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A Diagnosis Feature Space For Condition Monitoring And Fault Diagnosis Of Ball Bearings, Ali Kahirdeh
A Diagnosis Feature Space For Condition Monitoring And Fault Diagnosis Of Ball Bearings, Ali Kahirdeh
LSU Master's Theses
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 …
Nonlinear Data Driven Techniques For Process Monitoring, Michael C. Thomas
Nonlinear Data Driven Techniques For Process Monitoring, Michael C. Thomas
LSU Master's Theses
The goal of this research is to develop process monitoring technology capable of taking advantage of the large stores of data accumulating in modern chemical plants. There is demand for new techniques for the monitoring of non-linear topology and behavior, and this research presents a topological preservation method for process monitoring using Self Organizing Maps (SOM). The novel architecture presented adapts SOM to a full spectrum of process monitoring tasks including fault detection, fault identification, fault diagnosis, and soft sensing. The key innovation of the new technique is its use of multiple SOM (MSOM) in the data modeling process as …