temporal interval may induce a significant error in instantaneous velocity measurements. With the proposed digital dewarping method, this piston-motion-induced error can be eliminated. Uncertainty analysis with simulated particle images provides guidance on whether to back-project particle images or back-project velocity fields in order to minimize dewarping-induced uncertainties. The optimal implementation is piston-geometry-dependent. For regions with significant change in nominal magnification factor, it is recommended to apply the proposed back-projection approach to particle images prior to PIV interrogation. For regions with significant dewarping-induced particle elongation (${{E}_{\text{p}}}>3$), it is recommended to apply the proposed dewarping method to the vector fields resulting from PIV interrogation of raw particle image pairs.

A new scheme for methane remote sensing is presented. Unlike a standard published remote sensor based on wavelength modulation spectroscopy (WMS), a reference cell is inserted into the measuring optical path. This scheme inherits the merits of WMS and can achieve high signal-to-noise ratio especially in a low concentration environment. Experimental results show that the presented remote sensor can detect ambient methane with a detection limit of 5 ppm m (parts per million · meter) at a distance of 10 m and 16 ppm m for 20 m. A methane leak test shows the sensor can detect a methane leak of 15 ml min⁻¹ within a range up to 37 m.

The microscale schlieren technique provides a means for a non-invasive, full-field measurement for mixing microfluidics with excellent sensitivity and resolution. Nevertheless, an out-of-focus effect due to microscopic optics may lead to undesirable errors in quantifying the gradient information at high degrees of magnification. If the channel in the microfluidic device under study is too deep, light deflection caused by inhomogeneity located far from the focal plane may contributes little to the intensity change on the image plane. To address this issue, we propose the use of a weighting function that approximates a Gaussian profile with an optical-system-dependable width. We assume that the resultant intensity change is proportional to a weighted sum of the gradient across the channel depth and acquire micro-schlieren images of fluid mixing in a T-junction microchannel at various positions along the optical axis. For each objective, the width of the weighting function is then determined iteratively by curve fitting the ratio of changes in grayscale readouts for out-of-focus and focus micro-schlieren images. The standard deviation in the Gaussian distribution facilitates the quantification of the out-of-focus effect. In addition, we measure the sensitivities of a microscale schlieren system equipped with different objectives and compare the values to the model. Despite its better resolution, we find that an objective with higher magnification suffers from a more severe out-of-focus effect and a loss of sensitivity. Equations are proposed for estimations of the standard deviation and the sensitivity of microscale schlieren measurements. The outcome will facilitate the selection of proper microchannel depths for various microscale schlieren systems or vice versa, thus improving the precision of micro-schlieren measurements in microfluidic devices.

The multi-frequency fringe-projection phase unwrapping method (MFPPUM) is a typical phase unwrapping algorithm for fringe projection profilometry. It has the advantage of being capable of correctly accomplishing phase unwrapping even in the presence of surface discontinuities. If the fringe frequency ratio of the MFPPUM is too large, fringe order error (FOE) may be triggered. FOE will result in phase unwrapping error. It is preferable for the phase unwrapping to be kept correct while the fewest sets of lower frequency fringe patterns are used. To achieve this goal, in this paper a parameter called fringe order inaccuracy (FOI) is defined, dominant factors which may induce FOE are theoretically analyzed, a method to optimally select the fringe periods for the MFPPUM is proposed with the aid of FOI, and experiments are conducted to research the impact of the dominant factors in phase unwrapping and demonstrate the validity of the proposed method. Some novel phenomena are revealed by these experiments. The proposed method helps to optimally select the fringe periods and detect the phase unwrapping error for the MFPPUM.

The identification process based on measuring the level of haemoglobin and the classification of red blood cells using microscopic examination of blood smears is the principal way to diagnose anaemia. This paper presents a proposed algorithm for detecting some anaemia types like sickle and elliptocytosis and trying to count them with healthy ones in human red blood smears based on the circular Hough transform and some morphological tools. Some cells with unknown shapes (not platelets or white cells) also have been detected. The extracted data from the detection process has been analyzed by neural network. The experimental results have demonstrated high accuracy, and the proposed algorithm has achieved the highest detection of around 98.9% out of all the cells in 27 microscopic images. Effectiveness rates up to 100%, 98%, and 99.3% have been achieved by using neural networks for sickle, elliptocytosis and cells with unknown shapes, respectively.

