It is difficult to analyze the raw vibration signals of complex vibrating machines because these signals have complicated patterns. An appropriate preprocessing method has to be applied to enhance the signal resolution. In most cases, these preprocessed data are also difficult to inspect, however, because distributions of these data may have non-parametric and multi-modal distributions. If we apply the currently available methodologies to these data, we will encounter problems such as low accuracy, long delay times, and so on. To overcome these limitations, we developed the FPRIS (fast pattern recognition inspection system). FPRIS guarantees high diagnosis accuracy with fast running time, and the usefulness of FPRIS is demonstrated through the learning of sampled data.