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A key element to bring research advances on intelligent materials to industrial use is that the product CAE models must support such solutions. This involves modeling capabilities for intelligent material systems, sensor and actuator components, control systems as well as their integration in system-level application designs. The final result will then be a multi-attribute optimization approach integrating noise and vibration performance with reliability, durability and cost aspects. As no single integrated solution will fulfill all requirements of the various material and control approaches, the focus of the research is on the use, combination and extension of existing codes and tools.

Despite the fact that Transfer Path Analysis (TPA) is a well known and widely used NVH tool it still has some hindrances, the most significant being the huge measurement time to build the full data model. For this reason the industry is constantly seeking for faster methods. The core concepts of a novel TPA approach have already been published in a paper at the ISMA 2008 Conference in Leuven, Belgium. The key idea of the method is the use of parametric models for the estimation of loads. These parameters are frequency independent as opposed to e.g. the classical inverse force identification method where the loads have to be calculated separately for each frequency step. This makes the method scalable, enabling the engineer to use a simpler model based on a small amount of measurement data for quick troubleshooting or simply increase accuracy by a few additional measurements and using a more complex model.

Experimental identification of structural dynamics models is usually based on the modal analysis approach. In the classical modal parameter estimation approach, the baseline data which are processed are Frequency Response Functions measured in laboratory conditions. However, in many applications, the real operating conditions may differ significantly from those applied during the modal test. Hence, the need arises to identify a modal model in operational conditions. This issue is even more complicated by the fact that in most cases, only response data are measurable while the actual loading conditions are unknown. Therefore, the system identification process will need to base itself on output-only data.

Since its first publication in the beginning of the eighties, Transfer Path Analysis (TPA) has evolved into a widely used tool for noise and vibration troubleshooting and internal load estimation, and this for single source as well as multivariate problems. One of the main bottlenecks preventing its even more widespread use in the actual vehicle development process is the test time to build the full data model, requiring not only in-operation tests but also extensive Frequency Response Function tests. As a consequence, several new approaches have appeared over the past years attempting to circumvent this limitation, such as Fast and Multilevel TPA and Operational TPA. The latter method attracts quite some attention as it only requires operational data measured at the path references and target locations.

15 years of NVH applications make Transfer Path Analysis (TPA) appear a commodity tool. But despite the fact that TPA is today successfully used in a large variety of applications in automotive and mechanical industries, its main bottleneck remains the huge measurement time to build the full TPA model. This paper presents a new TPA method that provides a good compromise between path accuracy and measurement time. The method is also referred to as OPAX. The key idea of OPAX is the use of simplified parametric load models with limited number of model parameters. The main advantage of this is that one should measure only a small amount of FRF data to identify the operational loads. This drastically reduces measurement time and efforts. In addition to this, the OPAX method does not require mount stiffness data and allows a simultaneous identification of structural and acoustic paths.

Traditionally, vibration analysis in operating conditions (on the road or on a bench) had to be combined with experimental modal analysis in controlled laboratory conditions in order to understand the modal behaviour of the structure. This requires additional measurements, costs and time. However, in many applications, the real operating conditions may differ significantly from those applied during the modal test and hence the vibration modes from the modal test might not be representative for the active modes in operation conditions. The need for a capability of doing a modal analysis on data from operating conditions is obvious. Over the last years, several modal parameter estimation techniques have been proposed and studied for modal parameter extraction from output-only data. Each method needs to make a number of assumptions and has some limitations.

One of the scientific fields where, for already more than 20 years, system identification plays a crucial role is this of structural dynamics and vibro-acoustic system optimization. The experimental approach is based on the “Modal Analysis” concept. The present paper reviews the test procedure and system identification principles of this approach. The main focus though is on the real problems with which engineers, performing modal analysis on complex structures on a daily basis, are currently confronted. The added value of several new testing approaches (laser methods, smart transducers…) and identification algorithms (spatial domain, subspace, maximum likelihood,..) for solving these problems is shown. The discussed elements are illustrated with a number of industrial case studies.

