Application of a Pattern-Matching Expert System to Sucker-Rod, Dynamometer-Card Pattern Recognition

1991 ◽  
Author(s):  
J.F. Keating ◽  
R.E. Laine ◽  
J.W. Jennings
Keyword(s):  
Pattern Recognition ◽  
Expert System ◽  
Pattern Matching ◽  
Sucker Rod ◽  
Dynamometer Card

Modeling And Implementation Of A System For Sucker Rod Downhole Dynamometer Card Pattern Recognition

2003 ◽  
Author(s):  
L. Schnitman ◽  
G.S. Albuquerque ◽  
J.F. Corrêa ◽  
H. Lepikson ◽  
A.C.P. Bitencourt
Keyword(s):  
Pattern Recognition ◽  
Sucker Rod ◽  
Dynamometer Card

Identification for Sucker-Rod Pumping System’s Damping Coefficients Based on Chain Code Method of Pattern Recognition

2007 ◽  
Vol 129 (4) ◽  
pp. 434-440 ◽  
Author(s):  
Hongzhao Liu ◽  
Baixi Liu ◽  
Daning Yuan ◽  
Jianhua Rao
Keyword(s):  
Pattern Recognition ◽  
Euclidean Distance ◽  
Simulation Program ◽  
Similar Degree ◽  
Chain Code ◽  
Damping Coefficients ◽  
Pumping System ◽  
Sucker Rod ◽  
Dynamometer Card ◽  
Shape Characteristics

In this paper, a method for identifying the damping coefficients of a directional well sucker-rod pumping system is put forward by means of the chain code method of pattern recognition. The 24-directional chain code is provided to encode the dynamometer card curve. The parametric equation of the dynamometer card curve is transformed into Fourier series whose coefficients can be computed according to the curve’s chain codes. By means of these coefficients, shape characteristics of the curve are extracted. The Euclidean distance is introduced as the measurement of similar degree between the shape characteristics of measured dynamometer card and that of simulated dynamometer card. Changing the value of viscous damping coefficient and Coulomb friction coefficient in the simulation program, different simulated dynamometer cards are obtained. Substituting their shape characteristics to the Euclidean distance, respectively, a series of distances are acquired. When the distance is less than the given error, the corresponding values of the damping coefficients in the simulation program are regarded as real damping coefficients of the sucker-rod pumping system of directional well. In the end, an example is provided to show the correctness and effectiveness of the presented method.

Hybrid pattern matching algorithms for automated stratigraphic well correlation and log pattern recognition in Malaysian Basin

2021 ◽  
Author(s):  
A.S. Abdrahman ◽  
M.S. Jaya ◽  
A.R. Ali ◽  
A.H. Hasan ◽  
A.R. Ghazali ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Pattern Matching ◽  
Well Correlation

scholarly journals Recognition of Urdu Handwritten Characters Using Convolutional Neural Network

2019 ◽  
Vol 9 (13) ◽  
pp. 2758 ◽  
Author(s):  
Mujtaba Husnain ◽  
Malik Muhammad Saad Missen ◽  
Shahzad Mumtaz ◽  
Muhammad Zeeshan Jhanidr ◽  
Mickaël Coustaty ◽  
...  
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Pattern Matching ◽  
Character Recognition ◽  
Learning Models ◽  
Series Of Experiments

In the area of pattern recognition and pattern matching, the methods based on deep learning models have recently attracted several researchers by achieving magnificent performance. In this paper, we propose the use of the convolutional neural network to recognize the multifont offline Urdu handwritten characters in an unconstrained environment. We also propose a novel dataset of Urdu handwritten characters since there is no publicly-available dataset of this kind. A series of experiments are performed on our proposed dataset. The accuracy achieved for character recognition is among the best while comparing with the ones reported in the literature for the same task.

scholarly journals Classification in the Gabor time-frequency domain of non-stationary signals embedded in heavy noise with unknown statistical distribution

2010 ◽  
Vol 20 (1) ◽  
pp. 135-147 ◽  
Author(s):  
Ewa Świercz
Keyword(s):  
Pattern Recognition ◽  
Frequency Domain ◽  
Pattern Matching ◽  
Classification Algorithm ◽  
Statistical Distribution ◽  
Classification Rule ◽  
Matching Problem ◽  
Time Frequency ◽  
Stationary Signals ◽  
Non Stationary Signal

