Acoustic Beamforming for Vehicle Pass-By Noise Testing Using LabVIEW

"We chose NI hardware that is compact and DC-powered to provide power to the microphones in the array."

- Samir N.. Gerges, Federal University of Santa Catarina (UFSC)

challenge:

Develop a portable and affordable acoustic beamformer to enable noise source identification in pass-by noise measurements and other applications.

Solution:

A spiral array of 32 microphones, NI LabVIEW software, the NI Sound and Vibration Measurement Suite, and a 32-channel NI CompactDAQ system with eight NI 9234 4-channel dynamic signal acquisition (DSA) modules are used to obtain visualizations of noise sources and identify signals generated by moving vehicles.

The Noise and Vibration Laboratory of the Federal University of Santa Catarina (UFSC) in Brazil conducts various research projects and participates in the R&D of the automotive industry to enable products to comply with noise and vibration standards. In addition to supporting the development of local industry, our university also strongly promotes academic development in undergraduate/graduate teaching and research.

Pass-by noise tests are standardized to quantify the maximum incidental noise level of a vehicle during operation. In many countries, government agencies have limits on sound testing, usually ISO362 - Measurement of noise generated by accelerating road vehicles. These regulations are designed to record the level of the main noise sources generated by vehicles in normal urban traffic, usually with a speed limit of 50 or 70 km/h. Vehicle pass-by noise tests verify that a compliant car does not generate traffic noise exceeding the specified limits.

Many parts of a car generate noise, including the motor, exhaust, transmission, and tires. Standard pass-by noise tests cannot identify the source noise that will cause the test to fail, so we need a technology that can visualize the sound field to distinguish different sound sources. In this test, we use beamforming to see which sound sources will significantly increase the overall noise and affect the vehicle's pass-by noise.

Beamforming

We built a beamformer, or "acoustic camera," consisting of a spiral array of 32 microphones with a maximum diameter of 1 meter between the microphones to capture visual images of the noise source, and a 1.1 by 1 meter metal grid. The array was positioned the same as the single microphone in the standard test, 7.5 meters from the centerline of the channel, with its center 1.3 meters above the ground, to ensure that all measurement conditions in the test were the same.

Our students built an array microphone using low-cost electret box microphones. Traditional directional array hardware consists of commercially available condenser microphones and preamplifiers, but is too expensive for lab use. Creating a complete array microphone saves money and provides a valuable project for students. Research at NASA Langley Research Center found that the electret box used produced a microphone frequency response that is suitable for directional arrays, with minimal changes in the amplitude and phase response of the audio spectrum and moderate changes in high frequencies. We completed this design based on the above research.

Data collection

We used the NI USB-9162 high-speed C Series USB case with eight NI 9234 DSA modules for data acquisition. We chose compact, DC-powered NI hardware that can provide power to the microphones in the array. The module has an alias-free bandwidth of up to 20 kHz. In addition, phase matching of the channels is very important for acoustic beamforming, and the system stipulates that the phase mismatch between any two channels cannot exceed one degree.

Since the system is DC powered, it is convenient to operate with batteries. Running LabVIEW software and the Sound and Vibration Measurement Suite on a laptop computer, voltage values ​​can be easily converted to engineering units used in noise measurements. In addition, the Sound and Vibration Measurement Suite complies with the international standards of IEC61260 (electroacoustics, octave and fractional octave bandpass filters) and IEC61672 (electroacoustics and sound level meters) for sound level measurement, weighted filters, and octave analysis, and its measurement results are accurate and repeatable.

analyze

Once the data was acquired, we analyzed it using a traditional delay-and-sum beamforming algorithm. We summarized the sound signal and described the different propagation paths from the source to the different microphones. The sound source passed the acoustic camera at high speed (modern cars are still slow compared to the sampling speed of the data acquisition system), which allowed the beam to focus and track the source through the microphone array. We had to correct for the Doppler effect with the inverse Doppler process, which includes amplitude and frequency correction, to obtain a coherent signal sum.

To calibrate the acoustic measurements with photos of the vehicle being tested and superimposed noise amplitudes, we activated the buzzer (main unit approximately 90 dB at 2.2 kHz) and the vehicle running at a constant speed of 50 km/h, passing through the array like a regular pass test.

We adopted this method instead of the steady-state measurement because of its fast acquisition speed and high quality. It also presents the same kind of recordings as in the through-measurement. The position of the beeper allows the photo and data to be aligned accurately.

Since the vehicle's tires and turbulent motion around the body generate noise during movement, we apply this technology to the vehicle to accurately evaluate and identify these noises. In this way, we can effectively reduce the vehicle's passing noise outside the wind tunnel.