This paper presents a new time-domain source contribution analysis method for in-room pass-by noise. The core of the method is a frequency-domain ASQ model (Airborne Source Quantification) representing each noise generating component (engine, exhaust, left and right tyres, etc.) by a number of acoustic sources. The ASQ model requires the measurement of local FRF's and acoustic noise transfer functions to identify the operational loads from nearby pressure indicator responses and propagate the loads to the various target microphones on the sides of the vehicle. Once a good ASQ model is obtained, FIR filters are constructed, allowing a time-domain synthesis of the various source contributions to each target microphone. The synthesized target response signals are finally recombined into a pass-by sound by taking into account the speed profile of the vehicle.

Acoustic performance of vehicle engines is a real challenge for powertrain design engineers. Quiet engines are required to reduce noise pollution and satisfy pass-by noise regulations, but also to improve the driving comfort. Simulation techniques such as the Boundary Element Method (BEM) have already been available for some time and allow predicting the vibro-acoustic response of engines. Although the accuracy of these simulation techniques has been proven, a challenge still remains in the required computation time. Given the large amount of speeds for a full engine run-up and the need to cover a large frequency range, computation times are significant, which limits the possibility to perform many design iterations to optimize the system. In 2001, Acoustic Transfer Vectors (ATV) [1] have been presented to adequately deal with multiple rpm. The ATV provide the acoustic response for unit surface velocities and are therefore independent from the engine's actual surface vibrations.

This paper discusses a road noise analysis application on a passenger car. It involves a study of the interior noise in the car, which is explained in function of the energy transfer paths from the suspension into the car body. For this, multiple reference transfer path analysis is used. A link is made between specific characteristics of this energy transfer and the operational analysis of the measurements on the suspension during road tests, as well as the acoustical modes of the cavity. The operational data are correlated with modal analysis results on the suspension, explaining certain problems occurring during running condition.

The subjective quality of sounds is a topic of increasing importance in the automotive industry. The first consideration is to describe the perceptual characteristics of this quality by means of jury tests or appropriate metrics. Once a NVH problem is determined in terms of an appropriate Sound Quality description, an in-depth analysis of the underlying physical phenomena must be made and engineering solutions newel to be proposed and validated This involves: • the detailed analysis of the signal structure in the time, frequency and order domain and identifying the signal Components Critical to the relevant sound quality dimension • the Correlation of the critical signal components to specific sources noise or vibration transmission paths and vibro-acoustic system characteristics. Ultimately this should lead to the prediction of the effect of feasible modifications in sound quality terms through the use of engineering models.

Vibro-acoustical optimization of vehicles is a complex task, due to the many interactions that exist between subcomponents and car body in a broad acoustical frequency range. The goal of this paper is to present a view on the different experimental methodologies for vibro-acoustical analysis, that approach the vehicle as a source, transfer and receiver system. This approach focuses on the use of transfer path and source identification techniques, both for structure-borne and air-borne contribution analysis, and on the use of modeling techniques as there are vibro-acoustical modal analysis, FRF based substructuring and experimental statistical energy analysis techniques. It is explained what the main focus is of each of the techniques, where they can be used in the vibro-acoustical optimization process and in which frequency ranges they are useful.

The data measured during an ISO 362 pass-by-noise test are strongly non-stationary due to the fast acceleration of the vehicle and its moving position with respect to the ISO microphone position. Nevertheless, one would like to obtain an understanding of the relative contribution of the various noise generating components during the test. Since the classical signal analysis procedures based on the FFT calculation and auto/crosspower averaging for coherence/correlation analysis are no longer applicable, as they implicitly assume signal (and process) stationarity, an approach based on Autoregressive Vector (ARV) modelling of a set of measurement signals was developed and applied. An ARV model is calculated directly from a set of time data of limited duration.

