Absolute Phase Information Research Articles

A Y-shaped network based single-shot absolute phase recovery method for fringe projection profilometry

Fringe projection profilometry (FPP) is a widely used non-contact 3D measurement method. Though maturing in the last decade, it remains a significant challenge when facing the phase unwrapping of measured object surfaces in a single-shot measurement setting. With the rapid development of deep learning techniques, the adoption of a data-driven approach is gaining popularity in the field of optical metrology. This study proposes a new absolute phase recovery method based on the devised single-stage deep learning network. The aim is to ensure high-quality absolute phase recovery from a single-shot fringe projection measurement. Unlike most existing approaches, where the numerators and denominators of the wrapped phases and the fringe orders are predicted in various stages, the proposed method acquires the wrapped phases and the corresponding fringe orders within a single network, i.e. it can predict both wrapped phases and the corresponding fringe orders directly and simultaneously from the single fringe pattern projected in the single-shot mode based on a unified Y-shaped network. Experiments on benchmark datasets and models have demonstrated the effectiveness and efficiency of the technique, especially in terms of high-quality recovery of absolute phase information by using the lightweight single-stage network, and enabling the FPP-based phase 3D measurements in an online manner.

Performance Evaluation of ST-Based Methods for Simulating and Analyzing Power Quality Disturbances

Abstract The complexity of power quality disturbances (PQDs) is a significant risk factor in the electricity sector. An accurate and fast analysis of these disturbances provides crucial information to cover all the issues related to power quality. The main objective of this study is to explore a new analytic technique, including all kinds of disturbances that can appear in electrical networks, that differs from previous technologies such as the Fourier transform. Three methods based on the Stockwell transform, namely, the discrete orthonormal Stockwell transform (DOST), discrete cosine Stockwell transform (DCST), and discrete cosine transform (DCT), were used to analyze PQDs in time–frequency representation. These methods diagnose the disturbance's signal properties, which are dependent on resolution and absolute phase information. Nine PQDs, including normal sine waves, were mathematically modeled and used to evaluate the proposed methods. All the methods can effectively simulate and analyze PQDs. Among them, DOST is the most effective in providing clear and high-resolution time–frequency representations of signals. The classification of disturbances was fulfilled based on statistical features extracted from matrices derived from Stockwell transform-based methods, such as analytic approaches (mean, variation, standard deviation, entropy, skewness, and kurtosis). Neural networks, a method utilizing intelligence classifiers, were used for pattern recognition, and the patterns of the different methods were compared. Simulation results proved that DOST needs fewer samples than other methods; its capability to deal with signals in time–frequency resolution is also more viable. The neural network classifier has a higher accuracy rate than the K-nearest neighbor and decision tree methods and approximates the support vector machine method.

Use of mesh phasing to locate faulty planet gears

Abstract It is a challenge to determine by vibration analysis which planet gear carries a fault due to the complex layout of planetary gearboxes. In this study, we explain for the first time the possibility of using mesh phasing for distinguishing between faults on different planet gears. It has been found that, due to mesh phasing relationships, the vibration signals recorded on a planetary gearbox test rig exhibit different characteristics depending on the position of the faulty gear. These tests used localised seeded spalls giving impulsive signals, and it was found that due to the sequential mesh phasing arrangement, the timing of the fault-related impulse responses, as measured relative to the phase of the gearmesh component, depends on which planet is faulty. These timing differences can also give rise to different levels of asymmetry in the signal. This paper proposes a phase-based approach to differentiate and locate the faulty planet gear position using vibration response signals, and an indicator is developed for this purpose. With the assistance of absolute phase information, acquired through a tachometer on the planet carrier, the phase indicator is able to locate the position of the faulty gear. The approach has been applied to recorded experimental signals and it is found that the method can diagnose the position of the faulty gear effectively.

Improved phase-coding methods with fewer patterns for 3D shape measurement

Absolute phase information is required when multiple separated objects are being measured. The recent proposed phase-coding method can effectively achieve absolute phase retrieval by embedding the fringe order information in phase domain. However, it suffers from the limitation of codewords and the requirement of more coding patterns. To overcome these problems, this paper proposed several improved phase-coding methods to solve the absolute phase with fewer patterns. The four-frame and five-frame method are suitable when the fringes are sparse, since they can respectively encode N∕2 and N fringe periods(generally N≤16). If really dense fringe patterns with more than N periods are required, the improved two-step phase-coding algorithm can be adopted since it can encode about N2∕2 fringe periods. Experiments were conducted and the results verify the success of the proposed methods.

