Error Characteristics Research Articles

Modeling and in-depth analysis of the mid-spatial-frequency error influenced by actual contact pressure distribution in sub-aperture polishing.

In ultra-precision optical processing, the sub-aperture polishing is prone to produce a mid-spatial-frequency (MSF) error. However, the generation mechanism of the MSF error is still not fully clarified, which seriously affects the further improvement of optical component performance. In this paper, it is proved that the actual contact pressure distribution between the workpiece and tool is a crucial source which affects the MSF error characteristics. A rotational periodic convolution (RPC) model is proposed to reveal the quantitative relationship among the contact pressure distribution, speed ratio (spin velocity/feed speed) and MSF error distribution. In-depth analyses show that the MSF error is linearly related to the symmetry level of contact pressure distribution and inversely proportional to the speed ratio, where the symmetry level is effectively evaluated by the proposed method based on Zernike polynomials. In the experiments, according to the actual contact pressure distribution obtained from the pressure-sensitive paper, the error rate of modeling results under different processing conditions is around 15%, which proves the validity of the proposed model. The influence of contact pressure distribution on the MSF error is further clarified through the establishment of RPC model, which can further promote the development of sub-aperture polishing.

Why is the forecast error of quarterly GDP in Japan so large? – From an international comparison of quarterly GDP forecast situation

We examined the accuracy of prediction of Canada, Japan, United Kingdom, and United States from the viewpoint of forecast errors. Compared with the forecast error of each country at the around same time, the forecast error of Japan is about 2 times larger. In case of Japan, even immediately before release of quarterly GDP, the forecast error is over 1 %, which is the same level of forecast error as 94 days before in the United States and 135 days before in Canada.Evaluating the characteristics of forecast errors, it can be pointed out that Japan's forecasts are as efficient as those of other countries, and the addition of major economic statistics is unlikely to improve forecast errors. The reason for Japan's large forecast errors is the fluctuations in the GDP growth rate. These results provide evidence that volatile GDP may make the outlook worse.Large fluctuations in Japan's quarterly GDP have already been pointed out. It is necessary to examine the factors behind the large fluctuations in the rate of change in Japan's quarterly GDP.

Error analysis of Raven's Coloured Progressive Matrices in children and adolescents with cerebral palsy.

Analysis of the errors in the Raven's Coloured Progressive Matrices (RCPM) has been previously performed for children with intellectual disabilities but has not been investigated for those with cerebral palsy (CP). This study aimed to investigate whether the types and positions of errors made by individuals with CP differed from those made by typically developing (TD) controls. Forty-five participants with CP aged 4-18years and 30 TD children aged 3-9years underwent RCPM testing. We first compared the RCPM performance and error characteristics between the groups and then examined the association between RCPM and the severity of CP and receptive vocabulary in the CP group. The results showed that while mean total scores in the two groups were comparable, the types and positions of errors made by individuals with CP differed from those of TD controls. The development of non-verbal intelligence in children with CP increased with age; when controlling for age, non-verbal intelligence was significantly correlated with all three functional levels of CP severity and receptive vocabulary. This study provides valuable insights into the problem-solving strategies employed by children with CP.

An INS/Geomagnetic Integrated Navigation Method for Coarse Estimation of Positioning Error and Search Area Adaption Applied to High-Speed Aircraft

The geomagnet aided inertial navigation algorithm has become one of the current research hotspots in the field of aircraft navigation. It can overcome the shortcomings of pure inertial navigation error accumulation over time and achieve long-term, autonomous, and all-weather navigation. The traditional iterative closest contour point (ICCP) algorithm, however, requires high sensor performance, has poor tolerance to noise, and has a complex algorithm with poor real-time performance. The timeliness of the traditional magnetic contour matching (MAGCOM) algorithm is related to the search area, the matching search area is fixed, and the algorithm is inflexible. To address the above problems, this article proposes a geomagnetic navigation method based on coarse estimation of navigation error and search area adaption. When the aircraft flies into the geomagnetic database region, the navigation error is roughly estimated based on the error characteristics of the inertial navigation system. Considering the influence of noise and uncertainty, three times the value of the estimated error is used as the edge length of the geomagnetic matching search area, and geomagnetic matching is performed for positioning. The product of velocity and time provided by the inertial navigation system is used as a constraint to determine whether the geomagnetic matching results are abnormal. If multiple consecutive geomagnetic matching results are normal, the navigation system automatically reduces the matching search area and search step to improve the matching accuracy and timeliness. Simulation experiments show that the accuracy of the adaptive search area geomagnetic matching method proposed in this article can reach within 200 m.