Classification in the Gabor time-frequency domain of non-stationary signals embedded in heavy noise with unknown statistical distributionA new supervised classification algorithm of a heavily distorted pattern (shape) obtained from noisy observations of nonstationary signals is proposed in the paper. Based on the Gabor transform of 1-D non-stationary signals, 2-D shapes of signals are formulated and the classification formula is developed using the pattern matching idea, which is the simplest case of a pattern recognition task. In the pattern matching problem, where a set of known patterns creates predefined classes, classification relies on assigning the examined pattern to one of the classes. Classical formulation of a Bayes decision rule requiresa prioriknowledge about statistical features characterising each class, which are rarely known in practice. In the proposed algorithm, the necessity of the statistical approach is avoided, especially since the probability distribution of noise is unknown. In the algorithm, the concept of discriminant functions, represented by Frobenius inner products, is used. The classification rule relies on the choice of the class corresponding to themaxdiscriminant function. Computer simulation results are given to demonstrate the effectiveness of the new classification algorithm. It is shown that the proposed approach is able to correctly classify signals which are embedded in noise with a very low SNR ratio. One of the goals here is to develop a pattern recognition algorithm as the best possible way to automatically make decisions. All simulations have been performed in Matlab. The proposed algorithm can be applied to non-stationary frequency modulated signal classification and non-stationary signal recognition.

A Novel Method for Diagnosis of Sucker-Rod Pumping Systems Based on the Polished-Rod Load Vibration in Vertical Wells

SPE Journal ◽  
2020 ◽  
Vol 25 (05) ◽  
pp. 2470-2481 ◽  
Author(s):  
JiaoJian Yin ◽  
Dong Sun ◽  
Yousheng Yang
Keyword(s):  
Analytic Solution ◽  
Vibration Signal ◽  
Operating Conditions ◽  
Vertical Wells ◽  
Sucker Rod ◽  
Impulse Load ◽  
Novel Method ◽  
Dynamometer Card ◽  
Polished Rod ◽  
The Relationship

Summary The pump dynamometer card is a direct reflection of the operating conditions of the downhole pump, which is important for the diagnosis of sucker-rod pumping systems. In this paper, we propose a novel diagnostic method based on the estimation of the parameters from the polished-rod load vibration signal of sucker-rod pumping systems in a vertical well. In this study, we deduce a new analytic solution of the 1D wave equation of the sucker-rod string, which can be used for the predictive and diagnostic analyses. The relationship between the polished-rod load vibration and the pump equivalent impulse load based on the analytic solution is studied, and the diagnostic parameter estimating method is proposed. Therefore, the pump dynamometer card calculated method based on the surface dynamometer card is realized. This study shows that the method is efficient.

Expert system for coffee rust detection based on supervised learning and graph pattern matching

2017 ◽  
Vol 12 (1) ◽  
pp. 19 ◽  
Author(s):  
Emmanuel Lasso ◽  
Thiago Toshiyuki Thamada ◽  
Carlos Alberto Alves Meira ◽  
Juan Carlos Corrales
Keyword(s):  
Expert System ◽  
Supervised Learning ◽  
Pattern Matching ◽  
Graph Pattern Matching ◽  
Coffee Rust ◽  
Graph Pattern

A GENERAL FRAMEWORK FOR KNOWLEDGE-BASED PATTERN RECOGNITION

1987 ◽  
Vol 01 (02) ◽  
pp. 189-205 ◽  
Author(s):  
F. BERGADANO ◽  
L. SAITTA
Keyword(s):  
Pattern Recognition ◽  
Expert System ◽  
Knowledge Representation ◽  
General Framework ◽  
Common Knowledge ◽  
Learning Module ◽  
Knowledge Based ◽  
Recognition Phase ◽  
Representation Scheme

This paper surveys a long term project, aimed at providing a general methodology for building up and maintaining an expert system oriented to Pattern Recognition problems. The methodology makes use of an integrated set of modules, performing different functions but sharing a common knowledge representation scheme. In particular, a learning module allows to acquire the knowledge automatically from a set of examples and another module performs sophisticated reasoning, on the basis of the available knowledge, during the recognition phase.

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