In any experiment, there is a need to verify the reliability of the collected data. One of the solutions is to measure the data repetitively. It will lead to measurement of inconsistency that exists in the data. Similar things also happen in variable amplitude (VA) loading strain data collection where the data also need to be measured repetitively in order the collected data is reliable. The main objective of this study is to validate the reliability of collected VA loading strain data. Two techniques will be used for identifying the similarity in the pattern for strain signal which was measured repetitively. The probability distribution function (PDF) and power spectral density (PSD) diagrams of the strain data were used as the main tool to construct profile plots for the case study data. Then, each profile plot will be compared to each other in order to identify any similarities that exist in the case study data. For the purpose of the study, a set of nonstationary VA loadings strain data that exhibits random behaviour was used. This random data was measured in the unit of microstrain on the lower suspension arm of a car. The data was repetitively measured for 60 seconds at the sampling rate of 500Hz, giving 30,000 discrete data points. The distribution of the collected data was analysed using the PDF and PSD. Based on the analysis, it was found that PSD can produce better results at identifying the similar features that exist in the profile plot compared to PDF.