Compensation Method for the Nonlinear Characteristics with Starting Error of a Piezoelectric Actuator in Open-Loop Controls Based on the DSPI Model.

Nanopositioning stages with piezoelectric actuators have been widely used in fields such as precision mechanical engineering, but the nonlinear start-up accuracy problem under open-loop control has still not been solved, and more errors will accumulate, especially under open-loop control. This paper first analyzes the causes of the starting errors from both the physical properties of materials and voltages: the starting errors are affected by the material properties of piezoelectric ceramics, and the magnitude of the voltage determines the magnitude of the starting errors. Then, this paper adopts an image-only model of the data separated by a Prandtl-Ishlinskii model (DSPI) based on the classical Prandtl-Ishlinskii model (CPI), which can improve the positioning accuracy of the nanopositioning platform after separating the data based on the start-up error characteristics. This model can improve the positioning accuracy of the nanopositioning platform while solving the problem of nonlinear start-up errors under open-loop control. Finally, the DSPI inverse model is used for the feedforward compensation control of the platform, and the experimental results show that the DSPI model can solve the nonlinear start-up error problem existing under open-loop control. The DSPI model not only has higher modeling accuracy than the CPI model but also has better performance in terms of compensation results. The DSPI model improves the localization accuracy by 99.427% compared to the CPI model. When compared with another improved model, the localization accuracy is improved by 92.763%.

Transmission performance evaluation of non-circular spur bevel gear based on a novel isochronal measurement method

This paper aims to study the transmission performance evaluation of non-circular spur bevel gear (NCSB-gear) based on a novel isochronal measurement method. Firstly, the mathematical model of NCSB-gear is established. Then a novel isochronal measurement method is proposed, and the actual tooth surfaces are reconstructed by non-uniform rational B-spline interpolation. The advantages of the proposed method are discussed based on the geometric characteristics of tooth surface and measurement fitting error. A pair of forged NCSB-gears is measured through a coordinate measurement machine and the maximum tooth surface fitting error by the proposed method reduces 2μm compared with the traditional method. Moreover, deviation tooth contact analysis (DTCA) and load tooth contact analysis (LTCA) are conducted to evaluate the transmission performance. Finally, the transmission performance of measured NCSB-gear is obtained by a gear rolling tester. By comparing the TCA calculation of different measurement methods, it is found that the relative error of the maximum transmission error based on the isochronal measurement method reduces 4.719% compared with the traditional measurement method, thus verifying the validity of the proposed measurement method.

A framework for battery temperature estimation based on fractional electro-thermal coupling model

The temperature significantly affects the performance and safety of the battery. Therefore, this paper presents a novel framework for the estimation of the battery temperature based on a fractional-order electro-thermal coupling model. Due to the nonlinearity, coupling, and time varying parameters of lithium-ion batteries, the fractional-order equivalent circuit model is established using the fractional-order differential theory. Then it couples with the thermal model to establish the fractional order electro-thermal coupling model of lithium battery. Based on the model, the hybrid pulse power characteristic test method and the electro-thermal balance experiment are used to identify the parameters of the fractional order electro-thermal coupling model of lithium batteries. Finally, the fractional-order electro-thermal coupling model is used to estimate battery voltage, state of charge, and temperature under the conditions of the hybrid pulse power characteristic and the world transient vehicle cycle. The results show good consistency and responsiveness with the experiment under steady and dynamic conditions, and compared with the ETM, the characteristics of small error and low error rates of the F-ETM are introduced. Therefore, the fractional electrothermal coupling model of lithium batteries has good accuracy and applicability.

