Periodic Error Research Articles

Real-Time Eye Diagram Monitoring for Optical Signals Based on Optical Sampling

A real-time eye diagram monitoring method for optical signals is proposed and experimentally demonstrated based on optical sampling. In the system, the optical signals under test are directly sampled by an optical sampling pulse train with a narrow pulse width and a high repetition frequency. The sampling pulse train is achieved in a Mach-Zehnder modulator (MZM), gated on-off by an electrical pulse. The sampled optical signals are then broadened and detected by a photodetector (PD). A low-speed electrical analog-to-digital converter (ADC) will then quantify the detected electrical signals. Combining with an algorithm based on the infinitesimal calculus, the quantified data is then used to achieve the eye diagram, according to which more time-domain parameters, such as period, time jitter, Q value, and bit error rate (BER) for the optical signals under test, are obtained. Thanks to the high repetition rate of the optical sampling pulse train, the eye diagram and the time-domain parameters of the optical signals are observed in real time. Experimental results show that a real time of about 350-μs eye diagram monitoring for a 2.5-Gb/s optical signal with a dynamic range from −10 to −22 dBm is achieved. In addition, time jitters are measured to range from 4.3 to 49.8 ps. Q values are estimated to range from 20.4 to 4.3, corresponding to BERs ranging from 2.3 × 10−92 to 8.5 × 10−6. The results are also verified by a commercial real-time oscilloscope.

Distributed periodic event-triggered synchronization for discrete-time complex dynamical networks with time-varying delay

In this paper, we study the synchronization control problem for a class of discrete-time complex dynamical networks (CDNs) under an event-triggered mechanism (ETM). First, a discrete-time distributed periodic ETM is developed based on communication measurement. Under this mechanism, the signal is sampled in a periodic manner, but whether the control signal is updated or not depends on the pre-designed triggering condition. The sampling signal is designed as the communication measurement calculated by both state feedback and inner communication among nodes. Compared with the existing discrete-time ETMs, this method considers the topology connection among network nodes and avoids the continuous measurement of signals. Therefore, this mechanism effectively saves communication resources and reduces the waste of computing resources. Second, in order to analyze the serrated constraint caused by the periodic sampling error, a piecewise Lyapunov function is constructed. Third, under the distributed periodic ETM, sufficient conditions are derived for bounded synchronization of discrete-time CDNs with time-varying delay. Finally, a simulation example verifies the effectiveness and accuracy of the conclusion.

Pengaruh Citra Merek, Kualitas Pelayanan Dan Harga Terhadap Kepuasan Pelanggan Serta Implikasinya Pada Loyalitas Pelanggan PT Strait Liner Express Di Jakarta

Multicollinearity Test This test aims to determine whether there is a correlation for the independent variables in the regression model used. A good regression model is a regression model that is non-multicollinearity, meaning that between one independent variable and another in the regression model are not perfectly interconnected. The size of the correlation that is free of multicollinearity is 5 or can be measured through the tolerance value or VIF (Variance Inflation Factor) of each variable in the SPSS ver. 21.0 computer program, namely if the tolerance value is 1.0 or VIF 5, it indicates the presence of multicollinearity. 21.0, namely if the tolerance value is 1.0 or VIF 5, it indicates the presence of multicollinearity. SPSS output ver. 20.0 to explain whether there are symptoms of multicollinearity between independent variables. Autocorrelation Test The autocorrelation test aims to test whether in a linear regression model there is a correlation between confounding errors in period t and confounding errors in period t-1 (previous). The following are the results of the autocorrelation test using SPSS 20.0:

The Next Generation Heterodyne Laser Interferometer in Joule Balance

In the joule balance, it is important to measure the relative displacement between the exciting magnet and the suspended coil. So we have designed and applied a compact dual-axis heterodyne interferometer, which is vacuum compatible, and have been carefully aligned for dual parallel measurement arms. However, with the wear of the linear translation stage and the coupling of 3-axis relative displacement locking, the periodic nonlinearity error may drift during the displacement measurement of joule balance, and so the performance of the existing laser interferometer system is not so stable. In order to solve this problem, in this paper, we have designed and employed a new heterodyne interferometer based on spatially separated beams (SPB) to restrain the periodic nonlinearity error caused by the double-frequency mixing. As to this SPB heterodyne interferometer, the input and output (I/O) beams can share the same optical space, which will contribute a lot to a compact structure in the joule balance. Meanwhile, the spatial attitude of interferometer is precisely controlled to restrain the error caused by ghost reflections. The experimental result shows the validation of this SPB heterodyne interferometer for the displacement measurement in the joule balance.

