Optimisation of Autonomous Threaded Fastenings Based on Non-Linear Least Square Method With GUIs

2004 ◽  
Author(s):  
Mongkorn Klingajay ◽  
Wuttipong Wanathap
Keyword(s):  
User Interfaces ◽  
Least Square Method ◽  
Estimation Procedure ◽  
Least Square ◽  
Unknown Parameters ◽  
Screw Insertion ◽  
Assembly Method ◽  
Non Linear ◽  
On Line ◽  
Linear Least Square

Threaded fastenings are a common assembly method, accounting for over a quarter of all assembly operations. They are especially popular because they permit easy disassembly for maintenance, repair, relocation and recycling. Screw insertions are typically carried out manually as it is a difficult operation to automate. There is very little published research on automating threaded fastenings, and most research on automated assembly focuses on the peg-in-hole assembly problem. Non-linear least square method was designed and employed to identify torque signature signals during online threaded fastening. Creating interactive simulations and graphical user interfaces became necessary as a visualization aid. This provides help and support for the user, allowing them to concentrate on the concept they are illustrating and to put emphasis on the monitoring process rather than the mechanics of running the program. This paper presents a Graphical User Interface (GUI) tool to accommodate and support threaded fastening operations used in assembly line industries. This tool was produced as interactive software with a convenient GUI in combination with the computing and graphics capability of MATLAB. It has applied to automated monitoring of threaded fastenings based-on an analytical model and on-line parameter estimation. The monitoring problem deals with predicting the integrity of the screw insertion process based on the torque vs. insertion angle curves generated during the insertions. A Non-linear Least Square Method (NLSM) is applied for estimation of four unknown parameters during a self-tapping screw insertion to be presented. It is shown that these parameters, required by the model, can be reliably estimated on-line. Experimental results are presented to validate the estimation procedure.

scholarly journals Calculation of ICG kinetics by two simultaneous differential equations and non-linear least square method.

Kanzo ◽  
1988 ◽  
Vol 29 (10) ◽  
pp. 1368-1373
Author(s):  
Yutaka SAGAWA ◽  
Toshiko YOSHIKATA ◽  
Nagaki SHIMADA ◽  
Motonobu SUGIMOTO
Keyword(s):  
Differential Equations ◽  
Least Square Method ◽  
Least Square ◽  
Non Linear ◽  
Linear Least Square

scholarly journals COMPARISON OF THE LINEAR AND THE NON-LINEAR BLOCK ADJUSTMENT ON SATELLITE IMAGES RESEARCH

2018 ◽  
Vol XLII-3 ◽  
pp. 775-780
Author(s):  
C. Li ◽  
C. Chen ◽  
Z. Guo ◽  
Q. Liu
Keyword(s):  
Linear Model ◽  
Satellite Images ◽  
Satellite Image ◽  
Least Square Method ◽  
Least Square ◽  
Image Block ◽  
Function Model ◽  
Check Points ◽  
Non Linear ◽  
Linear Least Square

The Rational Function Model （RFM） is a non-linear model. Usually, the RFM-based satellite image block adjustment uses the Taylor series to expand error equations, and then solves the linear model. Theoretically, linearization of a non-linear model affects the accuracy and reliability of the adjustment result. This paper presents linear and non-linear methods for solving the RFM-based block adjustment,and takes ZiYuan3 (ZY-3) satellite imagery block adjustment as an example, using same check points to assess the accuracy of the two methods. In this paper, a non-linear least square method is used for solving the RFM-based block adjustment, which expands a solution to the block adjustment.

A Study on the New Static Photoelastic Experimental Hybrid Method

2005 ◽  
Vol 297-300 ◽  
pp. 2187-2194
Author(s):  
Jai Sug Hawong ◽  
Konstantin Teche
Keyword(s):  
Experimental Data ◽  
Numerical Method ◽  
Experimental Method ◽  
Hybrid Method ◽  
Least Square Method ◽  
Least Square ◽  
Photoelastic Experimental Hybrid Method ◽  
Non Linear ◽  
Newton Raphson ◽  
Linear Least Square

In photoelastic experimental method, until now, we have used the Newton-Raphson numerical method in analysis of photoelastic experimental data such as the non-linear least square method for the photoelastic expreriment. We used the Hook-Jeeves’ numerical method in stead of Newton-Raphson numerical method for the non-linear least square method for photoelastic experimental method. The new photoelastic experimental hybrid method, that is, the photoelastic experimental hybrid method with Hook-Jeeves’ numerical method has been developed in this research. Applying the new photoelastic experimental hybrid method to stress concentration problems and plane fracture problems, it’s validity was assured. The new photoelastic experimental hybrid method is more precise and stabler than the photoelastic experimental hybrid method with Newton- Raphson numerical method (the old photoelastic experimental hybrid method)

