Errors In Field Measurements Research Articles

The Effect of Vehicles Attitude Angle Error on Magnetic Compass Heading Estimation

The three-component magnetic sensor is used to measure the heading of the vehicle. Under working, the magnetic sensor be rotated to the horizontal plane according to the attitude angle of the vehicle, and then the heading estimation is performed. However, the vehicle’s attitude angle measurement errors affect the accuracy of the magnetic sensor measurement’s east and north components and then lead to a false heading result. Based on the relation of magnetic field measurement error and magnetic heading error, the effect model of geomagnetic measurement error on magnetic heading error is derived in this paper. Finally, the characteristics of attitude angle errors on magnetic heading are verified by experiments, and the results show that particular angles can avoid the magnetic compass’s effect by the vehicle’s attitude angle error.

Boiler Furnace Temperature Field Measurement and Reconstruction Error Elimination Based on Temperature Field Residual Correction Network

Boiler Furnace Temperature Field Measurement and Reconstruction Error Elimination Based on Temperature Field Residual Correction Network

Underwater magnetic field measurement error compensation based on improved mayfly algorithm

This paper investigates the magnetic filed interference problem when the ROV equipped with a three-axis magnetometer measures the magnetic field of underwater magnetic targets within a short range, and a magnetic field compensation method based on an improved mayfly algorithm is proposed to improve the measurement accuracy of underwater magnetic field information. Firstly, a compensation model is established based on the installation error of the three-axis magnetometer and the interference magnetic field of the ROV. Then, in view of the problem that the original mayfly algorithm is easy to fall into local optimal and the convergence accuracy is poor, the Tent chaotic sequence and the Levy flight mutation strategy are introduced to improve the original mayfly algorithm. Finally, a series of magnetic field information is obtained through the three-axis magnetometer, and the original mayfly algorithm, particle swarm algorithm and improved mayfly algorithm are used to estimate the compensation parameters. The experimental results show that the improved mayfly algorithm has obtained faster convergence speed and higher compensation accuracy than others.

A pilot study on an electromagnetic tracking system using tunneling magnetoresistance (TMR) sensors applicable to a 4F catheter (1.4mm in diameter).

Tracking the position and orientation of a 4F catheter ([Formula: see text] 1.4mm) is required in superselective intra-arterial chemotherapy (SSIAC). Tunneling magnetoresistance (TMR) sensors, which measure magnetic fields, are promising candidates because the size of the TMR sensor can be less than a few tenths of a millimeter. The purpose of this paper is to prove the feasibility of an EMT system utilizing TMR sensors as magnetometers. Three 1-axis TMR sensors (0.3mm × 0.3mm) were packaged on a flexible printed circuit board (PCB) together with an amplifier chip. The PCB was integrated into a 4F catheter. Six field generator coils driven by alternating current (AC) at different frequencies were used. Magnetic field measurement errors were evaluated to assess the effect of electromotive force (EMF) on TMR-based sensing by changing the coils' driving frequencies. The tracking error was also evaluated. As a result, the feasibility of catheter navigation utilizing the EMT system was demonstrated. There was a positive correlation between the frequency and the magnetic field measurement error using the TMR sensor (R2 = 0.999). With magnetic field frequencies less than 603Hz, the average position and orientation estimation error were 10.1mm and 2.3degree, respectively. Under ideal conditions, the average estimation error values were 0.9mm and 0.3degree, respectively. The position and orientation errors varied with frequency owing to the induced electromotive force. We should consider the effect of electromotive force on TMR sensor assemblies caused by alternating magnetic fields. An EMT system using TMR sensors was validated, although room for further improvement was identified.

Cross-Axis Dynamic Field Compensation of Optically Pumped Magnetometer Arrays for MEG

