Error Calculation Method Research Articles

Analysis of the Temperature Field Characteristics and Thermal-Induced Errors of Miniature Interferometric Fiber Optic Gyroscopes in a Vacuum Environment

This paper investigates the mechanism of thermal-induced errors in interferometric fiber optic gyroscopes (IFOGs) caused by temperature changes in a vacuum environment, proposing a method for calculating thermal-induced errors in small fiber coils. Firstly, based on the Shupe effect and the thermal stress caused by temperature changes around the fiber coil, a three-dimensional thermal-induced error model for small fiber coils is established. Secondly, a spatial fiber optic inertial measurement unit (IMU) model is designed using the Creo 3D modeling software (creo 7.0.0). The model is then imported into the Ansys finite element simulation software (ANSYS Workbench 15.0), where a temperature field is applied to the IMU based on actual temperature profiles to obtain the temperature distribution of the fiber coil at different times in a vacuum state. These data are then used in the three-dimensional thermal-induced error model to calculate the thermal-induced error of the FOG. Finally, a thermal vacuum experimental platform is set up to collect temperature variation data from the inertial measurement components. The experimental data are compared with the three-dimensional error model proposed in this paper as well as traditional error models. The root mean square error is approximately 33% lower than that of traditional error calculation methods, which also proves the theoretical accuracy.

Analysis of the baud rate of the UART to affects the data

This article explores the impact of different baud rates on Universal Asynchronous Receiver/Transmitter (UART) asynchronous serial communication. It discusses the frame format and calculation method of baud rate error, as well as the main reasons for error, such as clock error, sampling error, line noise, data bit error, and software delay. To ensure reliable communication, it is essential to test and debug the actual baud rate and adjust it accordingly. The study found that higher expected baud rates resulted in higher baud rate errors, affecting transmission distance, speed, reliability, and system complexity. The appropriate baud rate should be selected based on specific application scenarios and requirements. Higher baud rates are needed for high-speed transmissions, while lower baud rates are required for long transmission distances or high reliability requirements. However, further research is needed to determine the impact of unallocated baud rates on data. Overall, this article provides valuable insights into the development of UART.

Cross‐coupling control strategy based on intelligent adaptive control for cross‐shaped dual‐axis linear motors

AbstractIn order to ensure the high precision and good dynamic characteristics of the dual‐axis linear motor when machining components, the tracking error and contour error should be reduced with more complex machining trajectory. In this study, the characteristic model of position control of the linear motor is established by using the modelling principle of the characteristic model, and the intelligent adaptive controller is designed. In addition, a new calculation method of the equivalent contour error is proposed innovatively, and the dual axis is compensated by proportional feedback control, to improve the contour accuracy of the permanent magnet synchronous linear motor dual‐axis control system. Finally, through the simulation and experiment of the dual‐axis motor platform, the effectiveness of the proposed contour error calculation method and the intelligent adaptive controller can make the dual‐axis motion control system have higher accuracy and strong robustness and can also make the motor run more smoothly.

A Frequency Detection Circuit for Constant ON-Time LED Driver Chip

To meet the high-reliability requirements of switch mode power supply LED driver chips with constant on-time architecture, a detection mechanism circuit that can detect the switching frequency of the architecture is proposed. The detection circuit completes the conversion from switching frequency to output voltage through separate voltage tracing technology. The detection circuit uses the method of frequency error calculation to eliminate the interference of frequency jump on detection. The design is based on a 180 nm process simulation. The simulation results show that the detection mechanism has good linearity for frequency measurement and can eliminate the interference of frequency jump.