Direct Assessment of Effective Renal Plasma Flow from Renoscintigraphy with a Gamma Camera and an On-Line Computer

1981 ◽  
Vol 20 (06) ◽  
pp. 274-278
Author(s):  
J. Liniecki ◽  
J. Bialobrzeski ◽  
Ewa Mlodkowska ◽  
M. J. Surma
Keyword(s):  
Count Rate ◽  
Renal Plasma Flow ◽  
Early Period ◽  
Least Square Method ◽  
Least Square ◽  
Uptake Coefficient ◽  
Positive Linear Correlation ◽  
On Line ◽  
Best Fit ◽  
Plasma Activity

A concept of a kidney uptake coefficient (UC) of 131I-o-hippurate was developed by analogy from the corresponding kidney clearance of blood plasma in the early period after injection of the hippurate. The UC for each kidney was defined as the count-rate over its ROI at a time shorter than the peak in the renoscintigraphic curve divided by the integral of the count-rate curve over the "blood"-ROI. A procedure for normalization of both curves against each other was also developed. The total kidney clearance of the hippurate was determined from the function of plasma activity concentration vs. time after a single injection; the determinations were made at 5, 10, 15, 20, 30, 45, 60, 75 and 90 min after intravenous administration of 131I-o-hippurate and the best-fit curve was obtained by means of the least-square method. When the UC was related to the absolute value of the clearance a positive linear correlation was found (r = 0.922, ρ > 0.99). Using this regression equation the clearance could be estimated in reverse from the uptake coefficient calculated solely on the basis of the renoscintigraphic curves without blood sampling. The errors of the estimate are compatible with the requirement of a fast appraisal of renal function for purposes of clinical diagknosis.

Model-based control of the substrate concentration in an aeration basin using the wastewater level

1998 ◽  
Vol 37 (12) ◽  
pp. 335-342 ◽  
Author(s):  
Jacek Czeczot
Keyword(s):  
Substrate Concentration ◽  
Consumption Rate ◽  
Least Square Method ◽  
Estimation Procedure ◽  
Adaptive Controller ◽  
Open Loop ◽  
Least Square ◽  
Substrate Consumption ◽  
Model Based ◽  
Effluent Flow Rate

This paper deals with the minimal-cost control of the modified activated sludge process with varying level of wastewater in the aerator tank. The model-based adaptive controller of the effluent substrate concentration, basing on the substrate consumption rate and manipulating the effluent flow rate outcoming from the aerator tank, is proposed and its performance is compared with conventional PI controller and open loop behavior. Since the substrate consumption rate is not measurable on-line, the estimation procedure on the basis of the least-square method is suggested. Finally, it is proved that cooperation of the DO concentration controller with the adaptive controller of the effluent substrate concentration allows the process to be operated at minimum costs (low consumption of aeration energy).

scholarly journals Integer variables estimation problems: the Bayesian approach

1997 ◽  
Vol 40 (5) ◽  
Author(s):  
F. Sansò ◽  
G. Venuti
Keyword(s):  
Bayesian Approach ◽  
Estimation Procedure ◽  
Least Square ◽  
Unknown Parameters ◽  
Ordinary Least Square ◽  
Integer Variables ◽  
Cycle Slips ◽  
Estimation Problems ◽  
Continuous Range ◽  
Gps Observations

In geodesy as well as in geophysics there are a number of examples where the unknown parameters are partly constrained to be integer numbers, while other parameters have a continuous range of possible values. In all such situations the ordinary least square principle, with integer variates fixed to the most probable integer value, can lead to paradoxical results, due to the strong non-linearity of the manifold of admissible values. On the contrary an overall estimation procedure assigning the posterior distribution to all variables, discrete and continuous, conditional to the observed quantities, like the so-called Bayesian approach, has the advantage of weighting correctly the possible errors in choosing different sets of integer values, thus providing a more realistic and stable estimate even of the continuous parameters. In this paper, after a short recall of the basics of Bayesian theory in section 2, we present the natural Bayesian solution to the problem of assessing the estimable signal from noisy observations in section 3 and the Bayesian solution to cycle slips detection and repair for a stream of GPS measurements in section 4. An elementary synthetic example is discussed in section 3 to illustrate the theory presented and more elaborate, though synthetic, examples are discussed in section 4 where realistic streams of GPS observations, with cycle slips, are simulated and then back processed.

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