Post-Processing Analysis of Large Channel Count Order Track Tests and Estimation of Linearly Independent Operating Shapes

Large channel count data acquisition systems have seen increasing use in the acquisition and analysis of rotating machinery, these systems have the ability to generate very large amounts of data for analysis. The most common operating measurement made on powertrains or automobiles on the road or on dynamometers has become the order track measurement. Order tracking analysis can generate a very large amount of information that must be analyzed, both due to the number of channels and orders tracked. Analysis methods to efficiently analyze large numbers of Frequency Response Function (FRF) measurements have been developed and used over the last 20 years in many troubleshooting applications. This paper develops applications for several FRF based analysis methods as applied for efficient analysis of large amounts of order track data. Post-processing analysis methods are developed to generate order track autopowers, track order track based operating shapes, and generate virtual measurements and operating shapes.

A virtual measurement is formulated that enhances and identifies where in a speed sweep a particular virtual operating shape is excited, this virtual measurement is referred to as a Mode Enhanced Order Track. An analysis technique is also developed which has the ability to estimate linearly independent operating shapes from a set of operating shapes excited by different orders, this technique is based on the CMIF parameter estimation used in modal analysis. The estimated linearly independent operating shapes are especially useful in trouble shooting applications where there are several components rotating at nearly the same speeds, as in the wheels of an automobile.

Examples of the use of these techniques are presented based on both analytical and experimentally acquired automotive data.