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A significant challenge in successful implementation of large channel count dynamic test systems, like multi-channel modal systems, has been efficient and error free test set-up and data collection. Newly developed instrumentation that digitally communicates self-identifying information (including transducer type and serial number, calibration value and physical location) greatly enhances system performance and drastically reduces the opportunity for human documentation errors. Sensors featuring this Transducer Electronic Data Sheet (TEDS, consistent with the impending IEEE P1451.4 standard), in addition to such techniques as sonic digitization for geometry definition and automated data acquisition with computer controlled, bank switching signal conditioners are continually improving accuracy and reducing the per channel price of multi-channel dynamic test systems.

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.