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Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

Engine acoustics measured by microphones near the engine have been used in controlled laboratory settings for combustion feedback and even combustion phasing control, but the use of these techniques in a vehicle where many other noise sources exist is problematic. In this study, surface-mounted acoustic emissions sensors are embedded in the block of a 2.0L turbocharged GDI engine, and the signal is analyzed to identify useful feedback features. The use of acoustic emissions sensors, which have a very high frequency response and are commonly used for detecting material failures for health monitoring, including detecting gear pitting and ring scuffing on test stands, enables detection of acoustics both within the range of human hearing and in the ultrasonic spectrum. The high-speed acoustic time-domain data are synchronized with the crank-angle-domain combustion data to investigate the acoustic emissions response caused by various engine events.

The Kalman and Vold-Kalman order tracking filters have been implemented in commercial software since the early 90's. There are several mathematical formulations of filters that have been implemented by different software vendors. However, there have not been any papers that have been published which sufficiently explain the math behind these filters and discuss the actual implementations of the filters in software. In addition, upon generating the equations represented by these filters, solving the equations for datasets in excess of several hundred thousand datapoints is not trivial and has not been discussed in the literature. The papers which have attempted to cover these topics are generally vague and overly mathematically eloquent but not easily understandable by a practicing engineer.

The objective of this study was to identify and gain an understanding of the origins of noise in a commercial excavator cab. This paper presents the results of two different tests that were used to characterize the vibration and acoustic characteristics of the excavator cab. The first test was done in an effort to characterize the vibration properties of the cab panels and their associated contribution to the noise level inside the cab. The second set, of tests, was designed to address the contribution of the external airborne noise produced by the engine and hydraulic pump to the overall interior noise. This paper describes the test procedures used to obtain the data for the signature analysis, operational deflection shapes (ODS), and sound diagnosis analysis. It also contains a discussion of the analysis results and an inside look into the possible contributors of key frequencies to the interior noise in the excavator cab.

Sensory jury testing was utilized to characterize vibration levels perceived by the operator, with respect to levels measured using instrumentation, in order to develop a tool for the evaluation of vibration at the operator interfaces. Details of the jury testing and jury data processing method are highlighted as well as the refinement of vibration characterization for a specific application. The vibration at user interface locations of both snowmobiles and ATVs was measured along with subjective feedback from a panel of jurists. Statistical analysis was performed on the jury data to provide both a qualitative and quantitative number to represent the opinion of the jury. Correlations were developed between the measured levels of vibration and the opinions of the jury. Finally, a set of correlation functions suitable for design predictions was developed.

Rear Window Buffeting (RWB) is the low-frequency, high amplitude, sound that occurs in many 4-door vehicles when driven 30-70 mph with one rear window lowered. The goal of this paper is to demonstrate that the mechanisms of RWB are similar to that of sun roof buffeting and to describe the results of several actions suspected in contributing to the severity of RWB. Finally, the results of several experiments are discussed that may lend insight into ways to reduce the severity of this event. A detailed examination of the side airflow patterns of a small Sport Utility Vehicle (SUV) shows these criteria exist on a small SUV, and experiments to modify the SUV airflow pattern to reduce RWB are performed with varying degrees of success. Based on the results of these experiments, design actions are recommended that may result in the reduction of RWB.

This paper describes a study to demonstrate the feasibility of developing an acoustic encapsulation to reduce airborne noise from a commercial diesel engine. First, the various sources of noise from the engine were identified using Nearfield Acoustical Holography (NAH). Detailed NAH measurements were conducted on the four sides of the engine in an engine test cell. The main sources of noise from the engine were ranked and identified within the frequency ranges of interest. Experimental modal analysis was conducted on the oil pan and front cover plate of the engine to reveal correlations of structural vibration results with the data from the NAH. The second phase of the study involved the design and fabrication of the acoustical encapsulation (noise covers) for the engine in a test cell to satisfy the requirements of space, cost and performance constraints. The acoustical materials for the enclosure were selected to meet the frequency and temperature ranges of interest.