Weight distribution of low-density periodic random errors and their correcting codes with error decoding probability

We present weight distribution of low-density periodic random errors in the space of all q-ary n-tuples along with the average Hamming weight of the error set. We also provide necessary and sufficient conditions for the existence of linear codes correcting such error pattern. Examples of such codes are given. Finally, probability of decoding error of such codes over a binary symmetric channel is derived.

Modeling Method of Engine Zero-dimensional Combustion Model Based on PSO Algorithm Optimization

To improve the low accuracy of the zero-dimensional combustion model established by BP-NN, a particle swarm-neural network (PSO-NN) algorithm was proposed. The PSO optimize weights and thresholds of NN, and the operating and combustion parameters are constructed, and then compared with NN algorithm. The results show that comparing with NN algorithm, the zero-dimensional combustion model constructed by PSO-NN algorithm has higher prediction accuracy, and the mean square error of the main combustion period m is 0.0034, which is 78.21% lower than that before optimization. The particle swarm algorithm has quicker convergence and stronger versatility, which is suitable for the study of diesel engine 0-D model.

Correction of Periodic Random Errors by Cyclic Codes

Correction of Periodic Random Errors by Cyclic Codes

Simulations of Bubble Formation and Oscillation Behavior in Micro-Leakage Measurement System

In the process of measuring micro-leakage based on the bubble method, the physical parameters of the liquid phase have a great impact on the formation and movement of bubbles, thus affecting the measurement accuracy of the system. Therefore, it is of great significance to study the physical parameters of the liquid phase. At present, it is difficult to independently study the parameters of the liquid phase by experimental methods. In this paper, based on the Cahn-Hilliard phase field model, a gas-liquid two-phase flow model for the expression of leakage is established to independently study the influence of different physical parameters on the formation and movement of bubbles in the measuring system. Firstly, the effects of liquid medium density, dynamic viscosity coefficient and surface tension on the initial shape (aspect ratio), the generation period and the shape oscillation of bubbles after they leave the nozzle are analyzed. Then, an experimental platform for visualization of bubbles in two-phase flow based on machine vision is built, through which the morphological parameters of bubbles in the liquid phase can be obtained in real time. Finally, the results of visualization experiment and numerical simulation are compared. The results show that the initial aspect ratio error of bubbles obtained by visual experiment and numerical simulation is 1.8%, and the average oscillation period error is 12.3%. The results are basically consistent, which proves the rationality and correctness of the mathematical model established. It is found that the liquid with larger dynamic viscosity coefficient μ and density ρ and smaller surface tension σ can be selected as the liquid medium of the measurement system. It is more conducive to the accurate expression of micro-leakage in the measurement system, and the bubble shape can quickly reach a stable state. It provides theoretical support for improving the accuracy and stability of the micro-leakage measurement system.

ANALYSIS OF PRODUCT STOCK INVENTORY FORECASTING USING WEIGHTED MOVING AVERAGE METHOD

A company is said to be successful if it has fulfilled the demands of consumers in the future. cv. Aadiba company is engaged in sales services as a reseller by selling men's outdoor shoes. Problems with the company Cv. Aadiba, which is unable to meet consumer demand because they often experience a shortage of product stock, so far, planning for purchasing product stock is estimated manually based on previous experience and therefore this study aims to predict product stock inventory in order to minimize product stock purchases errors in the future period. and make the implementation of the forecasting system. The method used in the study is the Weighted Moving Average (WMA) method which can estimate the amount of stock that must be purchased for the future period. The data used for this research is sales data from January 2021 to April 2022, the moving average of the previous 3 months. Forecasting results using the Weighted Moving Average (WMA) method produce future sales of 612.5 and the error value of MAD is 104.448718, MSE 28380.712 and the MAPE value is 0.179160773% or 0.18% The smallest error value is considered the most appropriate used for forecasting, then the MAPE value is considered appropriate in forecasting because it has the smallest error value and the implementation of a forecasting system that can facilitate the Cv. Aadiba in terms of forecasting in the future period.