Cardiac arrhythmia beat classification using DOST and PSO tuned SVM

Background and objectiveThe increase in the number of deaths due to cardiovascular diseases (CVDs) has gained significant attention from the study of electrocardiogram (ECG) signals. These ECG signals are studied by the experienced cardiologist for accurate and proper diagnosis, but it becomes difficult and time-consuming for long-term recordings. Various signal processing techniques are studied to analyze the ECG signal, but they bear limitations due to the non-stationary behavior of ECG signals. Hence, this study aims to improve the classification accuracy rate and provide an automated diagnostic solution for the detection of cardiac arrhythmias. MethodsThe proposed methodology consists of four stages, i.e. filtering, R-peak detection, feature extraction and classification stages. In this study, Wavelet based approach is used to filter the raw ECG signal, whereas Pan–Tompkins algorithm is used for detecting the R-peak inside the ECG signal. In the feature extraction stage, discrete orthogonal Stockwell transform (DOST) approach is presented for an efficient time-frequency representation (i.e. morphological descriptors) of a time domain signal and retains the absolute phase information to distinguish the various non-stationary behavior ECG signals. Moreover, these morphological descriptors are further reduced in lower dimensional space by using principal component analysis and combined with the dynamic features (i.e based on RR-interval of the ECG signals) of the input signal. This combination of two different kinds of descriptors represents each feature set of an input signal that is utilized for classification into subsequent categories by employing PSO tuned support vector machines (SVM). ResultsThe proposed methodology is validated on the baseline MIT-BIH arrhythmia database and evaluated under two assessment schemes, yielding an improved overall accuracy of 99.18% for sixteen classes in the category-based and 89.10% for five classes (mapped according to AAMI standard) in the patient-based assessment scheme respectively to the state-of-art diagnosis. The results reported are further compared to the existing methodologies in literature. ConclusionsThe proposed feature representation of cardiac signals based on symmetrical features along with PSO based optimization technique for the SVM classifier reported an improved classification accuracy in both the assessment schemes evaluated on the benchmark MIT-BIH arrhythmia database and hence can be utilized for automated computer-aided diagnosis of cardiac arrhythmia beats.

Pixel-to-pixel correspondence alignment method of a 2CCD camera by using absolute phase map

An alignment method of a 2CCD camera to build pixel-to-pixel correspondence between the infrared (IR) CCD sensor and the visible CCD sensor by using the absolute phase data is presented. Vertical and horizontal sinusoidal fringe patterns are generated by software and displayed on a liquid crystal display screen. The displayed fringe patterns are captured simultaneously by the IR sensor and the visible sensor of the 2CCD camera. The absolute phase values of each pixel at IR and visible channels are calculated from the captured fringe pattern images by using Fourier transform and the optimum three-fringe number selection method. The accurate pixel corresponding relationship between the two sensors can be determined along the vertical and the horizontal directions by comparing the obtained absolute phase data in IR and visible channels. Experimental results show the high accuracy, effectiveness, and validity of the proposed 2CCD alignment method. By using the continuous absolute phase information, this method can determine the pixel-to-pixel correspondence with high resolution.

Robust self-calibration three-dimensional shape measurement in fringe-projection photogrammetry

Commonly, fringe-projection photogrammetry involves two independent stages: system calibration and measurement. The measurement accuracy largely depends on the calibration procedure. However, the results of system calibration may be unstable in different occasions. In this Letter, we propose a robust self-calibration 3D shape measurement in fringe-projection photogrammetry by combining control and measurement points. The control points with known 3D coordinates are provided on the checkerboard, and the measurement points are identified by absolute phase information in the deformed fringes. The introduction of control points in the nonlinear collinearity equations can be regarded as invariant in the optimization procedure, which enhances the measurement robustness. Compared to the binocular model in fringe-projection technique, moreover, multiple-view ray intersection is utilized to reflect the advantage of photogrammetry in the fringe-projection 3D measurement.

LOCALIZING SAGITTARIUS A* AND M87 ON MICROARCSECOND SCALES WITH MILLIMETER VERY LONG BASELINE INTERFEROMETRY

ABSTRACT With the advent of the Event Horizon Telescope (EHT), a millimeter/submillimeter very long baseline interferometer (VLBI), it has become possible to image a handful of black holes with sub-horizon resolutions. However, these images do not translate into microarcsecond absolute positions due to the lack of absolute phase information when an external phase reference is not used. Due to the short atmospheric coherence time at these wavelengths, nodding between the source and phase reference is impractical. However, here we suggest an alternative scheme which makes use of the fact that many of the VLBI stations within the EHT are arrays in their own right. With this we show that it should be possible to absolutely position the supermassive black holes at the centers of the Milky Way (Sgr A*) and M87 relative to nearby objects with precisions of roughly 1 μas. This is sufficient to detect the perturbations to Sgr A*'s position resulting from interactions with the stars and stellar-mass black holes in the Galactic cusp on year timescales, and severely constrain the astrophysically relevant parameter space for an orbiting intermediate-mass black hole, implicated in some mechanisms for producing the young massive stars in the Galactic center. For M87, it allows the registering of millimeter images, in which the black hole may be identified by its silhouette against nearby emission, and existing larger-scale radio images, eliminating present ambiguities in the nature of the radio core and inclination, opening angle, and source of the radio jet.