A Mobile Sensing Based Stochastic Model to Forecast AQI Variation of Pollution Hotspots on Urban Neighborhoods

Due to massive population migration, most Indian cities have experienced fast urbanization, resulting in a significant increase in construction activity, traffic pollution, and uncontrolled expansion. Some of these cities also have a high concentration of polluting industries, significantly worsening air quality. Pollution hotspots exist in certain cities, with levels well surpassing the authorized mark. Air pollution is generally classified as extremely hyper-local, which signifies that the pollution index decreases as we travel away from hotspots. Since the pollution data collected from traditional sources is occasionally inadequate, the extended consequences of such hotspots on neighboring communities remain unidentified. If the flux in pollution values in neighboring locales is efficiently mapped for locations encountered travelling further from identified hotspots, AQI levels for these areas can be forecasted and projected. Knowledge from monitoring these levels will aid the city administrations and government in drafting suitable proposals for susceptible establishments like hospitals and schools. In this research work, the Air Quality Index (AQI) data was accurately gathered at an identified pollution hotspot and its immediate neighborhood over a defined period along a specific route and a mathematical model was developed to forecast how AQI varies with distance for best results. Stochastic models such as ARMA and ARIMA were used to create the predicted model. Its reliability and performance were measured using various forecasting error calculation methods such as MPE (Mean Percentage Error), MAP (Mean Absolute Percentage), MAD (Mean Absolute Deviation), RMSE (Root Mean Square Error), and MSE (Mean Square Error).

Anti Interference Clock Error Correction Technology Based on BD3 System

Beidou-3 (BD3) uses the pseudo range transmission method to calculate the clock difference through the pseudo range. However, due to the influence of electromagnetic interference, the clock difference measurement error is too large, which affects the timing accuracy of the power system. This paper first introduces the principle of Beidou timing service; Secondly, it introduces the clock error calculation method; Finally, combined with the clock difference calculation method, this paper presents an anti-interference clock difference correction method based on Least Mean Square (LMS) filter. According to the principle of LMS filter, the influence of electromagnetic interference on pseudo distance can be eliminated, and the clock difference can be calculated. Then the clock difference can be corrected. The simulation results show that the method is feasible and effective.

Real-time trajectory position error compensation technology of industrial robot

In order to meet the requirements of high positioning accuracy and trajectory accuracy of industrial robots in the field of high-precision operation, this paper studied the real-time compensation method of the robot trajectory error used laser tracker to measure the end position of robot in real time. This real-time error calculation method of robot trajectory based on continuous dynamic time warping (CDTW), which was studied to determine the position error of robot trajectory at each moment. Moreover, this paper researched the PID parameter tuning technology of response surface model method based on gray analysis and got a real-time compensation method. The compensation value was fed back to the robot for motion compensation in real time through KUKA RSI. The last, the influence of compensation parameters and period was analyzed and the error compensation experiment of positioning, linear trajectory and arc trajectory were carried out. After compensation, the absolute positioning error of the robot was less than 0.06 mm and the trajectory position error was less than 0.15 mm, which greatly improved the position accuracy of the robot.

INVESTIGATING THE MEASUREMENT ERRORS OF THE COMPONENTS OF THE COMPLEX RESISTANCE OF MUTUAL INDUCTION BY THE PHASE METHOD

A microcontroller measurer of the complex resistance components of mutual induction (MI) of magnetically coupled coils is considered for the case when, due to the effects of “capacitance” and “eddy currents”, an active component arises in the EMF of the secondary coil, the 90° phase shift angle between this electromotive force and the current of the primary coil is violated (“phase defect”). At the same time, corrective terms ("admixture" and "frequency correction") appear in the resistance MI. These phenomena increase with an increase in the frequency and value of the supply current of the coils, when using ferromagnetic cores. Balanced AC bridges are used in well-known resistance component MI measurers; their disadvantages are listed. The developed measurer uses the phase method using a temporary separation of the measurement channel. The measuring circuit (MC) is powered by the current of a controlled generator of sinusoidal signals. In the MC, the measured parameters are converted into the phase shift angle between the two output voltages. These voltages are supplied to the analog inputs of a programmable microcontroller (MCC), in which angle is measured by the discrete counting method. During the measurement process, the MCC sets the frequency of the MC power generator, controls the position of the electronic switch of the measurement channel, measures angle and determines the values of the components of the MI complex resistance according to the specified algorithms. A method of theoretical investigation of measurement errors has been developed. The errors are caused by the inaccuracy and instability of the parameters of the MC and MCC elements appearing in the algorithms for determining the measured values. The method of error calculation is accompanied by a numerical example. The results of calculation of measurement errors are presented.

