• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.49 no.4
• /
• pp.111-119
• /
• 2012

Time Stretched Pulse (TSP) is used for transmitting and analyzing the impulse signal over the designated spatial place. However, if transfer functions of transmitter and receiver are unknown, performance investigation of free field in temporal domain is barely possible due to the overlap between the direct and indirect signal from the space. Generally, the free field or hemi-free field is evaluated by the Annex A of ISO 3745 in which utilizing the inverse square law with one-third octave band signals. In this paper, the author performs analysis of free field via applying TSP with inverse square law and the results are compared with the one-third octave band signals. According to the analysis of deviation between the corresponding signal and inverse square law model, the proposed TSP method provides the comparable performance index to the one-third octave band signal with reduced measuring time. Provided that the pre-whitening can be implementable by employing the speaker and microphone transfer function, further analyses from TSP compression are able to be performed such as multipath separation from time domain data. The anechoic chamber used in this experiment is verified conformance with ISO 3745 for free field and hemi-free field condition for limited frequency of the signal.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1994.06a
• /
• pp.867-872
• /
• 1994

The transfer function of an acoustic system, in general, often exhibits a wide dynamic range and a very long impulse response. The time-stretched pulse (TSP) proposed by Aoshima (ATSP) has a small peak-factor and is accordingly suitable for the measuring impulse responses. The pulse is not so suitable, however, for the measurement of impulse responses over a wide frequency range. In this paper, we try to generalize and optimize this method (OATSP). This makes the method applicable for measuring of impulse responses longer than the length of the TSP. An analysis of error in such a case is also shown. Finally, we discuss how to implement this technique in specific measurement conditins.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.05a
• /
• pp.495-498
• /
• 2004

In the sound insulation measurements, the influence of background (extraneous) noise is often serious problem and how to reduce its effect and to improve the signal-to-noise(S/N) ratio is an important theme. As the background noise, such extraneous noises as road traffic noise and machine noise often disturb the measurement. In laboratory measurements on specimens with high sound insulation performances, even the internal noise of the measurement system can become a problem. To improve the signal-to-noise ratio and to improve the measurement accuracy, various kinds of digital signal processing techniques can be applied. In this paper, four kinds of digital signal processing techniques are applied and their effectiveness is examined by a simple sound insulation measurement.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.441-444
• /
• 2004

In the sound insulation measurements, the influence of background (extraneous) noise is often serious problem and how to reduce its effect and to improve the signal-to-noise(S/N) ratio is an important theme. As the background noise, such extraneous noises as road traffic noise and machine noise often disturb the measurement. In laboratory measurements on specimens with high sound insulation performances, even the internal noise of the measurement system can become a problem. To improve the signal-to-noise ratio and to improve the measurement accuracy, various kinds of digital signal processing techniques can be applied. In this paper, four kinds of digital signal processing techniques are applied and their effectiveness is examined through field measurements.

• The Journal of the Acoustical Society of Korea
• /
• v.26 no.2
• /
• pp.61-68
• /
• 2007

The frequency response of a microphone, which indicates the frequency range that a microphone can output within the approved level, is one of the most significant standards used to measure the characteristics of a microphone. At present, conventional methods of measuring the frequency response are complicated and involve the use of expensive equipment. To complement the disadvantages, this paper suggests a new algorithm that can measure the frequency response of a microphone in a simple manner. The algorithm suggested in this paper generates the Optimized Aoshima's Time Stretched Pulse(OATSP) signal from a computer via a standard speaker and measures the impulse response of a microphone by convolution the inverse OATSP signal and the received by the microphone to be measured. Then, the frequency response of the microphone to be measured is calculated using the signals. The performance test for the algorithm suggested in the study was conducted through a comparative analysis of the frequency response data and the measures of frequency response of the microphone measured by the algorithm. It proved that the algorithm is suitable for measuring the frequency response of a microphone, and that despite a few errors they are all within the error tolerance.