A theoretical and experimental investigation into tool setting induced form error in diamond turning of micro-lens array

Micro-lens array (MLA) has been widely used for 3D imaging, etc., due to its excellent functional performances. Ultra-precision diamond turning (UPDT) offers a satisfying solution to the high-quality fabrication of MLA with sub-micrometric form accuracy and nanometric surface roughness. However, in UPDT tool setting, errors would deteriorate form accuracy as a crucial factor. This study focuses on discussing the tool setting effect on form error of MLA and proposes a new two-step tool setting method for UPDT. Firstly, a theoretical model was established for form error of MLA under tool setting errors. Moreover, a new two-step tool setting method was developed with high accuracy to control the tool setting errors. Finally, a series of experiments were carried out with different tool setting errors for the MLA fabrication, and its form error would be measured. The theoretical and experimental results are found that the proposed tool setting method is effective with a high-precision accuracy and the tool setting errors would crucially induce periodical form error at the MLA of UPDT. Significantly, the study draws up a comprehensive understanding of the tool setting effect on form accuracy of MLA in UPDT with the further improvement.

Reduction of Crosstalk Errors in a Surface Encoder Having a Long Z-Directional Measuring Range

A modified two-axis surface encoder is proposed to separately measure both the in-plane displacement and the Z-directional out-of-plane displacement with minor crosstalk errors. The surface encoder is composed of a scale grating and a small-sized sensor head. In the modified surface encoder, the measurement laser beam from the sensor head is designed to be projected onto the scale grating at a right angle. For measurement of the X- and Y-directional in-plane scale displacement, the positive and negative first-order diffracted beams from the scale grating are superimposed on each other in the sensor head, producing interference signals. On the other hand, the Z-directional out-of-plane scale displacement is measured based on the principle of a Michelson-type interferometer. To avoid the influence of reflection from the middle area of the transparent grating, which causes periodic crosstalk errors in the previous research, a specially fabricated transparent grating with a hole in the middle is employed in the newly designed optical system. A prototype sensor head is constructed, and basic performances of the modified surface encoder are tested by experiments.

A simplified formula for the determination of the fundamental period of mixed structures with vertical combination of different seismic resisting systems

Vertical combination of different seismic resisting systems, permitted in the seismic design codes such as ASCE/SEI7-16, is an effective choice for the structural design of mid- and high-rise buildings. In the seismic analysis of structures, according to the seismic codes, an estimate of the fundamental period of vibration is needed. On other hand, there is no simplified equation to compute the fundamental period of vibration of mixed buildings with vertical combination of different seismic resisting systems. In this study, by using the Rayleigh’s method, a simplified formula is proposed for determining the fundamental period of this type of structures. The proposed formula is verified by using the eigenvalue analysis of the mathematical model of the 11 building frames with different structural characteristics along their height. Also, two different mixed structures composed of steel and reinforced concrete moment-resisting frame (MRF) structures as well as of steel concentrically braced frame (CBF) and reinforced concrete MRF structures are examined. The fundamental period of a 3-dimensional (3D) vertically irregular 6-story building with setbacks is also determined to show the efficiency of the proposed method for vertically irregular structures. Furthermore, the proposed formula is verified by the period obtained from an experimental full-scale test of a structure. The results indicate that the proposed formula results in the fundamental period of the mixed structures with satisfactory accuracy. The largest and average errors in the fundamental period of the buildings under consideration, obtained by the proposed formula, are less than 10% and 6%, respectively, compared to the eigenvalue analysis. Therefore, the proposed formula can be used in the seismic evaluation process of existing buildings as well as in the design process of new ones.

