Keywords
Acoustics, Noise, Fluid Power, Positive Displacement Machines, Data Analytics
Presentation Type
Talk
Research Abstract
Noise control is an important factor in evaluating the design of positive displacement machines. This research project aims to develop new tools in MATLAB, with emphasis on visual approaches, to comprehensively characterize the noise generated by positive displacement machines in spatial, temporal and frequency domains. Sound pressure level (SPL), sound intensity level (SIL) and loudness were calculated and plotted on a measurement surface surrounding the pump, which illustrates the spatial distribution of the sound field. In order to highlight the phenomenon within specific frequency bands, Butterworth filters were used to isolate desired frequencies, such that specific harmonic content or 1/3 Octave bands content can be analyzed. In addition to static visualization methods, videos were created by compressing a series of sphere plots in time to illustrate the dynamic characteristics of the measured sound. Corresponding phase plots were generated at the same time to statically illustrate these dynamic characteristics shown on videos. The successful generation of the various methods of characterizing and visualizing pumps generated noise was evaluated on a large sample set of more than 150 measure grids with nearly 30000 individual microphone measurements. The creation of these analytics has already changed the conversation and challenged the state of the art in hydraulic Noise Vibration and Harshness (NVH).
Session Track
Modeling and Simulation
Recommended Citation
Dan Ding, Monika Ivantysynova, and Paul Kalbfleisch,
"Development of Data Analytics Tools for Acoustic Measurement of Positive Displacement Machines"
(August 4, 2016).
The Summer Undergraduate Research Fellowship (SURF) Symposium.
Paper 38.
https://docs.lib.purdue.edu/surf/2016/presentations/38
Included in
Development of Data Analytics Tools for Acoustic Measurement of Positive Displacement Machines
Noise control is an important factor in evaluating the design of positive displacement machines. This research project aims to develop new tools in MATLAB, with emphasis on visual approaches, to comprehensively characterize the noise generated by positive displacement machines in spatial, temporal and frequency domains. Sound pressure level (SPL), sound intensity level (SIL) and loudness were calculated and plotted on a measurement surface surrounding the pump, which illustrates the spatial distribution of the sound field. In order to highlight the phenomenon within specific frequency bands, Butterworth filters were used to isolate desired frequencies, such that specific harmonic content or 1/3 Octave bands content can be analyzed. In addition to static visualization methods, videos were created by compressing a series of sphere plots in time to illustrate the dynamic characteristics of the measured sound. Corresponding phase plots were generated at the same time to statically illustrate these dynamic characteristics shown on videos. The successful generation of the various methods of characterizing and visualizing pumps generated noise was evaluated on a large sample set of more than 150 measure grids with nearly 30000 individual microphone measurements. The creation of these analytics has already changed the conversation and challenged the state of the art in hydraulic Noise Vibration and Harshness (NVH).