scholarly journals Influence-Coefficient Method for Identifying Maximum-Load Configurations and Variable-Load Issues in Manipulators

Machines ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 27
Author(s):  
Raffaele Di Gregorio ◽  
Erkan Yilmaz
Keyword(s):  
Design Method ◽  
Dynamic Modelling ◽  
Maximum Load ◽  
General Purpose ◽  
Simulation Software ◽  
Variable Load ◽  
Influence Coefficient ◽  
Influence Coefficients ◽  
Influence Coefficient Method

The dimensioning of general-purpose machines such as manipulators involves the solution of a number of preliminary issues. The determination of reference external loads and the identification of machine configurations that give the maximum internal load for each component are two of these issues. These two problems are commonly addressed through trial-and-error procedures based on dynamic modelling, which are implemented with the support of simulation software, since static analyses are commonly considered inadequate to solve them. Despite this, here, a technique based on influence coefficients and static analyses is presented which solves them. Such technique is also able to foresee and justify dynamic issues (i.e., possible vibrations, etc.) that could heavily affect the machine behavior. The effectiveness of the proposed technique is proved by implementing it on a 3T1R parallel manipulator. The presented design method is general and applicable to any type of non-overconstrained manipulator or mechanism.

Influence Coefficients Obtained by Hammer Beat Permit Significant Time Savings When Balancing Simple Flexible Rotors

1999 ◽  
Author(s):  
D. Wiese ◽  
M. Breitwieser
Keyword(s):  
Influence Coefficient ◽  
Significant Time ◽  
Flexible Rotors ◽  
Influence Coefficients ◽  
Flexible Roll ◽  
Influence Coefficient Method ◽  
Time Savings ◽  
Positive Results ◽  
Coefficient Method

Abstract The following paper presents a method for balancing simple flexible rotors with the help of influence coefficients obtained by hammer beat. The method permits time savings of approx. 50% compared to the conventional influence coefficient method. Initial positive results obtained on a flexible roll are also presented.

NCSXRF: A General Geometry Monte Carlo Simulation Code for EDXRF Analysis

1991 ◽  
Vol 35 (B) ◽  
pp. 727-736 ◽  
Author(s):  
T. He ◽  
R. P. Gardner ◽  
K. Verghese
Keyword(s):  
Least Square ◽  
Influence Coefficient ◽  
Standard Samples ◽  
Simulation Code ◽  
X Ray ◽  
Fundamental Parameters ◽  
Edxrf Analysis ◽  
Influence Coefficient Method ◽  
Energy Pulse

EDXRF analysis is conveniently split into two parts: (1) the determination of X-ray intensities and (2) the determination of elemental amounts from X-ray intensities. For the first, most EDXRF analysis has been done by some method of integrating the essentially Gaussian distribution of observed full energy pulse heights. This might be done, for example, by least-square fitting of Gaussian distributions superimposed on a straight line or a quadratic background. Recently more elaborate shapes of the energy peaks also have been considered (Kennedy, 1990). After the X-ray intensities have been determined, interelement effects between the analyte element and other elements must be corrected for in order to obtain the elemental amounts from X-ray intensities. This correction can be done either by an empirical correction procedure as in the influence coefficient method which requires measurements on a number of standard samples to determine the required coefficients, or by theoretical calculation as in the fundamental parameters method which does not require standard samples.

scholarly journals A method to select correcting faces of a double-face dynamic balancing rotor

2016 ◽  
Vol 8 (12) ◽  
pp. 168781401668289
Author(s):  
Shihai Zhang ◽  
Zimiao Zhang
Keyword(s):  
Influence Coefficient ◽  
Axial Distribution ◽  
Dynamic Balancing ◽  
The Real ◽  
Influence Coefficients ◽  
Total Phase ◽  
Influence Coefficient Method ◽  
Phase Variations ◽  
Distribution Laws ◽  
Design And Practice

Considering the sensitivity and installing position limitation, the real positions for two correcting faces must be selected first in the process of double-face dynamic balancing design and practice for rigid rotor system. According to the principle of influence coefficient method, series of testing weight experiments are conducted in this article. Based on the experimental results, the axial distribution laws of the amplitudes and phases of influence coefficients are found and summarized as follows: the amplitude variations of influence coefficients are very small and the phase variations of influence coefficients are obvious when the correcting positions are changed along shaft, so the phases of influence coefficients have the key effect on the correcting vector in correcting faces. Based on this fact, the total phase difference maximum method of influence coefficients is proposed to select the real axial positions for correcting faces. The principle of the method is analyzed in theory, and the application effect is tested by double-face dynamic balancing experiments.