An Open Source Graph-Based Weighted Cycle Closure Method for Relative Binding Free Energy Calculations.

Free energy perturbation-relative binding free energy (FEP-RBFE) prediction has shown its reliability and accuracy in the prediction of protein-ligand binding affinities, which plays a fundamental role in structure-based drug design. In FEP-RBFE predictions, the calculation of each mutation path is associated with a statistical error, and cycle closure (cc) has proven to be an effective method in improving the calculation accuracy by correcting the hysteresis (summation of errors) of each closed cycle to the theoretical value 0. However, a primary hypothesis was made in the current cycle closure method that the hysteresis is evenly distributed to all paths, which is unlikely to be true in practice and may limit the further improvement of the calculation accuracy when better error estimation methods are available. Moreover, being a closed source software makes the current cycle closure method unachievable in many studies. In this paper, a newly implemented open source graph-based weighted cycle closure (wcc) algorithm was developed and introduced, not only including functions from the original cc method but also containing a new wcc method which can consider different error contributions from different paths and further improve the calculation accuracy. The wcc program also provides a new path-independent molecular error calculation method, which can be quite useful in many studies (like structure-activity relationship (SAR)) compared with the path-dependent method of the original cc program.

Optimization and S-N life cycle analysis of helical gear with nickel alloy MP35N

Gears are most critical components in mechanical power transmission systems. Helical gear is used to transmit power or torque at high speed, heavy loads with smooth and silent operation. It involves many variables including specific materials with consideration of force/stress analysis and its mechanical properties. The optimal design and its lead curve is the primary objective of the present work. The bending and surface strength of the gear tooth is considered to be the main contributors to gear failure. Thus, stress analysis on gear is vital to reduce the failures for optimal design. Analytical design for helical gear has been done with five different sets of parameters and then 3D modelling and FEM carried out with 30 cases and optimization was carried out to derive the best selection so that the fillet stress can be reduced and the life can be improved. The optimum lead curve is determined by the design of the experiment, transmission error calculation and response surface method. The results obtained in analytical design and FEM have been validated and it has been observed that by means of life it’s clear that Nickel alloy MP35N is more valuable and better material for manufacturing helical gear.

Quantitative Study of the T-AVIM-Based Simulated IMU Error in Polar Regions.

For solving the problem of polar performance of the inertial navigation system (INS) at mid-low latitudes, the simulation test system constructed by the “attitude and velocity invariant method of trajectory transfer rule based on the transverse coordinate system (T-AVIM)” of the Earth sphere model is used. The test system structure, especially the IMU conversion formula from mid-low latitudes to polar region simulation test, is introduced, and it is proved that the IMU conversion error can be equivalently superimposed on the bias error of the polar simulated IMU. According to the marine estimation formula for the effect of the reference error on the IMU conversion error, the specific influence of the constant error component and the random error component of the reference system on the simulated IMU is analyzed. The calculation method of the simulated IMU error is given with examples and intuitively explained, and the correctness of the theory is verified through simulation experiments.

Anomaly Detection for Internet of Things Time Series Data Using Generative Adversarial Networks With Attention Mechanism in Smart Agriculture.

More recently, smart agriculture has received widespread attention, which is a deep combination of modern agriculture and the Internet of Things (IoT) technology. To achieve the aim of scientific cultivation and precise control, the agricultural environments are monitored in real time by using various types of sensors. As a result, smart agricultural IoT generated a large amount of multidimensional time series data. However, due to the limitation of applied scenarios, smart agricultural IoT often suffers from data loss and misrepresentation. Moreover, some intelligent decision-makings for agricultural management also require the detailed analysis of data. To address the above problems, this article proposes a new anomaly detection model based on generative adversarial networks (GAN), which can process the multidimensional time series data generated by smart agricultural IoT. GAN is a deep learning model to learn the distribution patterns of normal data and capture the temporal dependence of time series and the potential correlations between features through learning. For the problem of generator inversion, an encoder–decoder structure incorporating the attention mechanism is designed to improve the performance of the model in learning normal data. In addition, we also present a new reconstruction error calculation method that measures the error in terms of both point-wise difference and curve similarity to improve the detection effect. Finally, based on three smart agriculture-related datasets, experimental results show that our proposed model can accurately achieve anomaly detection. The experimental precision, recall, and F1 score exceeded the counterpart models by reaching 0.9351, 0.9625, and 0.9482, respectively.