Achieving Heisenberg scaling on measurement of a three-qubit system via quantum error correction

In many-body quantum systems, the quantum Fisher information an observer can obtain is susceptible to decoherence. Consequently, quantum enhanced metrology, such as Heisenberg scaling, cannot usually be achieved. We show, via two distinct methods, that by applying periodic quantum error corrections, we can achieve the Heisenberg scaling for an extended period of time on a three-qubit Tavis-Cumming Model, where three two-level atoms interact with a single cavity mode, under certain approximations. The generalization to arbitrary number of atoms case is also discussed.

An advanced pressure pulsation model for external gear pump

Pressure pulsation is the inherent characteristic of external gear pump. This paper presents a new pressure pulsation model by considering the lateral clearance and manufacturing error. Firstly, inspired by the Archard model, the maximum roughness peak of lateral bushing surface with or without wear are measured by laser confocal microscope, which is to obtain the change law of lateral clearance indirectly and construct the lateral clearance model. Then, the manufacturing error model is constructed based on the long and short period errors of the master-slave gear acquired by the gear measuring center. Meanwhile, according to the boundary constraints, the lateral clearance model and the manufacturing error model are embedded into the lumped parametric model of the pressure pulsation to realize updating. Finally, the robustness of the new pressure pulsation model under different working conditions is verified, and the nature of the influence of the lateral clearance model and manufacturing error model on pressure pulsation is revealed. Experimental results on an external gear pump validate the merits of the new model in both time domain and frequency domain. The results can provide helpful guidance to understand the mechanism of external gear pump pressure pulsation.

Heat Flow and Thermal Stress Analysis to Enhance the Temperature Distribution and Service Life of Stone Grill Plates in Barbecue Ovens

The causes of the fracturing of stone grills in barbecue ovens were analyzed using a coupled analysis model that combined combustion thermodynamics with heat conduction and the finite element method. The proportion of mixed air for combustion was simulated, and the stone grill plate temperature and thermal stress distribution were the two factors taken to enhance the design of stone grill plates. Moreover, thermal images were used to compare the performance of the original and the improved plates to quantify the improvements, and validate the accuracy of the simulations. The results showed that the temperature distribution was uniform across the stone grill plate. When comparing the simulation model and the actual experiment, the simulation model can generate an optimal design with fewer errors in a shorter period. The combustion tube is deemed to have considerable influence on the performance of the barbecue oven. The surface temperature distribution of the stone grill plate was improved by controlling the amount of fuel entering the combustion system and/or changing the material and shape of the stone grill. On the other hand, the analysis results of the improved stone grill plate in this study showed that we can correct the temperature difference and thermal stress difference caused by the opening of the upper cover of the oven. According to our study, the average thermal stress on the surface of the stone grill plate was effectively reduced by 45.3 MPa. The average temperature difference decreased by 91 °C. At the same time, by improving the intake position and method of the combustion tube, the air mass flow in the combustion tube increased by 12%, which effectively improved the combustion efficiency of the combustion tube. In particular, a more uniform distribution was achieved by decreasing the temperature of the mixed air entering the combustion tube, which in turn increased the flow rate and velocity of the air flowing through the top of the flame to the bottom surface of the stone grill plate. The strategies employed can prevent the thermal-stress-induced fracturing of stone grill plates and prolong their service life.

Quantitative evaluation and removal of periodic error caused by ghost reflections in a double-path homodyne interferometer

This paper discusses periodic error caused by ghost reflections in a double-path homodyne interferometer, which is difficult to be removed by so-called Heydemann’s method due to its unique frequency. The mechanism of the periodic error is represented by a theoretical equation established focusing on the number of round trips of a measurement light path. Based on the theory, it was found that specific periodic errors are caused by the measurement light reflected on one surface of an optical element. To evaluate the presence and removal of the periodic error, the self-evaluation method, which was extended to include ghost reflections, was applied. Experimental evidence shows that a wedge provided on that surface prevents unwanted reflections and reduces the periodic error to approximately 2 pm.

