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Asynchronous motors are frequently used in many industrial applications, especially pumps and fans. Placement, bearing and coupling faults are common faults in these types of engines. Misalignment error is a common type of error that is seen very often among these errors. This error may cause efficiency decrease in a short run and vibration may cause short circuit and wear in moving parts in the stator windings in a long run. Early diagnosis of such faults is important in terms of machine health and productivity. In this study, loose connection and angular imbalance of the asynchronous machine were investigated. In the experimental works, a 1 Phase 0.75 KW power asynchronous motor, Y-0036-024A Electromagnetic Brake and SKF Microlog vibration meter were used during the measurements. The Frequency components of motor caused by the settlement errors were investigated under the different loads. A loose assembly error and angular imbalance were investigated from the misalignment errors. The engine was run idle and without any positioning errors and measurements were taken from different points with the accelerometer and the frequency spectrum examined. Measurements are repeated when the misalignment errors are occurred on purpose and the FFT frequency components were compared under the load of 12.50Nm using magnetic brake. The results show that the FFT frequency components are examined and the placement error can be determined with high success and accuracy. It has been found that harmonic components are formed in the frequency spectrum at 25Hz Coefficients. After the settlement error is generated it is seen that, undesired frequency components that are unloaded are lowered under load when the frequency spectra is examined. In this study, theoretical and experimental comparisons of settlement errors are made. Although many errors in this subject are examined in the same publication in general, only the results of the settlement errors are examined specifically as a contribution to the literature. The results and graphs are presented comparatively to the reader's knowledge.

Misalignment fault detection by wavelet analysis of vibration signals