<![CDATA[Rotating machinery is widely used in industry. Rotating machinery is very important, so that defect engine or parts can disturb industrial production process. Faults that are often occured are unbalance, misalignment, looseness, bearing fault, etc. This paper discuss unbalance and looseness fault detection in rotordynamic system with speed of 600, 800, and 1000 cpm. Data collection is conducted using acquisition data with accelerometer sensor attached in vertical direction on house bearing. Vibration signal data is processed with wavelet decomposition method using Matlab 2016. Fault diagnosis is indicate using spectrum. The result show that in unbalance condition, there is a dominant peak at frequency of 1x cpm for all speed variations. While in looseness condition, there is a dominant peak at frequency of 2x cpm for all speed variations. In both conditions, amplitude of signature at each speed variation increase with the rotation speed. It concludes, wavelet decomposition method provide distinct peaks correspond to fault frequency, so that fault detection can be accurately performed.]]>
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