Active Noise Control: Is it Good for Anything?
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1 Active Noise Control: Is it Good for Anything? Scott D. Sommerfeldt Acoustics Research Group Dept. of Physics & Astronomy Brigham Young University April 2, 2012
2 Acoustics AMO Astronomy/Astrophysics Condensed Matter Plasma Theoretical Physics Physics and Astronomy Department Size 32 Faculty Members 325 Undergraduates 35 Graduate Students
3 Acoustics Research Group Interdisciplinary Group currently primarily Physics and ME Physics: 4 full-time faculty (Sommerfeldt, Leishman, Gee, Thomas), one part-time faculty (Neilsen) ME: 2 faculty (Blotter, Thomson) Typically ~15 grads and ~ 25 undergrads involved from Physics, ME, few from EE ARG meets weekly to discuss acoustics topics typical attendance is about 30 External funding for group ~ $400k/year Strong student chapter of Acoustical Society of America Program recognized widely nationally
4 Outline History and background Principles of active control Local vs global control Global control for free-field radiation Global control in an enclosed field Conclusions
5 Brief History Active control began in 1930 s, with work of Paul Lueg λ/2 Major drawback: - acoustic feedback - only worked at certain frequencies - drifting electronics A
6 History (cont.) Brief revival in 1950 s Harry Olson Development of digital signal processing led to explosion of research beginning around Number of papers increased nearly exponentially for couple of decades appears to be leveling off some now.
7 Active Control Principles Most acoustics applications involve linear systems principle of superposition holds. How well must the fields match? Phase errors: Magnitude errors: For -20 db, θ = 5.7 For -20 db, amp. ratio = 1.0 db -30 db, θ = 1.8 For -30 db, amp. ratio = 0.3 db
8 Mechanisms of Active Control I. Destructive Wave Interference Interference between waves leads to "zone of silence." Size of zone of silence λ. Global energy in the field increases. May not be a problem if the increase in energy is localized to areas of little concern.
9 Mechanisms of Active Control (cont.) II. Mutual Coupling Closely spaced sources modify each other's radiation impedance. Possible to achieve global attenuation of sound or vibration field. (Ex. dipole vs. monopole) Power radiated by two closely spaced sources proportional to 1 - sin(kd)/(kd). Thus, sources must be closely spaced. For enclosed fields, sources may be remote from each other, but still coupled through the modes of the enclosure.
10 Adaptive Minimization Schematic of control system Error given by: e( t) d ( t) N n 1 0 w n x( t n)
11 Adaptive Minimization (cont.) Update coefficients using negative gradient Result: w n ( t 1) w ( t) x( t n) e( t) n
12 Global ANC Suppression vs. interference Mutual coupling of sources affects radiation resistance, power radiated Multi-channel systems often required for three-dimensional sound fields Global control requires small separation between noise and control sources Choose error sensor locations and types which result in global attenuation
13 Difficulty of ANC Problems 13
14 Cooling Fan Noise Axial fans used to cool computers, projectors, etc. Spectrum dominated by tonal noise (BPF and harmonics) Tonal noise result of unsteady loading on the fan blades
15 Previous Research and Objectives Previous: Single channel efforts Error microphone usually in far field Significant global attenuation for BPF (~12 db), less for harmonics Objectives: Multi-channel ANC to achieve global tonal attenuation Error microphones in practical near field locations
16 Theoretical Analysis Determine: good near field error microphone locations for given control source configuration appropriate number of control sources Model fan/control sources as ideal point sources Calculate control source strengths that minimize radiated power Plot 2-D pressure and find potential microphone locations
17 Theoretical Analysis Results
18 Theoretical Analysis Results
19 Experimental Apparatus 80 mm (3.25 ) seven-bladed fan Mounted on face of CPU-like enclosure 1 wide rectangular obstruction to create unsteady loading on fan inlet BPF maintained at 370 Hz Four 1 1/8 loudspeakers mounted around fan Error microphones located on surface of enclosure Nonacoustic reference sensor Infrared emitter/detector Voltage waveform with BPF and harmonics Multi-channel filtered-x LMS algorithm