In this paper, we propose a large-scale and non-contact surface topography measurement method using a non-contact scanning probe microscopy (SPM) technique, scanning ion conductance microscopy (SICM), combined with the sub-aperture stitching technique. The phase correlation techniques were first applied to the three-dimensional (3D) images measured by the SICM to acquire an initially coarse stitching position. Then the tip–tilt compensated sub-aperture stitching algorithm is utilized to eliminate tilts and translations among adjacent images and expand the lateral measuring range of the existing hopping mode SICM system. This SICM and the stitching based method has been used to measure some large-scale samples (micrometer to millimeter scale) in a non-contact, quantitative and high resolution way. Simulation and experimental results on these samples verify the feasibility of this method and the effectiveness of the stitching algorithm. A measuring range of 1.08 mm  ×  0.55 mm and a lateral resolution of 100 nm or even higher were obtained in these experiments. Compared with atomic force microscopy (AFM), the non-contact feature of the proposed method ensures less damage to the surface topography. The non-optical feature makes the data stitching simpler than the existing optical microscopic methods, which need consider how to compensate the vignetting effect caused by the inhomogeneity of light.

Yarn density is always considered as the fundamental structural parameter used for the quality evaluation of woven fabrics. The conventional yarn density measurement method is based on one-side analysis. In this paper, a novel density measurement method is developed for yarn-dyed woven fabrics based on a dual-side fusion technique. Firstly, a lab-used dual-side imaging system is established to acquire both face-side and back-side images of woven fabric and the affine transform is used for the alignment and fusion of the dual-side images. Then, the color images of the woven fabrics are transferred from the RGB to the CIE-Lab color space, and the intensity information of the image extracted from the L component is used for texture fusion and analysis. Subsequently, three image fusion methods are developed and utilized to merge the dual-side images: the weighted average method, wavelet transform method and Laplacian pyramid blending method. The fusion efficacy of each method is evaluated by three evaluation indicators and the best of them is selected to do the reconstruction of the complete fabric texture. Finally, the yarn density of the fused image is measured based on the fast Fourier transform, and the yarn alignment image could be reconstructed using the inverse fast Fourier transform. Our experimental results show that the accuracy of density measurement by using the proposed method is close to 99.44% compared with the traditional method and the robustness of this new proposed method is better than that of conventional analysis methods.

In this paper, we present a 3D surface imaging system based on the well-known phase shift profilometry. To yield the analytical solutions, four shifted phases and three high carrier frequencies are used to compute the phase map and reduce the noises that are caused by the inherent optical aberrations and external influences, e.g. different illumination light sources, uneven intensity distribution and automatic image processing algorithms. To reduce the system noise, we propose to model the pattern of the calibration grid in a virtual space. To obtain the modeled pattern, we use a plane to intercept the rays that are modeled by the proposed angle modeling method. In the world coordinate system, the angle and the pattern are computed based on the calibration data. A registration method is used to transform the modeled pattern in the virtual space to the ideal pattern in the world coordinate system by computing the least squared errors between the true points in the modeled pattern and the measured points in the practical pattern. The modeled (true) points are used for re-calibration of the 3D imaging system. Experimental results showed that the measurement accuracy increases considerably and the MSE is reduced from 0.95 mm to 0.65 mm (32% average error decrease) after replacing the measured points with the true points for calibration.

No consensus has been reached so far about the hydrogen anomaly problem in Compton scattering of neutrons, although strongly reduced H cross-sections were first reported almost 20 years ago. Over the years, this phenomenon has been observed in many different hydrogen-containing materials. Here, we use yttrium hydrides as test objects, YH₂, YH₃, YD₂ and YD₃, Y(H_xD_1−x)₂ and Y(H_xD_1−x)₃, for which we observe H anomalies increasing with transferred momentum q. We also observe reduced deuteron cross-sections in YD₂ and YD₃ and have followed those up to scattering angles of 140° corresponding to high momentum transfers. In addition to data taken using the standard Au-197 foils for neutron energy selection, the present work includes experiments with Rh-103 foils and comparisons were also made with data from different detector setups.

The H and D anomalies are discussed in terms of the different models proposed for their interpretation. The 'electron loss model' (which assumes energy transfer to excited electrons) is contradicted by the present data, but it is shown here that exchange effects in scattering from two or more protons (or deuterons) in the presence of large zero-point vibrations, can explain quantitatively the reduction of the cross-sections as well as their q-dependence. Decoherence processes also play an essential role. In a scattering time representation, shake-up processes can be followed on the attosecond scale. The theory also shows that large anomalies can appear only when the neutron coherence lengths (determined by energy selection and detector geometry) are about the same size as the distance between the scatterers.

