The two-for-one(TFO) twister is precision machinery that twists fibers rapidly under constant tension. Since the quality of the twisted yarn is directly deteriorated by faults of the twister, such as the distortion of the spinning axis, bearing abrasion, and tension irregularity, it is important to detect faults of the TFO twister at an early stage. In this research, a new algorithm is proposed to detect faults of the TFO twister and their causes, by measuring the vibrations of the TFO twister and obtaining frequency components with a FFT algorithm. The TFO twister with faults showed increased vibrations and each fault generated vibrations at different frequencies. By analyzing changes of characteristics of vibrations, we can determine faulty twisters. The proposed fault detection algorithm can be implemented cheaply with a signal processor chip. It can be used to find when to repair a faulty TFO twister without much loss of yam on-line.