A Virtual Measurement Method of the Transmission Error Based on Point Clouds of the Gear

Abstract As the most widely used gear measuring instrument, the gear measuring center can measure the individual deviations of a gear tooth flank other than the comprehensive deviations of the gear. However, gear transmission error is an important transmission performance indicator in the gear meshing process. It is an important trend of gear measuring to obtain the transmission error from individual deviations. In this study, a calculation method of gear transmission error is proposed based on the point clouds of the gear obtained by optical sensors. According to the gear meshing principle, a method is introduced to determine the contact status between the tooth flanks formed by the point clouds. According to this introduced method, the single tooth pair meshing process and the meshing process of multiple tooth pairs are analyzed to determine the gear transmission error curve. The comparison results of tooth contact analysis and gear measurement experiments verify the proposed virtual measurement method.

A response surface methodology to determine the optimal objective function weightings within a multi-objective optimization digital human model used to predict postures

Multi-objective optimization digital human models permit users to predict postures that follow performance criteria, such as minimizing torques. Currently, it is unknown how to weight different objective functions to best predict postures. Objective one was to describe a response surface method to determine optimal objective function weightings to predict lift postures. Objective two was to evaluate the sensitivity of different error calculation methods. Our response surface approach has utility for determining optimal objective function weightings when using a digital human model to evaluate human-system interactions in early design stages. The approach was not dependent on variations in error calculation methods.

The Use of Genetic Algorithm, Multikernel Learning, and Least-Squares Support Vector Machine for Evaluating Quality of Teaching

The educational data mining (EDM) methods are increasingly diversified. In this research, a hybrid method of multikernel learning (MKL), least-squares support vector machine (LSSVM), and genetic algorithm (GA) is employed to evaluate teaching quality through nine indicators; the reliability of our proposed method is evaluated by confidence interval and prediction interval. First, English teaching quality samples occurring from three age groups at Guizhou Normal University are collected. Next, an intelligent method MK-LSSVM is proposed. Finally, the test sets are regression by the proposed model, and regression results are evaluated by confidence interval, prediction interval, and several error calculation methods; we also develop an ablation experiment for our proposed model. The experiment indicates that the MKL-LSSVM-GA outperforms other benchmark methods at three age-group levels. Additionally, at all three age-group levels, the experiment indicates that three indicators are crucial for the evaluation of teaching quality. Therefore, the proposed model in this paper can evaluate the English teaching quality effectively.

Research of optimization for crack propagation method

At present, extensive works have been done to predict the shape evolution of fatigue crack based on conventional numerical analysis method. However, few efforts have been made in the majorization of propagation points and increment for the accuracy of simulation. In this paper, a new error calculation method is proposed to quantify the simulation results and experimental results. Based on this, the influence of distribution and quantity of propagation points on the simulation results of crack propagation has been studied and optimized. And a kind of equivalent stress intensity factor amplitude expression based on the assumption that the stress intensity factor changes exponentially with crack depth is derived to achieve the larger crack growth increment by using calculus method. The validity is verified by comparing simulation results with existing expressions of stress intensity factor.

