Proposed Alignment Method Research Articles

Precision Measurement of Dimension over Two Pins of Flexspline of Harmonic Reducer

This paper presents a comparative method for accurately measuring dimension over two pins of flexspline of harmonic reducer. Firstly, we design a measuring system and introduce its composition and measuring principle. Secondly, we propose an alignment method to reduce measurement error caused by eccentric installation. Finally, the alignment method proposed was experimentally verified, and the dimension over two pins of flexspline was measured. The verification results showed that the proposed alignment method had a positive effect, and its feasibility was confirmed. Dimension over two pins of standard flexspline was found to be 64.855 mm. By employing the proposed comparison method, the dimension over two pins of the three measured flexsplines was 64.848 mm, 64.862 mm, and 64.857 mm, respectively. The measurement accuracy achieved was less than 10 μm, meeting the required measurement accuracy standards and significantly improving upon traditional measurement methods.

In-motion initial alignment method using Cayley–Kalman filter on special orthogonal group

Aiming at the in-motion initial alignment problem of strapdown inertial navigation system (SINS), this paper proposed a precise direct in-motion alignment method based on attitude matrix representation and Cayley–Kalman filter on the special orthogonal group. There are two innovations in this paper. First, as an element of the special orthogonal group [Formula: see text], the error attitude matrix is used to construct an in-motion alignment model, and it is transformed into the vector space to represent the attitude error state. The error matrix was used as a state to decrease the influence of the state-dependent problem. Second, this method uses the Cayley transform to replace the Taylor expansion to derive the update equation, which is a no approximation mapping relation to assure accuracy when deriving the filtering algorithm. Simulation and experimental results demonstrate the proposed alignment method has advantages over the existing methods in alignment accuracy and alignment time and performs well in the in-motion alignment process of SINS.

Inertial alignment with improved EMD filter of inclinometer in coal drilling rig

Inertial navigation system (INS) is widely used as inclinometer in coal drilling rig to realize navigation and attitude measurement. Vibration of coal drilling rig is one of the significant issues impacting the performance of alignment. Previous work has indicated that part of alignment error caused by vibration of gyroscope can be suppressed by inertial alignment frame. However, vibration error of accelerometer cannot be well suppressed. In this paper, an inertial alignment based on improved empirical mode decomposition (EMD) filter is proposed to address vibration issue in alignment. Moreover, a prediction strategy of extreme endpoints based on relativity of extreme points is proposed to reduce the endpoint error to suppress the accumulative error in EMD filter. The proposed alignment method is applied in laboratory condition. The result shows that the stability of accelerometer improves 42.43% at most, the alignment time reduce from 300 to 100 s and the alignment error of inclination angle is less than 5.4 arcmin. The experiment in coal mining rig shows the alignment time reduces from 300 to 50 s. The proposed alignment method improves the performance of inclinometer effectively and feasibly in alignment period and the improved EMD filter can be also applied in navigation period to suppress the vibration error of accelerometer.

Unsupervised domain adaptation in homogeneous distance space for person re-identification

Data distribution alignment and clustering-based self-training are two feasible solutions to tackle unsupervised domain adaptation (UDA) on person re-identification (re-ID). Most existing alignment-based methods solely learn the source domain decision boundaries and align the data distribution of the target domain to the source domain, thus the re-ID performance on the target domain completely depends on the shared decision boundaries and how well the alignment is performed. However, two domains can hardly be precisely aligned because of the label space discrepancy of two domains, resulting in poor target domain re-ID performance. Although clustering-based self-training approaches could learn independent decision boundaries on the pseudo-labelled target domain data, they ignore both the accurate ID-related information of the labelled source domain data and the underlying relations between two domains. To fully exploit the source domain data to learn discriminative target domain ID-related features, in this paper, we propose a novel cross-domain alignment method in the homogeneous distance space, which is constructed by the newly designed stair-stepping alignment (SSA) matcher. Such alignment method can be integrated into both alignment-based framework and clustering-based framework. Extensive experiments validate the effectiveness of our proposed alignment method in these two frameworks. We achieve superior performance when the proposed alignment module is integrated into the clustering-based framework. Codes will be available at: http://github.com/Dingyuan-Zheng/HDS.