A Combination Scheme of Pure Strapdown and Dual-Axis Rotation Inertial Navigation Systems

Compared with the strapdown inertial navigation system (SINS), the rotation strapdown inertial navigation system (RSINS) can effectively improve the accuracy of navigation information, but rotational modulation also leads to an increase in the oscillation frequency of attitude errors. In this paper, a dual-inertial navigation scheme that combines the strapdown inertial navigation system and the dual-axis rotation inertial navigation system is proposed, which can effectively improve the attitude error accuracy in the horizontal direction by using the high-position information of the rotation inertial navigation system and the stability characteristics of the attitude error of the strapdown inertial navigation system. Firstly, the error characteristics of the strapdown inertial navigation system and the rotation strapdown inertial navigation system are analyzed, and then the combination scheme and Kalman filter are designed according to the error characteristics, and finally, the simulation experiment shows that the pitch angle error of the dual inertial navigation system is reduced by more than 35% and the roll angle error is reduced by more than 45% compared with the rotation strapdown inertial navigation system. Therefore, the combination scheme of double inertial navigation proposed in this paper can further reduce the attitude error of the rotation strapdown inertial navigation system, and at the same time, the two sets of inertial navigation systems can also enhance the reliability of ship navigation.

Environmental reporting quality in Japan: discussing normativity, quasi-mandatory approach and norm entrepreneurship

PurposeJapan applies a quasi-mandatory approach to corporate environmental reporting by defining the desired norm through formal law and guidelines and pushing large companies to be role models regardless of their sensitivity to environmental impacts. This study aims to analyze the change in Japanese companies reporting quality to justify this approach’s capability to produce normativity of environmental reporting.Design/methodology/approachThis study examines the change in corporate environmental reporting quality and the effect of company characteristics on it. The analysis focuses on 88 companies for 2008, 2013 and 2018, resulting in 264 company-year observations.FindingsThe result shows a continuous upward trend, although it is unsatisfactory regarding the comparability and free from error characteristics. Then, company size positively affects the quality, and sensitivity to environmental impacts does not. Overall, the findings indicate that Japan is moving toward normativity through the quasi-mandatory approach and the norm entrepreneurship of its large companies, regardless of their sensitivity to environmental impacts.Research limitations/implicationsThis study could relieve the belief that it is necessary to apply a mandatory approach to improve reporting quality and enrich views on the effect of company characteristics which mainly used only the legitimacy perspective.Originality/valueThis study proposes a more comprehensive measure of environmental reporting quality. The measure is based on the qualitative characteristics of useful information from the most influential accounting standard-setting bodies. In addition, the effect of company characteristics on the quality is explained based on the norm entrepreneurship view instead of the legitimacy perspective.

SYNTHESIS AND SIMPLE METHOD OF CHARACTERIZATION OF ALDEHYDE-SILICA GEL

Two approaches to the functionalization of the silica gel surface have been proposed, which make it possible to obtain materials with covalently immobilized highly reactive aldehyde groups. Immobilization of aldehyde groups in the first case is achieved by the click-reaction of azido-alkyne cycloaddition of 4-(prop-2-in-1-yloxy)benzaldehyde and 3-azidopropyl silica gel. In the second case, surface modification is performed by the alkylation reaction of hydroxybenzaldehydes with 3-chloropropyl silica gel. The obtained silica gel samples were characterized by infrared spectroscopy and thermogravimetric analysis data. In IR spectra absorption bands determination of aldehyde groups on the silica gel surface using 2.4 -dinitrophenylhydrazine has been proposed. The proposed method is based on the condensation reaction between the aldehyde groups grafted on the surface and 2.4 -dinitrophenylhydrazine. The quantitative estimation of the grafted aldehyde groups is suggested to be calculated by the difference between the initial amount of 2.4-dinitrophenylhydrazine and the amount remaining in the solution after the reaction. The necessity of maintaining a constant acidity of the medium by adding H2SO4 was established. It is shown that at λ = 315 nm the Bouguer-Beer-Lambert Law is satisfied in the concentration range 2.5∙10-5 to 12.5∙10-5 M. The correctness of the proposed method was checked using the procedure of operative control of the correctness of the results of chemical analysis. This procedure provides the determination of aldehyde groups in the modified material by multiply varying the silica gel weight and using the root-mean-square deviation of the repeatability of measurement results as an error characteristic. The proposed method for determining the aldehyde groups was tested on all silica gel samples. It was shown that by varying the conditions of surface modification it is possible to obtain materials with different functional capacity for aldehyde groups.

