Confluent-analysis algorithm for processing measurement data in calibrating means of measurement

1990 ◽  
Vol 33 (6) ◽  
pp. 537-542
Author(s):  
A. B. Isaev
2011 ◽  
Vol 52-54 ◽  
pp. 1433-1437
Author(s):  
Hai Juan Chang ◽  
Jian Jun Zhang ◽  
Shu Zhu

Environment measurement technology of aircraft platform is the foundation of environment prediction, while inductive technology of environment measurement data is the support of environment prediction. To analysis how the vibration of different channel and in different position affect the equipment on board, it’s awfully needed to classify the vibration data of aircraft platform according to how was the aircraft flying and where was the sensor placed. However, the traditional method for categorizing gives the sort first, and then make certain if one sample belongs to this category, which is easy to withstand the influence of man-made factors. As it hard to fix the categories first for the vibration on aircraft platform, we put forward using clustering analysis into the categorizing of vibration measured data to eliminate the influence of man-made factors. This method is the improvement of the current inductive method for vibration environment measured data.


Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2366
Author(s):  
Zhifeng Wu ◽  
Bin Huang ◽  
Kong Fah Tee ◽  
Weidong Zhang

This paper proposes a new damage identification approach for beam structures with stochastic parameters based on uncertain static measurement data. This new approach considers not only the static measurement errors, but also the modelling error of the initial beam structures as random quantities, and can also address static damage identification problems with relatively large uncertainties. First, the stochastic damage identification equations with respect to the damage indexes were established. On this basis, a new homotopy analysis algorithm was used to solve the stochastic damage identification equations. During the process of solution, a static condensation technique and a L1 regularization method were employed to address the limited measurement data and ill-posed problems, respectively. Furthermore, the definition of damage probability index is presented to evaluate the possibility of existing damages. The results of two numerical examples show that the accuracy and efficiency of the proposed damage identification approach are good. In comparison to the first-order perturbation method, the proposed method can ensure better accuracy in damage identification with relatively large measurement errors and modelling error. Finally, according to the static tests of a simply supported concrete beam, the proposed method successfully identified the damage of the beam.


2018 ◽  
Vol 28 (2) ◽  
pp. 186-195
Author(s):  
Maria Mrówczyńska ◽  
Jacek Sztubecki

Abstract ART (Adaptive Resonance Theory) networks were invented in the 1990s as a new approach to the problem of image classification and recognition. ART networks belong to the group of resonance networks, which are trained without supervision. The paper presents the basic principles for creating and training ART networks, including the possibility of using this type of network for solving problems of predicting and processing measurement data, especially data obtained from geodesic monitoring. In the first stage of the process of creating a prediction model, a preliminary analysis of measurement data was carried out. It was aimed at detecting outliers because of their strong impact on the quality of the final model. Next, an ART network was used to predict the values of the vertical displacements of points of measurement and control networks stabilized on the inner and outer walls of an engineering object.


Author(s):  
A.P. Tarasov ◽  
D.A. Rogatkin

The paper justifies the possibility of creating software with a universal top-level structure using LabVIEW for noninvasive spectrophotometric diagnostic devices. To attain these ends it is proposed to use a modular structure of the program where specialized modules directly associated with measurements and processing measurement data work independently of common modules designed for working with service textual information and databases, and having no strong differences for different noninvasive medical spectrophotometry methods


Mechanik ◽  
2017 ◽  
Vol 90 (12) ◽  
pp. 1164-1168
Author(s):  
Piotr Lampa ◽  
Mariusz Mrzygłód ◽  
Jacek Reiner

An important problem of modern aero-engines’ construction is effective cooling of combustor liner attained by effusion holes. The laser-drilled channels are a critical metrological challenge resulting from their small diameter (below 1 mm), irregular shape and angular orientation to the surface. Hence, in this case, the tactile CMM measurement methods are timeconsuming, error-susceptible and hazardous to the measuring stylus. The paper compares two methods of triangulation scanning of the surface of the engine combustion chamber with angular effusion holes (according to normal to surface and coaxially with hole). Additionally, four algorithms for processing measurement data were developed and evaluated, aiming at determination of the position and holes diameter. The paper also discusses the problem of measurement and calculation disturbance.


2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
J. J. Águila ◽  
E. Arias ◽  
M. M. Artigao ◽  
J. J. Miralles

In different fields of science and engineering, a model of a given underlying dynamical system can be obtained by means of measurement data records called time series. This model becomes very important to understand the original system behaviour and to predict the future values of that system. From the model, parameters such as the prediction horizon can be computed to obtain the point where the prediction becomes useless. In this work, a new parallel kd-tree based approach for computing the prediction horizon is presented. The parallel approach uses the maximal Lyapunov exponent, which is computed by Wolf’s method, as an estimator of the prediction horizon.


2016 ◽  
Vol 21 (3) ◽  
pp. 83-87
Author(s):  
N. Kokodii ◽  
◽  
V. Timaniuk ◽  
E. Levitin ◽  
M. Kaydash ◽  
...  

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