A survey on statistical indexes applied on frequency response analysis of electric machinery and a trend based approach for more reliable results

• Statistical indexes add more objectivity to FRA results.
• A review of statistical indexes applied to FRA is presented.
• External factors such as temperature and humidity may induce to wrong diagnosis.
• A trend based approach is proposed to mitigate external influence on diagnosis.

This work presents some guidelines in order to achieve a more reliable diagnosis using the frequency response analysis (FRA) technique. Conventionally, this technique relies on comparisons between spectra obtained at different stages of the machine lifespan. A difference between the spectra may indicate the onset of a failure. However, these comparisons are very subjective to the experience of the analyst. To achieve a more objective diagnosis, statistical indexes have been introduced in the literature of FRA. This work presents a survey on these indexes and also compares them using experimental data. Another contribution of this work is the proposition of a trend based diagnostics. Thus, even if the FRA measurements are obtained at different temperatures/humidity or other external factors, the trend curve of the indexes is able to provide a more reliable diagnosis.