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A manual task can be performed based on alternative movement techniques. Ergonomic human motion simulation requires consideration of alternative movement techniques, because they could bring different biomechanical, physiological, and psychophysical consequences. A method for identifying movement techniques from existing motion data was developed. The method is based on a JCV (Joint Contribution Vector) index and statistical clustering. A JCV quantifies a motion's underlying movement technique by computing contributions of individual body joint DOFs (degree-of-freedom) to the achievement of the task goal. Given a set of motions (motion capture data) achieving the same or similar task goals, alternative movement techniques can be identified by 1) representing the motions in terms of JCV and 2) performing a statistical clustering analysis. Performance of this movement technique identification method was evaluated based on a set of stoop and squat lifting motions.

An experimental method to identify damping characteristics of a dynamic system is reported. The method identifies damping matrices of the equation of motion of the system from measured frequency response functions, each different damping mechanism in a distinct matrix. Related experimental techniques and signal processing issues are discussed. Theoretical validation and error study are conducted by applying the method to a theoretical example. The method is applied experimentally to a thin beam with two different damping characteristics for experimental validation and demonstration of the method. Important advantages of the method over existing methods are explained.

In highly reverberant enclosures, the identification of noise sources is a difficult and time consuming task. One effective approach is the Inverse Frequency Response Function (IFRF) method. This technique uses the inverse of an acoustic FRF matrix, that when multiplied by operating pressure response data reveals the noise source locations. Under highly reverberant conditions the deployment of a sound absorbing body is especially useful in reducing the effects of resonant modes that obscure important information in the FRFs. Without the absorption, the IFRF method becomes practically difficult to perform in these environments due to poor conditioning of the FRF matrix. This study investigates the feasibility of using Boundary Element and Finite Element Methods to establish the frequency response functions between selected panel points and microphones in the array.

As the drive to make automobiles more noise and vibration free continues, it has become necessary to analyze transient events as well as periodic and random phenomena. Averaging of transient events requires a repeatable event as well as an available trigger event. Knowing the exact event time, the data can be post-processed by re-sampling the time scale to capture the recorded event at the proper instant in time to allow averaging. Accurately obtaining the event time is difficult given the sampling restrictions of current data acquisition hardware. This paper discusses the ideal hardware needed to perform this type of analysis, and provides analytical examples showing the transient averaging improvements using time scale re-sampling. These improvements are applied to noise source identification of a single transient event using an arrayed microphone technique. With this technique, the averaging is performed using time delays between potential sources and microphones in the array.

Acoustic array techniques are presented as alternatives to intensity measurements for source identification in automotive and industrial environments. With an understanding of the advantages and limitations described here for each of the available methods, a technique which is best suited to the application at hand may be selected. The basic theory of array procedures for Nearfield Acoustical Holography, temporal array techniques, and an Inverse Frequency Response Function technique is given. Implementation for various applications is discussed. Experimental evaluation is provided for tire noise identification.