Adjusting videoendoscopic 3D reconstruction results using tomographic data

Videoendoscopic and tomographic research are the two leading medical imaging solutions for detecting, classifying and characterizing a wide array of pathologies and conditions. However, source information from these types of research is very different, making it hard to cross-correlate them. The paper proposes a novel algorithm for combining results of based on 3D surface reconstruction methods. This approach allows to align separate parts of two input 3D surfaces: surface obtained by applying bundle adjustment-based 3D surface reconstruction algorithm to the endoscopic video sequence, and surface reconstructed directly from separate tomographic cross-section slice projections with regular density. Proposed alignment method is based on using local feature extractor and descriptor algorithms by applying them to the source surface normal maps. This alignment allows both surfaces to be equalized and normalized relative to each other. Results show that such an adjustment allows to reduce noise, correct reconstruction artifacts and errors, increase representative quality of the resulting model and establish correctness of the reconstruction for hyperparameter tuning.

Alignment method for rotary stage axis and optical axis in the polar coordinate direct laser writing system

As a crucial part of a high-speed polar coordinate laser writing system, the alignment of the rotatory stage axis and the writing laser optical axis has been a key point that influences the accuracy of the whole system and the fabrication patterns. An alignment method of the rotatory stage axis and the writing laser optical axis is proposed. An alignment system is established and the imaging subsystem is calibrated by a high precision calibration object. A circle center lookup algorithm is applied to find the axis of the rotary stage. The accuracy of the alignment could reach 400 nm. The results of the alignment indicate that the proposed alignment method is a good method for the alignment of the rotary stage axis and the writing laser optical axis. The proposed alignment is useful in the fields of high-resolution maskless laser lithography in polar coordinates.

A Device-Independent, Shape Preserving Retinal Optical Coherence Tomography Image Alignment Method Applying TV-Unet for RPE Layer Detection

Retinal optical coherence tomography (OCT) images are widely used in diagnosis of ocular conditions. However, random shift and orientation changes of the retinal layers in OCT B-scans yield to appearance variations across the scans. These variations reduce the accuracy of the algorithms applied in the analysis of OCT images. In this study, we propose a preprocessing step to compensate these variations and align B-scans. At first, by incorporating total variation (TV) loss in the well-known Unet model, we propose a TV-Unet model to accurately detect the retinal pigment epithelium (RPE) layer in each B-scan. Then we use the detected RPE layer in the alignment method to form a curvature curve and a reference line. A novel window transferring-based alignment approach is applied to force the curve points to form a straight line, while preserving the shape and size of the pathological lesions. Since detection of RPE layer is a crucial step in the proposed alignment method, we utilized various datasets to train and test the TV-Unet and provided a multimodal, device-independent OCT image alignment method. The TV-Unet localizes the RPE layer in OCT images with low boundary error (maximum of 1.94pixels) and high Dice coefficient (minimum of 0.98). Quantitative and qualitative results indicated that the proposed method can efficiently detects the RPE layer and align OCT images while preserving the structure and size of the retinal lesions (biomarkers) in the OCT scans.

A Position Loci-Based In-Motion Initial Alignment Method for Low-Cost Attitude and Heading Reference System

In this article, a new position loci-based in-motion initial alignment method is proposed for a low-cost attitude and heading reference system (AHRS). A new sliding-window-based position integration method is proposed to construct the position vector observations, which weakens the accumulated errors induced by the inertial measurement unit (IMU) bias errors in vector observations. Also, a new closed-loop method is proposed to jointly estimate the time-varying body attitude matrix and the unknown IMU biases and global position system (GPS) lever-arm based on the Kalman filter. The estimates of the time-varying body attitude matrix, IMU biases, and GPS lever-arm are all used to construct and compensate for the position vector observations, which improves the alignment accuracy. Both the simulation and car-mounted test results illustrate that the proposed alignment method can achieve better alignment accuracy than these existing methods for a position loci-aided low-cost AHRS.