We present dynamic field compensation (DFC), whereby three-axis field measurements from reference magnetometers are used to dynamically maintain null at the alkali vapor cells of an array of primary sensors that are proximal to a subject's scalp. Precision measurement of the magnetoencephalogram (MEG) by zero-field optically pumped magnetometer (OPM) sensors requires that sensor response is linear and sensor gain is constant over time. OPMs can be operated in open-loop mode, where the measured field is proportional to the output at the demodulated photodiode output, or in closed-loop, where on-board coils are dynamically driven to maintain the internal cell at zero field in the measurement direction. While OPMs can be operated in closed-loop mode along all three axes, this can increase sensor noise and poses engineering challenges. Uncompensated fluctuations in the ambient field along any statically nulled axes perturb the measured field by tipping the measurement axis and altering effective sensor gain – a phenomenon recently referred to as cross-axis projection error (CAPE). These errors are particularly problematic when OPMs are allowed to move in the remnant background field. Sensor gain-errors, if not mitigated, preclude precision measurements with OPMs operating in the presence of ambient field fluctuations within a typical MEG laboratory. In this manuscript, we present the cross-axis dynamic field compensation (DFC) method for maintaining zero field dynamically on all three axes of each sensor in an array of OPMs. Together, DFC and closed-loop operation strongly attenuate errors introduced by CAPE. This method was implemented by using three orthogonal reference sensors together with OPM electronics that permit driving each sensor's transverse field coils dynamically to maintain null field across its OPM measurement cell. These reference sensors can also be used for synthesizing 1st-gradient response to further reduce the effects of fluctuating ambient fields on measured brain activity and compensate for movement within a uniform field. We demonstrate that, using the DFC method, magnetic field measurement errors of less than 0.7% are easily achieved for an array of OPM sensors in the presence of ambient field perturbations of several nT.

Real-time sextupole tuning for a long in-plane polarization at storage rings

A long in-plane beam polarization can be a desired feature for spin measurement experiments in storage rings. The spin precession of the particles within a beam can be controlled by means of the frozen spin method and beam bunching via RF cavities, eventually yielding a polarization lifetime of 10–100 s. Previous studies have shown that it can be further improved by sextupoles, which correct the second order effects related to the chromaticity of the beam. However, sextupoles can require readjustment after slight changes in ring parameters. This work presents a real-time sextupole tuning method that relies on a feedback algorithm. It adjusts the sextupole strength during storage, targeting a zero average radial spin component. Satisfying this condition results in a longer polarization lifetime. Simulation studies show that roughly determined feedback coefficients in this method work effectively for a wide range of ring parameters, with practical field imperfections and measurement errors taken into account. Alternatively, this technique can be used to optimize sextupole strengths in a test run without intervening the measurement.

Community approach for reducing small field measurement errors: Experience over 24 centres

PurposeThe complexity of the modern Stereotactic Body Radiation Therapy (SBRT) techniques requires comprehensive quality assurance programs, to ensure the right treatment to the patient. Dosimetry of small radiation fields is a challenge especially for radiotherapy centres starting to work on this issue. The matter to be discussed here concerns the need of detailed measurement procedures and cross checks to be paired to the usual recommendations on detectors and correction factors. Materials and MethodsThe presented work involved 24 Italian radiotherapy centres, with the specific purpose to minimize systematic errors in output factor measurements over different radiotherapy centres. Using the unshielded silicon diode IBA Razor, reference curves for the relative signal ratio (RSR) as a function of beam size were created for each Linac family. ResultsWith this study we have demonstrated consistency of small field dosimetry on all the centres involved, moreover all radiotherapy centres using Razor are allowed to compare measurements amongst each other and centres with values deviating more than 5% from the reference curve are advised to repeat their measurements. With this procedure, some critical issues were detected from two centres in RSR measurements, that, if implemented into the own treatment planning system, would induce an unwanted overdosage larger than 5%. ConclusionsThe proposed approach could allow one to envision high-skilled therapy centres providing support to those featuring minor experience and could represent an important strategy for the clinical implementation of emerging technologies at high quality levels. The methodology adopted exploits crowd knowledge methods which could be applied in others areas of radiation dosimetry.

Identification of Groundwater Pollution Sources by a SCE-UA Algorithm-Based Simulation/Optimization Model

Prevention and remediation strategies for groundwater pollution can be successfully carried out if the location, concentration, and release history of contaminants can be accurately identified. This, however, presents a challenge due to complex groundwater systems. To address this issue, a simulation-optimization (S/O) model by integrating MODFLOW and MT3DMS into a shuffled complex evolution (SCE-UA) optimization algorithm was proposed; this coupled model can identify the unknown groundwater pollution source characteristics. Moreover, the Grids Traversal algorithm was used for automatically searching all possible combinations of pollution source location. The performance of the proposed S/O model was tested by three hypothetical scenarios with various combinations of mixed situations (i.e., single and multiple pollution source locations, known and unknown pollution source locations, steady-state flow and transient flow). The field measurement errors was additionally considered and analyzed. Our results showed that this proposed S/O model performed reasonably well. The identified locations and concentrations of contaminants fairly matched with the imposed inputs with average normalized deviations less than 1% after sufficient generations. We further assessed the impact of generation number on the performance of the S/O model. The performance could be significantly improved by increasing generation number, which yet resulted in a heavy computational burden. Furthermore, the proposed S/O model performed more efficiently and robustly than the traditionally used artificial neural network (ANN)-based model. This is due to the internal linkage of numerical simulation in the S/O model that promotes the data exchange from external files to programming variables. This new model allows for solving the source-identification problems considering complex conditions, and thus for providing a platform for groundwater pollution prevention and management.