20 Experimental Apparatus
21 Reference Signal Power Spectrum
22 ANC at Error Microphone
23 2 x 2 ANC Ideal 7.1 db 13.5 db Mean-Square Pressure Reduction 5.6 db 5.4 db
24 4 x 4 ANC Ideal 8.4 db 18.5 db 15.5 db 14.3 db
25 Cooling Fan Control System Previous System 80 mm fan 32 mm loudspeakers 370 Hz BPF Modifications 60 mm fan 20 mm loudspeakers 600 Hz BPF Increase fan speed
26 60 mm Fan Results
27 Global Comparison Mean-square pressure reduction (MPR) 80 mm 60 mm Ideal kd MPR kd MPR kd MPR BPF db db 0.5 ~30 db 2 x BPF db db db 3 x BPF db db db
28 Optimizing the Source Configuration Symmetric source configuration shown was assumed to be optimal Configuration can be optimized through use of a genetic algorithm Four control sources assumed
29 Optimizing the Source Configuration
30 Symmetric vs. Linear Configuration
31 Fan-Noise Findings Multi-channel ANC for cooling fan successfully demonstrated Point source modeling yields consistently good near field locations for error microphones Fan is complex noise source at higher harmonics need multiple control channels for global reductions With better loudspeakers, can achieve more attenuation for BPF 80 mm fan 60 mm fan
32 Active Control of Energy Density in a Vehicle Cabin
33 The operator s head does not necessarily stay in a fixed location during typical operation.
34 Energy Density vs Pressure 2 Squared Pressure (SP) More spatial variation Control can yield low pressure but potentially high velocity Control tends to be more local Energy Density (ED) Less spatial variation Control requires both pressure and velocity to be minimized Control tends to be more global
35 Acoustic Energy Density Kinetic Energy Potential Energy Total Energy Instantaneous Energy Density
36 Spatial Dependence for a Rectangular Enclosure
37 SP Nodal Structure
38 ED Nodal Structure
39 2D Sensor 2D Sensor Effective When Placed Near Wall or Ceiling Computationally More Efficient
40 The Enclosure Potential Application: Cab Noise Enclosure Fairly Representative of Small Equipment Cab
41 Sensor and Mic Placement ED Control Has Less Dependence on Sensor Location
42 Noise Source and Subwoofer
43 110 Hz Sensor
44 110 Ear Location
45 Engine Tone Attenuation (db) 46 Hz 90 Hz 110 Hz 120 Hz 12-Mic Avg Right Ear Left Ear Sensor
46 Sound Level Reduction (dba) 46 Hz 90 Hz 110 Hz 120 Hz 12-Mic Avg Right Ear Left Ear Sensor
47 Cab Noise Findings Engine tones can be attenuated drastically Attenuation is achieved throughout cabin Significant reduction in total sound level is possible, even with A weighting Much can still be done with respect to performance optimization 50 Hz
48 Examples Heavy Equipment (Caterpillar) Wheel Loader Cab Focused on tonal noise at engine firing frequency 48
49 Hardware Configuration Sub-woofer used for low frequencies Smaller drivers (10 cm) used for higher frequencies ED sensor mounted in convenient location 49
50 50 May 22-23, 2011 Cab Response Engine Sweep Results measured at nominal operator head location Relative L p Relative L p
51 51 May 22-23, 2011 Control Results Engine Sweep Relative L p Relative L p
52 Lp (db) 10 db/div May 22-23, 2011 Engine Firing Freq Engine Sweep 972H prototype - firing frequency Lp at left ear ANC OFF ANC ON rpm
53 Cab Results Global Response operator head front upper plane lower plane 53
54 Conclusions Active noise control is a viable solution for certain applications. Need to be careful in applying technology in order to achieve desired results. Good understanding of physics of application necessary for proper implementation. Technology starting to find its way into real applications cost is still an issue but it has come way down.
55 Current Applications Honda 2005 Odyssey and Accord Hybrid Lexus Accura Saab commuter jet Active headsets BMW working on implementing an ANC system
56 Special Thanks To... Kent Gee Ben Faber Brian Monson Connor Duke Ben Shafer Jared Thomas Stephan Lovstedt The BYU Acoustics Research Group
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