A multi-resolution framework for automated in-plane alignment and error quantification in additive manufacturing

PurposeAdditive manufacturing (AM) has shown its capability in producing complex geometries. Due to the additive nature, the in situ layer-wise inspection of geometric accuracy is essential to making AM reach its full potential. This paper aims to propose a novel automated in-plane alignment and error quantification framework to distinguish the fabrication, measurement and alignment errors in AM.Design/methodology/approachIn this work, a multi-resolution framework based on wavelet decomposition is proposed to automatically align two-dimensional point clouds via a polar coordinate representation and then to differentiate errors from different sources based on a randomized complete block design approach. In addition, a two-stage optimization model is proposed to find the best configuration of the multi-resolution framework.FindingsThe proposed framework can not only distinguish errors attributed to different sources but also evaluate the performance and consistency of alignment results under different levels of details.Practical implicationsA sample part with different featured layers, including a simple free-form layer, a defective layer and a layer with internal features, is used to illustrate the effectiveness and efficiency of the proposed framework. The proposed alignment method outperforms the widely used iterative closest point algorithm.Originality/valueThis work fills a research gap of state-of-the-art studies by automatically quantifying different types of error inherent in manufacturing, measuring and part alignment.

Investigation of the Alignment Method for High-Frequency Gyrotrons

The successful operation of the gyrotron strongly depends on the proper alignment of the gyrotron with the magnet. The difficulty of the alignment will increase as the frequency becomes higher, especially for the terahertz pulsed gyrotron. In this article, we describe an easily implemented alignment method in detail. A triaxial adjusting flange was designed to align the gyrotron. The alignment of the gyrotron can be identified by the fluorescent effect of the electron beam on the sapphire output window, which will be captured by triggering a charge-coupled device camera. The affine transformation was also used to correct the distorted image. The validity of the proposed alignment method is verified via a prototype of an 800-GHz second-harmonic pulsed gyrotron.

Improving the speed of initial alignment for marine strapdown inertial navigation systems using heading control signal feedback in extended Kalman filter

In this article, a method was proposed for strapdown inertial navigation systems initial alignment by drawing on the conventional alignment method for stable platform navigation systems. When a vessel is moored, the strapdown inertial navigation system contributes to the disturbing motion. Moreover, the conventional methods of accurate alignment fail to succeed within an acceptable period of time due to the slow convergence of the heading channel in the mooring conditions. In this work, the heading was adjusted using the velocity bias resulting from the component of the angular velocity of the Earth on the east channel on the strapdown inertial navigation systems analytic platform plane to accelerate convergence in the initial alignment of navigation system. To this end, an extended Kalman filter with control signal feedback was used. The heading error was calculated using the north channel residual velocity of the strapdown inertial navigation systems analytic platform plane and was entered into an extended Kalman filter. Simulation and turntable experimental tests were indicative of the ability of the proposed alignment method to increase heading converge speed in mooring conditions.

A heuristic cabin-type component alignment method based on multi-source data fusion

In cabin-type component alignment, digital measurement technology is usually adopted to provide guidance for assembly. Depending on the system of measurement, the alignment process can be divided into measurement-assisted assembly (MAA) and force-driven assembly. In MAA, relative pose between components is directly measured to guide assembly, while in force-driven assembly, only contact state can be recognized according to measured six-dimensional force and torque (6D F/T) and the process is completed based on preset assembly strategy. Aiming to improve the efficiency of force-driven cabin-type component alignment, this paper proposed a heuristic alignment method based on multi-source data fusion. In this method, measured 6D F/T, pose data and geometric information of components are fused to calculate the relative pose between components and guide the movement of pose adjustment platform. Among these data types, pose data and measured 6D F/T are combined as data set. To collect the data sets needed for data fusion, dynamic gravity compensation method and hybrid motion control method are designed. Then the relative pose calculation method is elaborated, which transforms collected data sets into discrete geometric elements and calculates the relative poses based on the geometric information of components. Finally, experiments are conducted in simulation environment and the results show that the proposed alignment method is feasible and effective.