The objective of this study was to utilize Statistical Energy Analysis (SEA) to simulate the effects of a variety of noise control treatments on the interior sound pressure level (SPL) of a commercial excavator cab. In addition, the effects of leaks on the SPL of the excavator cab were also investigated. This project was conducted along with various tests that were used to determine the inputs needed to accurately represent the loads that the cab experienced during operation. This paper explains the how the model was constructed, how the loads were applied to the model, the results that were obtained from application of treatments, and a study of the effects of introducing leaks to the cab structure in the SEA model.

The classical methods of measuring acoustic absorption coefficient using an impedance tube and a reverberation chamber are well established [1, 2]. However, these methods are not suitable for in-situ applications. The two in-situ methods; single channel microphone (P- probe) and dual channel acoustic pressure and particle velocity (Pu-probe) methods based on measurement of impulse response functions of the material surface under test, provide considerable advantage in data acquisition, signal processing, ease and mobility of measurement setup. This paper evaluates the measurement techniques of these two in-situ methods and provides results of acoustic absorption coefficient of a commercial artificial Astroturf, a Dow quash material, and a grass surface.

The Time Variant Discrete Fourier Transform was implemented as a real-time order tracking method using developed software and commercially available hardware. The time variant discrete Fourier transform (TVDFT) with the application of the orthogonality compensation matrix allows multiple tachometers to be tracked with close and/or crossing orders to be separated in real-time. Signal generators were used to create controlled experimental data sets to simulate tachometers and response channels. Computation timing was evaluated for the data collection procedure and each of the data processing steps to determine how each part of the process affects overall performance. Many difficulties are associated with a real-time data collection and analysis tool and it becomes apparent that an understanding of each component in the system is required to determine where time consuming computation is located.

As noise concerns for snowmobiles become of greater interest for governing bodies, standards such as SAE J192 are implemented for regulation. Specific to this pass-by noise standard, and unlike many other pass-by tests, multiple non-standardized test surfaces are allowed to be used. Manufacturers must understand how the machines behave during these tests to know how to best improve the measured noise levels. Data is presented that identifies the contributions of different sources for different snowmobiles on various test surface conditions. Adaptive resampling for Doppler removal, frequency response functions and order tracking methods are implemented in order to best understand what components affect the overall measurement during the pass-by noise test.

Restrictions on noise and gaseous emissions of snowmobiles have been a topic of much attention for the past decade. Concerns with snowmobiles in our national parks and with private land owners have resulted in new park legislations as well as legal disputes regarding recreational vehicle rights-of-way. The most widely used standard for snowmobile testing is SAE J192 Exterior Sound Level for Snowmobiles, SAE Recommended Practice. This is a wide-open throttle test with sound level meters 50 feet on either side of the snowmobile. The sound pressure cannot exceed a certain level for the snowmobile to pass. Perceived noise also plays an important role in the objections to snowmobiles. This paper considers the role of Sound Quality methods, specifically Jury Analysis, in understanding the difference between objective noise analysis and subjective noise preferences; also considering the underlying snowmobile attributes that control snowmobile noise.

The objective of this project was to model and study the interior noise in an Off-Highway Truck cab using Statistical Energy Analysis (SEA). The analysis was performed using two different modeling techniques. In the first method, the structural members of the cab were modeled along with the panels and the interior cavity. In the second method, the structural members were not modeled and only the acoustic cavity and panels were modeled. Comparison was done between the model with structural members and without structural members to evaluate the necessity of modeling the structure. Correlation between model prediction of interior sound pressure and test data was performed for eight different load conditions. Power contribution analysis was performed to find dominant paths and 1/3rd octave band frequencies.

Performing acoustic measurements on or near engines, transmissions, as well as in other circumstances where the environment is hazardous and harsh for microphones requires special precautions. Fluids inevitably leak, and the possibility of transducer damage can be very high without proper protection. Properly protecting microphones during testing allows for consistent data quality in these hazardous and difficult environments. While this paper will present the use of a 5 mil Nitrile cover which protects against many fluids within the scope of automotive testing, including water, hydrocarbons, and alcohols, as well as having good heat resistance and high strength, the concepts developed are applicable to other types of microphone protective mechanisms. Acoustic sensitivity was measured and used to calculate the change of the microphone's response after the treatment is applied, as well as after being exposed to various contaminants.

