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The Panel Noise Contribution Analysis (PNCA) is a well-known methodology for an airborne Transfer Path Analysis (TPA) in car interior. Pressure contribution from the individual panels at a reference point can be very accurately calculated. Acoustic Trim package treatment can therefore be optimized in terms of frequency and panel area which saves money and time. The method uses only one type of sensors so called particle velocity probes for measuring source strength as well as transfer function (with a reciprocal measurement). Traditionally the PNCA makes use of a big amount of probes at fixed points (about 50) hence non-stationary conditions can be measured as well. Typically the measurement is performed in 3 sessions resulting in 150 individual panels. Because of the low spatial resolution the method can only be used at mid-low frequency range.

All surfaces of a cabin interior may contribute to the sound pressure at a certain reference position, e.g. the human's ear. Panel noise contribution analysis (PNCA) involves the measurement of the contribution of separate areas. This is an effective method to determine the effect of apparent noise sources at a specific location. This paper presents the latest developments on particle velocity based panel noise contribution analysis. In contrast to the traditional methods, the particle velocity approach is faster; it requires 3 days instead of weeks. While the theoretical base of the procedure in this paper is similar to previously published particle velocity based procedure, here the measurement protocol has now been simplified dramatically, which has reduced the measurement time even more to less than a day. The method and its implementation are explained in the paper and a full measurement procedure is reported.

Leakage ranking of vehicle cabin interiors is an important quality index for a car. Noise transmission through weak areas has an important role in the interior noise of a car. Nowadays the acoustic leakage inside a cabin can be measured with different techniques: Microphone array-based holography, Trasmission loss measurement, Beamforming analysis, Sound intensity P-P measurements and ultrasound waves measurements. Some advantages and limits of those measurement approaches for quantifying the acoustic performance of a car are discussed in the first part of this paper. In the second part a new method for fast leakage detection and stationary noise mapping is presented using the Microflown PU probe. This method is called Scan & Paint. The Microflown sensor can measure directly the particle velocity which in the near field is much less affected by background noise and reflection compared with normal microphones.

There are several methods to capture and visualize the acoustic properties in the vicinity of an object. This article considers scanning PU probe based sound intensity and particle velocity measurements which capture both sound pressure and acoustic particle velocity. The properties of the sound field are determined and visualized using the following routine: while the probe is moved slowly over the surface, the pressure and velocity are recorded and a video image is captured at the same time. Next, the data is processed. At each time interval, the video image is used to determine the location of the sensor. Then a color plot is generated. This method is called the Scan and Paint method. Since only one probe is used to measure the sound field the spatial phase information is lost. It is also impossible to find out if sources are correlated or not. This information is necessary to determine the sound pressure some distance from the source, at the driver's ear for example.

The interior noise of a car is a general quality index for many OEM manufacturers. A reliable method for sound source ranking is often required in order to improve the acoustic performance. The final goal is to reduce the noise at some positions inside the car with the minimum impact on costs and weight. Although different methodologies for sound source localization (like beamforming or p-p sound intensity) are available on the market, those pressure-based measurement methods are not very suitable for such a complex environment. Apart from scientific considerations any methodology should be also “friendly” in term of cost, time and background knowledge required for post-processing. In this paper a novel approach for sound source localization is studied based on the direct measurement of the acoustic particle velocity distribution close to the surface. An airborne transfer path analysis is then performed to rank the sound pressure contribution from each sound source.