Fast Alignment of SINS for Marching Vehicles Based on Multi-Vectors of Velocity Aided by GPS and Odometer.

In the strap-down inertial navigation system (SINS), the initial attitude matrix is acquired through alignment. Though there were multiple valid methods, alignment time and accuracy are still core issues, especially regarding the condition of the motion carrier. Inspired by the idea of constructing nonlinear vectors by velocity in a different coordinate frame, this paper proposes an innovative alignment method for a vehicle-mounted SINS in motion. In this method, the core issue of acquiring the attitude matrix is to calculate the matrix between the inertial frame and the initial body frame, which can be constructed through the nonlinear velocity vectors’ information from the GPS and the odometer at different moments, which denominate the multi-vector attitude determination. The possibility of collinearity can easily be avoided by a turning movement. The characteristic of propagation of error is analyzed in detail, based on which an improved method is put forward to depress the effect of random noise. Compared with the existing alignment methods, this method does not use the measurement information of accelerometers. In order to demonstrate its performance, the method is compared with the two-position alignment method and the traditional two-stage alignment method. Simulation and vehicle-based experiment results show that the proposed alignment method can establish an attitude reference in 100 s with an azimuth error of less than 0.06°, and that the accuracy does not have a strong correlation with the accelerometer.

Self-assembled vertical alignment layer of bifunctional amphiphiles for fast electro-optical switching of nematic liquid crystals

ABSTRACTWe present a novel homeotropic alignment method that simultaneously improves the ability of vertical alignment and fast switching of liquid crystals (LCs) in the electro-optical performance. The proposed method utilizes dual self-assembly of 4-(4-heptylphenyl)benzoic acid and 2-carboxyethyl acrylate via hydrogen bonding with ITO substrate. The 4-(4-heptylphenyl)benzoic acid composed of aromatic moieties and alkyl chains induce the homeotropic alignment of the LC molecules. Photopolymerization of 2-carboxylethyl acrylate with a reactive acrylate group under UV irradiation gives the LC molecules a fast response. Our proposed alignment method allows for fabrication of LC devices exhibiting fast LC switching without a conventional polyimide layer.

Fabrication of a new homeotropic alignment layer for nematic liquid crystals using an in situ self-assembly of alkylated benzoic acid derivative

ABSTRACTWe have presented a novel vertical alignment method simultaneously enhancing the alignment ability and electro-optical performances of nematic liquid crystals (LCs). The method relies on the self-assembly of 4-(4-heptylphenyl)benzoic acid and 2-carboxyethyl acrylate through hydrogen bonding with conventional polyimide and the generation of pre-tilting in the LC molecules using ultraviolet irradiation under applied voltage. The electro-optical measurements of a LC device fabricated by using this self-assembled polyimide layer exhibited strong homeotropic alignment and fast response time. The proposed alignment method may be valuable in providing new functional alignment materials for high-performance LC devices.

Alignment of wave functions for angular momentum projection

Angular momentum projection is used to obtain eigen states of angular momentum from general wave functions. Multi-configuration mixing calculation with angular momentum projection is an important microscopic method in nuclear physics. For accurate multi-configuration mixing calculation with angular momentum projection, concentrated distribution of $z$ components $K$ of angular momentum in the body-fixed frame ($K$-distribution) is favored. Orientation of wave functions strongly affects $K$-distribution. Minimization of variance of $\hat{J}_z$ is proposed as an alignment method to obtain wave functions that have concentrated $K$-distribution. Benchmark calculations are performed for $\alpha$-$^{24}$Mg cluster structure, triaxially superdeformed states in $^{40}$Ar, and Hartree-Fock states of some nuclei. The proposed alignment method is useful and works well for various wave functions to obtain concentrated $K$-distribution.

