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The most damaging events controlling the low cycle fatigue life of a mechanical component are typically characterized by a relatively few, large amplitude, low frequency loadings where, for this paper, signals below 60 to 100Hz are considered low frequency. These are usually accompanied by a large number of small amplitude, high frequency loadings that may contribute little or no damage and often are merely a measure of system noise. Over sampling by factors of five to ten relative to the sampling theorem is often recommended to achieve the time domain resolution necessary for an accurate capture of peaks and valleys used in component fatigue evaluation. This over sampling limits the elapsed time capacity of digital recording devices used for field tests, slows data transfer rates, and expands database storage requirements.

The use of Kalman filter methods for high-performance order tracking of noise and vibration signals was introduced in 1993. Based on experience with that original formulation, further work has produced significant enhancements which greatly extend the ability of these methods to deal with several practical issues of concern in vehicle testing. This paper reports on advances in the areas of: RPM estimation accuracy, even for fast-changing events such as gear shifts; Higher order Kalman filters, with improved shapes for extracting modulated orders; Decoupling of close and even crossing orders by use of multiple RPM references; Significant speed improvement over the original algorithm. Besides obtaining the magnitude and phase of selected orders as a function of time or RPM, the harmonic content may be extracted as time-histories, with no phase or leakage distortion.