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UBC Theses and Dissertations

Investigating the use of compliance for fault detection in hydraulic machines Pirouz, Zarin


The problem of measuring the compliance of a hydraulic system using flow and pressure measurements was studied to determine if this method could be used to detect faults in mobile heavy-duty hydraulic machines. As a start, previous research that used Genetic Algorithms (GA) for compliance identification in a hydraulic machine and GA principles were studied in detail to determine if using the GA is necessary for compliance identification. Some discrepancies and misconceptions in the previous research were discovered. To eliminate the misconceptions, many elements contributing to the compliance of the machine and obstacles to using pressure and flow measurements in compliance calculation were studied. It was shown that many inter-related elements have to be modeled to be able to interpret the compliance value obtained from pressure and flow measurements in hydraulic machines. Some models believed to be most suitable for fault detection were developed. It was shown that despite the complexity of the elements, as far as fault detection is concerned, the system can be modeled in such a way that in most cases it is linear in the parameters which allows the use of simple identification methods. Experiments were performed on a hydraulic test-bed to examine the suitability of the proposed models. A few unexpected obstacles in using flow and pressure measurement to measure compliance for fault detection were encountered. It was discovered that even small amounts of leak that can be present during normal machine operation may cause enough distortion in flow measurement to overshadow the compliance value. It was also discovered that using flow and pressure measurements in compliance measurement is only possible if very accurate measurements are available. A few practical and simple methods were proposed to cope with these problems and extract useful information from these measurements for fault detection.

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