2004
DOI: 10.1088/0964-1726/13/3/001
|View full text |Cite
|
Sign up to set email alerts
|

Modeling active vibration control of a geared rotor system

Abstract: This paper analyzes the practicality of active internal shaft transverse vibration control using a piezoelectric stack actuator for reducing external gearbox housing structure response due to transmission error excitation from a gear pair. The proposed adaptive controller that is designed specifically for tackling mesh frequency vibrations is based on an enhanced filtered-x least mean square algorithm with frequency estimation to synthesize the required reference signal. The vital system secondary path charac… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
2

Citation Types

1
19
0

Year Published

2008
2008
2018
2018

Publication Types

Select...
6
1

Relationship

1
6

Authors

Journals

citations
Cited by 25 publications
(20 citation statements)
references
References 28 publications
1
19
0
Order By: Relevance
“…a feedback control that has a feedback controller K(s) embedded with a feedforward control loop in which an adaptive FIR filter W(z) is used, as illustrated in Figure 2. (a) Feedforward control-The feedforward loop is an adaptive controller which uses the filtered-x least mean square (FXLMS) algorithm to adjust the filter weights. The FXLMS control algorithm, an extended version of the LMS algorithm typically used for dynamic systems with phase delay secondary paths, is well studied and has been widely applied to many active vibration and noise control applications [14,16,[19][20][23][24]. This controller requires detailed information about the secondary path transfer function.…”
Section: Controller Designmentioning
confidence: 99%
See 1 more Smart Citation
“…a feedback control that has a feedback controller K(s) embedded with a feedforward control loop in which an adaptive FIR filter W(z) is used, as illustrated in Figure 2. (a) Feedforward control-The feedforward loop is an adaptive controller which uses the filtered-x least mean square (FXLMS) algorithm to adjust the filter weights. The FXLMS control algorithm, an extended version of the LMS algorithm typically used for dynamic systems with phase delay secondary paths, is well studied and has been widely applied to many active vibration and noise control applications [14,16,[19][20][23][24]. This controller requires detailed information about the secondary path transfer function.…”
Section: Controller Designmentioning
confidence: 99%
“…To ensure an adequate coherence level between the reference and disturbance signals, the exact principal frequency of MRI noise must be obtained in advance. A frequency estimator [24] uses the acquired signal to estimate in real time the instantaneous principal frequency. Using this frequency estimation technique, the reference signal, r(n), at the target principal frequency can be accurately synthesized.…”
Section: Controller Designmentioning
confidence: 99%
“…The results show the vibrations reduction up to about 20 dB at the first two mesh harmonics. Li et al [7][8][9] adopted the FxLMS control algorithm to actuate the PZT to produce the active control force for reducing the gearbox vibrations, and the simulation work successfully demonstrated the feasibility of applying the proposed control scheme to gear vibration problems. Based on a combination of feedback and repetitive control strategy, Pinte et al [10] applied a modular bearing using piezostacks to generate secondary forces for suppressing the noise and vibration of the rotation machinery.…”
Section: Introductionmentioning
confidence: 97%
“…Vibration and noise caused by gearbox will weaken the stealthy performance of ships and contribute the structural-borne noise in helicopters [1]. In order to suppress the vibration and improve dynamic properties of gearbox, such methods as active vibration control and dynamic optimization should be taken [2][3][4]. But the prerequisite is that the dynamic transmission characteristics must be studied.…”
Section: Introductionmentioning
confidence: 99%