Papers by Author: Abdul Lennie

Abstract: This paper presents a relative study on variable amplitude (VA) strain data distribution using the approach of probability density function (PDF) and power spectral density (PSD). PDF is a technique to identify the probability of the value falling within a particular interval, and a PSD is to measure the power of a signal by converting it from the time domain to the frequency domain. The objective of this study is to observe the applicability of both techniques in detecting the pattern behaviour in terms of energy and probability distribution. For this reason, a set of case study data consist of nonstationary VA pattern with a random behaviour was used. This kind of data was measured by fixing a strain gauge that connected to the strain data acquisition on the lower suspension arm of a mid-sized sedan car. The data was measured for 60 seconds at the sampling rate of 500 Hz, which gave 30,000 discrete points. The distribution of collected data was then calculated and analysed in the form of both PDF and PSD, and they were then compared for further analysis. The findings from this study are expected for determining the pattern behaviour that exists in VA strain signals.

Abstract: A durability related analysis has been performed using a new statistical-based method, called the Hybrid Integrated Kurtosis-based Algorithm for Z-notch filter (Hybrid I-kaz) Technique. This method provides a two dimensional graphical representation of the signal amplitude and the Hybrid I-kaz coefficient that were used to measure the degree of data scattering. For validation purposes, road tests have been conducted in order to measure the strain and vibration signals on a coil spring. Three road surfaces were used for the road test and data collection purposes. This study used test signals which excited based on three different road surfaces. The 5-mm strain gauge and an accelerometer were fixed on the outer surface of the coil spring for measuring the variable amplitude strain loadings together with the vibration response. The time domain strain and vibration signals were then analysed using global signal statistics and Hybrid I-kaz coefficients. Finally, it was found that the respective coefficients for each signals showed an increment with the total value of strain range and vibration amplitudes.

Abstract: 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.