Spatially Separated Heterodyne Grating Interferometer for In-Plane and Out-of-Plane Displacement Measurements

Grating interferometers that measure in-plane and out-of-plane displacements are not only effective two-degree-of-freedom (DOF) sensors, but are also basic units of six-DOF measurement systems. Besides resolution and accuracy, periodic nonlinear errors, misalignment tolerance, and size of reading heads are more crucial than ever. In this work, a spatially separated heterodyne grating interferometer that measures in- and out-of-plane displacements is proposed. A prototype with 3 mm diameter beams with a size of 69 mm × 51 mm × 41 mm was built and tested. The experiment results show that the 30 s stability is 2.5 nm; the periodic nonlinear errors of the two measuring directions are less than the resolutions (0.25 nm for in-plane motions and 0.15 nm for out-of-plane motions). Double-diffracted configuration ensures that the misalignment tolerances are three axes larger than ±2 mrad.

Using NDVI, climate data and machine learning to estimate yield in the Douro wine region

Estimating vineyard yield in advance is essential for planning and regulatory purposes at the regional level, with growing importance in a long-term scenario of perceived climate change. With few tools available, the current study aimed to develop a yield estimation model based on remote sensing and climate data with a machine-learning approach. Using a satellite-based time-series of Normalized Difference Vegetation Index (NDVI) calculated from Sentinel 2 images and climate data acquired by local automatic weather stations, a system for yield prediction based on a Long Short-Term Memory (LSTM) neural network was implemented. The study was conducted in the Douro Demarcated Region in Portugal over the period 2016–2021 using yield data from 169 administrative areas that cover 250,000 ha, in which 43,000 ha of the vineyard are in production. The optimal combination of input features, with an Mean Absolute Error (MAE) of 672.55 kg/ha and an Mean Squared Error (MSE) of 81.30 kg/ha, included the NDVI, Temperature, Relative Humidity, Precipitation, and Wind Intensity. The model was tested for each year, using it as the test set, while all other years were used as input to train the model. Two different moments in time, corresponding to FLO (flowering) and VER (veraison), were considered to estimate in advance wine grape yield. The best prediction was made for 2020 at VER, with the model overestimating the yield per hectare by 8 %, with the average absolute error for the entire period being 17 %. The results show that with this approach, it is possible to estimate wine grape yield accurately in advance at different scales.

Effect of Grating Ruling Machine System Errors on Grating Spectral Performance

Grating groove functions scalar theory can describe the light source through the grating interference and diffraction effect of the physical phenomenon of splitting light. It can be used to represent the distribution of the complex amplitude of the illumination light source on the diffraction screen under the action of the diffraction grating and display the information on the diffracted light position and intensity distribution. As a result, the effect of groove error on the intensity of grating ghost lines and stray light is analyzed. This paper presents an energy solution and analysis of the grating periodic groove error utilizing the grating scalar diffraction theory. Based on this, the effect of the core components of the grating ruling machines, such as screw and worm gear, on the stray light and ghost line of the grating is analyzed. Finally, the random groove error is analyzed. The analysis results show that the worm gear error is an important reason for the appearance of ghost lines in the machine ruling grating, and the lead screw error and random grooving error are the main reasons for the stray light produced by the grating. We optimize the worm gear, lead screw, and error compensation system of the grating ruling machine to effectively improve the ruling quality of the grating.

Recognition of Air Passengers' Willingness to Pay for Seat Selection for Imbalanced Data Based on Improved XGBoost

Passenger-paid seat selection is one of the important sources of ancillary revenue for airlines, and machine learning-based willingness-to-pay identification is of great practicality for airlines to accurately tap potential willing passengers. However, affected by periodic statistical errors, air passenger order data often has some problems such as high noise, high latitude, and unbalanced category. In view of this, this paper proposes a method for identifying air passengers' willingness to pay for seat selection based on improved XGBoost, which is improved and integrated from three stages: data, feature, and algorithm. The feasibility of the proposed multi-stage improved integration method is verified by real airline passenger dataset, and the experimental results show that the proposed improved method has better classification effect when compared with the classical six imbalance classification models, which provides a basis for accurate marketing of airline paid seat selection programs.