Prognostic and health management (PHM) monitors machine health and detects anomalies in the early stages to reduce down time. The vibration signals are calculated and turned to feature values such as FFT, RMS, and peak-to-peak. The change of feature values is key to anomaly detection. Therefore, by analyzing the trend and the level of the feature values, the machine health can be evaluated. In order to implement PHM solutions, users will need high-speed data acquisition modules integrated with vibration sensors to acquire the vibration signals and users will also need the computing capability to calculate the feature values. After getting the data, users will need the insight and algorithm to analyze the feature values and determine the machine health. If any sign shows that an anomaly has or may occur, users will receive an alarm notification.