A glacier runoff extension to the Precipitation Runoff Modeling System

AbstractA module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed‐parameter, physical‐process hydrological simulation code. The extension does not require extensive on‐glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while maintaining model usability. PRMSglacier is validated on two basins in Alaska, Wolverine, and Gulkana Glacier basin, which have been studied since 1966 and have a substantial amount of data with which to test model performance over a long period of time covering a wide range of climatic and hydrologic conditions. When error in field measurements is considered, the Nash‐Sutcliffe efficiencies of streamflow are 0.87 and 0.86, the absolute bias fractions of the winter mass balance simulations are 0.10 and 0.08, and the absolute bias fractions of the summer mass balances are 0.01 and 0.03, all computed over 42 years for the Wolverine and Gulkana Glacier basins, respectively. Without taking into account measurement error, the values are still within the range achieved by the more computationally expensive codes tested over shorter time periods.

О разрешающей способности метода дирекционных магнитотеллурических зондирований

The problem is to examine the resolution of directional magnetotelluric soundings (DMTS). Abrupt changes of impedances of electrical and magnetic types in critical region of parameters R~0, J~ωµσ are shown to result in significantly higher resolution of the method as compared with the traditional interpretation using Tikhonov–Cagniard impedance. The stability of solution of DMTS method inverse problem is considered subject to field measurement errors limited the resolution. The minimum of the limits is determined for the conductivity ∆σ/σ small variations. For studying DMTS resolution as applied to MT monitoring of earthquake site the mathematical experiment for three-layer geoelectric model was carried out. When changing the earthquake site conductivity of ∆σ~±10 % variations of reflection coefficient of electric mode are in the range of 20 % that is significantly more than the field measurement error. The possibility for prediction modeling in the context of obtained results is discussed.

Sensor Interaction as a Source of the Electromagnetic Field Measurement Error

Abstract The article deals with analytical calculation and numerical simulation of interactive influence of electromagnetic sensors. Sensors are components of field probe, whereby their interactive influence causes the measuring error. Electromagnetic field probe contains three mutually perpendicular spaced sensors in order to measure the vector of electrical field. Error of sensors is enumerated with dependence on interactive position of sensors. Based on that, proposed were recommendations for electromagnetic field probe construction to minimize the sensor interaction and measuring error.

Snow stratigraphic heterogeneity within ground‐based passive microwave radiometer footprints: Implications for emission modeling

Two-dimensional measurements of snowpack properties (stratigraphic layering, density, grain size, and temperature) were used as inputs to the multilayer Helsinki University of Technology (HUT) microwave emission model at a centimeter-scale horizontal resolution, across a 4.5 m transect of ground-based passive microwave radiometer footprints near Churchill, Manitoba, Canada. Snowpack stratigraphy was complex (between six and eight layers) with only three layers extending continuously throughout the length of the transect. Distributions of one-dimensional simulations, accurately representing complex stratigraphic layering, were evaluated using measured brightness temperatures. Large biases (36 to 68 K) between simulated and measured brightness temperatures were minimized (−0.5 to 0.6 K), within measurement accuracy, through application of grain scaling factors (2.6 to 5.3) at different combinations of frequencies, polarizations, and model extinction coefficients. Grain scaling factors compensated for uncertainty relating optical specific surface area to HUT effective grain size inputs and quantified relative differences in scattering and absorption properties of various extinction coefficients. The HUT model required accurate representation of ice lenses, particularly at horizontal polarization, and large grain scaling factors highlighted the need to consider microstructure beyond the size of individual grains. As variability of extinction coefficients was strongly influenced by the proportion of large (hoar) grains in a vertical profile, it is important to consider simulations from distributions of one-dimensional profiles rather than single profiles, especially in sub-Arctic snowpacks where stratigraphic variability can be high. Model sensitivity experiments suggested that the level of error in field measurements and the new methodological framework used to apply them in a snow emission model were satisfactory. Layer amalgamation showed that a three-layer representation of snowpack stratigraphy reduced the bias of a one-layer representation by about 50%.