As quality control of micro devices and early detection of micro defects in these devices are becoming increasingly important, the demand for a fast and automated online inspection technique to detect micro defects with high spatial resolution is increasing. In this study, a reference-free micro defect visualization algorithm is developed based on laser scanning thermography to detect micro defects in devices instantaneously and automatically with high spatial resolution. A pulse modulated continuous wave laser generates thermal waves in a target device, and the corresponding thermal responses are recorded by an infrared (IR) camera. When the thermal wave encounters a micro defect, the propagation of the thermal wave is blocked at the interface of the micro defect. The blockage of the thermal wave is detected by the proposed reference-free micro defect visualization algorithm. First, an edge detection algorithm is applied to a raw thermal image obtained at a specific time point to extract the thermal discontinuities formed at the boundaries of the defect. The edge images obtained from all time sequences are then assembled into a single accumulated edge image to accentuate defect-induced thermal disturbances in the form of edge features. Finally, the accumulated edge image is automatically processed using a binary imaging algorithm to visualize the micro defect in the target device. The performance of the proposed reference-free micro defect visualization algorithm is examined using two types of specimens, semiconductor chips and ceramic-epoxy composites. The proposed algorithm successfully diagnoses micro defects ranging from 4 μm to 40 μm in width.

The objective of this study was to provide guidance on material specifications for powders used in laser powder bed fusion based additive manufacturing (AM) processes. The methodology was to investigate how different material property assumptions in a simulation affect meltpool prediction and by corrolary how different material properties affect meltpool formation in AM processes. The sensitvity of meltpool variations to each material property can be used as a guide to help drive future research and to help prioritize material specifications in requirements documents. By identifying which material properties have the greatest affect on outcomes, metrology can be tailored to focus on those properties which matter most; thus reducing costs by eliminating unnecessary testing and property charaterizations. Futhermore, this sensitivity study provides insight into which properties require more accurate measurements, thus motivating development of new metrology methods to measure those properties accurately.

It is well known that, in excitable cells, the dynamics of the ion currents (I_i) is extremely important to determine both the magnitude and time course of an action potential (A_p). To observe these two processes simultaneously, we cultured NG108-15 cells over a multi-walled carbon nanotubes electrode (MWCNTe) surface and arranged a two independent Patch Clamp system configuration (Bi-Patch Clamp). The first system was used in the voltage or current clamp mode, using a glass micropipette as an electrode. The second system was modified to connect the MWCNTe to virtual ground. While the A_p was recorded through the micropipette electrode, the MWCNTe was used to measure the underlying whole-cell current. This configuration allowed us to record both the membrane voltage (V_m) and the current changes simultaneously. Images acquired by atomic force microscopy (AFM) and scanning electron microscopy (SEM) indicate that cultured cells developed a complex network of neurites, which served to establish the necessary close contact and strong adhesion to the MWCNTe surface. These features were a key factor to obtain the recording of the whole-cell I_i with a high signal to noise ratio (SNR). The experimental results were satisfactorily reproduced by a theoretical model developed to simulate the proposed system. Besides the contribution to a better understanding of the fundamental mechanisms involved in cell communication, the developed method could be useful in cell physiology studies, pharmacology and diseases diagnosis.

An entirely pressure-based vortex-shedding meter has been designed for use in practical time-dependent flows. The meter is capable of measuring mass-flow rate in variable density gases in spite of the fact that fluid temperature is not directly measured. Unlike other vortex meters, a pressure based meter is incredibly robust and may be used in industrial type flows; an environment wholly unsuitable for hot-wires for example. The meter has been tested in a number of static and dynamic flow cases, across a range of mass-flow rates and pressures. The accuracy of the meter is typically better than about 3% in a static flow and resolves the fluctuating mass-flow with an accuracy that is better than or equivalent to a hot-wire method.

Confocal fluorescence microscopy (CFM) is widely used in biological sciences because of its enhanced 3D resolution that allows image sectioning and removal of out-of-focus blur. This is achieved by rejection of the light outside a detection pinhole in a plane confocal with the illuminated object. In this paper, an alternative detection arrangement is examined in which the entire detection/image plane is recorded using an array detector rather than a pinhole detector. Using this recorded data an attempt is then made to recover the object from the whole set of recorded photon array data; in this paper maximum-likelihood estimation has been applied. The recovered object estimates are shown (through computer simulation) to have good resolution, image sectioning and signal-to-noise ratio compared with conventional pinhole CFM images.

We present the design, construction and test of an automated electronic controller for a Langmuir plasma probe. The novel aspect of this system lies in the isolation of the high voltage present in the discharge from the grounded reference of the controller. This controller detects currents over the range from  ±1 μA to  ±50 mA, using dynamic and automated switching of a transresistance amplifier. This automated Langmuir probe (LP) system has been successfully tested in a glow discharge in argon at 0.8 and 10 Torr.