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Research Papers

Hydraulic Modal Analysis in Theory and Practice

[+] Author and Article Information
Gudrun Mikota

Institute of Machine Design and
Hydraulic Drives,
Johannes Kepler University Linz,
Altenbergerstrasse 69,
Linz A-4040, Austria
e-mail: gudrun.mikota@jku.at

Bernhard Manhartsgruber

Institute of Machine Design and
Hydraulic Drives,
Johannes Kepler University Linz,
Altenbergerstrasse 69,
Linz A-4040, Austria
e-mail: bernhard.manhartsgruber@jku.at

Franz Hammerle

Institute of Machine Design
and Hydraulic Drives,
Johannes Kepler University Linz,
Altenbergerstrasse 69,
Linz A-4040, Austria
e-mail: f.hammerle@gmx.at

Andreas Brandl

Institute of Technical Mechanics,
Johannes Kepler University Linz,
Altenbergerstrasse 69,
Linz A-4040, Austria
e-mail: andreas.brandl@jku.at

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received July 3, 2018; final manuscript received November 28, 2018; published online January 18, 2019. Assoc. Editor: Youngsu Cha.

J. Dyn. Sys., Meas., Control 141(5), 051007 (Jan 18, 2019) (12 pages) Paper No: DS-18-1315; doi: 10.1115/1.4042145 History: Received July 03, 2018; Revised November 28, 2018

Theoretical and experimental modal analyses are treated for hydraulic systems modeled by discrete capacities, inductances, resistances, and fluid lines with dynamic laminar flow. Based on an approximate multi-degrees-of-freedom description, it is shown how hydraulic natural frequencies, damping ratios, and mode shapes can be identified from measured frequency response functions between flow rate excitation and pressure response. Experiments are presented for a pipeline system that includes three side branches and an accumulator. In view of practical applications, two different types of servovalve excitation as well as impact hammer excitation are considered. Pressure is measured by 19 sensors throughout the system. Results are compared in terms of frequency response functions between 50 and 850 Hz, the first five hydraulic modes, and weighted auto modal assurance criteria of experimental mode shapes. Out of the tested excitation devices, the servovalve is clearly preferred; if valves cannot be used, the impact hammer offers a reasonable workaround. For a reduced number of five sensors, different sensor arrangements are assessed by the respective weighted auto modal assurance criteria of experimental mode shapes. A theoretical hydraulic modal model provides a similar assessment. The quality of the theoretical model is confirmed by the weighted modal assurance criterion of theoretical and experimental mode shapes from servovalve excitation.

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References

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Figures

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Fig. 1

Three-dimensional hydraulic schematic of experimental setup, lengths in mm

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Fig. 2

Detail of experimental setup

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Fig. 3

Frequency response function between flow rate from servovalve ramp excitation and pressure response at sensor 2

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Fig. 4

Frequency response function between flow rate from servovalve burst chirp excitation and pressure response at sensor 2

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Fig. 5

Frequency response function between flow rate from impact hammer excitation and pressure response at sensor 2

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Fig. 6

Frequency response function between flow rate from servovalve ramp excitation and pressure response at sensor 19

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Fig. 7

Frequency response function between flow rate from servovalve burst chirp excitation and pressure response at sensor 19

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Fig. 8

Frequency response function between flow rate from impact hammer excitation and pressure response at sensor 19

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Fig. 9

First pressure mode shape from servovalve ramp excitation at 109.0 Hz, 5.94% damping

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Fig. 10

Second pressure mode shape from servovalve ramp excitation at 335.4 Hz, 3.17% damping

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Fig. 11

Third pressure mode shape from servovalve ramp excitation at 406.8 Hz, 3.34% damping

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Fig. 12

Fourth pressure mode shape from servovalve ramp excitation at 711.0 Hz, 2.50% damping

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Fig. 13

Fifth pressure mode shape from servovalve ramp excitation at 820.5 Hz, 2.25% damping

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Fig. 14

First pressure mode shape from impact hammer excitation at 110.1 Hz, 5.02% damping

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Fig. 15

Second pressure mode shape from impact hammer excitation at 337.0 Hz, 2.89% damping

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Fig. 16

Third pressure mode shape from impact hammer excitation at 401.5 Hz, 4.17% damping

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Fig. 17

Fourth pressure mode shape from impact hammer excitation at 725.5 Hz, 3.48% damping

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Fig. 18

Fifth pressure mode shape from impact hammer excitation at 817.8 Hz, 1.54% damping

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Fig. 19

AutoWMAC matrix of experimental mode shapes from servovalve ramp excitation and pressure sensors 1–19

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Fig. 20

AutoWMAC matrix of experimental mode shapes from servovalve burst chirp excitation and pressure sensors 1–19

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Fig. 21

AutoWMAC matrix of experimental mode shapes from impact hammer excitation and pressure sensors 1–19

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Fig. 22

AutoWMAC matrix of experimental mode shapes from servovalve burst chirp excitation and pressure sensors 1, 3, 7, 14, and 19

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Fig. 23

AutoWMAC matrix of experimental mode shapes from servovalve burst chirp excitation and pressure sensors 1, 5, 9, 16, and 19

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Fig. 24

AutoWMAC matrix of experimental mode shapes from impact hammer excitation and pressure sensors 1, 5, 9, 16, and19

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Fig. 25

AutoWMAC matrix of theoretical mode shapes based on frequency response functions between flow rate from servovalve excitation and pressure response at sensors 1, 3, 7, 14, and 19

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Fig. 26

AutoWMAC matrix of theoretical mode shapes based on frequency response functions between flow rate from servovalve excitation and pressure response at sensors 1, 5, 9, 16, and 19

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Fig. 27

Weighted modal assurance criterion matrix of theoretical and experimental mode shapes from servovalve burst chirp excitation and pressure sensors 1–19

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Fig. 28

Weighted modal assurance criterion matrix of theoretical and experimental mode shapes from servovalve ramp excitation and pressure sensors 1–19

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Fig. 29

Weighted modal assurance criterion matrix of theoretical and experimental mode shapes from impact hammer excitation and pressure sensors 1–19

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