The Use of Parameter Influence Coefficients in Computer Analysis of Dynamic Systems

SIMULATION ◽  
1964 ◽  
Vol 3 (2) ◽  
pp. 53-63 ◽  
Author(s):  
Hans F. Meissinger
Keyword(s):  
Random Noise ◽  
Original System ◽  
Operating Conditions ◽  
Influence Coefficient ◽  
Problem Solution ◽  
Computer Technique ◽  
Influence Coefficients ◽  
Parameter Values ◽  
Parameter Influence

A new computer technique is described which yields the partial derivatives of problem variables with re spect to pertinent system parameters simultaneously with the solution of the original system differential equations. These derivatives, known as parameter influence coefficients, are valuable to the analyst in enhancing his understanding of system characteris tics. If the problem solution x(t, λ) and the parameter influence coefficient ∂x/∂λ (t, λ) is known for a par ticular operating point where λ= λ0, then it is pos sible to make a first-order prediction of system behavior at a neighboring point having the new parameter value λ1 = λ0 + Δλ. Similar predictions can be made if not one but several parameters are to be varied. Thus, the knowledge of parameter in fluences often helps to reduce the total number of computer runs required in a parametric system study. Typical applications of the technique are: linear ex trapolation in the neighborhood of a known solution, determination of design tolerances of a system, and prediction of critical parameter values and stability boundaries. The most useful application pertains to systems disturbed by random noise where normally a very large number of computer runs would be re quired to analyze the system on a statistical basis in a variety of operating conditions. Several illustrative examples are presented in the paper.

Analysis of III-Conditioned Characteristics about Weight Location of Rotor Dynamic Balancing

2014 ◽  
Vol 602-605 ◽  
pp. 670-673
Author(s):  
Ke Wang ◽  
Zhixu Dong ◽  
Long Tao Cong ◽  
Xing Wei Sun ◽  
Meng Nan Sun
Keyword(s):  
Mechanical Vibration ◽  
Great Influence ◽  
Solution Process ◽  
Influence Coefficient ◽  
Influence Coefficients ◽  
Location Parameters ◽  
Influence Coefficient Method ◽  
The Relationship ◽  
Coefficient Method ◽  
Mechanical Nature

Balancing with the influence coefficient method can eliminate rotor unbalance effectively and briefly which usually causes mechanical vibration. But the accuracy of this method is susceptible to operating condition and the structure of mechanical equipments will leads to unstable equilibrium outcomes. The theoretical study of the influence coefficient balancing method can find that the solution process of balancing weight does not involve the mechanical nature of unbalance vibration, and therefore it will be subject to greater interference of equation’s ill-conditioned characteristics. By introducing the modal superposition, vibration mode function can be linked with the influence coefficients to establish the relationship between counter weight location parameters and ill-conditioned equations. The simulation results of multiple-blade rotor shows that positions of balancing weight will exert great influence on ill-conditioned characteristics. So the position parameters should be chosen in front of balancing service reasonably.

Two-Plane Balancing of a Rotor System Without Phase Response Measurements

1987 ◽  
Vol 109 (2) ◽  
pp. 162-167 ◽  
Author(s):  
Louis J. Everett
Keyword(s):  
Phase Measurement ◽  
Influence Coefficient ◽  
Single Plane ◽  
Flexible Rotors ◽  
Influence Coefficients ◽  
Wide Range ◽  
Influence Coefficient Method ◽  
Require Response ◽  
Rigid Rotors ◽  
Coefficient Method

This paper presents, and experimentally verifies, a two-plane balancing technique for rigid rotors and possibly flexible rotors operating at a constant speed. The technique, based upon influence coefficients, extends the single-plane four-run balancing procedure to two planes. Like the four-run method, this technique is most easily performed graphically and does not require response phase measurement. Despite the additional runs required to obtain data, its simplicity and applicability to a wide range of equipment renders it more useful, in some cases, than the standard two-plane influence coefficient method.

The Influence Coefficient Method and its Linear Increment Calculation Research of the Creep Effect for an Un-Cracked Concrete Beams Reinforced with FRP

2011 ◽  
Vol 250-253 ◽  
pp. 2129-2134
Author(s):  
Guo Dong Zheng
Keyword(s):  
Concrete Beams ◽  
Influence Coefficient ◽  
Cracked Concrete ◽  
Influence Coefficients ◽  
Influence Coefficient Method ◽  
Stress Prediction ◽  
Modulus Method ◽  
Coefficient Method ◽  
Linear Increment

On the basis of the time-adjusted effective modulus method (AEMM method) and the steel influence coefficients, the combined influence coefficients of the concrete beams strengthened with FRP is proposed. It will have a higher numerical accuracy if the initial stress is substituted with the average stress of concrete and the stress is assumed to remain linear with time during the period in the step by step calculation process. The linear incremental calculation method based on the idea of the creep combined influence coefficient method of concrete beams reinforced with FRP is proposed, which provides a theoretical basis for the creep calculation and long-term stress prediction for an un-cracked concrete beams reinforced with FRP.