An assessment of field-portable X-ray fluorescence analysis for nickel and iron in laterite ore (New Caledonia)

The aim of this work was to determine how in-situ portable XRF (pXRF) analysis of ores (in this study, nickel and iron) may be consistent with data obtained from well-prepared samples analysed by conventional XRF methods, and to investigate potential sources of error in field measurements due to different chemical composition, moisture content and particle size. For this study, 201 samples of saprolite and laterite, sieved at 125 μm, were selected for their Ni and Fe contents (from 0.119 to 5.225 % Ni and from 4.7 to 37.2 % Fe for saprolite samples and from 0.38 to 2.94 % Ni and from 21.5 to 55.55 % Fe for laterite samples), compressed to make powder pellets and used to calibrate the pXRF. It is shown that for these two elements, pXRF can correlate extremely well (r 2 > 0.98, relative standard error <7 %) with conventional laboratory results when samples are suitably prepared (dried, pulverized and pelletized). Laboratory analysis of a few artificially wetted samples shows that both Ni and Fe estimated concentrations are directly proportional to moisture content. In the field, two experiments were conducted, one on an air-dried drill-core and the second directly on the pit face. The results indicate that because of sample heterogeneity, Ni and Fe contents are better estimated in the laterite layer than in the saprolite layer. Despite the many challenges associated with field conditions, pXRF can provide useful benefits for a number of applications in the mining sector.

Numerical Analysis of Isotropy Electromagnetic Sensor Measurement Error

Abstract The article deals with classification and quantification of electromagnetic field measurement errors in case an isotropic sensor as a field probe is used. The focus is mainly on the error of measurement method, resulting from mutual interaction of the field probe sensors associated with the origin of the so-called mutual impedance.

The importance of non-photon noise in stellar spectropolarimetry

The low-resolution, Cassegrain mounted, FORS spectropolarimeter of the ESO Very Large Telescope is being extensively used for magnetic field surveys. Some of the new discoveries suggest that relatively strong magnetic fields may play an important role in numerous physical phenomena observed in the atmospheres as well as in the circumstellar environments of certain kinds of stars. We show in detail how small instabilities or data-reduction inaccuracies represent an alternative explanation for the origin of certain signals of circular polarisation published in recent years. With the help of analytical calculations we simulate the observation of a spectral line in spectropolarimetric mode, adding very small spurious wavelength shifts, which may mimic the effects of seeing variations, rapid variations of the stellar radial velocity, or instrument instabilities. As a case study, we then re-visit the FORS2 measurements that have been used to claim the discovery of a magnetic field in the A0 supergiant HD 92207. In addition, we present new observations of this star obtained with the HARPSpol instrument. Both calibration and science data show compelling evidence that photon-noise is not the only source of error in magnetic field measurements, especially in sharp spectral lines. Non-photon noise may be kept under control by accurate data reduction and quality controls. Our re-analysis of FORS2 observations of HD 92207 shows no evidence of a magnetic field, and we are able to reproduce the previous FORS detection only by degrading the quality of our wavelength calibration. Our HARPSpol spectropolarimetric measurements show no evidence of a magnetic field at the level of 10 G.

Verification methods and antenna horizontal beamwidth of across-the-road radar for traffic speed enforcement in China

Across-The-Road (ATR) radar is the most common type of traffic speed measurement devices used in China for traffic law enforcement. Its speed measurement accuracy is highly concerned by drivers, lawyers, policemen and metrologists as well. Among those influence factors, antenna horizontal beamwidth is an important one, which has not been taken into account in the current verification regulation of ATR radar in China. In this paper, the current verification methods of ATR radar in China are firstly introduced, and the reason for the field measurement error of ATR radar is analyzed. The speed measurement error of ATR radar related to antenna horizontal beamwidth is investigated in details, and theoretically calculated in various combinations of installation angles and horizontal beamwidths. Field tests with three equal-distanced piezo sensors each lane as triggering reference have also been performed on two ATR radar samples with horizontal beamwidth 5° and 10° respectively. The results of theoretical analysis and field tests verify that antenna horizontal beamwidth smaller than 6° is a precondition for accurate and reliable field measurements, which has also been added to the newly published pattern approval regulation of ATR radar in China.

Heterogeneous or homogeneous? Implications of simplifying heterogeneous streambeds in models of losing streams

Summary A common approach in modeling surface water–groundwater interaction is to represent the streambed as a homogeneous geological structure with hydraulic properties obtained by means of model calibration. In reality, streambeds are highly heterogeneous, and there are currently no methodical investigations to justify the simplification of this geologic complexity. Using a physically based numerical model, synthetic surface water–groundwater infiltration flux data were generated using heterogeneous streambeds for losing connected, losing transitional and losing disconnected streams. Homogeneous streambed hydraulic conductivities were calibrated to reproduce these fluxes. The homogeneous equivalents were used for predicting infiltration fluxes between streams and the aquifer under different hydrological conditions (i.e. for different states of connection). Homogeneous equivalents are shown to only accurately reproduce infiltration fluxes if both the calibration and prediction are made for a connected flow regime, or if both the calibration and prediction are made for a disconnected flow regime. The greatest errors in flux (±34%) using homogeneous equivalents occurred when there was a mismatch between the flow regime of the observation data and the prediction. These errors are comparatively small when compared with field measurement errors for hydraulic conductivity, however over long river reaches these errors can amount to significant volumes of water.

