Identification Of Error Sources Research Articles

Error Characteristic Analysis and Error Source Identification of Aeromagnetic Field Gradient Tensor Measurements

Error Characteristic Analysis and Error Source Identification of Aeromagnetic Field Gradient Tensor Measurements

An Investigation into Error Source Identification of Machine Tools Based on Time-Frequency Feature Extraction

This paper presents a new identification method to identify the main errors of the machine tool in time-frequency domain. The low- and high-frequency signals of the workpiece surface are decomposed based on the Daubechies wavelet transform. With power spectral density analysis, the main features of the high-frequency signal corresponding to the imbalance of the spindle system are extracted from the surface topography of the workpiece in the frequency domain. With the cross-correlation analysis method, the relationship between the guideway error of the machine tool and the low-frequency signal of the surface topography is calculated in the time domain.

Identification of error sources in high precision weight measurements of gyroscopes

A number of weight anomalies have been reported in the past with respect to gyroscopes. Much attention was gained from a paper in Physical Review Letters, when Japanese scientists announced that a gyroscope loses weight up to 0.005% when spinning only in the clockwise rotation with the gyroscope’s axis in the vertical direction. Immediately afterwards, a number of other teams tried to replicate the effect, obtaining a null result. It was suggested that the reported effect by the Japanese was probably due to a vibration artifact, however, no final conclusion on the real cause has been obtained. We decided to build a dedicated high precision setup to test weight anomalies of spinning gyroscopes in various configurations. A number of error sources like precession and vibration and the nature of their influence on the measurements have been clearly identified, which led to the conclusive explanation of the conflicting reports. We found no anomaly within Δm/m<2.6×10−6 valid for both horizontal and vertical orientations.

Identification of error sources in a five-axis machine tool using FFT analysis

The use of five-axis machine tools is increasing because of their flexibility and high throughput. However, having more components in motion, these machines are more prone to failure than their three-axis counterparts. In this paper, using previously published tests of the double ball bar (DBB), the deviations of the rotary axis are measured and then treated to remove the eccentricity due to setup errors. Fast Fourier transform (FFT) analysis is applied to the centered readings, in order to obtain the machine frequency spectrum. From the latter, the contribution of error sources and their amplitude are obtained. This method can be used on a regular basis as a predictive maintenance (PM) tool. The novelty of this work falls in the realm of condition monitoring (CM) of rotary-axis components using a commercial instrument, with limited angular velocity and number of turns.

Error Source Identification of Machining Accuracy of Five-Axis Linkage CNC Machine Tools

The error sources of machining accuracy of CNC machine tools including geometric error, thermal error, system error and error of load control etc. The error source affect the relative position of the cutting tool and the workpiece by the dynamic motion, and then affect the machining accuracy of the workpiece. By trial cutting method, "S" test part is a new test part for detecting machining accuracy of five-axis linkage machine tools. Through experiment and simulation, identification of the error source of the machining accuracy and the regular of "S" test part surface errors, surface quality, results show that "S" test part can reflect the machining accuracy of CNC machine tool.

New Reflection Suppression Method in Antenna Measurement Systems Based on Diagnostic Techniques

A new method to reduce the unwanted reflection effects in antenna measurements is presented. The proposed method can be applied to measurements performed in semi-anechoic chambers, outdoor systems or even anechoic environments with a poor reflectivity level to remove reflected components and to retrieve the results one would obtain in an ideal anechoic chamber. The method is based on spatial filtering over the plane where the antenna under test (AUT) is placed. To calculate the field in this plane, a diagnostic technique is employed. However, in contrast to classic application (error source identification), the reconstructed field has to be obtained in a zone larger than the antenna dimensions. Thus, it is possible to identify virtual sources out of the antenna aperture, which appear due to the presence of reflections (image theory). Then, by cancelling the virtual and unwanted sources, the related reflected components can be suppressed. Finally, by employing this filtered reconstructed field, a new radiation pattern similar to the one obtained in a fully anechoic environment is calculated. To verify the effectiveness of the method, three examples are presented.

Error Source Identification and Stability Test of a Precision Capacitance Measurement System

An experimental study is reported for low-frequency noise behavior and identifying the error source of a capacitance measurement system. A test set-up and a special test strategy for this measurement were applied to differentiate between the kinds of external low-frequency interference. The set-up and strategy allowed accurate measurement of the low-frequency component of the intrinsic input noise of the capacitance measurement system. The capacitance measurement system reported was found in the study along with an extremely low value for the low-frequency (1/f) noise with a corner frequency of 2 mHz, and a very high thermal stability of 2 ppm/K, which confirm the design target of this capacitance measurement system.

Variance component analysis based fault diagnosis of multi-layer overlay lithography processes

The overlay lithography process is one of the most important steps in semiconductor manufacturing. This work attempts to solve a challenging problem in this technique, namely error source identification and diagnosis for multistage overlay processes. In this paper, a multistage state space model for the misalignment errors of the lithography process is developed and a general mixed linear input–output model is then formulated to incorporate both fixed and random effects. Furthermore, the minimum norm quadric unbiased estimation strategy is used to estimate the mean and variance components of potential fault sources, and their asymptotic distributions are used to test the hypothesis concerning the statistical significance of each potential fault. Based on the above procedures, the root cause of misalignment errors in a multi-layer overlay process can be detected and diagnosed with physical inference. A number of simulated examples are designed and tested to verify the validity of the presented approach in fault detection and diagnosis of multi-stepper overlay processes.