Load Distribution of Straight Beveloid Gears with Parallel Axes

2011 ◽  
Vol 308-310 ◽  
pp. 1773-1777
Author(s):  
Qiang Liu ◽  
Jia Xu Wang ◽  
Bei Li Yu ◽  
Ke Xiao
Keyword(s):  
Computer Program ◽  
Load Distribution ◽  
General Purpose ◽  
Influence Coefficient ◽  
The Finite Element Method ◽  
Beveloid Gears ◽  
Influence Coefficient Method ◽  
General Purpose Computer ◽  
Purpose Computer ◽  
Coefficient Method

An approach for the analysis of tooth contact and load distribution of straight beveloid gears with parallel axes is proposed. The approach is based on application of influence coefficient method that accommodates the influence of contact deformation and tooth deflection. Computer program has been written to calculate the distribution of pressure. Results have been analyzed and validated by comparison with studies carried out by the finite element method with the aid of ANSYS general purpose computer program. Suggestion has been given to minimize the drawback generated by stress concentration.

Extended Influence Coefficient Method for Rotor Active Balancing During Acceleration

2004 ◽  
Vol 126 (1) ◽  
pp. 219-223 ◽  
Author(s):  
Shiyu Zhou ◽  
Stephen W. Dyer ◽  
Kwang-keun Shin ◽  
Jianjun Shi ◽  
Jun Ni
Keyword(s):  
Fatigue Life ◽  
Gain Scheduling ◽  
Rotor System ◽  
Influence Coefficient ◽  
Resonant Vibration ◽  
Active Balancing ◽  
Look Up Table ◽  
Influence Coefficients ◽  
Influence Coefficient Method ◽  
Coefficient Method

Imbalance-induced vibration of rotating machineries is an important factor limiting the performance and fatigue life of a rotor system. Particularly, the severe resonant vibration of a rotor when it passes through its critical speeds could damage the rotor system. To avoid this peak vibration, this paper presents an active balancing method to offset the imbalance of the rotor system during acceleration by using an electromagnetic balancer. In this method, “instantaneous” influence coefficients at different speeds are obtained and stored in a look-up table. Then, a gain scheduling strategy is adopted to suppress the imbalance-induced vibration during acceleration based on the “instantaneous” influence coefficient table. A comprehensive testbed is built to validate this scheme, and the validation results are presented.

Practical Balancing of Flexible Rotors for Power Generation

2007 ◽  
Author(s):  
Zlatan Racic ◽  
Juan Hidalgo
Keyword(s):  
Power Plants ◽  
Influence Coefficient ◽  
Theoretical Derivation ◽  
Flexible Rotors ◽  
Influence Coefficients ◽  
Turbo Generator ◽  
Mass Moment ◽  
Practical Standpoint ◽  
Influence Coefficient Method ◽  
Generator Sets

Balancing technology is still relatively new. Thirty years ago it was primarily still part of the skilled trade and was often obscured. Today there is enough reference literature printed during the last 20 years alone on general balancing and balancing of flexible rotors, that could fill a room, (Ref: N. Rieger). The majority of papers and other references deal with theoretical derivation of equations based on Jeffcott rotor model. With the growth of rotor sizes specifically of electric generators in power plants, so grew the need to develop not only a theory, but also the way to practically balance these rotors. The economy of manufacturing required pushing the rotors to more and more slender; lower and lower stiffness (∝ EIxx/L3) designs, in relation to its mass moment of inertia (Im), these rotors were more difficult to balance. The first to encounter the problem of balancing these rotors were the OEMs. On two different shores of the Atlantic Ocean, two basic balancing theories known as balancing in “N”, or in “N+2” balancing planes and operating rotor modes were developed. Later, with the development of the microcomputer the influence coefficient method had gained popularity among the power plant community and despite good experiences from both sides the controversy over which one produces better results was left open. In this paper a review of the “N” and “N+2” methods including notes on influence coefficients (IC) is conducted from a practical standpoint. The conclusion by the Authors is that there is no “better” or “worse” balancing method, only the more or less economical in a given situation, and neither gives a unified method to satisfy every rotor. General guidance is also provided over which method to use for best results in balancing large turbo-generator sets.

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