Robust face alignment and tracking by combining local search and global fitting

When a face in an image is considerably occluded, existing local search and global fitting methods often cannot find the facial features due to failures in the local facial feature detectors or the fitting limitations of appearance modeling. To solve these problems, we propose a new face alignment method that combines the local search and global fitting methods, where local misalignments in the local search method are restricted by holistic appearance fitting in the global fitting method and the divergent or shrinking alignments in the global fitting method are avoided by the restricting local movements in the local search method. The proposed alignment method consists of two stages: the initialization stage detects the face, estimates the facial pose and obtains the initial facial features by locating a pose-specific mean shape on the detected face; the optimization stage then obtains the facial features by updating the parameter set from the combined Hessian matrix and the combined gradient vector. We also extend the proposed face alignment to face tracking by adding a template image that is warped from the facial features obtained in the previous frame. In the experiments, the proposed method yields more accurate and stable face alignment or tracking under heavy occlusion and pose variation than the existing methods.

Modeling of kinematics errors and alignment method of a swing arm ultra-precision diamond turning machine

Ultra-precision machining has been widely used in the manufacturing of optical components. Volumetric error analysis and error compensation are essential issues that must be considered to improve the accuracy of the machining process. However, analysis of the effects of kinematics errors on surface generation by ultra-precision machining using a swing arm ultra-precision diamond turning machine (SA-UDTM) and the alignment methods required have received little research attention to date. This paper presents the development of a kinematics error model of the SA-UDTM that accounts for geometric errors by simplifying the machining system and considering it as a rigid multi-body system. Then, the main error contributions to the processing precision can be derived from sensitivity analysis of error components. Finally, an alignment method is developed to reduce or eliminate the corresponding positioning errors of the mechanical system and thus improves the form accuracy of processed surface. To verify the theoretical kinematics model and the proposed alignment method, a series of contrast machining experiments have been performed, and the experimental results indicate that the proposed method is effective.

Effects of metal filament’s alignment on tensile and electrical properties of conductive hybrid cover yarns

AbstractOf late, a significant amount of research has been carried out using metals for conductive fabrics and composites to obtain the desired level of electromagnetic shielding along with physical and mechanical properties for its durability. However, incorporating these metallic filaments as core or as an integral part of core deteriorate the mechanical properties of textile yarns and ultimately the fabrics’. Moreover, the transparency of fabrics to high frequency/smaller wavelength waves further increases with the attempt to increase the metallic filament diameter. This study, therefore analyses the effects of metallic filament alignment in order to improve the mechanical properties of the resultant hybrid yarns, and devises an alternative method to increase the amount of conductive filament without increasing the diameter of the conducting wire in hybrid yarn structures. The results suggest that the tensile properties of the proposed hybrid cover yarns with conductive filament as covering component is superior as compared to the yarns having a conductive filament in the core, however, the electrical resistance increases with an increase in conductive filament length. The tenacity, elongation and initial modulus values were enhanced several times by incorporating the conductive filament as spiral covering. Moreover, with the proposed alignment method, the amount of copper in hybrid yarn can be increased up to some extent by changing the number of turns of covering component.

An alignment method for the reflective zoom system by applying vector wavefront aberration theory

The image quality of the reflective zoom system is strongly reduced when the position of the mirror is changed during the zooming process. A new alignment method based on vector wavefront aberration theory is suggested in order to surmount this problem during the zoom process. During the three-mirror reflective zoom system zooming process, the secondary mirror plays an active role and the tertiary mirror plays a complementary role. This feature enables adjustment of the tertiary mirror to compensate for the misalignment of the secondary mirror in the zoom process. The alignment of a three-mirror reflective zoom system was simulated. First, we imposed a feeble maladjustment on the secondary mirror as its position was changed during the zooming process. Then, we obtained the compensation values for the tertiary mirror by using the vector wavefront aberration theory. Lastly, the compensation values were imported to be applied to a misaligned three-mirror reflective zoom system. The image quality of the zoom system prior to and after the application of our proposed alignment method validates its correctness and viability.