Papers by Author: Zulkifli Mohd Nopiah

Abstract: Various condition monitoring techniques were applied during a laboratory engine test in order to understand the wear processes occurring and to determine a suitable method which could be applicable to the detection and diagnosis of abnormal engine condition in practice. The goal of the research presented in this study is to monitor the internal combustion engine block. The proposed engine block approach is based on measuring and monitoring the engine operation in variable speed and torque using Piezoelectric Sensor. However, it normally requires analyzing the obtained signal for providing valuable information. This research involves two main procedures including data collecting as well as data analyzing. Data collecting is processes of sensor attach, run the engine and record the data while data analyzing is translating the data using data acquisition and filtering by fast furrier transform and analyzing by I-kaz and MZN methods.

Abstract: This paper presents the comparative study on three types of fatigue data editing technique for summarising long records of fatigue data. Two of techniques were developed based on timefrequency domain (continous wavelet and discrete wavelet) and another one technique was developed based on time domain. These three techniques are used to extract fatigue damaging events in the record that cause the majority of fatigue damage, whilst preserving the load cycle sequence in the data. The objective of this study is to observe the capability of each technique in summarising long records of fatigue data. For the purpose of this study, two set of nonstationary data that exhibits random behaviour was used. This random data was measured in microstrain unit on the SAE1045 material that were used as a lower suspension arm of a car. Experimentally, the data was collected for 60 seconds at sampling rate of 500Hz, which gave 30, 000 discrete data points. The result of the study indicates that all techniques are applicable in detecting and extracts fatigue damaging events that exist in the fatigue data. However, it was found that continous wavelet can extract the data better than the other technique based the shorten signals, retention of damage and statistical parameter.