The successful implementation of a clean, quiet, four-stroke engine into an existing snowmobile chassis has been achieved. The snowmobile is easy to start, easy to drive, and environmentally friendly. The following paper describes the conversion process in detail with actual dynamometer and field test data. The vehicle is partially compliant with the proposed 2010 EPA snowmobile emissions regulations and passes an independently conducted, 74 dBA, full throttle pass-by noise test. The vehicle addresses the environmental issues surrounding snowmobiles and remains economical, with an approximate cost of $6,345.

Compared to moving coil loudspeakers, carbon nanotube (CNT) loudspeakers are extremely lightweight and are capable of creating sound over a broad frequency range (1 Hz to 100 kHz). The thermoacoustic effect that allows for this non-vibrating sound source is naturally inefficient and nonlinear. Signal processing techniques are one option that may help counteract these concerns. Previous studies have evaluated a hybrid efficiency metric, the ratio of the sound pressure level at a single point to the input electrical power. True efficiency is the ratio of output acoustic power to the input electrical power. True efficiency data are presented for two new drive signal processing techniques borrowed from the hearing aid industry. Spectral envelope decimation of an AC signal operates in the frequency domain (FCAC) and dynamic linear frequency compression of an AC signal operates in the time domain (TCAC). Each type of processing affects the true efficiency differently.

When a manual transmission (MT) powertrain is subjected to high speeds and high torques, the vehicle driveshaft, and other components experience an increase in stored potential energy. When the engine and driveshaft are decoupled during an up or down shift, the potential energy is released causing clunk during the shift event. The customer desires a smooth shift thus reduction of clunk will improve experience and satisfaction. In this study, a six-speed MT, rear-wheel-drive (RWD) passenger vehicle was used to experimentally capture acoustic and vibration data during the clunk event. To replicate the in-situ results, additional data was collected and analyzed for powertrain component roll and pitch. A lumped parameter model of key powertrain components was created to replicate the clunk event and correlate with test data. The lumped parameter model was used to modify clutch tip-out parameters, which resulted in reduced prop shaft oscillations.

In this paper, two correlations, Windowed Selected Moving Autocorrelation (WSMA) and Tri-Correlation (TriC), are introduced and discussed. The WSMA is simpler than the conventional autocorrelation. WSMA uses less data points to obtain useful signal content at desired frequencies. The computational requirement is therefore reduced compared to the conventional autocorrelation. The simplified TriC provides improved signal to noise separation capability than WSMA does while still requiring reduced computational effort compared to the standard autocorrelation. Very often, computation resource limitation exists for real-time applications. Therefore, the WSMA and TriC offer more opportunities for real-time monitor and feedback control applications in the frequency domain due to their high efficiencies. As an example, applications in internal combustion (IC) engine misfire detection are presented. Simulation and vehicle test results are also presented in this paper.

We present techniques of symbolic time-series analysis which are useful for analyzing temporal patterns in dynamic measurements of engine combustion variables. We focus primarily on techniques that characterize predictability and the occurrence of repeating temporal patterns. These methods can be applied to standard, cycle-resolved engine combustion measurements, such as IMEP and heat release. The techniques are especially useful in cases with high levels of measurement and/or dynamic noise. We illustrate their application to experimental data from a production V8 engine and a laboratory single-cylinder engine.

A study was performed to understand how the environment affects the results of J-192 pass-by noise testing of snowmobiles. This study involved measuring the sound pressure at 7 different microphone positions due to both speaker excitation and various snowmobiles passing through the microphone array. Simultaneous to the sound measurements, weather conditions were recorded including wind speed and direction, temperature, humidity, snow depth, and in some cases ground hardness. All measured data was then used to determine which environmental factors influenced the measured sound pressures the most. Finally, a sound power approach was also used to measure the snowmobile pass-by noise to determine whether this method was more repeatable than the single microphone approach which showed variations of over 7 dBA over the course of testing.