Surrogate model based prediction of transmission error characteristics based on generalized topography deviations

Simulation models of the tooth contact can provide valuable information of the gearbox operational behavior for deviated gears. It is therefore possible to gather geometry and deviation information of the two gears in contact and then estimate how they will perform in the assembled unit before even mounting them. This procedure could save time and costs used to disassemble gear boxes which fail the end of line tests because of acoustic reasons. The major challenge using sophisticated simulation models, which can describe the tooth contact is the tremendous amount of calculation time they need to produce suit-able results. In a productive gearbox manufacturing process this time is just not available. Therefore, a method to predict the operational behavior faster, than with the current used simulation models is needed. Firstly the size of the problem is downsized by introducing the sum deviation surface. It allows to reduce the number of necessary input parameters for a gear topography description to eighteen factors. With the help of that sum deviation surface, 3000 variants within a given variation space are calculated. The resulting training dataset is used to develop a deep neural network meta-model of the gear contact, which can predict the characteristics of the transmission error under load. With the help of that meta-model, the excitation of a gear pair can be predicted faster than real-time.

An Efficient Ensemble Technique for Hydrologic Forecasting Driven by Quantitative Precipitation Forecasts

Abstract Uncertainty in quantitative precipitation forecasts (QPFs) from numerical weather prediction (NWP) models manifests in errors in the amounts of rainfall, storm structure, storm location, and timing, among other precipitation characteristics. In flash flood forecasting applications, errors in the QPFs can translate into significant uncertainty in forecasts of surface water flows and their impacts. In particular, the QPF errors in location and structure result in errors on flow paths, which can be highly detrimental in identifying locations susceptible to flash flood impacts. To account for this type of uncertainty, the neighboring pixel ensemble technique (NPET) was devised and implemented as a postprocessing algorithm of deterministic or ensemble outputs from a distributed hydrologic model. The aim of the technique is to address displaced hydrologic responses resulting from location biases in QPFs using a probabilistic approach. NPET identifies a sampling region surrounding each forecast pixel and builds an ensemble of surface water flow values considering the pixel’s physiographic similarities. The probabilistic information produced with NPET can be calibrated through a set of tunable parameters that are adjusted to account for NWP-specific QPF error characteristics. The utility of NPET is demonstrated for the Ellicott City flash flood event on 27 May 2018, using products and tools routinely used in the U.S. National Weather Service for warning operations. Results from this case demonstrate that NPET effectively conveys uncertainty information about QPF precipitation location in a hydrologic context. Significance Statement This study introduces a new method suitable for operational use called the neighboring pixel ensemble technique (NPET). NPET is an algorithm that generates ensemble-based streamflow forecasts accounting for the location uncertainties in quantitative precipitation forecasts (QPFs) without the requirement of multiple hydrologic model runs. NPET is capable of this feat through probabilistic assimilation of a priori QPF displacement information and its uncertainty. The application of NPET with the Flooded Locations and Simulated Hydrographs (FLASH) project shows the technique could be beneficial for flash flood warning operations in the U.S. National Weather Service (NWS). It is envisioned that the application of NPET with Warn-on-Forecast System (WoFS)-forced FLASH outputs will further enhance the quality of flash flood forecasts that support NWS warning operations.

