A Diagnosis Feature Space for Condition Monitoring and Fault Diagnosis of Ball Bearings

The problem of fault diagnosis and condition monitoring of ball bearings is a multidisciplinary subject. It involves research subjects from diverse disciplines of mechanical engineering, electrical engineering and in particular signal processing. In the first step, one should identify the correct method of investigation. The methods of investigation for condition monitoring of ball bearings include acoustic emission measurements, temperature monitoring, electrical current monitoring, debris analysis and vibration signal analysis. In this thesis the vibration signal analysis is employed. Once the method of analysis is selected, then features sensitive to faults should be calculated from the signal. While some of the features may be useful for condition monitoring, some of the calculated features might be extra and may not be helpful. Therefore, a feature reduction module should be employed. Initially, six features are selected as a candidate for the diagnosis feature space. After analyzing the trend of the features, it was concluded that three of the features are not appropriate for fault diagnosis. In this thesis, two problem is investigated. First the problem of identifying the effects of the fault size on the vibration signal is investigated. Also the performance of the feature space is tested in distinguishing the healthy ball bearings from the defective vibration signals

Energy Dissipation and Entropy Generation During the Fatigue Degradation: Application to Health Monitoring of Composites

In this dissertation, an experimental approach for characterizing energy dissipation and degradation evolution in a woven Epoxy/Glass (G10/FR4) laminate subjected to fully reversed bending fatigue test is presented. Infrared thermography and acoustic emission are utilized to characterize the degradation progression. The results show similar evolutionary response indicating the presence of three degradation stages. The effect of the surface cooling on the fatigue life of the laminates is investigated both experimentally and analytically. The results show that the life of the laminate is highly dependent on the temperature and that surface cooling can significantly increase the fatigue life of the laminate. The signatures of acoustic emission (AE) response emanating from laminates are studied. The distribution of the cumulative AE amplitude is described by a power law. Examination of the evolution of the probability density function (PDF) of the AE energy (counts) reveals two scaling zones wherein the transition from the low energy (count) to high energy (count) regime is identified. The low-energy phase represents very low damage state of the laminate characterized by a power law. The AE energy release and counts follow the statistics and power laws that do not depend on the operational conditions. A fatigue damage detection method for the laminates based on the cumulative information entropy is reported. The cumulative entropy demonstrates a persistent trend of nonlinear damage evolution typically observed in the experimental measures of the damage in composite materials. In this dissertation, a continuum formulation for irreversible energy dissipation that accounts for generated acoustic emissions during the loading of the materials is also developed. The evolution of the dissipative energy for AL6061 specimens is experimentally measured as the material is degraded. A statistically similar behavior is observed in different forms of the dissipated energy as the material degrade. Finally, a damage detection method for detection of wear in thrust ball bearings coated with molybdenum disulphide (MoS2) is presented. It employs an energy feature obtained from time-frequency representation of the vibration signal. Extensive experimental studies are conducted to verify the efficacy of the proposed method for fault diagnosis of MoS2 coating

Acoustic Entropy of the Materials in the Course of Degradation

We report experimental observations on the evolution of acoustic entropy in the course of cyclic loading as degradation occurs due to fatigue. The measured entropy is a result of the materials’ microstructural changes that occur as degradation due to cyclic mechanical loading. Experimental results demonstrate that maximum acoustic entropy emanating from materials during the course of degradation remains similar. Experiments are shown for two different types of materials: Aluminum 6061 (a metallic alloy) and glass/epoxy (a composite laminate). The evolution of the acoustic entropy demonstrates a persistent trend over the course of degradation

Damage Assessment Using Information Entropy of Individual Acoustic Emission Waveforms during Cyclic Fatigue Loading

Information entropy measured from acoustic emission (AE) waveforms is shown to be an indicator of fatigue damage in a high-strength aluminum alloy. Three methods of measuring the AE information entropy, regarded as a direct measure of microstructural disorder, are proposed and compared with traditional damage-related AE features. Several tension–tension fatigue experiments were performed with dogbone samples of aluminum 7075-T6, a commonly used material in aerospace structures. Unlike previous studies in which fatigue damage is measured based on visible crack growth, this work investigated fatigue damage both prior to and after crack initiation through the use of instantaneous elastic modulus degradation. Results show that one of the three entropy measurement methods appears to better assess the damage than the traditional AE features, whereas the other two entropies have unique trends that can differentiate between small and large cracks