Forecasting Broiler Sales on CV. Berkah Bersama

The purpose of this study was to find out forecasting broiler chicken sales at CV. Berkah Bersama with using the trend moment method in May to July 2021. Previously the method was tested by its accuracy using the Mean Absolute Percentage Error (MAPE) calculation method. The data used in the form of sales data in the perioe January to April 2021. The result of the calculation of the accuracy of the trend moment method are 3% which indicate that the method is feasibleor can be used to predict the sale of broiler chicken on CV. Berkah Bersama. The result of calculation of forecasting chicken sales in the period May, June and July are equal to 60,957.90 Kg, 62,739.79 Kg dan 64,521.68 Kg. Keywords : Sales forecasting, Trend Moment Method, MAPE

Alignment error calculation and measurement method of a compact spaceborne focal plane

The thermal and mechanical stabilization of the focal plane assembly (FPA) naturally has a magnificent impact on the performance of space camera. Thermal and mechanical features of the proposed FPA are described first. Special attention is paid to the thermo-structure design of the FPA. Then the fitting methods based on singular value decomposition and least square are proposed to use the finite-element analysis results to predict the relative position changes between charge coupled devices under thermal and mechanical load cases. A comprehensive finite-element model of the FPA has been built, and the alignment errors, which were induced thermal and gravity loads, are predicted based on the proposed fitting method. To further prove that the design of FPA meets the mechanical and thermal stability requirements, an optical bench was developed. Meanwhile thermal cycling and vibration test of the three FPAs were performed; the alignment error measurements of the FPAs after each test were also performed. Both the simulation and tests show a good stability of the FPA design under operational and test environments.

Study on quantitative characterization method of measurement accuracy of geostress technology and equipment

In view of the shortcomings of existing research, the definition, quantitative characterization of all elements and its application of geostress measurement accuracy are studied. On the basis of the summary and classification of the measurement accuracy research in past decades, the definition of geostress measurement and its accuracy are given from the perspective of closed-loop measurement, different from the definition of taking rock mass as measurement object. The function and significance of the measurement accuracy research is also clearly pointed out. The quantitative characterization idea and procedure of geostress measurement accuracy are introduced. A physical model test device is provided, and the coordinate setting and the method of reducing the uncertainty of measurement accuracy representation by coordinate conversion are explained. 2D and 3D accuracy characterization formulas of all stress component which including single indexes of average-mode and maximum-mode are given first in the world, and the calculation method of angle error is discussed, the relationship between characterization modes and technical requirements is explained. Taking the measurement accuracy characterization of the physical model test results of early USBM borehole deformation gauge(USBM-type gauge) and CSIRO hollow inclusion strain cells(CSIRO HI cells) as example, the quantitative characterization process of measurement accuracy is shown, the characterization indexes are compared with the original ones, and the overall measurement error of the single index of the maximum-mode of the two test technology is 10% and 27%, respectively.Accuracy indexes of different dimension test methods are calculated and compared for the first time, and the data show that the overall measurement accuracy of the former is much better than the latter.

SafeDrive: Hybrid Recommendation System Architecture for Early Safety Predication Using Internet of Vehicles.

The Internet of vehicles (IoV) is a rapidly emerging technological evolution of Intelligent Transportation System (ITS). This paper proposes SafeDrive, a dynamic driver profile (DDP) using a hybrid recommendation system. DDP is a set of functional modules, to analyses individual driver’s behaviors, using prior violation and accident records, to identify driving risk patterns. In this paper, we have considered three synthetic data-sets for 1500 drivers based on their profile information, risk parameters information, and risk likelihood. In addition, we have also considered the driver’s historical violation/accident data-set records based on four risk-score levels such as high-risk, medium-risk, low-risk, and no-risk to predict current and future driver risk scores. Several error calculation methods have been applied in this study to analyze our proposed hybrid recommendation systems’ performance to classify the driver’s data with higher accuracy based on various criteria. The evaluated results help to improve the driving behavior and broadcast early warning alarm to the other vehicles in IoV environment for the overall road safety. Moreover, the propoed model helps to provide a safe and predicted environment for vehicles, pedestrians, and road objects, with the help of regular monitoring of vehicle motion, driver behavior, and road conditions. It also enables accurate prediction of accidents beforehand, and also minimizes the complexity of on-road vehicles and latency due to fog/cloud computing servers.