Estimating the Relative Impact of Measurement, Parameter, and Flow Law Errors on Discharge from the Surface Water and Ocean Topography Mission

Abstract The Surface Water and Ocean Topography (SWOT) mission will allow the estimation of discharge in rivers wider than 100 m, filling important gaps in the network of in situ measurements. This novel source of discharge observations has the potential to enable significant progress toward closing Earth’s water budget and creating new understanding of the water cycle. Quantifying the uncertainty in the SWOT estimates of discharge, mapping the error sources, and understanding their relative importance is essential to the fulfillment of this potential. Here, we break the SWOT discharge production process into its essential parts: 1) retrieval of river width and water surface heights and slopes, 2) estimation of unobservable parameters, and 3) computation of discharge with the selected flow law, and through a Monte Carlo simulation study, we assess the sensitivity of the overall discharge error to each of these parts. We analyze the discharge error characteristics in terms of bias, error standard deviation, and the correlation between true and retrieved discharges and map the contribution of the essential discharge production elements to each of the error metrics. Our study revealed that biases in parameters are the most important source of discharge biases, yet we found that a larger than expected fraction of the discharge biases can be attributed to observation errors. Surprisingly, we found that parameter biases are also the most important contributor to discharge error standard deviation and to the deterioration of the correlation between truth and retrieved discharges, which were previously thought of as being controlled by observation errors.

Clustering-based average state observer design for large-scale network systems

This paper addresses the aggregated monitoring problem for large-scale network systems with a few dedicated sensors. Full state estimation of such systems is often infeasible due to unobservability and/or computational infeasibility; therefore, through clustering and aggregation, a tractable representation of a network system, called a projected network system, is obtained for designing a minimum-order average state observer. This observer estimates the average states of the clusters, which are identified under explicit consideration of estimation error. Moreover, given the clustering, the proposed observer design algorithm exploits the structure of the estimation error dynamics to achieve computational tractability. Simulations show that the computation of the proposed algorithm is significantly faster than the usual H2/H∞ observer design techniques. On the other hand, compromise on the estimation error characteristics is shown to be marginal.

Unraveling the Usage Characteristics of Human Element, Human Factor, and Human Error in Maritime Safety

Human-related issues have become a popular topic in maritime safety research, with an increasing number of relevant research articles being published annually. However, a persistent problem in this field is that three terms, namely “human element”, “human factor”, and “human error” are used interchangeably in the literature. This issue poses questions regarding the characteristics of their usage; do these three terms have the same meaning? Herein, we conducted systematic research on the three terms by analyzing official information and published research using a collecting–classifying–summarizing policy. The results show that “human error” is easier to identify than “human element” and “human factor”, while the latter two terms have intersecting contents. These contents prompt the user to decide which term to choose depending on the situation. Herein, we aim to help scholars accurately distinguish these terms.

Gravity disturbance compensation for dual-axis rotary modulation inertial navigation system

Gravity disturbance compensation is an important technique for improving the positioning accuracy of high-precision inertial navigation systems (INS). Aiming at the current problems of the resolution of gravity compensation background field and the robustness of gravity compensation algorithm are insufficient for gravity compensation. In this study, the error and frequency characteristics of INS caused by gravity disturbances are investigated. The gravity disturbance with a spatial resolution of 1’ × 1’ from a high-precision satellite altimetry marine gravity field model is preliminarily introduced into the initial alignment and pure INS calculation to implement the gravity compensation of the dual-axis rotary modulation INS. Detailed calculation results show that the east gravity disturbance affects the north attitude, and the north gravity disturbance affects the east attitude in the initial alignment. In the pure INS calculation, the horizontal gravity disturbance causes a navigation error in the form of Schuler oscillation. The INS navigation error caused by horizontal gravity disturbance is mainly affected by its amplitude; however, the horizontal gravity disturbance accuracy from the satellite altimetry model for INS gravity compensation can be ignored in practice. In addition, for low-speed underwater vehicles, the influence of high-frequency gravity disturbance signals on the INS position shows an increasing trend. Finally, the effectiveness of the gravity compensation achieved by the horizontal gravity disturbance from the satellite altimeter model is confirmed by a dynamic shipborne test. The positioning accuracy of the rotary modulation INS is maximally improved by approximately 17.9% after the horizontal gravity disturbance is compensated simultaneously in the pure INS calculation and the initial alignment.

Statistical perception of the chaotic fabrication error and the self-adaptive processing decision in ultra-precision optical polishing.