One of the practical consequences of the development of low CO₂ emission cars is that many of the traditional NVH sound engineering processes no longer apply and must be revisited. Different and new sound sources, new constraints on vehicle body design (e.g., due to weight) and new sound perception characteristics make that the NVH knowledge built on generations of internal combustion-powered vehicles cannot be simply transferred to Hybrid and Electric Vehicles (HEV). Hence, the applicability of tools must be reviewed and extensions need to be developed where necessary. This paper focuses on sound synthesis tools as developed for ICE-powered vehicles. Because of the missing masking effect and the missing intake and exhaust noise of the Internal Combustion Engine (ICE) in electric vehicles, on one hand electric vehicles are quieter than traditional vehicles.

Vehicles with electrified powertrains are being introduced at an increasing pace. On the level of interior sound, one is often inclined to assume that NVH problems in EV have disappeared together with the combustion engine. Three observations demonstrate that this is not the case. First of all, only the dominant engine sound disappears, not the noise from tire, wind or auxiliaries, which consequently become increasingly audible due to the removal of the broadband engine masking sound. Secondly, new noise sources like tonal sounds from the electro-mechanical drive systems emerge and often have, despite their low overall noise levels, a high annoyance rating. Thirdly, the fact that engine/exhaust sounds are often used to contribute to the “character” of the vehicle leads to an open question how to realize an appealing brand sound with EV. Hybrid vehicles are furthermore characterized by mode-switching effects, with impact on both continuity feeling and sound consistency problems.

Aircraft noise modeling aims to provide designers with computational tools that allow exploring the design parameters domain early in the design and development process. A number of modeling techniques are available for acoustics and vibration prediction, but in order to define objective targets for sound quality perception, dedicated tools are still needed to correlate structural models and design modifications with human perception of sounds. This paper presents a model-based sound synthesis concept for interior and exterior aircraft noise that allows interactive, real-time sound reproduction and replay. The proposed approach is presented through two application cases: jet flyover noise and turboprop interior noise.

This paper presents the results of an experimental test campaign carried out on a city bus powered by serial hybrid power train. The driveline system combines an Internal Combustion Engine with a battery pack and two electric motors. Tests were aimed at identifying the salient signal characteristics of the noise spectra recorded during operating conditions and to assess the acoustic comfort in the passenger compartment. Transfer Path Analysis technique was applied to identify airborne and structure borne vibro-acoustic loads, to measure transfer functions linking source locations to target locations and to estimate the internal vibro-acoustic comfort in operating conditions.

The paper will introduce some recent advances in vibration testing and modal analysis of airplanes. Recently, a very promising parameter estimation method became available, that has the potential to become the new standard. The main advantage of this so-called PolyMAX method is that it yields extremely clear stabilization diagrams even for broadband and high-order analyses. The method will be applied to two aircraft cases: a Ground Vibration Test using broadband shaker excitation on a small composite aircraft and in-flight data using natural turbulences as excitation. These two data sets allow illustrating both the classical Frequency Response Function based as well as the operational output-only modal analysis process.

Traditionally, vibration analysis in operating conditions (on the road or on a bench) had to be combined with experimental modal analysis in controlled laboratory conditions in order to understand the modal behaviour of the structure. This requires additional measurements, costs and time. However, in many applications, the real operating conditions may differ significantly from those applied during the modal test and hence the vibration modes from the modal test might not be representative for the active modes in operation conditions. The need for a capability of doing a modal analysis on data from operating conditions is obvious. Over the last years, several modal parameter estimation techniques have been proposed and studied for modal parameter extraction from output-only data. Each method needs to make a number of assumptions and has some limitations.

Certification of vehicle noise emissions for passenger vehicles, motorcycles and light trucks is achieved by measuring external sound levels according to procedures defined by international standards such as ISO362. The current procedure based on a pass-by test during wide-open throttle acceleration is believed far from actual urban traffic conditions. Hence a new standard pass-by noise certification is being evaluated for implementation. It will put testing departments through their paces with requirements for additional testing under multiple ‘real world’ conditions. The new standard, together with the fact that most governments are imposing lower noise emission levels, make that most of the current models do not meet the new levels which will be imposed in the future. Therefor automotive manufacturers are looking for new tools which are giving them a better insight in the Pass-by Noise contributors.