Thesis Abstract and Dissertation Abstracts
On-line Balancing of Rotors
Abstract Category: Engineering
Course / Degree: Bachelor of Technology
Institution / University: Indian Institute of Technology, Kharagpur, India
Published in: 2004
The current on-line rotor balancing systems are made up of four major parts: the balanced rotor system, the sensor, the controller and the balancing regulator among which the former two are well known while the later are still being researched. The controlling method of the online balancing regulator has been designed according to whether the position of the correction mass is able to be detected accurately in few or more trial runs. The electromagnetic balancing regulator (EBR) which operates in accordance with the motor principle adopts an optimum seeking rule. When the electromagnetic torque generated by the electric current which is fed into the coils on the stator is more powerful than the joint torque between the slide plate seats, the slide plate and the correction mass rotate circumferentially and there is an angle displacement with respect to the balanced shaft (Fig. 1).
Fig. 1:(Index) Design of the balancing regulator. 1: sensor for detecting the position of mass; 2: stator; 3: reflection film; 4: press board; 5: slide plate; 6: slide plate seat; 7: correction mass; 8: balanced shaft; 9: screw and spring
A control scheme has been developed such that when the vibration of the rotor increases to a certain extent, it judges whether to perform balancing or not, detects the positions of the correction masses, calculates the unbalance on the rotor and determines the optimum position of each correction mass. A particularly attractive feature of the system is that it provides a vibration feedback and a position feedback, so that after the correction masses are driven to move a detectable angle displacement separately, their influence on vibration can be determined. This is analogous to the trial weight and to the influence coefficient calculation process of ICM, but avoids the need to stop the rotor for each trial weight addition. In view of the fact that the majority of rotors work at a relatively constant rotating speed whether they are rigid or flexible, the on-line balancing is carried out at the same constant speed.
Balancing Method for the Electromagnetic Balancing Regulator
Considering P measuring points and N balancing planes, the vibration correlation of the balancing regulator can be derieved.
In the virtue of the linear Equation correlating the balancing angle with the impel forces of initial unbalance and balancing force on the right side, the balancing aim is to adjust the balancing angle to minimize vibration of the rotor. Here the vibration and the balancing force are measurable, balancing force is controllable and intial vibration due to unbalance and the influence coefficients are unknown.
The vibration caused by initial unbalance, which is constant during a process of balancing, is determined by few initial test runs. Then the influence matrix is evaluated. Once this is done for different rotating speeds, a curve-fitting can give influence coefficient values for any speed of the rotor.
During the identification process for mass adjustment of the nth balancing head (n = 1,…,N) the goal function (vibration of rotor at the bearings) may increase, because the correction masses can rotate only in one direction. In order to minimize this effect, the ‘optimum seeking method’ is introduced: for the nth (n = 1, …., N) balancing head, first, move either correction mass; then if the goal function decreases, move it continuously; but if the goal function increases, move the other correction mass for the same angle displacement. The masses which make the goal function decrease are given the priority to rotate. We can then control each mass to rotate to its optimum position to finish the balancing.
Keeping all the above in view, an advanced control scheme was simulated in a MATLAB program and its effects on the EBR are listed in Table 1.
Thesis Keywords/Search Tags:
Rotor Balancing, Online Balancing, Feedback Control
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Fig. 1: Design of the balancing regulator (click to enlarge) |
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Table 1: Results (click to enlarge) |
Submission Details: Thesis Abstract submitted by Debraj Sarangi from India on 09-Mar-2006 14:19.
Abstract has been viewed 4126 times (since 7 Mar 2010).
Debraj Sarangi Contact Details: Email: sarangi_00@mech.iitkgp.ernet.in
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