The effects of level quantization in slidewire automatic devices on the test error

1973 ◽  
Vol 16 (8) ◽  
pp. 1190-1192
Author(s):  
A. I. Lisenkov
Keyword(s):  
Test Error ◽  
Level Quantization

Development of a Visual Monitoring System for Deformation Measuring of Welded Members and its Application

2008 ◽  
Vol 580-582 ◽  
pp. 557-560 ◽  
Author(s):  
J.G. Han ◽  
Kyong Ho Chang ◽  
Gab Chul Jang ◽  
K.K. Hong ◽  
Sam Deok Cho ◽  
...  
Keyword(s):  
Monitoring System ◽  
Three Dimensional ◽  
Measuring Method ◽  
Welding Residual Stress ◽  
Measuring System ◽  
Visual Monitoring ◽  
Test Error ◽  
Steel Members ◽  
Loading Tests ◽  
Visual Monitoring System

Recently, in the loading tests for steel members, the deformation value is measured by calculating a distance of both cross-heads. This measuring method encounters a test error due to various environmental factors, such as initial slip, etc.. Especially, in the case of welded members, the non-uniform deformation behavior in welded joints is observed because of the effect of welding residual stress and weld metal. This is mainly responsible for a test error and a loss of the reliability for used test instruments. Therefore, to improve the accuracy and the applicability of measuring system, it is necessary to employ a visual monitoring system which can accurately measure the local and overall deformation of welded members. In this paper, to accurately measure a deformation of welded members, a visual monitoring system (VMS) was developed by using three-dimensional digital photogrammetry. The VMS was applied to the loading tests of a welded member. The accuracy and the applicability of VMS was verified by comparing to the deformation value measured by a test instrument (MTS-810). The characteristics of the behavior near a welded joint were investigated by using VMS.

scholarly journals Computing Expectiles Using k-Nearest Neighbours Approach

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 645
Author(s):  
Muhammad Farooq ◽  
Sehrish Sarfraz ◽  
Christophe Chesneau ◽  
Mahmood Ul Hassan ◽  
Muhammad Ali Raza ◽  
...  
Keyword(s):  
Computational Cost ◽  
Real Life ◽  
Distance Measures ◽  
Computational Time ◽  
High Dimensional ◽  
Test Error ◽  
Nearest Neighbours ◽  
Comparable Performance ◽  
Asymmetric Least Squares ◽  
Low Computational Cost

Expectiles have gained considerable attention in recent years due to wide applications in many areas. In this study, the k-nearest neighbours approach, together with the asymmetric least squares loss function, called ex-kNN, is proposed for computing expectiles. Firstly, the effect of various distance measures on ex-kNN in terms of test error and computational time is evaluated. It is found that Canberra, Lorentzian, and Soergel distance measures lead to minimum test error, whereas Euclidean, Canberra, and Average of (L1,L∞) lead to a low computational cost. Secondly, the performance of ex-kNN is compared with existing packages er-boost and ex-svm for computing expectiles that are based on nine real life examples. Depending on the nature of data, the ex-kNN showed two to 10 times better performance than er-boost and comparable performance with ex-svm regarding test error. Computationally, the ex-kNN is found two to five times faster than ex-svm and much faster than er-boost, particularly, in the case of high dimensional data.

scholarly journals Assessment of the Content of Dry Matter and Dry Organic Matter in Compost with Neural Modelling Methods

Agriculture ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 307
Author(s):  
Dawid Wojcieszak ◽  
Maciej Zaborowicz ◽  
Jacek Przybył ◽  
Piotr Boniecki ◽  
Aleksander Jędruś
Keyword(s):  
Image Analysis ◽  
Organic Matter ◽  
Dry Matter ◽  
Neural Model ◽  
Original Method ◽  
Neural Models ◽  
Test Error ◽  
Effective Assessment ◽  
Modelling Methods

Neural image analysis is commonly used to solve scientific problems of biosystems and mechanical engineering. The method has been applied, for example, to assess the quality of foodstuffs such as fruit and vegetables, cereal grains, and meat. The method can also be used to analyse composting processes. The scientific problem lets us formulate the research hypothesis: it is possible to identify representative traits of the image of composted material that are necessary to create a neural model supporting the process of assessment of the content of dry matter and dry organic matter in composted material. The effect of the research is the identification of selected features of the composted material and the methods of neural image analysis resulted in a new original method enabling effective assessment of the content of dry matter and dry organic matter. The content of dry matter and dry organic matter can be analysed by means of parameters specifying the colour of compost. The best developed neural models for the assessment of the content of dry matter and dry organic matter in compost are: in visible light RBF 19:19-2-1:1 (test error 0.0922) and MLP 14:14-14-11-1:1 (test error 0.1722), in mixed light RBF 30:30-8-1:1 (test error 0.0764) and MLP 7:7-9-7-1:1 (test error 0.1795). The neural models generated for the compost images taken in mixed light had better qualitative characteristics.

Measurement Method Research on Inertial Parameters of Motor Assembly

2013 ◽  
Vol 437 ◽  
pp. 663-668
Author(s):  
Ling Sun ◽  
Peng Yu ◽  
Tong Zhang
Keyword(s):  
Measurement Method ◽  
Center Of Mass ◽  
Moment Of Inertia ◽  
Balance Method ◽  
Test Error ◽  
Inertial Parameters ◽  
Drive Motor ◽  
Weight Method ◽  
Mass Position

Inertial parameters of the motor assembly include its mass, CM (center of mass) position, moment of inertia and product of inertia. Taking one vehicle drive motor as the research object, its mass and CM position are measured by using weight method and moment balance method respectively. Its moment of inertia and product of inertia are measured by using three-wire pendulum. On the basis of analyzing the test error, this paper proposed specific measures to reduce the test error.

scholarly journals Numerical evaluation of sine-Gordon chain energy control via subdomains state feedback under quantizationand time sampling

2019 ◽  
pp. 18-28
Author(s):  
Boris Andrievsky ◽  
Yury Orlov
Keyword(s):  
State Feedback ◽  
Communication Channel ◽  
Closed Loop ◽  
Signal Transmission ◽  
Control Signal ◽  
Time Sampling ◽  
Signal Quantization ◽  
First Order ◽  
Time Control ◽  
Level Quantization

The paper is devoted to the numerical performance evaluation of the speed-gradient algorithms, recently developed in (Orlov et al., 2018; Orlov et al., 2019) for controlling the energy of the sine-Gordon spatially distributed systems with several in-domain actuators. The influence of the level quantization of the state feedback control signal (possibly coupled to the time sampling) on the steady-state energy error and the closed loop system stability is investigated in the simulation study. The following types of quantization are taken into account: sampling-in-time control signal quantization, the level quantization for control, continuous in time; control signal quantization on level jointly with time sampling; control signal transmission over the binary communication channel with time-invariant first order coder; control signal transmission over the binary communication channel with first order coder and time-based zooming; control signal transmission over the binary communication channel with adaptive first order coder. A resulting impact on the closed-loop performance in question is concluded for each type of the quantization involved.

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