Substrate Alignment for Single and Multilayer Ink Jet Materials Deposition in Digital Fabrication Systems

As materials deposition technologies for digital fabrication evolve, the inevitable push toward volume manufacturing will necessitate the application of alignment and inspection technologies to monitor and control the production process. Many of these processes will depend on ink jet deposition of materials onto substrates with previously or subsequently applied structures or images. The successful function of the end product will depend on the precise alignment of materials from layer to layer. This paper describes the development of a Substrate Alignment Tool (SAT) using machine vision methodologies for rapid in-line measurement and adjustment of the alignment between layers. In addition, the SAT can double as an Image Analysis Tool (IAT) for in situ monitoring of process quality. This paper will focus on the design and use of the SAT for ink jet applications. Of particular concern to this study will be the identification of error sources and their contribution to process accuracy and repeatability.

Identification of error sources in convective planetary boundary layer cloud forecasts using SIRTA observations

[1] In this study, errors in cloud base height predicted by two numerical weather prediction models is evaluated using observations from the French instrumented site SIRTA. Results show that a significant portion of the error is due to errors in predicted surface relative humidity. These errors are in turn thought to be caused by the convection schemes.

Identification of nonlinear recording error in phase shifting interferometry

The phase shifting method for quantitative fringe pattern analysis provides high accuracy if stringent requirements on the component interferogram recording are met. In the paper the issue of detection and identification of error sources in the two-beam interferogram phase shifting experiment is discussed. The phase shift angle histogram and lattice-site representation are applied for that purpose. Special attention is paid to possible nonlinear recording of component interferograms in the presence of linear and nonlinear phase step errors. Four and five step phase shifting algorithms are considered. The superiority of the lattice-site representation is shown. In the case of phase steps equal to π/2, however, the lattice-site representation of shift angles for five frame algorithm does not allow to detect recording nonlinearity. The four frame counterpart shows to be very helpful in this respect. Its properties related to the fringe pattern profile under study, including a defocused Ronchi grating, are discussed.

Improved Modeling Capabilites with Reduced-Order Integration

Many rectangular isoparametric finite elements contain a modeling error known as parasitic shear. Parasitic shear can be removed by applying the correct reduced-order Gauss quardrature integration rule. When the 1×1 rule is blindly applied another error, spurious zero energy modes, can be introduced. An analysis procedure is presented that identifies the correct Gauss integration rule for eliminating parasitic shear without introducing spurious zero energy modes. Displacement polynomials expressed in transparent notation assists in the identification of error sources. The procedure is developed with the four-node membrane element and then applied to analyze and correct four- and nine-node Mindlin plate bending elements. Eigenvalue analyses and sample problems are presented to demonstrate the improvements produced by the procedure.

Improving machining accuracy in precision line boring

There is an ever-growing demand for high precision machining to obtain increased accuracy and surface finish, as they are key factors in product quality and performance. Machining operations, in general, are associated with errors of varying magnitude originating from different sources. As a result, the sizes of the machined features usually deviate from their desired, nominal values. Identification of error sources, techniques of measurements (on/off line), and efficient strategies for their compensation are the steps required to minimize, and, in some cases eliminate process errors. This paper focuses on modeling and compensation of geometric errors in machining operations specific to the line boring process. It is part of an undergoing research project focused on design and development of an agile precision line boring station for machining of long bores. After a brief overview of sources of geometric errors and their components, a methodology for their calculation is introduced. In this regard, error equations reflecting the effects of machine tool geometric errors at the tool tip are derived. It is shown that these equations can be further simplified without significantly affecting computational accuracy of the results. This makes the approach more attractive for real-time applications. A set of experimental data obtained from a prototype of the machine is used to study the effectiveness of the proposed approach and the results are reported. The paper concludes with discussions and presentation of different methods and available tools for real time compensation of these errors.

Cutter path preview for contour machining based on efficient identification of motion error sources

This paper presents an efficient approach to the identification of the motion error sources in CNC contour machining. The motion error sources include the mismatch of feed drives, the friction disturbances and the cutter path curvature. Their effects on the contour error in linear and circular motions are analyzed, respectively. On the basis of the analysis, the procedure for the identification of these error-source effects is developed. With the identification results, the cutter path trajectory can be previewed before the real run.

Estimating manipulation errors in finite element analysis part II

With the increasing use of microcomputers for engineering research and production analyses, control of round-off error is of increasing concern. An essential ingredient in control is the ability to estimate the errors. Part I of this paper described the errors in processing numbers with digital computers [4]. This part, Part II, presents and illustrates the effectiveness of error estimation for three goals: pre-estimating, measuring actual errors, and identifying the error source. Pre-estimation is intended to eliminate analyses whose results would be inaccurate. Measurement of actual errors qualifies the accuracy of calculations. Error source identification leads to selection of error reduction methods. The authors conclude that bound estimates of lost precision are excessively high, do not correlate with actual round-off errors, and are not reliable in identifying the key sources of error. Experiments show that the closure measure provides excellent estimates of maximum error in stress predictions. This fact suggests a conservative approach to protect against use of inaccurate analysis results.