PHASE DETECTION WITH SUB-NANOMETER SENSITIVITY USING POLARIZATION QUADRATURE ENCODING METHOD IN OPTICAL COHERENCE TOMOGRAPHY

This paper presents a phase-resolved optical coherence tomography (OCT) system that uses the polarization quadrature encoding method in a two-channel Mach-Zehnder interferometer. OCT is a powerful optical signal acquisition method that can capture depth-resolved micrometer-resolution images. In our method, a complex signal is optically generated, and its real and imaginary components are encoded in the orthogonal polarization states of one sample beam; absolute phase information can then be acquired instantaneously. Neither phase modulation nor numerical Fourier or Hilbert transformation to extract phase information is required, thereby decreasing data acquisition rates and processing time. We conducted signal post-processing to select data from the instabilities of reference scanning delay lines; the measured phase sensitivity was as low as 0.23 - , and the corresponding path-difierence resolution was 265pm. A localized surface proflle measurement of a chromium- coated layer deposited on a commercial resolution target surface was conducted. The results conflrmed that successful images can be obtained even with very small optical path difierences using the proposed method.

Improved, Approximate, Time-Domain ML Estimators of Chirp Signal Parameters and Their Performance Analysis

We derive an improved, approximate, maximum likelihood (ML) estimator for the parameters of a single-component chirp signal in the time domain, which has much lower computational complexity than that of the traditional estimators in the frequency domain. We term it the zero-order amplitude weighted phase-based estimator (AWPE). It is a weighted linear combination of the phases of the received signal samples, where the weights are determined by the amplitudes of the received signals. It achieves better performance than the only existing time-domain estimator in the literature that only exploits the phase information. A phase unwrapping (PU) algorithm is needed to recover the phase information correctly from the received signal samples. Several PU algorithms are compared and analyzed. A new, robust PU algorithm based on the first-order phase differences of the consecutive received signal samples is proposed. This new unwrapping algorithm has smaller PU failure probability than that based directly on the phases of the received signal samples. The need for PU can even be removed by using the second-order phase differences of the consecutive received signal samples. Two additional structures for the ML-based AWPE using the phase differences are derived starting from using the zero-order AWPE obtained. The first is based on the first-order phase differences and the second on the second-order phase differences. When the PU algorithm works perfectly, i.e., no phase unwrapping failure occurs, the estimators based on phase differences do not perform as well as the original one based on absolute phase information due to the increased noise variance. This is also applicable when the chirp parameters take on very small values. However, when no knowledge of the ranges of the chirp parameters is available, and the possible PU failures are taken into account, the estimators based on the phase differences could perform better. Performance analysis of the estimators is given based on an improved phase noise model. It is easy to verify that the estimates obtained are unbiased. The cramer-rao lower bound (CRLB) on the mean-square error (MSE) is derived. The MSE performance of the estimators approaches the CRLB at high signal-to-noise ratios. The variance performance of the estimators based on phase differences is analyzed, whose validity is demonstrated by simulation results.

Investigating the absolute phase information in acoustic wave resonance scattering

The aim of this work is to investigate the absolute phase information in resonance acoustic scattering by spheres and cylinders and place this work in the broader context of scattering in which the properties of the magnitude and (processed) phase have been examined in a more general way than in the classical resonance scattering theory (RST). Here, comparisons are made between the classical and modified RST formalisms of acoustic resonance scattering. Experimental and theoretical backscattering form functions are obtained and discussed. It is shown that the magnitude and processed (unwrapped) phase can be correctly obtained through the classical RST, suggesting that the modified RST formalism offers little new practical advantage. Furthermore, the absolute phase is shown to be very sensitive to object’s resonances, suggesting that the unwrapped phase may be considered as an efficient tool, along with the magnitude information, to carry out remote (active) classification of targets in underwater acoustics applications. The combination of absolute phase information with the magnitude data offers a complementary advantage in the identification of resonances from cylinders and spheres.

Hardware Implementation of a 16-QAM Modem Using Waveform Switching Technique

A new modem circuit technique is proposed for multilevel signal transmission to utilise the transmission bandwidth efficiently in bandwidth-constrained voice-band channels. Using this technique, a 16-level quadrature amplitude modulated (16-QAM ) signal is generated as a cascaded configuration of an 8-level phase-shift keying (8-PSK) and a 4-level amplitude-shift keying ( 4-ASK) using waveform mapping rules. The data detection procedure, which is based on the determination of each symbol one-by-one by inspection of their amplitude level and absolute phase information, is described.

A modified hybrid mapping technique for VLBI data

A modified interferometric mapping technique is presented for observations where absolute phase information is not available. This is especially applicable to VLBI observations. The technique corrects weaknesses of conventional hybrid mapping methods in measuring source symmetry, particularly for arrays with an outrigger antenna. An example of such an array is a set of earth-based antennas plus an orbiting antenna.