Correction of ADC Errors by Additive Iterative Method with Dithering

The authors have recently developed a number of instruments for measuring harmonic composition of power grid signals. These instruments have a simple, predominantly digital architecture and they are based on an assumption that the frequency of the measured signals equals its nominal value (50 Hz, 60 Hz or 400 Hz). This approach has enabled the measurement of a high number of harmonics within a single period. However, the internal oscillator in the instrument generates the nominal frequency and cannot adapt to frequency changes in the input signal. This paper presents a method for the improvement of the operation of the developed instruments in cases when the fundamental frequency drifts from its nominal value as is the case with real power grid signals. Based on this method, modified versions of the harmonic measurement instruments have been developed. A comparison of the measurement error with and without the application of the proposed method is presented in the paper.

Section: Introductionmentioning

confidence: 99%

A Method for Harmonic Measurement of Real Power Grid Signals with Frequency Drift using Instruments with Internally Generated Reference Frequency

Antić¹,

Mitrovic²,

Vujičić³

2012

“…Thus, the mathematical model of the dynamic error should be based on some average values for which it is aptly to use the root-mean-square value [8][9][10], provided that process x(t) possesses the quality of ergodicity, i.e.…”

Section: Mathematical Model Of the Dynamic Errormentioning

confidence: 99%

A Model of the Dynamic Error as a Measurement Result of Instruments Defining the Parameters of Moving Objects

Dichev

Koev

Bakalová

et al. 2014

The present paper considers a new model for the formation of the dynamic error inertial component. It is very effective in the analysis and synthesis of measuring instruments positioned on moving objects and measuring their movement parameters. The block diagram developed within this paper is used as a basis for defining the mathematical model. The block diagram is based on the set-theoretic description of the measuring system, its input and output quantities and the process of dynamic error formation. The model reflects the specific nature of the formation of the dynamic error inertial component. In addition, the model submits to the logical interrelation and sequence of the physical processes that form it. The effectiveness, usefulness and advantages of the model proposed are rooted in the wide range of possibilities it provides in relation to the analysis and synthesis of those measuring instruments, the formulation of algorithms and optimization criteria, as well as the development of new intelligent measuring systems with improved accuracy characteristics in dynamic mode.Keywords: dynamic error, measurement in dynamic mode, inertial effects, parameters of moving objects, set-theoretic model.

“…According to (6) and (7), the following is obtained. Therefore, we can detect the outlier of the original data sequence by detecting the outlier of the adjacent variance ratio of the original data sequence.…”

Section: Characteristics Of the Outliers From Tooth Profilesmentioning

confidence: 99%

“…The measurement of tooth profiles is a difficult measurement item, and now tooth profiles are usually measured by gear measuring center [3][4][5]. Gear measuring center is a kind of efficient precision measuring instrument, but outliers easily cause sudden measurement environment changes in the measurement of tooth profiles, such as the effect of mechanical vibration on the measuring head and the impact of the sharp current on the data acquisition card [6][7][8]. The outliers lead to the abnormal data and decrease the measurement precision of tooth profiles, so the outliers must be removed as soon as they are detected [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Outlier Detection and Correction for the Deviations of Tooth Profiles of Gears

Han¹,

Fu²,

Wang³

et al. 2013

To decrease the influence of outlier on the measurement of tooth profiles, this paper proposes a method of outlier detection and correction based on the grey system theory. After studying the characteristics of outliers from the deviations of tooth profiles, this paper proposes a preprocessing method for the modeling data which include abnormal value, and establishes an outlier detection and correction model for the deviations of tooth profiles. Simulation results show that the precision of ONDGM(1,1)(one order and one variable non-homogenous discrete grey model whose outlier is processed by the preprocessing method proposed in this paper) is higher than that of NDGM(1,1)(one order and one variable non-homogenous discrete grey model), and the ONDGM(1,1) is more suitable than the NDGM(1,1) for dealing with the outliers from the deviations of tooth profiles. The experiment results show that the outlier detection and correction model detects and corrects the outliers from the deviations of tooth profiles, and the correction value of the outlier is basically in accordance with the actual deviation. Therefore, the method of outlier detection and correction decreases the influence of outlier and improves the precision in the measurement of tooth profiles.