Subaperture polishing is a key technique for fabricating ultra-precision optics. However, the error source complexity in the polishing process creates large fabrication errors with chaotic characteristics that are difficult to predict using physical modelling. In this study, we first proved that the chaotic error is statistically predictable and developed a statistical chaotic-error perception (SCP) model. We confirmed that the coupling between the randomness characteristics of chaotic error (expectation and variance) and the polishing results follows an approximately linear relationship. Accordingly, the convolution fabrication formula based on the Preston equation was improved, and the form error evolution in each polishing cycle for various tools was quantitatively predicted. On this basis, a self-adaptive decision model that considers the chaotic-error influence was developed using the proposed mid- and low-spatial-frequency error criteria, which realises the automatic decision of the tool and processing parameters. An ultra-precision surface with equivalent accuracy can be stably realised via proper tool influence function (TIF) selection and modification, even for low-deterministic level tools. Experimental results indicated that the average prediction error in each convergence cycle was reduced to 6.14%. Without manual participation, the root mean square(RMS) of the surface figure of a ϕ100-mm flat mirror was converged to 1.788 nm with only robotic small-tool polishing, and that of a ϕ300-mm high-gradient ellipsoid mirror was converged to 0.008 λ. Additionally, the polishing efficiency was increased by 30% compared with that of manual polishing. The proposed SCP model offers insights that will help achieve advancement in the subaperture polishing process.

Design of high-efficiency complex multiplier for fault-tolerant computation

In this paper, two improved structures and a truncation strategy with compensation for complex multiplication are proposed. Simulation in 28-nm CMOS for hardware performance is provided. Compared to the general complex multiplier, the two accurately improved structures realize 18.58% and 20.80% power consumption reduction, respectively. The truncation strategy with compensation reduces power consumption by 46.8% and controls Mean Relative Error Distance (MRED) at 0.54%. To verify the practicability of the proposed architecture, our designs are applied to the Fast Fourier Transform (FFT) processor to comprehensively evaluate the error characteristics and circuit performance.

The Integrated Strategy of LIDAR Points’ Evaluation Localization and Lateral Tracking Optimization for a New Parking Robot's Tight Space Transportation

With the increase of car's number, the problem of insufficient parking space in cities is becoming more and more prominent. The high-density parking lots using parking robots can greatly improve space utilization. However, there is a great collision risk in the parking lot's tight space navigation. So, precise LIDAR localization and trajectory tracking control are the key technologies of autonomous driving along a predetermined path. Due to the laser points’ sparse character, the LIDAR points’ extracted features have distribution errors. In order to further optimize the LIDAR's localization, this article establishes the feature's error ellipsoid model, and the model's information and error entropies are calculated separately. The error entropy is utilized to optimize the feature-matching weight and improve the localization accuracy. Based on the higher localization result, a state-of-the-art lateral tracking model is proposed to address the challenges faced by the long parking robot. Then, the adaptive fuzzy control is designed to achieve precise control of wheel motion. Finally, an experimental platform is built to compare the effectiveness of different positioning and tracking algorithms. The comparison results show that the integration of laser evaluation localization and lateral tracking optimization algorithm can provides a collision-free improvement of 50% in the parking lot's tight spaces.

Gravity Matching Algorithm Based on Correlation Filter

The gravity-matching algorithm is one of the key technologies in the gravity-aided inertial navigation system (GAINS). The matching accuracy determines the correction accuracy of the inertial navigation system (INS). However, the initial position error of the INS and gravity measurement error lead to a decrease in matching accuracy. In this article, the characteristics of gravity measurement error and inertial navigation information are made full use of to reduce the impact on matching. A gravity-matching algorithm based on a correlation filter (CF) is proposed, which includes preprocessing, CF, and mismatch detection. Meanwhile, the shape of the INS trajectory is used as a constraint to reduce the mismatch caused by the measurement error to improve the matching accuracy. Moreover, two matching strategies are given, including normal matching and sliding window matching. Experimental results show that the proposed method can effectively improve the matching accuracy under initial position error and gravity measurement error.