Effect of Data Collection on the Estimation of Wall Reaction Coefficients for Water Distribution Models

During a model calibration process, errors in field measurements propagate to uncertainties in model parameter estimates and model predictions. This paper presents a means to quantify that effect in a water distribution water quality model and provides guidance on data collection experiment design. Water quality in the distribution systems is dominated by advective transport that is hydraulically driven. The hydraulic model, including the nodal demand, is assumed well calibrated and provides no uncertainty. Thus, only the wall decay coefficients are to be estimated and evaluated. The uncertainty assessment procedure consists of a parameter estimation model, parameter estimation uncertainty analysis, and model prediction uncertainty analysis. The shuffled frog leaping algorithm (SFLA), an optimization algorithm, is used to estimate the parameters in the water quality model in a least-squares regression given a set of field data. The parameter uncertainty is calculated using a first-order approximation and is further propagated to model prediction uncertainty. The model prediction uncertainty is calculated using a similar first-order analysis. The methodology is applied to two networks. Alternative conditions are analyzed in terms of data collection and model prediction conditions to examine the benefits of performing pulse injection test and data collection design. The results showed that pulse injection provides more information and better parameter estimates. As a result, parameters estimated from a data set with pulse injection produced lower model prediction uncertainty. For a given simulation time, earlier pulses remained in the system for a longer duration, providing more calibration information and, hence, improving parameter estimation accuracy.

Evaluation of multiple-sphere head models for MEG source localization

Magnetoencephalography (MEG) source analysis has largely relied on spherical conductor models of the head to simplify forward calculations of the brain's magnetic field. Multiple- (or overlapping, local) sphere models, where an optimal sphere is selected for each sensor, are considered an improvement over single-sphere models and are computationally simpler than realistic models. However, there is limited information available regarding the different methods used to generate these models and their relative accuracy. We describe a variety of single- and multiple-sphere fitting approaches, including a novel method that attempts to minimize the field error. An accurate boundary element method simulation was used to evaluate the relative field measurement error (12% on average) and dipole fit localization bias (3.5 mm) of each model over the entire brain. All spherical models can contribute in the order of 1 cm to the localization bias in regions of the head that depart significantly from a sphere (inferior frontal and temporal). These spherical approximation errors can give rise to larger localization differences when all modeling effects are taken into account and with more complex source configurations or other inverse techniques, as shown with a beamformer example. Results differed noticeably depending on the source location, making it difficult to recommend a fitting method that performs best in general. Given these limitations, it may be advisable to expand the use of realistic head models.

SU‐E‐T‐269: Study IMRT Dosimetry Uncertainty Factors by Simulation

Purpose: To analyze IMRT dosimetry uncertainty by simulation, and identify the key error from IMRT verification. Method: IMRT uncertainty factors are convoluted in the routine verification results, and can be from treatment plan, LINAC, and QA tools. With similar dosimetry coverage, several controlled IMRT plans can be generated by varying optimization parameters and algorithms. Some of them are more sensitive to certain perturbation and may fail to pass routine IMRT QA. First we modify the plan parameters to simulate the uncertainties. For example, we change MLC leaf and isocenter positions to simulate leaf and setup errors, and we change machine with different output factors to simulate small field measurement error. Then we import the plan back for dose calculation and comparison. Results: In the high dose region with low gradient, the mean dose is quite robust to positioning perturbation. In prostate case, the mean dose changes are within 2%, even with ±5mm random MLC leaf, or setup error. For HN cases, the mean dose changes are within 3% for most of perturbed plan with same uncertainties. However, large variations for the point dose from each beam are observed. The random MLC leaf error results the distribution broadened in the analysis of planar dose error distribution. As for the small field output factor error, it can cause a typical prostate IMRT case fail to pass standard QA criteria dependent on the plan. The small field error can behave randomly in the distribution of percentage dose error. In the low dose region with low gradient, simulation results indicated systematical MLC leaf position error is important, apart for MLC modeling parameters. Conclusion: IMRT verification is a part of on‐going efforts to improve the IMRT process. By identifying the key factors from QA data to optimizes the IMRT treatment.